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Recently, a controversial paper reviewing both the health and environmental benefits of animal foods was published to the journal, Animal [[1](https://pubmed.ncbi.nlm.nih.gov/35158307/)]. This was brought to my attention by one of my patrons, who specifically requested that I respond to the first section of the article, titled "why the nutritional case against animal source foods may be overstated". My response was originally supposed to be a reaction video for my patrons. But, the more of the paper that I read, the more I realized that this would require a much more systematic appraisal.
Although I have only reviewed one section of the paper, I am told that the rest of the paper is also filled with questionable claims, falsehoods, half-truths, and dubious reasoning. As such, I will leave it to people with more domain knowledge to comment on the latter sections of the paper. As for the section that I was tasked with critiquing, I'm completely comfortable with systematically evaluating the claims contained within it. So, let's get into it.
> "Even though advocacy for moderate to heavy restriction [of animal foods] is echoed by various public heath institutions worldwide, suggesting apparent consensus, the scientific debate is not settled as the evidence has been challenged by various scientists, both for red meat (Truswell, 2009; Hite et al., 20100; Alexander et al., 2015; Klurfeld, 2015; Kruger & Zhou, 2018; Händel et al., 2020; Hill et al., 2020; Johnston et al., 2019; Leroy and Cofnas, 2020; Sholl et al., 2021)"
**Weasel words:**
Citing a couple of authors to represent the "public heath institutions" that advocate for animal food restriction, whilst also citing ten authors who challenge this notion, is a painfully misleading move. The evidence for reducing most animal foods is actually extensive, with only a small handful of exceptions. Not only that, but it's also questionable whether or not any public health institutions actually advocate for the moderate or heavy restriction of these exceptions. It's unclear, because the terms "moderate" and "heavy" are not clearly defined.
**Motte and Bailey:**
The paragraph began by referencing the presumed attitudes of "public health institutions" toward animal foods more broadly. A truly extraordinary claim that is not supposed by any of the their reference material. They then follow it up by citing authors who have pushed back specifically on these institutions' attitudes toward red meat and saturated fat. Most public health institutions that are concerned with nutrition do indeed advocate for the restriction of these foods.
> "...and saturated fat, which is not exclusive to animal source foods (Astrup et al., 2020; Krauss & Kris Etherton, 2020)."
**Red herring:**
While there are some plant foods that are high in saturated fat, we need not consume them. Those sources of saturated fat can be avoided on an animal food restricted diet. This is less true of the animal foods that these authors are specifically attempting to defend. Not only that, but no public health institutions are advocating for the consumption of plant foods like coconut or palm oil. So, I'm not even sure what this point is meant to address.
> "Among other concerns, one of the objections is that pleas for restriction are based on conflicting findings and observational relationships that are not necessarily causal, suffering from confounding and bias (Grosso et al., 2017; Händel et al., 2020; Hill et al., 2020; Leroy & Barnard, 2020; Nordhagen et al., 2020)."
**Potential contradiction:**
Confounding is a causal concept. All posited confounders need to be validated as genuine confounders using evidence that meets these authors' bar for causal inference. Otherwise we don't have a reason to consider them confounders at all. The truth is that virtually all accepted confounders in this domain are validated via epidemiological data itself. I can formalize the argument like this:
**P1)** If evidence that is stronger than the best animal food epidemiology is required to demonstrate causality and confounding is a causal concept, then evidence that is stronger than the best animal food epidemiology is required to validate potential confounders.
**(E∧C→P)**
**P2)** Evidence that is stronger than the best animal food epidemiology is required to demonstrate causality.
**(E)**
**P3)** Confounding is a causal concept.
**(C)**
**C)** Therefore, evidence that is stronger than the best animal food epidemiology is required to validate potential confounders.
**(∴P)**
In the above syllogism, the authors could very easily be affirming E and ¬E. If the authors are rejecting epidemiological evidence while simultaneously positing confounders that will be validated with epidemiological evidence, their position would entail a contradiction.
> "Unwarranted use of causal language is nonetheless widespread in the interpretation of nutritional epidemiological data, thereby posing a systemic problem and undermining the field’s credibility (Cofield et al., 2010; Ioannidis, 2018)."
**Red herring:**
Firstly, there is no reference for the claim that causal language is widespread in the interpretation of nutritional epidemiological data. Secondly, even if it were true, nutritional epidemiology has excellent validation for both its results as well as the underpinning methodology, considering its limitations and shortcomings.
If the goalpost for causal inference is human experiments, then the use of causal language is likely to be warranted more often than it is unwarranted. This is due to the high degree of concordance between the results of nutritional epidemiology and randomized controlled trials [[2](https://pubmed.ncbi.nlm.nih.gov/34526355/)][[3](https://pubmed.ncbi.nlm.nih.gov/23700648/)][[4](https://pubmed.ncbi.nlm.nih.gov/34308960/)]. Regardless, it's not clear how the widespread use of causal language poses either a systemic problem or undermines the field's credibility. Again, it just isn't clear what the point of these claims is supposed to be.
> "Moreover, the associations between red meat and metabolic disease have not only been evaluated as weak..."
**Red herring:**
It is not true that these associations are weak. When meta-analytically summated the associations are often close to linear. Not only for total mortality but also for many major chronic diseases [[5](https://pubmed.ncbi.nlm.nih.gov/28446499/)][[6](https://pubmed.ncbi.nlm.nih.gov/29039970/)][[7](https://pubmed.ncbi.nlm.nih.gov/28397016/)]. The associations generally only appear weak when there are certain sources of bias present, such as inadequate exposure contrasts, follow-up times, participant numbers, or even overadjustment for mediators.
> "...translating into small absolute risks based on low to very low certainty evidence (Johnston et al., 2019)..."
**Red herring:**
Absolute risk and certainty are concepts that don't strongly interact. You can have low absolute risks and a high degree of certainty, such as with successful human trials with event-based stopping conditions. You can also have high absolute risks and low certainty, such as with underpowered human studies with high event rates.
It's also not clear why the authors would choose to favour absolute risk over relative risk, considering that the maximum possible absolute risk differences are going to be dictated by event rates in the comparator population. This concept can be easily illustrated referring to populations that have longer follow-up times, such as with the literature on LDL and cardiovascular disease risk [[8](https://pubmed.ncbi.nlm.nih.gov/30571575/)].
The distance between the two green lines represents the absolute risk difference between low and high LDL over 10 years. Whereas the distance between the two red lines represents the absolute risk difference between low and high LDL over 30 years. Here we can see that if insufficient follow-up is observed, absolute risk differences will inevitably be smaller. This is because event rates naturally increase with time.
The meta-analysis by Vernooij et al. (2019) that the authors cited to support the claim of "small" absolute risk differences with red meat had a median follow-up time of 10.5 years for cardiovascular disease [[9](https://pubmed.ncbi.nlm.nih.gov/31569217/)]. Despite this limitation, Vernooij et al. did not appear to have made any substantive attempt to explore the heterogeneity between their included studies with subgroup analyses or meta-regression analyses. Had they done so, they could have subgrouped by follow-up time and inevitably found that the absolute risks were higher in cohorts with longer follow-ups.
But we can take it a step further. We can reveal the inconsistency in their reasoning by formalizing their argument against nutritional epidemiology, and showing that their criticisms apply to, say, human experiments as well.
**Definitions:**
V := human studies are vulnerable to bias and small effect sizes
D := human studies can demonstrate causality or support causal inference
G := are garbage
e := human experiments
**P1)** If human studies are vulnerable to bias and small effect sizes, then human studies cannot demonstrate causality or support causal inference.
**(∀x(Vx→¬Dx))**
**P2)** Human studies are vulnerable to bias and small effect sizes.
**(∀x(Vx))**
**P3)** If human experiments are human studies that cannot demonstrate causality or support causal inference, then human experiments are human studies that are garbage.
**(¬De→Ge)**
**C)** Therefore, human experiments are human studies that are garbage.
**(∴Ge)**
Using the authors' own logic, we can show that they would have to dismiss human experimental evidence on the same basis. This is because human experimental evidence is vulnerable to the same types of limitations that the authors are positing as presumably invalidating for nutritional epidemiology.
> "Associations are particularly noticeable in North America, where meat is often consumed through a fast-food window and where high-meat consumers tend to also eat less healthy diets and follow less healthy lifestyles in general. In a Canadian study, eating more meat was only associated with more all-cause cancer incidence for the subpopulation eating the lowest amounts of fruits and vegetables (Maximova et al., 2020)."
**Potential contradiction:**
Again, the authors appear to be dismissing nutritional epidemiological evidence on the basis of confounding, without justifying their asymmetrical attitudes toward the supporting evidence for the confounders they're positing. What is true of the evidence between fruits and vegetables and cancer and the evidence between meat and cancer, such that we can infer causality for one and not the other?
**Equivocation:**
This is the second time the authors have shifted the goalpost regarding what types of animals foods that are in question. First they were discussing animal foods simpliciter, only to shift the goalpost to red meat. Now they were talking about red meat, and have shifted goalposts to meat as a broad category. Whether this is intentional or just the result of sloppy writing, it is not a good look for the authors.
> "Several large-scale population-based studies, performed in individuals with ‘healthy lifestyles’, such as the Oxford-EPIC Study (Key et al., 2003) and the 45-and-Up Study (Mihrshahi et al., 2017), also find that the negative effects of red meat consumption on all-cause mortality become benign."
**Red Herring:**
From the wider literature, the typical threshold for harm with meat is at approximately 100g/day on average [[5](https://pubmed.ncbi.nlm.nih.gov/28446499/)].
The Oxford-EPIC cohort lacks power in those ranges [[10](https://pubmed.ncbi.nlm.nih.gov/23497300/)]. Data on the exposure contrasts in the 45-and-Up Study are even more unpersuasive [[11](https://pubmed.ncbi.nlm.nih.gov/28040519/)]. We have far more robust data than this, with better internal validity, follow-up times, and measurements.
In this Japanese cohort with a follow-up of 14 years, diet and lifestyle covariates were largely balanced across the quantiles of red meat intake [[12](https://pubmed.ncbi.nlm.nih.gov/33320898/)]. In fact, many covariates we'd suspect to be detrimental actually favoured meat consumption. Despite this, total meat was still associated with a statistically significant 21% increase in all-cause mortality among men between the ages of 65 and 79 years old, and a borderline-significant 41% increase in all-cause mortality risk among women between the ages of 45 and 54 years old.
These results could indicate that meat consumption is more likely to lead to premature death due to an unmeasured cause earlier in life than with men. Perhaps the seemingly premature increase in mortality could plausibly be attributed to an unmeasured female-specific endpoint, such as breast cancer [[13](https://pubmed.ncbi.nlm.nih.gov/31389007/)].
Again, just to hammer the point home, we can actually defeat the authors' position with a simple modus tollens.
**P1)** If meat consumption is likely to decrease mortality risk, then those consuming the most meat do not die more than those consuming the least meat.
**(P→¬L)**
**P2)** Those consuming the most meat do die more than those consuming the least meat.
**(L)**
**C)** Therefore, meat consumption is not likely to decrease mortality risk.
**(∴¬P)**
Given the weight and strength of the evidence in favour of meat restriction for longevity, it would be quite hilarious to see the authors attempt to reject P2. The evidence they referenced from the Oxford-EPIC cohrot and the 45-and-Up Study could be used in an attempt to reject P2. However, that evidence is very easily superseded by higher internal validity evidence with greater power, not to mention in populations that don't suffer from the same supposed confounding.
> "If red meat were indeed causally driving the associations, one would anticipate finding stronger effects in systematic reviews looking specifically at red meat intake (able to evaluate a large intake gradient) compared to dietary pattern studies (smaller intake gradient) (Johnston et al., 2018)."
**Potential contradiction:**
The association between all-cause mortality and red meat consumption is stronger than the inverse association between all-cause mortality and fruit and vegetable consumption in the most well-done systematic reviews [[5](https://pubmed.ncbi.nlm.nih.gov/28446499/)]. Again, what is true of the association between fruits and vegetables and all-cause mortality and red meat and all-cause mortality, such that we can infer causality for one and not the other?
> "On the contrary, the absolute risk reductions from both reviews specific to intake versus dietary pattern (Johnston et al., 2019) were very similar in their magnitude of effect, indicating the possibility that, even after adjustment, a multitude of other diet or lifestyle components may be confounding the associations irrespective of whether they are negative or positive (Zeraatkar & Johnston, 2019)."
**Red herring:**
This literally just doesn't make any sense. Similar effect sizes are not indicators of multicollinearity or interaction between exposures. I have no idea how the authors come to this conclusion. If I punch people in the face on Mondays and kick people in the balls on Wednesdays, the risk of injury is equal between both Mondays and Wednesdays, but Mondays and Wednesdays aren't the same thing. Just as dietary patterns and individual foods aren't the same thing.
Just because the contribution of meat and diet/lifestyle factors have similar magnitudes of effect doesn't mean a mutual adjustment would do anything to either effect. Both exposures could be interacting with the outcome without interacting with each other. This is easily one of the most bizarre claims in the entire paper. They're also comparing effect sizes between analyses investigating different populations. It's just unfounded speculation.
> "While such troubling incongruity can be partially ascribed to differences in methodological set-up between studies, it has been hypothesised that the associations found in the West could at least partially be seen as cultural constructs generated by responses to norms of eating right (Hite, 2018)."
**Red herring:**
Again, these associations are seen in populations that are not consuming Westernized diets [[12](https://pubmed.ncbi.nlm.nih.gov/33320898/)]. I'm not entirely sure why the authors seem to believe that these associations are limited to Western populations eating Western diets with Western attitudes toward health.
> "An important question to consider, therefore, is "whether intake of animal and plant proteins is a marker of overall dietary patterns or of social class" (Naghshi et al., 2020). Upper-middle classes, who are particularly sensitive to the ideologies of eating virtuous, tend to eat less red meat and saturated fat because of what they symbolise, and because of what they are being told by authorities and moralising societal discourse (Leroy & Hite, 2020). However, those same people are also more educated, wealthier, and healthier in general (Leroy & Cofnas, 2020)."
**Equivocation:**
Yet again, the authors have shifted their goalpost. They went from animal foods to red meat, from red meat to meat, and now from meat to animal protein. Again, it's unclear if this is intentional or just really atrocious writing on the part of the authors. But, I will attempt to keep my rebuttals relevant to the authors' most recently stated goalpost.
**Bullshit:**
These associations are seen even when socioeconomic status are largely balanced across the quantiles of animal protein intake [[14](https://pubmed.ncbi.nlm.nih.gov/33624505/)]. In fact, in this analysis of the Women's Health Initiative Observational Study by Sun et al. (2021), those who consumed the most plant protein were typically in the lower socioeconomic strata. This is in direct opposition to their speculation about socioeconomic status confounding. Additionally, replacing animal protein with plant protein associates with a reduced risk of all-cause mortality even in populations that are situated in a higher socioeconomic stratum [[15](https://pubmed.ncbi.nlm.nih.gov/27479196/)].
> "Even if multivariable models are used to account for such confounding effects as smoking, alcohol consumption, or obesity, it may not be possible to disentangle the effects of all dietary and lifestyle factors involved, especially given the low certainty of evidence."
**Potential contradiction:**
Yet again, we find ourselves needing to ask the authors what is true of the evidence between smoking/alcohol/obesity and health outcomes and animal foods/red meat/meat/animal protein and health outcomes such that we can infer causality for one and not the other? Thus far, the authors have not divulged any clear answers to this question in their paper.
> "Therefore, WHO (2015) mentions that eating unprocessed red meat "has not yet been established as a cause of cancer” (emphasis added)..."
**Appeal to authority:**
Causal inference is an epistemic question, informed and largely adjudicated by statistics. It's rather interesting that the authors tend to offer next to no critical appraisal of methodology or interpretation when the results concord with their (obvious) biases. So far any evidence against animal food consumption as been scrutinized extensively, albeit fallaciously, but the same attempt at rigour is not extended to the counterevidence.
> "...while IARC (2015) stated that "chance, bias, and confounding could not be ruled out” with respect to the association between red meat intake and colorectal cancer. According to some (e.g., Hite, 2018), nutritional epidemiology of chronic disease is thus at risk of capturing cultural artefacts and health beliefs within observational relationships, rather than reliably quantifying actual health effects. Such observations are then used to reinforce dietary advice, potentially creating a positive feedback loop (Leroy & Hite, 2020)."
**Red herring:**
This is true of any association, as per the Duhem-Quine thesis [[16](https://en.wikipedia.org/wiki/Duhem%E2%80%93Quine_thesis)]. Causal inference is a separate consideration, and the fact that auxiliary hypotheses can be proposed is tangential. The authors imply that the ability to appeal to these auxiliary hypotheses presents a barrier to reliably quantifying actual health effects. What type of evidence do they propose needs to be used, then? Because no scientific evidence is free from this limitation.
> "This problem is further underlined by the lack of support from intervention trials (O’Connor et al., 2017; Turner & Lloyd, 2017; Leroy & Cofnas, 2020), which are designed to account for known and unknown confounders, and the fact that the mechanistic rationale for red meats remains speculative at best (Delgado et al., 2020; Leroy & Barnard, 2020)."
**Equivocation:**
The authors' references don't support the claim. Until this point they were discussing the impact of meat products on disease outcomes, not disease risk markers or biochemical mechanisms. However, one of the only studies that did attempt to replace animal foods in the diet also showed one of the largest effect sizes in reducing the risk of acute myocardial infarction [[17](https://pubmed.ncbi.nlm.nih.gov/7911176/)]. On top of that, the most well-controlled human mechanistic studies also support the inference that meat increases CVD risk factors [[18](https://pubmed.ncbi.nlm.nih.gov/31161217/)].
> "Taken together, various public health organisations make a case for the reduction of animal source foods based on their interpretation of the prevailing scientific evidence. Others, however, argue that conclusive proof for (some of) these recommendations is missing, particularly given the contribution of animal source foods to closing essential micronutrient gaps (Leroy & Barnard, 2020)."
**Potential contradiction:**
The authors need to define "conclusive proof", and demonstrate how it has been shown for all variables that they are positing as confounding. However, it's beginning to sound as though they're getting close to planting their goalpost at human experimental evidence. However, this would be a mistake, as they've already posited a number of confounders for which we have no human experimental evidence for causal interaction with the outcomes that have been discussed.
> "Arguing for strong reductions contradicts common-sense approaches, especially from an anthropological perspective (Gupta, 2016; Leroy et al., 2020a). Meat, marrow, and seafood are evolutionary components of the human diet, even if they may have displayed some nutritional and biochemical differences compared to what is produced today in intensified operations, e.g., with respect to fat composition (Kuipers et al., 2010; Manzano-Baena & Salguero-Herrera 2018) and the presence of phytochemicals (van Vliet et al., 2021a, and 2021b). The health impact of these differences may be significant but remains difficult to quantify, though polyunsaturated fatty acids/saturated fatty acids and omega 3/6 ratios of wild ruminants living in current times are similar to pasture-raised (grass-fed) beef, but dissimilar to grain-fed beef (Cordain et al., 2002b). Be that as it may, the abundant consumption of animal source foods over 2.5 million years has resulted in an adapted human anatomy, metabolism, and cognitive capacity that is divergent from other apes (Milton, 2003; Mann, 2018). Also, many hunter-gatherer populations consume far larger amounts of meat and other animal source foods (sometimes > 300 kg/p/y), than what is now consumed in the West (around 100 kg/p/y). This is likely still much below what was once valid for early humans preying on megafauna (Ben-Dor & Barkai, 2020). On a caloric basis, the animal:plant ratio of Western diets (about 1:2 in the US; Rehkamp, 2016) is the inverse of most pre-agricultural diets (mean of 2:1; Cordain et al., 2000). Such high amounts of animal source foods are not necessarily indicative of a health advantage, but it can be assumed that animal source foods are at least compatible with good health."
**Equivocation:**
Apparently we've gone from talking about animal foods to talking about red meat, from talking about red meat to talking about meat, from talking about meat to talking about animal protein, and now from talking about animal protein to to talking about meat, marrow, and seafood. This is truly astonishing. Especially considering that now they're including seafood, which no major public health institution recommends that we eschew.
**Appeal to nature:**
Just because meat is an integral part of our evolutionary history does not actually mean that it is necessarily beneficial for the long-term health of modern humans. In fact, there are valid reasons to suspect that foods to which we are most strongly adapted may actually be more detrimental for long-term health, via antagonistic pleiotropy. I discuss this in a previous blog article [[19](https://www.the-nutrivore.com/post/should-we-eat-like-hunter-gatherers)].
Appeal to nature fallacies basically affirm that because something is natural (or in this case, "evolutionary"), it then follows that it is good. However, taking this position leads to hilarious consequences. Let me demonstrate by formalizing the authors' position once more.
**P1)** If the behaviour is evolutionary, then the behaviour is good.
**(∀x(Ex→Ox))**
**P2)** Meat consumption is a behaviour that is evolutionary.
**(Ea)**
**C)** Therefore, meat consumption is a behaviour that is good.
**(∴Oa)**
It should be obvious straight away why this is problematic. There are plenty of things that are natural or "evolutionary" that we also consider to be undesirable, and we can illustrate that with a reductio ad absurdum.
**P1)** If the behaviour is evolutionary, then the behaviour is good.
**(∀x(Ex→Ox))**
**P2)** Murder is a behaviour that is evolutionary.
**(Em)**
**C)** Therefore, murder is a behaviour that is good.
**(∴Om)**
If animal foods are good by virtue of them being natural or "evolutionary", the authors will have to explain to me why something like murder is not good. As they share the same property of being evolutionary.
> "So-called "diseases of modernity" were rare in ancestral communities, in contrast to what is now seen in regions where Western diets rich in energy-dense foods and (sedentary) lifestyles prevail. In the US, 71% of packaged foods are ultraprocessed (Baldridge et al., 2019)..."
**Red herring:**
There are a number of epistemic barriers that challenge inferences about the long-term health value of more primitive living conditions for modern humans, such as survivorship bias [[20](https://pubmed.ncbi.nlm.nih.gov/25489027/)]. Primitive cultures tend to have very high rates of infant and child mortality, which modern medicine can rescue. When those children are _not_ saved, the population will appear more robust by weeding out less resilient people. When those children _are_ saved, you increase the number of less resilient people within the population.
> "Even if this has been described as a "paradox” (Cordain et al., 2002a), it mainly indicates that today’s assumptions about healthy diets, as being de facto low in red meat and saturated fat, are flawed and represent a romanticised Western viewpoint."
**Strawman:**
No public health institutions are suggesting that healthy diets are _defined_ by the absence of red meat and saturated fat. Rather, diets lower in red meat and saturated fat tend to be healthier than diets that are higher in red meat and saturated fat. But, this doesn't mean that other factors don't also matter. These dietary patterns have many other characteristics that contribute to healthfulness that have nothing to do with red meat or saturated fat.
> "To sum up, although animal source foods are primary components of the Western diet, they are also evolutionary foods to which the human body is anatomically and metabolically adapted, up to the level of the microbiome (Sholl et al., 2021), and has always obtained key nutrients from."
**Appeal to nature:**
The status of red meat as an evolutionary food is tangential to the question of whether or not red meat increases long-term disease risk in modern populations. Investigations into the health status of primitive cultures is insufficient to inform this question.
> "Although further research may be needed, their role in chronic diseases could as well be a mere artefact based on association with the actual damage from other dietary and lifestyle factors. It is uncertain yet possible that high intake of red meat could become problematic in a contemporary Western context."
**Red herring:**
Again, this is true of any association. Causal inference is a separate consideration, and the fact that auxiliary hypotheses can be proposed is, again, tangential.
**Potential contradiction:**
For the last time, posited confounders require validation that meets the authors' bar for causal inference. Thus far, no such bar has been provided and no validation was offered for any of the confounders that were posited. That which is stated without evidence can be dismissed without evidence. Anyone can baselessly speculate.
> "Moreover, contemporary cultures that have maintained traditional diets and lifestyles typically have low burdens of chronic disease (e.g., Kaplan et al., 2017)."
**Red herring:**
The authors reference a cross-sectional analysis of the Tsimane population conducted by Kaplan et al. (2017) [[21](https://pubmed.ncbi.nlm.nih.gov/28320601/)]. It's questionable whether or not their results qualify as low burdens of chronic disease for that population in the first place.
This is made even more questionable after accounting for ~15-year age overestimations that were likely to have biased their results [[22](https://immunityageing.biomedcentral.com/articles/10.1186/s12979-019-0165-8)][[23](https://pubmed.ncbi.nlm.nih.gov/27511193/)][[24](https://pubmed.ncbi.nlm.nih.gov/34038540/)]. After this adjustment, the cardiovascular disease burden within the Tsimane is likely largely comparable with the results of the MESA cohort.
Here on the chart above we see Tsimane age estimates using DNA methylation on the Y axis, against Tsimane age estimates using the methods of Kaplan et al. on the X axis. Kaplan et al. (2017) estimated the ages of the Tsimane participants using written records, relative age lists, dated events, photo comparisons of people with known ages, and cross-validation of information from independent interviews of kin.
Apparently such methodology would appear to introduce a fair amount of bias, as the more objective measures of age tend not to agree with them. Furthermore, all of these more robust measures of age seem to point to overestimations on the party of Kaplan et al. that are all roughly in the same ballpark of 10-20 years.
**Equivocation:**
The category of "chronic disease" is a superset, including many individual diseases. The only disease endpoint investigated in the authors' reference was cardiovascular disease progression (measured by coronary artery calcification). So, I'm not sure why they feel justified in referring to chronic disease as a broad category with this single reference.
To wrap this up, I'd just like to say that I've never before seen a peer-reviewed publication that was so densely packed with logical fallacies and inconsistencies. Mind you this is only the first section, related to disease risk. I was only responsible for appraising this section, but from what I've been told about the remainder of the paper it could potentially be even more absurd. Which is scary to me.
Altogether the authors were guilty of eleven red herrings, six potential contradictions, five equivocations, and eight other assorted fallacies. From what I've read, no truly persuasive arguments were offered in favour of their view, and their attempts to criticize the prevailing paradigm were uniformly hollow and superficial.
Ultimately, the authors actually describe the absurdity of their approach better than I could in the introduction of their paper. Truly astonishing.
> _"Due to constraints in format, we restrict ourselves to generating a perspective that favours concepts over details and methodological data."_
Thanks for reading! If you enjoy my writing and want more content like this, consider pledging to my [Patreon](https://www.patreon.com/thenutrivore)!
**References:**
[1] Leroy, Frédéric, et al. ‘Animal Board Invited Review: Animal Source Foods in Healthy, Sustainable, and Ethical Diets - An Argument against Drastic Limitation of Livestock in the Food System’. _Animal: An International Journal of Animal Bioscience_, vol. 16, no. 3, Mar. 2022, p. 100457. _PubMed_, [https://doi.org/10.1016/j.animal.2022.100457](https://doi.org/10.1016/j.animal.2022.100457.)
[2] Schwingshackl, Lukas, et al. ‘Evaluating Agreement between Bodies of Evidence from Randomised Controlled Trials and Cohort Studies in Nutrition Research: Meta-Epidemiological Study’. _BMJ (Clinical Research Ed.)_, vol. 374, Sept. 2021, p. n1864. _PubMed_, [https://doi.org/10.1136/bmj.n1864](https://doi.org/10.1136/bmj.n1864)
[3] Moorthy, Denish, et al. _Concordance Between the Findings of Epidemiological Studies and Randomized Trials in Nutrition: An Empirical Evaluation and Citation Analysis: Nutritional Research Series, Vol. 6_. Agency for Healthcare Research and Quality (US), 2013. _PubMed_, [http://www.ncbi.nlm.nih.gov/books/NBK138246/](http://www.ncbi.nlm.nih.gov/books/NBK138246/)
[4] Beyerbach, Jessica, et al. ‘Evaluating Concordance of Bodies of Evidence from Randomized Controlled Trials, Dietary Intake, and Biomarkers of Intake in Cohort Studies: A Meta-Epidemiological Study’. _Advances in Nutrition (Bethesda, Md.)_, vol. 13, no. 1, Feb. 2022, pp. 48–65. _PubMed_, [https://doi.org/10.1093/advances/nmab095](https://doi.org/10.1093/advances/nmab095)
[5] Schwingshackl, Lukas, et al. ‘Food Groups and Risk of All-Cause Mortality: A Systematic Review and Meta-Analysis of Prospective Studies’. _The American Journal of Clinical Nutrition_, vol. 105, no. 6, June 2017, pp. 1462–73. _PubMed_, [https://doi.org/10.3945/ajcn.117.153148](https://doi.org/10.3945/ajcn.117.153148)
[6] Bechthold, Angela, et al. ‘Food Groups and Risk of Coronary Heart Disease, Stroke and Heart Failure: A Systematic Review and Dose-Response Meta-Analysis of Prospective Studies’. _Critical Reviews in Food Science and Nutrition_, vol. 59, no. 7, 2019, pp. 1071–90. _PubMed_, [https://doi.org/10.1080/10408398.2017.1392288](https://doi.org/10.1080/10408398.2017.1392288.)
[7] Schwingshackl, Lukas, et al. ‘Food Groups and Risk of Type 2 Diabetes Mellitus: A Systematic Review and Meta-Analysis of Prospective Studies’. _European Journal of Epidemiology_, vol. 32, no. 5, May 2017, pp. 363–75. _PubMed_, [https://doi.org/10.1007/s10654-017-0246-y](https://doi.org/10.1007/s10654-017-0246-y)
[8] Abdullah, Shuaib M., et al. ‘Long-Term Association of Low-Density Lipoprotein Cholesterol With Cardiovascular Mortality in Individuals at Low 10-Year Risk of Atherosclerotic Cardiovascular Disease’. _Circulation_, vol. 138, no. 21, Nov. 2018, pp. 2315–25. _PubMed_, [https://doi.org/10.1161/CIRCULATIONAHA.118.034273](https://doi.org/10.1161/CIRCULATIONAHA.118.034273)
[9] Vernooij, Robin W. M., et al. ‘Patterns of Red and Processed Meat Consumption and Risk for Cardiometabolic and Cancer Outcomes: A Systematic Review and Meta-Analysis of Cohort Studies’. _Annals of Internal Medicine_, vol. 171, no. 10, Nov. 2019, pp. 732–41. _PubMed_, [https://doi.org/10.7326/M19-1583](https://doi.org/10.7326/M19-1583)
[10] Rohrmann, Sabine, et al. ‘Meat Consumption and Mortality--Results from the European Prospective Investigation into Cancer and Nutrition’. _BMC Medicine_, vol. 11, Mar. 2013, p. 63. _PubMed_, [https://doi.org/10.1186/1741-7015-11-63](https://doi.org/10.1186/1741-7015-11-63)
[11] Mihrshahi, Seema, et al. ‘Vegetarian Diet and All-Cause Mortality: Evidence from a Large Population-Based Australian Cohort - the 45 and Up Study’. _Preventive Medicine_, vol. 97, Apr. 2017, pp. 1–7. _PubMed_, [https://doi.org/10.1016/j.ypmed.2016.12.044](https://doi.org/10.1016/j.ypmed.2016.12.044)
[12] Saito, Eiko, et al. ‘Association between Meat Intake and Mortality Due to All-Cause and Major Causes of Death in a Japanese Population’. _PloS One_, vol. 15, no. 12, 2020, p. e0244007. _PubMed_, [https://doi.org/10.1371/journal.pone.0244007](https://doi.org/10.1371/journal.pone.0244007)
[13] Lo, Jamie J., et al. ‘Association between Meat Consumption and Risk of Breast Cancer: Findings from the Sister Study’. _International Journal of Cancer_, vol. 146, no. 8, Apr. 2020, pp. 2156–65. _PubMed_, [https://doi.org/10.1002/ijc.32547](https://doi.org/10.1002/ijc.32547)
[14] Sun, Yangbo, et al. ‘Association of Major Dietary Protein Sources With All-Cause and Cause-Specific Mortality: Prospective Cohort Study’. _Journal of the American Heart Association_, vol. 10, no. 5, Feb. 2021, p. e015553. _PubMed_, [https://doi.org/10.1161/JAHA.119.015553](https://doi.org/10.1161/JAHA.119.015553)
[15] Song, Mingyang, et al. ‘Association of Animal and Plant Protein Intake With All-Cause and Cause-Specific Mortality’. _JAMA Internal Medicine_, vol. 176, no. 10, Oct. 2016, pp. 1453–63. _PubMed_, [https://doi.org/10.1001/jamainternmed.2016.4182](https://doi.org/10.1001/jamainternmed.2016.4182)
[16] ‘Duhem–Quine Thesis’. _Wikipedia_, 13 Jan. 2022. _Wikipedia_, [https://en.wikipedia.org/w/index.php?title=Duhem%E2%80%93Quine_thesis&oldid=1065410241](https://en.wikipedia.org/w/index.php?title=Duhem%E2%80%93Quine_thesis&oldid=1065410241)
[17] de Lorgeril, M., et al. ‘Mediterranean Alpha-Linolenic Acid-Rich Diet in Secondary Prevention of Coronary Heart Disease’. _Lancet (London, England)_, vol. 343, no. 8911, June 1994, pp. 1454–59. _PubMed_, [https://doi.org/10.1016/s0140-6736(94)92580-1](https://doi.org/10.1016/s0140-6736(94)92580-1)
[18] Bergeron, Nathalie, et al. ‘Effects of Red Meat, White Meat, and Nonmeat Protein Sources on Atherogenic Lipoprotein Measures in the Context of Low Compared with High Saturated Fat Intake: A Randomized Controlled Trial’. _The American Journal of Clinical Nutrition_, vol. 110, no. 1, July 2019, pp. 24–33. _PubMed_, [https://doi.org/10.1093/ajcn/nqz035](https://doi.org/10.1093/ajcn/nqz035)
[19] Hiebert, Nick. ‘Should Modern Humans Eat Like Hunter-Gatherers?’ _The Nutrivore_, 14 May 2021, [https://www.the-nutrivore.com/post/should-we-eat-like-hunter-gatherers.](https://www.the-nutrivore.com/post/should-we-eat-like-hunter-gatherers.)
[20] Perrin, James M., et al. ‘The Rise in Chronic Conditions among Infants, Children, and Youth Can Be Met with Continued Health System Innovations’. _Health Affairs (Project Hope)_, vol. 33, no. 12, Dec. 2014, pp. 2099–105. _PubMed_, [https://doi.org/10.1377/hlthaff.2014.0832](https://doi.org/10.1377/hlthaff.2014.0832)
[21] Kaplan, Hillard, et al. ‘Coronary Atherosclerosis in Indigenous South American Tsimane: A Cross-Sectional Cohort Study’. _Lancet (London, England)_, vol. 389, no. 10080, Apr. 2017, pp. 1730–39. _PubMed_, [https://doi.org/10.1016/S0140-6736(17)30752-3](https://doi.org/10.1016/S0140-6736(17)30752-3)
[22] Li, Mingde, et al. ‘Age Related Human T Cell Subset Evolution and Senescence’. _Immunity & Ageing_, vol. 16, no. 1, Sept. 2019, p. 24. _BioMed Central_, [https://doi.org/10.1186/s12979-019-0165-8](https://doi.org/10.1186/s12979-019-0165-8)
[23] Horvath, Steve, et al. ‘An Epigenetic Clock Analysis of Race/Ethnicity, Sex, and Coronary Heart Disease’. _Genome Biology_, vol. 17, no. 1, Aug. 2016, p. 171. _PubMed_, [https://doi.org/10.1186/s13059-016-1030-0](https://doi.org/10.1186/s13059-016-1030-0)
[24] Irimia, Andrei, et al. ‘The Indigenous South American Tsimane Exhibit Relatively Modest Decrease in Brain Volume With Age Despite High Systemic Inflammation’. _The Journals of Gerontology. Series A, Biological Sciences and Medical Sciences_, vol. 76, no. 12, Nov. 2021, pp. 2147–55. _PubMed_, [https://doi.org/10.1093/gerona/glab138](https://doi.org/10.1093/gerona/glab138)

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It's basically a sound induction at this point that anti-seed oil clowns won't debate me. My comprehensive, 15,000+ word, 200+ reference [article](https://www.the-nutrivore.com/post/a-comprehensive-rebuttal-to-seed-oil-sophistry) on seed oils is almost three years old, and since it was published, nobody from the opposition has offered even a shred of substantive criticism toward it. A few have tried, but ultimately their efforts were akin to taking halfhearted swats at low-hanging fruit and ultimately failing, rather than actually meaningfully engaging with my core findings and the arguments underpinning my interpretations. They really are just a pathetically weak lot of human beings.
At the risk of sounding self-aggrandizing, I think I have a pretty good idea why these people won't debate me—I have the tools to dismantle them. I'm well-versed on the relevant empirics, I'm intimately familiar with several formal systems of reasoning, I use semantic analysis to make sure my interlocutor's term meanings and usages are understood and remain consistent, I have decent knowledge of philosophy and, more specifically, scientific epistemology, and I deploy an algorithmic debate strategy. I am essentially kryptonite to anti-seed oil quacks. That's probably why they never show up to debate.
My most recent exposure to anti-seed oil cuckery was so profoundly egregious that it warranted writing about it here on my main blog. This extra special example of subhuman behavior comes from Cate Shanahan herself, or as I like to call her, Cate Shenanigans. If you want more info on Cate Shenanigans' history of debate-dodging, I have compiled an inventory [here](https://www.the-nutrivore.com/dodgers). For now, let me start from the beginning.
Nearly a year ago, I was [invited](https://x.com/zbitter/status/1668413822388916224) by Zach Bitter, via X, to debate the proposition "seed oils are not a significant, independent concern for public health" on his podcast with a willing interlocutor. Cate Shenanigans was [tagged](https://x.com/NTxLoneRider/status/1673811898645598211) in this post but did not reply. In fact, every single high-profile seed oil skeptic who responded to the thread declined my invite, while others, like Cate Shenanigans, were pinged and never replied. The nutrition debate arena was a ghost town that day. Not an ounce of courage was to be found among the anti-seed oil clowns.
However, nearly a year after that, Cate Shenanigans put out a general [invite](https://x.com/drcateshanahan/status/1773836787196346592) to debate. Even going so far as to [suggest](https://x.com/drcateshanahan/status/1774490576362062311) that I was scared to face her, to which I replied. Shortly after, she actually decided to engage and [replied](https://x.com/drcateshanahan/status/1774681584907559220) to me, encouraging me to DM her (presumably to work out the details of the debate). After some minor miscommunications, she instructed me in another [reply](https://x.com/drcateshanahan/status/1774830896006185446) to contact her via email. I did. I never received a reply. Some time passed, and Zach Bitter once again started [prodding](https://x.com/zbitter/status/1778171569967190413) at Cate Shenanigans about the status of her debate invitation to me (presumably with the intention of once again offering to host it). A day later, after a brief back and forth, Cate Shenanigans [replied](https://x.com/drcateshanahan/status/1778430104617603232) with what seemed like an alteration in the conditions to debate. At least this is how I interpreted it, as someone who has an interest in her arguments. I [pressed](https://x.com/TheNutrivore/status/1778456234078662984) her for clarification, and even quoted her in a [post](https://x.com/TheNutrivore/status/1778490825124552875) later that day about it, and received no reply. But not before she made her own [post](https://x.com/drcateshanahan/status/1778483241755787308) in a different thread, which I didn't initially see, wherein she withdrew from the debate that day. What a bizarre series of behaviours.
Fast forward to June 2nd, 2024, and I was DMed by another third party looking to coordinate yet another debate between Cate Shenanigans and myself. I won't reveal this person's identity and throw this individual under the bus, because they were nothing but cordial and respectful to me. After a short exchange, I was CC'd into an email chain with Cate Shenanigans, and this is where the fun begins. But rather than narrate the exchange, I'll just post it here:
**Host:**
> Hi cate
>
> Nick, CCed, would be down to do the seed oil debate for my show… Are you game? If so my team, CCed, can help to arrange…
**Nick:**
> If the debate proposition is clear and I disagree with it, then absolutely. I generally won't debate anything vague or normative, though. I'll happily debate a proposition like "seed oil consumption increases the risk of heart disease", for example.
**Shenanigans:**
> HI Host
>
> Someone else wanted to set up a debate on their podcast between myself and Nick. But what was proposed looked more like just an unstructured argument, and that is not something I’m interested in. I don’t know if the disconnect was with that host or with Nick….? So I’d like to make sure we’re all on the same page about what a debate is.
>
> A debate starts with an assertion and the two participants who are debating take opposing sides.
>
> So if Nick wants to debate, then the assertion could be “RBD vegetable oils are part of a healthy diet.”
>
> Sound good?
**Host:**
> What do you think Nick?
**Nick:**
> First of all, it's not just that someone else has previously wanted to set up a debate between Cate and myself. Cate herself put out what I (quite reasonably) interpreted as a general invitation to those challenging her positions, which can be found [here](https://x.com/drcateshanahan/status/1773836787196346592), on March 29th. I accepted the invite, to which Cate replied on March 31st with an invitation to me to DM her (presumably to set up a debate), which can be found [here](https://x.com/drcateshanahan/status/1774681584907559220). I responded via email on April 1st, after she invited me to do so [here](https://x.com/drcateshanahan/status/1774830896006185446), on the same day. There was no third party present at this time. This was Cate clearly inviting me, personally, to debate. Just to be clear about the facts.
>
> Furthermore, while we're being clear about the facts, Cate also presumably withdrew from the debate for what would be completely bizarre reasons that are ultimately orthogonal to the debate itself, which can be found [here](https://x.com/drcateshanahan/status/1778483241755787308). But, not before implying that she had altered the necessary conditions for a debate, which can be found [here](https://x.com/TheNutrivore/status/1778490825124552875). Whatever the case, declining to debate someone on an empirical position because they disagree with you on an unrelated normative position is **beyond** strange, and honestly it was so outlandish that I just flagged it as a blatant excuse not to debate. I hope, Host, you can also see that this is the most reasonable interpretation of her behaviour.
>
> Now that that's out of the way and clarified, I'd be happy to debate Cate on a number of propositions. So long as she's done making excuses. Specifically, I might want to debate against [this](https://x.com/drcateshanahan/status/1516786219841073153) proposition:
>
> "current levels of seed oil consumption are the main driver of the obesity and chronic disease epidemics that now represent an existential threat to human populations around the world.
>
> Out of all of her claims, this could easily be one of the most egregious, depending on how the semantics are unpacked. So, I'd need some of those semantics clarified. Cate, when you say seed oils are the main driver, do you mean that in a counterfactual scenario wherein all the seed oils in the food supply were replaced with low-PUFA alternatives like butter or tallow, those same diseases epidemics would be less likely to occur? If yes, I disagree with the proposition and will happily debate it. If not, what do you mean?
>
> As for the stuff about what the debate would be. I typically don't do "structured" debates in the traditional sense. They seem closer to theatrics than debates, with time limits and scheduled topic shifts, opening statements, closing statements, etc. I prefer a linear, continuous Socratic debate format where the truth value of a proposition can be scrutinized to completion with no get-out-of-jail free cards granted by the clock. If it takes many hours to reach a concession, so be it. Other formats typically just make sophistry and dodging easier to get away with, because one party can just filibuster until the clock runs out.
>
> Also, Cate, my debate style is far from unstructured. My debate algorithm can be found [here](https://drive.google.com/file/d/1QQaN6HRwzp3kY2DAcnHVBxeX6jBhrvkw/view). So everyone knows what to expect of me. No rational person would look at this and conclude that my approach to debate is unstructured. I just refuse to debate with my hands tied behind my back, or debate under conditions where the proposition can't be scrutinized to completion.
**Host:**
> Thanks Nick!
> Cate, you game to schedule?
**Shenanigans:**
> Dear Nick and Host,
>
> Nick, my tweet "sure I’ll take all comers,” was a casual proposition subject to agreeing on further details, which we have yet to do.
>
> Host, from Nick's email it looks like he wants to argue against a primary thesis of my book, without having read my book. That doesn’t seem like a debate to me. 
>
> In Dark Calories I lay out the groundwork to support my claims across multiple chapters, each with scores of scientific references to support the arguments I make in the book. I can’t skip that information and jump right into a debate on my conclusions. 
>
> Maybe an analogy will help, here. Let’s say, hypothetically, that after publishing his theory of relativity, Einstein announced in a public forum “Hey everyone I think E=MC squared. Read my paper for supporting arguments." And then, someone wanted to debate his paper without having read it. Einstein would have been in a position to have to spell out many details of his complex thesis, including technical information that would probably not be interesting to a lay audience. (Not when presented in debate format. A good documentarian or science writer would be able to make it interesting, however.) In order to “win” the debate, Einstein may even have had to defend the veracity of fundamental principles of physics. That would take the form of a lecture, or a series of lectures. That’s not a debate. It’s a college course.
>
> Therefore, I’ve proposed we debate this: “Vegetable oils are heart healthy.” After all, that is what the AHA claims. It’s also what docctors learn, and it is influencing public policy, what American farmers grow, and what every child and adult eats. It’s an important topic that merits debate. I would argue against and Nick would argue for.
>
> Nick, are you willing to do that?
**Host:**
> I love that proposition “Vegetable oils are heart healthy.”
>
> What do u think Nick?
**Nick:**
> Just ignoring the fact that, in a blatant display of unbridled narcissism, Cate has unabashedly compared herself to Einstein, and her work to Einstein's theory of relativity, I'd like to ask Cate a few questions:
>
> 1. If I read your book, Dark Calories, will you debate the proposition I suggested (provided you actually unpack your semantics in a way that leads me to disagree with it)? If yes, surely you'd be willing to provide me with a free PDF of Dark Calories for me to scrutinize, no?
>
> 2. If you wish to debate what I believe on the subject, surely you've done me the likewise courtesy of reading my [article](https://www.the-nutrivore.com/post/a-comprehensive-rebuttal-to-seed-oil-sophistry) on the subject, right? If yes, why did you not suggest a proposition directly from my work?
>
> I also have some further objections to Cate's reasoning. Unlike Einstein's theories and models, the predictions of which could only be confirmed many decades later (if not a century later in some cases), Cate's thesis has been tested (and ultimately falsified with respect to human outcome data), which is why the debate would likely lead heavily into empirics and not require a whole book's worth of lectures on fundamentals. So no, I don't need to read her book to show that the proposition is false. Her reasoning here is ridiculous.
>
> Respectfully, Host and Cate, "vegetable oils are heart healthy" is an awful proposition, for a number of reasons:
>
> 1. It's not my proposition.
> 2. I don't represent the AHA.
> 3. I don't even care what the AHA says about seed oils.
> 4. I don't even know what it means because it's so semantically vague.
> 5. I can think and reason for myself and can defend my own propositions, thank you.
>
> How about we narrow the scope of the proposition I suggested down to a single disease? Since Cate quantifies the detrimental effects of seed oils over the entire scope of chronic diseases that qualify as epidemics, it is entailed logically that we could choose any disease within that scope. So, how about we meet half way on the subject and debate this proposition:
>
> "current levels of seed oil consumption are the main driver of heart disease."
>
> To the degree that Cate affirms that heart disease is an epidemic, she should affirm that the proposition is true. I affirm that the proposition is false. So, we simply exchange the relevant empirics and have the debate. EZPZ.
**Shenanigans:**
> Dear Host and Nick,
>
> I am interested in a debate on the topic I proposed. But I feel this particular email chain is no longer constructive. 
>
> Resorting to character attacks during what should be a civil conversation is outside the realm of what I consider acceptable discourse.
>
> Respectfully,
> Cate
**Nick:**
> You've attacked my character on multiple occasions, Cate. I don't care about that. Let's just discuss the arguments, and hammer out a path toward a productive debate.
>
> It's also ridiculous to imply that I'm not contributing productively to the conversation. I literally suggested a proposition that seems to satisfy us both. If I've failed to do that, please explain how so I can improve upon further suggestions.
>
> Just give me a yay or nay, Cate. I don't want to waste my time if you're not interested in actually defending your views or answering any clarifying questions.
**Shenanigans:**
> Nick,
>
> As I said two emails ago, because most people, including you, are not familiar with the scientific underpinnings of my work I would first need to explain them, and that is not a debate.
>
> What I proposed is a debate. If you are not interested in that debate then I believe we have reached the conclusion of this discussion.
>
> Best wishes to you.
**Nick:**
> And I explained to you how that's a dodge. Again, I don't need a lecture on the theoretical underpinnings when the predictions of the hypothesis have been tested and there is tons of empirical data on it. We only need to have a discussion about the empirics that test the hypothesis' fruitfulness, not the theoretical underpinnings. Insisting that I read your book is just filibustering.
>
> But hey, I'm still super curious to hear the answer to this question that I already asked you. If I were to read your book, would you debate the prop? Yes or no. If yes, then would you be willing to supply me with a free PDF of your book as a good faith gesture that you're interested in having your work scrutinized? Yes or no.
>
> I'm likewise super curious to hear the answer to this further question that I also already asked you. If you instead want to debate my beliefs, have you paid me the likewise courtesy of reading my work? Yes or no. If yes, then why haven't you picked a prop that has been extracted from my work directly? Why in the world do you want me to defend the AHA's prop and not a prop of my own?
**Shenanigans:**
> Nick I am responding to your questions and only your questions and I hope that can be the end of it.
>
> "And I explained to you how that's a dodge. Again, I don't need a lecture on the theoretical underpinnings when the predictions of the hypothesis have been tested and there is tons of empirical data on it. We only need to have a discussion about the empirics that test the hypothesis' fruitfulness, not the theoretical underpinnings. Insisting that I read your book is just filibustering.
>
> But hey, I'm still super curious to hear the answer to this question that I already asked you. If I were to read your book, would you debate the prop? Yes or no."
>
> No. For reasons I explained. Just because you’ve read the book does not mean the audience has and I will still be in the position to essentially give a lecture on the topics in my books. Its simply not suitable for normal debate format. Furthermore, I’m not interested in debating someone who thinks familiarizing himself with the basic underpinnings of the topic being debated is optional.
>
> "If yes, then would you be willing to supply me with a free PDF of your book as a good faith gesture that you're interested in having your work scrutinized? Yes or no.
>
> N/A
>
> "I'm likewise super curious to hear the answer to this further question that I also already asked you. If you instead want to debate my beliefs, have you paid me the likewise courtesy of reading my work?
>
> I am familiar with your thoughts. You cite the same type of evidence that the AHA uses to support its heart healthy claim.
>
> "Yes or no. If yes, then why haven't you picked a prop that has been extracted from my work directly?
>
> Not all propositions are equally interesting. I want to debate something interesting.
>
> "Why in the world do you want me to defend the AHA's prop and not a prop of my own?
>
> See above. Additionally, keep in mind that I did not bring you into this conversation.
**Nick:**
> So basically you're just dodging. Got it.
>
> Before we killscreen the entire enterprise, I would like one more answer to a question, because it might provide for a way forward. With respect to the AHA prop that you bizarrely want me to defend, what does it mean to say that seed oils are heart healthy? For example, does that mean that seed oils decrease the risk of heart disease?
>
> Because if that prop cashes out into a prop that I'd be willing to defend, then I don't see a reason why we couldn't debate it. If it means what I think it means, it'll just lead into the exact same empirical debate that you're currently dodging, so it makes no difference to me.
**Host's Producer:**
> Hi Nick and Cate,
>
> Host's Producer here; I'm the producer at [redacted]. Host and I agreed that we would like to conclude this discussion and explore other debate topics. The tone of the email discourse is not what we had in mind for our debut episode of this new podcast.
>
> We appreciate your consideration.
**Nick:**
> I'd be happy to debate cordially with somebody who is not a sophist. Cate, unfortunately, is one of the most dishonest actors in this entire space and deserves zero respect from anybody (though I would give her more than what she deserves and actually be respectful to her in a verbal discussion for the betterment of your podcast). There are people I could recommend who disagree with me who I don't think are dishonest but rather just confused about the empirics. If you guys are still interested in having a productive seed oil debate, I'd be happy to provide a list.
>
> Also if you're worried about my tone during the debate, you need not be concerned. I don't think anybody can actually find more than a single example of me being rude to my interlocutor across what is probably dozens of verbal debates by now. Other than that one exception, which I actually think was justified anyway, I am always polite and cordial with my interlocutor in verbal discussions.
This is where the email exchange ended. So much of what Cate Shenanigans said was just brain-dead lunacy. Let's go through the list.
**A) Suggesting that I defend a proposition that isn't my own**
Why? Why in the world would I be asked to defend a proposition that I, myself, am not even sure I affirm? I'm not even sure what the proposition "seed oils are heart healthy" even means. Does it mean that seed oils will increase your VO2 max? Does it mean seed oils will cure hypertension? Who the hell knows. It was just beyond strange that it was even suggested and demonstrates to me that Cate Shenanigans is operating with a level-zero debate meta.
Furthermore, if she was truly interested in contesting my views, why did she not pay me the likewise courtesy of reading my article and selecting a proposition directly from my own writing? Seems not only to be ridiculously stupid, but also a ridiculously stupid double-standard. Yet another example of Shenanigans-level cuckery.
**B) Shifting the goalpost three times**
Months ago, she dodged me on the grounds that I haven't read her book and that reading her book was necessary to have a debate. I [offered](https://x.com/TheNutrivore/status/1778490825124552875) to read her book then to satisfy the criteria and got no reply. Now, she dodged me for the second time on these grounds, and when I directly offered to read her book and satisfy her criteria, she shifted the goalpost a third time. Apparently, it's not good enough that I read her book, but now the entire audience needs to read her book in order for us to debate. This is just the most cuckish form of sophistry imaginable, and she should be ashamed.
**C) Her goalposts are dumb anyway**
To anyone with even a modicum of understanding with respect to scientific epistemology, it should be quite clear that Cate Shenanigans is dodging. Essentially, the strength of a scientific hypothesis does not rest upon its complexity, its elegance, its creativity, or any other such quality. It rests upon how scientifically virtuous it is, and this is determined by testing the hypothesis' compatibility with the theoretical virtues of science. I wrote a lengthy article on the subject [here](https://www.the-nutrivore.com/post/the-hitchhiker-s-guide-to-quack-smashing).
To determine if a hypothesis is strong, we should ask three fundamental questions, compared to other hypotheses:
1. Does this hypothesis make more novel predictions?
2. Does this hypothesis explain a wider breadth of phenomena?
3. Does this hypothesis make fewer overall assumptions?
There are other questions some philosophers think we should ask, but generally speaking, philosophers of science do not disagree about these three core questions. So, let's take them one by one.
Firstly, the hypothesis doesn't really seem to make very many novel predictions at all. In fact, as I had previously discussed in another blog [article](https://www.the-nutrivore.com/post/a-comprehensive-rebuttal-to-seed-oil-sophistry), the overall weight of the literature heavily favours the negation of Cate Shenanigans' hypothesis. When confronted with this fact on a [podcast](https://gimletmedia.com/shows/science-vs/mehwdgww) (33:00), Cate Shenanigans had no compelling answers and merely insisted that it "didn't make any sense" and that every single study on the subject (150-300 studies by her count) was "flawed". Very persuasive, Dr. Shenanigans. Gold fucking star.
As for the second question, the scope of her hypothesis is actually quite impressive. As she stated in the linked podcast above, seed oils literally have a causal role to play in every disease. That is quite an impressive scope. Think of all the phenomena this accounts for. Looks great for the hypothesis, except when we try to answer the third question.
With respect to the final question we're asking, every disease Cate Shenanigans blames on seed oils in an attempt to inflate her scope, she piles on more and more assumptions. Assumptions that empirically verifiable pathophysiological mechanisms that explain a number of diseases, that have nothing to do with seed oils, are either wrong or so incomplete that they might as well be wrong. This produces an insane amount of assumptions. And that's not even counting the assumptions that are stacked in virtue of the hypothesis' failures to make novel predictions.
As I explained in a previous article, The Hitchhiker's Guide to Quack-Smashing, quacks will often inflate scope at the expense of parsimony and/or fruitfulness. They want to be able to capture the widest scope of phenomena with their hypothesis without actually having evidence or having to explain a damn thing.
No, Dr. Shenanigans, I don't need to read your book in order to debate your proposition that seed oils are responsible for all disease, or chronic disease, or even just heart disease. As I explained in the email exchange, the only thing that is required is an investigation into the empirical data that tests your hypothesis. We can test the fruitfulness, we can test the scope, and we can test the parsimony. You're just dodging because you are scared.
Thanks for reading! If you enjoy my writing and want more content like this, consider pledging to my [Patreon](https://www.patreon.com/thenutrivore)!

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Firstly, I'd like to thank all of the people who volunteered days of their time in order to make this article possible!
Some time ago, the YouTube channel, [What I've Learned](https://www.youtube.com/@WhatIveLearned), release the video called "[Vegan diets don't work. Here's why](https://www.youtube.com/watch?v=MpxgZGnEF7E)", wherein the channel's host, [Joseph Everett](https://twitter.com/JEverettLearned), tells a cautionary tale regarding the health-related pitfalls of so-called "vegan" diets. In this article, Joseph will be exposed as the shameless fabulist that he is. Most of the references are taken out of context or cherry-picked, while others actually directly contradict the claims that they were cited to support.
In order to save on characters, I'm forced to truncate my introduction. So, I'll just take this time to say that you, Joseph, are a complete sophist, and you should be utterly ashamed for misleading the millions of people who consume your content. The effort that it took to write this article is more than you deserve, but its contents are more than deserved by your viewers. Your viewers deserve the truth— not cringey narratives about maverick dentists and cave paintings. With that, let's begin.
**Claim #1 (**[**00:00**](https://youtu.be/MpxgZGnEF7E?t=1)**):**
> It’s well understood that each of these vitamins have many functions in the body, but what does this have to do with nice teeth or looking attractive? Well, research later confirmed that along with things like protein and calcium, these vitamins indeed work together to transport minerals to support proper formation of the bones. [[1](https://pubmed.ncbi.nlm.nih.gov/29138634/)][[2](https://pubmed.ncbi.nlm.nih.gov/33801011/)] And of course your facial structure which includes the dental arch depends on proper development of your facial bones.
This is incredibly unscientific evidence on this hypothesis. The potential for selection bias with this particular body of evidence is enormously high, and on multiple levels. Of course we do not want to assume bad faith on the part of the researcher himself, but no credible scientific establishment would consider this evidence to be anything above laughable on the hypothesis specified. The specified hypothesis is that vitamin K2 (presumably in conjunction with other fat soluble vitamins) is responsible for teeth being straight rather than crooked.
It's not clear at all how the evidence presented even interacts with the hypothesis. These traditional peoples were not screened for vitamin K2 status or intake. There were no prospective analysis. No intake measurements. No biomarker measurements. Just storytelling. In fact, four years ago Joseph published a video that present a far more plausible hypothesis for the appearance of strong jaws and straight teeth in traditional populations eating traditional diets. In the video he cites [a researcher named Clark Spencer Larson from Ohio State University](https://youtu.be/zbzT00Cyq-g?t=591), who claims that stronger jaws and straighter teeth seen in ancestral populations are a consequence of the repetitive chewing of tough, fibrous plant material.
There is also evidence that [straighter teeth tend to be more worn down in traditional populations](https://www.youtube.com/watch?v=ybRD4UPN3D4&t=505s), which supports the chewing hypothesis. [[3](https://www.aegisdentalnetwork.com/cced/2009/06/interdisciplinary-analysis-origins-of-dental-crowding-and-malocclusions-an-anthropological-perspective)] In fact, Joseph references the pictures from Weston A Price's Nutrition and Physical Degeneration as evidence for the chewing hypothesis. [He remarks that the straight teeth in the traditional populations appear more worn down](https://www.patreon.com/file?h=24534404&i=3265485).
Has Joseph changed his view? It's unclear why, as this is a far more plausible hypothesis, and can actually subsume the vitamin K2 hypothesis. If vitamin K2 intake is a correlate for traditional diets, and traditional diets are more likely to be high in fibrous, tough plant foods, and straighter teeth tend to be more worn then crooked teeth, then the chewing hypothesis would appear to be more parsimonious.
Also, if insufficiency of K2 and the other fat soluble vitamins are to blame for crowded teeth due to their role in bone formation, why is there no mention of any of these people have any other issues associated with those sorts of nutritional insufficiencies? Like rickets, blindness, poor skin, or even haemophilia? It doesn't make sense.
**Claim #2 (**[**01:01**](https://youtu.be/MpxgZGnEF7E?t=61)**):**
> If eating zero animal foods improves health so much, why would a 2016 study find that 84% of vegans eventually quit their diet? [[4](https://faunalytics.org/a-summary-of-faunalytics-study-of-current-and-former-vegetarians-and-vegans/#:~:text=84%25%20of%20vegetarians%2Fvegans%20abandon,former%20vegetarians%2Fvegans%20was%20health)]
First of all, the claim of 84% of vegans quitting is just blatantly incorrect according to his own citation, which found a 70% dropout rate for vegans. Second of all, this is a ridiculous question. People stop doing health promoting things for all sorts of reasons, and it probably would have been a good idea for him to read the goddamn reference instead of resorting to conspiracy theories. The study includes an inventory of explanations for participant recidivism, and [the craving of animal products only occurred in the minority of recidivists](https://faunalytics.org/wp-content/uploads/2016/02/Faunalytics-Study-of-Current-and-Former-Vegetarians-and-Vegans-%E2%80%93-Secondary-Findings-.pdf).
Furthermore the study includes a table of motivations for pursuing veganism. Only a measly 1-3% of participants had motivations that were purely ethical in nature. While most motivations were health related. So, it seems like people are generally going on plant-based diets for health related reasons, and abandoning the diets without generally suffering health related costs. This isn't the only reason the question is stupid. Plenty of health promoting behaviours have high recidivism rates, such as exercise.
The Faunalytics study [from the previous year](https://faunalytics.org/wp-content/uploads/2015/06/Faunalytics_Current-Former-Vegetarians_Full-Report.pdf) actually explicitly stated that health did not present a noticeable difficulty for study participants, with the exception of vitamin B12 monitoring. Very few people actually reported any health issues at all, and it's not clear how many of them were actually supplementing B12.
The study had 54 current vegans and 129 former vegans. Of those 129 former vegans, 123 gave reasons. Of those 123, 104 reported no health issues. Of the remaining 19, 7 had no health issues, but rather just "felt" like they weren't getting enough nutrients or were concerned for no particular reason. One seemed to quit because they doubted the benefits. Only 11 reported actual health issues.
Of those 11, 6 were vague like "sick", "lightheaded", "not healthy", and "health issues", and doctors and/or dietitians were rarely, or never, involved to actually confirm that the diet was the issue. In conclusion, if we're being outrageously generous to his position, 6% of those who tried a vegan diet reported any health issues at all. But as we discussed above, it's unclear if this is just a result of poor supplementation practices.
It's not clear why we should accept the implication that a diet is healthy if and only if it can be generally adhered to. There are many examples of diets with poor adherence rates that I don't think Joseph would sign off on being unhealthy, and there are plenty of examples of diets with high adherence rates that Joseph wouldn't consider healthy at all.
**Definitions:**
**D** := (x) diet is great
**G** := people generally adhere to (x) diet
**s** := Standard American Diet
**k** := Ketogenic Diets
**P1)** A diet is great if and only if people generally adhere to it.
**(∀x(Dx↔Gx))**
**P2)** People generally adhere to SAD and not keto.
**(Gs∧¬Gk)**
**C)** Therefore, SAD is great and keto isn't.
**(∴Ds∧¬Dk)**
**Claim #3 (**[**04:59**](https://youtu.be/MpxgZGnEF7E?t=299)**):**
> So it’s interesting to observe that the Dutch are competing with Montenegrins for the tallest people in the world title (animation source: USA data) and they happen to be 2nd and 3rd on the list for the most milk consumed per capita in the world. A study of 105 countries in the journal Economics & Human Biology noted that animal food, particularly dairy, most correlated with increases in height. [[5](https://pubmed.ncbi.nlm.nih.gov/26948573/)]
This is actually the first claim where he actually starts citing peer reviewed research and not just the 1930s equivalent of a blog article with no citations.
Firstly, this is an ecological fallacy. Essentially, Joseph is looking at two temporally concurrent variables and implying a causal relationship. Specially, the research that Joseph cites does not look at individuals, their animal food/dairy consumption in childhood, nor their attained height in adulthood. These heights aren't compared to height projections or heights of peers consuming different diets.
Instead, this research is just looking at the average height of each entire country and the average intake of said foods. Such studies are susceptible to something called the [ecological fallacy](https://en.wikipedia.org/wiki/Ecological_fallacy), meaning what applies on a country average level may not apply on an individual level.
In this graph on average as X increases, so does Y. But if you look at each cluster separately, as X increases Y decreases. A real life example of this is the relationship between smoking and longevity.
If you plot each country's smoking rate and lifespan you'll see that [the more people smoke the longer they live](https://www.thefunctionalart.com/2018/07/visualizing-amalgamation-paradoxes-and.html). This correlation, of course, breaks at an individual level.
I very much doubt that Joseph would approve of this ecological study. [[6](https://pubmed.ncbi.nlm.nih.gov/1140864/)]
The study makes no attempt to adjust for socioeconomic or genetic differences in the countries involved. Richer countries tend to have access to more expensive sources of calories, but also have fewer infections and cleaner water, among many other things conducive to better health. They also tend to eat meat. This doesn't tell us what's happening within each of those populations across the spectrum of meat consumption.
Also it's likely that the reason animal protein correlates strongly with height in Joseph's reference is that it's the main source of protein calories in most diets around the world. For example, in Europe where they essentially consume no plant protein (most plant foods consumed lack significant protein), highly correlated protein (defined by the authors as milk, eggs, pork, beef and potatoes), as well as animal protein and total meat associate more with height than total calories and total protein. If you look at Asia where people eat more plants protein, you'll see total protein and total calories correlate better. Also, inequality adjusted human development index unsurprisingly was more strongly correlated with height than any food.
**Claim #4 (**[**05:30**](https://youtu.be/MpxgZGnEF7E?t=330)**):**
> I recently interviewed Yovana Mendoza who had essentially made a career based around her vegan lifestyle when she had health issues she tried her best to solve them while staying on the diet, using all kinds of supplements and troubleshooting strategies but she eventually had to prioritize her health and quit the diet after 6 years … even though she had every motivation to keep being vegan. Reintroducing animal foods fixed her health issues. Yovana’s case is a peak at how complex it can be to replace animal foods in your diet.
Yovana Mendoza was a so-called "raw" vegan. As you can see from the picture he flashed, she was on a meme starvation diet of only raw food averaging an abysmal ~1000 calories a day.
Raw food diets are associated with many stupid beliefs revolving around self-purification, including extensive fasting periods (49% of study participants), not supplementing B12 (7% took any supplement at all), and enemas (16% of them). [[7](https://pubmed.ncbi.nlm.nih.gov/10436305/)]
Some believe once you are "purified" you lose your period which is a sign you're clean, for example. As you approach 100% raw food, pretty much half of them complain of amenorrhea, probably due to insufficient calories.
As you can see, raw diets associate with considerably low BMI scores.
Rawvana also [made a video](https://youtu.be/hMO4m0rZAB8?t=27) telling us how since she's gotten healthier on her raw vegan diet her "eyes have become greener", so I don't know how much stock we should put in her health advice, Joseph.
As illustrated by [Anna's analysis](https://youtu.be/iqDK_0iaVCE), this seems to be an extremely common pipeline. People go raw vegan, influenced by social media morons, they don't eat enough calories, because their diets aren't formulated correctly, and then they return to some omnivorous diet and claim that veganism failed them. No. Veganism didn't fail you. You played a stupid game and you won a stupid prize.
**Claim #6 (**[**06:18**](https://youtu.be/MpxgZGnEF7E?t=378)**):**
> Take Vitamin A - you might think the average vegan has way more vitamin A because it comes from vegetables like carrots or sweet potatoes - but that’s not vitamin A, that’s beta carotene that has to be converted into vitamin A …and the conversion rate is very poor - about 12:1. [[8](https://pubmed.ncbi.nlm.nih.gov/20237064/)] Though it’s more like 21:1 when you account for the hampering effect of fiber in the diet. [[9](https://pubmed.ncbi.nlm.nih.gov/12221270/)] Not only that, the more you eat, the worse the conversion rate becomes. Further, depending on your genes, your conversion rate could be even lower - [this is the case for me](https://www.youtube.com/watch?v=gWiC4ZCS55Y&t=421s) and for potentially as much as 37% of people of European descent (See also, 57% lower. [[101](https://pubmed.ncbi.nlm.nih.gov/35571879/)][[1](https://pubmed.ncbi.nlm.nih.gov/35571879/)[12](https://pubmed.ncbi.nlm.nih.gov/19103647/)] Actual vitamin A only comes from animal foods or synthetic supplements.
Firstly, let's cut to the chase. Is there a risk of vitamin A deficiency among those only relying on non-retinol sources of vitamin A? That's the question. We'll get to the mechanistic speculation, and why it's so dumb, but for now let's focus on actual outcomes. To my knowledge there are two studies assessing retinol status in vegans after excluding those who supplement. [[13](https://pubmed.ncbi.nlm.nih.gov/24394311/)][[14](https://pubmed.ncbi.nlm.nih.gov/26502280/)]
Both studies showed that vegans had statistically significantly lower retinol status than omnivores, but the differences were not clinically significant. We're free to speculate all we want, but at the end of the day there is no reason to believe that the differences in status actually amount to any differences in expected health outcomes between the two groups.
Now, let's get to the mechanistic fuckery. Joseph claims that there are genetic differences in carotenoid to retinol conversion capacity that could lead to deficiency in some who are relying on carotenoids over retinol. Right off the bat, Joseph's own reference contradicts his claim, as the entire variance in the population sample had fasting plasma retinol within the reference range.
> _...the lowest plasma concentration was 963.8 nM, indicating that all volunteers had adequate serum vitamin A concentrations._
Even the people with the worst impairments maintain adequate retinol status, despite only getting an average of a measly 133mcg/day of retinol. The only thing that changes is that the ratio of beta-carotene to retinol is increased based on the severity of the impairment in conversion rates. That's all.
But, we can take this a step further and actually see what happens when we try to correct vitamin A deficiency using dietary carotenoids in human subjects. [[15](https://pubmed.ncbi.nlm.nih.gov/15883432/)][[16](https://pubmed.ncbi.nlm.nih.gov/17413103/)][[17](https://pubmed.ncbi.nlm.nih.gov/9808223/)][[18](https://pubmed.ncbi.nlm.nih.gov/10584052/)][[19](https://pubmed.ncbi.nlm.nih.gov/15321812/)][[20](https://pubmed.ncbi.nlm.nih.gov/16210712/)] On the whole, eating foods rich in carotenoids reliably improves and/or normalizes vitamin A status. Even foods that have been genetically engineered to have higher levels of carotenoids reliably improve vitamin A status in humans. [[21](https://pubmed.ncbi.nlm.nih.gov/19369372/)] In fact, a newer study published in 2020 found no differences in retinol status between BCO1 genotypes in a population consuming low amounts of preformed retinol. [[22](https://pubmed.ncbi.nlm.nih.gov/32560166/)]
Let me explain what's happening here. These genetic variants likely aren't changing the total amount of retinol converted from carotenoids. Likely the only thing that's happening here is that the conversion curve is changing shape without a change to the area under that curve. Meaning that across these genetic variants, people are capable of converting the same amount of retinol from carotenoids, but the rate at which they make that conversion is slightly longer in those with the so-called impairments. In my opinion, this is the most parsimonious way to reconcile the data.
As a side note, the only cases of vitamin A toxicity (hypervitaminosis A) from whole foods that I could find in the literature involved the consumption of preformed retinol from liver. [[23](https://pubmed.ncbi.nlm.nih.gov/25850632/)][[24](https://pubmed.ncbi.nlm.nih.gov/21902932/)][[25](https://pubmed.ncbi.nlm.nih.gov/10424294/)][[26](https://pubmed.ncbi.nlm.nih.gov/31089689/)][[27](https://pubmed.ncbi.nlm.nih.gov/3655980/)] In one case, a child died from consuming chicken liver pate sandwiches. I could find no case reports of such vitamin A toxicity related to carotenoids.
**Claim #7 (**[**06:58**](https://youtu.be/MpxgZGnEF7E?t=418)**):**
> A 2021 study found vegan Finnish children had insufficient vitamin A and a 2020 German study found vegans to have a lower vitamin A level than omnivores. [[28](https://pubmed.ncbi.nlm.nih.gov/33471422/)][[29](https://pubmed.ncbi.nlm.nih.gov/33161940/)]
In both studies, vegan participants had lower vitamin A status, but again, this seemed to be clinically irrelevant. With the authors of the Finnish study concluding that none of the vegans could be classified as deficient, and the the authors of the German study reporting that Vitamin A status among vegans was still well within the reference range.
We should be starting to see a pattern here, and this should lead us to question the utility of having higher vitamin A status as a consequence of consuming preformed retinol. Even if we granted that you will boast a higher vitamin A status as an omnivore, it's not clear that possessing a higher status actually has any clinical benefit or advantage. I don't know why it would be desirable. Is Joseph prepared to resign himself to affirming that more is simply better? Shall we coin this the Everett Fallacy?
**Claim #8 (**[**07:26**](https://youtu.be/MpxgZGnEF7E?t=446)**):**
> Vitamin D is pretty much only found in animal foods with some exceptions like some mushrooms and some algae. Some people can get enough vitamin D from the sun, but if you live at latitudes above 37 degrees, your skin barely makes any vitamin D from the sun except for in summer. [[30](https://www.health.harvard.edu/staying-healthy/time-for-more-vitamin-d#:~:text=Except%20during%20the%20summer%20months,risk%20for%20vitamin%20D%20deficiency)]
This is one of those times where I won't say anything I will just let his citation speak for itself.
> "Lack of sun exposure would be less of a problem if diet provided adequate vitamin D. But there aren't many vitamin D–rich foods (see chart, below), and you need to eat a lot of them to get 800 to 1,000 IU per day...For these and other reasons, a surprising number of Americans — more than 50% of women and men ages 65 and older in North America — are vitamin D–deficient, according to a consensus workshop held in 2006."
His own citation notes that a massive portion of the population is deficient and the treatment for that is sun exposure or supplementation, not goose liver.
**Claim #9 (**[**07:40**](https://youtu.be/MpxgZGnEF7E?t=460)**)**
> A 2016 Finnish study found vegans’ levels of vitamin D to be 34% lower than omnivores. [[31](https://pubmed.ncbi.nlm.nih.gov/26840251/)]
They had lower intake and therefore lower levels. According to Joseph's previous reference, they should probably be supplementing more.
**Claim #10 (**[**07:52**](https://youtu.be/MpxgZGnEF7E?t=472)**):**
> Unless you’re eating fermented foods, you’ll only find vitamin K2 in animal foods. The richest sources of K2 are going to be animal livers (especially goose liver), egg-yolks, hard cheese and full-fat dairy. Unfortunately New York City made it illegal for schools to serve whole milk in 2006. [[32](https://www.politifact.com/factchecks/2021/jun/07/lorraine-lewandrowski/whole-milk-prohibited-being-offered-new-york-schoo/)] The fermented soybean dish natto does in fact have a ton of K2 and sauerkraut has some too. Vitamin K2 helps put calcium into the right places like your bones and keeps it out of your heart which is thought to be one reason higher vitamin K2 strongly correlated with reduced risk of heart disease. [[33](https://pubmed.ncbi.nlm.nih.gov/34785587/)][[34](https://pubmed.ncbi.nlm.nih.gov/28639365/)]
Here's a quick intro for vitamin K2. There are many different vitamin K isomers (or vitamers). We have vitamin K1 from plants and vitamin K2, primarily from fermented foods or animal products. There is only one vitamin K1, but vitamin K2 has many forms, including MK4 and MK7, which have been studied most. The form of K2 you can not obtain from fermented foods is MK4, but it doesn't appear to be bioavailable at nutritional doses.
First, we'll look at bioavailability of MK4. He mentions animal livers (especially goose liver), egg-yolks, hard cheese and full-fat dairy. I couldn’t find any study on bioavailability of MK4 from foods rather than supplements. But, we can look at studies with doses one could plausibly obtain from diet alone. In probably the best study on this subject, researchers assessed **420 μg of MK-4 compared to 420 μg of MK-7**. [[35](https://pubmed.ncbi.nlm.nih.gov/23140417/)] As you can see from this chart, the only reasonable way to obtain this is with goose liver. [[36](https://pubmed.ncbi.nlm.nih.gov/11356998/)]
The other things he recommended simply don’t have enough. To get this amount it would take **8.9 kilograms of hard cheese, 52.5 liters of whole milk, or 52.4 average eggs.** The amount of goose liver it would take to get this dose of MK-4 is roughly **115g of liver,** however this has **over 10,000μg of retinol, the upper limit is 3000μg** and hypervitaminosis A is no joke.
But regardless, let’s say someone managed to eat this amount of MK-4 regularly. Is it actually absorbed? It wouldn't appear so.
At no time point after the oral administration of 420μg of MK4 is it actually detectable in the blood.
In summary, Joseph suggests food items like hard cheese and whole milk for vitamin K2 when they have abysmal amounts that probably aren't even absorbed. Worth noting that the natto he dismissed contains MK7 which is actually bioavailable, as evidenced by the same reference. Natto also contains it in concentrations over **700 times that of hard cheese**, which is the richest source of MK7 out of the foods he listed.
**Claim #11 (**[**08:25**](https://youtu.be/MpxgZGnEF7E?t=505)**):**
> Speaking of all these nutrients for the skeleton, a 2021 polish study found vegan children to have weaker bones and were 3cm shorter than their meat eating counterparts. [[37](https://pubmed.ncbi.nlm.nih.gov/33740036/)]
What Joseph didn't mention was that 29% of the vegan children did not consume vitamin B12 supplements or fortified foods, and only 32.7% used vitamin D supplements. Those who did actually consume vitamins B12 and D had comparable B12 and D status to omnivores. It's entirely plausible, if not probable, that this high percentage of non-supplementing participants was enough to drag down the average for the entire group.
I mention this because it's clear that a large chunk of the cohort was not actually supplementing vitamin B12 and vitamin D. Both of which are nutrients that are strongly associated with normal growth. There was also little to no consideration for other dietary variables, and the analysis itself is cross-sectional with extremely small sample-sizes.
Perhaps also worth noting are the similar lean mass, lower fat mass, and preferable LDL-C and hs-CRP values of the vegans. But he didn't mention that.
**Claim #12 (**[**08:27**](https://youtu.be/MpxgZGnEF7E?t=507)**):**
> A British study and a Dutch study also found vegan children to be shorter. [[38](https://pubmed.ncbi.nlm.nih.gov/3414589/)]
Let's start with the British study. These results are trivially explainable by the lower caloric intakes for vegans in his reference.
Also, while the vegans tended to fall below the 50th percentile for weight, the vast majority experienced normal growth, and the lower weight (and in some cases height) may be attributable to the lower caloric intake. The authors actually take note of this, but Joseph didn't mention it.
The authors also suggest that the lower fat intake may be the reason they had a lower caloric intake, and go on to state that dense fat sources can be important for children for that reason (eat your avocados, kids). They concluded that children can grow up to be "normal" and that there's no evidence of impairment to cognitive development.
Just as a side note, it's also funny to mention that the vegan diets were more nutrient dense than the average omnivorous UK diet. Even more hilariously, they explicitly state that there are healthy and unhealthy versions of vegan diets and that clowns will run with the occasional case reports on unhealthy vegan kids fed **inappropriate** diets. These authors were calling out Joseph in 1988.
On to the Dutch study. Firstly, the so-called "vegan" diet was actually a type of meme "vegan" diet called the macrobiotic diet. This diet is highly restrictive and often very low in protein. This is not representative of what a well-balanced "vegan" diet would look like.
Thus far, the studies he cited either haven't supported his claim or provide clear reasons for why there may be differences in growth. With the reasons provided not being intractable characteristics of vegan diets themselves. He also left out the studies where we do see similar growth between vegan and omnivorous kids with adequate diets.
In the Farm Study was a 1989 study involving children ages four months to ten years residing in a community in Tennessee. [[39](https://pubmed.ncbi.nlm.nih.gov/2771551/)] 75% of mothers were vegan through pregnancy and 73% of children were vegan since birth. These mothers consumed well balanced diets with fortified foods (soy milk and nutritional yeast), which they fortified themselves!
> The Farm community was generally well informed regarding issues related to vegetarianism, including complementing different protein sources, for example, grains and legumes and nonanimal sources of vitamins and minerals. Until 1983, the population followed a vegan diet, with soybeans being their primary source of protein. Supplements of vitamins A, D, and B12 were added to the soy milk produced on The Farm. Nutritional yeast (containing vitamin B12) and other vitamin and mineral supplements were also used. In the fall of 1983, some members of the community introduced eggs and dairy products into their diets.
Across vegan children, growth was skirting the 50th percentile on average. This is exactly where these growth trajectories should be.
Same for weight.
We also have the VeChi Diet Study. [[40](https://pubmed.ncbi.nlm.nih.gov/31013738/)] Vegan and omnivorous children had similar caloric intakes. Omnivores had the highest protein, fat, and added sugar intake, while vegans had the highest total carb and fibre intake. In fact, the vegans were still able to consume a median of 2.25g of protein per kg bodyweight. While there were a few outliers in each group, growth was generally very similar overall.
There are explanations for the children who may have been stunted or wasted, and they're nothing that is necessarily inherent to vegan diets themselves. These reasons include: short parents, inadequate caloric intake, exclusively breastfeeding longer than recommended (probably due to hippie vegan parents doing dumb hippie things).
> Regarding these eight children classified as stunted, two had very low reported energy intakes (534 kcal/day and 598 kcal/day, respectively), and both were exclusively breastfed >6 months (7 and 9 months, respectively). An overly long period of exclusively breastfeeding can result in an insufficient intake of complementary foods and inadequate low TEI because, after a certain age, human milk alone cannot supply energy and all nutrients in adequate amounts to meet a child’s requirements [71]. Furthermore, one of the two children as well as three other children classified as stunted had parents with a BH (mother: 161 cm, father: 170 cm) below the German average (167 cm and 180–181 cm of 25–55-year-old women or men, respectively) that might have influenced the child’s BH. The other child with low energy intake was also categorized as SGA, which is considered a risk factor for stunting [72]. Another stunted child was categorized as SGA, and its birthweight was only slightly above 2500 g (2545 g). The seventh child was exclusively breastfed for twelve months (the eighth child was breastfed for eight months), and it had parents with BHs (mother: 160 cm, father: 178 cm) below the German average.
We also have data on intake of micronutrients and fatty acids in the 1-3 year olds in this cohort. [[41](https://pubmed.ncbi.nlm.nih.gov/34855006/)] All diet groups had low iodine intake, and the vegans had the lowest intakes of saturated fat, cholesterol, and DHA (although omnivores had low intakes too), but higher intakes of ALA and LA. They also mention that vegan and vegetarian children had the more favourable intakes of several micronutrients and fatty acids.
In addition to evaluating nutrient intake, they also measured status in 6-18 year olds. [[42](https://pubmed.ncbi.nlm.nih.gov/34069944/)] Ultimately, the results are very similar to the those of the VeChi Diet Study that was previously mentioned, with preferable blood lipids in the vegans.
A further study on mothers consuming various dietary patterns supports that a vegan diet can support "normal and physiological growth" through pregnancy and the first year of life. Also of note, 95.2% (20/21) of the vegan mothers took supplements through pregnancy. [[43](https://www.minervamedica.it/en/journals/minerva-pediatrics/article.php?cod=R15Y9999N00A21041604)]
So some of Joseph's own references suggest vegan diets can support growth and development, and that is consistent with other research where vegans are consuming a balanced and appropriately supplemented diet.
**Claim #13 (**[**09:34**](https://youtu.be/MpxgZGnEF7E?t=574)**):**
> Most vegans know they need to supplement B12 which is very important for proper brain function. Yet, one study looking at B12 status in vegetarians and vegans found that 7% of vegetarians and 52% of vegans were not getting enough B12. [[44](https://pubmed.ncbi.nlm.nih.gov/20648045/)] However, in another study with a more sensitive testing method - they found a whopping 77% of vegetarians and 92% of vegans had insufficient B12 whereas only 11% of omnivores did. [[45](https://pubmed.ncbi.nlm.nih.gov/12816782/)] Perhaps these B12 supplements don’t work exactly like animal foods do. Also it can take years to deplete the body’s B12 store, so people can be lacking B12 for a while without realizing it.
Right off the bat, 81% of vegans did not supplement in the first study. In the second, the authors did not assess how many of them were supplementing, but we know 59% supplemented "B vitamins".
Joseph then concludes (from two studies were the majority did not supplement B12) that B12 supplements "don’t work exactly like animal foods do". If Joseph wanted to know if B12 supplements work at all he could've simply read his previous reference, Elorinne, et al. (2016). [[31](https://pubmed.ncbi.nlm.nih.gov/26840251/)] Had he done so, he would have noticed that 91% of that cohort took B12 supplements, and as you'd expect they were not B12 deficient.
If Joseph wanted to know if B12 supplements work differently than animal foods, he could turn his attention to this interventional study that found that fortified cereal was more effective at raising B12 than pork. [[46](https://pubmed.ncbi.nlm.nih.gov/31519167/)]
Also, various doses of cheapo, vanilla-ass cyanocobalamin rescue vitamin B12 deficiency in clinically deficient vegans. [[47](https://pubmed.ncbi.nlm.nih.gov/29499976/)] This is confirmed by clinically meaningful reductions in both methylmalonic acid and total homocysteine. If Joseph knows of any better biological correlates for B12 absorption and utilization, as well as evidence that they're uniquely affected by animal foods, I'd love to hear from him about it.
**Claim #14 (**[**11:38**](https://youtu.be/MpxgZGnEF7E?t=698)**):**
> ...another possibility is the vegan diet has impaired digestion.
The term "digestion" here is so unclear and nebulous, that it is uncertain what exactly to look for in the literature in order to test the hypothesis. However, if we assume that the hypothesis is referring to any symptoms related to digestion, we should expect to see increased rates of digestion-related symptoms, as reported as adverse events, in any of the randomized controlled trials that have been done on so-called "vegan" diets. But we can find close to none, which calls into question whether or not this is even an effect, let alone a generalizable effect.
**Claim #15 (**[**12:25**](https://youtu.be/MpxgZGnEF7E?t=745)**):**
> ...many [vegans] do quit the diet because of health issues.
If "many" is meant to be some sort of generalization, then his claim is straightforwardly contradicted by a study discussed in one of his own references on vegan recidivism rates, the 2015 Faunalytics study.
> Interestingly, health did not present a noticeable difficulty for study participants, with the exception of vitamin B12 monitoring. 2) Consider increasing awareness about the importance of B12: a far greater percentage of former (76%) than current (42%) vegetarians/vegans never had their B12 levels checked while they were adhering to the diet.
His only evidence for this claim is a montage of ex-vegan YouTubers who already have a demonstrable history of lying to people's faces. What the fuck are we even doing here, Joseph? These people were telling their audiences that they had newfound health on a vegan diet, and now they are once again telling their audiences that they have newfound health, but on a non-vegan diet. Joseph expects us to believe them. I can only guess that's because he is an idiot and doesn't understand what evidence is.
**Claim #16 (**[**13:21**](https://youtu.be/MpxgZGnEF7E?t=801)**):**
> A 2012 study found in 63 patients with constipation, reducing fiber intake improved symptoms but eating a zero fiber diet completely eliminated all symptoms. [[48](https://pubmed.ncbi.nlm.nih.gov/22969234/)]
This is a category mistake. Constipation isn't indigestion. Digestion precedes stool formation and colonic transit. Also, there is no mention of vitamin B12 deficiency or its related symptoms among the subjects in the reference Joseph provided. It's not clear how this is interacting with the claim.
I'll briefly entertain the tangent, though. The trial that Joseph references is not easily generalizable, because the subjects had idiopathic constipation. It's also not clear at all what this has to do with "vegan" diets. Additionally the researchers did not actually assess fibre intake. Fibre intake was assumed based on the researchers instructions to the subjects, which naturally is a very poor measurement to fibre intake.
Meanwhile, we see very consistently that increased consumption of fibre associates with a decrease in bowel transit time and improving symptoms of constipation. [[49](https://pubmed.ncbi.nlm.nih.gov/26950143/)][[50](https://pubmed.ncbi.nlm.nih.gov/35816465/)]
**Claim #17 (**[**13:46**](https://youtu.be/MpxgZGnEF7E?t=826)**):**
> As for B12, you need to have strong enough stomach acid to properly absorb it and dietary fiber is known to weaken the stomach acid. [[51](https://pubmed.ncbi.nlm.nih.gov/2823869/)][[52](https://www.tandfonline.com/doi/abs/10.3109/00365528709095891)][[53](https://pubmed.ncbi.nlm.nih.gov/6095709/)]
For the former claim, there is no reference. But what Joseph is probably referring to here is the requirement for a lower stomach pH in digesting food normally in general. Without a sufficiently acidic stomach acid, it is true that vitamin B12 may not be adequately liberated from a given food matrix.
However, this doesn't apply to supplements (as supplements do not have a food matrix that requires a particularly low pH stomach acid to digest), and therefore doesn't apply to "vegan" diets. Also, we can easily see from previously cited research that vegans can achieve and maintain normal B12 status on high fibre diets.
In fact, you can even absorb B12 adequately and rescue frank B12 deficiency syndromes by shoving it directly up your ass. [[54](https://pubmed.ncbi.nlm.nih.gov/5924495/)] Sublingual B12 supplements are effective in rescuing B12 deficiency. [[55](https://pubmed.ncbi.nlm.nih.gov/14749150/)] Both of these methods bypass the stomach completely.
**Claim #18 (**[**13:56**](https://youtu.be/MpxgZGnEF7E?t=836)**):**
> So the context matters - what else are you getting with the nutrients? For example, there are plenty of plant sources of iron, but plant foods like whole grains, legumes and nuts contain phytic acid that impairs iron absorption. [[56](https://pubmed.ncbi.nlm.nih.gov/12936958/)] Spinach is thought to be a great source of iron but you can only absorb 2% of it because of the oxalate in it. [[57](https://pubmed.ncbi.nlm.nih.gov/1745900/)]
Once again, Joseph shows that he either doesn't read the studies he cites or ignores where they contradict him. From the first study:
> Iron deficiency anemia appears to be no more prevalent among vegetarian women than among nonvegetarian women...Thus, although several reports indicate that vegetarians in Western societies have lower iron stores and may have lower hemoglobin concentrations, they do not indicate a greater incidence of iron deficiency anemia...Lowering iron stores without increasing the risk of iron deficiency anemia may confer a health advantage when vegetarian diets are chosen from an abundant food supply.
Joseph further shows that he is really good at constructing strawmen. What official public health authority in any developed country actually recommends spinach as a significant source of iron? Regardless, it's also a non-sequitur that just because spinach has a particularly poor bioavailability of iron that there exist no vegan sources of iron with good bioavailability. There even exist other green vegetables with good bioavailability, such as broccoli and cabbage. [[58](https://pubmed.ncbi.nlm.nih.gov/31394334/)]
**Claim #19 (**[**14:00**](https://youtu.be/MpxgZGnEF7E?t=840)**)**
> Then, where the heme-iron in animal foods is very easily absorbed, the non heme iron in plants and supplements is quite poorly absorbed. Two different literature reviews suggest that vegans are at greater risk for iron deficiency than omnivores [[59](https://pubmed.ncbi.nlm.nih.gov/28319940/)][[60](https://pubmed.ncbi.nlm.nih.gov/30783404/)].
No citation was provided for this claim and he says it as if it follows logically from what he said beforehand. Which it doesn't. Phytic acid in isolation impairing iron absorption in some plant foods high in phytic acid having low bioavailability of iron also doesn't imply that iron is poorly absorbed from all plant sources.
Firstly, despite whole wheat flour being higher in phytic acid than white wheat flour, it has better bioavailability of iron. [[61](https://pubmed.ncbi.nlm.nih.gov/10655952/)] Granted this is in animal models, but this is evidence Joseph has been known to accept in the past.
Secondly, other compounds that are common in plant foods but are absent (or virtually absent) from animal foods may have pleiotropic effects that mitigate or even overcome the effect of phytates on iron absorption, with vitamin C probably being the most prominent example. In regards of counteracting phytic acid, 50mg (less than an orange worth) does more than 50g of meat. [[62](https://pubmed.ncbi.nlm.nih.gov/2911999/)]
It also doesn't follow that one needs to consume animal products to meet iron needs, which Joseph heavily implies. Increased intake through diet and/or supplementation are clearly possible.
First of all, both the literature reviews Joseph cites are looking at vegetarians, not vegans. I thought his video was on so-called "vegan" diets, not vegetarianism. Even the authors of his own references disagree with his interpretation. Here's a quote from Pawlak, et al. (2017):
> Findings regarding individuals who adhere to specific vegetarian diet type, such as vegans, were underrepresented and thus, conclusions regarding iron status among such individuals were not possible.
And from another of Joseph's references, Pawlak, et al. (2018):
> Considering the limitations, it is reasonable to conclude that the findings are most likely not representative of the entire vegetarian populations nor are they representative of any one specific vegetarian subgroup. 3 of the studies were published in the 1990s and one in 1982. It is reasonable to assume that iron fortification practices have changed since the time of food availability has improved due to globalization. Consequently, this makes the generalization of the findings difficult
So, what is the point in wrongly applying or generalizing these findings with already questionable external validity from vegetarians onto vegans? That being said, just because the studies Joseph cites don't appropriately support his claim does not imply that his claim is wrong. For that, we need to go deeper.
There are three studies that were published before the two reviews that Joseph cited that differentiate between vegans and vegetarians, while also comparing them to omnivores with measurements of plasma ferritin. There are four that were published afterward. It would be valuable to go through them one by one.
In Schüpbach, et al. (2017), omnivores had higher plasma ferritin, but there was a lower percentage of vegans than omnivores in the range of deficiency, while vegans had almost double the iron intake of omnivores. [[14](https://pubmed.ncbi.nlm.nih.gov/26502280/)]
The more curious finding with respect to iron was that for omnivores and vegetarians, the correlation between iron intake and plasma ferritin was fairly strong and statistically significant (r = 0.247, p = 0.030; r = 0.331, p = 0.030, respectively), but not so for vegans (r = 0.168, p = 0.281).
The more concerning finding outside of iron was that despite a similar zinc intake across groups almost half of vegans were below the normal range compared to just 10% of omnivores. However, almost 60% of omnivores had folate levels below the normal range as well.
Vegans in Elorinne, et al. (2016) had much lower plasma ferritin than non-vegetarians despite higher intake. [[31](https://pubmed.ncbi.nlm.nih.gov/26840251/)] It's unclear whether there was a single subject with low ferritin and this result was not discussed anywhere in the text. However, there were funny sections about selenium in fertilizers and how a low LA intake might help vegans convert LNA to DHA.
Less than half the vegan children in Desmond, et al. (2021) used B12 supplements, almost a third got neither B12 supplements nor B12 fortified foods. [[37](https://pubmed.ncbi.nlm.nih.gov/33740036/)] Under their second adjustment model, the vegan children had 25% lower ferritin levels. 30% of the vegan children had ferritin levels below the cut-off, compared to 13% of the omnivore children. 2% and 6% of vegan children had moderate and mild iron deficiency anemia, respectively, compared to none of the omnivore children. The authors were (rightfully) much more concerned about the differences in bone mineral content and B12 deficiency. They also get props for looking at cardiovascular risk factors in children.
Another study, by Slywitch, et al. (2021), gets props for a 10 year long recruitment period and for differentiating between menstruating and non-menstruating women. [[63](https://pubmed.ncbi.nlm.nih.gov/34578841/)] However, for unknown reasons, these authors only differentiated between vegans and vegetarians for the analysis on BMI but not for ferritin. To be fair, they were more interested in how inflammation may mask iron deficiency, but still. It would have been nice to have that data.
Weikert, et al. (2020) represents one of the better studies on the subject, because the groups were similar in their characteristics and all but one vegan were actually using supplements. [[29](https://pubmed.ncbi.nlm.nih.gov/33161940/)] Plasma iron and ferritin levels were on average lower in vegans than omnivores, but not statistically significantly so, with the vegans having a 50% higher iron intake. 11% of vegans showed signs of iron deficiency compared to 8% of omnivores. Vegans who substituted iron had higher average ferritin than omnivores who did not substitute iron.
Another study by Alexy, et al. (2021) found statistically significantly lower plasma ferritin than omnivores despite 50% higher iron intake, but prevalence below the cut-off was called "low" by the authors and thrown into the supplemental. [[42](https://pubmed.ncbi.nlm.nih.gov/34069944/)] Weirdly, the authors were concerned about the high prevalence of B2 deficiency in all groups, using a cut-off of 199 µg/l.
In Wilsen, et al. (1999), despite the 50% higher iron intake, the vegans had almost 50% lower serum ferritin than omnivores, with 20% falling below 12 ng/ml. [[64](https://pubmed.ncbi.nlm.nih.gov/10201799/)] The difference in hemoglobin between vegans and omnivores was also statistically significant. On the other hand, 20% of omnivores had ferritin levels elevated above 200 ng/ml, which is indicative of inflammation.
In conclusion, even though Josephs citations don't support his claim, there is some truth to the matter. The literature is in unanimous agreement that iron in vegan diets has much lower bioavailability, but this is not due to phytates alone. Dietary fiber and polyphenols are important as well. Of course this is not enough to infer an outcome such as iron deficiency, let alone iron deficiency anemia, since vegans also have a much higher iron intake than omnivores. Furthermore, in many of the studies lower iron status is observed without a particularly increased risk of deficiency.
Vegans, especially those who menstruate, might want to err on the side of caution by regularly getting their ferritin checked whenever they get their B12 checked, and then supplementing accordingly. Pretty much the same is true for vegetarians, or even omnivores for that matter. But what these studies show overall is that no matter their diet, people kind of suck at hitting reference ranges of biomarkers for all nutrients.
**Claim #20 (**[**14:30**](https://youtu.be/MpxgZGnEF7E?t=870)**):**
> Now before we continue, why should we assume a meat containing diet was the natural default for humans rather than a plant-based diet? Well, to get a wide variety of nutrients, vegans have to eat a huge variety of modern fruits and vegetables, but the fruits and vegetables early humans had access to were nothing like modern ones. Before cultivation, they had far less actually edible material and far more fiber and seeds. Paleoanthropologist Daniel Lieberman has said that the sweetest fruit available would have been no sweeter than a modern day carrot.
Previously having less edible material is trivially true of animal foods produced from modern animal agriculture.
**Claim #21 (**[**14:58**](https://youtu.be/MpxgZGnEF7E?t=898)**):**
> We have stable isotope studies finding we ate pretty much whatever meat we could get our hands on… our earliest art is cave paintings of hunts. Lastly, the brain is a disproportionately energy expensive organ, hogging 20% of our oxygen and calories. [[65](https://pubmed.ncbi.nlm.nih.gov/30872714/)][[66](https://pubmed.ncbi.nlm.nih.gov/12149485/)] Our guts (also energy expensive) shrank in size to allocate more resources to the brain. [[67](https://pubmed.ncbi.nlm.nih.gov/22174868/)] Thus, to fuel our big brains, the more energy efficient animal fat became favored over fibrous plants that took time and energy to chew and digest.
What point is Joseph trying to make here? We could try to formalize it, perhaps.
**Definitions:**
**B** := (x) food make brain big
**G** := (x) food gud
**O** := ooga booga
**m** := meat
**p** := plants
**P1)** If food gud, then food make brain big.
**(∀x(Gx→Bx))**
**P2)** Meat gud.
**(Gm)**
**P3)** Plants no make brain big.
**(¬Bp)**
**P4)** Ooga booga.
**(O)**
**C)** Therefore, meat make brain big, plants no gud, ooga booga.
**(∴Bm∧¬Gp∧O)**
**Claim #22 (**[**15:34**](https://youtu.be/MpxgZGnEF7E?t=934)**):**
> Most people are not aware that animal foods are packed with far more of a huge variety of nutrients, especially ones critical for brain function. This may have a role in why a 2021 study found people who don’t eat meat to have significantly higher risk of depression and anxiety. [[68](https://www.tandfonline.com/doi/full/10.1080/10408398.2020.1741505)]
Again, in his typical style, the review Joseph linked contained only one randomized controlled trial and guess what that one trial showed. I'll quote the authors directly.
> Restricting meat, fish, and poultry improved some domains of short-term mood state in modern omnivores. To our knowledge, this is the first trial to examine the impact of restricting meat, fish, and poultry on mood state in omnivores.
Also, the authors overlooked a couple more trials, and didn't even mention them. I personally don't really see a reason for their exclusion. [[69](https://pubmed.ncbi.nlm.nih.gov/24524383/)][[70](https://pubmed.ncbi.nlm.nih.gov/20389060/)] They also rated the one RCT that they did include as "low quality" without providing a decent justification. In both trials, a benefit of so-called "vegan" diets was observed.
Not only that, but in a 2022 systematic review including more studies, they note that higher quality studies and studies that can distinguish temporal relationships (such as RCTs and cohort studies) the effects of plant-based diets on mental health are either positive or non-significant. This review contained two RCTs, one on vegetarians (which can be interpretated as a meat-restriction intervention, so it is still relevant) which showed improved confusion and stress and one on vegans which showed improvements in depression indicators.
Lastly, one of the two "high quality" studies in the review that Joseph cited evaluated the temporal relationship and suggests that the so-called vegan diet came **after** the development of mental health issues. [[71](https://pubmed.ncbi.nlm.nih.gov/22676203/)] When vegan, vegetarian, and semi-vegetarian diets are separated, meta-analyses suggest that semi-vegetarian diets are associated with higher prevalence of depression, while there is no statistically significant relationship between "vegan" or vegetarian diets and depression. [[72](https://pubmed.ncbi.nlm.nih.gov/33822140/)]
Here is the prevalence of depression forest plot from that meta-analysis.
And mean depression scores.
Also, just for flavour, I'll point out that Joseph's reference was funded by the beef industry.
> This study was funded in part via an unrestricted research grant from the Beef Checkoff, through the National Cattlemen’s Beef Association. The sponsor of the study had no role in the study design, data collection, data analysis, data interpretation, or writing of the report.
**Claim #23 (**[**17:17**](https://youtu.be/MpxgZGnEF7E?t=1037)**):**
> The peoples Weston price studied had an intuitive understanding of the importance of nutrient dense foods - especially in pregnancy and childhood. Even without a nutrition label, they knew that certain animal foods encouraged proper robust growth.
There is an implicit claim here that animal foods have some kind of special importance for pregnancy and childhood. Ultimately, this is just an anecdote, barely distinguishable from an appeal to authority. So, let's throw one back from the American Dietetic Association:
> ...appropriately planned vegetarian, including vegan, diets are appropriate for all stages of the life cycle, including pregnancy, lactation, infancy, and childhood
To be clear, I think hinging the truth value of any claims about the health value of either co-called "vegan" diets or omnivorous diets on either of these opinions is incredibly cringe. It's just not clear to me why we can't just counter anecdotes with anecdotes.
**Claim #24 (**[**18:12**](https://youtu.be/MpxgZGnEF7E?t=1092)**):**
> As Michael Pollan has argued in his book In Defense of Food - we frequently fall victim to this concept of 'nutritionism' that we don’t necessarily need whole foods, we just need their components.
Joseph, what does it mean to fall victim to a concept that is arguably true? Also, what do you mean by need? Is there some sort of necessity relation between whole foods and human health that you'd like to tell me about?
**Claim #25 (**[**18:34**](https://youtu.be/MpxgZGnEF7E?t=1114)**):**
> According to a 2012 study, despite taking prenatal supplements, 58% of pregnant woman had iron levels below normal. [[73](https://pubmed.ncbi.nlm.nih.gov/22113871/)]
Joseph makes this claim to vaguely support the notion that we should not rely on supplements. However, the study cited to support this claim is a study of 19 pregnant women who were given labelled iron supplements in order to better characterise placental iron transport. It is not a large scale study of prevalence of iron deficiency in pregnant women who take prenatal supplements and therefore does not support the claim.
On the contrary, a meta-analysis involving 43274 women shows that preventative daily oral iron supplementation reduces iron deficiency and iron deficiency anemia at term by 57% and 70%, respectively. [[74](https://pubmed.ncbi.nlm.nih.gov/26198451/)]
**Claim #26 (**[**18:40**](https://youtu.be/MpxgZGnEF7E?t=1120)**):**
> 90% of Americans are not getting enough [choline]. [[75](https://pubmed.ncbi.nlm.nih.gov/30853718/)]
While it is clear that choline is an essential nutrient for proper liver, muscle, and brain function, and this study does estimate 90% of Americans to fall short of the adequate intake, the same study caveats that:
> Current intakes cannot be deemed inadequate based upon the [adequate intake] value alone. Although [adequate intakes] may be useful in guiding individual dietary plans, by definition, they are established when the evidence is insufficient to calculate an [estimated average requirement]. Therefore it is not possible to conclusively assess the risk of inadequacy in a population.
In short, the way Joseph presents this study is essentially fear-mongering.
**Claim #27 (**[**18:47**](https://youtu.be/MpxgZGnEF7E?t=1127)**):**
> Choline from egg-yolk is better absorbed than choline from the common supplement, choline bitartrate. 150 calories of egg yolk (a little over 2 eggs) are enough to meet ones adequate choline intake.
While choline absorption from eggs is particularly high, choline intake in the American population is driven by egg intake and vegetarians have the lowest intakes among the US population, this does not support the notion that choline requirements cannot be met with proper supplementation.
On the other hand, the same authors as from the paper before state that choline is a precursor to betaine, another 'methyl donor' largely present in plant foods such as wheat bran, beets and spinach. Higher intakes of betaine may spare some of the potential negative consequences of low choline intake among vegetarian populations. [[76](https://pubmed.ncbi.nlm.nih.gov/31385730/)]
The main concern with choline deficiency is non-alcoholic fatty liver disease (NAFLD). If choline deficiency was an issue among vegans we'd expect a positive correlation between higher adherence to so-called "vegan" diets and NAFLD, an inverse correlation between consumption of animal foods and NAFLD, no change or an increase in liver enzymes for NAFLD patients being told to eat a "vegan" diet, and lower odds of NAFLD in people who eat more than 2 eggs per day (calculated from the calories from egg yolk needed to achieve adequate choline intake as given by Joseph (keep this number in mind).
However, we see the opposite. Higher adherence to plant-based diets, especially healthful plant-based diets is associated with lower likelihood of fatty liver. [[77](https://pubmed.ncbi.nlm.nih.gov/30578029/)][[78](https://pubmed.ncbi.nlm.nih.gov/36235752/)] Higher consumption of animal foods correlated with a higher prevalence of NAFLD, while a higher consumption of grains and vegetables was correlated with a lower prevalence of NAFLD in Chinese Adults. [[79](https://pubmed.ncbi.nlm.nih.gov/26083112/)] Also, in a pilot study with 26 NAFLD patients who agreed to eat a vegan diet for six months 20 normalised their liver function tests, independently of their improvements in body weight. [[80](https://pubmed.ncbi.nlm.nih.gov/33548123/)] Meanwhile, in a case-control study of 951 patients who had been referred to hepatology clinics, those participants who consumed 2-3 eggs per week (not per day) had over 3-times higher odds of having NAFLD than those who consumed less than 2 eggs. [[81](https://pubmed.ncbi.nlm.nih.gov/28443155/)]
It doesn't actually seem like consuming choline from animal products, particularly eggs, is even an effective means of avoiding NAFLD. This may be because animal-derived sources of choline are also typically high in fat, which would likely increase the choline requirement.
Consuming more fats means activating the bodies lipid transport system, such as lipoproteins, to a greater degree. Phosphatidylcholine is one of the primary phospholipids that make up the membranes of lipoproteins. The more fat you eat, the more choline you require. This is basically why choline deficiency can cause fatty liver.
So, even from a mechanistic standpoint, it would be unclear whether or not high fat animal-based diets would have an advantage over low fat plant-based diets.
**Claim #28 (**[**19:02**](https://youtu.be/MpxgZGnEF7E?t=1142)**):**
> Dietary calcium reduces risk of heart attack, calcium supplements increase the risk of heart attack.
This claim, which Joseph bases off of a single study that he fails to cite in his substack document, is not supported by the larger literature. A multitude of meta-analyses of prospective cohort studies with combined sample sizes of hundreds of thousands of patients show an inverse correlation of total calcium intake and all-cause mortality in the short term (≤ 10 years), but no statistically significant correlation in the long term (> 10 years). This difference is likely explained by the positive correlation between both dietary and supplemental calcium with cardiovascular mortality, following a U-shaped dose response curve that becomes statistically significant for intakes exceeding ~1200 mg/day. [[82](https://pubmed.ncbi.nlm.nih.gov/25912278/)][[83](https://pubmed.ncbi.nlm.nih.gov/33382441/)][[84](https://pubmed.ncbi.nlm.nih.gov/25252963/)]
The only statistically significant finding of the only meta-analysis of RCTs of calcium supplementation was a 9% increased risk of coronary heart disease incidence, driven by dosages exceeding 1000 mg/day in men, but no statistically significant difference in all-cause mortality. [[85](https://www.tandfonline.com/doi/full/10.1080/07315724.2019.1649219)]
Therefore, calcium supplementation in a range similar to reasonable dietary intakes should be regarded as safe. It is also effective at improving bone mineral density in both preadolescent children and adults with osteoporosis. [[86](https://pubmed.ncbi.nlm.nih.gov/36808216/)][[87](https://pubmed.ncbi.nlm.nih.gov/36810543/)]
**Claim #29 (**[**19:12**](https://youtu.be/MpxgZGnEF7E?t=1152)**):**
> Vegans have weaker bones and a 43% higher risk for fractures than omnivores. [[88](https://pubmed.ncbi.nlm.nih.gov/33222682/)]
On average, vegans do in fact tend to have a lower bone mineral density and higher hip fracture risk compared to non-vegans. This alone is uninteresting, though. We know that, on average, omnivores have a higher BMI than vegans. In this study the difference in BMI between the groups was 2.4 points, in the general population it is more than double that.
BMI has been shown to causally increase bone mineral density, which in turn has been shown to causally decrease risk of fracture. This effect mediation has been found independently in observational studies, and the differences in bone mineral density seem to align with what we would expect based on the differences in BMI. [[89](https://pubmed.ncbi.nlm.nih.gov/33784428/)][[90](https://pubmed.ncbi.nlm.nih.gov/36260985/)][[91](https://pubmed.ncbi.nlm.nih.gov/24862213/)][[92](https://pubmed.ncbi.nlm.nih.gov/15817133/)]
So the question that is interesting here, from a causal perspective, is whether vegans have weaker bones and higher risk of fracture independently of BMI and other important confounders such as calcium and vitamin D. Vitamin D has not been taken into account at all in the EPIC-Oxford study. BMI and dietary calcium were adjusted for, but only via categorisation, which is known to bias results when examining continuous variables with non-linear responses. [[93](https://pubmed.ncbi.nlm.nih.gov/17938055/)]
In the Adventist Health Study 2, a better prospective cohort study (more recent, bigger sample size, higher proportion of vegans, longer follow-up, etc), the same question was investigated. When adjusting for all known confounders (and unlike EPIC-Oxford using a proper adjustment model), only female vegans who did not supplement calcium and vitamin D were at a higher risk of hip fractures. [[94](https://pubmed.ncbi.nlm.nih.gov/33964850/)]
On the other hand, in another prospective cohort study, a higher ratio of animal protein to plant protein was found to increase rates of bone loss and fracture risk in postmenopausal women. [[95](https://pubmed.ncbi.nlm.nih.gov/11124760/)]
**Claim #30 (**[**19:52**](https://youtu.be/MpxgZGnEF7E?t=1192)**):**
> Dr. Francis Pottenger had been trying to formulate a healthy diet for his laboratory cats ... This had Dr. Pottenger conduct a 10 year study to puzzle out the effects of cooked meat versus raw meat on hundreds of cats. He found that the cooked meat cats consistently had health problems but the problems were even worse for their kittens.
This might be interesting if we continued to have an incomplete understanding of feline nutrition. But this isn't 1932. In fact we have such a strong understanding of feline nutrition these days, that we can even formulate nutritionally complete animal-free diets for cats.
There are plenty of plausible explanations for what happened to the cats. One plausible explanation is that cooking the meat destroyed the taurine content, as we understand that even mild temperatures can significantly reduce the taurine content of meat. [[96](https://pubmed.ncbi.nlm.nih.gov/22060873/)] Taurine is an essential nutrient in cats, and most of the symptoms described can be explained by a taurine deficiency.
At present, our understanding of human nutrition is such that many can live for years on total parenteral nutrition (TPN), which is a type of intravenous total dietary replacement. There has been plenty of literature pointing out that TPN is associated with a wide range of negative health outcomes. But, it's difficult enough to disambiguate the effects of the TPN and the effects of whatever led to the patient requiring TPN to begin with, let alone the ostensible effects of unknown, spooky mystery meat nutrients.
**Claim #31 (**[**25:05**](https://youtu.be/MpxgZGnEF7E?t=1505)**):**
> A huge 2020 review explained that saturated fat rich foods like whole-fat dairy or unprocessed meat themselves are not associated with an increase risk of heart disease and a 2022 systematic review found the previous evidence that shows unprocessed meat is linked to chronic diseases like cancer or heart disease to be far too weak to make the recommendation to reduce meat consumption.
The evidence used to buttress the JACC paper is the same sort of evidence that the BOP paper authors considers too weak to be reliable. Why even point it out if the evidence is shit?
But, just for clarification, it is understood that whole fat dairy blunts the effect of saturated fats on blood lipids, due to its unique food matrix and the presence of something called the milk fat globule membrane. [[97](https://pubmed.ncbi.nlm.nih.gov/26016870/)] It is also understood that chocolate, while high in saturated fat, is high in a particular type of saturated fat called stearic acid. This particular saturated fat does not have a significant effect on blood lipids. [[98](https://pubmed.ncbi.nlm.nih.gov/32998517/)]
This is just Joseph using these exceptions to the rule to obfuscate the effect that meat itself has on blood lipids, which is significant and replicable. [[99](https://pubmed.ncbi.nlm.nih.gov/31161217/)] Overall, we understand that the relationship between meat and heart disease is likely mediated by blood lipids, particularly LDL. Meat has a tendency to raise LDL, which just straightforwardly explains its strong association with heart disease.
**Claim #32 (**[**25:44**](https://youtu.be/MpxgZGnEF7E?t=1544)**):**
> Yet, the anti-meat push has gotten so strong that as investigative journalist Nina Teicholz reveals, a recent Tufts University ranking system bogusly ranks Reese’s Peanut Butter Cups as healthier than Eggs, Cheese or Ground Beef.
These data don't represent any official guidelines. And I'm not sure how shitty input data and shitty methodology constitutes an "anti-meat push", honestly. But Joseph is not even representing the results of the Food Compass accurately. While it's true that on average animal products get a mediocre score, it's not true that they rank lower than snacks and desserts on average. [[100](https://pubmed.ncbi.nlm.nih.gov/37117986/)] What he presented in his video is an example of cherry picking.
In fact, some animal foods rank higher than some plant foods, and in the aggregate there is non-inferiority between some animal foods and some plant foods. For example, seafood ranks particularly high, and is non-inferior to both fruits and vegetables. Both meat and dairy are also non-inferior to grains. If Joseph wants to make some kind of claim about a vegan conspiracy to suppress the health value of animal foods, he'll have to explain why seafood gets such a remarkable score here.
**Claim #33 (**[**26:04**](https://youtu.be/MpxgZGnEF7E?t=1564)**):**
> It’s easy to assume that our understanding of individual nutrients is so advanced that we don’t need to rely on outdated meat-based diets - we can make replacements. But, while the amount of knowledge on nutrition that’s been accumulated is incredible, is it as complete as we assume?
While this has the appearance of being a sound inductive sort of argument, it ultimately seems to be an argument that is halfway between an appeal to ignorance and some nutrition-focused flavour of Pascal's wager. I'm not sure why we should find this persuasive. If we don't know if there are any nutrients in meat that currently render meat indispensable, I would just be agnostic about the existence of those nutrients.
**Claim #34 (**[**27:26**](https://youtu.be/MpxgZGnEF7E?t=1646)**):**
> It wasn’t even until 1998 that the nutrient Choline was recognized to be essential. Liver disease, atherosclerosis and neurological dysfunction taught us that Choline is pretty important. [[101](https://pubmed.ncbi.nlm.nih.gov/19906248/)]
>
> A paper from just last year in 2022, suggests we underestimate the optimal intake of choline. [[102](https://pubmed.ncbi.nlm.nih.gov/34962672/)] This Cornell study found that seven-year-old children had better attention span if their mothers consumed twice the recommended amount of choline during their pregnancy.
It is known that prenatal DHA supplementation positively influences attention of infants and preschool children in a similar manner as found for choline in the Cornell study. [[103](https://pubmed.ncbi.nlm.nih.gov/27362506/)][[104](https://pubmed.ncbi.nlm.nih.gov/27604770/)] Additionally, there is high-quality emerging evidence that prenatal choline supplementation improves DHA status in pregnant women but not in lactating women (also no statistically significant difference for DHA concentration in breast milk) making it likely that the beneficial effect of prenatal choline supplementation on sustained attention is mediated through DHA. [[105](https://pubmed.ncbi.nlm.nih.gov/35575618/)][[106](https://pubmed.ncbi.nlm.nih.gov/33516092/)]
Therefore, it may be prudent for both vegan and non-vegan women, especially those with certain PEMT genotypes, to supplement choline in addition to DHA during the second and third trimester of their pregnancies. [[107](https://pubmed.ncbi.nlm.nih.gov/36145177/)]
**Claim #35 (**[**28:33**](https://youtu.be/MpxgZGnEF7E?t=1713)**):**
> If a mother can’t breastfeed or get donor milk, of course modern infant formula is basically a miracle. But even as a representative of Abbott, a leading infant formula manufacturer admits: “to mimic and replicate breast milk is not possible.” Yes, a newborn will have far more sensitive nutrient requirements than an adult or even a child, but it’s an example the difficulty of trying to make a complete replacement of a natural food.
The two scenarios are not analogous. In the case of vegan replacements for animal based foods, we generally don't see people on properly planned "vegan" diets experiencing negative health outcomes as a consequence. So, even if the association between formula feeding and negative health outcomes was strong, it's not clear how one functions as a plausible analogy for the other.
**Claim #36 (**[**29:28**](https://youtu.be/MpxgZGnEF7E?t=1768)**):**
> ...there is evidence that [insert non-essential animal nutrient here] has beneficial effects. [[108](https://pubmed.ncbi.nlm.nih.gov/32072297/)]
In most studies wherein a benefit of these animal-derived compounds is found, supranutritional doses are given to subjects. Not only that, but the minimum doses required to achieve maximum benefits (when benefits are even present) is often well above and beyond what we could reasonably obtain from diet alone. This just leaves us asking why omnivore shouldn't be relying on supplements too.
**Claim #37 (**[**29:38**](https://youtu.be/MpxgZGnEF7E?t=1778)**):**
> Just to look at two This 2002 paper argues that taurine may be essential in certain circumstances, and creatine supplementation has benefits for brain function in adults like improving memory, intelligence and mood and it reduces the negative effects of sleep deprivation. [[109](https://pubmed.ncbi.nlm.nih.gov/12514918/)][[110](https://pubmed.ncbi.nlm.nih.gov/29704637/)][[111](https://pubmed.ncbi.nlm.nih.gov/16416332/)] Further, creatine is transferred from the mother to her baby during pregnancy providing several benefits to the baby. [[112](https://pubmed.ncbi.nlm.nih.gov/24766646/)]
The "certain circumstances" here were premature infants on total parenteral nutrition. The authors say this is due to them being unable to synthesize their own taurine at this stage and depending on breast milk. How is this related to vegan diets or even animal foods?
Regarding creatine, all studies he cited were on supplemental creatine with doses that would require over 1kg of beef a day to get. For most individuals, beyond their caloric needs.
**Claim #38 (**[**30:14**](https://youtu.be/MpxgZGnEF7E?t=1814)**):**
> You could take substantial amounts of soy or pea protein powders to make up for the fact that most plant proteins are poorly absorbed and have lower amounts of amino acids and so on and so on.
I'm sorry, Joseph. But tracer studies disagree. [[113](https://pubmed.ncbi.nlm.nih.gov/33693735/)] In fact, tofu appears to be on par with pork, and better than eggs, in terms of its contribution to total positive protein balance in the human body.
If you're going to try to make this point to shit on tofu, would you please be consistent and also shit on pork and eggs?
**Claim #39 (**[**30:28**](https://youtu.be/MpxgZGnEF7E?t=1828)**):**
> Again, meat is so nutrient dense that you can get a decent amount of well absorbed zinc, iron, selenium, choline, various B-vitamins, vitamin A, calcium and other nutrients just eating a crappy cheeseburger.
Here, in another certified bruh moment, Joseph relies on vague language to make a point that nobody should care about. You can only eat around three Burger King Whopper cheese burgers before exceeding 2200 Kcal, but you'd also be deficient in most nutrients.
While it's true that you would get the RDA of a number of nutrients, you would also exceed your sodium RDA by 268%, the AI for potassium would be undershot by 50%, and only 50% of the conservative 600 IU of vitamin D would be obtained. Additionally, you would only get about 40% of the RDA of vitamin A, in exchange for over 40g of saturated fat.
While I am aware that Joseph is not advocating for cheeseburger consumption, it's just an incredibly stupid point to make. Which leads me to the next claim.
**Claim #40 (**[**30:40**](https://youtu.be/MpxgZGnEF7E?t=1840)**):**
> Ideally people shouldn’t eat crappy cheeseburgers… but the average busy person doesn’t have time to craft the perfect meal - convenience is important. This is evidenced by the fact that a 2021 paper found that the more people avoided animal products in their diet - the more they ate convenient ultra-processed foods with vegans eating the most processed foods. [[114](https://pubmed.ncbi.nlm.nih.gov/32692345/)]
In yet another instance of Joseph failing to read his own references, possibly because he's rushing for that confirmation bias induced YouTube money, he mentions convenience ultra-processed foods (UPF) but links a paper where the reason vegans seemingly ate more UPF (not convenience foods) was that the authors classified meat alternatives and plant based milks like soy milk as UPF.
> Concomitantly with the increased numbers of vegetarians or vegans, the offer of industrial plant-based meat and dairy substitutes on the market has been growing during the past decade in Western countries (e.g., tofu, textured vegetable foods such as vegetarian sausages or patties, and plant-based drinks such as soy “milk”) (9, 10). Most of these substitutes are ultra-processed foods (UPFs). The development of this industrial plant-based meat and dairy substitutes market (11, 12, 13, 14) may have contributed to the growing consumption of UPFs in countries such as France (15) by specific populations. For example, persons avoiding most animal-based foods may have high intakes of UPFs, driven by higher consumptions of plant-based meat and dairy substitutes.
The difference was so tiny as to be entirely explained by that classification.
> The proportion of energy from UPFs was significantly higher for vegetarians (37.0% of the total energy intake) and vegans (39.5%) than for meat eaters (33.0%) (Figure 1A). Comparing vegans to meat eaters, for example, vegans consumed a greater proportion of UPFs (+6.41%) (Figure 1B).
In addition, Joseph failed to mention that vegans eat more unprocessed foods than omnivores.
> The proportion of energy from unprocessed foods was significantly higher for vegans (31.2% of the total energy intake) than for meat eaters (29.0%) (Figure 1A and B).
**Claim #41 (**[**31:13**](https://youtu.be/MpxgZGnEF7E?t=1873)**):**
> Eating tons of processed soy protein and vegetable oils like sunflower oil is quite new to the human stomach. Sunflower oil seems like a simple swap for animal fat … but they are totally different. Many animal fats can be a good source of vitamin K2, but vegetable oil in fact hampers the activity of vitamin K, increasing your need for it. [[115](https://pubmed.ncbi.nlm.nih.gov/12032162/)][[116](https://pubmed.ncbi.nlm.nih.gov/27251151/)][[117](https://pubmed.ncbi.nlm.nih.gov/28962307/)][[118](https://pubmed.ncbi.nlm.nih.gov/29353277/)] It also oxidizes very easily so it will increase your need for the antioxidant vitamin E. [[119](https://pubmed.ncbi.nlm.nih.gov/26291567/)] Vegetable oil has several other negative effects which I have talked about in another video.
We already discussed vitamin K2 earlier, and touched on how animal foods are generally a pathetic source, but even if they weren't, it's not clear that animal-derived vitamin K2 is even bioavailable. Additionally, vegetable oil consumption is not an entailment of veganism, so I'm not entirely sure why it's being discussed here. Nor is UPF consumption, unless you're dense enough to categorize B12 and D3 supplements as UPFs. At best this is a red herring, at worst this is a non sequitur.
**Claim #42 (**[**31:47**](https://youtu.be/MpxgZGnEF7E?t=1907)**):**
> Vegans and vegetarians tend to rely on soy for protein a lot. The hormone disrupting effects of increased soy consumption is somewhat controversial, but it may explain why a study on almost 8000 boys found boys born to vegetarian mothers had a higher risk for a specific deformity in the genitals called hypospadias. [[120](https://pubmed.ncbi.nlm.nih.gov/10619956/)]
Risk is not exactly what is being assessed in this study. This is a case-control study, which means we're looking at odds ratios. This is the ratio of the odds of the outcome of interest between two groups at varying levels of exposure. Case-control studies are also missing a temporal component, which is often considered critical for making sound causal inferences. With case-control studies, the direction of causality is extremely difficult to ascertain. Additionally, the study did not even measure or assess soy intake.
In this case, the odds ratio for hypospadias from low to high soy exposure was actually non-significant. However, in a similar case-control study from 2013, phytoestrogen consumption was inversely associated with hypospadias incidence. [[121](https://pubmed.ncbi.nlm.nih.gov/23752918/)] At best I think we can say that the literature on soy is pretty mixed, ranging from non-significant increases in the odds of hypospadias to statistically significant decreases in the odds of hypospadias.
**Claim #43 (**[**32:09**](https://youtu.be/MpxgZGnEF7E?t=1929)**):**
> Soy contains the isoflavonoid genistein, which studies show has “detrimental effects on the male reproductive system…” [[122](https://pubmed.ncbi.nlm.nih.gov/35760341/)]
Bruh, this is a meta-analysis of rodent studies with a blurb about how the results may or may not translate to humans.
**Claim #44 (**[**32:17**](https://youtu.be/MpxgZGnEF7E?t=1937)**):**
> Lastly, impossible burger has tried to make their product taste meatier with something called leghemoglobin from the roots of genetically modified soy plants. [[123](https://www.canada.ca/en/health-canada/services/food-nutrition/genetically-modified-foods-other-novel-foods/approved-products/soy-leghemoglobin/document.html)]
>
> GMOscience.org writes that:
>
> A 28-day study commissioned by Impossible Foods in 2017 on soy leghemoglobin found that soy leghemoglobin caused statistically significant changes in weight gain, changes in the blood that can indicate the onset of inflammation or kidney disease, and possible signs of anaemia in the rats.
In isolation, leghemoglobin actually had better bioavailability than iron(II)-sulfate, and when part of a food matrix, here as fortification for corn tortillas, had similar (ie non stat sig different) bioavailability compared to bovine heme iron. [[124](https://pubmed.ncbi.nlm.nih.gov/16478282/)]
As an added fun fact that may blow up the brains of Joseph's audience, leghemoglobin is actually evolutionarily just as old as hemoglobin. See the following figure from Biochemistry 6th edition by Berg, Tymoczko and Styer.
**Claim #45 (**[**32:43**](https://youtu.be/MpxgZGnEF7E?t=1963)**):**
> Further studies did eventually persuade the FDA to designate leghemoglobin as safe, but Impossible Foods admitted that a quarter their new ingredient was composed of 46 “unexpected” additional proteins, none of which were assessed for safety in the dossier. [[125](https://twitter.com/ImpossibleFoods/status/1000397509196505089?s=20)]
These "unexpected additional" proteins are just unknown proteins, which in this context simply means that their biological behaviour is not yet known. If you analyse any food, including beef, there will be many, many such "unknown" proteins. It's not spooky. This characteristic likely quantifies over all foods, and as such we have no good reason to consider this a cause for any concern.
**Claim #46 (**[**33:27**](https://youtu.be/MpxgZGnEF7E?t=2007)**):**
> This is another big issue with trying to replace animal foods. The replacement almost always comes with plenty of other stuff. Kidney beans are a good source of protein need to be soaked and cooked to reduce the lectin content. Some boys in the UK showed up in the hospital with profuse diarrhea and vomiting because they ate 4 kidney beans that were soaked, but not cooked. [[126](https://pubmed.ncbi.nlm.nih.gov/2249712/)]
Okay, Joseph. Either you're not reading your references at all or you're just memeing at this point. The results are relevant to raw beans, which everyone agrees shouldn't be eaten. This isn't revelatory. Soaking your legumes is some level-zero Weston A Price bullshit. They need to be cooked, dude. **COOKED**.
Even without soaking, and instead pressure cooking, the time required to deactivate the lectins was well below the time required to make them edible. [[127](https://www.researchgate.net/publication/229968837_Effect_of_Heat_Processing_on_Hemagglutinin_Activity_in_Red_Kidney_Beans)]
Additionally, in the years between 1976 and 1989, the UK only saw 50 suspected incidents related to un- or under-cooked legumes were registered. Meanwhile, [according to the USDA](https://www.fsis.usda.gov/inspection/inspection-programs/inspection-poultry-products/reducing-salmonella-poultry/salmonella), poor meat preparation can account for approximately 1.35 million salmonella-related infections, 26,500 salmonella-related hospitalizations, and 420 salmonella-related deaths every year just in the United States.
Joseph also tries to address those who react to lectins in cooked kidney beans too. News flash. There are no fucking lectins in cooked kidney beans. [[128](https://pubmed.ncbi.nlm.nih.gov/34829077/)]
**Claim #47 (**[**33:56**](https://youtu.be/MpxgZGnEF7E?t=2036)**):**
> Phytic acid found in beans, seeds, nuts and grains inhibits fat digestion and the absorption of calcium, magnesium, phosphorus and Zinc. How much? Well, this study found about 35% less Zinc is absorbed in a vegetarian diet. [[129](https://pubmed.ncbi.nlm.nih.gov/31095149/)][[130](https://pubmed.ncbi.nlm.nih.gov/16401188/)][[56](https://pubmed.ncbi.nlm.nih.gov/12936958/)] Fiber itself worsens the activity of pancreatic lipase which is important for the absorption of fat soluble vitamins like A, D and K2. [[131](https://pubmed.ncbi.nlm.nih.gov/2819858/)]
Joseph's reference for this claim is the same paper that he cited for his claim about phytate-mediated inhibition of iron absorption. However, straight from the author's conclusions, we can read:
> The iron and zinc from vegetarian diets are generally less bioavailable than from nonvegetarian diets because of reduced meat intake as well as the tendency to consume more phytic acid and other plant-based inhibitors of iron and zinc absorption. However, in Western countries with varied and abundant food supplies, it is not clear that this reduced bioavailability has any functional consequences.
What's worse, Joseph's reference for phytate-mediated inhibition of hepatic lipase activity is an in vitro study. It's not clear why we should care.
**Claim #48 (**[**34:19**](https://youtu.be/MpxgZGnEF7E?t=2059)**):**
> A high intake of goitrogenic foods like cabbage, kale and turnips can interfere with iodine functioning.
Show me the study that actually divulges that any of these sorts of foods have any goitrogenic effects, please. We've tried to look for this effect in foods that are highest in these so-called goitrogens, such as broccoli sprouts, and we so far haven't found any generalizable effect. [[132](https://pubmed.ncbi.nlm.nih.gov/30735751/)] In fact, the number of subjects with subclinical hypothyroidism actually went down in the broccoli sprout group, compared to baseline.
**Claim #49 (**[**34:25**](https://youtu.be/MpxgZGnEF7E?t=2065)**):**
> Food Scientist Dr. Frederic Leroy has written an extensive article on the various examples of why it’s a challenge to acquire enough of certain nutrients just from plants due to inhibiting compounds like these. [[133](https://aleph-2020.blogspot.com/2019/05/animal-source-foods-provide-nutrients.html)] This nutrient challenge is part of the reason why The German Nutrition Society in 2016 and the French-speaking Pediatric HGN Group in 2019 recommend against a vegan diet for adolescents, children or mothers. [[134](https://www.ernaehrungs-umschau.de/english-articles/15-06-2016-vegan-diet/)][[135](https://pubmed.ncbi.nlm.nih.gov/31615715/)]
Well, as long as we're appealing to authorities, we should point out that both the French and German governments recommend limiting meat intake to no more than 500g per week and 600g per week, respectively.
**Claim #50 (**[**34:49**](https://youtu.be/MpxgZGnEF7E?t=2089)**):**
> Several studies have found babies born to vegan mothers to have a lower birth weight than babies of omnivore mothers. [[136](https://pubmed.ncbi.nlm.nih.gov/30909771/)][[137](https://journals.lww.com/ijcm/Abstract/1999/24020/A_STUDY_OF_EFFECT_OF_MATERNAL_NUTRITION_ON.4.aspx)][[138](https://pubmed.ncbi.nlm.nih.gov/32776295/)][[139](https://pubmed.ncbi.nlm.nih.gov/8172120/)][[140](https://pubmed.ncbi.nlm.nih.gov/33232446/)][[141](https://www.nichd.nih.gov/newsroom/news/122120-vegetarian-diets)][[142](https://pubmed.ncbi.nlm.nih.gov/28745335/)][[143](https://sciendo.com/article/10.5604/01.3001.0014.9343)]
> Birth weight can be a predictor of infant health and growth. [[144](https://pubmed.ncbi.nlm.nih.gov/15703531/)][[145](https://pubmed.ncbi.nlm.nih.gov/32928144/)][[146](https://pubmed.ncbi.nlm.nih.gov/26288495/)][[147](https://pubmed.ncbi.nlm.nih.gov/28840655/)] In fact, one study that meticulously analyzed the records of 4,300 adults who were in the Danish Medical Birth Register found that the lower their weight at birth, the shorter they would be as adults. [[148](https://pubmed.ncbi.nlm.nih.gov/10206622/)]
> This study points out that the growth of vegetarian children was adequate, but less than average. [[39](https://pubmed.ncbi.nlm.nih.gov/2771551/)] I wonder how people would react to a doctor saying “your son won’t be as tall as he could be, but don’t worry his height will be adequate.”
Firstly, it's probably not actually birth weights we should be caring about necessarily. It's whether or not the infants are considered small for gestational age. Secondly, Joseph's references don't actually provide very persuasive evidence to support the notion that vegan diets increase the risk of small for gestational age. One particularly strong reason for this is poor B12 supplementation practices, which is a known risk factor among vegans that has not been adequately accounted for.
For instance, Ferrara et al. found that only 15% of the vegan cohort supplemented B12, while only 5% supplemented D3. Similarly, Yisahak et al. conducted a tangential study on vegetarians, but even then no assessment for B12 or D3 supplementation was made.
In addition, the study by R.K. Sharma et al. was done in 1999 before fortification and supplementation standards were established. Although they found that low birth weights were largely explained by the height and weight of the mother and that anemia was a risk factor for small for gestational age. These authors also did not account for B12 supplementation.
Kesary et al. lumped B12, iron, folate, and multivitamins together, and participants were said to be taking supplements if they took supplements more than once per week. However, the odds of small for gestational age between vegans and omnivores was not significant after an adjustment for BMI. Therefore, it is difficult to draw a definitive conclusion about the relationship between "vegan" diets and small for gestational age from this study.
Basically if vegans tend to have lower baseline BMI and tend to gain less weight during pregnancy, normally they will give birth to smaller babies. By definition, since you shifted the distribution curve, more of them will fall bellow the 10th percentile. Any unique effect of vegan diets here are probably with respect to more powerfully resisting weight gain and than typical omnivorous diets.
Finally, two cautionary narrative review articles by Miedziaszczyk et al. and Pawlak et al. highlighted that most of the vegan populations mentioned had either high MMA, low B12 intake or status, or poor supplementation practices. These observations further emphasize the importance of adequate B12 supplementation when considering the risks associated with vegan diets during pregnancy. Here's a quote from one of the authors:
> It should be thus concluded that vegan diets are appropriate for pregnant and lactating women only if these women habitually use reliable B12 sources, preferably oral supplements.
**Claim #51 (**[**38:18**](https://youtu.be/MpxgZGnEF7E?t=2118)**):**
> What is the difference between enough nutrients and the optimal amount of nutrients...cutting out nutrient dense animal foods doesn’t seem like a move in the right direction for health
This just seems like pure speculation. Maybe optimal is not achievable without a supplement on any natural diet. I mean, think about it. What's the argument for omnivorous diets necessarily providing optimal amounts of all nutrients? If there's no argument for that, then it's possible that even the diet that he's recommending is horribly insufficient in some way.
How has Joseph determined that the optimal range for nutrient intakes aren't above what could be obtained from omnivorous diets? Seems like his argument here is begging the question. If it's the case that optimal levels of nutrients are only practical to obtain from supplements, then we'd all benefit— not just vegans.
It's also true that this works in reverse. If Joseph is arguing that we should eat more meat to hit some nebulous "optimal" ranges for all nutrients, what's the argument that this is not true for plant foods? Perhaps eating more meat displaces plant foods and keeps us from achieving an optimal intake of some other plant-derived nutrients as well, notably vitamin C, folate, fibre, potassium, manganese, or polyphenols. Yes, Joseph, I live in the real world where getting ample fibre intake is actually beneficial for the vast majority of people.
So perhaps the optimal intake of many of plant-derived nutrients cannot be achieved if you are eating a significant amount of meat. Since Joseph insists on discussing non-essential, animal-derived nutrients for which the evidence for benefit is paltry at best. There is literally more evidence of benefit for polyphenols than there is for carnitine, anserine, taurine, and perhaps even creatine.
**Claim #52 (**[**36:44**](https://youtu.be/MpxgZGnEF7E?t=2204)**):**
> For 99% of human history we relied on animal foods for nutrients - the an animal food containing diet has a strong track record that spans arguably over 1.7 million years. [[149](https://pubmed.ncbi.nlm.nih.gov/32508752/)][[150](https://bigthink.com/the-past/brain-evolution/)] Various cultures viewed animal foods as important to growth and despite the challenging circumstances they lived in, they were protected from infectious diseases, they didn’t have the modern diseases of civilization, and they enjoyed proper growth in their body, faces and mouths.
There is no source provided for Joseph's claim that "various cultures" do not suffer from the modern diseases of civilization. Joseph characterizes these diseases as "heart disease, cancer, osteoporosis, diabetes, and so on", but there is plenty of evidence against the notion that these diseases are somehow modern.
Cancer in humans is a phenomenon that is over a million and a half years old, for example. [[151](https://carta.anthropogeny.org/libraries/bibliography/earliest-hominin-cancer-17-million-year-old-osteosarcoma-swartkrans-cave)] Heart disease is prevalent in nearly every population we study, whether traditional, ancient, or modern. [[152](https://pubmed.ncbi.nlm.nih.gov/23489753/)] Even the Tsimane have advanced atherosclerosis. [[153](https://pubmed.ncbi.nlm.nih.gov/28320601/)] Even diabetes dates back millennia. [[154](https://pubmed.ncbi.nlm.nih.gov/26788261/)]
**Claim #53 (**[**37:07**](https://youtu.be/MpxgZGnEF7E?t=2227)**):**
> With that in mind, a plant-based diet is an experiment without any meaningful track record. It’s been a couple decades at best that people have been doing vegan diets, yet already many people quit for health reasons. Research is a promising story of progress - maybe one day we’ll learn enough to make sufficient plant-based replacements for animal foods. But it’s probably not happening any time soon.
It seems like the word "experiment" is being used in a strange way here. From what I can gather, Joseph is either trying to convey that there is significant risk entailed by being on a "vegan" diet OR that there is no historical precedent for animal-free diets and that we should apply some precautionary principle OR veganism is being used to test a hypothesis.
Either of these three propositions requires an argument. If "experiment" is just being used as it is commonly used, as something done to test a hypothesis, then it is not clear that veganism is an experiment on that construal. If "experiment" just means that there is a possibility of some undesirable outcome actualizing, then it seems trivially true and misleading to refer to veganism as an experiment. If "experiment" means that there is some demonstrably entailment to a poor outcome, then he would actually need to provide decent evidence for that.
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Back in August of 2021, I invited [Tucker Goodrich](https://twitter.com/TuckerGoodrich) to a debate about the health value of seed oils. Tucker agreed to participate immediately, but after a brief back-and-forth (which resulted in Tucker [contradicting himself](https://twitter.com/The_Nutrivore/status/1428064287059324929?s=20&t=rmYpT72-5Tan31MnU_ptlw)), he eventually [withdrew](https://twitter.com/TuckerGoodrich/status/1428062578668830720?s=20&t=rmYpT72-5Tan31MnU_ptlw) without an explicit justification. Shortly thereafter he wrote a [blog article](https://yelling-stop.blogspot.com/2021/12/thoughts-on-nick-hieberts-comprehensive.html), wherein he paints a caricature of the events that transpired, which included everything from exaggerations to full-throated lies. Despite this, I reinvited him to debate multiple times since the incident, with either no response or outright refusals in reply.
My initial invitation was prompted by my discovery that Tucker was actually just straight up [fabricating evidence](https://twitter.com/The_Nutrivore/status/1489863311155810304?s=20&t=DhYUMrwmqG260Ft7uNHozg) in a debate with a friend of mine, [Alan Flanagan](https://www.alineanutrition.com/about/). Needless to say, Tucker appears to be a particularly dishonest actor and a coward. When he wants to engage with me he does so in the safety of his blog, and critiques my writings and public statements with strawman arguments and red herrings, as well as just attacking very low-hanging fruit. At this point I don't think it's unfair to speculate that he conducts himself in this manner because he knows his arguments would not withstand scrutiny in a debate against me.
Recently I was invited to set the record straight and shed some light on some of Tucker's more misleading claims on [Mark Bell's Power Project](https://www.youtube.com/watch?v=omzCi2CGoxo). Naturally Tucker felt compelled to write [a response](http://yelling-stop.blogspot.com/2022/02/thoughts-on-nick-hiebert-on-mark-bells.html) that was also particularly low-level and ultimately did not provide any stable defeaters for any of my positions. That didn't stop him from writing the article as though my arguments had been thoroughly dispatched, despite his counterarguments not even meaningfully interacting with what I had said to begin with.
At this point I figured that enough was enough. So, I contacted an acquaintance of mine (who through this whole ordeal would become a friend), [Matthew Nagra](https://drmatthewnagra.com). I knew Matt was experienced in empirical debate and didn't hold any whacky heterodox views about seed oils, so I asked him if he'd be interested in debating Tucker. Matt agreed and promptly extended an invitation to Tucker. After Tucker agreed to a debate against Matt on [Simon Hill](https://twitter.com/theproof)'s [podcast](https://theproof.com/podcast/), it was time to get to work. With some help from [Matthew Madore](https://twitter.com/MattMadore576) over at [My Nutrition Science](https://www.mynutritionscience.com/authors-page/), we developed about 200 pages worth of debate-prep, syllogisms, and dialogue trees over approximately six weeks.
As you will see throughout this article, our hard work paid off in the sweetest way possible. Matt was able to tease an absolutely enormous amount of dodges, strawman arguments, and straight up contradictions out of Tucker. It was more than any of us could have hoped for, and it truly reveals just how weak Tucker's arguments really are. The number of self-defeating bullets Tucker tried to bite in order to stay ahead in the debate was exquisite— a true treat. All in all, I'm very pleased with the results. Matt did a truly phenomenal job. Enjoy!
**MATTHEW NAGRA VS TUCKER GOODRICH**
Let's start. Tucker and Matt both agree to the following:
**Debate Rules:**
1) The debate will be open and conversation-style.
2) Both parties will avoid talking over one another.
3) Both parties must answer questions directly.
4) Both parties will make and address one claim at a time.
5) Both parties will refrain from using personal insults.
6) Both parties will provide adequate time for response.
**Matt's Debate Proposition:**
"It is more reasonable to believe that seed oils are beneficial, rather than harmful, for coronary heart disease risk."
**Tucker's Definition of Seed Oils:**
"Oils made from seeds, like canola oil, soybean oil, sunflower oil, etc. Not the fleshy part of the fruit, like olive oil, palm oil, avocado oil, or coconut oil. With the primary focus being high linoleic acid oils."
Now let's get into the actual debate.
**Rule violation (**[**30:20**](https://youtu.be/5nZSV-DyVRM?t=1820)**,** [**30:38**](https://youtu.be/5nZSV-DyVRM?t=1838)**):**
Tucker breaks rule three twice. Matt provides evidence from three independent analyses that shows a concordance rate of 65-67% between nutritional epidemiology and nutritional randomized controlled trials (RCTs). Matt then asks Tucker if nutritional epidemiological evidence is concordant with nutritional RCTs two thirds of the time, which is a yes or no question. Tucker responds by saying its irrelevant due to being a tangent. However, it's not clear exactly how Matt's question is an irrelevant tangent, since it directly interacts with Tucker's opening claim at the beginning of the debate.
**Strawman (**[**32:09**](https://youtu.be/5nZSV-DyVRM?t=1929)**):**
Tucker finally answers "no" in response to Matt's question. When Matt asks why not, Tucker responds by saying "it's just a meta-analysis", which doesn't provide us with any clarity on why he provided the answer that he did. Tucker further elaborates with a strawman of Matt's position, stating that the data provided by Matt doesn't provide us with any information about the likelihood of a high-LA intervention being beneficial. However, this wasn't Matt's point. Matt's point was that Tucker's characterization of nutritional epidemiology on the whole was a red herring and false.
**Rule violation (**[**37:24**](https://youtu.be/5nZSV-DyVRM?t=2239)**):**
Tucker breaks rule three for the third time. Matt shows Tucker the power calculation from MCE, and demonstrates that the trial was actually underpowered. Matt then asks Tucker if the trial had adequate power. Tucker again says that the question is irrelevant, stating that when a trial shows harm, it shouldn't be discounted based on a P-value. This is a truly bizarre answer, as Matt has yet to discount the trial.
**Rule violation (**[**38:50**](https://youtu.be/5nZSV-DyVRM?t=2330)**):**
Tucker breaks rule four. Instead of resolving Matt's point about MCE, Tucker wants to pivot to the LA Veterans Administration Hospital Trial (LAVAT).
**Rule violation (**[**43:20**](https://youtu.be/5nZSV-DyVRM?t=2600)**):**
Tucker breaks rule three for the fourth time. Matt presents a subgroup analysis from MCE that shows that older subjects who maintained the intervention diet for more one year tended to see a benefit when compared to the control diet. Matt asks Tucker if the older subjects in MCE who were consuming the intervention diet for longer saw a benefit compared to the control diet. Tucker rejects the question, saying that Matt is citing a "sub-population" analysis, and that it is superseded by the total outcome. This answer doesn't interact with Matt's question.
**Rule violation (**[**42:56**](https://youtu.be/5nZSV-DyVRM?t=2576)**,** [**43:30**](https://youtu.be/5nZSV-DyVRM?t=2610)**):**
Tucker breaks rule three for the fifth time. Matt rephrases his question, asking Tucker if harm would be more likely if subjects were to maintain the intervention diet for a longer period of time as opposed to a shorter period of time in MCE. Tucker again, dismisses a yes-or-no question as being irrelevant without any clarifying explanation.
**Rule violation (**[**44:06**](https://youtu.be/5nZSV-DyVRM?t=2646)**):**
Tucker breaks rule two. Matt wants to elaborate on why his question is important, but Tucker cuts him off. Matt allows it, but Tucker shouldn't have done it to begin with.
**Rule violation (**[**48:18**](https://youtu.be/5nZSV-DyVRM?t=2898)**):**
Tucker breaks rule one and three. Tucker attempts an explanation for why MCE showed benefit for older subjects over two years. When Matt asks for further clarification, Tucker refuses to provide it. Not only is this directly dodging a question, this behaviour also calls into question whether or not Tucker is actually there for an open, conversation-style debate.
**Rule violation (**[**49:07**](https://youtu.be/5nZSV-DyVRM?t=2947)**):**
Tucker breaks rule four again. Instead of resolving Matt's point about MCE, Tucker wants to pivot to the Oslo Diet-Heart Study (ODHS).
**Strawman (**[**50:34**](https://youtu.be/5nZSV-DyVRM?t=3034)**):**
Tucker offers a strawman of Matt's position, claiming that Matt's conclusions were based on ODHS. In fact, Matt's position was not based on ODHS, and Matt even said that the evidence underpinning his position is virtually the same if ODHS is omitted completely.
**Strawman (**[**51:52**](https://youtu.be/oYsRgsJoZc4?t=3112)**):**
Tucker offers a strawman of Matt's position, claiming that the composition of fats in margarines would need to be known in order to conclude that trans-fats (TFA) were confounding in MCE. This isn't Matt's position. Matt's position was that TFA confounding is likely based on two pieces of evidence. Firstly, the vast majority of margarines during that time period contained TFA. Secondly, there was disagreement between the observed cholesterol changes and the predicted cholesterol changes in MCE. From these data Matt infers that TFA confounding was likely, which is merely a truism that can be soundly inferred a priori. Matt doesn't conclude that TFA confounding did in fact occur. He merely takes the position that is likely.
**Rule violation (**[**55:27**](https://youtu.be/oYsRgsJoZc4?t=3327)**):**
Tucker breaks rule three. Matt asks Tucker if he thinks that a cooking oil with 1% TFA would be equivalent to a cooking oil with 15% TFA, which is a yes or no question. Tucker responds by saying that TFA confounding would have to be a systematic issue across all of the RCTs using Matt's assumptions. However, this doesn't interact with Matt's question.
**Rule violation (**[**1:02:00**](https://youtu.be/oYsRgsJoZc4?t=3720)**):**
Tucker breakers rule three again. Tucker cites a result from the LAVAT that is incongruent with Matt's figures, so Matt asks him what Tucker's figure is representing. After Matt finishes explaining the incongruency, he asks Tucker where he is getting the number from. Instead of answering, Tucker just asks him what his point is.
**Potential contradiction (**[**1:08:00**](https://youtu.be/oYsRgsJoZc4?t=4080)**):**
Tucker concedes that LAVAT showed a slight benefit for vegetable oils compared to animal fats. However, earlier he characterized MCE as showing "harm", but it wasn't qualified as slight. However, LAVAT showed a statistically significant 49% increase in CVD mortality risk in the control group, but MCE showed a non-significant 24% increase in CVD mortality risk in the intervention group. If a non-significant 24% increase in CVD mortality is noteworthy in Tucker's view, why is a statistically significant 49% increase in CVD mortality risk only slight in his view as well?
Without further elaboration, would have to either accept that the increase in CVD mortality in LAVAT is noteworthy, or accept that the CVD mortality increase in MCE is at least just as unnoteworthy as LAVAT, if he wishes to stay consistent. We can syllogize the logical entailments of accepting the CVD mortality risk in MCE as "not slight" like this:
**Definitions:**
C := the trial has a CVD mortality risk that is over 23%
M := the trial has a CVD mortality risk that is not slight
e := MCE
v := LAVAT
**P1)** If the trial has a CVD mortality risk that is over 23%, then the trial has a CVD mortality risk that is not slight.
**(∀x(Cx→Mx)**
**P3)** MCE and LAVAT are trials that have CVD mortality risks that are over 23%.
**(Ce∧Cv)**
**C)** Therefore, MCE and LAVAT are trials that have CVD mortality risks that are not slight.
**(∴Me∧Mv)**
**Rule violation (**[**1:08:22**](https://youtu.be/oYsRgsJoZc4?t=4102)**,** [**1:08:34**](https://youtu.be/oYsRgsJoZc4?t=4114)**):**
Tucker breaks rule three two more times. Matt presented data from LAVAT that divulged that the intervention diet resulted in statistically significant benefits to CVD mortality and all-cause mortality. Matt asked Tucker if he though the data shows that the intervention diet in LAVAT resulted in a benefit to CVD mortality and all-cause mortality, which is again a yes or no question. First, Tucker dismisses the question, saying that LAVAT also saw an increase in cancer. When Matt asks again, Tucker says that he doesn't agree that studies can be "sliced and diced", which doesn't interact with Matt's question.
**Rule violation (**[**1:10:44**](https://youtu.be/oYsRgsJoZc4?t=4244)**,** [**1:14:22**](https://youtu.be/oYsRgsJoZc4?t=4462)**):**
Tucker breaks rule four two more times. Instead of resolving Matt's point about LAVAT, Tucker tries to pivot to talking about the standard American diet (SAD), which is tangential to the claim being discussed at that moment. When asked again, Tucker responds by talking about rates of acute myocardial infarction (AMI) in Africans, which is also tangential to the claim being discussed at that moment.
**Rule violation (**[**1:18:03**](https://youtu.be/QGNNsiINehI?t=4683)**):**
Tucker breaks rule three yet again. Matt attempts an internal critique by asking if Tucker would believe that adding vegetable oils to the SAD would be a benefit, based on the results of LAVAT. Tucker replies by saying that Lee Hooper would conclude that there is little to no benefit. A truly bizarre reply that doesn't interact with Matt's question at all.
**Potential contradiction (**[**1:21:11**](https://youtu.be/QGNNsiINehI?t=4871)**):**
Matt responds to ecological data that Tucker presented earlier, stating that he disagrees with the notion that it can be used to determine independent effects of seed oils. Tucker denies that he is making such a claim, and clarifies that he is speculating off that data. However, earlier in the debate Tucker objected to Matt's speculation regarding TFA confounding in MCE. Why is it OK for Tucker to submit speculation as evidence but not OK for Matt to submit speculation as evidence?
Without further elaboration, it's unclear why Tucker would not be OK with a priori inferences about the potentially confounding effects of TFA in MCE being used in debate, when he also relies on such a priori inferences. Such as when he infers from ecological data that seed oils are likely to be detrimental. We can syllogize the logical entailments of accepting the use of a priori inferences in debate like this:
**Definitions:**
N := speculation counts as evidence
B := speculation can be used in debate
n := a priori inferences about the effects of seed oils from ecological data
m := a priori inferences about TFA in MCE
**P1)** If speculation counts as evidence, then speculation can be used in debate.
**(∀x(Nx→Bx))**
**P4)** A priori inferences about the effects of seed oils from ecological data and a priori inferences about TFA in MCE are speculations that count as evidence.
**(Nn∧Nm)**
**C)** Therefore, a priori inferences about the effects of seed oils from ecological data and a priori inferences about TFA in MCE are speculations can be used in debate.
**(∴Bn∧Bm)**
**Rule violation (**[**1:32:15**](https://youtu.be/QGNNsiINehI?t=5535)**):**
Tucker breaks rule four once more. At this point, both are discussing Lyon Diet-Heart Study (LDHS), and the differential effects of the various dietary modifications that were made in that study, such as the reduction in LA. Matt takes the position that it is unlikely the the 73% reduction in AMI risk seen in LDHS is attributable to LA-reduction due to many other dietary variables changing alongside the reduction in LA. Tucker takes the position that reduction in LA explains the majority of the effect. Instead of resolving Matt's point about LDHS, Tucker wants to pivot to discussing the mechanisms of atherosclerosis.
**Potential contradiction (**[**1:35:45**](https://youtu.be/QGNNsiINehI?t=5745)**):**
Tucker holds the view that alpha-linolenic acid reduces risk, but he also holds the view that risk is mediated solely by LA-specific metabolites. However, this is true of all non-LA fatty acids. If the metabolites that confer harm are LA-specific, then shouldn't all non-LA fatty acids be equally non-atherogenic? He tries to reconcile this by saying that ALA "blocks" the negative effects of LA. Does that mean that ALA is an antioxidant? Does the mean that ALA detoxifies LA-specific metabolites somehow? He offers no further explanation.
**Rule violation (**[**1:47:53**](https://youtu.be/QGNNsiINehI?t=6473)**):**
Tucker breaks both rule two and rule six. In response to an objection from Tucker, Matt wanted to ask a question so that he could have specific clarity on Tucker's position, but Tucker cut Matt off before Matt could ask.
**Potential contradiction (**[**1:39:20**](https://youtu.be/QGNNsiINehI?t=5960)**):**
Matt uses one of Tucker's references to present an internal critique. The reference appears to contradict Tucker's model of CVD by stating that hyperlipidemia is sufficient to explain the development of CVD in all its manifestations. Tucker objects to this, saying that the paper is referring to the "genetic hypothesis" of CVD, which involves CVD risk being conferred via genetically mediated concentrations of LDL. Tucker elaborates by stating that if the hypothesis were true, there wouldn't be observable differences in CVD rates between people with the same genetic background between different environments. This appears to be discounting the possibility that LDL can vary between individuals within a genetically homogenous group. Yet, here he affirms that environmental factors like dietary modification can affect LDL levels.
**Strawman (**[**1:49:00**](https://youtu.be/QGNNsiINehI?t=6540)**):**
Matt claims that oxidation of LDL is virtually inevitable after LDL are irreversibly retained within the subendothelial space. Tucker objects, saying it is not inevitable. Matt asks for clarification, requesting evidence that oxidation can be abolished in the subendothelial space. Tucker informs Matt that the fat composition of the diet can influence LDL oxidation rates. After Matt tells Tucker that this isn't what he's asking about, Tucker insists that this is indeed what Matt is asking about, without any further explanation.
**Potential contradiction (**[**1:53:46**](https://youtu.be/QGNNsiINehI?t=6826)**):**
Tucker correctly states that the LA-derived metabolite, malondialdehyde (MDA), is responsible for oxidative modification of LDL particles. However, he also states that ALA can produce this metabolite as well. If Tucker's position is that MDA-mediated oxidative modification of LDL particles initiates CVD, then why would it matter if an intervention involves both LA and ALA? At **58:32**, Tucker states that the inclusion of ALA confounded LAVAT.
If Tucker wants to remain consistent, he'll have to explain why the atherogenic properties of ALA that are entailed from his stated position don't seem to matter. He seems to singling out LA based on characteristics that he admits are shared by ALA. Without further elaboration, Tucker should have to accept ALA as atherogenic, and the reasoning can be syllogized like this:
**Definitions:**
M := MDA is atherogenic
F := increase heart disease risk
x := MDA-producing fatty acids
n := ALA
**P1)** If MDA is atherogenic, then all MDA-producing fatty acids increase heart disease risk.
**(M→∀x(Fx))**
**P2)** MDA is atherogenic.
**(M)**
**C)** Therefore, ALA is an MDA-producing fatty acid that increases heart disease risk.
**(∴Fn)**
**Direct contradiction (2:18:19):**
Tucker directly contradicts himself when he suggests that corn oil is not a seed oil. At **1:43:50**, he cited two primary interventions that demonstrate that seed oils produce harm, but the sole oil used in those trials was corn oil.
**P1)** If MCE and RCOT used corn oil and MCE and RCOT demonstrate the harms of seed oils, then corn oil is a seed oil.
**(H∧R→O)**
**P2)** MCE and RCOT used corn oil.
**(H)**
**P3)** MCE and RCOT demonstrate the harms of seed oils.
**(R)**
**C)** Therefore, corn oil is a seed oil.
**(∴O)**
**Potential contradiction (**[**2:09:08**](https://youtu.be/QGNNsiINehI?t=7748)**):**
Tucker again concedes that LAVAT showed a "fairly small" benefit of vegetable oils compared to animal fats. Earlier in the debate, Tucker stated that other trials such as MCE as showed "harm". However, LAVAT showed a statistically significant 49% increase in CVD mortality risk in the control group, but MCE showed a non-significant 24% increase in CVD mortality risk in the intervention group. If a non-significant 24% increase in CVD mortality is noteworthy in Tucker's view, why is a statistically significant 49% increase in CVD mortality risk only "fairly small" in Tucker's view as well?
**Rule violation (**[**2:10:08**](https://youtu.be/QGNNsiINehI?t=7808)**,** [**2:10:41**](https://youtu.be/QGNNsiINehI?t=7841)**):**
Tucker breaks rule three another three times. After Tucker implies that the benefits seen in LAVAT are inconsequential, Matt once again presents the findings of LAVAT. Matt asks Tucker if he believes that a 33% reduction to all-cause mortality and a 35% reduction to CVD mortality is "small", which is a yes or no question. Rather than answering, Tucker starts talking about Christopher Ramsden's meta-analysis. When Matt asks again, Tucker continues talking about the Ramsden meta-analysis.
**Rule violation (**[**2:10:52**](https://youtu.be/QGNNsiINehI?t=7852)**):**
Tucker breaks rule one again. Matt attempts to explain what his question for Tucker is, but Tucker mind-reads and tries to tell Matt what he means instead of listening.
**Direct contradiction (**[**2:10:59**](https://youtu.be/QGNNsiINehI?t=7859)**):**
Tucker objects to Matt's use of LAVAT to demonstrate a potential benefit of seed oils, saying that "you can't take one single RCT and prove an effect". However, this is the exact manner in which Tucker relies on LDHS to demonstrate the benefits of LA reduction in the context of high ALA. There is no other study that included such an intervention.
Without additional clarification, Tucker would need to reject his own reliance on LDHS to prove the effect of LA-reduction in the context of an ALA-rich diet. Such an entailment can be syllogized like this:
**P1)** If a single study cannot be used to prove an effect, then one cannot use LDHS to prove the effect of LA-reduction in the context of an ALA-rich diet.
**(P→¬U)**
**P2)** A single study cannot be used to prove an effect.
**(P)**
**C)** Therefore, one cannot use LDHS to prove the effect of LA-reduction in the context of an ALA-rich diet.
**(∴****¬****U)**
**Rule violation (**[**2:13:03**](https://youtu.be/QGNNsiINehI?t=7983)**):**
In an astonishing feat, Tucker breaks rules two, four, five, and six all at the same time. Rather than engaging with Matt's question about the clinical significance of the LAVAT results, Tucker dodges by attacking Matt's intellectual integrity. When Matt attempts to interject, Tucker cuts Matt off, attempting to pivot to discussing meta-analyses despite agreeing to systematically discuss the relevant trials one by one.
**Strawman (**[**2:14:21**](https://youtu.be/QGNNsiINehI?t=8061)**):**
Tucker finishes his rant by suggesting that the LAVAT results don't show that increasing seed oils can "reduce heart disease by 30%", which was not at all what Matt was suggesting. All Matt asked Tucker was whether or not Tucker believed that the effects observed in LAVAT were small.
**Strawman (**[**2:14:33**](https://youtu.be/QGNNsiINehI?t=8073)**):**
Tucker claims that Matt agreed that you cannot "prove" something based on one study, and in fact meta-analysis is required for proof. Matt never committed himself to such a concept for causal inference. This is a truly bizarre move on Tucker's part.
**Rule violation (**[**2:16:32**](https://youtu.be/QGNNsiINehI?t=8192)**):**
Tucker breaks rules two and six again. Now discussing the paper by Hooper et al. (2020), Tucker asks Matt where in the paper can the evidence for his claims be found. Matt attempts to respond, but Tucker cuts Matt off again by asking the exact same question he just asked, but with a slightly more crazed inflection.
**Rule violation (**[**2:19:30**](https://youtu.be/QGNNsiINehI?t=8370)**,** [**2:19:38**](https://youtu.be/QGNNsiINehI?t=8378)**,** [**2:19:45**](https://youtu.be/QGNNsiINehI?t=8385)**):**
Tucker breaks rule three three more times. Tucker criticizes the Hooper (2020) meta-analysis by stating that the analysis found "little to no effect" of reducing saturated fat on CVD mortality. Not only is this tangential, but Matt humours the objection long enough to make the point that events is a much more sensitive endpoint than mortality, and events is where the benefit can be seen. Matt follows up by asking Tucker if he thinks reducing total CVD events is beneficial if all else was held equal, which is a simple yes or no question. Rather than answering, Tucker starts painting a caricature of Matt's question instead. When it is clear that Matt is not getting a straight answer, the moderator interjects and allows the yes-or-no question to be asked again. Again, Tucker dodges.
**Direct contradiction (**[**2:21:19**](https://youtu.be/QGNNsiINehI?t=8479)**):**
Tucker takes the position that silent and non-fatal AMIs are not important outcomes and we need not care about them. Yet, at [**1:16:22**](https://youtu.be/QGNNsiINehI?t=4582), Tucker makes it clear that silent and non-fatal AMIs are important and that we should care about them.
This one is pretty straight forward. Either silent and non-fatal AMIs are important and we should care about them, or they are not important and we shouldn't care about them. If Tucker wishes to remain consistent while also preserving his own arguments, we'd need to accept that silent and non-fatal AMIs are important, and that we should care about them. This entailment can by syllogized like this:
**P1)** If silent and non-fatal AMIs are important, then we should care about silent and non-fatal AMIs.
**(N→W)**
**P2)** Silent and non-fatal AMIs are important
**(N)**
**C)** Therefore, we should care about silent and non-fatal AMIs.
**(∴W)**
**Rule violation (**[**2:25:20**](https://youtu.be/QGNNsiINehI?t=8720)**):**
Tucker breaks rule four for the seventh time. After agreeing to discuss the results of Hooper (2020), Tucker suddenly attempts to steer the debate toward some sort of meta-level discussion about seed oil consumption in the general population.
**Rule violation (**[**2:30:31**](https://youtu.be/QGNNsiINehI?t=9031)**):**
Tucker breaks both rules four and six. The moderator poses a question to both Matt and Tucker, and gets a satisfactory answer from both Matt and Tucker. However, rather than returning the floor to the moderator or continuing with the debate, Tucker takes the opportunity to address points that Matt hasn't even made yet in the debate, and doesn't give Matt any amount of time to respond.
**Rule violation (**[**2:37:06**](https://youtu.be/QGNNsiINehI?t=9426)**):**
Tucker breaks rules two and four again. The moderator recognizes that Tucker's incoherent flow-of-consciousness monologue has been going on for nearly ten minutes, and the moderator tries to interject. Tucker cuts the moderator off and proceeds to ramble about vitamin E for another minute.
**Rule violation (**[**2:38:42**](https://youtu.be/QGNNsiINehI?t=9522)**):**
Tucker can't help but break rule four again. Tucker interjects, before Matt can even finish a single sentence, in order to tell Matt that ecological studies are the worst form of epidemiology. At this point it is fair to say that Tucker is breaking rule one as well. It's clear that Tucker is no longer here for an "open, conversation-style" debate.
**Direct contradiction (**[**2:38:50**](https://youtu.be/QGNNsiINehI?t=9530)**):**
Tucker takes the position that ecological studies are of critical importance, superseding all other forms of epidemiology. Yet, only moments earlier, Tucker took the position that ecological studies are the worst form of epidemiological evidence.
Again, we have another relatively simple inconsistency to address. In order for Tucker to make his case against seed oils, he systematically rejected all nutritional epidemiology except for ecological studies. Yet, claiming that ecological studies are the worst form of epidemiology entails a contradiction, as it means that Tucker is simultaneously holding the view that it is both the best and the worst form of epidemiology at the same time. If Tucker wished to resolve the inconsistency, he'd probably have to acknowledge that ecological studies are not the worst form of epidemiology. This can be syllogized like this:
**P1)** If ecological studies are the best form of nutritional epidemiology, then ecological studies are not the worst form of nutritional epidemiology.
**(B→¬W)**
**P2)** Ecological studies are the best form of nutritional epidemiology
**(B)**
**C)** Therefore, ecological studies are not the worst form of nutritional epidemiology.
**(∴¬W)**
**Direct contradiction (**[**2:42:37**](https://youtu.be/QGNNsiINehI?t=9757)**):**
Tucker makes the claim that we can't know whether or not the margarine used in Sydney Diet-Heart Study (SDHS) contained TFA. Moments later, at [**2:44:23**](https://youtu.be/QGNNsiINehI?t=9863) he suggests that it is valid to argue that we absolutely can know the margarine in SDHS did not contain TFA.
If Tucker maintains that it cannot be known whether or not TFA was confounding in SDHS, then he cannot posit that it can be known one way or the other. Either position that Tucker took could work for his argument on this subject, but they're just not compatible with each other, and that can be illustrated like this:
**P1)** If it cannot be known whether TFA was confounding in SDHS, then it is not reasonable to posit that we absolutely know that TFA wasn't confounding in SDHS.
**(¬T→¬S)**
**P2)** It cannot be known whether TFA was confounding in SDHS.
**(¬T)**
**C)** Therefore, it is not reasonable to posit that we absolutely know that TFA wasn't confounding in SDHS.
**(∴¬S)**
**Rule violation (**[**2:57:59**](https://youtu.be/QGNNsiINehI?t=10679)**,** [**2:58:53**](https://youtu.be/QGNNsiINehI?t=10733)**):**
Tucker breaks rule three two more times. While discussing a paper that models substitutions of olive oil for various other fats, Matt asks Tucker if he has any problems with the paper. Rather than answering, Tucker starts discussing issues he has with another paper published by the same group investigating dairy fat. Matt attempts to interject, but Tucker continues to discuss previous research on potatoes that was also published by this group.
**Rule violation (**[**2:59:44**](https://youtu.be/QGNNsiINehI?t=10784)**):**
Tucker breaks rules two, three, and four again. Matt once again asks Tucker if he has any issues with the olive oil substitution analysis. Rather than answering, Tucker cuts Matt off before he can finish asking his question, and Tucker starts asking why Matt included the paper in his references.
**Rule violation (**[**3:00:44**](https://youtu.be/QGNNsiINehI?t=10844)**):**
Tucker once again breaks rule three. Matt asks his yes-or-no question yet again, to which Tucker responds by stating that the mechanisms favour his position. This is just another dodge.
**Rule violation (**[**3:00:53**](https://youtu.be/QGNNsiINehI?t=10853)**,** [**3:02:18**](https://youtu.be/QGNNsiINehI?t=10938)**):**
Tucker breaks rule three again, despite it now being enforced by the moderator. The moderator notices that Matt is not getting an answer to his question, and the moderator steps and reminds Tucker of the question being asked. Rather than answering the question, Tucker continues to discuss mechanisms. The moderator again notices that this doesn't answer Matt's question, and implores Tucker to answer. Again, Tucker dodges the question and starts talking about the paper itself, rather than addressing Matt's question about Tucker's interpretation of the paper.
**Rule violation (**[**3:06:00**](https://youtu.be/QGNNsiINehI?t=11160)**):**
Tucker breaks rules one and six again. Not even one minute after Tucker grants Matt the floor to make a point about mechanistic data, Tucker interrupts Matt on the basis that Matt's point isn't relevant. Though, only moments before, the moderator gave Matt the floor to complete his point. It is clear that Tucker has no respect for the moderator's wishes, nor the debate parameters.
**Rule violation (**[**3:06:52**](https://youtu.be/QGNNsiINehI?t=11212)**):**
Tucker breaks rules one and six again. For the second time, Tucker interrupts Matt when he's been given the floor by the moderator to complete his point.
**Rule violation (**[**3:13:34**](https://youtu.be/QGNNsiINehI?t=11614)**):**
Tucker breaks rules two again. Rather than letting Matt complete his point about the olive oil substitution analysis, Tucker interrupts him.
**Direct contradiction (**[**3:15:10**](https://youtu.be/QGNNsiINehI?t=11710)**):**
Tucker concedes that margarine and mayonnaise are not the same thing as isolated vegetable oils. However, at [**3:14:30**](https://youtu.be/QGNNsiINehI?t=11670), Tucker rejects that there are differences between margarine, mayonnaise, and isolated vegetable oils. Another layer of hilarity would be to point out that if Tucker maintains that mayonnaise is the same as an isolated seed oil, he'd be holding the position that corn oil is not a seed oil, but mayonnaise is.
**Definitions:**
S := seed oils are the topic of debate
T := non-seed oil topics are not the topic of debate
m := mayonnaise and margarine
**P1)** If seed oils are the topic of debate, then non-seed oil topics are not the topic of debate.
**(S→(∀x(Tx))**
**P2)** Seed oils are the topic of debate.
**(S)**
**C)** Therefore, mayonnaise and margarine are non-seed oil topics that are not the topic of debate.
**(∴Tm)**
This is where the debate portion of the episode ends, with Matt and Tucker both giving their closing statements. Altogether, Tucker violated the rules at least 50 times and committed at least 18 fallacies, and that's not counting the various hilarious empirical and epistemic claims that Tucker made. For anyone interested in reading more about Tucker's errors, Matt published a comprehensive rebuttal to his personal blog, which can be found on [Matt's blog](https://drmatthewnagra.com/seed-oil-debate-with-tucker-goodrich/). From what I could tell, Matt did not really break the rules at all, except for perhaps a few minor instances when he attempted to interject when Tucker was rambling. Other than that, he conducted himself according to the rules.
Whether you're skeptical, supportive, or unsure of Tucker's work, I hope that this debate, as well as the breakdown contained within this article, gives you a decent perspective on just how bad his arguments actually are. I'm truly failing to imagine any good reasons for why someone with a stable position, which is truly robust to scrutiny, should struggle this hard to stay consistent in a debate. Tucker's performance was truly terrible, and should be eye-opening to anyone who thought that he might have even a scrap of credibility within this domain.
Thanks for reading! If you enjoy my writing and want more content like this, consider pledging to my [Patreon](https://www.patreon.com/thenutrivore)!

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Many Paleo diet advocates claim that hunter-gatherer diets optimally promote the long-term health of human beings. There are typically two primary justifications for this claim— firstly, the fact that hunter-gatherer populations typically appear to be robustly healthy, and secondly, the fact that humans evolved eating these types of diets. While these are technically statements of fact, I find myself forced to take a page out of the Paleo-dieter's playbook, as I remind them that correlation doesn't equal causation. So, let's dig into why their reasoning is flawed.
Firstly, let me hit you with a thought experiment for a moment. Do you think that the elderly people within a given population would appear either more healthy or less healthy if that population _never_ had access to modern medical technology? Think about this for a moment. You may understandably intuit that their health would probably be worse, correct? But that probably isn't what would happen. They would probably appear healthier, and I'll explain why.
If a population never had access to modern medical technology, one of the things you couldn't reliably do is save sick or injured children. No matter what culture you observe, a sizable proportion of children will develop infectious illnesses. These illnesses, like bacterial or viral infections, are generally mundane by modern standards. However, without modern medicine many children who developed these types of illnesses would likely not survive them.
Those who are more prone to illness likely do not have the same chances of survival as those who are less prone to illness. As such, why wouldn't the elderly in this hypothetical population present with more robust health as a result? Without medical intervention, the environment is essentially selecting for the fittest possible individuals in our hypothetical population. This would likely generate the appearance of more robust health in the elderly. Consider this carefully for a moment. If you weed out all of the weaker people, of course the remaining population is going to appear stronger.
This presents a significant problem for Paleo diet advocates who choose to cite the robust health of hunter-gatherer populations as a justification for the Paleo diet, or as a justification for recommending the diet to others. Most Paleo-dieters do seem to be aware of the environmental adversity faced by hunter-gatherer populations. But they often don't seem to appreciate how this also produces significant challenges for their narrative.
For example, if you remind a Paleo-dieter that hunter-gatherers typically had an average life expectancy of around 30 years, they will often immediately retort by stating that those estimates are confounded by infant and child mortality. But therein lies the problem— they can't have it both ways. A Paleo diet advocate cannot use that argument without tacitly admitting that infant and child mortality is typically enormously high among hunter-gatherer populations. Which it most certainly is [[1]](https://www.sciencedirect.com/science/article/abs/pii/S1090513812001237).
Approximately 26.8% of infants and 48.8% of prepubescent children die in hunter-gatherer populations. With such a high proportion of children dying, how could it be the case that the apparent health of elderly hunter-gatherers is **not** coloured by this? Remember, hunter-gatherer populations likely appear healthier because the least resilient members of those populations are already dead. Paleo diet advocates cannot admit that hunter-gatherer populations had high rates of infant and child mortality without also admitting that the resulting population is a heavily biased sample.
This type of confounding is known as survivorship bias. Basically, survivorship bias is a type of selection bias that can occur when those who did not survive a selection event or process are overlooked in favour of those who did survive. For example, let's say we were trying to construct better body armour for soldiers to wear in combat. Perhaps we might conduct a study of the soldiers who returned from battle. We could collect bullet wound distribution pattern data to help ascertain where soldiers were most likely to get shot.
However, as we see in the graphic above, this sort of analysis would exclude all those who were shot and did **not** survive. It would also overlook the sorts of bullet wound distribution patterns that tended to lead to death, which would actually have given us a significantly clearer picture of how we might construct better body armour.
Likewise, when Paleo diet advocates claim that we should eat like hunter-gatherers because hunter-gatherers are robustly healthy, they're not appreciating how survivorship bias is confounding their appraisal of hunter-gatherer health. They are essentially overlooking the other fifty percent of the hunter-gatherer population that didn't survive.
For this reason, it is dubious to use the apparent good health of hunter-gatherers as the basis for the assumption that their diets are appropriate for modern humans. Until Paleo diet advocates can figure out a way to explain why survivorship bias would not be confounding in an evaluation of hunter-gatherer health, they cannot rely on the apparent good health of hunter-gatherer populations to determine the applicability of hunter-gatherer diets to modern humans. In reality, the degree to which hunter-gatherer diets are appropriate for modern humans remains unclear.
But this isn't the only erroneous argument that Paleo-dieters will use to justify their claims. Often times Paleo diet advocates will also suggest that since we evolved eating certain foods, it is absurd to believe that any of the foods that we evolved eating could pose a long-term health risk to the average person. This reasoning has been used to dismiss robust and well-studied diet-disease relationships, such as saturated fat and cardiovascular disease, red meat and cancer, or even sodium and hypertension [[2]](https://pubmed.ncbi.nlm.nih.gov/32428300/)[[3]](https://pubmed.ncbi.nlm.nih.gov/28487287/)[[4]](https://pubmed.ncbi.nlm.nih.gov/27216139/)[[5]](https://pubmed.ncbi.nlm.nih.gov/28655835/).
Right off the bat it is quite easy to identify that this is a blatant appeal to nature fallacy, and can be outright dismissed on that basis alone. However, it is important to describe precisely why this line of reasoning fails. What we really want to know is whether or not foods are necessarily beneficial (or neutral) for long-term health merely because we evolved eating them.
To explore this question, let's first briefly consider how Darwinian natural selection works. Essentially, it is the process by which random gene mutations are selected for by different environmental challenges. Some mutations are better at dealing with certain environmental challenges than other mutations. As a result, these more adaptive mutations increase an organism's chances of producing offspring. These organisms subsequently pass on these adaptive mutations to their offspring as well.
In this image we see that black mice are less likely to get eaten by the bird than tan mice. For this reason, the random mutations that produces black mice rather than tan mice ends up being naturally selected for by the environment. However, environmental challenges like getting eaten aren't quite the same as environmental challenges that affect the long-term health of an organism.
Getting eaten when you're young is an acute event. Developing a life-threatening chronic disease in old-age, as a result of a life-long environmental exposure (like a food or nutrient), is a long, protracted event. It is unlikely that selection pressure applies to these two events symmetrically, because adaptations occur as a function of successful reproduction. As a result, the probability that _deleterious_ traits will be successfully selected against likely diminishes with age.
So, the question ends up being: how long after reproductive age does natural selection still robustly apply to human beings? Surely selection pressure doesn't end at reproductive age, because human children need human adults to raise them and care for them. But does selective pressure exist to a meaningful degree for those in the age ranges that typically associate with life-threatening chronic disease? Some scholars have attempted to estimate the force of natural selection as a function of age [[6]](https://pubmed.ncbi.nlm.nih.gov/30124168/).
Applying the above graph to human beings, our best estimations suggest that the forces of natural selection rapidly wane down to nil shortly after sexual maturity, which would be approximately 16 to 17 years of age. Around the ages of 30 to 40 is when humans likely enter the "selection shadow", which is the zone wherein natural selection no longer robustly applies.
It seems highly unlikely that the fate of a population could ever hinge on the fitness of middle-aged people who are past their prime. For fun, let's estimate the age range wherein peak human performance is likely to occur. Perhaps we could look at the average age range of Olympic athletes [[7]](https://venngage.com/blog/olympics/).
The average age range of Olympic athletes is between ~22.5 and ~25.5, which is well before the age range seen within the selection shadow. Which honestly makes sense if you think about it. As you age it becomes less likely that natural selection will select against deleterious traits, like losing athletic performance. Once inside the selection shadow, there is likely insufficient selective pressure to extend peak physical performance into higher and higher age ranges.
The selection shadow may actually be observable in some existing traditional populations as well, such as the Tsimané people of Bolivia. While they are technically hunter/forager-horticulturalists and not strictly hunter-gatherers, they are one of the only traditional populations for which we have decent data regarding the progression of chronic disease.
Using a measurement of atherosclerotic cardiovascular disease (ASCVD) progression known as coronary artery calcification (CAC) scoring, researchers were able to quantify the prevalence of ASCVD by age group among the Tsimané [[8]](https://www.thelancet.com/journals/lancet/article/PIIS0140-6736(17)30752-3/fulltext).
It should also be noted that CAC scores are indicative of advanced ASCVD [[9]](https://pubmed.ncbi.nlm.nih.gov/24530667/). The exclusive use of CAC scoring in this study of the Tsimané leaves us with many interpretive challenges. For example, if CAC scores are representative of advanced ASCVD (so called "hard plaques"), what proportion of less advanced ASCVD (so-called "soft plaque") might have been overlooked? It is difficult to say for sure. But the bottom line is that the Tsimané experience increases in chronic disease at approximately the same time as modern populations— well inside the selection shadow.
Granted, the prevalence of chronic disease in the Tsimané is overall lower than that of Western cultures. But, this could be expected given the fact that their diets and lifestyles are likely preferable to that of Western cultures as well. Not to mention the possible confounding due to survivorship bias, to which they are also not immune [[10]](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3502712/). The Tsimané have infant mortality rates that are many fold higher than in Western cultures. This means that the Tsimané are vulnerable to the same type of confounding via survivorship bias that we discussed earlier, thus adding more layers of interpretive challenges.
The methods used to determine the age-ranges of the Tsimané were also questionable, and relied mostly on anecdote and personal judgement rather than objective measurements.
_“Birth years were assigned based on a combination of methods including using known ages from written records, relative age lists, dated events, photo comparisons of people with known ages, and cross-validation of information from independent interviews of kin.”_
When compared to more objective measures of age, the methods described above would appear to overestimate ages as the age of the subjects increases [[11]](https://pubmed.ncbi.nlm.nih.gov/27511193/). Below the age of 40, estimates appear to be rather accurate. However, the age estimations used by Kaplan et al. (2017) would seem to overestimate ages by approximately 15 years above the age of 60. After adjusting for this, it is unlikely that CAC prevalence among the Tsimané differs significantly from Western populations. In fact, it might actually be higher.
It is also imperative to mention that foods to which we are adapted might actually be more likely to be harmful for us as we age. This is because of a concept in evolutionary biology called antagonistic pleiotropy, which is the most widely accepted explanation for the evolutionary origin of aging [[12]](https://pubmed.ncbi.nlm.nih.gov/31870250/)[[13]](https://pubmed.ncbi.nlm.nih.gov/30524730/). The theory of antagonistic pleiotropy essentially posits some genetic adaptations can trade long-term health for short-term reproductive success. However, it can be inferred that most genetic adaptations are antagonistically pleiotropic.
Essentially, human DNA tends to degrade over time when it doesn't rightfully need to, as evidenced by the existence of biologically immortal organisms. Human DNA repair is also regulated and gene-specific. Given these facts, the interaction between gene degradation and gene repair is likely to be adaptive. This assigns every gene in our DNA that tends to degrade more with time a single antagonistically pleiotropic trait. Since most DNA in the human genome degrades over time, we can infer that over 50% of genes are antagonistically pleiotropic.
Since adaptations to foods are no more or less genetic than any other adaptations, we can infer that most adaptations to food are also likely to be antagonistic pleiotropic as well. From here we just infer that antagonistic pleiotropy applies more to ancestral foods than it does to novel foods. Which would suggest that the foods to which we are most strongly adapted would tend to be most antagonistically pleiotropic. This increases the likelihood that ancestral foods trade long-term fitness for short-term reproductive success.
For example, perhaps adaptations to sodium and saturated fat consumption, like regulated changes in blood pressure or lipoprotein secretion from the liver, may help to carry people to reproductive age without incident. However, those adaptations might actually increase the risk of poorer health later in life if those dietary exposures persist too long. This is why we cannot assume that natural diets are actually appropriate for maintaining the long-term health of modern humans. These adaptations to diet are likely to be antagonistic pleiotropic.
Without scientific evidence to help inform our attitudes toward the relative health value of novel foods, the health value of those foods remains is a black box. Due to the principle of indifference, we have no particular reason to suspect that truly novel foods will be either beneficial or detrimental. However, if it can be demonstrated that both an ancestral food and a novel food have the same thriving potential during the reproductive years, we can actually infer that the novel food is to be favoured.
Novel foods do not belong to the domain of foods that have the potential to be antagonistic pleiotropic, since we did not evolve consuming them. Conversely, the ancestral food in our scenario is likely to be antagonistically pleiotropic. Thus, the novel food is to be favoured over the ancestral food in this case. This concept can be illustrated clearly with a couple of simple tables.
To summarize, we can infer that ancestral foods are likely to have both positive short-term health value, as well as negative long-term health value. However, in the absence of empirical data, our doxastic attitude toward the health value of novel foods should be one of agnosticism. When the thriving potential of novel foods and ancestral foods show non-inferiority, we infer that the novel foods is less likely to be detrimental for long-term health. Altogether, the argument can be summarized like this:
**Definitions:**
**A** := a human trait (x) is antagonistically pleiotropic
**E** := the human trait (x) is an evolutionary adaptation
**N** := the human trait (x) mediates more than one downstream effect, one of which is negative in the post-reproductive window of the carrier
**D** := human genes succumb to degradation
**M** := human genes must be assumed to be antagonistically pleiotropic
**R** := humans have more genetic adaptations to ancestral foods than novel foods
**C** := antagonistic pleiotropy applies more to ancestral foods than it does to novel foods
**V** := there is a novel food that has non-inferior short-term health value compared to a given ancestral foods
**U** := there is a novel food that is likely to be superior to such an ancestral food in the long-term
**O** := there are unnatural diets that are preferable to ancestral diets.
**x** := human genes
**y** := trait of a human gene
**i** := the interaction between degradation and repair
**P1)** A human trait is antagonistically pleiotropic if and only if the human trait is an evolutionary adaptation and the human trait mediates more than one downstream effect, one of which is negative in the post-reproductive window of the carrier.
**(∀x(Ax↔(Ex∧Nx)))**
**P2)** The interaction between gene degradation and gene repair is an evolutionary adaptation.
**(Ei)**
**P3)** The interaction between gene degradation and gene repair mediates more than one downstream effect, one of which is negative in the post-reproductive window of the carrier.
**(Ni)**
**P4)** If the interaction between gene degradation and gene repair is antagonistically pleiotropic and all human genes succumb to degradation, then all human genes must be assumed to be antagonistically pleiotropic.
**(Ai∧D→M)**
**P5)** All human genes succumb to degradation.
**(D)**
**P6)** If all human genes must be assumed to be antagonistically pleiotropic and humans have more genetic adaptations to ancestral foods than novel foods, then antagonistic pleiotropy applies more to ancestral foods than it does to novel foods.
**(M∧R→C)**
**P7)** Humans have more genetic adaptations to ancestral foods than novel foods.
**(R)**
**P8)** If antagonistic pleiotropy applies more to ancestral foods than it does to novel foods and there is a novel food that has non-inferior short-term health value compared to a given ancestral food, then there is a novel food that is likely to be superior to such an ancestral food in the long-term.
**(C∧V→U)**
**P9)** There is a novel food that has non-inferior short-term health value compared to a given ancestral food.
**(V)**
**P10)** If there is a novel food that is likely superior to such an ancestral food in the long-term, then there are some unnatural diets that are superior to some ancestral diets.
**(U→O)**
**C)** Therefore, there are some unnatural diets that are superior to some ancestral diets.
**(∴O)**
Essentially, once you equalize advantages across a given novel food and a given ancestral food, the inherent disadvantages of antagonistic pleiotropy would leave us favouring the novel food over the ancestral food for long-term health. From here we can infer a priori that a diet that maximizes benefits and minimizes risks for the most amount of people is likely to be a diet that is on some level unnatural or non-ancestral. It is also important to discuss what this position is **not** arguing. It is **not** being argued that every novel food is going to be superior to every ancestral food, and it is **not** being argued that all ancestral foods are bad.
As an aside, one might point out that while ancestral foods like meat seem to increase the risk of many diseases, while other ancestral foods like fruit seem to decrease the risk of many diseases. So what gives? My arguments apply equally to fruit, and adaptations of fruit are also likely to be antagonistically pleiotropic. However, it is likely the case that the antagonistically pleiotropic pathways that are influenced by foods like fruit are less impactful than those influenced by foods like meat.
Diet is about substitutions. Replacing meat with fruit lowers risk, but that doesn't mean that fruit is without long-term harms or risks as well. Bearing this in mind, I posit that if we truly want to maximize the thriving potential of food, we must engineer our own food. Assuming that no diet of natural foods will actually lower risk to zero, if we wanted to improve the health value of food even more, how would we accomplish this without artificially manipulating those foods? In fact, we have evidence that the health value of natural foods can be improved, with examples like Golden rice.
**P1)** If the health value of natural foods can be improved via artificial manipulation, then there are unnatural foods that are preferable to some natural foods.
**(V→M)**
**P2)** The health value of natural foods can be improved via artificial manipulation.
**(V)**
**C)** Therefore, there are some unnatural foods that are preferable to some natural foods.
**(∴M)**
Lastly, it has also been suggested by some Paleo diet advocates that certain hunter-gatherer migrant studies provide us with a justification for why hunter-gatherer diets are appropriate for modern humans. This is due to the fact that these studies demonstrate that when certain hunter-gatherer populations transition from their traditional diets to more Westernized diets, they experience increases in chronic disease risk [[14]](https://pubmed.ncbi.nlm.nih.gov/6937778/)[[15]](https://pubmed.ncbi.nlm.nih.gov/7462380/). However, this is ultimately irrelevant to my point.
The fact that Western diets increase disease risk relative to certain hunter-gatherer diets does not actually lend any credibility to the notion that modern humans can achieve robust health that is equal to that of hunter-gatherers merely by emulating their diets. Perhaps the Western diet is so bad that it would negatively impact the health of any human population who ate it over the long-term. But, it could also be the case that hunter-gatherer diets are still inappropriate for modern humans in many ways— ways that may not be obvious for the reasons I've discussed throughout this article. These are not incompatible concepts.
The most I would have to grant is that a hunter-gatherer diet is likely an improvement over a Western diet. But that is a far cry from ascertaining that a hunter-gatherer diet is optimal for the long-term health of modern humans. This is just a gross overextrapolation from altogether irrelevant data.
The last inference is the icing on the cake, and a bit more convoluted, but it is necessary to argue it to an ancestral diet advocate. This is next argument cuts to the core of their epistemology regarding ancestral diets and health. All we need to do is prime the ancestral diet advocate for the inference by asking them if they identify as "**F**" (as defined below). If they do, then we proceed. If they don't, then their motivations for advocating for ancestral diets diets isn't clear at all.
**Definitions:**
**A** **:**= F(x) would be acting against their values to not be in favour of consuming N(y).
**F(x)** := someone who favours consuming ancestral foods to the exclusion of novel foods because they value reducing disease risk.
**N(y)** := a novel food that reduces disease risk when replacing an ancestral food.
**P1)** If there exists someone who favours consuming ancestral foods to the exclusion of novel foods because they value reducing disease risk, and there exists a novel food that reduces disease risk when replacing an ancestral food, then that person would be acting against their values to not be in favour of consuming that novel food.
**∃xF(x)∧∃yN(y)→∀x∀y(Axy)**
**P2)** There exists someone who favours consuming ancestral foods to the exclusion of novel foods because they value reducing disease risk.
**(∃xF(x))**
**P3)** There exists a novel food that reduces disease risk when replacing an ancestral food.
**(∃yN(y))**
**C)** Therefore, that person would be acting against their values to not be in favour of consuming that novel food.
**(∴∀x∀y(Axy))**
Essentially, if our interlocutor identifies as "**F**", then all we need to do is demonstrate to them that "**N**" exists, and we're essentially home free. If they accept that "**N**" exists and they also identify as "**F**", then they should be in favour of substituting such a novel food for such an ancestral food. If they don't, then they have a contradiction. This is where the ancestral diet advocate could face quite a dilemma.
However, there is a way around this for them, but it's absurd. They can simply reject the evidence for "**N**" existing. Which would be a hilarious move for them to make, but they can make it if they want. However, implicit in this move is the rejection of all evidence that supports "**N**" existing, regardless of the quality.
For example, if they maintain that animal fat consumption is more supportive of health than vegetable fat consumption, they'd need to reject the multiple meta-analyses and meta-regression analyses of randomized controlled trials on the subject, as well as the consistency of effect in seen in high internal validity epidemiology. The implications of taking such a position are hilarious, because they could very easily have to also reject many other diet/lifestyle-disease relationships that they likely take for granted on much weaker evidence. Such as exercise and alcohol consumption affecting cardiovascular disease risk.
It is likely that the vaunted "optimal human diet", which is to say a diet that maximizes long-term health for the greatest number of people, has actually yet to be discovered. Ultimately, to answer the question of what foods are healthy, we need science. We need robust outcome data on modern human beings, not speculation and appeal to nature fallacies. We need this science to teach us how to eat.
**UPDATE:**
Chris Masterjohn has apparently written a [lengthy response](https://chrismasterjohnphd.substack.com/p/ancestral-health-vs-antagonistic) to my position on antagonistic pleiotropy and how it relates to the long-term health value of ancestral foods. Many have asked me to rebut the article, but it's not clear to me why I should. He's not interacting with the argument at all. Let me give you an example to help illustrate my feelings in this matter. If I give someone an argument, and their response is to turn around and scream at a wall, should I feel any sort of drive to "rebut" the screaming? I don't think so.
Constructing a lengthy reply to Masterjohn's article would only serve to give readers the impression that he actually said anything of substance against my position, which he hasn't. When someone tells me that they disagree with an argument that I have presented, I take this to mean one of two things. Either they have an argument of their own that forms a conclusion that is the negation of at least one of my premises, or they give at least one of my premises such low credence that they just deny that it's true. Masterjohn didn't do either in his article.
Masterjohn just spends the article giving low credence to concepts that aren't even entailed from the argument itself, so why should I care? It's doubly hilarious to expect me to rebut his article when he actually signed off on the entailments of my position at least twice in our [debate](https://chrismasterjohnphd.substack.com/p/the-ancestral-health-debate) when he was actually interacting with the argument itself and not going off on tangents. Once at [58:26](https://youtu.be/n1I5xgvERbo?t=3506) and again at [1:39:16](https://youtu.be/n1I5xgvERbo?t=5956). Not sure what more there is to comment on here.
Thank you for reading! If you like what you've read and want help support my content, consider pledging to my [Patreon](https://www.patreon.com/thenutrivore). Every little bit helps! I hope you found the content interesting!
**References:**
[1] Anthony A. Volka and Jeremy A. Atkinson. Infant and child death in the human environment of evolutionary adaptation. Evolution and Human Behavior. Volume 34, Issue 3, May 2013, Pages 182-192. [https://www.sciencedirect.com/science/article/abs/pii/S1090513812001237](https://www.sciencedirect.com/science/article/abs/pii/S1090513812001237)
[2] Lee Hooper, et al. Reduction in saturated fat intake for cardiovascular disease. Cochrane Database Syst Rev. 2020 May. [https://pubmed.ncbi.nlm.nih.gov/32428300/](https://pubmed.ncbi.nlm.nih.gov/32428300/)
[3] Arash Etemadi, et al. Mortality from different causes associated with meat, heme iron, nitrates, and nitrites in the NIH-AARP Diet and Health Study: population based cohort study. BMJ. 2017 May 9. [https://pubmed.ncbi.nlm.nih.gov/28487287/](https://pubmed.ncbi.nlm.nih.gov/28487287/)
[4] Andrew Mente, et al. Associations of urinary sodium excretion with cardiovascular events in individuals with and without hypertension: a pooled analysis of data from four studies. Lancet. 2016 Jul 30. [https://pubmed.ncbi.nlm.nih.gov/27216139/](https://pubmed.ncbi.nlm.nih.gov/27216139/)
[5] Rik H G Olde Engberink, et al. Use of a Single Baseline Versus Multiyear 24-Hour Urine Collection for Estimation of Long-Term Sodium Intake and Associated Cardiovascular and Renal Risk. Circulation. 2017 Sep 5. [https://pubmed.ncbi.nlm.nih.gov/28655835/](https://pubmed.ncbi.nlm.nih.gov/28655835/)
[6] Thomas Flatt and Linda Partridge. Horizons in the evolution of aging. BMC Biol. 2018 Aug 20.
[https://pubmed.ncbi.nlm.nih.gov/30124168/](https://pubmed.ncbi.nlm.nih.gov/30124168/)
[7] Ryan McCready. For Olympic Athletes, Is 30 the New 20? July 2016. [https://venngage.com/blog/olympics/](https://venngage.com/blog/olympics/)
[8] Hillard Kaplan, et al. Coronary atherosclerosis in indigenous South American Tsimane: a cross-sectional cohort study. Lancet. 2017 Apr 29. [https://www.thelancet.com/journals/lancet/article/PIIS0140-6736(17)30752-3/fulltext](https://www.thelancet.com/journals/lancet/article/PIIS0140-6736(17)30752-3/fulltext)
[9] Mahesh V Madhavan, et al. Coronary artery calcification: pathogenesis and prognostic implications. J Am Coll Cardiol. 2014 May. [https://pubmed.ncbi.nlm.nih.gov/24530667/](https://pubmed.ncbi.nlm.nih.gov/24530667/)
[10] Michael Gurven. Infant and fetal mortality among a high fertility and mortality population in the Bolivian Amazon. Soc Sci Med. 2012 Dec. [https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3502712/](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3502712/)
[11] Horvath et al. An epigenetic clock analysis of race/ethnicity, sex, and coronary heart disease. Genome Biol. 2016 Aug. [https://pubmed.ncbi.nlm.nih.gov/27511193/](https://pubmed.ncbi.nlm.nih.gov/27511193/)
[12] J Mitteldorf. What Is Antagonistic Pleiotropy? Biochemistry (Mosc). 2019 Dec. [https://pubmed.ncbi.nlm.nih.gov/31870250/](https://pubmed.ncbi.nlm.nih.gov/31870250/)
[13] He and Zhang. Toward a molecular understanding of pleiotropy. Genetics. 2006 Aug. [https://pubmed.ncbi.nlm.nih.gov/16702416/](https://pubmed.ncbi.nlm.nih.gov/16702416/)
[14] J M Stanhope and I A Prior. The Tokelau island migrant study: prevalence and incidence of diabetes mellitus. N Z Med J. 1980 Dec. [https://pubmed.ncbi.nlm.nih.gov/6937778/](https://pubmed.ncbi.nlm.nih.gov/6937778/)
[15] J M Stanhope and I A Prior. The Tokelau Island Migrant Study: serum lipid concentration in two environments. J Chronic Dis. 1981. [https://pubmed.ncbi.nlm.nih.gov/7462380/](https://pubmed.ncbi.nlm.nih.gov/7462380/)

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Because every online diet camp purports that their pet diet cures every disease known to mankind, naturally each one will give you some fantastical mechanistic story about how said diet cures type 2 diabetes mellitus (T2DM). In the paleo/keto/carnivore camp, people will often claim that T2DM is caused by chronic exposure to refined sugar, with some even going so far as to claim that it is caused by exposure to carbohydrates (CHO) more broadly (including foods like apples and even carrots). However, these days it is more trendy in that group to blame T2DM on vegetable oils, but I have previously debunked this on my blog. Over in the "whole food plant-based" (WFPB) cult, it is routinely remarked that T2DM is caused by intramyocellular lipid (IMCL), and that chronic exposure to the saturated fat (SFA) in animal products is responsible for the condition.
In this article, I'll go over the mechanistic reasoning and experiment and/or observational support for these hypotheses, as well as provide an accounting of the leading hypothesis and its supporting evidence. Let's start off by tackling the fantastical notions dreamed up by our vegan friends, and address the IMCL hypothesis.
## The Intramyocellular Lipid Hypothesis
The core idea with this hypothesis is that IMCL, primarily in the form of triglycerides (TG) stored within lipid droplets in muscle cells, act through various pathways to disrupt insulin signaling. The IMCL hypothesis has drawn attention to the role of diet in modulating IMCL levels. High intakes of certain types of fats, particularly SFAs found abundantly in animal products, have been implicated by the proponents of this hypothesis in elevating IMCL levels and contributing to insulin resistance.
This association is often highlighted in discussions on the benefits of WFPB diets for reducing the risk of T2DM and improving insulin sensitivity. Advocates of WFPB diets suggest that such a diet, which is typically lower in SFA and higher in unsaturated fats like monounsaturated fats (MUFA) and polyunsaturated fats (PUFA), which can purportedly help reduce IMCL accumulation and make traction against insulin resistance.
The dietary focus is on whole grains, legumes, fruits, vegetables, nuts, and seeds, with minimal or no intake of animal products. The concern with animal products stems from their content of SFAs, dietary cholesterol, and perhaps even certain supposed inflammatory mediators (possibly Neu5Gc), which may contribute to increased IMCL levels and insulin resistance. WFPB proponents argue that replacing animal products with plant-based sources of protein and fat can mitigate these risks. But is it true?
The IMCL hypothesis attempts to highlight the potential impact of IMCL accumulation on insulin resistance and physiological markers of T2DM. While WFPB are promoted as strategies to reduce IMCL and improve metabolic health, it's important to consider the broader literature and where this hypothesis lands with respect to epistemic virtues over other, possibly more prevailing hypotheses for which there is more evidence.
The mechanistic case for the IMCL hypothesis was first outlined in the late 1990s with two small studies by Jacob, et al. and Perseghin, et al., which discovered relationships between IMCL and insulin resistance in T2DM-free subjects who were born of parents with T2DM [[1]](https://pubmed.ncbi.nlm.nih.gov/10331418/)[[2]](https://pubmed.ncbi.nlm.nih.gov/10426379/). In these experiments, the offspring of those with T2DM were subjected to the gold-standard measure of whole-body insulin sensitivity, the hyperinsulinemic-euglycemic clamp test (HEC). It was discovered that there was an inverse association between IMCL and insulin sensitivity, which led researchers to suspect that perhaps this biomarker was relevant to the pathophysiology of T2DM.
Fast forward to 2004, and another small study from van Loon, et al. would introduce the hypothesis' first paradox [[3]](https://pubmed.ncbi.nlm.nih.gov/15165998/). In this experiment, muscle biopsies and less precise (but still adequate) measures of insulin sensitivity were deployed in an investigation of subjects who were either sedentary, afflicted with T2DM, or who were trained athletes. The study found that the IMCL concentrations of IMCL were actually statistically significantly higher in athletic subjects compared to either sedentary or T2DM-afflicted subjects. Yet, the athletic subjects did not suffer from impaired insulin sensitivity or the hyperglycemia that is characteristic of T2DM.
Researchers Coen and Goodpaster attempted to reconcile the findings in 2012 [[4]](https://pubmed.ncbi.nlm.nih.gov/22721584/). They hypothesized that IMCL behaves differently in the context of T2DM, and that while IMCL serves as a fuel source in athletic subjects, in sedentary subjects with T2DM the IMCL seems to produce more disruptive mediators like ceramides and diacylglycerols. However, the authors tend to play fast and loose with their causal inferences, often citing animal research to buttress clear implications about what holds true in human beings. In fact, the majority of their supporting evidence is derived from mice, despite mice generally being poor facsimiles for human subjects [[5]](https://pubmed.ncbi.nlm.nih.gov/31307492/).
Some of the only human research they can cite are studies wherein there was an observed association between intramyocellular ceramides (IMCC) and insulin resistance. However, there are many biomarkers that serve as proxies for insulin resistance, and there did not seem to be a clear reason proposed by the authors to favour IMCC as causal or mediating. In fact, they cite research that offered conflicting evidence with a broader sample of human subjects, showing that IMCC has no clear association with insulin sensitivity [[6]](https://pubmed.ncbi.nlm.nih.gov/18458871/).
Additionally, Itani, et al (2002) discovered that the concentrations of IMCC do not differ substantially between subjects with varying degrees of insulin sensitivity [[7]](https://pubmed.ncbi.nlm.nih.gov/12086926/). In fact, these researchers challenged subjects with lipids during a HEC to try to alter lipid states in muscle tissue, and ceramides did not change. However, a legitimate criticism of this study is that the lipid challenge done using Liposyn II, which is an intravenous lipid product consisting of 50% soybean oil and 50% safflower oil, making it over half PUFA in its composition. Coen and Goodpaster also cited research on diacylglycerols, but they themselves admit that the human data isn't particularly conclusive on the matter.
To my knowledge there are no recent landmark human experiments that persuasively show that T2DM pathology can be modulated up or down with varying animal products, or even SFA, in the diet. Altogether, the hypothesis has a lot of failed predictions and phenomena to reconcile before it can be taken seriously and can even begin to be seen as epistemically virtuous compared to some other, more scientifically grounded hypotheses. What we need to see is a study that shows that removing SFA and/or animal products from the diets of those with T2DM actually makes traction against pathophysiological markers of T2DM. Ideally this would be done while also controlling for potential confounders or mediators that other competing hypotheses predict would make an impact. The aim is to demonstrate independent effects, and so far no research on the IMCL hypothesis persuasively does this.
## The Sugar Hypothesis
Even though I have touched on this hypothesis five years ago [[8]](https://thenutrivore.blogspot.com/2019/10/sugar-doesnt-cause-diabetes-and-ketosis.html), it bears repeating, with updated epistemic and philosophical rigour. For a recap, my original article challenges perceptions about T2DM that are common in the low carb (LC) diet sphere. I argue against the notions that sugar causes T2DM and that ketosis can somehow reverse it. But we're going to go a little deeper today. So, what is the hypothesis and how does it work? Basically, the hypothesis supposes that chronic exposure to refined sugar or insulin-stimulating CHO leads to T2DM through prolonged over-stimulation of the pancreas. This hypothesis involves several key mechanisms.
Firstly, regular intake of high-sugar or high-glycemic CHOs prompts frequent blood insulin excursions by via the pancreas. To be clear, insulin is the hormone responsible for signaling cells to absorb glucose from the bloodstream for energy or storage. The idea is that over time, constant demand for more and more insulin can lead to insulin resistance via negative feedback. This is when cells become less responsive to insulin's signals because insulin levels are too high. This requires the pancreas to produce even more insulin to achieve the same effect, placing stress on the pancreatic beta cells (which are responsible for insulin secretion).
Secondly, chronic over-stimulation of the pancreas due to persistent high sugar/CHO intake and supposed, resultant insulin resistance can lead to beta-cell dysfunction (which is characteristic of advanced T2DM). Over time, the beta cells' capacity to produce insulin can diminish due to the increased demand, oxidative stress, and subsequent glucotoxicity (toxicity due to hyperglycemia). This dysfunction contributes to the progression of T2DM, where insulin production eventually becomes insufficient to control blood sugar levels effectively.
Lastly, high levels of circulating glucose (glucotoxicity) and fatty acids (lipotoxicity) are actually detrimental to pancreatic beta cells. High glucose levels can lead to the formation of reactive oxygen species (ROS), causing an inflammatory cascade effect, damaging beta cells and impairing insulin secretion. Similarly, elevated free fatty acids (FFAs) can accumulate in non-adipose tissues, including the pancreas, causing cellular dysfunction.
The mechanisms, epidemiological, and experimental evidence for this hypothesis were most succinctly summarized by Stanhope in 2016 [[9]](https://pubmed.ncbi.nlm.nih.gov/26376619/). This review discusses the evidence and controversies surrounding the impact of sugar consumption on T2DM, including mechanisms by which excess sugar intake may promote the development of T2DM directly and indirectly. It covers the direct metabolic pathways through which fructose, a component of table sugar, sucrose, can lead to intrahepatic lipid (IHL) accumulation and decreased insulin sensitivity, contributing to the pathophysiology of T2DM independent of total caloric intake.
The author first refers to literature they themselves conducted, including three primary human trials demonstrating disturbances to energy expenditure, markers of liver function, as well as measures of IHL accumulation [[10]](https://pubmed.ncbi.nlm.nih.gov/26376619/)[[11]](https://pubmed.ncbi.nlm.nih.gov/21952692/)[[12]](https://pubmed.ncbi.nlm.nih.gov/22828276/). The first trial discovered that isocaloric feeding of fructose compared to glucose over a ten-week period significantly increased hepatic fat.
However, it's unclear what the clinical significance of this finding is, considering that the fructose-based intervention resulted in significant overfeeding and only increased fasting glucose by 5% compared to the glucose-based control. Seems like the authors tried pretty damn hard to induce a T2DM phenotype feeding fructose to subjects, and were ultimately unable to achieve that. In fact, they weren't really able to get close. Even the oral glucose tolerance test results, though far from ideal, showed an altogether normal blood glucose curve for the fructose group.
The second trial was unremarkable, and suggested that fructose consumption may decrease energy expenditure over time when isocalorically compared to glucose. Again, it's interesting, but it's far from demonstrating a cause and effect relationship between T2DM and sugar. The third trial is a bit more complicated to unpack. Basically, subjects were split into two groups, 25% of calories as either fructose or glucose as parts of eucaloric diets over 10 weeks, with the primary endpoints beings measures of liver function. Overall, the results of the trial suggest a significantly detrimental effect of fructose compared to glucose on a number of markers related to liver function. However, it's slightly more complicated than that.
While it's true that the treatment effect showed a benefit of glucose over fructose, it's also true that the marker of liver function that was negatively perturbed was gamma-glutamyl transferase (GTT). The change in GGT was also barely statistically significant compared to baseline, while markers such as aspartate aminotransferase (AST) and alanine aminotransferase (ALT) showed a non-significant decrease. Glucose showed greater reductions that were barely statistically significantly different from that of fructose.
Other than that, fructose did seem to increase uric acid levels to a statistically significant degree, making fructose a potential aggravating factor for conditions such as gout. But again, this is a far cry from causally linking fructose consumption to the development of T2DM, especially since fructose seemed to do nothing particularly interesting to markers of liver function. It is true that sugar intake is severely negatively associated with health outcomes [[13]](https://pubmed.ncbi.nlm.nih.gov/34444794/). However, while this is a consistent finding, clinical trials on sugar consistently fail to demonstrate a connection between sugar intake and the development of T2DM.
We can indirectly test the sugar hypothesis by looking at long-term data in those following ketogenic diets for T2DM remission. If subjects cut nearly all carbohydrates out of their diets, presumably this subsumes sugar, and could present a valid test of the hypothesis. One such study might be the Virta Health trial [[14]](https://pubmed.ncbi.nlm.nih.gov/29417495/). In this trial, a non-randomized, self-selected sample of eager subjects elected to participate in a cutting-edge, individualized dietary intervention program, with the aim of nutritional ketosis, called the Continuous Care Intervention (CCI), utilizing a web-app, ketone-verified adherence monitoring, and constant patient support.
> Other aspects of the diet were individually prescribed to ensure safety, effectiveness, and satisfaction, including consumption of 3–5 servings of non-starchy vegetables and adequate mineral and fluid intake for the ketogenic state. At onset of dietary changes, participants were advised to consume a multivitamin, 1000–2000 IU vitamin D3, and up to 1000 mg omega-3 daily. If participants exhibited signs of magnesium depletion (e.g., muscle twitches or cramps), daily supplementation (500 mg magnesium oxide or 200 mg magnesium chloride) was suggested. If participants exhibited headaches, constipation, or lightheadedness, adequate sodium and fluid intake was recommended.
Suffice it to say, there would be little, if any, room for sugar while on such a diet. These subjects were followed up for one year, and, as expected (given the high potential for bias with such a study design), results were impressive. By the end of the first year, the control group was floundering and the CCI group managed to achieve a massive 1.3% reduction in HbA1c, which effectively pushed the once diabetic group into the non-diabetic range on average. However, this change was commensurate with a 14.3% drop in body weight, which we'll revisit in a later section of this article.
Despite these improvements, recidivism continued to climb. As of two years, the CCI group had crept back into the diabetic range on average [[15]](https://pubmed.ncbi.nlm.nih.gov/31231311/). By, 3.5 years, the CCI group was once again firmly within the diabetic range on average, having regained a significant amount of weight [[16]](https://www.hsrd.research.va.gov/publications/esp/virtual-diet-brief.pdf)[[17]](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7208790/).
To be clear, there was a clear distinction between remission and reversal, as defined by the authors. Remission was a much more robust measure of traction against T2DM than reversal, even though it sounds like the latter is stronger than the former. Remission was defined in two parts; partial remission and complete remission. Partial remission was defined as "sub-diabetic hyperglycemia of at least 1 year duration, HbA1c level between 5.7-6.5%, without any medications (two HbA1c measurements)" and complete remission was defined as "Normoglycemia of at least 1 year duration, HbA1c below 5.7%, without any medications (two HbA1c measurements)". Reversal was defined more loosely, as "sub-diabetic hyperglycemia and normoglycemia (HbA1c below 6.5%), without medications except metformin" (Athinarayanan, et al., (2019), Supplement Table 2).
Unfortunately, all but the second year remission data is either aggregated or ambiguous, so it's difficult to make distinctions between partial and complete remission for years one and 3.5. However, at year two only 6.7% of the cohort had achieved complete remission. It's not clear what percentage of the cohort achieved complete remission by year 3.5. Furthermore, reversal rates, as they're defined, are probably just reflecting attrition rates (which were 26%), as the criteria for reversal is having achieved a sub-diabetic blood glucose at least once throughout the trial. It's actually not clear how meaningful that data even is on that definition.
While a 9% weight reduction over 3.5 years is impressive, I'll reiterate the limitations— the subjects were self-selected, and highly motivated to participate in the CCI. In fact, the patients were paying customers of Virta Health's cutting-edge primary care service. This significantly challenges the external validity of the findings, as impressive as they are, to the general population. What we're seeing are results in the context of what is likely to be extraordinary ambition to succeed, and should be interpreted with caution.
As for how these results relate to the sugar hypothesis, it's difficult to tell, had the subjects managed to control their weight. However, adherence rates to the diet dropped significantly by year two, with nutritional ketosis being achieved in 96% of CCI subjects in year one to only 14.1% by the end of year two. This non-adherence makes it difficult to infer the degree of sugar avoidance actually observed by the cohort on average, and makes cause and effect conclusions difficult to draw. There was no 3.5 year data on ketosis rates, and one can only speculate as to why. But given the poor adherence at two years, it's probably not unreasonable to assume it's because the numbers didn't look very good.
## The Oxidation Hypothesis
The underlying premise is that PUFAs, particularly omega-6 fatty acids found in seed oils, are susceptible to oxidation. When oxidized, these fatty acids can form reactive compounds such as malondialdehyde (MDA) and other harmful products, leading to cellular damage and oxidative stress. In the context of the pancreas and liver, organs that, as previously mentioned, are crucial for glucose metabolism and insulin regulation, such oxidative stress could impair their function, contributing to insulin resistance and β-cell dysfunction— key features of T2DM. A tidy little bundle of sophistry indeed.
Since I've already covered how the human outcome data flies in the face of this hypothesis in a previous article [[18]](https://www.the-nutrivore.com/post/a-comprehensive-rebuttal-to-seed-oil-sophistry), I won't rehash all of it here. But, essentially there is no human outcome data supporting this effect across multiple cohort studies and multiple RCTs. In the epidemiology, tight markers of seed oil consumption show a consistent inverse association with T2DM [[19]](https://pubmed.ncbi.nlm.nih.gov/29032079/).
Additionally, there have been several interventions feeding large amounts of PUFA to subjects, to the exclusion of SFA, and measuring long term effects on insulin sensitivity [[20]](https://www.sciencedirect.com/science/article/abs/pii/0163782781900709)[[21]](https://pubmed.ncbi.nlm.nih.gov/1347091/). In both Houtsmuller, et al. (1979) and Watts, et al. (1992), long term feeding of PUFA was associated with improvements in insulin sensitivity. In the case of the former trial, the insulin sensitivity measure, an oral glucose tolerance test (OGTT), showed improvement to glucose tolerance among diabetics over time. These results were aggregated by Hooper, et al. back in 2020 in an exploratory analysis [[22]](https://pubmed.ncbi.nlm.nih.gov/32428300/).
Additionally, we can also see that Ley, et al. (2004) showed an improvement in OGTT results, but with the substitution of CHO for SFA, rather than PUFA for SFA (which is kinda funny) [[23]](https://pubmed.ncbi.nlm.nih.gov/14739050/).
## The Twin Cycles Hypothesis
The prevailing hypothesis, or the hypothesis that has been given the most credence in this domain, is the twin cycles hypothesis (TCH), which was spearheaded by Dr. Roy Taylor. It is closely interconnected with another concept from Dr. Taylor's work, known as the personal fat threshold (PFT). So what are these things? Let's start with the TCH. The TCH postulates that there are two stages, or "cycles", to T2DM development. The TCH was first discussed in a 2011 paper by Lim, et al. (coauthored by Dr. Taylor) detailing the development of the hypothesis from previous clinical trials performed on patients with T2DM [[24]](https://pubmed.ncbi.nlm.nih.gov/21656330/). This trial would come to be known as the Counteracting Pancreatic Inhibition by Triglyceride (CounterPoint) study, and would be reviewed in greater detail two years later by the same authors [[25]](https://pubmed.ncbi.nlm.nih.gov/23075228/).
The first cycle originates in the liver, where chronic, excess calorie intake leads to ectopic fat accumulation, causing hepatic insulin resistance. The reason for this is because tissues that are energy replete will resist the action of insulin, with is a signalling hormone responsible for facilitating energy deposition in tissues. The second cycle concerns the pancreas, where the continued excess fat spills over to the pancreas (primarily via nonesterified fatty acids (NEFA), leading to lipotoxicity and subsequently impairing β-cell function. Ultimately, this contributes to β-cell dysfunction, rather than outright β-cell death, as the pivotal event in diabetes progression.
In fact, the TCH originally came about by appreciating that the assumptions typically relied upon when inferring β-cell death in T2DM patients may be faulty. Usually, we infer to β-cell death by staining pancreatic tissue for insulin; no insulin, no β-cells. However, what if the β-cells aren't really dead? What if the diabetic pancreas is just so dysfunctional that the β-cells aren't producing as much insulin? Those assumptions would have us believing that the β-cells are dead when in fact they are merely dormant due to lipotoxicity— waiting to be brought back to life upon fat mass loss. Which brings us to the next piece of the puzzle.
Now let's discuss the PFT, and how it ties into the overall picture. Essentially, the PFT posits that hepatic and pancreatic fat deposition are facilitated by accumulating more subcutaneous body fat (SBF) than one's body can tolerate, regardless of whether their body mass index (BMI) categorizes them as overweight or obese [[26]](https://pubmed.ncbi.nlm.nih.gov/25515001/). In basic terms, after non-hepatic, non-pancreatic tissues get too fat, there is a spillover of fat (precipitated by chronic calorie excess) onto the liver and the pancreas, which initiates the T2DM phenotype.
Think about it. There's just nowhere left for the energy substrates to go, be it glucose, triglycerides (TG), or even amino acids. They're all increased with T2DM, because all the tissues are energy replete. The liver and the peripheral tissues essentially play a never-ending game of ping pong with the energy substrates because no tissues are able to take on the extra calories. This hypothesis was tested with vindicating results in a recent trial by Taylor, et al. in 2024 [[27]](https://pubmed.ncbi.nlm.nih.gov/37593846/). Essentially, it seems that T2DM development and remission have very little, if anything, to do with BMI, and BMI may be a very poor risk factor for T2DM, due to the individual variation in the PFT from person to person.
Now that we have a clear understanding of the model, let's discuss the overwhelming evidence in favour of it. The clinical trials that first gave rise to the TCH were human experiments that involved both pharmaceutical and dietary means of reducing hepatic fat [[28]](https://pubmed.ncbi.nlm.nih.gov/18535187/)[[29]](https://pubmed.ncbi.nlm.nih.gov/15734833/).
For the first study by Ravikumar, et al., a single-arm trial of 10 subjects, the drug pioglitazone was investigated for its effects on markers of T2DM, particularly postprandial endogenous glucose production (EGP) using isotope labeled glucose, as well as IHL. After 16 weeks of treatment, the pioglitazone group experienced an increase in total body weight equal to +6.2kg on average. Yet, the pioglitazone group also experienced a decrease in IHL.
However, to be fair, the pioglitazone group also experienced a significant decrease in IMCL as well, however there was no significant correlation between decreases in IMCL and EGP. There was however, a direct association between IHL and EGP. Although this trial was not controlled, it certainly doesn't produce results expected on the IMCL hypothesis, and it lends further credence to the TCH. Additionally, many markers of T2DM subsequently improved, such as plasma glucose, hemoglobin A1c (HbA1c), and even TGs, with the changes being -2.3mmol/L, -1.9%, and 0.4mmol/L, respectively.
It can also be inferred that there was a meaningful increase in insulin sensitivity, given the fact that plasma glucose dropped despite the same amount of insulin being produced by subject. Essentially, glucose disposal per unit insulin went up, implying that insulin signalling had improved.
In the second study by Petersen, et al., eight subjects with T2DM were compared to 10 healthy volunteers in a non-randomized weight loss trial over an average of seven weeks. Essentially, subjects were followed up until normoglycemia was achieved, so not every subject was subjected to the same amount of weight loss for the same time period. In this time, body weight dropped by an average of 8kg in the T2DM group. This was marked with commensurate drops in plasma glucose, plasma insulin, and TG, at -2.4mmol/L, -108pmol/L, and -0.3mmol/L, respectively.
The most interesting and surprising finding was that there was no significant change in IMCL despite weight loss. But, subjects did end up achieving normoglycemia and near normal insulin sensitivity as determined by a HEC. However, much like the previous study, insulin sensitivity was directly associated with IHL reduction. Once again, this flies in the face of the IMCL hypothesis, and offers further support for the TCH as the T2DM approached nearly normal levels of IHL. Although neither of these papers directly test for evidence of the sugar or oxidation hypotheses, it should be noted that both of these trials involve the consumption of both sugar and most likely animal products.
In light of this evidence, Steven and Taylor conducted another preliminary human trial, the CounterBalance study, involving 29 subjects in 2015 to test the effects of the same intervention in those with long- versus short-term T2DM [[30]](https://pubmed.ncbi.nlm.nih.gov/25683066/). Both groups experienced similar weight loss (short-duration: 14.8%, long-duration: 14.4%), indicating that the VLCD was effective for weight reduction regardless of diabetes duration. These results were also durable throughout the six month post-intervention follow-up.
In terms of other T2DM markers, such as plasma glucose, the response to the diet was heterogeneous among participants with long-term T2DM. Some showed similar responses to those in the short-term group and some responded slowly. By the end of the study, 87% of the short-term group and 50% of the long-term group achieved non-T2DM fasting plasma glucose levels. HbA1c levels also decreased in both groups, with a more significant reduction observed in the short-term group. However, there was an unforeseen result— about half of subjects did not respond to the treatment at all, which was not expected given nearly all previous research.
Given these results and Dr. Taylor's previous characterization of the PFT concept, the most likely hypothesis seemed clear— these people just needed to lose more weight, which we'll get to later. For now, there was enough evidence of the effectiveness of weight loss for T2DM treatment that Dr. Taylor and his colleagues decided it was time to test the efficacy of the treatment in a real-world outpatient scenario. A cluster-randomized experiment was designed and undertaken, and would come to be known as the Diabetes Remission Clinical Trial (DiRECT) [[31]](https://pubmed.ncbi.nlm.nih.gov/29221645/).
The DiRECT trial involved 298 subjects across 49 primary care practices (or clusters) randomized two groups, a control group receiving the standard of care for T2DM management, and the treatment group receiving a three stage program: stage one, total diet replacement; stage two, food reintroduction; phase three, weight maintenance. For the first stage, the treatment group received a liquid diet consisting of four packets of meal replacement formula, which totaled around 825-853 kcal/day for three to five months (depending on patient-specific goals). For the second stage, after subjects completed the first weight loss phase of the trial, food was gradually reintroduced over a period of two weeks to two months. During the last stage, patients were followed up over the course of around a year. The results were encouraging.
Over the course of the trial, the treatment group lost an average of 10kg, with over 86% of them achieving T2DM remission by the end of the first year. An interesting finding was that on average, at the end of the first year, the treatment group still technically qualified as obese, despite the vast majority of them achieving T2DM remission. This would come to be the first nail in the coffin with respect to the idea that T2DM was somehow coupled to BMI. Additionally, patients experienced significant improvements to quality of life without serious side effects or complications. Altogether the treatment was successful, well-tolerated, and produced impressive rates of T2DM remission that was durable long-term.
However, Dr. Taylor's group published two follow-up, long term durability studies on the DiRECT trial [[32]](https://pubmed.ncbi.nlm.nih.gov/30852132/)[[33]](https://pubmed.ncbi.nlm.nih.gov/38423026/). The results of these follow-up studies was bitter-sweet. At the two-year follow-up, only 41% of the treatment group remained in remission compared to the previous year, and only 10% at five years of follow-up. These results were not promising for the treatment over time once people were reintroduced to their previous diets and left without practitioner support. Even after the two-year follow-up, 94 or the remaining 101 subjects in the treatment group were given access to extended care, which only resulted in 13% remission rates within the extended care group at five years.
It sounds bleak, but let's think about it. Dr. Taylor's research was essentially testing two things at the end of the day— the conceptual model of T2DM, encompassing the TCH and the PFT, as well as the efficacy of radical weight loss in an outpatient setting. With respect to the former, Taylor's work has been a resounding success, and it buttresses the strongest model of T2DM development and progression that we currently have. In regards to the latter, radical supervised weight loss with the practitioner support did not yield terribly promising results beyond two years. All isn't lost, though.
The important thing is that we now have a firm grasp about what causes T2DM. It isn't sugar, seed oils, animal fat, or any other harebrained dietary boogeyman. It's just energy poisoning, with a simple, easy-to-understand etiology; if you gain more fat than your body can tolerate, you develop the phenotype of T2DM. If at that point you do indeed lose enough body fat to fall back below the maximum your body can withstand, T2DM remission follows. The last piece of the puzzle is figuring out what factors cause over-consumption, and how to durably address excessive body fat.
## Discussion
In conclusion, while a myriad of hypotheses continue to circulate within nutritional and diabetic research spheres regarding the genesis and treatment of T2DM, it becomes increasingly clear that simplicity often guides the best practice. The TCH, underscored by the PFT, offers a cogent framework suggesting that T2DM is not merely a product of specific dietary components like sugars, SFA, or PUFA, but rather a complex interplay of caloric excess leading to dysfunctional energy storage and insulin response. As emerging studies, such as those by Dr. Taylor and his colleagues, indicate, interventions aiming at substantial and sustained weight loss may hold the key to reversing T2DM, provided these interventions are maintained with consistent medical oversight and support.
While the exploration of dietary influence on T2DM remains important, we also have to acknowledge the apparently lack of elasticity of our food culture and the stark tendency toward recidivism with dietary intervenions. Emerging pharmacological interventions, particularly GLP-1 receptor agonists, are presenting promising frontiers in the management and potential reversal of this condition. As we advance, the integration of such pharmaceutical approaches alongside dietary management could revolutionize the treatment landscape of T2DM. Emphasizing the synergy between medication and lifestyle changes will likely be pivotal in crafting effective, personalized treatment plans that address both the biochemical and lifestyle facets of diabetes care.
Thanks for reading! If you enjoy my writing and want more content like this, consider pledging to my [Patreon](https://www.patreon.com/thenutrivore)!
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By no stretch of the imagination is there any shortage of quackery on social media. Chances are excellent that if you’ve spent any appreciable amount of time on social media, you have encountered some number of quacks and some sort of quackery that they espouse. You might not even be aware that you’re looking at quackery while you’re being exposed to it. So, the aim of this article will be to attempt to simplify the processes of both identifying quackery and dealing with quackery.
Fundamentally, the issue is not merely that quacks are just interpreting studies incorrectly or affirming crazy beliefs. Those are just symptoms of the problem, rather than being the root cause of the problem. Typically, the problem is occurring within their epistemic framework, and is the very thing that is actually leading them to form their crazy beliefs to begin with. As such, a universally efficacious way to get under a quack’s position and expose them as a raving lunatic is to press them on their epistemic standards in one way or another. That is to say, subject their belief-formation process to a thorough stirring, so that their insanity is allowed to bubble to the surface for all to see.
This means dragging them down to a level that is inferentially prior to their current understanding, and away from the level of research and studies. Just like the scientific method is inferentially prior to studies or study design, scientific epistemology is inferentially prior to the scientific method. If your starting point is on the level of studies and study design, following the inferential lineage backward will eventually bring you to a level where the premises will all be principles, virtues, or axioms. This is the level we need to bring the quack to in order to address the fundamental flaws in their reasoning.
The ultimate aim of this process is to expose errors in the quack’s reasoning, not to necessarily convince them of anything. Of course, the hope is that they correct the complications in their belief-formation process, such that they cease to be a quack by the end of the discussion. However, this isn’t a very likely outcome, but this is nonetheless the outcome that you should be aiming for in order to have the best good faith conversation possible. To explore why this outcome isn’t particularly likely, we’ll have to explore what a quack is, and why they’re typically so immovable. So, let’s get into some definitions.
## Quack
> “A quack is a type of scientific delinquent— one who brandishes the trappings of science, yet whose scientific standards are obstinately in violation of those considered most virtuous within the contemporary philosophy of science.”
It was no easy task to get to the bottom of what is so objectionable about the quack’s behaviour. It took interviewing multiple domain experts and trashing dozens of revisions, but I think I finally have something that is workable and minimally assailable for the time being. Essentially, the trait that quantifies over all quacks is a fundamental lack of respect for the rules of scientific inquiry.
If we were to think of science as a country with laws, a quack would be a contemptuous sort of outlaw within that country. But, quacks are not only rule-breakers by nature, they also actively turn their noses up at the rules— almost relishing in their own intransigence. Despite the commonalities, quacks can usually be categorized in at least one of three distinct ways: **deranged**, **dense**, or **dishonest**.
## Deranged
1. **The Zealot**: one who has assimilated quackery into their identity, and will be emotionally damaged if the quackery is challenged.
2. **The Contrarian**: one who espouses quackery due to strong anti-establishment and/or conspiratorial and/or paranoid tendencies.
3. **The Narcissist**: one who is simply so self-assured of their own infallibility that they cannot fathom that their beliefs could be quackery.
4. **The Aggrieved**: one who feels wronged by some conventional scientific paradigm and is seeking vindication or revenge through quackery.
5. **The JAQ-off**: one who slyly hat-tips to quackery, often in an ostentatious or cheeky manner, but claims to be just asking questions when challenged.
6. **The Circlejerker**: one who is deeply impressionable and merely forms the beliefs of whatever community will accept them.
## Dense
1. **The Zombie**: one who has made little to no effort to form their own beliefs, but rather just recapitulates the beliefs of influential people.
2. **The Imbecile**: one who lacks the requisite intelligence and/or cognitive faculties to form rational beliefs of their own accord.
## Dishonest
1. T**he Grifter**: one who espouses quackery, not necessarily because they believe it to be true, but rather for some ulterior motive such as money or clout.
2. **The Yo-Yo**: one who spouses both quackery and non-quackery, often to the point of self-contradiction, depending on the context.
This probably isn’t an exhaustive list of quack species and subspecies, and will likely be updated in the future. For now, these are the most common types of quacks you’re likely to encounter online or on social media. Most quacks you will encounter will be of the deranged variety, and of them, the majority will be either contrarian or narcissistic. The narcissistic quacks are hardly worth engaging with, unless it is for the benefit of an audience. But other than that, you’ll never convince them of anything because they’re cocksure of their own perfection. Contrarians may be swayed by reason, but it is not particularly likely.
Much like the narcissistic quack, the dishonest quacks are also not likely to be worth engaging with, except for the benefit of onlookers to whom you seek to reveal the quack’s dishonesty. Dishonest quacks, especially grifters, will tend to sway their affirmations in lockstep with the trends of the time. For example, many grifters who were pushing low carbohydrate diets back in 2017 are now pushing raw, grassfed carnivore diets in 2022. It just depends on what’s trending at the moment. It’s a game to them. Engaging is typically pointless and you’re justified in disengaging, in my opinion.
Altogether, you have the best chance of convincing dense quacks, because they’re less likely to be as intransigent as other varieties. These types of quacks don’t typically believe quackery due to some emotional commitment or ulterior motives. Usually they’re just either uneducated or dumb. However, if they’re too dumb to understand the difference between good evidence and bad evidence, convincing them may be ultimately beyond your reach. But it is nonetheless worthwhile to attempt reasoning with them. The best discussions will likely be had with the zombie variety of quack, as they’re usually the closest to just being truly naive, and they’re not necessarily dumb.
Now that we have a bit of a handle on what constitutes a quack, let’s move on to the next definition we need to cover:
## Quackery
> “Any ostensible hypothesis that either fails to satisfy any critical theoretical virtue of a scientific hypothesis (i.e., testability, fruitfulness, scope, parsimony, conservativism) or satisfies fewer theoretical virtues compared to the prevailing scientific hypotheses against which it is intended to compete.”
Given that a proposition is a statement that can be either true or false, a scientific hypothesis can be thought of as basically being an empirically testable proposition. For example, say that we wanted to develop a theory to explain the rising of the sun each morning. We could generate a few different hypotheses. Hypothesis A might suppose that the sun rises because God is pulling it across the sky. Hypothesis B might suppose that the sun rises because it is revolving around the Earth. Hypothesis C might suppose that the sun rises because the Earth is spinning.
Let’s linger on hypothesis A for a moment to discuss some of its issues. Firstly, it’s completely unclear how hypothesis A could be tested, so whether or not it genuinely qualifies as a hypothesis is questionable. Those with a background in science have likely been exposed to the principle that unfalsifiable hypotheses are to be avoided, and hypothesis A is an example of that. Testability is arguably the most important aspect of a scientific hypothesis. Without testability, there is no empirical investigation. Without an empirical investigation, there is no science. The hypothesis ends up being completely ad hoc (which we will discuss later).
On the other hand, hypothesis B certainly has the capacity to make predictions. One could create a model wherein the sun travels around the Earth, and observations can certainly be made that are consistent with that model. Hypothesis C could be tested similarly. One could construct a model wherein the Earth is spinning and the sun is fixed in place, and observations can be made to see if that model pans out.
So far, hypothesis B and hypothesis C don’t seem to underdetermine phenomena differently, and the observations seem equally expected on both hypotheses. However, what if we also made the observation that there are other planets out there in space, and we also observe that those planets seem to move in relationship to the sun in a way that suggests that the sun is a fixed object. This observation is more expected on hypothesis C than hypothesis B. The observed phenomena are underdetermined on hypothesis B, and thus hypothesis C would come out on top until there is a better hypothesis to supplant it.
Great! We have established what it takes for a proposition to be a scientific hypothesis, as well as what it takes for one scientific hypothesis to prevail over another. Now let’s move on to discuss the different criteria that such hypotheses need to satisfy in order for them to be competitive within the domain of science. These are the epistemic virtues we touched on earlier— the standards by which the viability of a tentatively competing scientific hypothesis will be measured. [¹](https://www.oxfordbibliographies.com/display/document/obo-9780195396577/obo-9780195396577-0409.xml) [²](https://books.google.ca/books/about/How_to_Think_About_Weird_Things_Critical.html?id=YR4iAAAAQBAJ&redir_esc=y)
## Criteria of Adequacy
1. **Testability**: A hypothesis is scientific only if it is testable, that is, only if it predicts something more than what is predicted by the background theory alone.
2. **Fruitfulness**: Other things being equal, the best hypothesis is the one that is the most fruitful, that is, makes the most successful novel predictions.
3. **Scope**: Other things being equal, the best hypothesis is the one that has the greatest scope, that is, that explains and predicts the most diverse phenomena.
4. **Parsimony**: Other things being equal, the best hypothesis is the simplest one, that is, the one that makes the fewest assumptions.
5. **Conservatism**: Other things being equal, the best hypothesis is the one that is the most conservative, that is, the one that fits best with established beliefs.
All else equal, if an alternative hypothesis fails to outcompete a prevailing hypothesis on any of these measures, why form the belief that the alternative hypothesis is more likely to be true compared to the prevailing hypothesis? Beyond the testability of a hypothesis, the extent to which a hypothesis fails to satisfy any of these theoretical virtues will determine the “ad-hocness” of that hypothesis. An ad hoc hypothesis is also known as a “just-so story”, which is a phrase you may have heard before.
While it goes without saying that ad-hocness is undesirable in science, it is important to emphasize that this is the crux of the quack’s rhetoric. Quackery is like an artichoke of idiocy, and just-so story-telling is at the heart of it. You have to peel it slowly to expose the fuckery. This sort of delinquent fabulism takes many forms, and it’s not always obvious when a hypothesis is ad-hoc and failing to satisfy one or more theoretical virtues compared to another hypothesis. But, hopefully your intuitions can be adequately primed with a few examples. Let’s examine this scientific hypothesis:
> “Vegetable oils are the cause of heart disease.”
At first glance, this hypothesis appears to be extremely attractive in its parsimony. It appears to be making very few assumptions, as it is reducing the cause of heart disease down to a single variable. However, this is an illusion. This hypothesis must actually bootstrap an enormous number of assumptions in order to compensate for its lack of scope and fruitfulness. Not only does the totality of the empirical evidence weigh heavily against this hypothesis, it’s not clear what novel predictions the hypothesis has generated, if any at all.
The primary issue is that the hypothesis is lacking in scope because it does not account for the majority of our observations regarding vegetable oils and heart disease. Typically, the quack will attempt to compensate for this shortcoming by casting doubt on existing research— “those findings are wrong because epidemiology is pseudoscience”. What the quack doesn’t realize is that this actually decreases the parsimony of their hypothesis. This leaves them with an ad-hoc story that is not particularly unifying, fruitful, or parsimonious. Let’s examine another hypothesis:
> “Ancestral foods protect against all illnesses.”
On the face of it, this hypothesis might appear similar to the first in that it lacks scope and fruitfulness, and in turn compromises its own parsimony. However, it may be even worse than that. If ancestral foods are referring to foods that humans consumed during some prehistoric time period, then the hypothesis is actually untestable. Humans no longer have access to those foods, and as such the hypothesis is almost entirely ad hoc, and the theoretical virtues that it upholds are few to none.
The more sensitive you become to when a hypothesis is failing in its virtuousness, the more straightforward it will be to identify and dispatch quackery. For instance, consider what has been described above in previous examples, and examine these other quack hypotheses carefully:
> “Red meat protects against mental illness.”
> "Sunlight protects against skin cancer.”
> “Blueberries cure Alzheimer’s disease.”
> “Refined carbohydrates cause obesity.”
> “Milk products impair bone health.”
> “Soy products feminize men.”
> “Vegan diets cure cancer.”
Remember that quacks fundamentally don’t care about scientific rigour, and virtually all quackery will follow a similar structure at its core— an utter lack of respect for the rules we just discussed. Thus, there is a virtually universally efficacious way of uprooting quackery. Simply interrogate the quack about how their hypothesis better conforms to the rules compared to other hypotheses, and watch them crumble.
Once you start scrutinizing quackery like this on this basis, you will quickly realize that quacks are just master fabulists— iron chefs of word salads. Mind you, quacks will never admit to this. Even when their bullshit has been revealed to them point blank, the exact lack of rigour that got them to be in their current state will end up keeping them smiling through their humiliation.
At this point it would be worthwhile to discuss the **Quack’s Trichotomy**. This concept has been borrowed from Lance Bush’s anti-realist metaethical thesis. While it was originally a way of categorizing different types of moral realism, it would appear to be highly applicable to categorizing different types of quackery as well.
Basically, quackery will ultimately reduce down into one of three categories: **false**, **trivial**, or **unintelligible**. As discussed above, most quackery will end up being false (or at least more likely to be false than true). But, there are some other common cases to explore. Identifying just what kind of utterances the quack is making will be helpful in figuring out whether or not it’s even worth entertaining their madness. Consider the following three interpretations of this hypothesis:
> “Red meat is healthy.”
## False Interpretation
Perhaps the tentative quack cashes out the term “healthy” into some sort of claim about red meat not increasing the risk of heart disease. This can be tested, and it turns out that when the best available data is aggregated together, across multiple domains, red meat consumption reliably associates with an increased risk of heart disease. This means that this hypothesis would just be false, or more likely false than true.
## Trivial Interpretation
Let’s just say that all the tentative quack means by “healthy” is that they themselves just feel really good on a diet that is high in red meat. In this case, the hypothesis is actually going to be “I feel really good on a diet that is high in red meat.” This is not anything that anyone would contest, as it’s clearly true. However, it’s trivially true, and a pointless proposition to utter. We need not debate this. This claim may not necessarily make them a quack, but we should probably just leave this idiot to their fuzzy feelings and move on.
## Unintelligible Interpretation
In this case, we’ll imagine that the tentative quack doesn’t unpack the utterance any further, and just continues to insist that red meat is “healthy”, over and over. If no further clarification is offered, this interpretation of the hypothesis is just gibberish. What is healthy supposed to mean? To me, “healthy” is a relational concept that joins many relata— X is healthy for Y compared to W relative to standard Z (where healthy is defined as an exposure that increases the lag-time to the onset of illness compared to a different exposure). Unless their meaning is unpacked in an intelligible way, their utterance doesn’t even rise to the level of being a proposition. They’re literally just gibberating, and we need not debate their ramblings. Leave them to their delusions.
In an exceedingly small minority of cases that fall outside of the scope of the **Quack’s Trichotomy**, the tentative quack’s proposition will be true and convincing, rather than being false, trivial, or unintelligible. In this case, the proposition likely isn’t quackery and you likely just mistook the proposition as quackery due to miscommunication. If this happens, you should just accept the proposition and feel good that you learned a new fact today. Enjoy it when it happens. But again, this almost never happens.
There is one final trope we need to explore, though. Every so often, you will encounter someone who is committed to extraordinarily high standards of evidence. For example, quacks in the nutrition blogosphere will sometimes claim the following:
> “Evidence cannot be obtained in nutrition science unless you have studied the effects of a food in a multi-generational, quadruple-blind randomized controlled metabolic ward crossover trial in human clones.”
This is not really a hypothesis. It’s just a claim that directly pertains to scientific epistemology itself, which means we must deal with this in a unique way. In this case, we should simply ask them what theoretical virtue would be either violated or unable to be satisfied unless we had such evidence for our hypothesis? As such, it would be worthwhile to get into a few definitions regarding what constitutes evidence.
## Evidence
> “That which is more expected on a given hypothesis compared to the negation of that hypothesis.”
On this definitions, falling short of achieving a trial design like the one described above does not bar us from making discoveries that are more or less expected on different hypotheses. Thus, failing to achieve such a trial design is not a barrier to discovering any sort of evidence. If a short trial with a limited number of people finds an effect of some intervention, that effect is still going to be expected on a hypothesis that predicts it. So, it’s still evidence.
Now we’re ready to start tackling quackery ourselves. Next up, we’ll go through a universally applicable procedures for smashing quackery. The beauty is that the procedures leave the burden of proof squarely on the quack, and pressure test their epistemic standards. This means that you probably don’t even need to show up with studies of your own if you don’t want to. The ball will mostly be in their court, and the burden of proof will be squarely theirs. By the end they’ll find themselves looking up from within their own grave and they will have nobody but themselves to blame for them being there.
Before we move on to the quack-smashing debate procedure, it's recommended that you download the included [dialogue tree](https://drive.google.com/file/d/1QQaN6HRwzp3kY2DAcnHVBxeX6jBhrvkw/view?usp=share_link) and refer to it while reading.
###### PHASE ONE
###### CLARIFICATION
## Step 1: Ask for a proposition
Essentially, a proposition is what is known as a truth-apt statement. Meaning that it is a statement that can be either true or false. You can think of a proposition like a claim. A common tactic among quacks is to dance around some implied commitment without ever actually explicitly making any claims.
Quacks are notoriously unclear when they communicate. Sometimes quacks will simply gesture in your direction with a series of vague utterances that merely have the appearance of communicating disagreement. For example, a quack might say to you:
> “Read the studies you idiot!”
> “Follow the money to know the truth!”
> “We’ve been lied to for over fifty years!”
Notice how vague these statements are. Quackery thrives on vagueness. You must straightforwardly ask the quack for their position— “I’m sorry, I just want to understand what you mean. What do you think is true that people who believe this study think is false?” Be firm, and stand your ground. Press them until they give you an utterance that at least has the appearance of something propositional.
## Step 2: Evaluate their ostensible proposition
Once you have a proposition, we begin the clarification phase. During this step you are aiming to demystify anything that you find unclear. If there are terms over which there may be disagreement, such as relational terms with missing relata, you must ask for clarification.
If clarification is required, proceed to **step 2.1**. If clarification is not required, proceed to **step 2.2**.
## Step 2.1: Ask for clarification
Essentially what we need from the quack is a clear, contestable proposition. Scrutinize every word in their proposition if necessary. This is not to bog down the debate, but to make sure that there is as close to a complete, unambiguous shared understanding of the terms being used by the quack as possible. In the vast majority of cases, asking the quack simple clarifying questions about their proposition will make it fall apart on the spot.
If the tentative quack’s explanation devolves into bullshit like rambling or gibberish, just walk away from the idiot. If it appears intelligible and it’s just some trivial utterance that isn’t worth discussing, we can start assessing its truth value.
###### PHASE TWO
###### ARGUMENTATION
## Step 2.2: Check for modal claims
If we manage to obtain an intelligible proposition from the quack, we can begin checking for modal language. Modal language typically refers to concepts like impossibility, necessity, possibility, or contingency. Be sensitive to when your interlocutor is using words that function as synonyms for any of these terms. For example, words like “can”, “able”, “may”, “could”, or “capable” should all be taken as synonyms for the modal term “possible”, whereas words like “unable”, “cannot”, “couldn’t”, “unable”, “incapable”, should all be taken as synonyms for the modal term “impossible”.
Additionally, if your interlocutor suggests that something is necessarily the case, that should be taken as just another way of saying that the contrary is impossible. As such, impossibility and necessity are modal terms that can essentially be captured by the same modal operator. Similarly, if your interlocutor suggests that something is possible, all they’re saying is that it's necessarily not impossible, which is to say that it's contingent upon something else. So, much like impossibility and necessity, possibility and contingency can also be interpreted interchangeably, under the same modal operator. At the end of the day the terms can ultimately be cashed out into what is impossible or possible.
To be clear, these terms are just operators, and don’t mean much unless they’re in reference to a given modality. Modalities are just means by which these modal operators can be understood. There are two primary modalities that are commonly discussed in the philosophy literature— physical and logical. For example, something is logically impossible if it entails a contradiction, and something is physically impossible if it violates a law of physics.
Of course there are other modalities. In fact, there are probably infinite numbers of modalities on which an operator like impossible can be understood. For instance, while it’s certainly logically and physically possible to murder someone in any country, it is legally impossible to murder someone in most countries. Though we don’t really use modal language in this way.
Overall, impossibility can be interpreted as something that is incompatible with a given rule/standard or set of rules/standards, and possibility can just be interpreted as something that is compatible with a given rule/standard or rule/standard set.
In most cases, if the modal operator they’re invoking relates to possibility, then it’s probably not even worth continuing the discussion. In the vast majority of cases it’s just trivial to claim something is possible. If the proposition contains a modal operator related to impossibility, proceed to **step 2.3**. If their proposition does not contain a modal operator, proceed to **step 2.4**.
## Step 2.3: Ask which law is broken on their stated modality
This step is pretty straightforward. If your interlocutor is claiming something is impossible, ask them on what modality is it impossible. If necessary, explain to them what modalities and modal operators are, just so they’re both clear on what you’re asking of them and what kind of claim they’ve actually made.
If they cannot unpack the modality and the law that’s violated on that modality first give them the opportunity to amend their claim. If they refuse to amend the claim or are unable to unpack the claim, then proceed to **step 6**. If they actually manage to unpack the modality and the law that’s violated on that modality, and it’s convincing to you, you should probably just concede.
## Step 2.4: Ask for a goalpost
Assuming there were no modal claims in our tentative quack’s proposition, we can proceed to the first step in the actual debate— requesting a goalpost. Basically, you will merely ask them what evidence would be required for them to affirm that their proposition is false. This is different than asking them what evidence it would take for them to reject their proposition. We want to know what it would take for them to affirm their proposition’s negation.
This step isn’t vital, so it’s not a huge concern if our tentative quack doesn’t render a goalpost to you. However, keep in mind that if they can’t tell you their goalpost for affirming their proposition’s negation, they are essentially telling you that they don’t even know why they believe that their proposition is true. So, it’s up to you if you want to proceed further. If you want to stop here, just shame them for being a sophist and disengage.
If you decide to continue, proceed to **step 3**.
## Step 3: Ask for an inference for their proposition
This step is pretty straightforward. You’re just straight up asking for the argument for the proposition. After you’ve obtained a clear, contestable proposition from the quack, you must then ask them what the evidence is for their proposition. Asking the quack for evidence is perfectly fair. Don’t let them try to convince you otherwise. They bear the burden of proof, and the onus is solely on them to demonstrate the merits of their proposition.
If they actually manage to render an argument, you can proceed to **step 3.1**. If they refuse to render an argument, proceed to **step 6**.
## Step 3.1: Identify the type of inference
Basically there are two broad categories of inference someone can make. Either their inference is going to be a posteriori or it is going to be a priori. Both a posteriori and a priori inferences are forms of deductive arguments. However, in contrast to an a priori inference, an a posteriori inference requires synthesizing prior experience of the world. The truth or falsity of an a posteriori inference will rest on empirical evidence.
## A Posteriori
> **P1)** An unmarried person is more likely to be depressed.
> **P2)** Jim is unmarried.
> **C)** Therefore, Jim is more likely to be depressed.
An a priori inference doesn’t require prior experience of the world, and the truth of falsity of the inference will hinge on the definitions or meaning of the terms used.
## A Priori
> **P1)** An unmarried man is a bachelor.
> **P2)** Jim is an unmarried man.
> **C)** Therefore, Jim is a bachelor.
For the purposes of this article, we’ll just be focusing on a posteriori inferences. If you are interested in how to address a priori inference, please refer to the included dialogue tree at the top of this section. Otherwise, proceed to **step 3.2**.
## Step 3.2: Check for modal claims
Generally speaking, if their inference is a posteriori and it contains a modal operator, they’re likely to be referring to a physical modality (but they could be referring to another modality).
If they are invoking an operator that is related to impossibility, proceed to **step 3.3**. Once again, if the invoke a modal operator related to possibility, then it’s probably worthwhile to just agree and disengage, as it’s typically just trivial to claim that things are possible. If there are no modal operators in their claim, proceed to **step 3.4**.
## Step 3.3: Ask which law is broken on their stated modality
The overall procedure is identical to **step 2.3**. If the quack can’t unpack the claim or they refuse to amend the claim, then proceed to **step 6**. If they actually manage to unpack their the modality and the law that’s violated on that modality, and it’s convincing to you, you should probably just concede.
## Step 3.4: Evaluate their empirical evidence
During this step, it pays to have some critical appraisal skills to fall back on, but it’s not necessary. The most important thing to remember is that you have to be honest about what you find convincing and you have to be honest enough to amend your views according to new evidence.
Keep the definitions of evidence that we discussed earlier in mind going forward. After the quack has rendered their evidence, examine it carefully. In the vast majority of cases it will be unclear how this evidence should be more expected on their hypothesis as opposed to some other hypothesis, even another hypothesis that you literally dream up on the spot as a counter explanation (which we will be covered in later steps). Consider the following proposition:
> “Carnivorous diets made humans more intelligent.”
A bold proposition like this certainly requires substantial evidence, which is perfectly reasonable to request of the quack. Let’s say you ask for the evidence, and the quack renders something along the lines of this in response:
> “Because plant agriculture decreased human brain size by 11%.”
Bearing all of the above in mind, critically evaluate their evidence and think hard about the assumptions it makes. If you don’t find anything objectionable, it is perfectly OK to admit that sufficient evidence for the proposition has been rendered, and that you concede the proposition on that basis.
If the quack managed to render a goalpost to you in **step 2.4**, then proceed to **step 3.5**. If they did not render a goalpost to you, and their evidence is not convincing to you, then proceed to **step 5**.
## Step 3.5: Compare their evidence to their goalpost
Check to see if their empirical evidence is actually consistent with the goalpost they described. If their empirical evidence is either consistent or stronger than the sort of evidence described in their goalpost, then simply proceed to **step 5**. However, if their empirical evidence is _weaker_ than the sort of evidence they described in their goalpost, then the quack has just straightforwardly contradicted themselves and you can proceed straight to **step 6**.
## Step 5: Propose an alternative hypothesis
As with **step 3.4**, it pays to have some critical appraisal skills, but it is again not actually necessary. The only thing that you really require to proceed with this step is the creativity to dream up alternative hypotheses. But not just any alternative hypothesis. Your alternative hypothesis has to make the same prediction as their hypothesis, but also be mutually incompatible with their hypothesis.
In reference to the evidence presented in **step 3.4**, while this evidence may sound hilarious to us, it may actually be convincing to some people, so contesting it is probably still a good idea. Don’t dismiss it outright. At this point, it may be true that the quack has already put their foot in their mouth. But continue to be a fair interlocutor, and give the quack an opportunity to either swallow it or pull it out. Hit them back with an alternative hypothesis that makes the same prediction:
> “Perhaps agriculture actually increased the efficiency of the human brain, and there was actually no change in intelligence.”
Remember that it’s not at all clear why plant agriculture decreasing human brain size by 11% would necessarily, or even probably, be evidence for carnivorous diets making humans more intelligent. Perhaps plant agriculture increased the efficiency of our brains, such that our brains could achieve the same level of intelligence using less tissue. So, why would plant agriculture decreasing human brain size by 11% be more expected on the quack’s hypothesis as opposed to your alternative hypothesis?
Now the quack is in a tough position, because he has to actually explain why the evidence in question is more expected on their hypothesis than the one you just cooked up on the spot. In the vast majority of cases, the quack will not be able to produce any compelling reason for why one hypothesis has more explanatory power over the other.
Notice as well that we’re not asking them to substantiate their evidence, and we’re not scrambling to find studies of our own to refute their evidence. We’re just asking the quack why their hypothesis is more virtuous than ours. This is not a strategy that virtually any quacks are going to be prepared to deal with (because if they were, they probably wouldn’t propose stuff as stupid as they typically do).
In the vast majority of cases, merely asking the quack why the evidence in question is more expected on their hypothesis, rather than your own hypothesis, will lead them to fold like a chair, right on the spot.
If your interlocutor actually can demonstrate that the evidence they brought to the table is indeed more expected on their hypothesis than some alternative hypothesis, you have a few options. You retry **step 5**, and attempt to create another alternative hypothesis that will challenge the strength of their evidence even harder. Alternatively, you can concede the proposition for the time being and come back to it later, even if you don’t find it convincing. Just be honest. Conceding the debate doesn’t mean that your interlocutor was correct.
Remember, you can always be agnostic (even about your own alternative hypotheses), and try to remember that you don’t need to affirm the negation of their proposition. The onus is not on you to prove anything in this exchange. Not a goddamn thing. Remember that.
Assuming they’re unable to answer your question, it must be reiterated that it is very important to never allow the quack to flip the burden of proof on you. It’s their proposition, and the burden of proof is theirs and only theirs. A tip for identifying when the quack is trying to flip the burden of proof is when they attempt to ask questions that are not clarifying questions. Any question other than a clarifying question is always a dodge when you hold the line of questioning, and your line of questioning is only over when you’ve obtained all of the answers you require.
If the quack rejects your alternative hypothesis, proceed to **step 5.1**. If the quack accepts your alternative hypothesis and admits that he has no justification for why their evidence is more expected on their hypothesis than your hypothesis, then proceed to **step 6**.
## Step 5.1: Ask what’s wrong with your alternative hypothesis
Rejecting your alternative hypothesis could mean a couple different things. Either they’re calling the alternative hypothesis itself into question, or they are going to explain why their evidence is more expected on their hypothesis than your hypothesis. If they’re rejecting your alternative hypothesis, just ask them for the explanation. If their explanation is convincing to you, there are a couple of different options. You can either concede or return to **step 5** and press them with an even stronger hypothesis. It just depends on how comfortable you are giving it another shot.
Alternatively (and altogether more likely), if they can’t give you a clear explanation as to why their evidence is more expected on your hypothesis, then proceed to **step 6**.
###### PHASE THREE
###### STEAMROLLING
## Step 6: Demand that they concede their proposition
Once you find yourself in a position where you have not conceded the proposition and the quack is unable to render an argument in favour of the proposition, you’ve obtained all you need from the quack to begin steamrolling. Just refuse to proceed until you obtain either an argument for the proposition or a concession on the proposition itself. Anything other than these outcomes is not satisfactory. Don’t accept any “agree to disagree” cop-outs. Hold their feet to the fire and press the issue.
The quack may try to spiral down on some tangent that isn’t germane to any of the previous questions you have asked them. In this event, redirect them immediately after their ramble. If their ramble is excessively long, feel free to cut them off. Tangents waste time, and it’s inappropriate to let tangents go to completion. Most quacks are bad faith actors, so concessions are too optically intolerable for them and rendering an argument for their claim is usually beyond their capabilities. Most will simply just disengage once you’ve gotten this far.
Lastly, we have to talk about an exceptionally rare outcome you will almost never encounter on your quack smashing journey— the quack concedes the proposition. Congratulate and praise the quack for their honesty. In fact, they may not even be a quack anymore. You may have rescued them from utter insanity, and that’s certainly worth a pat on the back for both of you.
Thanks for reading! If you enjoy my writing and want more content like this, consider pledging to either my [Patreon](https://www.patreon.com/thenutrivore) or my [LiberaPay](https://liberapay.com/TheNutrivore/)! Alternatively, I accept crypto as either ETH, MATIC, or BTC at 0xdfcb7e3D00EdC138300E9Ad122dB0ebE85426a65!
## References:
[1] ‘Theoretical Virtues in Science’. Obo, Accessed 24 Dec. 2022. [https://www.oxfordbibliographies.com/display/document/obo-9780195396577/obo-9780195396577-0409.xml](https://www.oxfordbibliographies.com/display/document/obo-9780195396577/obo-9780195396577-0409.xml).
[2] Schick, Theodore, and Lewis Vaughn. How to Think About Weird Things: Critical Thinking for a New Age: Seventh Edition. McGraw-Hill Higher Education, 2013. [https://books.google.ca/books/about/How_to_Think_About_Weird_Things_Critical.html?id=YR4iAAAAQBAJ&redir_esc=y](https://books.google.ca/books/about/How_to_Think_About_Weird_Things_Critical.html?id=YR4iAAAAQBAJ&redir_esc=y)

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[Brian Sanders](https://www.sapien.org/brian) is an entrepreneur and filmmaker who advocates for an "ancestral" diet he has coined the Sapien Diet™. This diet is characterized by high intakes of animal products and considerably strict abstinence from processed food consumption. His diet is supposedly based on the teaching of [Weston Price](https://en.wikipedia.org/wiki/Weston_A._Price), a dentist and nutritional anthropologist of the early 1900s who also advocated for the consumption of animal products. Right off the bat, we can tell that Brian's diet is marinated in quackery, as Price's methods and inferences were [questionable at best](https://quackwatch.org/related/holisticdent/).
Whatever the case, Brian publicly advocated for his diet back in 2020 during a talk at [Low Carb Down Under](https://lowcarbdownunder.com.au) entitled ["Despite what you've been told COWS CAN SAVE THE WORLD"](https://www.youtube.com/watch?v=VYTjwPcNEcw). In this talk, he describes the benefits and virtues of animal food production and consumption, and also touches on the supposed pitfalls and fallacies of veganism and plant-based diets. He structures his talk into three sections, which serve as direct rebuttals to three propositions that he characterizes as mainstream:
- Red meat is harmful to human health.
- Cows are harmful to the environment.
- It's unethical to kill animals for food.
Brian's talk is riddled with half-truths, misunderstandings, bald-faced lies, and other idiocy. To go through everything individually would take far too long, so in this article I will only be addressing the primary points that Brian makes throughout his presentation. Some of the quotes that I will be referencing will be paraphrased to account for Brian's unclear manner of speaking, but I nonetheless believe that I have represented his beliefs fairly. So, let's dive in!
###### Heath Claims
**Claim #1 (**[**4:52**](https://youtu.be/VYTjwPcNEcw?t=292)**):**
> "Hong Kong eats the most amount of meat and animal foods in the world and has the longest life expectancy."
**Post-hoc Fallacy**
This is just a post-hoc fallacy and a misunderstanding of the evidence being presented. Firstly, Brian's argument doesn't even get off the ground unless there is an assessment of what is causing the differences in longevity, and how the mortality stats are calculated. In this case, Brian is suggesting temporal connections that can't be verified to exist based on the data provided. More to the point, differential ecological associations between populations can't really tell us anything about differences in outcomes between individuals consuming the least meat versus individuals consuming the most meat.
For example, there is a positive ecological association between smoking and life expectancy [[1]](http://www.thefunctionalart.com/2018/07/visualizing-amalgamation-paradoxes-and.html). But, we wouldn't infer from this association that cigarette consumption increases longevity. Those sorts of inferences are what prospective cohort studies and randomized controlled trials are for, as they are actually equipped to assess individual-level exposure and outcomes.
**Base Rate Fallacy**
According to Brian's source, Hong Kong's meat intake has been steadily increasing and didn't reach UK-levels of intake in 1972 and US-levels of intake in 1967 [[2]](https://www.nationalgeographic.com/what-the-world-eats/). If the hypothesis is that meat causes higher mortality via chronic disease, then people who started eating that much meat during those time periods would barely even be old enough to contribute substantially higher mortality statistics at the time of this report anyway. So, while it's true that Hong Kong now eats a lot of meat and enjoys longer lifespans, Brian is not appreciating the base rate of historical meat consumption for this population.
As an aside, it is also interesting to note that those in Hong Kong who followed a non-ancestral "Portfolio diet" (which is characterized by low saturated fats, sodium, and dietary cholesterol, as well as higher plant proteins, vegetable oils, high fruits, vegetables, and whole grains) were at a lower risk of dying from all causes, as well as dying of CVD or cancer [[3]](https://pubmed.ncbi.nlm.nih.gov/34959911/). In fact, multiple sensitivity analyses were done to remove the possibility for reverse causality, and the reductions in risk are still apparent.
**Claim #2 (**[**5:13**](https://youtu.be/VYTjwPcNEcw?t=313)**):**
> "There is an inverse association between red meat and total mortality in Asian populations."
**Red Herring**
The aggregated difference in the lowest to highest red meat intake in this pooled analysis was ~60g/day, which is approximately two bites [[4]](https://pubmed.ncbi.nlm.nih.gov/23902788/). It's unclear how this is capable of informing our judgements about the health value of red meat in the context of something like a Sapien Diet™. Not only that, but the contrast is occurring primarily at lower levels of intake.
Generally speaking, contrasts in red meat intake exceeding 80-100g/day are typically required on a per-cohort basis to reveal the increased risk of cardiovascular disease mortality or even all-cause mortality. Contrasts that fall below this threshold often do not provide for the statistical power that is necessary to obtain a statistically significant estimate.
Brian's own reference also confirms that meat intake in Asian populations is generally quite a bit lower than the United States.
> “Per capita beef consumption has decreased to some degree in the past decade in the United States but still remains substantially higher than that in Asian countries. Beef consumption increased in China, Japan, and Korea from 1970 to 2007.”
In actuality, when we select Asian populations with the widest contrasts in red meat intake, with sound multivariable adjustment models, appropriate population ages, and adequate follow-up time, we see the increase in total mortality with red meat very clearly [[5]](https://pubmed.ncbi.nlm.nih.gov/33320898/). Even when diet and lifestyle covariates are balanced between ranges of intake. These results are also consistent with results we see in American cohorts that also balance diet and lifestyle covariates reasonably well, such as the Nurse's Health Study [[6]](https://pubmed.ncbi.nlm.nih.gov/22412075/).
**Potential Contradiction**
Additionally, Brian has [stated publicly](https://twitter.com/FoodLiesOrg/status/1419347985935257601?s=20&t=_2uz8-vTlkgxnFPP4DCqtg) that steak is a good source of iron and can protect against iron deficiency. This claim is in accord with the available evidence on red meat consumption and iron deficiency anemia, with unprocessed red meat associating with a 20% decreased risk of anemia in the UK Biobank cohort [[7]](https://pubmed.ncbi.nlm.nih.gov/33648505/). Interestingly, unprocessed red meat was also associated with a statistically significant increase in the risk of many other diseases as well.
If the methods were sensitive enough to detect the inverse association with iron deficiency anemia, why not also conclude that the methods were also sensitive enough to detect the effect on heart disease as well? Why form differential beliefs about the causal nature of these associations?
Furthermore, the association between red meat intake and heart disease is observable when meta-analyzed as well [[8]](https://pubmed.ncbi.nlm.nih.gov/34284672/). For every 50g/day increase in red meat intake, there was a statistically significant dose-dependent relationship between red meat intake and heart disease.
Almost all of the most highly powered studies found positive associations between heart disease risk and red meat. Altogether, those studies also had the highest contrast in red meat, with Asian countries having the lowest contrast, as mentioned earlier. The majority of the included studies included adjustments for diet quality, used validated food frequency questionnaires, and had adequate follow-up time. The greatest increase in risk was found among studies with follow-up times exceeding 10 years. Removing all of the more poorly powered cohorts leaves us with a remarkably consistent relationship overall.
This one change results in a 38.3% attenuation in the I², going from 41.3% to 13%. Which suggests that of the variance that was attributable to heterogeneity, poor statistical power could explain about 68% of it.
Lastly, when cohort studies from around the world are meta-analyzed, we see the same thing for all cause mortality [[9]](https://pubmed.ncbi.nlm.nih.gov/24148709/). Overall, there is a non-significant increase in all-cause mortality risk when comparing the lowest red meat intakes to the highest red meat intakes. Whiteman, et al. (1999) was the only study that found a statistically significant decrease in risk, and is the sole reason for the non-significant finding.
However, Whiteman, et al. also had one of the shortest follow-up times, one of the youngest populations (and thus one of the lowest death rates), and used a very poor adjustment model (only adjusting for three confounders). If a leave-one-out analysis is performed that excludes Whiteman, et al., a different picture is painted.
Anybody who wishes to complain about this reanalysis is free to try to explain to me why increasing the potential for bias with poor multivariable adjustment is a desirable thing. But, it probably doesn't matter anyway. This meta-analysis was published in 2014, and more cohort studies have been published since then. If we add those results to the original forest plot conducted by Larsson et al., we would still get significant results.
**Claim #3 (**[**5:22**](https://youtu.be/VYTjwPcNEcw?t=322)**):**
> "We cannot use correlational studies to try to say that meat is bad."
**Category Error**
It's unclear what this means. As per the Duhem-Quine thesis, all scientific findings are correlational in one way or another [[10]](https://en.wikipedia.org/wiki/Duhem%E2%80%93Quine_thesis). As such, the state of being "correlational" is not a differential property between any two modes of scientific investigation. For example, intervention studies are a form of observational study, because you're observing what happens when you intervene. So this objection just seems like confusion, because if there ever was a study that showed meat to be "bad", it would be straightforwardly correlational in nature. Assuming that what Brian means by "correlational studies" is actually just nutritional epidemiology, even that would still be wrong.
In 2021, Shwingshakl et al. published an enormous meta-analysis that compared the results of 950 nutritional randomized controlled trials to results from 750 prospective cohort studies [[11]](https://pubmed.ncbi.nlm.nih.gov/34526355/). In the aggregate, results from nutritional epidemiology are consistent with results from nutritional randomized controlled trials approximately 92% of the time when comparing intakes to intakes (omitting supplements).
Across 23 comparisons of meta-analytically summated findings from both bodies of evidence, only 2 comparisons showed discordance. This means that nutritional epidemiology tends to replicate in randomized controlled trials in the supermajority of cases.
If not randomized controlled trials, I have no idea where Brian plants his goalpost for high evidential quality. Nevertheless, current evidence suggests that nutritional epidemiology is highly validated methodology if randomized controlled trials are used as the standard. If one places high credence in randomized controlled trials, it's unclear why they wouldn't also place high credence in nutritional epidemiology.
**Claim #4 (**[**5:36**](https://youtu.be/VYTjwPcNEcw?t=336)**):**
> "73% of hunter gatherers get over 50% of their diet from animal foods."
**Non Sequitur**
I'm not sure why we should care. If this isn't cashing out into some sort of health claim, then it seems very much like a non sequitur. Assuming this is implying something about the health value of hunter-gatherer diets, it is also misleading. I've discussed [here](https://www.the-nutrivore.com/post/should-we-eat-like-hunter-gatherers) why positions like this ultimately fail.
**Claim #5 (**[**5:51**](https://youtu.be/VYTjwPcNEcw?t=351)**):**
> _"We have beef as this highly bioavailable, easily digestible protein, and beans is one example of something that is touted as a pretty high protein food. But this is not the case."_
**False Claim**
This is just whacky, and it seems to be based on data from a 1950s textbook to which I cannot get access. However, we don't really need to in order to address this claim. Let's take a look at this table that Brian has generated.
First of all, if these two foods are weight-standardized, then the protein content of navy beans only makes sense if the navy beans were considered raw. Navy beans can't even be consumed raw because they're hard as fucking rocks. So, immediately this table is potentially misleading, having possibly presented an unrealistic comparison between these two foods. But, that's not the most egregious part of Brian's table. It's actually completely unnecessary to consider digestibility and biological value separately as Brian has [[12]](https://pubmed.ncbi.nlm.nih.gov/26369006/).
> _"The PDCAAS value should predict the overall efficiency of protein utilization based on its two components, digestibility and biological value (BV; nitrogen retained divided by digestible nitrogen). The principle behind this approach is that the utilization of any protein will be first limited by digestibility, which determines the overall amount of dietary amino acid nitrogen absorbed, and BV describes the ability of the absorbed amino acids to meet the metabolic demand."_
Biological value is inherently captured by both of the standard protein quality scores, the protein digestibility-corrected amino acid score (PDCAAS) and the digestible indispensable amino acid score (DIAAS). This means that if you want to represent all the things that matter for a given protein in isolation (such as digestibility, biological value, and limiting amino acids), all you need is either a PDCAAS or DIAAS value for the proteins in question. But, the DIAAS is probably better.
Aggregating DIAAS data across multiple protein foods paints a completely different picture than the one that Brian cobbled together [[13]](https://pubmed.ncbi.nlm.nih.gov/28748078/)[[14]](https://pubmed.ncbi.nlm.nih.gov/33333894/)[[15]](https://pubmed.ncbi.nlm.nih.gov/34476569/)[[16]](https://onlinelibrary.wiley.com/doi/full/10.1002/fsn3.1809). Some plant proteins actually do quite well. But what are these numbers really representing? Ultimately the scores are going to be truncated by limiting amino acids more than any other parameter, and pairing complementary proteins will increase the DIAAS value [[17]](https://pubmed.ncbi.nlm.nih.gov/34685808/). In fact, this is also true of the PDCAAS, as combining different lower-scoring plant proteins will often result in perfect scores [[18]](https://www.2000kcal.cz/lang/en/static/protein_quality_and_combining_pdcaas.php).
If beef is awesome in virtue of it getting a perfect score for protein digestibility, biological value, and limiting amino acids, then navy beans and wild rice must also be awesome too. If not, then I don't know what the hell Brian is talking about, or why he even brings the point up. It's also worth pointing out that certain animal foods, like collagen, actually score a zero on the PDCAAS as well.
As an aside, even if plant protein was generally inferior to animal protein by some evaluative standard (such as the PDCAAS or DIAAS), it would not necessarily mean that it would be more desirable to consume animal protein over plant protein. That would depend on one's goals. In fact, animal protein is associated with a number of chronic diseases in a dose-dependent manner, whereas plant protein is inversely associated, also in a dose-dependent manner [[19]](https://pubmed.ncbi.nlm.nih.gov/32699048/). This also holds true for Japanese populations, by the way [[20]](https://pubmed.ncbi.nlm.nih.gov/31682257/).
**Claim #6 (**[**6:35**](https://youtu.be/VYTjwPcNEcw?t=395)**):**
> "744 studies were excluded from consideration in the WHO's evaluation of meat as a carcinogen."
**Red Herring**
Here, Brian is referring to an analysis on red meat and colorectal cancer risk that was conducted by the International Agency for Research on Cancer (IARC) [[21]](https://pubmed.ncbi.nlm.nih.gov/26514947/). If you dig into the IARC's methods, you can see that they had very specific, sound inclusion-exclusion criteria, which involved selecting cohort studies with the widest contrasts in red meat intake, clear definitions, sufficient event rates and participant numbers, and adequate adjustment models.
> "A meta-analysis including data from 10 cohort studies reported a statistically significant dose-response association between consumption of red meat and/or processed meat and cancer of the colorectum. The relative risks of cancer of the colorectum were 1.17 (95% CI, 1.05-1.31) for an increase in consumption of red meat of 100 g/day and 1.18 (95% CI, 1.10-1.28) for an increase in consumption of processed meat of 50 g/day. Based on the balance of evidence, and taking into account study design, size, quality, control of potential confounding, exposure assessment, and magnitude of risk, an increased risk of cancer of the colorectum was seen in relation to consumption of red meat and of processed meat."
This is very sensible methodology for anyone familiar with epidemiology. Additionally, this is not the only reason Brian's claim is misleading, because there are not 744 cohort studies or RCTs combined on this question. Full stop. I can only imagine that he is referring to mechanistic studies or other weaker forms of evidence. He's never fully unpacked this claim, to my knowledge.
**Claim #6 (**[**7:05**](https://youtu.be/VYTjwPcNEcw?t=425)**):**
> _"There were 15 studies showing that red meat was good and 14 studies showing that red meat was bad. I mean, it's basically a toss-up."_
**Red Herring**
Again, the IARC had very strict inclusion-exclusion criteria, and of the studies that met those criteria, the majority of them found statistically significant associations between red meat and colorectal cancer. This is after multivariable adjustment for known confounders and covariates, in populations that we'd expect to have an increased risk. It's straight up expected that not all of the available studies on a given research question will be included in a meta-analysis.
**Red Herring**
Brian then goes on to claim that the results are a toss-up simply because there were 15 studies ostensibly showing that red meat was "good" and 14 studies ostensibly showing that red meat was "bad". To imply that this is necessarily a "toss up" is just pure confusion. Even if you have double the studies showing that red meat is "good", that doesn't necessarily mean there is a lower probability that red meat is "bad". It depends on the strength of the studies included. Consider this forest plot.
Here we see that despite the fact that there is a 2:1 ratio of studies that show a decreased risk with red meat to studies that show an increased risk with red meat, the summary effect measure still points toward a statistically significant increase in risk. This is because not every study has equal power or precision. Some findings are just less certain than others.
**Claim #7 (**[**7:22**](https://youtu.be/VYTjwPcNEcw?t=442)**):**
> "The risk factor of cancer from meat is 0.18%, whereas the risk factor of cancer from smoking is 10-30%."
**Unintelligible**
This is truly bizarre. It's incredibly unclear what Brian is trying to say here, and he was unable to unpack it to me in [our verbal debate](https://www.youtube.com/watch?v=S8p39Gwct1Y), so I'm not even sure he knowns what the fuck he means. His use of the term "risk factor" here makes the utterance appear like a category error. However, if I really stretch my imagination, I may be able to cobble together an interpretation that isn't gibberish.
**Equivocation**
Firstly, this appears to be just a straight up equivocation of cancer types. Colorectal cancer and lung cancer are two different diseases, and the prevalence of these diseases are different in the general population. If Brian's criticism is that the relative risk of lung cancer from smoking is higher than the relative risk of colorectal cancer from red meat, then he's just confused. Massive differences in the magnitude of those effect estimates are expected, as the prevalence of a given disease will determine the maximum possible relative risk [[22]](https://pubmed.ncbi.nlm.nih.gov/21402371/).
Let's take a look at the prevalence of these diseases in Canada [[23]](https://cancer.ca/en/cancer-information/cancer-types.). The prevalence of lung cancer among Canadian non-smokers is 1 in 84 (1.19% prevalence). Prevalence of colorectal cancer, assuming red meat has nothing to do with colorectal cancer, is 1 in 16 (6.25% prevalence). The baseline prevalence of lung cancer is much smaller than the baseline prevalence of colorectal cancer, so comparing the two is dubious.
In the case of lung cancer and colorectal cancer, the maximum possible relative risks would be ~53 and ~16, respectively. So it's not even mathematically possible for the relative risk of colorectal cancer from red meat to even approach the upper bounds for the relative risk of lung cancer from smoking that Brian submitted (assuming he meant 30x and not 30%).
For this reason, it's best that we do an apples to apples comparison. In a massive 2009 analysis by Huxley, et al., which helped inform the IARC's analysis on meat and cancer, 26 cohort studies were included in their meta-analytic summation [[24]](https://pubmed.ncbi.nlm.nih.gov/19350627/). Overall they showed a statistically significant 21% increase in risk of colorectal cancer with unprocessed red meat.
However, they also included an analysis on smoking, which found a statistically significant 16% increase in the risk of colorectal cancer with smoking as well. Yes, that is right— there was a slightly stronger association between red meat and colorectal cancer than there was between smoking and colorectal cancer. But the two were likely non-inferior. Huxley et al. also found around the same magnitude of effect for many other exposures.
What's the symmetry breaker? Why form a causal belief with regards to smoking or physical inactivity or obesity and not red meat? If Brian argues that he doesn't infer causality for any of the exposures with non-inferior effect sizes to red meat, then the appropriate thing to do is honestly just to laugh at his absurdity and move on.
If Brian argues that red meat has never been studied in the context of a junk-free diet, then we could just argue it in the opposite direction. For example, the smoking literature is also notoriously unadjusted for dietary covariates (which is something not many people appreciate about that body of evidence). As such, smoking arguably has never been studied in the context of a meat-free diet either, so perhaps the data on smoking is simply biased by red meat. Again, we need symmetry breakers.
**Claim #8 (**[**7:37**](https://youtu.be/VYTjwPcNEcw?t=457)**):**
> _"Ancestral foods are better than processed foods."_
**Appeal to Nature**
Why should we be using anthropological data about ancestral diets to inform best practice in terms of modern diets for modern humans? And why is the property of being ancestral a reasonable sufficiency criteria for a food to be "better" than processed foods? This seems like a non sequitur.
Favouring whole foods is heuristic, and not a rule. There are plenty of examples of processed foods being superior to whole foods, even foods that we could identify as ancestral. In fact, there are been specific analyses investigating the differential contributions of animal-based foods (red meat, poultry, fish, dairy, and eggs) and ultra-processed foods to disease risk within the context of a health-conscious population [[25]](https://pubmed.ncbi.nlm.nih.gov/35199827/).
Overall, ultra-processed foods and animal foods are non-inferior to one another for CVD mortality and cancer mortality risk. Animal based foods also seem to associate with the risk of endocrine disorders like T2DM, whereas ultra-processed foods did not. Once again, we require symmetry-breakers. Why form the belief that ultra-processed foods increase the risk of these diseases and not animal foods?
###### Environmental Claims
**Claim #9 (**[**10:13**](https://youtu.be/VYTjwPcNEcw?t=613)**):**
> "Grazing agricultural systems are better for the environment and sequester more carbon."
**False Claim**
This claim is as hilarious as it is vague. Firstly, better compared to what? According to Brian's reference (which was an analyses of the association between White Oak Pastures' regenerative grazing methodology and carbon balance) it was assumed that carbon sequestration estimates were exclusively from beef, yet poultry accounted for almost half of the carcass weight (46.5%) of the entire system [[26]](https://www.frontiersin.org/articles/10.3389/fsufs.2020.544984/full). They also can’t even attribute the sequestration to cows because the study was cross-sectional in design.
This study isn't actually investigating temporal changes in soil carbon at all. To make matters worse, the author's darling figure, −4.4kg CO₂-e kg carcass weight−1 per year, was actually just produced from thin air, and the cross-sectional association between years of grazing and soil carbon stocks between pasturelands was just assumed to be reflecting grazing-mediated soil carbon sequestration. Utterly misleading sophistry.
> _"Importantly, if we were to attribute the soil C sequestration across the chronosequence to only cattle, MSPR beef produced in this system would be a net sink of −4.4 kg CO2-e kg CW−1 annually."_
Even just ignoring the fact that this methodology creates mathematically atrocious pigs and chickens in terms of carbon balance in their model, the data provided suggests that 20 years worth of carbon sequestration are roughly equal to three years of plant composting. In second figure of the publication, they show a cross-sectional analysis of seven different degraded lands (previously used for crops) that are in the process of being restored over a varied number of years.
> _"In years 1–3, these fields are minimally grazed and receive 1 cm of compost ha−1 yr−1. After year 3, exogenous inputs (hay and compost) were ceased, and the regeneration strategy shifted toward an animal-only approach, whereby animals were the primary mechanism of improving the land."_
The third dot is roughly equal to that of the seventh dot on the chart, which represents three years of plant composting and 20 years of grazing, respectively. If we're assuming a causal relationship between grazing and soil carbon stock, why not also assume a causal relationship between composting and soil carbon stock?
If composting can increase soil carbon sequestration that much, why are they even trying to argue for grazing agriculture as a solution? It would appear that plant agriculture waste could be a viable solution for restoring these degraded lands as well. This is also just granting that these associations are reflective of soil carbon sequestration over time at all, which they may not be. Again, this analysis is cross-sectional.
It's convenient that the time scale of the investigation by Rowntree, et al. caps out at 20 years, because current literature suggests that there is a soil carbon saturation point at around 20 years, after which pasture grazing systems will yield diminishing returns.
Here we see three different scenarios for soil carbon sequestration rates from grazing agriculture. Even under the most generous estimates (the larger black hashed line), soil carbon sequestration plateaus at around 20 years.
However, current estimates suggest that if we switch to more plant-predominant diets by the year 2050, we could reforest a large proportion of current pastureland, which acts as a substantial carbon sink (~547GtCO2) [[27]](https://www.nature.com/articles/s41893-020-00603-4). The effect of that over 30 years is to neutralize about 15 years of fossil fuel emissions and 12 years of total world GHG emissions.
If we switch to plant-predominant diets by 2050 we could sequester -14.7 GtCO2 per year by reforesting pasture land, compared to other agricultural methods that make use of grazing land for pasture. Merely the introduction of pasture grazing increases land use by almost double compared to a vegan agricultural system [[28]](https://experts.syr.edu/en/publications/carrying-capacity-of-us-agricultural-land-ten-diet-scenarios).
In fact, there are stepwise decreases in the per-person carrying capacity of different agricultural scenarios as more pastureland is included in the model. However, vegan agricultural scenarios were largely comparable to both dairy-inclusive and egg-inclusive vegetarian models.
As mentioned earlier in this article, there are plant agriculture methods that are also touted as "regenerative", that also may have greater soil carbon sequestration potential per hectare than current "regenerative" grazing livestock methods [[29]](https://www.nature.com/articles/ncomms6012). It would be interesting to see a head-to-head comparison of wheat versus meat, using "regenerative" methodology, on soil carbon sequestration overall.
**Claim #10 (**[**13:15**](https://youtu.be/VYTjwPcNEcw?t=795)**):**
> "We have enough land for grazing agricultural systems."
**False Claim**
It has been calculated that even if all grasslands were repurposed for grazing, this could provide everyone on earth with 7-18g/day of animal protein per person on Earth [[30]](https://www.oxfordmartin.ox.ac.uk/publications/grazed-and-confused/). The authors also provided a hyper-idealized, candy-land scenario they also calculated that 80g/day of animal protein per person on Earth. However, this would require all pasturable land on Earth being used. As an aside, the authors also calculated an additional scenario that included waste from plant agriculture, but it probably won't be very relevant to Brian's idealized world, because plant agriculture would be extremely minimal on the Sapien Diet™.
The remaining two scenarios encounter some issues when we think of what would be required to sustain people on meat-heavy diets, because 80g of protein from the fattiest beef still would not provide enough calories per person. We would appear to need multiple planets. But we should use a grass-fed example to do the calculations, so I've chosen White Oak Pastures' ground beef as the example meat. We'll also be multiplying the results by 2.5 to account for the extra land used by rotational grazing and/or holistic management [[26]](https://www.frontiersin.org/articles/10.3389/fsufs.2020.544984/full).
Under no plausible scenario (calculable from the 'Grazed and Confused?' report) would either continuous grazing or rotational grazing be tenable on a global scale. Even if the calorie allotment for animal foods in the EAT Lancet diet was occupied only by grass-fed beef, we'd still be exceeding the carrying capacity of the Earth by 70% for continuous grazing and 325% for rotational grazing. As for Brian's pet diet, the Sapien Diet™, we'd need over 10 Earths in the optimistic plausible scenario.
Essentially, we would need to figure out a way to extend the pasturable land beyond the available land on Earth. Perhaps we could do this by terraforming Mars or ascending to a type 2 civilization on the Kardashev scale by building a megastructure in space, such as a Dyson sphere or an O'Neill cylinder. But, those options don't sound very ancestral at all.
We're not even scratching the surface, though. The authors of 'Grazed and Confused?' likely did not consider the suitability of each grassland in their calculation, because current suitability thresholds are set for crop production, rather than livestock. The issue is that grass itself could be considered a crop, so it's unclear why suitability considerations that have been established for crop production wouldn't also apply to pasture-raised animal production.
The IIASA/FAO define the suitability of a given grassland as a threshold of a 25% ratio of actual yield per acre and potential yield per acre [[31]](https://pure.iiasa.ac.at/id/eprint/13290/). Had these suitability criteria been considered by the authors of 'Grazed and Confused?', their models likely would have produced much smaller estimates. This is because much of the available grassland is either unsuitable or poorly suitable to begin with.
These suitability criteria have been used by livestock agriculture advocates to argue against the scalability of crop agriculture and for the scalability of grazing-based livestock agriculture [[32]](https://www.sciencedirect.com/science/article/abs/pii/S2211912416300013). However, [Avi Bitterman](https://twitter.com/AviBittMD) demonstrated on his [Discord server](https://discord.gg/YtfQNPnk) that these individuals are not symmetrically applying this standard and it would actually turn out that current "regenerative" grazing systems wouldn't be likely to even meet the suitability standards themselves.
According to figures produced by White Oak Pastures, their "regenerative" grazing system is far less efficient than conventional feedlot approaches [[33]](https://blog.whiteoakpastures.com/hubfs/WOP-LCA-Quantis-2019.pdf). Overall, White Oak Pastures uses 150% more land than conventional approaches to yield only about 20% of what a conventional farm can produce, and only 90% of the average slaughter weight.
This would give us a "suitability" estimate of around 7%, which would likely drastically reduce the amount of grassland that would be considered suitable for "regenerative" grazing agriculture as well. It would be doubly important to adhere to this standard when critiquing "regenerative" plant agricultural methods, in order to ensure an apples-to-apples comparison [[29]](https://www.nature.com/articles/ncomms6012).
**Claim #11 (**[**13:54**](https://youtu.be/VYTjwPcNEcw?t=834)**):**
> _"If we don't use all this cropland for corn, wheat, and soy...we can use some of this land for cows."_
**False Claim**
Here, Brian presents us a with figure from the USDA showing the available cropland in the United States as of 2007, and suggests that we simply have enough land for "regenerative" grazing. No analysis or even conceptual model of how this could be done was actually provided. He just expects us to take it for granted that the claim is true. But is it actually true?
As with the issues for this narrative that were entailed from the land requirement estimates detailed in the 'Grazed and Confused?' report, this narrative again encounters similar issues here. Firstly, a complete grazing agriculture scenario has been modeled, and the results suggest that the United States wouldn't get anywhere close to plausibly being able to meet their current demand for beef with grazing agriculture [[34]](https://iopscience.iop.org/article/10.1088/1748-9326/aad401). We'd simply need more land. About 30% more land.
> _"Increases in cattle population, placements, and slaughter rates are demonstrated in figure 2. The increased slaughtering and placement numbers would also require a 24% increase in the size of the national beef cow-calf herd, proportional to the increased annual grass-finishing placement rate, in order to provide additional cattle to stock the grass-finishing stage. Increases in both the cow-calf herd and the grass-finishing population together would result in a total increase to the US cattle population of an additional 23 million cattle, or 30% more than the current US beef cattle population as a whole"_
If Brian wants to criticize vegans for indulging idealized pie-in-the-sky fantasies, what in the sweet holy blue fuck is this shit? The United States can't maintain their current demands for beef with the system that Brian is proposing. This is doubly problematic if you consider that the White Oak Pastures model for which Brian advocates probably requires even more land than the conventional grazing methods included in the above model. This means that 30% could very well be an underestimate.
###### Ethical Claims
**Claim #12 (**[**19:11**](https://youtu.be/VYTjwPcNEcw?t=1151)**):**
> _"Vegans kill animals too. It's death on a plate, there's just no blood."_
**Appeal to Hypocrisy**
It's not clear what point this is trying to make. It seems like a failed appeal to hypocrisy to me. But, let's try to tackle the proposition in the most charitable way possible. Let's assume that Brian means to say that the Sapien Diet™ leads to fewer animal deaths than vegan diets that rely on plant agriculture (which is a claim that he has made before). In this case, this is just an empirical claim and needs to be supported by some sort of evidence.
In Brian's presentation, he supports this claim with a study of wood mouse predation after harvest, which showed that up to 80% of mice were preyed upon by predators upon the harvesting of cereal crops [[35]](https://www.sciencedirect.com/science/article/abs/pii/000632079390060E?via%3Dihub). What Brian isn't taking into account is that this can actually be used to are for less mouse predation on cropland as opposed to pastureland. Let me explain.
If you cut down your crop, you will expose the mice to predation. This is true. However, this also applies to pastureland. On pastureland, there is no substantial amount of tall forage that mice can use for shelter. The mice are exposed all year round. Which actually allows for the possibility that cropland could temporarily shelter mice from predators in a way that pastureland can't.
Furthermore, during [my debate](https://www.youtube.com/watch?v=S8p39Gwct1Y) with Brian, his cited evidence was the single cow that was killed when he paid a visit to his friend's cattle farm. Needless to say, this is not very good evidence, and this is not the evidence we will be using to steelman Brian's position. Instead, let's actually look at literature that compares the wildlife carrying capacity of plant verses grazing agricultural scenarios.
In 2020, Tucker et al. published a comprehensive comparative analysis of mammalian populations across a number of human-modified areas, such as cropland and pastureland [[36]](https://onlinelibrary.wiley.com/doi/full/10.1111/ecog.05126). Overall, their findings suggest that there is higher taxonomic diversity with increasing pastureland as opposed to increasing cropland.
In the absence of countervailing data, this actually counts against the hypothesis that pastureland entails less animal death than cropland. This is because increasing taxonomic diversity implies a higher number of trophic strata. A higher number of trophic strata implies higher levels of predation. Higher levels of predation thus imply higher levels of animal death. The land with the lesser carrying capacity should probably be assumed to entail less death.
**Red Herring**
Even if we granted Brian that pastureland entailed fewer animal deaths than cropland, it's not clear why vegans should necessarily care. If veganism is understood to be a social and politic movement that aims to extend human rights to animals when appropriate, it's not clear how the deaths entailed from cropland would be incompatible to those goals. In fact, we'd likely tolerate the killing of people who threatened our food supply in comparable ways as well.
For example, if our food security was threatened by endless armies of humans with the intelligence of fieldmice or insects and we had no practical means of separating them from our food without killing them, I don't think we'd consider killing them to be a rights violation. In fact, we'd likely assume a similar defensive posture and similarly tolerate the loss of human life if a foreign country was also threatening to destroy our food. I doubt we'd even consider the enemy deaths entailed from such a defensive posture to constitute a rights violation. We have the right to defend our property against assailants, and I doubt Brian would even deny this himself.
**Claim #13 (**[**19:19**](https://youtu.be/VYTjwPcNEcw?t=1159)**):**
> _"There is no life without death. This is how nature works...animals in nature either starve to death or are eaten alive...the animals are going to die either way, and it's not a good death...billions of people rely on animals for their livelihood."_
**Potential Contradiction**
This proposition is simple to address. If Brian believes that we are ethically justified in breeding sentient animals into existence for the explicit purpose of slaughtering them for food, but we would not be justified in condemning humans to likewise treatment, he must explain why. This same question can be asked of him regardless of the justification he uses for animal agriculture.
During my debate with Brian, I submitted to him an argument for the non-exploitation of animals, which is essentially just a rephrasing of [Isaac Brown](https://twitter.com/askyourself92)'s [Name the Trait](https://drive.google.com/drive/folders/1tAjU2Bv1tsGbNLA2TfJesgbIh8JKh9zc) argument.
**Definitions:**
**W** := Moral worth
**N** := Exploit it unnecessarily any more than we would for humans
**A** := Absent
**a** := animal
**h** := human
**t** := property
**P1)** For all things, if something has moral worth we should not exploit it unnecessarily any more than we would for humans.
**(∀x(Wx→¬Nx))**
**P2)** If animals don’t have moral worth, then there exists a property that is absent in animals such that if it were absent in humans, humans wouldn’t have moral worth.
**(¬Wa→∃t(Ata→(Ath→¬Wh)))**
**P3)** There doesn’t exist a property that is absent in animals such that if it were absent in humans, humans wouldn’t have moral worth.
**(¬∃t(Ata→(Ath→¬Wh)))**
**C)** Therefore, we should not exploit animals unnecessarily any more than we would for humans.
**(∴¬Na)**
This argument for non-exploitation simply requires one to identify the property that is true of humans that also is untrue of animals, that if true of humans, would cause humans to lose sufficient moral value, such that we’d be justified in slaughtering them for food as well. Brian rejected P3, stating that "consciousness" was the property true of humans, but untrue of animals, such that animals were ethical to exploit for food but humans were not. This fails and entails a contradiction on Brian's part, because consciousness is not a differential property between humans and the animals he advocates farming for food.
Thanks for reading! If you enjoy my writing and want more content like this, consider pledging to my [Patreon](https://www.patreon.com/thenutrivore)!
**References**
[1] Cairo, Alberto. Visualizing Amalgamation Paradoxes and Ecological Fallacies. [http://www.thefunctionalart.com/2018/07/visualizing-amalgamation-paradoxes-and.html](http://www.thefunctionalart.com/2018/07/visualizing-amalgamation-paradoxes-and.html.). Accessed 21 Aug. 2022.
[2] ‘What the World Eats’. _National Geographic_, [http://www.nationalgeographic.com/what-the-world-eats/](http://www.nationalgeographic.com/what-the-world-eats/.). Accessed 21 Aug. 2022.
[3] Lo, Kenneth, et al. ‘Prospective Association of the Portfolio Diet with All-Cause and Cause-Specific Mortality Risk in the Mr. OS and Ms. OS Study’. _Nutrients_, vol. 13, no. 12, Dec. 2021, p. 4360. _PubMed_, [https://doi.org/10.3390/nu13124360](https://doi.org/10.3390/nu13124360.).
[4] Lee, Jung Eun, et al. ‘Meat Intake and Cause-Specific Mortality: A Pooled Analysis of Asian Prospective Cohort Studies’. _The American Journal of Clinical Nutrition_, vol. 98, no. 4, Oct. 2013, pp. 1032–41. _PubMed_, [https://doi.org/10.3945/ajcn.113.062638](https://doi.org/10.3945/ajcn.113.062638.).
[5] Saito, Eiko, et al. ‘Association between Meat Intake and Mortality Due to All-Cause and Major Causes of Death in a Japanese Population’. _PloS One_, vol. 15, no. 12, 2020, p. e0244007. _PubMed_, [https://doi.org/10.1371/journal.pone.0244007](https://doi.org/10.1371/journal.pone.0244007.).
[6] Pan, An, et al. ‘Red Meat Consumption and Mortality: Results from 2 Prospective Cohort Studies’. _Archives of Internal Medicine_, vol. 172, no. 7, Apr. 2012, pp. 555–63. _PubMed_, [https://doi.org/10.1001/archinternmed.2011.2287](https://doi.org/10.1001/archinternmed.2011.2287.).
[7] Papier, Keren, et al. ‘Meat Consumption and Risk of 25 Common Conditions: Outcome-Wide Analyses in 475,000 Men and Women in the UK Biobank Study’. _BMC Medicine_, vol. 19, no. 1, Mar. 2021, p. 53. _PubMed_, [https://doi.org/10.1186/s12916-021-01922-9](https://doi.org/10.1186/s12916-021-01922-9.).
[8] Papier, Keren, et al. ‘Meat Consumption and Risk of Ischemic Heart Disease: A Systematic Review and Meta-Analysis’. _Critical Reviews in Food Science and Nutrition_, July 2021, pp. 1–12. _PubMed_, [https://doi.org/10.1080/10408398.2021.1949575](https://doi.org/10.1080/10408398.2021.1949575.).
[9] Larsson, Susanna C., and Nicola Orsini. ‘Red Meat and Processed Meat Consumption and All-Cause Mortality: A Meta-Analysis’. _American Journal of Epidemiology_, vol. 179, no. 3, Feb. 2014, pp. 282–89. _PubMed_, [https://doi.org/10.1093/aje/kwt261](https://doi.org/10.1093/aje/kwt261.).
[10] ‘Duhem–Quine Thesis’. _Wikipedia_, 19 Aug. 2022. _Wikipedia_, [https://en.wikipedia.org/w/index.php?title=Duhem%E2%80%93Quine_thesis&oldid=1105377595](https://en.wikipedia.org/w/index.php?title=Duhem%E2%80%93Quine_thesis&oldid=1105377595.).
[11] Schwingshackl, Lukas, et al. ‘Evaluating Agreement between Bodies of Evidence from Randomised Controlled Trials and Cohort Studies in Nutrition Research: Meta-Epidemiological Study’. _BMJ (Clinical Research Ed.)_, vol. 374, Sept. 2021, p. n1864. _PubMed_, [https://doi.org/10.1136/bmj.n1864](https://doi.org/10.1136/bmj.n1864.).
[12] ‘Dietary Protein Quality Evaluation in Human Nutrition. Report of an FAQ Expert Consultation’. _FAO Food and Nutrition Paper_, vol. 92, 2013, pp. 1–66. [https://www.fao.org/ag/humannutrition/35978-02317b979a686a57aa4593304ffc17f06.pdf](https://www.fao.org/ag/humannutrition/35978-02317b979a686a57aa4593304ffc17f06.pdf).
[13] Nosworthy, Matthew G., et al. ‘Determination of the Protein Quality of Cooked Canadian Pulses’. _Food Science & Nutrition_, vol. 5, no. 4, July 2017, pp. 896–903. _PubMed_, [https://doi.org/10.1002/fsn3.473](https://doi.org/10.1002/fsn3.473.).
[14] Han, Fei, et al. ‘Digestible Indispensable Amino Acid Scores (DIAAS) of Six Cooked Chinese Pulses’. _Nutrients_, vol. 12, no. 12, Dec. 2020, p. E3831. _PubMed_, [https://doi.org/10.3390/nu12123831](https://doi.org/10.3390/nu12123831).
[15] Fanelli, Natalia S., et al. ‘Digestible Indispensable Amino Acid Score (DIAAS) Is Greater in Animal-Based Burgers than in Plant-Based Burgers If Determined in Pigs’. _European Journal of Nutrition_, vol. 61, no. 1, Feb. 2022, pp. 461–75. _PubMed_, [https://doi.org/10.1007/s00394-021-02658-1](https://doi.org/10.1007/s00394-021-02658-1).
[16] Herreman, Laure, et al. ‘Comprehensive Overview of the Quality of Plant‐ And Animal‐sourced Proteins Based on the Digestible Indispensable Amino Acid Score’. _Food Science & Nutrition_, vol. 8, no. 10, Oct. 2020, pp. 5379–91. _DOI.org (Crossref)_, [https://doi.org/10.1002/fsn3.1809](https://doi.org/10.1002/fsn3.1809).
[17] Han, Fei, et al. ‘The Complementarity of Amino Acids in Cooked Pulse/Cereal Blends and Effects on DIAAS’. _Plants (Basel, Switzerland)_, vol. 10, no. 10, Sept. 2021, p. 1999. _PubMed_, [https://doi.org/10.3390/plants10101999](https://doi.org/10.3390/plants10101999).
[18] _PDCAAS Calculator - 2000KCAL_. [https://www.2000kcal.cz/lang/en/static/protein_quality_and_combining_pdcaas.php](https://www.2000kcal.cz/lang/en/static/protein_quality_and_combining_pdcaas.php). Accessed 24 Aug. 2022.
[19] Naghshi, Sina, et al. ‘Dietary Intake of Total, Animal, and Plant Proteins and Risk of All Cause, Cardiovascular, and Cancer Mortality: Systematic Review and Dose-Response Meta-Analysis of Prospective Cohort Studies’. _BMJ (Clinical Research Ed.)_, vol. 370, July 2020, p. m2412. _PubMed_, [https://doi.org/10.1136/bmj.m2412](https://doi.org/10.1136/bmj.m2412).
[20] Budhathoki, Sanjeev, et al. ‘Association of Animal and Plant Protein Intake With All-Cause and Cause-Specific Mortality in a Japanese Cohort’. _JAMA Internal Medicine_, vol. 179, no. 11, Nov. 2019, pp. 1509–18. _PubMed_, [https://doi.org/10.1001/jamainternmed.2019.2806](https://doi.org/10.1001/jamainternmed.2019.2806).
[21] Bouvard, Véronique, et al. ‘Carcinogenicity of Consumption of Red and Processed Meat’. _The Lancet. Oncology_, vol. 16, no. 16, Dec. 2015, pp. 1599–600. _PubMed_, [https://doi.org/10.1016/S1470-2045(15)00444-1](https://doi.org/10.1016/S1470-2045(15)00444-1).
[22] Sainani, Kristin L. ‘Understanding Odds Ratios’. _PM & R: The Journal of Injury, Function, and Rehabilitation_, vol. 3, no. 3, Mar. 2011, pp. 263–67. _PubMed_, [https://doi.org/10.1016/j.pmrj.2011.01.009](https://doi.org/10.1016/j.pmrj.2011.01.009).
[23] _'Cancer Types'_. Canadian Cancer Society, [https://cancer.ca/en/cancer-information/cancer-types](https://cancer.ca/en/cancer-information/cancer-types.). Accessed 24 Aug. 2022.
[24] Huxley, Rachel R., et al. ‘The Impact of Dietary and Lifestyle Risk Factors on Risk of Colorectal Cancer: A Quantitative Overview of the Epidemiological Evidence’. _International Journal of Cancer_, vol. 125, no. 1, July 2009, pp. 171–80. _PubMed_, [https://doi.org/10.1002/ijc.24343](https://doi.org/10.1002/ijc.24343).
[25] Orlich, Michael J., et al. ‘Ultra-Processed Food Intake and Animal-Based Food Intake and Mortality in the Adventist Health Study-2’. _The American Journal of Clinical Nutrition_, vol. 115, no. 6, June 2022, pp. 1589–601. _PubMed_, [https://doi.org/10.1093/ajcn/nqac043](https://doi.org/10.1093/ajcn/nqac043.).
[26] Rowntree, Jason E., et al. ‘Ecosystem Impacts and Productive Capacity of a Multi-Species Pastured Livestock System’. _Frontiers in Sustainable Food Systems_, vol. 4, 2020. _Frontiers_, [https://www.frontiersin.org/articles/10.3389/fsufs.2020.544984](https://www.frontiersin.org/articles/10.3389/fsufs.2020.544984).
[27] Hayek, Matthew N., et al. ‘The Carbon Opportunity Cost of Animal-Sourced Food Production on Land’. _Nature Sustainability_, vol. 4, no. 1, Jan. 2021, pp. 21–24. _www.nature.com_, [https://doi.org/10.1038/s41893-020-00603-4](https://doi.org/10.1038/s41893-020-00603-4).
[28] Peters, Christian J., et al. ‘Carrying Capacity of U.S. Agricultural Land: Ten Diet Scenarios’. _Elementa_, vol. 2016, no. e000116, 2016. _Experts@Syracuse_, [https://doi.org/10.12952/journal.elementa.000116](https://doi.org/10.12952/journal.elementa.000116).
[29] Gan, Yantai, et al. ‘Improving Farming Practices Reduces the Carbon Footprint of Spring Wheat Production’. _Nature Communications_, vol. 5, no. 1, Nov. 2014, p. 5012. _www.nature.com_, https://doi.org/10.1038/ncomms6012.
[30] ‘Grazed and Confused?’ _Oxford Martin School_, [https://www.oxfordmartin.ox.ac.uk/publications/grazed-and-confused/](https://www.oxfordmartin.ox.ac.uk/publications/grazed-and-confused/). Accessed 24 Aug. 2022.
[31] Fischer, G., et al. _Global Agro-Ecological Zones (GAEZ v3.0)- Model Documentation_. 2012, [http://www.fao.org/soils-portal/soil-survey/soil-maps-and-databases/harmonized-world-soil-database-v12/en/](http://www.fao.org/soils-portal/soil-survey/soil-maps-and-databases/harmonized-world-soil-database-v12/en/).
[32] Mottet, Anne, et al. ‘Livestock: On Our Plates or Eating at Our Table? A New Analysis of the Feed/Food Debate’. _Global Food Security_, vol. 14, Sept. 2017, pp. 1–8. _ScienceDirect_, [https://doi.org/10.1016/j.gfs.2017.01.001](https://doi.org/10.1016/j.gfs.2017.01.001).
[33] ‘Carbon Footprint Evaluation of Regenerative Grazing At White Oak Pastures: Results Presentation’. _Quantis - Environmental Sustainability Consultancy_, [https://blog.whiteoakpastures.com/hubfs/WOP-LCA-Quantis-2019.pdf](https://blog.whiteoakpastures.com/hubfs/WOP-LCA-Quantis-2019.pdf). Accessed 24 Aug. 2022.
[34] Hayek, Matthew N., and Rachael D. Garrett. ‘Nationwide Shift to Grass-Fed Beef Requires Larger Cattle Population’. _Environmental Research Letters_, vol. 13, no. 8, July 2018, p. 084005. _DOI.org (Crossref)_, [https://doi.org/10.1088/1748-9326/aad401](https://doi.org/10.1088/1748-9326/aad401).
[35] Tew, T. E., and D. W. Macdonald. ‘The Effects of Harvest on Arable Wood Mice Apodemus Sylvaticus’. _Biological Conservation_, vol. 65, no. 3, Jan. 1993, pp. 279–83. _ScienceDirect_, [https://doi.org/10.1016/0006-3207(93)90060-E](https://doi.org/10.1016/0006-3207(93)90060-E).
[36] Tucker, Marlee A., et al. ‘Mammal Population Densities at a Global Scale Are Higher in Human‐modified Areas’. _Ecography_, vol. 44, no. 1, Jan. 2021, pp. 1–13. _DOI.org (Crossref)_, [https://doi.org/10.1111/ecog.05126](https://doi.org/10.1111/ecog.05126).

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A recent study has been floating around the nutrition blogosphere for the last year that seems to indicate that early time-restricted feeding (eTRF) has some unique advantages [1](https://www.cell.com/cell-metabolism/fulltext/S1550-4131(18)30253-5). The protocol involved the experimental group eating all their meals within a six hour window starting at 7am. The control group had the same meals spaced out within a twelve hour window, eating on typical breakfast-lunch-dinner schedule. The study was carried out over five weeks.
The results? The eTRF group had lower insulin area-under-the-curve, greater insulin sensitivity, greater β-cell responsiveness, lower hsCRP, lower blood pressure, and reported greater satiety and feelings of fullness. Sounds great, and I won't deny that all of those things are awesome results. However, like everything in life, there's a cost. The eTRF group also had higher triglycerides, higher average blood glucose, higher total cholesterol, lower HDL-cholesterol, higher LDL-cholesterol, and higher levels of an inflammatory cytokine called IL-6. The eTRF group also had wider variations in cortisol, with some of the cohort having higher cortisol than baseline, whereas the control group had no participants with cortisol higher than baseline.
The point here is that we have to be very careful when we claim things have an advantage, because advantages usually come with drawbacks. Often when something seems to have an advantage, those advantages are often equally offset by costs that may not be immediately obvious.
**Key points:** 
- eTRF seems to improve glucose disposal and insulin sensitivity.
- eTRF seems to improve feelings of satiety and fullness. 
- eTRF seems to be anti- and pro-inflammatory in different ways.
- eTRF seems to perturb blood lipids in a negative way.
- eTRF seems to be more physiologically stressful.
**References:**
[1] Elizabeth F. Sutton, et al. Early Time-Restricted Feeding Improves Insulin Sensitivity, Blood Pressure, and Oxidative Stress Even without Weight Loss in Men with Prediabetes. Cell Metab. June 2018. [https://www.cell.com/cell-metabolism/fulltext/S1550-4131(18)30253-5](https://www.cell.com/cell-metabolism/fulltext/S1550-4131(18)30253-5)
#patreon_articles
#nutrition
#disease
#fasting
#clownery

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In continuation of what I wrote [here](https://www.patreon.com/posts/anti-nutrients-1-32218661), I'd like to expand on the role of phytate in the human diet. Last time we talked about its negative effects on mineral bioavailability and absorption. This time we're going to talk about all of the ways in which phytate can be good for us, and why some people would be wise to include it in their diet.
The first reason phytate is great is also the same reason it sucks. It binds minerals and keeps us from absorbing them. But, for some people that's a good thing. People with a condition called hemochromatosis often hyper-absorb the iron in their diet. This can lead to over-saturation of their iron stores, resulting in increased oxidative stress and a number of other unpleasant symptoms. 
It has been speculated that if those with hemochromatosis made an effort to pair their iron-rich foods with their phytate-rich foods, they could very well make traction against their symptoms [1](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4680572/). As a proof-of-principle, I'll direct your attention to a drug called [Deferasirox](https://en.wikipedia.org/wiki/Deferasirox). It operates according to a very similar mechanism to that of phytate, and is used for managing hemochromatosis symptoms.
The second way phytate may be good for us is through its somewhat puzzling ability to reduce advanced glycation end-products (AGEs) in the body [2](http:). Diabetic patients given an oral supplement of a type of phytic acid known as myo-inositol hexaphosphate showed marked reductions in AGEs as a consequence of the intervention. Total iron, ferritin, transferrin, and transferrin saturation did not differ between diet conditions. 
Additionally, the more phytate you consume, the more adept your body becomes at mitigating its negative effects [3](https://www.ncbi.nlm.nih.gov/pubmed/23551617). This is said to be operating through the gut microbiome, which adjusts its composition and enzymatic activity to accommodate for higher levels of phytate in the diet. This isn't to suggest that a persistently high phytate diet leads to phytate being a non-issue. It merely means that the more phytate you consume, the less of an issue phytate appears to be. This is good news, considering that phytate may have a number of additional benefits of in terms of disease prevention and management [4](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5067332/).
**Key points:**
- Phytate may help those with hemochromatosis avoid symptoms of iron overload.
- Phytate seems to help mitigate the burden of AGEs in diabetic patients.
- Eating more phytate may make you better at mitigating its harmful effects.
- There are many promising benefits of phytate that are being actively researched.
**References:**
[1] Robin F. Irvine, et al. There is no ‘Conundrum’ of InsP6. Open Biol. 2015 Nov. [https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4680572/](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4680572/) 
[2] Pilar Sanchis, et al. Phytate Decreases Formation of Advanced Glycation End-Products in Patients with Type II Diabetes: Randomized Crossover Trial. Sci Rep. 2018; 8. [https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6018557/](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6018557/) 
[3] Markiewicz LH, et al. Diet shapes the ability of human intestinal microbiota to degrade phytate--in vitro studies. J Appl Microbiol. 2013 Jul. [https://www.ncbi.nlm.nih.gov/pubmed/23551617](https://www.ncbi.nlm.nih.gov/pubmed/23551617) 
[4] Mariano Bizzarri, et al. Broad Spectrum Anticancer Activity of Myo-Inositol and Inositol Hexakisphosphate. Int J Endocrinol. 2016. [https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5067332/](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5067332/)
#patreon_articles
#nutrition
#disease
#antinutrients
#phytate
#clownery

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Phytates are a class of molecules found in most plants that act to bind certain minerals in our foods. Phytate primarily binds iron, zinc, calcium, manganese, and possibly magnesium. The binding of minerals to phytate inhibits the absorption of these minerals, and explains why we refer to phytate as an anti-nutrient. We're warned by many nutrition gurus to limit the phytate load of our diet, and some even suggest that we avoid plants all together merely on the basis of phytate and compounds like phytate. Here I'll argue that there are nuances to this discussion worth considering before we decide to never eat another legume in our lives.
While it is true that phytate binds certain minerals, I'm not convinced that this alone justifies food avoidance on the basis of phytate alone. In terms of the overall diet, it is true that the mineral to phytate ratio is actually a pretty decent proxy for the nutritional status of certain minerals [1](https://www.ncbi.nlm.nih.gov/pubmed/20715598)[2](https://www.ncbi.nlm.nih.gov/pubmed/22990464). But, it's possible that this data is confounded by low intakes of mineral-rich animal foods. So, how relevant is this to people like us in Western society? 
Most research indicates that the inhibition of mineral bioavailability due to phytate is a function of food pairing, rather than the mere inclusion of phytate-rich foods in the overall diet [3](https://www.ncbi.nlm.nih.gov/pubmed/458251). In other words, the negative effects of phytate have more to do with how you eat rather than what you eat. If you eat oats for breakfast, the phytate from those oats is not at all likely to inhibit any of the minerals from the steak you have for dinner. However if you eat oats and steak in the same meal, it is highly likely that many of the minerals in the steak will not be absorbed.
There is also another layer of nuance. If you must pair phytate-rich foods with mineral-rich foods, there are steps you can take to limit phytate's ability to bind minerals in the gastrointestinal tract. Soaking phytate-rich foods significantly reduces the phytate content of various foods [4](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3550828/).  Adding vitamin C to the meal can improve mineral bioavailability and absorption [5](https://www.ncbi.nlm.nih.gov/pubmed/1989423)[6](https://www.ncbi.nlm.nih.gov/pubmed/2911999). Lastly, as odd as it sounds, adding meat itself might actually enhance the absorption of non-heme iron [7](https://www.ncbi.nlm.nih.gov/pubmed/6538742)[8](https://www.ncbi.nlm.nih.gov/pubmed/12499338).
**Key points:**
- Phytate-rich foods do inhibit the absorption of minerals from other foods in the diet.
- The phytate-to-mineral ratio of the diet is a decent proxy for overall mineral status, but is likely due to inappropriate food pairing.
- Pairing phytate-rich foods with mineral-rich foods is the most relevant consideration regarding the inhibition of mineral absorption.
- Food avoidance on the basis of phytate is probably unjustified.
- Soaking, vitamin C, and perhaps even meat itself can improve the bioavailability of minerals from phytate-rich foods.
- Many phytate-rich foods are healthy and nutritious in ways unrelated to their mineral content.
**References:**
[1] Gibson RS, et al. A review of phytate, iron, zinc, and calcium concentrations in plant-based complementary foods used in low-income countries and implications for bioavailability.  Food Nutr Bull. 2010 Jun. [https://www.ncbi.nlm.nih.gov/pubmed/20715598](https://www.ncbi.nlm.nih.gov/pubmed/20715598) 
[2] Abizari AR, et al. Phytic acid-to-iron molar ratio rather than polyphenol concentration determines iron bioavailability in whole-cowpea meal among young women. J Nutr. 2012 Nov. [https://www.ncbi.nlm.nih.gov/pubmed/22990464](https://www.ncbi.nlm.nih.gov/pubmed/22990464) 
[3] Solomons NW, et al. Studies on the bioavailability of zinc in man. II. Absorption of zinc from organic and inorganic sources. J Lab Clin Med. 1979 Aug. [https://www.ncbi.nlm.nih.gov/pubmed/458251](https://www.ncbi.nlm.nih.gov/pubmed/458251)
[4] Vellingiri Vadivel and Hans K. Biesalski. Effect of certain indigenous processing methods on the bioactive compounds of ten different wild type legume grains. J Food Sci Technol. 2012 Dec. [https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3550828](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3550828/)
[5] Siegenberg D, et al. Ascorbic acid prevents the dose-dependent inhibitory effects of polyphenols and phytates on nonheme-iron absorption. Am J Clin Nutr. 1991 Feb. [https://www.ncbi.nlm.nih.gov/pubmed/1989423](https://www.ncbi.nlm.nih.gov/pubmed/1989423)
[6] Hallberg L, et al. Iron absorption in man: ascorbic acid and dose-dependent inhibition by phytate. Am J Clin Nutr. 1989 Jan. [https://www.ncbi.nlm.nih.gov/pubmed/2911999](https://www.ncbi.nlm.nih.gov/pubmed/2911999) 
[7] Hallberg L and Rossander L. Improvement of iron nutrition in developing countries: comparison of adding meat, soy protein, ascorbic acid, citric acid, and ferrous sulphate on iron absorption from a simple Latin American-type of meal. Am J Clin Nutr. 1984 Apr. [https://www.ncbi.nlm.nih.gov/pubmed/6538742](https://www.ncbi.nlm.nih.gov/pubmed/6538742)
[8] Baech SB, et al. Nonheme-iron absorption from a phytate-rich meal is increased by the addition of small amounts of pork meat. Am J Clin Nutr. 2003. [https://www.ncbi.nlm.nih.gov/pubmed/12499338](https://www.ncbi.nlm.nih.gov/pubmed/12499338)
#patreon_articles
#nutrition
#disease
#antinutrients
#phytate
#clownery

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💻 Hyperblog/Blogs/Patreon/Anti-Nutrients (Part 2), Oxalate.md Executable file
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I recently had the misfortune of skimming through Paul Saladino's book the Carnivore Code. God, what a smoking pile of horseshit that book was. That being said, one thing it did do well was give us a succinct rundown of typical fallacious rhetoric surrounding dietary oxalate.
Essentially the argument revolves around fringe cases of dietary oxalate inducing various pathological states in human beings. He then uses these case reports to buttress an argument against all plant foods, in support of his particular flavour of the carnivore diet. However, if we pick through his citations a completely different picture emerges.
Firstly, he makes the claim that rhubarb has killed people through oxalate poisoning, which is true [1](https://jamanetwork.com/journals/jama/article-abstract/222117)[2](https://pubmed.ncbi.nlm.nih.gov/1288268/). However, these cases specifically involve consumption of rhubarb leaves and/or roots, not stalks. Stalks are also relatively high-oxalate, but do not appear to be associated with toxicity.
It is widely accepted that the leaves of the rhubarb plant are inedible. This is like me saying that puffer fish flesh is dangerous, even when properly prepared. When in reality, the danger is isolated to only a couple different tissues within the fish that can be removed with proper preparation.
His next reference involves a chain-smoking, alcoholic, insulin-dependent diabetic who died from eating sorrel soup [3](https://pubmed.ncbi.nlm.nih.gov/2574796/). He technically didn't die of oxalate poisoning per se, but rather he died due to diabetic acidosis that resulted from oxalate producing acute hypocalcemia. In a normal person, this imbalance is corrected by a subsequent increase in PTH and a restoration of normal blood calcium. However, because he was diabetic, he was uniquely vulnerable to acidosis. So he died.
Additionally, the soup he was consuming had 6-8g of oxalate. Whereas a typical spinach salad, or rhubarb stalk, typically has under 900mg. Upon autopsy, it was discovered that he had chronic kidney disease, liver disease, and oxalate crystals in his kidneys. These are diabetic complications that were exacerbated by eating an almost unheard of amount of oxalate. Not particularly robust evidence.
Similar to his last reference, he then cites another individual with pre-existing morbidities who developed end-stage renal disease after consuming nothing but vegetable smoothies for over a week [4](https://pubmed.ncbi.nlm.nih.gov/29203127/). This woman was consuming nothing but these smoothies, and her average daily intake of oxalate was 1.3g. This is 940% more oxalate than the national average of the United States.
This carnivore quack's next piece of groundbreaking evidence is a case report of a middle-aged, diabetic, hypertensive, alcoholic male who developed renal dysfunction after chronically consuming a quarter pound of peanuts per day [5](https://pubmed.ncbi.nlm.nih.gov/26877960/). Even the authors of the case report seemed skeptical that peanuts alone were responsible for his decline.
He then goes on to cite a case report of three prepubescent children who all began pissing blood after consuming up to a litre of almond milk per day for two years straight [6](https://pubmed.ncbi.nlm.nih.gov/26382627/). In addition to this, one of the children was also consuming moderate amounts of other almond-based products. 
Virtually all of these case reports involve high oxalate foods being processed in one way or another such that the oxalate content of the final product is maximized. The product is then typically dosed at extremely high amounts in individuals with pre-existing illnesses. This isn't evidence in support of a carnivore diet. This is evidence against consuming abnormally high levels of oxalate when you have pre-existing health conditions. This doesn't mean that spinach salads are dangerous. It means that living off of spinach juice is probably a bad idea.
Pretty much the only caveat that I could find was star fruit [7](https://pubmed.ncbi.nlm.nih.gov/16169255/). One star fruit can contain up to 10g of oxalate, and is pretty much the only whole food associated with oxalate-induced complications. However, again, these complications seem to be isolated to individuals with pre-existing health problems.
So, no. Generally speaking, I don't find this to be persuasive evidence against the inclusion of plant foods. Plant foods don't have to be juiced and eaten to the exclusion of everything else in order to be enjoyed, so I don't personally see how his conclusion logically follows from his premises.
**Key points:**
- There are case reports of oxalate-induced illness and death in the literature.
- These case reports almost universally involve individuals with pre-existing health conditions.
- These case reports also almost universally involve juicing, blending, or otherwise processing high oxalate foods.
- Star fruit is the only whole food associated with oxalate-induced illness, but only really in people with chronic kidney disease.
- High oxalate mono-diets are fucking bad for you.
**References:**
[1] Henry Leffmann, M.D. Death from rhubarb leaves due to oxalic acid poisoning. JAMA. Sept. 1919. [https://jamanetwork.com/journals/jama/article-abstract/222117](https://jamanetwork.com/journals/jama/article-abstract/222117)
[2] P Sanz and R Reig. Clinical and pathological findings in fatal plant oxalosis. A review. Am J Forensic Med Pathol. 1992 Dec. [https://pubmed.ncbi.nlm.nih.gov/1288268/](https://pubmed.ncbi.nlm.nih.gov/1288268/) 
[3] M Farré, et al. Fatal oxalic acid poisoning from sorrel soup. Lancet. 1989 Dec 23.  [https://pubmed.ncbi.nlm.nih.gov/2574796/](https://pubmed.ncbi.nlm.nih.gov/2574796/) 
[4] Swetha Makkapati, et al. "Green Smoothie Cleanse" Causing Acute Oxalate Nephropathy. Am J Kidney Dis. 2018 Feb. [https://pubmed.ncbi.nlm.nih.gov/29203127/](https://pubmed.ncbi.nlm.nih.gov/29203127/) 
[5] Hyeoncheol Park, et al. Peanut-induced acute oxalate nephropathy with acute kidney injury. Kidney Res Clin Pract. 2014 Jun. [https://pubmed.ncbi.nlm.nih.gov/26877960/](https://pubmed.ncbi.nlm.nih.gov/26877960/) 
[6] Demetrius Ellis and Jessica Lieb. Hyperoxaluria and Genitourinary Disorders in Children Ingesting Almond Milk Products. J Pediatr. 2015 Nov. [https://pubmed.ncbi.nlm.nih.gov/26382627/](https://pubmed.ncbi.nlm.nih.gov/26382627/) 
[7] Meng-Han Tsai, et al. Status epilepticus induced by star fruit intoxication in patients with chronic renal disease. Seizure. 2005 Oct. [https://pubmed.ncbi.nlm.nih.gov/16169255/](https://pubmed.ncbi.nlm.nih.gov/16169255/) 
#patreon_articles
#nutrition
#antinutrients
#oxalate
#clownery

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💻 Hyperblog/Blogs/Patreon/Are Artificial Sweeteners Fattening.md Executable file
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No health and nutrition echo-chamber is without its ridiculous quackery, but sometimes there are examples of quackery that is so deeply rooted that they transcend the differences between these echo-chambers. For example, the notion that vegetable oils are bad for our health is a piece of nonsensical rhetoric that has managed to find its way into many competing camps. This is also true of the idea that artificial sweeteners cause weight gain— keto quacks believe it, vegan quacks believe it, and even if-it-fits-your-macros gym bro quacks believe it.
We have no shortage of data on this subject. We have meta-analyses of both prospective cohort studies and randomized controlled trials investigating the relationship between artificial sweeteners and weight gain. Let's review some of those findings.
In one meta-analysis investigating the relationship between artificial sweeteners and body composition, there was a statistically significant association between artificial sweeteners and increased BMI [1](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4135487/).
![[1-33.png]]
However, when the same endpoints were measured in randomized controlled trials, the authors' finders were somewhat contradictory. They showed a statistically significant decrease in fat mass, waist circumference, and BMI.
![[1-32.png]]
Another meta-analysis investigating the same question found no overall association between artificial sweeteners and weight gain in prospective cohort studies. When the included studies were stratified by baseline body weight, a statistically significant reduction in weight was observed in overweight or obese subjects [2](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6313893/).
![[1-31.png]]
It would be negligent of me to not also address claims made about artificial sweeteners and insulin secretion in humans. As it has been suggested by some (particularly in the low carb community) that artificial sweeteners could increase weight gain by increasing levels of circulating insulin. Which is an interesting hypothesis, however this hypothesis would have difficulty explaining why artificial sweeteners seem to be superior for weight loss, even when compared to water in human trials [3](https://pubmed.ncbi.nlm.nih.gov/24862170/).
But, let's dig into this question. There is at least one study that directly measured insulin secretion in humans after dosing various types of artificial or non-nutritive sweeteners [4](https://pubmed.ncbi.nlm.nih.gov/27956737/). In this study, subjects were given a preload meal of artificial sweeteners for breakfast, and also consumed artificial sweeteners with a lunch. For both meals, a glucose-based drink was used as the control.
![[Pasted image 20221123153414.png]]
Findings are consistent with another study investigating the relationship between an artificial sweetener called sucralose and changes in plasma insulin [5](https://pubmed.ncbi.nlm.nih.gov/19221011/). Only the glucose control caused a statistically significant increase in plasma insulin. However, the glucose control actually lowered blood glucose compared to baseline after 90 minutes. The effect persisted for two and half hours afterward.
![[Pasted image 20221123153420.png]]
All in all, most of the narratives surrounding artificial sweeteners and weight gain, or even insulin secretion, do not pan out it human experiments. In light of the randomized controlled trial data, some of the associations between overweight and obesity in epidemiology are probably best explained by reverse causality— the artificial sweeteners aren't causing weight gain. The artificial sweeteners associate with overweight and obesity because overweight and obese people are more likely to drink artificial sweeteners. Presumably as a strategy to lose weight.
I have a couple hypotheses as to why artificial sweeteners would be better for weight loss. My first hypothesis is that the sweet taste actually causes people to drink more liquid than they would otherwise drink without the artificial sweeteners. This could actually reduce caloric intake by augmenting the satiety effects of each meal. My second hypothesis is that the artificial sweeteners could satisfy a desire for additional palette entertainment that would otherwise be satisfied with more calorie-dense foods. This could lead to greater diet adherence overall, due to dieters perhaps feeling less deprived.
**Key points**
- It has been suggested that artificial sweeteners cause weight gain.
- Human experiments shows that artificial sweeteners tend to lead to weight loss.
- Artificial sweeteners do no increase plasma glucose or plasma insulin.
**References:** 
[1] [https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4135487/](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4135487/)
[2] [https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6313893/](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6313893/)
[3] [https://pubmed.ncbi.nlm.nih.gov/24862170/](https://pubmed.ncbi.nlm.nih.gov/24862170/)
[4] [https://pubmed.ncbi.nlm.nih.gov/27956737/](https://pubmed.ncbi.nlm.nih.gov/27956737/)
[5] [https://pubmed.ncbi.nlm.nih.gov/19221011/](https://pubmed.ncbi.nlm.nih.gov/19221011/)
#patreon_articles
#nutrition
#disease
#obesity
#artificial_sweeteners
#metabolic_syndrome
#type_2_diabetes

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💻 Hyperblog/Blogs/Patreon/Are Fried Potatoes Unhealthy.md Executable file
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It's likely that most of us will have the intuition that fried potato products like potato chips and French fries are ultra-processed foods that are assuredly bad for out health. However, the evidence suggesting that these foods are actually bad for us isn't the greatest. Let's dive in.
First, let's see if fried potatoes even meet the definition of an ultra-processed food. The NOVA classification system is the closest thing to a standardized method for categorizing foods by their degree of processing [1](https://world.openfoodfacts.org/nova). According to this classification system, fried potatoes would be a "class 3" food, known as a "processed food".
![[1-79.png]]
However, many other foods, that nobody in their right mind would consider ultra-processed, also meet this bar. Foods like pan-fried steak, canned fish, or even cheese would also meet these criteria for categorization as a processed food. So yes, potato products are processed foods, but in terms of their categorization, not any more so than seared broccoli.
Now on to the observational evidence. Firstly, fried potato consumption is strongly associated with an increase in total mortality in one prospective cohort study [2](https://pubmed.ncbi.nlm.nih.gov/28592612/). They discovered a 2.26x increase in the risk of total death over the 8-year follow-up with intakes of fried potato products exceeding three servings per week.
![[1-77.png]]
There are some issues with this study, however. For starters, they did not disclose the mortality endpoints that constituted their total mortality figure, so it's unclear how much of that mortality would actually be relevant. For example, accidental deaths or even suicides could be potentially confounding.
Also, the precise food frequency questionnaire (FFQ) used in this cohort study was an older FFQ with fewer food options. There is a clear limitation with this particular FFQ, due to them lumping potato chips in with other non-potato snacks, as well as only providing a single entry for fried potatoes, which included multiple different products.
![[1-78.png]]
Another issue is the adjustment model. Rather than adjusting for dietary variables individually, they choose to adjust for "adherence to a Mediterranean diet", which could miss some major confounders if not carefully formulated.
Lastly, the cohort itself was a biased sample, as they were subjects from the Osteoarthritis Initiative cohort. This is a cohort that could already be at a higher risk of death, particularly accidental death due to injury. Couple this with the fact that the actual causes of death were not disclosed, and we can see a clear opportunity for confounding.
Contrast this with two cohort studies that used better data collection methods, better adjustment models, larger sample sizes, and populations that were less susceptible to potential bias [3](https://pubmed.ncbi.nlm.nih.gov/27680993/). They found no significant association between the consumption of fried potato products and any outcome related to cardiovascular disease (CVD). 
![[1-76.png]]
Granted, this is not entirely apples-to-apples. It could still be the case that fried potatoes increase the risk of non-CVD related diseases, like cancer or dementia. However, CVD is the endpoint that is most plausible (and the most discussed) with regards to fried potato consumption.
Segueing on to human experiments, I managed to find a single intervention trial using potato chips as the exposure [4](https://pubmed.ncbi.nlm.nih.gov/19158207/). The intervention itself is actually really cleverly designed. Essentially, researchers kept a group of subjects weight stable while feeding two different diets in sequence.
The first diet consisted of 400g of boiled potatoes per day, along with an amount of salt and heated vegetable fat that would equal the amounts of salt and fat found in potato chips when matched for carbohydrates. The next diet consisted of an isocaloric substitution of potato chips for the 400g of boiled potatoes and vegetable fat. 
This is an absolutely brilliant design. It could elucidate any independent effect of actually frying the potatoes themselves. That is, of course, if it were powered to do so. Unfortunately it is a non-randomized, single-armed pilot study involving only 14 subjects. It would be dubious to infer much of anything from this trial.
The paper purports that there were statistically significant increases in the inflammatory markers: AAHb, IL-6, hsCRP, and GGT. I calculated the change scores myself and found that there was actually no statistically significant increase in either AAHb or hsCRP. There was a statistically significant increase in both IL-6 and GGT. However, both were still smack-dab in the middle of the reference range, and the increases themselves were small and likely clinically irrelevant.
All in all, I remain agnostic about the potential long-term health value of fried potatoes, as I was not able to find any truly persuasive evidence that these foods actually cause harm. Especially with regards to CVD. Until better data comes out, it appears that their effect on health is likely rather neutral.
**Key points:**
- Fried potatoes do not qualify as ultra-processed foods.
- Fried potatoes have been shown to increase the risk of total mortality in prospective cohort studies that use questionable methods.
- In prospective cohort studies that are well-designed and well-powered, fried potatoes show no increase in cardiovascular disease.
- Current human trials do not have enough power to tell us how fried potato consumption affects intermediate markers of disease.
**References:**
[1] [https://world.openfoodfacts.org/nova](https://world.openfoodfacts.org/nova) 
[2] [https://pubmed.ncbi.nlm.nih.gov/28592612/](https://pubmed.ncbi.nlm.nih.gov/28592612/) 
[3] [https://pubmed.ncbi.nlm.nih.gov/27680993/](https://pubmed.ncbi.nlm.nih.gov/27680993/) 
[4] [https://pubmed.ncbi.nlm.nih.gov/19158207/](https://pubmed.ncbi.nlm.nih.gov/19158207/)
#patreon_articles
#nutrition
#potatoes
#all_cause_mortality
#food_frequency_questionnaires
#epidemiology
#cohort_studies
#cardiovascular_disease
#biomarkers

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💻 Hyperblog/Blogs/Patreon/Are Ultra-processed Foods Actually Unhealthy.md Executable file
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No matter where you stand in the nutrition blogosphere, it is extremely common to hear from all corners that the standard Western diet (SWD) is unhealthy. The justification for this claim is that the diet is comprised solely of ultra-processed foods (UPF), and these UPFs are inherently harmful in and of themselves. But the latter statement doesn't necessarily have to follow from the former statement.
![[1-13.png]]
Looking at this 3x3 grid, every single possibility is a plausible hypothesis. Let's look at the claim currently being made, which is cell E— the SWD is unhealthy and UPFs are also unhealthy.
Firstly, there is no question that the SWD is characterized by UPF consumption, and that UPF consumption correlates well with poor health outcomes [1](https://pubmed.ncbi.nlm.nih.gov/31099480/). It definitely seems to be the case that the SWD is an unhealthy dietary pattern. But I think we can use a thought experiment to help us understand why this isn't the same thing as saying that the UPFs themselves are inherently unhealthy or harmful.
I think we can agree that fruit is healthy. But what if you ate nothing but fruit? What if you ate fruit to the exclusion of everything else? I'm pretty confident that terrible things would happen to virtually anyone who attempted that diet. But does that make fruit unhealthy? Of course not!
Similarly, the SWD is for all intents and purposes a mono-diet. It is characterized by the exclusive consumption of UPF, which have an incredibly homogeneous composition— wheat flour, vegetable oils, sugar, animal by-products, and salt. So why the double-standard? Why do we assume that fruit is healthy despite the fact that bad things are likely happen on a diet of nothing but fruit, but we also assume UPFs are unhealthy because bad things are likely to happen on a diet of nothing but UPF? Seems weird.
We need a symmetry-breaker to justify the disparity between these positions. If we suggest that the symmetry-breaker is that fruit correlates with positive health outcomes from the lowest to highest intakes in epidemiology, but UPFs correlate with negative health outcomes from the lowest to highest intakes, I'd say we're not actually comparing like with like. 
In epidemiology investigating UPFs and health, the highest quantiles of intake will be representative of people eating almost exclusively UPFs. In essence, these people would be eating mono-diets. Whereas in epidemiology investigating fruit and health, the upper quantiles of intake will almost never be representative of people eating exclusively fruit. The people eating the most fruit will still have very heterogeneous diets. In one instance we're dealing with a mono-diet, and in the other instance we're not. So I don't think that works as a symmetry-breaker.
Plus, imagine what we would see in the epidemiology if we did manage to isolate a large subset of the population who've been eating nothing but fruit for the last forty years. Do you think we'd see their health status improve or worsen compared to the general population? It's likely that the fruit-only diet would probably be worse for health in a lot of ways that the SWD would be.
So, what do I think? I think diet-health relationships are often about substitution effects. Every time you add something to your diet, you have to remove something else. Every time you remove something from your diet, you have to add something else. If someone is eating a single food item/category to the exclusion of everything else that could be conferring additional benefits, we'd expect worse outcomes. It doesn't matter if the food is "healthy" or "unhealthy", to be perfectly honest.
The fact that when someone eats nothing but UPFs their health outcomes tend to worsen doesn't shock me. But I'm not convinced that it is because UPFs are inherently harmful. Because we can't disassociate the negative effects of the foods themselves from the negative effects of such a drastic substitution.
But before I sign off here, let me give you one more hypothetical. Say I'm eating a diet that has: 20 servings of fruits and vegetables, adequate protein (mostly from lean meats and pulses), micronutrient sufficiency, and saturated fat under control. It doesn't get much better than that, honestly. Maximal benefit of fruits and vegetables occurs around 10 servings per day, so this diet has a lot of redundancy. What if I wanted to shave off two servings of fruits and vegetables and add in UPFs like candy, biscuits, or potato chips? I don't think there is data to suggest that such a substitution would cause negative health outcomes. In fact, the diet I'm describing is likely the diet that is representative of the reference diet in many epidemiological studies on So, why suggest that UPFs are inherently harmful?
So are UPFs unhealthy? Personally, I'm agnostic about it. I haven't seen any good data to suggest that they are inherently harmful, and I can make plenty of arguments for their health value as well. So, I remain open to persuasion in either direction.
**Key points:**
- Many claim that ultra-processed foods are inherently harmful.
- There is evidence that diets of primarily ultra-processed foods are harmful.
- Diets of primarily fruit would be likely to be equally harmful.
- Nevertheless, fruit are still assumed healthy and ultra-processed foods are still assumed unhealthy.
- Justifications for this double-standard are not obvious and require elucidation.
- There doesn't seem to be any robust evidence that ultra-processed foods are inherently harmful.
**References:**
[1] Stefanie Vandevijvere, et al. Global trends in ultraprocessed food and drink product sales and their association with adult body mass index trajectories. Obes Rev. 2019 Nov. [https://pubmed.ncbi.nlm.nih.gov/31099480/](https://pubmed.ncbi.nlm.nih.gov/31099480/)
#patreon_articles
#ultraprocessed_foods
#healthy_diets
#western_diets
#disease

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💻 Hyperblog/Blogs/Patreon/Bart Kay Debate Notes.md Executable file
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Recently, I extended a debate invitation to Bart Kay via email. That exchange is documented [here](https://www.youtube.com/watch?v=M7vTJ02xxrw). Essentially I gave him an ultimatum. Either he lifts the [unreasonable stipulations](https://youtu.be/rYcy9YhS8NU?t=609) that he had previously placed upon [Avi Bitterman](https://twitter.com/AviBittMD) for their debate, or him and I will not debate. He claimed that my stipulations were unreasonable because they were not related to the debate. However, this is also true of his stipulations against Avi.
Basically, either he gives me a justification that renders his stipulations valid in a way that renders mine invalid, or his position entails a contradiction. If both of our stipulations are valid, then he can't say that I'm dodging him without it also being entailed that he is dodging Avi. If both of our stipulations are invalid, then he has no excuse for dodging a debate with Avi. He's effectively trapped until he provides the argument.
I don't believe this debate will actually happen, because Bart has previously shown himself to be unable to engage with [basic logical concepts](https://www.youtube.com/watch?v=Cknpks3QlBk) like consistency. For this reason, I'm releasing my debate notes to my patrons. Here is the line of questioning that I was going to run on Bart's debate proposition. Ultimately my game plan was to pin him on empirics, which would have been very straight forward. Enjoy!
**Bart's Debate Proposition:**
> _"100% Carnivore diet is the appropriate and best health choice for all people."_
- It's unclear if this qualifies as a proposition.
- What does "appropriate" mean? In relation to what?
- What does "best" mean?
- What does "health" mean? Some endpoint?
- What constitutes a 100% carnivore diet? Does 100% horse hooves count?
**Bart's Clarified Debate Proposition:**
> _"Z is X and Y W choice for all people."_
- It's unclear what sort of claim this proposition is making.
- Is this a scientific claim?
- If not a scientific claim, is this claim simply a belief?
- If a belief, agree with the proposition, laugh, and leave.
- If a scientific claim, proceed to the line of questioning.
**Line of Questioning:**
- What's the evidence?
- What is the argument that is this evidence is more expected on the proposition than the negation of the proposition? (An argument is required, because maybe the "evidence" is less or equally expected on the proposition (which would not be evidence for the proposition)).
- If he does provide an argument, examine the premises carefully.
- If a premise is unconvincing, ask for the argument for the premise.
- Repeat if necessary or until you become convinced or until Bart rage-quits.
#patreon_articles
#carnivore

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💻 Hyperblog/Blogs/Patreon/Beastmode Fatty Acid Composition Charts.md Executable file
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Maybe I'm weird, but for some reason I often find myself searching on Google Images for pictures of fatty acid composition charts. However, the vast majority of the ones I have seen are not nearly as comprehensive as I would prefer. So I used data from the [Nutri-Dex](https://www.the-nutrivore.com/nutri-dex) to create a series of comprehensive fatty acid composition charts. The charts are sorted by each fatty acid subtype, as well as alphabetically. Enjoy!
![[Pasted image 20221123153503.png]]
![[Pasted image 20221123153507.png]]
![[Pasted image 20221123153510.png]]
![[Pasted image 20221123153514.png]]
![[Pasted image 20221123153518.png]]
![[Pasted image 20221123153521.png]]
![[Pasted image 20221123153524.png]]
#patreon_articles
#nutrition
#dietary_fat
#polyunsaturated_fat
#saturated_fat
#monounsaturated_fat
#trans_fat
#vegetable_oil
#animal_fats

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💻 Hyperblog/Blogs/Patreon/Blood Glucose on Low Carb Diets.md Executable file
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Hi everyone! Now that school's over I have some time to write more. So, what better topic to discuss than one about which I have recently changed my mind!
Back in 2020, I published a meta-analysis to my blog that, in retrospect, was actually pretty poorly done [1](https://thenutrivore.blogspot.com/2020/10/low-carbohydrate-diets-and-health.html#BG)]. This last semester I took a graduate studies data synthesis course on systematic review and meta-analysis, so now I'm hyper-critical of much of my previous meta-analyses.
I think the data from the low carb blog article is still valuable, despite the fact that it definitely wasn't done according to best practice. The findings of that meta-analysis suggested that reductions in blood glucose on ketogenic diets could be mediated by weight loss, so that is what I had believed for a long time.
However, there was only one study in the <1kg weight loss subgroup in my weight loss sensitivity analysis. This study was Myette-Côté et al. (2018) [2](https://pubmed.ncbi.nlm.nih.gov/30303707/). According to my analysis, both the between-group treatment effect and the within-group change score for keto was non-significant, and nowhere close to even being borderline significant.
But this was actually just an artifact of the particular statistical tests I was using. In the actual paper, the authors used specific normality tests in conjunction with an ANOVA test, which is a continuous outcome test that is more robust than the one I was using. The inverse variance test that I was using assumes normal distributions.
![[1-90.png]]
This is paper we're comparing the control diet (GL) to the ketogenic diet without exercise (LC). It is clear from this data that the distribution for LC is non-normal, which violates the assumptions of the test that I used. The distribution almost looks bimodal, which is something my test could not account for. It's easy to see how just comparing the mean and standard deviation of both GL and LC could produce non-significant treatment effects.
Using better tests, the authors found a statistically significant reduction in fasting blood glucose with LC compared to control, without weight loss. In fact, the LC did not lose a statistically significant amount of weight, which could imply that the LC subjects may have even gained body fat, because normally some non-fat weight loss is expected in ketosis due to water loss.
As far as I know this is the most controlled test of the hypothesis that ketogenic levels of carbohydrate-restriction cause reductions in blood glucose. So, it looks like my previous inferences about how carbohydrate-restriction relates to blood glucose were probably incorrect. Though, I think the effect is probably unique to ketogenic diets. In this pre-print manuscript by Ozairi et al. (2021), the effect of a number of non-ketogenic levels of carbohydrate restriction on blood glucose were tested [3](https://www.medrxiv.org/content/10.1101/2021.05.30.21258049v1)].
![[1-92.png]]
Overall, even levels of carbohydrate restriction as low as 10% of energy did not yield statistically significant differences in average blood glucose. The authors suggest that this could be due to a unique glucose-lowering effect of ketones themselves:
> _"There is growing evidence that ketone bodies themselves independently lower glucose at least partly by reducing hepatic glucose output and long-term randomised and open-label trials which have used nutritional ketosis (>0.5mmol) as a therapeutic goal and a measure of compliance suggest that carbohydrate restriction in the context of significant weight loss and sufficient to induce ketosis may produce large reductions in both HbA1c and diabetes medication use."_
One of the primary studies used as the basis for this speculation is a ketone supplementation trial that suggested that ketones could uniquely lower blood glucose [4](https://pubmed.ncbi.nlm.nih.gov/33367782/). In this study one group received ketone monoester of beta-hydroxybutyrate, and the other group received placebo. There was a consistent, statistically significant effect of the ketone esters on lowering blood glucose, even outside the context of a carbohydrate-restricted ketogenic diet or weight loss.
![[1-91.png]]
To wrap things up, it's likely the case that ketosis has a unique effect of lowering blood glucose, independent of changes in body weight. This effect can likely be achieved through extreme carbohydrate restriction or ketone supplementation. Though, ketone supplementation could potentially be dangerous for those with impaired beta-cell function. Though, that's just speculation on my part.
**Key points:**
- Both ketogenic diets and ketone supplementation appear to independently lower blood glucose.
- Blood glucose lowering appear to occur independent of weight loss.
**References:**
[1] [https://thenutrivore.blogspot.com/2020/10/low-carbohydrate-diets-and-health.html#BG](https://thenutrivore.blogspot.com/2020/10/low-carbohydrate-diets-and-health.html#BG) 
[2] [https://pubmed.ncbi.nlm.nih.gov/30303707/](https://pubmed.ncbi.nlm.nih.gov/30303707/) 
[3] [https://www.medrxiv.org/content/10.1101/2021.05.30.21258049v1](https://www.medrxiv.org/content/10.1101/2021.05.30.21258049v1) 
[4] [https://pubmed.ncbi.nlm.nih.gov/33367782/](https://pubmed.ncbi.nlm.nih.gov/33367782/)
#patreon_articles
#keto
#blood_glucose
#hba1c
#nutrition
#type_2_diabetes

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💻 Hyperblog/Blogs/Patreon/Bustin' Nuts for Prostate Health.md Executable file
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For those who listen to [Sigma Nutrition Radio](https://sigmanutrition.com/podcasts/), you'll know that Danny always closes his podcast by asking his guests to recommend a single thing they could do each day that would improve their life. If you listened to [my interview](https://sigmanutrition.com/episode360/) on Danny's podcast, you undoubtedly remember my answer. I suggested to Danny's listeners that they masturbate to improve their lives, haha. This is a follow-up to that recommendation.
It has been observed that ejaculation frequency seems to be inversely associated with prostate cancer incidence. To the best of my knowledge, this particular research question was first investigated in a 1986 case-control study [1](https://pubmed.ncbi.nlm.nih.gov/3739124/). 
![[Pasted image 20221123153604.png]]
There seemed to be a potential protective effect of more frequent ejaculations on prostate carcinoma. The author speculates that the effect may be conveyed through higher rates of prostate epithelial cell turnover with increasing ejaculation frequency. 
Though I can't comment on epithelial cell turnover, I can say from personal experience that ejaculation volume seems to be a function of the total area under the curve of arousal during a sexual event. So, the cells are certainly doing something as a function of sexual stimulation/arousal that they otherwise wouldn't be doing, haha.
This question was revisited in a 2002 meta-analysis of case-control studies that found somewhat contradictory results [2](https://pubmed.ncbi.nlm.nih.gov/11805589/). The highest octile of ejaculations yielded a 44% and 440% increase in risk for population-based case-control studies and hospital-based case-control studies, respectively. Overall they observed an aggregated relative risk of 1.53, which is a 53% increase in the risk of prostate cancer with the highest frequency of ejaculations.
![[Pasted image 20221123153610.png]]
However, case-control studies are generally considered one of the weakest forms of observational evidence, as the assessments are all post-hoc. There are no prospective measurements that actually quantify exposures and outcomes in real-time in the populations studied.
Prospective cohort studies are considered much stronger evidence than case-control studies, and at least one prospective cohort study has investigated the relationship between ejaculation frequency and prostate cancer incidence [3](https://pubmed.ncbi.nlm.nih.gov/15069045/). The Health Professionals Follow-up Study (HPFS) was an extremely thorough, multi-decade prospective cohort study conducted in the United States. 
Ejaculation frequency was robustly, inversely associated with prostate cancer incidence. For those wanking off more than 21 times per month, a 33% reduction in the risk of prostate cancer was observed. There was also a 52% reduction in the risk of organ confined prostate cancer.
![[Pasted image 20221123153614.png]]
Twelve years later, different researchers would publish an additional ten years of prostate cancer outcome data related to ejaculation frequency in the HPFS cohort [4](https://pubmed.ncbi.nlm.nih.gov/27033442/). The same associations were observed, except this time around the authors provided pretty compelling survival curves.
![[Pasted image 20221123153618.png]]
So, based on the best available evidence, increasing the frequency of ejaculations seems to be associated with lower rates of prostate cancer overall in a relatively dose-dependent manner. 
**Key points:**
- Ejaculating once every 1.42 days may reduce the risk of prostate cancer.
**References:**
[1] [https://pubmed.ncbi.nlm.nih.gov/3739124/](https://pubmed.ncbi.nlm.nih.gov/3739124/)
[2] [https://pubmed.ncbi.nlm.nih.gov/11805589/](https://pubmed.ncbi.nlm.nih.gov/11805589/)
[3] [https://pubmed.ncbi.nlm.nih.gov/15069045/](https://pubmed.ncbi.nlm.nih.gov/15069045/)
[4] [https://pubmed.ncbi.nlm.nih.gov/27033442/](https://pubmed.ncbi.nlm.nih.gov/27033442/)
#patreon_articles
#prostate_cancer
#masturbation
#ejactulation
#sexuality
#disease

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💻 Hyperblog/Blogs/Patreon/Can Flaxseed Oil Increase DHA Status.md Executable file
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There exists a pretty pervasive trope that tends to circle around plant-based communities, suggesting either that an essential omega-3 fatty acid called docosahexaenoic acid (DHA) is unnecessary in the diet, or that our DHA requirement can be entirely satisfied through supplementing with a precursor fatty acid that can be found in plant foods called alpha-linolenic acid (ALA). I was recently sent a paper that could help tease this apart.
Firstly, I can't stress enough that DHA is an essential nutrient. Whether or not we can convert enough DHA from ALA, the fact of the matter is that we need DHA in our bodies in order for our bodies to function optimally. DHA is integral to proper neurological and immunological functioning. It's probably a good idea to make sure your DHA status is optimal.
I was recently sent a paper by my buddy, [Zachary](https://twitter.com/ZacharyWenger) (you should follow him on Twitter, by the way). Basically, in this study, researchers divided people into six groups and gave them varying doses of either ALA (via flaxseed oil), DHA (via fish oil), or a placebo [1](https://pubmed.ncbi.nlm.nih.gov/18779299/). Their plasma and red blood cell (RBC) membrane ALA, eicosapentaenoic acid (EPA), and DHA representation was measured every two weeks for twelve weeks. Here are the results:
![[1-30.png]]
Take a moment to review the data carefully. As you can see, over twelve weeks fish oil does nothing to ALA status, but increases both EPA and DHA status. Flaxseed oil increases ALA status and, much to my surprise, it actually increases EPA status as well. But sadly, flaxseed oil does absolutely nothing to DHA status. 
This will be a disappointing finding for many people in the plant-based community. Some might criticize the finding, due to inadequate assessment of baseline omega-3 status using a gold standard measure like the omega-3 index. It could be that flaxseed oil actually does increase (or maintain) adequate DHA status, but perhaps we don't convert more than we need, with the end result being no measurable difference in RBC DHA if omega-3 status is optimal at baseline.
This is absolutely fair. However, we do have data investigating changes RBC DHA levels in response to flaxseed oil in those with suboptimal DHA status, as measured by the omega-3 index [2](https://pubmed.ncbi.nlm.nih.gov/17053155/). The results are consistent with the previous study discussed in this article— flaxseed oil increases EPA status but not DHA status. So the conclusion that flaxseed oil probably isn't helping your DHA status appears reasonably solid.
But hope is not lost. Preformed DHA can be obtained from vegan-friendly sources. You see, the reason fish are so rich in these long-chain omega-3 fatty acids is because they biomagnify up the food chain. The source of these fatty acids is actually from algae that fish on lower trophic levels will eat. For this reason we need not source our DHA from animal sources at all. We can just take algae supplements. An example of one such supplement can be found [here](https://www.amazon.com/dp/B07V7FHHWQ/ref=sspa_dk_detail_0?psc=1&pd_rd_i=B07V7FHHWQ&pd_rd_w=vcWRV&pf_rd_p=7d37a48b-2b1a-4373-8c1a-bdcc5da66be9&pd_rd_wg=zSZ5h&pf_rd_r=H4E990WYSMDA4E8K4NJ5&pd_rd_r=cd03fdea-cad0-4246-849c-199b9cccb2ed&spLa=ZW5jcnlwdGVkUXVhbGlmaWVyPUEyNDVSMVU5UkVLWU1MJmVuY3J5cHRlZElkPUEwOTk4Mjc2MkNLU0pYQllHUkNQVSZlbmNyeXB0ZWRBZElkPUEwNjYwNTgyM0FIVVA4SjNSR1FQMCZ3aWRnZXROYW1lPXNwX2RldGFpbCZhY3Rpb249Y2xpY2tSZWRpcmVjdCZkb05vdExvZ0NsaWNrPXRydWU=).
**Key points:**
- It has been speculated that flaxseed oil can provide us with adequate DHA through its conversion from ALA.
- Experiments investigating the relationship between flaxseed oil and DHA show that flaxseed oil does not improve DHA status.
- It would be prudent for vegans to supplement with plant-based sources of DHA.
**References:**
[1] [https://pubmed.ncbi.nlm.nih.gov/18779299/](https://pubmed.ncbi.nlm.nih.gov/18779299/)
[2] [https://pubmed.ncbi.nlm.nih.gov/17053155/](https://pubmed.ncbi.nlm.nih.gov/17053155/)
#patreon_articles
#nutrition
#flaxseeds
#polyunsaturated_fat
#docosahexaenoic_acid
#eicosapentaenoic_acid
#vegan_talking_points

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💻 Hyperblog/Blogs/Patreon/Cheese vs Tofu (An Independent Meta-Analysis).md Executable file
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I'm not sure why, but this comparison rears its head in many nutrition conversations related to dairy and cardiovascular disease (CVD) risk through changes in low density lipoprotein cholesterol (LDL-C). Many claim that cheese should be avoided in favour of tofu because cheese does not improve blood lipids compared to tofu.
Personally, I don't think it's a very interesting or fair comparison. The two foods are not matched for protein, carbohydrates, fat, or fatty acid composition in the least. But nonetheless it makes for good debate fodder for reductionist ideologues, and maybe it will be interesting to see what the data says.
Oddly enough, there are three studies that have measured blood lipid changes between groups fed either tofu or cheese [1](https://pubmed.ncbi.nlm.nih.gov/8780967/)[2](https://www.sciencedirect.com/science/article/pii/S0271531786800197)[3](https://pubmed.ncbi.nlm.nih.gov/2621294/). The first is the most often cited as evidence of the LDL-C raising effects of cheese, but many of their data points are confusing.
![[1-19.png]]
Seriously, though. What in the world is going on with these lipid metrics? There is no consistency in the findings except for LDL-C, and even that seems to have some issues.
We can see that cheese increases LDL-C compared to baseline, but it also seems to have the capacity to lower it. Unless that middle measurement was just randomly low for some reason. It is interesting to note that egg whites lowered LDL-C reliably compared to tofu. So, as we tumble down the slippery slope of diet reductionism, we're left concluding that egg whites are preferable to tofu, and that tofu should be avoided as well.
Just out of curiosity I decided to meta-analyze the results from all of these trials.
![[Pasted image 20221123153712.png]]
In the aggregate, tofu results in lower LDL-C than what is achieved by cheese, and the results are statistically significant (P=0.03). I chose my words here very carefully, because it is not the case that cheese _increases_ LDL-C, either.
![[Pasted image 20221123153715.png]]
When we consider the effects of cheese on LDL-C compared to baseline, we cannot say that cheese increases LDL-C. It just doesn't lower LDL-C, either. Its effects are neutral. This is good and bad for cheese-lovers. It could conceivably be the case that cheese could be an obstacle to lower LDL-C, but it is unlikely to make your LDL-C worse all by itself. 
In fact, two studies saw cheese either decrease LDL-C, or leave it unchanged, from a baseline of <102mg/dL. Meaning that it likely isn't the case that the neutral effects of cheese are just an artifact generated from higher baseline LDL-C to begin with. But let's take a look at the data for tofu compared to baseline, too.
![[Pasted image 20221123153719.png]]
This seems way more definitive to me. Tofu almost certainly lowers LDL-C. Which is fantastic news for me, because I love tofu with a passion, haha. But it also doesn't necessarily mean that we need to avoid cheese on the basis of its effects on LDL-C. Since cheese does not reliably affect LDL-C, it could still be the case that the effects of tofu on lowering LDL-C could have more to do with the presence of the tofu itself, and less to do with the absence of cheese.
Y'know what this sounds like to me?
![[1-21.png]]
**Key points:**
- Tofu tends to lower LDL-C.
- Cheese doesn't necessarily increase LDL-C.
- Eat tofu, but don't sweat the cheese either.
**References:**
[1] [https://pubmed.ncbi.nlm.nih.gov/8780967/](https://pubmed.ncbi.nlm.nih.gov/8780967/) 
[2] [https://www.sciencedirect.com/science/article/pii/S0271531786800197](https://www.sciencedirect.com/science/article/pii/S0271531786800197) 
[3] [https://pubmed.ncbi.nlm.nih.gov/2621294/](https://pubmed.ncbi.nlm.nih.gov/2621294/)
#patreon_articles
#nutrition
#LDL
#cheese
#tofu
#dairy
#soy

33
💻 Hyperblog/Blogs/Patreon/Dietary Fructose and NAFLD.md Executable file
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It's been proposed that the primary cause of NAFLD in the population is the overconsumption of dietary fructose. Physicians such as Robert Lustig and Peter Attia have outright claimed that fructose is overwhelmingly the culprit in the NAFLD epidemic. But, how true is this?
Let's look at some of the available evidence for this claim, such as controlled feeding studies using hypercaloric (weight-gaining) and eucaloric (weight-maintaining) diets. Let's start with hypercaloric feeding experiments. When subjects are overfed 1000 extra calories, consisting of 50% glucose and 50% fructose (equal to approximately 125g of fructose per day), there is a marked increase in liver fat— around 27% [1](https://www.ncbi.nlm.nih.gov/pubmed/22952180). This is because fructose stimulates de novo lipogenesis (DNL) to a greater degree than glucose. The effect reduces insulin sensitivity and definitely contributes to visceral adiposity.
However, what happens if we're maintaining our weight on a diet equally rich in fructose? Even under these conditions it has been shown that dietary fructose uniquely produces a 25% increase in liver fat on average [2](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4454806). However, because the diet is eucaloric, these effects are actually transient. Fasting insulin, triglycerides, and DNL did not differ significantly between diet periods. This means that, yes, fructose did increase postprandial liver fat. But, it was burned off by the next day, as evidenced by the fact that the subjects maintained their weight. So, who cares about the transient increase in liver fat?
Overwhelmingly the driver behind NAFLD is excess weight, which is a function of caloric intake [3](https://www.ncbi.nlm.nih.gov/pubmed/29221645). When those with NAFLD lose weight, their NAFLD either improves or resolves, regardless of whether they are consuming a high carbohydrate diet or not [4](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2677125). But, I'll direct your attention to the fact that during overfeeding, fructose consumption only increases liver fat by 27%. So, where did the baseline liver fat come from, if not from fructose? It came from dietary fat. Without a doubt the most lipogenic energy substrate to the liver is dietary fat. Hands down. A protocol that maximally reduces liver fat is likely a protocol that restricts dietary fat above all other macros.
If we were somehow able to learn the history of every fatty acid in the liver of someone with NAFLD, we'd very likely discover that the vast majority of those lipids ended up there as fat brought in as dietary fat, not dietary fructose.
**Key points:**
- Fructose does increase liver fat content in hypercaloric conditions.
- Fructose only transiently increases liver fat content in eucaloric conditions.
- Regardless of fructose intake, obesity is the primary cause of NAFLD.
- Weight loss reverses NAFLD regardless of the macronutrient ratios of the diet.
**References:**
[1] Sevastianova K, et al. Effect of short-term carbohydrate overfeeding and long-term weight loss on liver fat in overweight humans. Am J Clin Nutr. October 2012. [https://www.ncbi.nlm.nih.gov/pubmed/22952180](https://www.ncbi.nlm.nih.gov/pubmed/22952180)
[2] Jean-Marc Schwarz, et al. Effect of a High-Fructose Weight-Maintaining Diet on Lipogenesis and Liver Fat. J Clin Endocrinol Metab. June 2015. [https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4454806](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4454806/)
[3] Lean ME, et al. Primary care-led weight management for remission of type 2 diabetes (DiRECT): an open-label, cluster-randomised trial. Lancet. February 2018. [https://www.ncbi.nlm.nih.gov/pubmed/29221645](https://www.ncbi.nlm.nih.gov/pubmed/29221645)
[4] Erik K, et al. Dietary fat and carbohydrates differentially alter insulin sensitivity during caloric restriction. Gastroenterology. May 2009. [https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2677125](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2677125/)
#patreon_articles
#nutrition
#disease
#fructose
#non_alcoholic_fatty_liver_disease
#clownery

39
💻 Hyperblog/Blogs/Patreon/Do Low Carb Diets Reverse Diabetes.md Executable file
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I have covered this topic in tremendous depth [on my main blog](https://www.the-nutrivore.com/post/sugar-doesn-t-cause-diabetes-and-ketosis-doesn-t-reverse-it). I have also covered how low carb high fat diets (LCHF) diets relate to insulin resistance [here](https://www.patreon.com/posts/do-low-carb-34341540). When I wrote those two articles, I was merely skeptical that LCHF had an independent capacity to remit type 2 diabetes (T2DM). However, after completing my work on the [Low Carbohydrate Diets and Health](https://thenutrivore.blogspot.com/2020/10/low-carbohydrate-diets-and-health.html) meta analysis, I'm now very, very confident that LCHF does not actually reverse T2DM in any independent capacity at all.
I find the evidence quite clear that T2DM is a disease of chronically high energy status, and I explain this in detail in [this video](https://www.youtube.com/watch?v=Zu2Sl3qEh9I). This is why I included subgrouping by weight loss in my meta-analysis. Without the luxury of a meta-regression analysis, this is the next best way to tease out an effect of LCHF on either one of these endpoints that is independent of weight loss.
T2DM can be diagnosed about four different ways. But, typically T2DM is diagnosed using either fasting blood glucose (FBG) or hemoglobin A1C (HbA1C). An FBG of >7mmol/L, or an HbA1C of >6.5% is sufficient to diagnose an individual with T2DM. I collected data for both of these endpoints for my Low Carbohydrate Diets and Health meta analysis, and here's what they showed:
**HbA1C by weight-loss vs baseline:**
![[1-28.png]]
**FBG by weight-loss vs baseline:**
![[1-27.png]]
Note that I am comparing LCHF to baseline rather than control. This is because I want to know whether or not LCHF has an effect at all, not whether or not it performs better than control. I want to know if subjects saw an improvement from where they were, not whether or not there was a difference relative to the comparator diet.
As you can see, there is insufficient evidence to suggest that either HbA1C or FBG will budge an inch without weight loss. Granted, in the case of FBG, there is only one study in the lowest weight loss subgroup. As I've mentioned before in my writing, you cannot meta-analyze a a sample of one. But this doesn't bode well for LCHF advocates either way. There is virtually no evidence that LCHF lowers HbA1C or FBG independent of weight loss. It has not been persuasively demonstrated. It's the same story for insulin too.
**Fasting insulin by weight-loss vs baseline:**
![[1-29.png]]
Again, there is insufficient evidence that insulin can be reduced without weight loss either. Based on all of the data together, I'm utterly unconvinced that LCHF remits T2DM in any capacity independent of weight loss.
**Key points:**
- It has been claimed that LCHF reverse and/or remit T2DM independent of weight loss.
- No aggregate of the available literature supports this hypothesis.
- LCHF has not been shown to reduce fasting blood glucose independent of weight loss.
- LCHF has not been shown to reduce HbA1C independent of weight loss.
- LCHF has not been shown to reduce fasting insulin independent of weight loss.
#patreon_articles
#nutrition
#low_carb
#keto
#type_2_diabetes
#blood_glucose
#hba1c

36
💻 Hyperblog/Blogs/Patreon/Do Low Carb Diets Reverse Insulin Resistance.md Executable file
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We've likely heard before that low carb high fat diets (LCHF) are good for diabetes because they supposedly improve insulin sensitivity. The idea that tends to make the rounds within LCHF circles is that insulin resistance is a consequence of prolonged exposure to insulin. It isn't, as I've discussed [here](https://thenutrivore.blogspot.com/2019/10/sugar-doesnt-cause-diabetes-and-ketosis.html). But, that's their idea. Leaving aside questions about whether or not LCHF has independent utility for diabetes treatment or management, let's just tackle this central question— do LCHF diets reverse insulin resistance?
Luckily, there have been a number of studies looking into this question [1](https://www.ncbi.nlm.nih.gov/pubmed/11237931)[2](https://www.ncbi.nlm.nih.gov/pubmed/15310747)[3](https://www.ncbi.nlm.nih.gov/pubmed/11679437). Across the board, isocaloric substitutions of carbs for fat yield consistent and predictable effects on glucose disposal and insulin sensitivity. Using a technique called a hyperinsulinemic euglycemic clamp test, researchers can actually measuring the differences in insulin sensitivity by observing glucose disposal in real-time. 
As a general principle, LCHF feeding tends to reduce insulin sensitivity and glucose disposal on average. Whereas high carb low fat (HCLF) feeding tends to increase insulin sensitivity and glucose disposal on average. 
So, from where does the confusion arise? Well, insulin sensitivity is typically reported using HOMA-IR in the LCHF literature [4](https://www.ncbi.nlm.nih.gov/pubmed/31231311)[5](https://www.ncbi.nlm.nih.gov/pubmed/23155696)[6](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3981696/). HOMA-IR is an indirect measurement of insulin sensitivity. It is merely a calculation that considers fasting glucose and fasting insulin in order to generate an insulin sensitivity score. However, this is not a gold standard tool and is not validated for use in LCHF subjects. LCHF diets reduce fasting insulin and fasting glucose, so HOMA-IR tends to produce unrealistically favourable results for LCHF diets. 
**Key points:** 
- LCHF diets induce a state of insulin resistance and HCLF diets improve insulin sensitivity, as demonstrated by direct measurements of insulin sensitivity.
- LCHF studies tend to report insulin sensitivity via HOMA-IR, which is not a direct measurement of insulin sensitivity and isn't validated in LCHF subjects.
**References**
[1] Bisschop PH, et al. Dietary fat content alters insulin-mediated glucose metabolism in healthy men. Am J Clin Nutr. 2001 Mar. [https://www.ncbi.nlm.nih.gov/pubmed/11237931](https://www.ncbi.nlm.nih.gov/pubmed/11237931) 
[2] Pehleman TL, et al. Enzymatic regulation of glucose disposal in human skeletal muscle after a high-fat, low-carbohydrate diet. J Appl Physiol (1985). 2005 Jan. [https://www.ncbi.nlm.nih.gov/pubmed/15310747](https://www.ncbi.nlm.nih.gov/pubmed/15310747) 
[3] Bachmann OP, et al. Effects of intravenous and dietary lipid challenge on intramyocellular lipid content and the relation with insulin sensitivity in humans. Diabetes. 2001 Nov. [https://www.ncbi.nlm.nih.gov/pubmed/11679437](https://www.ncbi.nlm.nih.gov/pubmed/11679437) 
[4] Athinarayanan SJ, et al. Long-Term Effects of a Novel Continuous Remote Care Intervention Including Nutritional Ketosis for the Management of Type 2 Diabetes: A 2-Year Non-randomized Clinical Trial. Front Endocrinol (Lausanne). 2019 Jun. [https://www.ncbi.nlm.nih.gov/pubmed/31231311](https://www.ncbi.nlm.nih.gov/pubmed/31231311) 
[5] Partsalaki I, et al. Metabolic impact of a ketogenic diet compared to a hypocaloric diet in obese children and adolescents. J Pediatr Endocrinol Metab. 2012. [https://www.ncbi.nlm.nih.gov/pubmed/23155696](https://www.ncbi.nlm.nih.gov/pubmed/23155696) 
[6] Laura R. Saslow, et al. A Randomized Pilot Trial of a Moderate Carbohydrate Diet Compared to a Very Low Carbohydrate Diet in Overweight or Obese Individuals with Type 2 Diabetes Mellitus or Prediabetes. PLoS One. 2014. [https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3981696/](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3981696/)
#patreon_articles
#nutrition
#disease
#insulin_sensitivity
#insulin
#low_carb
#keto
#type_2_diabetes
#metabolic_syndrome

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💻 Hyperblog/Blogs/Patreon/Do Processed Foods Make Us Fat.md Executable file
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I've heard dozens of answers to this question, ranging from plausible to absolutely absurd. Luckily, researchers have actually investigated this question and have yielded some highly practical answers. The truth is that there is an entire constellation of mechanisms that lead to processed foods having a tendency to make us fat. But here are just a few of the most important ones.
The first reason is that processed foods just taste really damn good. When we eat processed foods instead of whole foods, we just tend to eat more [1](https://www.ncbi.nlm.nih.gov/pubmed/31105044). The feeding efficiency of calorie-dense junk food is just so high that achieving satiety typically requires additional calories.
The second reason is that processed foods are incredibly easy to digest, and this has a massive impact on our energy expenditure after a meal. It costs double the calories to digest and metabolize a whole food meal when compared to a processed food meal [2](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2897733/). This means that even when calories are equated, a meal of processed food is more likely to cause weight gain than a meal of whole foods.
The third reason is that processed foods are often sorely lacking in protein. Protein has an independent effect on increasing our energy expenditure and lean body mass. Our lean tissue is a massive energy sink, and provides a buffer for excess calories. Chronically under-consuming protein can decrease our lean body mass and lead to lower energy expenditures over time [3](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3777747/). This exacerbates the first two issues, potentially creating a downward spiral.
**Key points:**
- Processed foods usually taste super awesome and can cause us to overeat.
- Processed foods cause us to burn fewer calories, making fat gain more likely.
- Processed foods often lack protein and can negatively affect our lean body mass.
**References:**
[1] Hall KD, et al. Ultra-Processed Diets Cause Excess Calorie Intake and Weight Gain: An Inpatient Randomized Controlled Trial of Ad Libitum Food Intake. Cell Metab. July 2019 [https://www.ncbi.nlm.nih.gov/pubmed/31105044](https://www.ncbi.nlm.nih.gov/pubmed/31105044)
[2] Sadie B. Barr and Jonathan C. Wright. Postprandial energy expenditure in whole-food and processed-food meals: implications for daily energy expenditure. Food Nutr Res. July 2010. [https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2897733/](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2897733/) 
[3] George A. Bray, et al. Effect of Dietary Protein Content on Weight Gain, Energy Expenditure, and Body Composition During Overeating. JAMA. January 2012. [https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3777747/](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3777747/)
#patreon_articles
#nutrition
#disease
#processed_food
#obesity
#weight_gain

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💻 Hyperblog/Blogs/Patreon/Do Vegetable Oils Increase Lung Cancer Risk.md Executable file
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The primary evidence used to support the claim that vegetable oils increase the risk of lung cancer usually comes from an IARC report that was published back in 2010 [1](https://www.ncbi.nlm.nih.gov/books/NBK385523/pdf/Bookshelf_NBK385523.pdf). All in all, the report includes 24 case-control studies and an enormous amount of mechanistic speculation. I'll explain why it doesn't significantly move my needle on the question. 
Right off the bat, I should say that this document is largely an equivocation. Because I don't think that people deep-frying >3 meals a day in small Chinese bedrooms is typically what vegetable oil alarmists are referring to when they claim vegetable oils increase "our" risk of lung cancer. But we can explore the findings anyway. 
First off, going from a high-PUFA oils to a high-MUFA oils in these case-control studies pretty consistently increases the relative risk of lung cancer. Which would seem to contradict the hypothesis that MUFA would have much superiority over PUFA for this endpoint. 
![[1-95.png]]
You may have also noticed that boiling food was also associated with an increased risk of lung cancer. Which seems very odd. But, the results could be reconciled when we realize that a lot of the people included in these studies were using things like wood- and coal-burning stoves to cook their food.
It's plausible that the risk is just tracking cooking frequency, and that people who cooked at home more often with these methods were more likely to be exposed to wood smoke. 
Some of the case-control studies didn't even report relative risks relevant to vegetable oils. As some of them only report relative risk for years spent cooking in a bedroom, and the type of cooking fuel was not adjusted for. There are many more ways to produce smoke than heating vegetable oils in a pan. Hell, you can produce "kitchen fumes" by scorching butter in a pan or burning food with or without the use of oils.
Most of the remaining case-control studies report their relative risks as function of deep frying with no adjustment for anthropometrics or confounders like ventilation or the use of wood- or coal-burning stoves. One study actually failed to report the confidence internals for their relative risk and had zero adjustments, haha.
This one is truly hilarious, as they perform multiple sensitivity analyses that test for the effect of a few variables that could be potentially confounding. Such as windows, ventilation, and socioeconomic status. Unfortunately the type of cooking fuel was not adjusted for.
![[1-94.png]]
A significant increase in risk was only found in those consuming two or more meals per day cooked in the home. Again, wood smoke could be confounding here. But even if the association was reflecting a "real" effect, so to speak, there are no dietary guidelines from around the world encouraging anyone to eat the majority of their meals fried in a pan.
The next one probably has one of the best adjustment models out of the lot, and they find no statistically significant increase in risk among non-smokers. Which is interesting, because it raises the possibility that in-home cooking may also be a correlate for cigarette smoking for some reason.
![[Pasted image 20221123154022.png]]
Now that we've reached the end of the list, it is important to emphasize that these are case-control studies. Case-control studies are retrospective in nature and cannot be used to assess temporality. This means that they are extremely ill-equipped to inform causal inference. The associations are interesting, but it's not clear whether or not they are particularly useful.
What dissatisfies me the most with these case-control studies is that in most of the analyses, it is unknown if vegetable oils are truly the source of the "kitchen fumes" or "kitchen smoke", as I've discussed already. It's even possible that the risk could still be tracking cigarette smoking.
To try to get around this, I aggregated all of the data that was specific to cooking with vegetable oils. In an attempt to make sure that lower PUFA oils were always the comparator, I had to make some of the risk ratios inverse. But here are the results:
**Random Effects Model**
RR 0.93 (CI 0.68-1.27), P=0.64
![[Pasted image 20221123154041.png]]
**Fixed Effects Model:**
RR 0.91 (CI 0.78-1.05), P=0.20
![[Pasted image 20221123154044.png]]
In the aggregate, cooking with higher PUFA oils results in a non-significant decrease in lung cancer risk. Neither of these results should cause us to run for the hills when we see a deep fryer. Chances are good that the results of these case-control studies are tracking some other exposure. Like kang use, coal stoves, wood stoves, overconsumption, or even smoking. Especially since two studies showed an increased risk of boiling food, haha.
Thankfully, there is also a meta-analysis of prospective cohort studies investigating the relationship between PUFA and lung cancer, which showed a linear, non-significant decrease in risk with higher intakes [2](https://pubmed.ncbi.nlm.nih.gov/24925369/).
![[Pasted image 20221123154050.png]]
However, many of the included risk ratios were specific to fish. If we limit the risk ratios to just those that investigated total PUFA, and not fish specifically, we see no significant association with lung cancer risk. 
![[Pasted image 20221123154053.png]]
This is very poor evidence for an effect in either direction. But it certainly doesn't appear as though PUFA consumption is associated with a statistically significant increase in the risk of lung cancer.
**Key points:**
- The evidence for vegetable oils increasing lung cancer risk is very poor quality with a high risk of confounding.
- Higher quality evidence shows no significant effect of PUFA on lung cancer risk.
**References:**
[1] [https://www.ncbi.nlm.nih.gov/books/NBK385523/pdf/Bookshelf_NBK385523.pdf](https://www.ncbi.nlm.nih.gov/books/NBK385523/pdf/Bookshelf_NBK385523.pdf)
[2] [https://pubmed.ncbi.nlm.nih.gov/24925369/](https://pubmed.ncbi.nlm.nih.gov/24925369/)
#patreon_articles
#vegetable_oil
#lung_cancer
#disease
#nutrition

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💻 Hyperblog/Blogs/Patreon/Do the Guidelines Recommend a High PUFA Diet.md Executable file
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This is a pretty common trope that emerges from many different diet camps— particularly from the low carb community. The idea is that the guidelines led us to replace our saturated fats (SFA) with polyunsaturated fats (PUFA), which led to all sorts of poorer health outcomes. I'm not going to explore the health claims today, but I will talk about whether or not the guidelines actually do necessitate eating enormous amounts of PUFA.
I was only able to find a couple definitions for high PUFA diets in the literature. Some studies define high-PUFA diets as diets containing 10-21% of energy from PUFA [1](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6444462/)[2](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7050740/). So, let's take an average of 15.5% of energy. I could definitely agree with this. That can certainly be a lot of fucking PUFA, haha.
To start, I plugged the 2000 calorie [Mediterranean Dietary Pattern](https://health.gov/our-work/food-nutrition/2015-2020-dietary-guidelines/guidelines/appendix-4/) recommended by the [Dietary Guidelines for Americans, 2015-2020](https://health.gov/our-work/food-nutrition/2015-2020-dietary-guidelines/guidelines/), into Cronometer. Some of the dietary recommendations set weekly goals, while others set daily goals. But all together this is what the dietary pattern looks like if intakes are followed to the letter.
![[Pasted image 20221123153829.png]]
To my surprise, the guidelines allow for a decent whack of fat, and a pretty hefty amount of protein as well. The macronutrient breakdown is about 50% carbohydrates, 30% fat, and 20% protein. Not bad at all, really. But what about the PUFA?
![[Pasted image 20221123153832.png]]
The diet provides 18.8g of PUFA per day and 18.8g of SFA per day. Personally, I find it hilarious that the guidelines seem to permit equal quantities of total PUFA and total SFA.
All together this means that PUFA and SFA comprise about 8.4% of energy each. Since the most conservative definition of a high-PUFA diet that I could find in the literature is 10% of energy, this would not seem to be a high PUFA diet.
"But, wait, Nick. You didn't disclose the foods you inputted."
Get fucked, lol. Fine. Here they are:
![[Pasted image 20221123153835.png]]
For added fats, the guidelines give no specific qualitative recommendations other than to replace solid fats with oils. They give a list of oils that are commonly used, but do not say which ones are to be favoured over others. So I included all of the oils they mention toward the allotment of 27g/day that they suggested, but in equal proportions. Seems fair to me.
This is actually just one interpretation of the guidelines. It's probably one of the most fair interpretations, too. But, we can interpret the guidelines differently. If we replace some of the eggs with chicken, replace some of the salmon with shrimp, and replace all of the oils with avocado oil, we get this:
![[Pasted image 20221123153840.png]]
This is perfectly compatible with the guidelines, and actually provides more SFA than PUFA. But, to be fair this isn't the only way to stretch our interpretation of the guidelines. If you tweak everything to maximize the PUFA, you can get this after some trial and error:
![[Pasted image 20221123153844.png]]
In this interpretation, most of the meat is salmon and pork, the nuts and seeds are selected for their PUFA content, and the oil of choice is sunflower oil. All together this gives us 28.8g/day of total PUFA, which amounts to 12.4% of energy. 
By one definition I was able to find, this is a high intake. By another definition it is not. If the average threshold of 15.5% of energy is considered, this highly contrived, worse-case-scenario interpretation of the guidelines doesn't meet the criteria either.
So, in conclusion, if certain people still want to claim that the guidelines yield high PUFA intakes, I guess the people making this claim should just set their goalpost and justify it credibly— what is a high PUFA intake and why is it undesirable? Until they do that, I will maintain that the guidelines do not recommend a diet that is especially high in PUFA.
**Key points:**
- Some claim that the guidelines suggest a high omega-6/PUFA diet.
- Following the guidelines as literally as possible, this isn't true.
- Only absurd interpretations of the guidelines yield high PUFA intakes.
**References:**
[1] [https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6444462/](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6444462/)
[2] [https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7050740/](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7050740/)
#patreon_articles
#nutrition
#polyunsaturated_fat
#dietary_guidelines

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💻 Hyperblog/Blogs/Patreon/Does Cheese Increase LDL.md Executable file
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As a follow up to my independent [meta-analysis](https://www.patreon.com/posts/cheese-vs-tofu-44223669) on cheese and tofu, I decided to tackle this question more directly. We understand from previous research that the ratio of polyunsaturated fat (PUFA) to saturated fat (SFA) changes the concentration of low density lipoprotein cholesterol (LDL-C). However, does this relationship hold true in the context of cheese? 
If the claim is that the lipid-modulating effects of the PUFA to SFA ratio does **not** apply to cheese, then the relationship should not hold true— altering the PUFA to SFA ratio in cheese should yield no differential effects on LDL-C. That is to say, substituting PUFA and SFA should make no difference with regards to LDL-C if the SFA from cheese is expected to have no impact on LDL-C.
Here we have two studies that attempted to answer this question in a pretty clever way [1](https://pubmed.ncbi.nlm.nih.gov/8363165/)[2](https://pubmed.ncbi.nlm.nih.gov/12428175/). In both cases full-fat cheeses were compared to cheeses that had their saturated fat content replaced with unsaturated fats. Unfortunately, I cannot access one of the papers. So I'll discuss the paper I can access.
![[1-23.png]]
As we can see it does appear as though the PUFA to SFA ratio is relevant, even when cheese is the food being compared. But how meaningful is it?
![[Pasted image 20221123154201.png]]
Here are the study results. Neither at two weeks nor four weeks does the PUFA-enriched cheese lower LDL-C to a statistically significant degree. However, results are statistically significant when both measurements are considered together as a composite (P=0.03).
![[Pasted image 20221123154205.png]]
We can also see that, much like the cheese and tofu analysis, cheese fails to increase LDL-C relative to baseline. So, it would be accurate to say that cheese probably won't increase LDL-C, but if you're replacing cheese with PUFA, you can probably expect LDL-C to decrease. 
![[Pasted image 20221123154154.png]]
In the aggregate, the PUFA-enriched cheese lowers LDL-C compared to baseline. Which means that even in the context of cheese, the ratio of PUFA and SFA still maintain the same relationship with LDL-C. When PUFA replaces SFA, LDL-C tends to drop.
However, since cheese does not increase LDL-C to the degree we would expect given its SFA content, it would be most accurate to say that cheese likely blunts the hyperlipidemic effect normally observed with SFA consumption.
**Key points:**
- SFA-rich cheese does not seem to increase LDL-C
- PUFA-enriched cheese lowers LDL-C.
- The ratio of PUFA to SFA still affects LDL-C, even when cheese is the exposure.
**References:**
[1] [https://pubmed.ncbi.nlm.nih.gov/8363165/](https://pubmed.ncbi.nlm.nih.gov/8363165/) 
[2] [https://pubmed.ncbi.nlm.nih.gov/12428175/](https://pubmed.ncbi.nlm.nih.gov/12428175/)
#patreon_articles
#nutrition
#cheese
#dairy
#LDL
#ApoB

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💻 Hyperblog/Blogs/Patreon/Does Fruit Cause Fatty Liver.md Executable file
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By now, you may be aware that there is a study that has been recently published to the Scandinavian Journal of Gastroenterology by Alami et al. (2022), purporting to show that fruit increases the risk of non-alcoholic fatty liver disease (NALFD) [1](https://pubmed.ncbi.nlm.nih.gov/35710164/). Many low carb influencers have used the results of this study to make the claim that fruit causes NALFD. However, this isn't a correct interpretation. Let's get into it.
Essentially, 80 NAFLD patients were randomized to receive either additional fruit in a fruit-rich diet (FRD) group, or restricted fruit in a control group. They stayed on their respective diets for six months, and many biomarkers of insulin resistance and fatty liver were incrementally collected during that time.
The FRD group was instructed to add fruit to their diet with no specific instructions to replace anything else that they were currently eating. Whereas the control group was instructed to remove a certain amount of fruit from their diet with no specific instructions to eat anything else in place of the fruit. Non-adherers were also excluded from the final analysis.
> _"The participants in the [fruit-rich diet] group were recommended to consume at least 4 servings of fruits per day and the control group was asked not to consume more than 2 servings of fruit per day...those who received less than 4 servings of fruits in the intervention group or more than 2 servings of fruits in the control group were excluded from the analyses."_
A potential issue may already be obvious to you. Perhaps the FRD group just ended up consuming more calories than the control group. Based on the design this is certainly plausible. In fact, it's probable. A quick scan of Table 2 confirms our suspicions, with the control group consuming anywhere from ~202-338 kcal more than the FRD group throughout the study.
![[1-84.png]]
At this point it should be clear why the FRD group performed worse than the control group. However, there is an additional issue. The association between fruit intake and biomarkers of liver fat survived adjustment for BMI.
> _"After 6 months, the FRD group had higher serum levels of ALT, AST, ALP, and GGT compared to the control group. Adjustments for the effect of change in BMI, energy, bread and cereals, meats, vegetables, dairies, sugars, fats, and oils intake did not change the results...the present study showed that the main findings on the adverse effects of fruits in patients with NAFLD are independent from changes in the BMI, energy or other food group’s intake."_
However, this isn't the whole story here. The subjects in the study started off on the cusp of being obese, with an average BMI of 28.1. If we turn our attention to Table 3, we see that the FRD group actually became prediabetic during the study, based on their fasting blood glucose, which went from 96.9 mg/dL to 115.5 mg/dL. This is a potentially critical piece of information.
Based on the work of Taylor and Holman (2015) and Johansson et al. (2019), we understand that the relationship between liver fat and BMI is almost linear [2](https://pubmed.ncbi.nlm.nih.gov/25515001/)[3](https://pubmed.ncbi.nlm.nih.gov/21656330/)[4](https://pubmed.ncbi.nlm.nih.gov/31685793/). This is hypothesized to be what initiates the development of the diabetic phenotype in humans [5](https://pubmed.ncbi.nlm.nih.gov/23075228/).
Alami et al. adjusted for changes in BMI, which should have rendered the relationship between fruit intake and liver fat non-significant. But it didn't, the effect remained statistically significant even after the adjustment for BMI. Since BMI should mediate the relationship between calorie intake and liver fat, there are only two ways I can think to interpret this; either fruit has such a unique effect on liver fat that there is a second, unmeasured mediator that absolutely dominates over calories, or BMI differences were not enough to produce the sensitivity needed for the adjustment to affect the relationship, or there was a clerical error in their modeling somewhere.
Even though fructose is an independent mediator of liver fat in humans, we know from wider research that the calorie-independent effect of fructose on liver fat is miniscule at best [6](https://pubmed.ncbi.nlm.nih.gov/33381794/)[7](https://pubmed.ncbi.nlm.nih.gov/35889803/). So, it's unclear why an adjustment for BMI changes would not render the relationship non-significant. So, I'm personally leading toward the second or third explanation, that the BMI differences in the study weren't sensitive enough or there was some sort of clerical error somewhere in their modeling.
Maybe randomization failed somehow. Maybe someone inputted some data wrong when formulating the adjustment models. Who knows. It just seems utterly implausible that the effect would survive adjustment for BMI changes.
**Key Points:**
- The association between fruit and liver fat survived adjustment for BMI changes.
- These results are difficult to interpret and probably do not show us that fruit increases the risk of fatty liver.
**References:**
[1] [https://pubmed.ncbi.nlm.nih.gov/35710164/](https://pubmed.ncbi.nlm.nih.gov/35710164/) 
[2] [https://pubmed.ncbi.nlm.nih.gov/25515001/](https://pubmed.ncbi.nlm.nih.gov/25515001/) 
[3] [https://pubmed.ncbi.nlm.nih.gov/21656330/](https://pubmed.ncbi.nlm.nih.gov/21656330/)
[4] [https://pubmed.ncbi.nlm.nih.gov/31685793/](https://pubmed.ncbi.nlm.nih.gov/31685793/)  
[5] [https://pubmed.ncbi.nlm.nih.gov/23075228/](https://pubmed.ncbi.nlm.nih.gov/23075228/)
[6] [https://pubmed.ncbi.nlm.nih.gov/33381794/](https://pubmed.ncbi.nlm.nih.gov/33381794/)
[7] [https://pubmed.ncbi.nlm.nih.gov/35889803/](https://pubmed.ncbi.nlm.nih.gov/35889803/)
#patreon_articles
#fruit
#non_alcoholic_fatty_liver_disease
#disease
#nutrition

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💻 Hyperblog/Blogs/Patreon/Does Keto Increase LDL.md Executable file
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Even though my meta-analysis on low carbohydrate diets and health showed that keto tends to increase low density lipoprotein cholesterol (LDL-C), I had a suspicion that there might be more to the story. I wasn't quite ready to take for granted that keto increased LDL-C, in and of itself.
I noticed a tendency among the studies that actually reported the saturated fat (SFA) intakes of the subjects in the trial. I noticed that when keto resulted in only modest changes in SFA intake compared to baseline, LDL-C was also virtually unchanged. In fact, sometimes LDL-C would decrease. That is to say, I ended up having a hunch that the differences in LDL-C observed on keto were likely a function of SFA intake.
So I gathered all of the literature used in my low carb meta-analysis that I could, as well as some new publications that have been released within the last two years. I required that studies report both the SFA intakes of the subjects as well as LDL-C, compared to either control, baseline, or both. The results were pretty interesting.
![[Pasted image 20221123154254.png]]
First off, here we see the differences in SFA intake between keto and control plotted against the differences in LDL-C between keto and control. As you can see, no keto intervention resulted in lower SFA intake compared to control, but some did result in lower LDL-C compared to control. The correlation between the ΔSFA intake and ΔLDL-C is actually pretty high.
![[Pasted image 20221123154257.png]]
Here we see the changes in SFA intake with keto compared to baseline plotted against the changes in LDL-C with keto compared to baseline. There are fewer studies included because there were fewer studies that reported baseline SFA intakes and LDL-C. Looking at the data this way (which is likely a better angle to investigate), we see a tighter correlation.
But something is off. There is a clear outlier at the bottom of the chart. Participants increased SFA intake by approximately 11g/day but saw a non-trivial reduction in LDL-C. This is the only instance of this happening, so a remove-one analysis may be warranted.
![[Pasted image 20221123154306.png]]
Removing the outlier pushes the R^2 from 0.655 to 0.833. Which is pretty close to a linear correlation.
I also investigated this question in the same way with apolipoprotein B-100 (ApoB). 
![[Pasted image 20221123154309.png]]
Here are the differences in SFA intake between keto and control plotted against the differences in ApoB between keto and control. There were no studies that actually showed reductions in ApoB with keto compared to control. And the correlation, while technically "smaller", shows us pretty much what we would expect to see. As SFA intake goes up, so does ApoB.
However, like the previous plots, there is an obvious outlier. We see an instance were ApoB increases disproportionate to SFA intake, so perhaps we should see what would happen if we remove it.
![[Pasted image 20221123154314.png]]
Again, we see the R^2 increase. This time from 0.325 to 0.644. Which is a decently tight correlation. Also, again, this is what we would expect to see.
I should stress that this analysis is exploratory and observational. It doesn't really have much explanatory power in and of itself. But, it corroborates what we understand from the greater body of literature regarding the effect of SFA intake on blood lipids.
In conclusion, it is unlikely that keto uniquely increases LDL-C or ApoB in and of itself. Rather, it is more likely that ApoB and LDL-C respond to SFA intake on keto precisely as we would expect them to, in the general population.
**Key points:**
- Keto does not appear to increase ApoB or LDL-C any differently than any other diet.
- The increases in ApoB and/or LDL-C observed on keto can be largely explained by increases in SFA intake.
**Supplementary Materials:**
[https://docs.google.com/spreadsheets/d/1vtuzsp8PDq2s0zliKdlcX8536iwt3OdoT9oW6os6mnY/edit?usp=sharing](https://docs.google.com/spreadsheets/d/1vtuzsp8PDq2s0zliKdlcX8536iwt3OdoT9oW6os6mnY/edit?usp=sharing)
#patreon_articles
#nutrition
#keto
#LDL
#ApoB
#saturated_fat

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💻 Hyperblog/Blogs/Patreon/Does Keto Protect Against Heart Disease.md Executable file
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The low carb crackpot, Dave Feldman, has popularized the idea that ketogenic diets may offer unique protection against cardiovascular disease (CVD), due to the diet's tendency to lower triglycerides (TG) and increase high-density lipoprotein cholesterol (HDL). This is because it has been shown that lower TG/HDL ratios are more reliable disease correlates than most other traditional metrics [1](https://pubmed.ncbi.nlm.nih.gov/18719750/).
![[1-42.png]]
But why? The TG/HDL ratio is essentially a reflection of atherogenic dyslipidemia. Atherogenic dyslipidemia is a lipid phenotype that is characterized by high TG, low HDL, and either high or low low-density lipoprotein cholesterol (LDL). The lipid phenotype is typically concomitant with metabolic syndrome and type 2 diabetes.
The notion that ketogenic diets uniquely correct this deleterious lipid phenotype, and thus protect against cardiovascular disease (CVD), seems to center around the fact that ketogenic diets tend to increase HDL and reduce TG. But does this make ketogenic diets less atherogenic? Let's find out.
The reason the TG/HDL ratio is a decent correlate for CVD outcomes is not because the ratio itself does something bad. It's because the ratio is also a robust correlate for low-density lipoprotein particle number (LDLp) [2](https://pubmed.ncbi.nlm.nih.gov/15296705/). LDLp can also be represented as apolipoprotein B (ApoB), and is probably the most robust CVD risk predictor other than age.
![[Pasted image 20221123154342.png]]
Essentially, the higher your TG and the lower your HDL, the more likely it is that you will have a high ApoB. As I've discussed [before](https://www.patreon.com/posts/does-ldl-cause-43573104), ApoB is the causal agent in CVD. As such, even if one were to correct their TG/HDL ratio with a ketogenic diet, it would be reasonable to suspect that if ApoB remained high they haven't done much to mitigate their CVD risk. So, what do ketogenic diets typically do to ApoB?
![[1-43.png]]
This is from my [meta-analysis](https://thenutrivore.blogspot.com/2020/10/low-carbohydrate-diets-and-health.html) of ketogenic diets. In the aggregate, ketogenic diets don't appear to increase ApoB to a statistically significant degree (P=0.14). However, non-ketogenic low carb diets do not appear to have this effect. In fact, they appear to lower ApoB by 0.05 g/L, and the results were statistically significant (P=0.02). This is probably good news.
Not everyone reports this effect of a ketogenic diet, however. Many report extremely high LDL levels on the diet [3](https://thenutrivore.blogspot.com/2020/09/dave-feldmans-rhetoric-is-dangerous.html). Not to mention the fact that we do have epidemiology investigating the relationship between high LDL and CVD endpoints in the context of a low TG/HDL ratio [4](https://pubmed.ncbi.nlm.nih.gov/25458651/).
![[1-17.jpg]]
Of all of the high-LDL phenotypes, it is certainly optimal to maintain lower TG and higher HDL. However, it is still not as good as having normal lipids overall. This looks great for ketogenic diets, if you think about it. Higher TG could carry a residual, independent CVD risk, even after controlling for ApoB [5](https://pubmed.ncbi.nlm.nih.gov/32203549/). However, this is not always observed [6](https://pubmed.ncbi.nlm.nih.gov/30694319/). 
I think we all appreciate that ketogenic diets have a tendency to lower TG. So, for the sake of argument let's just grant that lowering TG is independently beneficial for CVD risk reduction. With that in mind, let's investigate the relationship between ketogenic diet and TG when stratified by weight loss:
![[1-44.png]]
According to this analysis, ketogenic diets fail to lower TG unless weight loss was achieved (P=0.67). However, if weight loss is achieved, a ketogenic diet may lower TG by 22-47mg/dL. So, there doesn't seem to be anything uniquely protective about a ketogenic diet with regards to how it affects either TG or ApoB, independent of weight loss. For this reason I would suspect that ketogenic diets likely don't improve CVD risk by improving the TG either.
In conclusion, do ketogenic diets uniquely protect against CVD as a function of correcting the TG/HDL ratio? Probably not. That being said, ketogenic diets don't seem to have any uniquely atherogenic tendencies, either. However, if you are on a ketogenic diet and experience a pathological increases to your ApoB, you're probably worse off than you were.
**Key points:**
- Ketogenic diets typically lower TG and increase HDL.
- The TG/HDL ratio is a strong correlate for CVD outcomes because it is also a correlate for ApoB.
- ApoB is a causal agent in the pathogenesis and pathophysiology of CVD.
- Ketogenic diets do not tend to increase ApoB.
- Ketogenic diets do not improve TG independent of weight loss.
- Ketogenic diets are not likely to be uniquely protective against CVD as a function of their "tendency" to lower the TG/HDL ratio.
**References:**
[1] [https://pubmed.ncbi.nlm.nih.gov/18719750/](https://pubmed.ncbi.nlm.nih.gov/18719750/)
[2] [https://pubmed.ncbi.nlm.nih.gov/15296705/](https://pubmed.ncbi.nlm.nih.gov/15296705/)
[3] [https://thenutrivore.blogspot.com/2020/09/dave-feldmans-rhetoric-is-dangerous.html](https://thenutrivore.blogspot.com/2020/09/dave-feldmans-rhetoric-is-dangerous.html)
[4] [https://pubmed.ncbi.nlm.nih.gov/25458651/](https://pubmed.ncbi.nlm.nih.gov/25458651/)
[5] [https://pubmed.ncbi.nlm.nih.gov/32203549/](https://pubmed.ncbi.nlm.nih.gov/32203549/)
[6] [https://pubmed.ncbi.nlm.nih.gov/30694319/](https://pubmed.ncbi.nlm.nih.gov/30694319/)
#patreon_articles
#nutrition
#disease
#keto
#cardiovascular_disease
#coronary_heart_disease
#LDL
#ApoB
#HDL
#triglycerides

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💻 Hyperblog/Blogs/Patreon/Does Keto Reverse Fatty Liver.md Executable file
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Do low-carbohydrate ketogenic diets (LCKD) reverse fatty liver? This idea is circulated widely in many LCKD communities, and the idea itself is actually very simple and has some mechanistic plausibility— ketones are made from fatty acids in the liver, therefore a LCKD will burn through those fatty acids faster than a non-ketogenic diet. Let's investigate this.
There have been plenty of trials investigating the effects of LCKDs on abdominal fat mass (AFM) in humans [1](https://pubmed.ncbi.nlm.nih.gov/19373224/)[2](https://pubmed.ncbi.nlm.nih.gov/31963475/)[3](https://pubmed.ncbi.nlm.nih.gov/18326593/)[4](https://pubmed.ncbi.nlm.nih.gov/31277506/)[5](https://pubmed.ncbi.nlm.nih.gov/19082851/)[6](https://pubmed.ncbi.nlm.nih.gov/33042004/)[7](https://pubmed.ncbi.nlm.nih.gov/32179679/). Most of them see a benefit of the LCKD. In the aggregate, LCKDs tend to lead to an average of 730g of AFM.
**Abdominal Fat Mass:**
![[1-71.png]]
**Intrahepatic Triglycerides:**
![[Pasted image 20221123154528.png]]
The majority of studies find a statistically significant reduction in AFM, but does this actually mean that the keto rabble were right? No really. Not yet, anyway. Other research shows that non-ketogenic weight loss can produce linear reductions in AFM [8](https://pubmed.ncbi.nlm.nih.gov/31685793/).
![[Pasted image 20221123154517.png]]
In this paper, obese women were put on weight loss diets that were 50% carbohydrates by energy. There was a linear reduction in AFM that was commensurate with a reduction in total body weight (R^2 = 0.981). 
So, what happens when we scrutinize the LCKD literature in the same way, and stratify the studies by achieved weight loss and AFM reduction?
![[Pasted image 20221123154457.png]]
We see virtually the exact same relationship (R^2 = 0.857). The more weight that subjects lost, the more AFM that they lost as well. In fact, no study investigating the relationship between LCKDs and AFM has succeeded in keeping subjects weight stable. Every last study saw reductions in body fat, even these two additional studies that couldn't be included in the forest plots above due to unclear reporting [9](https://pubmed.ncbi.nlm.nih.gov/29456073/)[10](https://pubmed.ncbi.nlm.nih.gov/17219068/).
It is also untrue that LCKDs offer immunity to AFM accumulation. This is evidenced by a case report of a 57-year old woman who developed hepatic steatosis in response to a self-administered LCKD [11](https://pubmed.ncbi.nlm.nih.gov/32064187/). Her diet consisted of eggs, cheese, butter, oil, nuts, leafy green vegetables, and low-carbohydrate plant-based milk alternatives.
![[Pasted image 20221123154452.png]]
In conclusion, we can say that LCKDs do tend to reduce AFM in humans. This is because LCKDs tend to lead to weight loss when compared to the average diet. However, that is not to say that LCKDs actually lead to unique reductions in AFM independent of weight loss. That has not yet been demonstrated, and more research is required to elucidate the effects of LCKDs on AFM.
**Key points:**
- It is claimed that ketogenic diets uniquely reduce abdominal fat mass independent of weight loss.
- No study to date has controlled for weight loss well enough to divulge this.
- There is no evidence that ketogenic diets reduce abdominal fat mass independent of weight loss.
**References:**
[1] [https://pubmed.ncbi.nlm.nih.gov/19373224/](https://pubmed.ncbi.nlm.nih.gov/19373224/) 
[2] [https://pubmed.ncbi.nlm.nih.gov/31963475/](https://pubmed.ncbi.nlm.nih.gov/31963475/) 
[3] [https://pubmed.ncbi.nlm.nih.gov/18326593/](https://pubmed.ncbi.nlm.nih.gov/18326593/) 
[4] [https://pubmed.ncbi.nlm.nih.gov/31277506/](https://pubmed.ncbi.nlm.nih.gov/31277506/) 
[5] [https://pubmed.ncbi.nlm.nih.gov/19082851/](https://pubmed.ncbi.nlm.nih.gov/19082851/) 
[6] [https://pubmed.ncbi.nlm.nih.gov/33042004/](https://pubmed.ncbi.nlm.nih.gov/33042004/) 
[7] [https://pubmed.ncbi.nlm.nih.gov/32179679/](https://pubmed.ncbi.nlm.nih.gov/32179679/) 
[8] [https://pubmed.ncbi.nlm.nih.gov/31685793/](https://pubmed.ncbi.nlm.nih.gov/31685793/) 
[9] [https://pubmed.ncbi.nlm.nih.gov/29456073/](https://pubmed.ncbi.nlm.nih.gov/29456073/) 
[10] [https://pubmed.ncbi.nlm.nih.gov/17219068/](https://pubmed.ncbi.nlm.nih.gov/17219068/) 
[11] [https://pubmed.ncbi.nlm.nih.gov/32064187/](https://pubmed.ncbi.nlm.nih.gov/32064187/)
#patreon_articles
#nutrition
#disease
#non_alcoholic_fatty_liver_disease
#keto

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💻 Hyperblog/Blogs/Patreon/Does LDL Cause Cardiovascular Disease.md Executable file
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If we spend any time in the low carb or ketogenic corners of Twitter, we'll undoubtedly encounter the suggestion that low density lipoproteins (LDL) do not actually cause atherosclerotic cardiovascular disease (ASCVD). So, I'm going to just quickly go over the evidence for why this is complete bullshit, and I will also explain why medical practice wouldn't change even if it wasn't bullshit. It would also be a good idea to get a refresher on ASCVD pathophysiology from my previous blog article [here](https://www.patreon.com/posts/why-does-ldl-33915357).
Let's start off with the randomized controlled trial (RCT) data. In biomedical science, RCT data gives us the best possible reflection of cause and effect relationships between variables. For example, if we administer a drug in one random group of people and a placebo in a likewise random group of people, we can measure differences in endpoints between these groups and ascertain the independent effects of the drug. If the intervention group yields consistent, statistically significant effects, this gives us a strong basis for causal inference.
We have a number of RCTs testing different mechanisms for lowering LDL in humans. When you consider all of these interventions together in a meta-regression analysis, it is revealed that an intervention lowers ASCVD events in proportion to the LDL-lowering effect of the intervention itself [1](https://pubmed.ncbi.nlm.nih.gov/27673306/). This means that the reductions in ASCVD events can be accurately predicted by the degree of LDL lowering achieved. The sole exception is CETP-inhibitors, but they did not actually lower LDL. They lowered the cholesterol content of LDL, and also inhibited reverse cholesterol transport. 
![[1-15.jpg]]
Is this just an amazing coincidence, or are we looking at a cause and effect relationship? Imagine what would need to be true in order for this to **not** be a cause and effect relationship. All of these mechanisms would need to be operating through independent pleiotropic mechanisms that all conspire to produce reductions in ASCVD events that can be reliably predicted by the degree of LDL-lowering achieved. That's crazy. But, even if it were true, it looks like LDL would still be a reasonable target for therapy, because it is the common denominator between all of those hypothetical pleiotropic mechanisms.
Next we have more natural experiments. These come in the form of Mendelian randomization (MR) studies, which are types of observational research that investigate the relationships between gene variants and outcomes in free-living populations. Basically, we presume that gene variants are randomly distributed across the population, such that relevant covariates  are also randomized. This essentially creates the next best thing to an RCT, and likely would sit just under RCTs on the hierarchy of evidence.
Again, we have plenty of gene variants that modulate LDL up or down. When we look at gene variants that reduce LDL, we see the same hierarchy of effect that we see with the RCTs [2](https://pubmed.ncbi.nlm.nih.gov/30694319/). The ASCVD event reduction is also a function of the LDL-lowering that resulted from the particular gene variant. If you have a gene variant that reduces LDL by a little, you see a little effect. If you have a gene variant that reduces LDL by a lot, you see a larger effect.
![[1-14.png]]
Again, is this just a remarkable coincidence that these two lines of data converge so perfectly? I'll make the same argument again. What would need to be true in order for LDL to **not** be causal here? Again, all of these gene variants would need to be operating through independent pleiotropic mechanisms that all conspire to produce reductions in ASCVD events that can be reliably predicted by the degree of LDL-lowering achieved. Again, that's crazy. But again, even if it were true it would still be a good idea to target LDL to lower ASCVD events.
**Key points:**
- It has been suggested that LDL are not causal in ASCVD.
- Randomized controlled trials using eight different mechanisms to lower LDL all see reductions in ASCVD events that are predicted by the degree of LDL-lowering achieved.
- Mendelian randomization studies investigating almost two dozen different mechanisms that lower LDL all see reductions in ASCVD events that are predicted by the degree of LDL-lowering achieved.
- LDL is causal in ASCVD, but even if it wasn't it would still be a good idea to target LDL to reduce ASCVD events. 
**References:**
[1] Michael G Silverman, et al. Association Between Lowering LDL-C and Cardiovascular Risk Reduction Among Different Therapeutic Interventions: A Systematic Review and Meta-analysis. JAMA. 2016 Sep. [https://pubmed.ncbi.nlm.nih.gov/27673306/](https://pubmed.ncbi.nlm.nih.gov/27673306/) 
[2] Brian A Ference, et al. Association of Triglyceride-Lowering LPL Variants and LDL-C-Lowering LDLR Variants With Risk of Coronary Heart Disease. JAMA. 2019 Jan. [https://pubmed.ncbi.nlm.nih.gov/30694319/](https://pubmed.ncbi.nlm.nih.gov/30694319/)
#patreon_articles
#LDL
#cardiovascular_disease
#disease
#ApoB

25
💻 Hyperblog/Blogs/Patreon/Does TIme Restricted Feeding Increase CVD Risk?.md Executable file
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Many people have asked me to comment on a recent poster of a study from the American Heart Association (AHA) that purports to have discovered a link between time-restricted feeding (TRF) and cardiovascular disease (CVD) mortality (https://newsroom.heart.org/news/8-hour-time-restricted-eating-linked-to-a-91-higher-risk-of-cardiovascular-death). Essentially the study broke the cohort up into five non-uniform quintiles of feeding window duration: <8h, 8-<10h, 10-<12h, 12-16h, and >16h. Participants with a mean age of 48 were followed for eight years time, and it was apparently discovered that those eating in a window of less than eight hours per day almost doubled their risk of dying due to CVD.
I'll start of by saying that the study itself is not the most impressive piece of epidemiology I've ever seen, and I remain skeptical that we're observing a genuine causal relationship. Let me explain. While the study did include a large sample size of over 20,000 participants, it's important to note some key limitations. Firstly, the population data comes from the National Health and Nutrition Examination Survey (NHANES) dataset, which didn't use very rigorous measurements of dietary intake (https://www.cdc.gov/nchs/nhanes/measuring_guides_dri/measuringguides.htm). In fact, it's not entirely clear how they extracted feeding window data from the NHANES dataset at all, since the diet-related data just contains two 24-hour dietary recalls as their measurement of food intake between 2003 and 2018.
Before we go further into my criticisms, let's discuss a few of the findings. Essentially, Eight-hour TRE was not linked to reductions in all-cause or cancer mortality when compared to other eating windows durations. A significant association was found between the <8h TRE window and a higher risk of CVD mortality. This was true both in the general population and among individuals with preexisting CVD or cancer. Lastly, eating durations exceeding 16 hours per day were associated with a lower risk of cancer mortality in people with cancer. Which is actually understandable, since a significant causes of death in cancer patients is wasting due to cachexia (https://pubmed.ncbi.nlm.nih.gov/25291291/).
Now let's go over some issues. As previously mentioned, one of the biggest issues is the quality of the dietary assessment and the lack of clarity about how the feeding windows were ascertained. But, even if we grant that the dietary and feeding window measurements were precise and accurate, we still would have a good reason to question the results. Firstly, the adjustment model, while admittedly comprehensive by conventional standards in nutritional epidemiology, lacked at least one key confounder. For example, there is no adjustment for occupation, which makes shiftwork a potential confounder that went unaccounted for. Shiftwork can limit one's access to food (and opportunities to eat it even if there is access), forcing individuals to shorten their feeding window. But shiftwork also increases the risk of CVD (https://pubmed.ncbi.nlm.nih.gov/29247501/).
Another concerning issue is that the sample size for the <8h quintile was only 414 participants out of a total sample of >20,000, and only seeing 31 events. That's only 2.1% of the total study population. This could drastically influence the reliability of the risk estimate for this group. The bulk of the participants landed in the reference quintile of 12-16h, at 11,831 participants. There also wasn't a clear dose-response, with the 8-<10h and 10-<12h quintiles not being statistically significantly different from the reference quintile. I just don't have a lot of confidence in the sample size. Lastly, another issue is the population's mean age. Overall, participants were an average of 48 years old, but the <8h quintile was almost seven years younger at 41 years old on average. CVD deaths are far less prevalent at this age, which can easily inflate the relative risk, making a potential statistical anomaly appear more severe than it rightfully is.
Just for flavour, there is one other reason to doubt the findings, and it's a reason that is even mentioned by the authors themselves. From the randomized controlled trials (RCTs) that have been done on TRF, we don't have a good reason to believe that such a population would be at an increased risk of CVD to begin with. If anything, we'd expect such a population of people to have a lower overall risk of CVD (https://pubmed.ncbi.nlm.nih.gov/31808043/)(https://www.researchgate.net/publication/353140261_Effect_of_Time-Restricted_Feeding_on_Body_Weight_and_Cardiometabolic_Risks_A_Systematic_Review_and_Meta-Analysis_of_Randomized_Controlled_Trials). Overall there are, in my opinion, good reasons to doubt the findings, and there are other explanations for the relationship that seem altogether more plausible.
In light of the methodological challenges, small sample size for the key group, and conflicting evidence from prior randomized controlled trials, the study's claim of a near-doubling in cardiovascular disease mortality risk with an 8-hour time-restricted feeding pattern should be interpreted with caution. Further rigorous research is necessary to validate these findings and clarify the true impact of time-restricted feeding on long-term cardiovascular health.
**Key points:**
- Reliance on NHANES dataset with 24-hour dietary recalls may not accurately measure TRF, and lack of adjustment for shift work could skew results.
- The <8h TRF group was a small fraction of the study, potentially affecting the reliability of CVD mortality risk findings.
- The study's conclusion that TRF increases CVD mortality contradicts evidence from other RCTs suggesting cardiometabolic benefits of TRF.
#patreon_articles
#nutrition
#time_restricted_feeding

64
💻 Hyperblog/Blogs/Patreon/Fact-Checking Chris Masterjohn (Part 1), Are PUFAs Toxic.md Executable file
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Recently, Chris Masterjon hosted a [live Q&A](https://www.youtube.com/watch?v=WRmUzYD8l7Q) about nutrition and health. A viewer asked Chris if polyunsaturated fats (PUFA) were toxic and to be avoided. Chris' answers were mostly reasonable and didn't quite devolve into a blatant anti-PUFA narrative until about 25 minutes into the video.
Chris spends most of the video caveating his empirical claims at the end. To his credit at least he is prefacing his scaremongering with the caveat that he doesn't believe PUFA-avoidance is rational if it compromises the nutritional adequacy of the diet. Which is fine. I don't think food avoidance makes much sense in that case myself as well.
His empirical claims begin around 25 minutes into the video, so let's start there.
[**24:47**](https://youtu.be/WRmUzYD8l7Q?t=1489) 
**Claim:** There is some indication that if the population is old enough, substituting PUFAs for saturated fat (SFA) can increase the risk of cancer.
**Fact:** I have touched on this topic before [here](https://www.patreon.com/posts/do-vegetable-48046151), and discussed in detail why it is probably wrong. Essentially, the only randomized controlled trial (RCT) that actually observed a potential association between PUFA and cancer risk had a couple issues [1](https://pubmed.ncbi.nlm.nih.gov/4100347/). Firstly, the effect itself was unadjusted and non-significant. Secondly, the effect nullified after an adjustment for adherence.
A recent meta-analysis investigating the relationship between PUFA and cancer in RCTs found the same non-significant increase in risk for some cancers [2](https://pubmed.ncbi.nlm.nih.gov/32114592/). However their risk-of-bias assessment revealed that most of the included trials either had an unknown or high risk of bias due to poor compliance and attention.
Cochrane also did their own meta-analysis investigating this question in one of their secondary endpoint analyses [3](https://pubmed.ncbi.nlm.nih.gov/32428300/). Their findings were also null, as we might suspect.
![[1-60.png]]
There is very limited evidence from certain observational studies that PUFA intake may increase the risk of certain types of skin cancer [4](https://pubmed.ncbi.nlm.nih.gov/31298947/). However, higher PUFA intakes seem to lower cancer risk, or have no effect, overall [5](https://pubmed.ncbi.nlm.nih.gov/32020162/)[6](https://pubmed.ncbi.nlm.nih.gov/30545042/).
[**25:00**](https://youtu.be/WRmUzYD8l7Q?t=1503) 
**Claim:** You cannot make a strong case that increasing PUFAs improves heart disease outcomes.
**Fact:** This is an extremely bold claim, because it is one of the most robust and well-studied effects of diet on chronic disease risk that we have in nutrition science. I wrote about this in detail [here](https://thenutrivore.blogspot.com/2020/05/saturated-fat-cutting-through-noise.html).
Again, referencing Lee Hooper's Cochrane review on SFA from 2020, we see that the extend to which SFA lowers cholesterol will dictate the degree of heart disease risk reduction [3](https://pubmed.ncbi.nlm.nih.gov/32428300/).
![[1-62.png]]
This relationship was also discovered in a subgroup meta-regression analysis conducted in 2016 by Silverman et al [7](https://pubmed.ncbi.nlm.nih.gov/27673306/). Four diet trials were included in this analysis. These trials were investigating the relationship between dietary fat and heart disease when PUFA is substituted for SFA. Again, the degree of cholesterol-lowering dictates reductions in disease risk.
![[1-59.png]]
[**25:25**](https://youtu.be/WRmUzYD8l7Q?t=1525)
**Claim:** While reducing serum cholesterol may lower heart disease risk, increasing PUFA increases the tendency for LDL to oxidize, which also contributes to heart disease.
**Fact:** I have written about this point [here](https://www.patreon.com/posts/does-saturated-35112489). While it is true that oxidized LDL are implicated in the pathogenesis of heart disease, it has never been persuasively shown that increasing dietary PUFA increases heart disease risk. It is also true, as references in my linked article, that eating SFA to the exclusion of PUFA also predisposes LDL to oxidation. MUFA does not seem predispose LDL to oxidation to the same extent as SFA or PUFA, but MUFA is actually not as effective as PUFA in lowering CVD risk [8](https://pubmed.ncbi.nlm.nih.gov/26429077/).
![[1-61.png]]
**References:**
[1] [https://pubmed.ncbi.nlm.nih.gov/4100347/](https://pubmed.ncbi.nlm.nih.gov/4100347/)
[2] [https://pubmed.ncbi.nlm.nih.gov/32114592/](https://pubmed.ncbi.nlm.nih.gov/32114592/)
[3] [https://pubmed.ncbi.nlm.nih.gov/32428300/](https://pubmed.ncbi.nlm.nih.gov/32428300/)
[4] [https://pubmed.ncbi.nlm.nih.gov/31298947/](https://pubmed.ncbi.nlm.nih.gov/31298947/)
[5] [https://pubmed.ncbi.nlm.nih.gov/32020162/](https://pubmed.ncbi.nlm.nih.gov/32020162/)
[6] [https://pubmed.ncbi.nlm.nih.gov/30545042/](https://pubmed.ncbi.nlm.nih.gov/30545042/)
[7] [https://pubmed.ncbi.nlm.nih.gov/27673306/](https://pubmed.ncbi.nlm.nih.gov/27673306/)
#patreon_articles
#nutrition
#polyunsaturated_fat
#clownery
#cardiovascular_disease
#LDL

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💻 Hyperblog/Blogs/Patreon/Fact-Checking Kyle Mamounis (Part 1), Cholesterol and Heart Disease.md Executable file
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For those of you who are unaware, Kyle Manounis is a nutrition scientist who frequently publishes on the effects of dietary fatty acids in rodent models. He holds a number of radical views regarding diet, disease, and diet-disease relationships. For example, he has particular disdain for polyunsaturated fatty acids, and considers them undesirable, despite the overwhelming evidence of benefit in humans. 
Apparently Kyle has published the [first video](https://www.youtube.com/watch?v=h_9aG01n2Oc) in a new series on heart disease. Given how egregious it was, I've decided to make it my mission to fact-check each of the videos in his series as they are published. So let's get into the first one.
[**1:26**](https://youtu.be/h_9aG01n2Oc?t=86)
**Claim:** The lipid hypothesis is untenable if several carefully selected datasets reveal results contrary to its principles.
**Fact:** This is an example of a fallacy in the philosophy of science known as naive falsification. Naive falsification is invalid under the Duhem–Quine thesis, which argues that hypotheses can never be tested in truly assumption-free conditions. This means that if our hypotheses fail to predict results, we are never truly certain whether or not this is due to an error with the hypothesis or an error with our knowledge. 
For this reason, we assess the likelihood of causality using confidence, because absolute certainty will always be unattainable. Confidence is built on what we observe in the aggregate. As such, outliers do not overthrow hypotheses.
[**6:50**](https://youtu.be/h_9aG01n2Oc?t=410)
**Claim:** The diet-heart hypothesis would posit that dietary cholesterol consumption would predict serum cholesterol concentration.
**Claim:** The lipid hypothesis and diet-heart hypothesis should be able to predict heart disease, as a function of serum cholesterol levels.
**Claim:** Interventions to lower serum cholesterol should predict reductions in heart disease outcomes.
**Fact:** He’s equivocating by using serum cholesterol and LDL-cholesterol as interchangeable terms, and he has even gone so far as to mention that LDL particles (LDL-P) are the focus of both the lipid hypothesis and the diet-heart hypothesis. No credible, modern interpretation of either hypothesis is concerned with total serum cholesterol (TC). Apolipoprotein B-containing lipoproteins (ApoB) are the current targets for therapy.
[**9:04**](https://youtu.be/h_9aG01n2Oc?t=545) 
**Claim:** The 1988 paper titled “Cholesterol and lipids in the risk of coronary artery disease - the Framingham Heart Study” authored by WP Castelli states that "35 years of data suggest factors other than total or low density lipoprotein (LDL) cholesterol must be considered when evaluating [coronary artery disease] (CHD) risk. Low levels of high density lipoprotein cholesterol (HDL-C) needed for predictive power: total cholesterol/HDL".
**Fact**: The paper actually states that LDL-cholesterol is predictive of CHD, and that non-HDL-cholesterol (non-HDL-C) is most robustly predictive. This is perfectly consistent with what the modern lipid hypothesis would predict, as it recognizes non-HDL-C as one of the most validated marker of ASCVD risk [1](https://pubmed.ncbi.nlm.nih.gov/28444290/).
![[0L5tTbvNaPndZVTxy5kEH0b7wZVWT7S_muIE6Jp2geu4UBg5pte940rR4FrTcEVPvlLv-73QNKmmLMvcJQqdjz_pPMvUkNQhvuBT.png]]
This is because non-HDL-C is a near-perfect correlate for ApoB. Remember, ApoB is the primary target for therapy in the prevention of ASCVD.
![[m9kF7u1MTifBZL5jccuheHUTKq6Fh2KAiNHjJhofzY7GT8tDDLX1xX74IyxFJXp7kbahmj3tcS0kpmJQyRXm9t2w2qQk1wKHptrJ.png]]
However, that actually isn't to say that the older risk correlates are no longer reliable. TC and HDL are still a tight correlate for CVD events (AMI) in a dose-dependent manner [2](https://pubmed.ncbi.nlm.nih.gov/25568296/). In terms of risk, non-HDL-C has better predictive power than LDL-C [3](https://pubmed.ncbi.nlm.nih.gov/22453571/). So naturally it is considered over LDL-C in an assessment of ASCVD risk. Again, this is because non-HDL-C is an extremely tight correlate for ApoB [4](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3056766/).
![[E4J9gGioMg-RMWKRBf9DYzwqh2sLmsGcLZYsMBOeIj5X7G9seK8xPoKRvjz_8KALdYsGd4KJ-6erYdQ-uPC-4mgaO0HLZ5pDwzsf.png]]
[**11:21**](https://youtu.be/h_9aG01n2Oc?t=679)
**Claim:** More markers for ASCVD progression are being proposed, not because these markers are actually better discoveries, but because it is an attempt to explain heterogeneity in the results.
**Fact:** Yes, as discussed above, there is heterogeneity when looking at LDL-C, TC, or even HDL-C in isolation. However, they are all still correlates for risk. We just have better correlates these days. The discovery of better correlates does not invalidated previously discovered correlates. Right now, the best correlate we have is either LDL-P or ApoB [5](https://pubmed.ncbi.nlm.nih.gov/21392724/)[6](https://pubmed.ncbi.nlm.nih.gov/30694319/)[7](https://pubmed.ncbi.nlm.nih.gov/32203549/).
![[kfdabcw1EzLqsFb12DJo3ss6D4R3bmQcnlfm8G_FD_Jm6En0AJMEwHutl53p0L_t6ohRtEwUPRvchu-a7l7wIgBrM01FuBm4zufU.png]]
The only correlate that survives multivariable adjustment is ApoB at the end of the day.
[**11:50**](https://youtu.be/h_9aG01n2Oc?t=709) 
**Claim:** No statistically significant differences in serum cholesterol with regards to egg consumption, which contradicts the diet-heart hypothesis.
**Fact:** The relationship between dietary cholesterol and TC is a hyperbolic curve [8](https://pubmed.ncbi.nlm.nih.gov/1534437/). If the background diet of the subjects was already sufficiently high enough in dietary cholesterol, you would not expect to see a robust effect.
![[6vNu8uFpKZVX3qh4bcBlWMPmKy-yYR_BW-h7hAm-WGG7zV4OWs-iEdlSLH6bVC3mVOiWy_euM13LClwrB-n4DQ5UiANHGsrkshDO.png]]
Meta-regression analyses on cholesterol-feeding studies divulge the non-linearity in the effect of dietary cholesterol on blood lipids, particularly LDL-C [9](https://pubmed.ncbi.nlm.nih.gov/30596814/). With intakes of dietary cholesterol exceeding 300mg/day, it is statistically unlikely that you would continue to see increases in LDL-C.
![[HVxrrrcwIH4Kgu8Kv0Px3wA1lvgeg1v1SMJDKWyI9RtazULQokAqgvD_M4sE1tPjcEd_Rm1AGfFALscrnwzfZRee8EVYcLSO4B28.png]]
While dietary cholesterol is part of the Keys equation, which is an equation that is used to predict the effect of dietary lipids on blood lipids, dietary cholesterol was never a primary consideration for the diet-heart hypothesis [10](https://academic.oup.com/jn/article-abstract/59/1/39/4722525).
![[pjLYKPrQCY2wj6J6yh63jktj6e5H4j7pomxz9wGDIVe9sQo8cWhnI2XEznOci2xzYBbni46tPyweiG2ultqAV9sjinzFiYY5pX8T.png]]
In fact, Ancel Keys himself had stated that dietary cholesterol was not likely to be a significant contributor to ASCVD risk.
![[HbWG2hVKTppNaob8CJS_CpDOYd9Qujg--p-aXWQwrWSDCwozmz1Wo2OJ90KkShxN_mPjpI2QFaBN2gYoPks_8FyUQT5T2fylvGS4.png]]
![[vMAtMf7I_llynE4plxW-QkBeMlk3GHOKm_iQj4PImEOLx3vdQU5G3I6nP3vzPDh3lecF0pHHV6y3aeEylQZURGZGxwRBnzB-5U1y.png]]
[**13:43**](https://youtu.be/h_9aG01n2Oc?t=823)
**Claim:** Contradictory findings mean that you “don’t have anything”. Which is to say that the hypothesis is wrong if it fails to predict an outcome.
**Fact:** As previously mentioned, this would only makes sense if scientific investigation was assumption-free. Inconsistent findings could result from covariates or confounders that have not been identified and accounted for in some datasets versus other datasets.
Also, lacking an association does not necessarily mean that there is nothing there. It could just as easily mean that more investigation is needed so we can recalibrate our assumptions. For example, testing for linear effects when the effect is non-linear can easily hide associations.
[**17:10**](https://youtu.be/h_9aG01n2Oc?t=1031) 
**Claim:** Decreases in cardiovascular disease mortality were concomitant with increases in serum cholesterol levels in Japanese populations.
**Fact:** The 1980s saw an explosion in advancements to medical technology that led to better treatment of ASCVD. In relation to the diet-heart hypothesis, this is best observed by looking at the North Karelia Project [11](https://pubmed.ncbi.nlm.nih.gov/19959603/).
![[nB9abdWnslsyX6h1PqWB07bJcY_FTGvvz-OgaWrLicDvzIgosObIUrb8M6I_MVkp7wjDf873yIkenfg4J6fBatDEMr8GYwjxQQmb.png]]
Reductions in serum cholesterol as a consequence of replacing butter with unsaturated fats accounted for 50% of the 30% reduction in CHD mortality between 1972 and 1985. However, the modeled reductions in CHD mortality diverge from the observed reductions in CHD mortality in 1985 due to advancements in medical technology.
![[8gpMO2vFWF3kOOYHECmMqpMfWVPGxSligaCll3LT9iXedc3yo8OGsliw66uEHgw7cWHx7jPv2qrGXSeZe0Ej1oEiT4rJ7i-BfPF2.png]]
[**19:00**](https://youtu.be/h_9aG01n2Oc?t=1140) 
**Claim:** There is an inverse association between serum cholesterol and acute myocardial infarction or unstable angina in high risk populations over <70 years of age.
**Fact:** Even if acute myocardial infarction (AMI) is the leading cause of mortality in your population, the age of the population matters. The risk of AMI peaks between the ages of 45-65. Beyond 65, your risk of dying from ASCVD is lower by virtue of the fact that the risk of dying due to other diseases is going up. If high cholesterol doesn’t kill you between the ages of 45-65, it is unlikely to kill you before something like cancer does, for example.
Also, many of the diseases that would be likely to kill you instead of ASCVD result in lower cholesterol, so reverse causality is still a valid explanation without appropriate adjustment.
![[oGhWZ9iBql5WsxhWpHgcIdOTyO2FXtLx8_0WxI3meXVxEIEw2EVKrJ90iHXyT31J7hx_Qjng3pwQqlNZugfHoTUXIgdlEWUYT0l6.png]]
[**26:30**](https://youtu.be/h_9aG01n2Oc?t=1590) 
**Claim:** In reference to the relationship between coronary artery calcification and statin medication, there was more coronary artery calcification in the group receiving a higher dose of atorvastatin.
**Fact:** The effect of statin therapy on CAC progression appears to be a function of the baseline level of calcification present [12](https://pubmed.ncbi.nlm.nih.gov/33426001/). In the aggregate, subjects on statin therapy with CAC scores exceeding 400 see a statistically significant decrease in calcium scores by the end of the study period (P=0.009).
![[9QhaGijiaFvLR5Yd-5Pk1rxyqAkDVWfps-TK2Q73_PRkKRwSgSgTKOnTyadV5_0R_tWPAoz6cWFaV0hy25MRxk3VoqzRCwlFl9DD.png]]
Kyle’s referenced study was among the studies in the statistically significant subgroup, and showed a non-significant trend toward a benefit of statins. Kyle is misreading the figure provided in the original paper [13](https://pubmed.ncbi.nlm.nih.gov/16415377/).
![[uFF2GlLwgjQXPH4jhka9x_1J3H--pUube2oP0p-tXHKyWnJqcLHEQfVLdOBUcC5tBBV00ccfleVPseQyrw32K9J7W6GOea-TB90j.png]]
It looks like the group receiving the higher dose of atorvastatin had more CAC progression, however these are representing medians and percentiles. Generally statistics like this are reported as means and confidence intervals or standard deviations, like they are in the meta-analysis above. When represented this way, there is a trend toward a benefit of statins consistent with the majority of the literature on this subject.
[**28:08**](https://youtu.be/h_9aG01n2Oc?t=1688) 
**Claim:** Both the diet-heart hypothesis and lipid hypotheses fail to explain all observations pertaining to lipids and atherogenesis.
**Fact:** Again, for the reasons we discussed throughout this article, this is essentially just naive falfisicationism. A hypothesis failing to predict an outcome does not necessarily invalidate the hypothesis.
[**28:32**](https://youtu.be/h_9aG01n2Oc?t=1712)
**Claim:** Heterogeneity in the results of studies using similar methodologies usually means there is a third unmeasured variable that is interacting with the variables you’re measuring and/or manipulating.
**Fact:** It is true that a third unmeasured confounder could explain heterogeneity in some cases. But it depends on the extent of the heterogeneity and how likely it is that unmeasured confounders could explain the effects that we observe. 
With regards to statin medication and CAC, there is some heterogeneity, but overall statins are beneficial. With regards to the prevention of ASCVD events, the effect of statins is **overwhelmingly** beneficial.
![[WTJMMBj5ctIOzC4fdGvfNQFyV258Ys-ww572VORdwV8bbOAN9-U4Zc2UAlzt1JnWZsuYv44suFLaWFUq7BLM7a6DUlyzkrV4KXWd.png]]
**References:**
[1] [https://pubmed.ncbi.nlm.nih.gov/28444290/](https://pubmed.ncbi.nlm.nih.gov/28444290/) 
[2] [https://pubmed.ncbi.nlm.nih.gov/25568296/](https://pubmed.ncbi.nlm.nih.gov/25568296/) 
[3] [https://pubmed.ncbi.nlm.nih.gov/22453571/](https://pubmed.ncbi.nlm.nih.gov/22453571/) 
[4] [https://pubmed.ncbi.nlm.nih.gov/21356116/](https://pubmed.ncbi.nlm.nih.gov/21356116/) 
[5] [https://pubmed.ncbi.nlm.nih.gov/21392724/](https://pubmed.ncbi.nlm.nih.gov/21392724/) 
[6] [https://pubmed.ncbi.nlm.nih.gov/30694319/](https://pubmed.ncbi.nlm.nih.gov/30694319/) 
[7] [https://pubmed.ncbi.nlm.nih.gov/32203549/](https://pubmed.ncbi.nlm.nih.gov/32203549/) 
[8] [https://pubmed.ncbi.nlm.nih.gov/1534437/](https://pubmed.ncbi.nlm.nih.gov/1534437/) 
[9] [https://pubmed.ncbi.nlm.nih.gov/30596814/](https://pubmed.ncbi.nlm.nih.gov/30596814/) 
[10] [https://academic.oup.com/jn/article-abstract/59/1/39/4722525](https://academic.oup.com/jn/article-abstract/59/1/39/4722525) 
[11] [https://pubmed.ncbi.nlm.nih.gov/19959603/](https://pubmed.ncbi.nlm.nih.gov/19959603/) 
[12] [https://pubmed.ncbi.nlm.nih.gov/33426001/](https://pubmed.ncbi.nlm.nih.gov/33426001/)
#patreon_articles
#clownery
#cardiovascular_disease
#statins
#dietary_cholesterol
#LDL

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💻 Hyperblog/Blogs/Patreon/Healthy Processed Foods.md Executable file
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With so much chatter about how processed foods are bad for us, we often forget that this isn't always the case. In some cases the processing of foods actually enhances their healthfulness and quality overall. I will be exploring some examples here.
**Whey protein** isolate is a popular protein supplement and anabolic aid used athletes to help meet their daily protein requirements. Whey is helpful not only because it is high in leucine, the principle amino acid responsible for stimulating muscle protein synthesis, but because the food itself is easy to consume and digest due to the processing itself. Ease of consumption is usually problematic with foods, but in this case we can actually leverage this characteristic to our advantage. Whey protein has been used to augment lean body mass and resist losses of lean body mass in elderly adults [1](https://www.ncbi.nlm.nih.gov/pubmed/22338070)[2](https://www.ncbi.nlm.nih.gov/pubmed/30289425). The elderly often find it difficult to consume adequate protein due to diminished appetite and difficulty chewing, but because of the heavily processed nature of whey protein isolate, they can navigate around this problem.
**Yeast extract** is another heavily processed food that can be made from certain byproducts of beer fermentation. As a liquid it is a salty, somewhat gross-tasting condiment marketed as Marmite in the Europe and Canada, and as Vegemite in Australia. A similar product known as nutritional yeast is also available as dry flakes that taste an awful lot like fish food. Bizarrely enough, researchers have attempted to investigate the effects of supplementing some of these yeast-based products in humans. Marmite supplementation has been shown to affect that balance of excitatory and inhibitory neurotransmitters in the brain, and could potentially have clinical benefits for epilepsy [3](https://www.ncbi.nlm.nih.gov/pubmed/28376309). Brewer's yeast, which is the same species of yeast used to make nutritional yeast, has also been shown to reduce blood pressure and improve blood lipids in human subjects with type II diabetes [4](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3744257/).
**Fruit juices** of all sorts have been studied numerous times for their health-promoting characteristics. Say what you want about sugar or liquid carbs, but orange juice can improve endothelial function, blood lipids, and inflammatory markers in humans [5](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4045306/). Carrot juice can reduce lipid peroxidation cascades in humans [6](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3192732/). Lastly, V8, a type of tomato-based vegetable juice, has the potential to lower blood pressure in pre-hypertensive adults [7](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2949782/). There are plenty of other similar findings related to beet juice, pomegranate juice, and grape juice [8](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5372571/).
**Collagen** comes in two forms. The first being collagen hydrolysate, which is a collagen protein isolate that is made from artificially hydrolyzed collagen, using digestive enzymes or heat-treatment. Gelatin is a similar product, and is offered as a crystalline substance that is extracted from the tendons of animals. However, despite these cold descriptions, consuming collagen in these forms is incredibly safe and seems to have nothing but benefits. Effects of collagen supplementation range from increased tendon strength to improved skin appearance to better wound healing [9](https://www.ncbi.nlm.nih.gov/pubmed/27852613)[10](https://www.ncbi.nlm.nih.gov/pubmed/30681787).
**Key points:**
- There are certain processed foods that contribute positively to health.
- Protein isolates such as whey protein can help the elderly meet their protein needs.
- Yeast extracts are rich in B-vitamins and can improve certain markers of health.
- Many fruit juices have been shown to have positive health benefits.
- Consuming collagen peptides can improve tendon and skin health overall.
**References:**
[1] Pennings B, et al. Amino acid absorption and subsequent muscle protein accretion following graded intakes of whey protein in elderly men. Am J Physiol Endocrinol Metab. 2012 Apr.  [https://www.ncbi.nlm.nih.gov/pubmed/22338070](https://www.ncbi.nlm.nih.gov/pubmed/22338070) 
[2] Oikawa SY, et al. A randomized controlled trial of the impact of protein supplementation on leg lean mass and integrated muscle protein synthesis during inactivity and energy restriction in older persons. Am J Clin Nutr. 2018 Nov.  [https://www.ncbi.nlm.nih.gov/pubmed/30289425](https://www.ncbi.nlm.nih.gov/pubmed/30289425) 
[3] Smith AK, et al. Dietary modulation of cortical excitation and inhibition. J Psychopharmacol. 2017 May.  [https://www.ncbi.nlm.nih.gov/pubmed/28376309](https://www.ncbi.nlm.nih.gov/pubmed/28376309) 
[4] Payam H, et al. Brewer’s Yeast Improves Blood Pressure in Type 2 Diabetes Mellitus. Iran J Public Health. 2013 Jun.  [https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3744257](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3744257/)
[5] Sedigheh A, et al. Effect of Fresh Orange Juice Intake on Physiological Characteristics in Healthy Volunteers. ISRN Nutr. 2014 Mar.  [https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4045306](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4045306/)
[6] Andrew S P, et al. Drinking carrot juice increases total antioxidant status and decreases lipid peroxidation in adults. Nutr J. 2011 Sept.  [https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3192732](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3192732/)
[7] Sonia F S, et al. The use of a commercial vegetable juice as a practical means to increase vegetable intake: a randomized controlled trial. Nutr J. 2010 Sep.  [https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2949782](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2949782/)
[8] Jie Zheng, et al. Effects and Mechanisms of Fruit and Vegetable Juices on Cardiovascular Diseases. Int J Mol Sci. 2017 Mar.  [https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5372571](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5372571/)
[9] Shaw G, et al. Vitamin C-enriched gelatin supplementation before intermittent activity augments collagen synthesis. Am J Clin Nutr. 2017 Jan.  [https://www.ncbi.nlm.nih.gov/pubmed/27852613](https://www.ncbi.nlm.nih.gov/pubmed/27852613)
[10] Choi FD, et al. Oral Collagen Supplementation: A Systematic Review of Dermatological Applications. J Drugs Dermatol. 2019 Jan.  [https://www.ncbi.nlm.nih.gov/pubmed/30681787](https://www.ncbi.nlm.nih.gov/pubmed/30681787)
#patreon_articles
#nutrition
#healthy_diets
#processed_food
#whey
#yeast
#fruit_juices

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💻 Hyperblog/Blogs/Patreon/Heart Disease, LDL or Inflammation.md Executable file
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It's an age old question. Well, no, not really. It's actually just some fuckery that low carb knobs like to talk about. The question is whether or not low density lipoproteins (LDL) are causal of atherosclerotic cardiovascular disease (ASCVD) in the context of low inflammation. Luckily we have plenty of data on this question. So let's dive in.
Firstly, we have epidemiological data that aims to divide a population up into quartiles related to acute myocardial infarction (AMI) [1](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7343474/). These quartiles have varying levels and combinations of exposure to either high LDL, or high C-reactive protein (CRP): high LDL and high CRP, high LDL and low CRP, low LDL and high CRP, and low LDL and low CRP.
![[Pasted image 20221123154714.png]]
Looking carefully at this graph, we see that risk is lowest when both LDL and CRP are both low. But risk does go up in the context of low LDL and high CRP as well. The absolute worst situation to be in is with high LDL and high CRP. That group is in its own league in terms of risk.
So, these data would seem to suggest that, yes, high inflammation does carry an independent risk of increased AMI, and presumably ASCVD. However, let's take another look at the graph. The green line is representing the risk of AMI in the context of high LDL and low CRP. This is the context low carb people love to speculate about, and it shows that LDL carries an independent risk all on its own as well.
Recently, subgroup analyses on the FOURIER trial have also been done investigating the relationship between inflammation and ASCVD endpoints [2](https://www.ahajournals.org/doi/full/10.1161/CIRCULATIONAHA.118.034032). The results essentially show the same thing.
![[Pasted image 20221123154709.png]]
Again, we see that having both high LDL and high CRP together yields the worst outcomes, having either elevated in isolation increases risk, and having both as low as possible maximally decreases risk. Now, granted we can't technically call this experimental data as far as CRP is concerned, since this is a post-hoc, observational analysis. Nevertheless, it shows the exact same hierarchy of effect as the epidemiology.
Here's a representation of the data that is a little easier on the eyes:
![[Pasted image 20221123154659.png]]
Now, why isn't inflammation a target for therapy if it's so damn important? Well, the truth is we have attempted to target inflammation. The results have been almost universally unsuccessful [3](https://www.wjgnet.com/2220-6132/full/v8/i1/1.htm)[4](https://pubmed.ncbi.nlm.nih.gov/30560921/). We target LDL specifically because it is the most reliable target for therapy at this time. Interventions aimed to lower LDL reduce the risk of AMI and ASCVD, but interventions aimed to lower inflammation do not.
**Key points:**
- LDL and inflammation are both independently causal of ASCVD.
- Inflammation causes ASCVD in both high and low LDL contexts.
- LDL causes ASCVD in the context of both high or low inflammation.
- Interventions to lower inflammation have largely been unsuccessful in reducing the risk of ASCVD.
- Interventions to lower LDL have been overwhelmingly successful in reducing the risk of ASCVD.
**References:**
[1] [https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7343474/](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7343474/)
[2] [https://www.ahajournals.org/doi/full/10.1161/CIRCULATIONAHA.118.034032](https://www.ahajournals.org/doi/full/10.1161/CIRCULATIONAHA.118.034032)
[3] [https://www.wjgnet.com/2220-6132/full/v8/i1/1.htm](https://www.wjgnet.com/2220-6132/full/v8/i1/1.htm)
[4] [https://pubmed.ncbi.nlm.nih.gov/30560921/](https://pubmed.ncbi.nlm.nih.gov/30560921/)
#patreon_articles
#disease
#LDL
#inflammation
#cardiovascular_disease

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💻 Hyperblog/Blogs/Patreon/Impossible Burger versus Beef.md Executable file
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Recently, I tried a beef analogue made by Impossible Foods. When I commented about this on social media, I was met with both support and criticism. Most of the criticisms were just a mix of appeals to nature, whole foods purism, or emotional reasoning. Nobody could provide me with an actual reason for why beef would actually be superior to Impossible Foods' product for health or disease endpoints. So, I figured I'd just compare the two myself.
The number one objection seemed to center around the quality of ingredients used in the production of the Impossible burger. People tended to take issue with the number of processed ingredients included in the product. Just for fun, let's take a quick look at the ingredients.
![[1-16.jpg]]
Now, I could go through this list and do an in-depth comparative analysis between each one of these ingredients and beef. But let's just stick to the most contentious ingredients: soy protein and oils. 
Dose-response analyses from nutritional epidemiology would seem to suggest that there is a danger of getting too little plant protein, and a danger of getting too much animal protein [1](https://www.bmj.com/content/370/bmj.m2412).
![[Pasted image 20221123154934.png]]
Perhaps from this we could make an argument against complete abstinence from animal protein on the basis of health outcomes (which is a separate consideration than ethics). But it is much harder to make an argument for reducing plant protein in the diet. For those of us who might want to adjust our intakes to include more plant protein and less animal protein, products like Impossible burger might actually help us achieve that.
On to the oils. Even vegans have complained about the volume of saturated fat (SFA) in the Impossible burger. Which is understandable. But the question is not whether or not Impossible burger is the pinnacle of healthy foods, but rather whether or not it is likely to be healthier than beef. 
When coconut oil is compared to beef fat, the differential effects on low density lipoprotein cholesterol (LDL-C) are null [2](https://pubmed.ncbi.nlm.nih.gov/4025191/)[3](https://pubmed.ncbi.nlm.nih.gov/30006369/). 
![[Pasted image 20221123154940.png]]
![[Pasted image 20221123154943.png]]
So in terms of saturated fat and its effects on LDL-C, it might appear that there could be no difference between Impossible burger and beef. However, Impossible burger also includes sunflower oil, which improves the ratio of polyunsaturated fat (PUFA) to saturated fat in the product compared to beef.
This same meta-analysis also suggests that the differential effects on LDL-C between sunflower oil and beef fat are null. 
![[Pasted image 20221123154955.png]]
Unfortunately, the authors of this meta-analysis are fuzzy on the details regarding the source data for the comparison of sunflower and beef fat. There is only one study that investigates that substitution, but LDL-C was not one of the endpoints reported in the paper [4](https://pubmed.ncbi.nlm.nih.gov/10799380/). So, I personally have no idea where they got that data. However, we have other ways of investigating this.
Achieving a higher ratio of polyunsaturated fat (PUFA) to SFA has a predictable effect on blood lipids [5](https://pubmed.ncbi.nlm.nih.gov/25286466/).
![[Pasted image 20221123154959.png]]
The P:S ratios for Impossible burger versus an equivalent beef product (fatty brisket in this case) are 0.43 and 0.09, respectively. Considering the higher fibre content, better P:S ratio, and the lack of dietary cholesterol, the Impossible burger is very likely to win in terms of managing LDL-C. Not to mention the lipid-lowering effect of soy protein isolate compared to red meat [6](https://pubmed.ncbi.nlm.nih.gov/17344494/).
Lastly, let's compare the nutritional value of both Impossible burger and our chosen beef-equivalent product, fatty brisket.
![[1-38.png]]
These are adjusted to be a single 240 calorie serving of both foods. That way we're ensuring an apples-to-apples comparison. The Impossible burger is higher in vitamins, minerals, and protein. Which segues nicely into the next topic; leghemoglobin.
Impossible burger is made using leghemoglobin, a plant-derived analogue to the hemoglobin that is responsible for the characteristic flavour of red meat. This means that beef and Impossible meat analogues are sources of heme iron. 
So, for those who want to shit on soy for having less bioavailable iron naturally, that concern literally does not apply to Impossible burger, as it very likely stands toe-to-toe with beef. All we need now is data showing that leghemoglobin can safely improve poor iron status in humans. So far, we only have papers investigating the mechanistic plausibility of leghemoglobin allergenicity [7](https://pubmed.ncbi.nlm.nih.gov/28921896/). The data seems to suggest that leghemoglobin poses very little risk to humans.
In conclusion, it is probable that Impossible burger would lead to better health outcomes overall if eaten to the exclusion of beef. However, it still has issues that would probably make it a suboptimal dietary staple. For example, it's probably better to consume whole soybeans, potatoes, and perhaps even coconuts as opposed to eating concentrated, processed versions of those foods in the form of an Impossible burger. But that doesn't change the fact that Impossible burger is likely superior to beef for health outcomes.
**Key points:**
- It has been suggested that the processed nature of Impossible burger makes it inferior to beef.
- Upon close inspection there are good reasons to suspect that Impossible burger would lead to better health outcomes when compared to beef.
- Eating the whole foods that are low in saturated fat and sodium is probably still optimal.
**References:**
[1] [https://www.bmj.com/content/370/bmj.m2412](https://www.bmj.com/content/370/bmj.m2412)
[2] [https://pubmed.ncbi.nlm.nih.gov/4025191/](https://pubmed.ncbi.nlm.nih.gov/4025191/)
[3] [https://pubmed.ncbi.nlm.nih.gov/30006369/](https://pubmed.ncbi.nlm.nih.gov/30006369/)
[4] [https://pubmed.ncbi.nlm.nih.gov/10799380/](https://pubmed.ncbi.nlm.nih.gov/10799380/)
[5] [https://pubmed.ncbi.nlm.nih.gov/25286466/](https://pubmed.ncbi.nlm.nih.gov/25286466/)
[6] [https://pubmed.ncbi.nlm.nih.gov/17344494/](https://pubmed.ncbi.nlm.nih.gov/17344494/)
[7] [https://pubmed.ncbi.nlm.nih.gov/28921896/](https://pubmed.ncbi.nlm.nih.gov/28921896/)
#patreon_articles
#nutrition
#vegan_talking_points
#mock_meats
#animal_foods
#meat
#soy
#nutrients

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💻 Hyperblog/Blogs/Patreon/Is Dietary Acrylamide Dangerous.md Executable file
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This article is section that was ultimately cut from my blog article, [A Comprehensive Rebuttal to Seed Oil Sophistry](https://www.the-nutrivore.com/post/a-comprehensive-rebuttal-to-seed-oil-sophistry). It was necessary to cut it out in order to save space, but it will live on as a Patreon exclusive until I'm finished writing the book. Enjoy!
Not all speculation regarding the supposed health harms of vegetable oils revolve around the passive peroxidation of linoleic acid (LA) in human tissues. There are also hypotheses specific to certain byproducts produced from certain high heat cooking methods that often involve vegetable oils. Acrylamide (ACR) is one such compound that is formed from the Maillard reaction, which is responsible for the browning of food and occurs between the temperatures of 120-140°C.
Technically, ACR is not formed from the oils themselves, but rather from sugars and amino acids during heating. It just so happens that vegetable oils serve as a common medium for cooking and can uniquely retain higher levels of acrylamide after cooking [1](https://pubmed.ncbi.nlm.nih.gov/27374529/).
![[_0PYseBzWVeP8wLMMxgdUegJ_1o0FP6-il42QgkIpGAS-2MokM_geBROUmXSJ9KzQ4pZ7cpSVpzB8wcfIuZRzjWv3WAnuIFBgTHp.png]]
However, a food merely having a higher amount of a spooky compound doesn’t necessarily make it dangerous to consume that food. While it is true that ACR has shown to be carcinogenic in rodents, it is also the case that rodents and humans digest and metabolize dietary ACR differently [2](https://pubmed.ncbi.nlm.nih.gov/16492914/)][3](https://pubmed.ncbi.nlm.nih.gov/19166901/). The rate of excretion of ACR detoxification metabolites is much higher in humans than it is in rodents, which suggests that the total area under the curve exposure to ACR and its toxic metabolites (like glycidamide) are also much lower in humans than in rodents. As such, it is likely that the carcinogenicity of ACR is also attenuated in humans.
In an exploratory analysis of the Women’s Health Initiative conducted by Sun et al. (2019), it was found that when comparing weekly intake of fried foods to zero intake, there was no statistically significant increase in cancer mortality after adjustment for a number of confounding variables, including diet quality [4](https://pubmed.ncbi.nlm.nih.gov/30674467/).
![[BSXbgLjZodsPMQ8QwwoO1igq9hVgvcvYrJ0_wokx4qek_Nf9MAen_vlHNkBOcTYjfZ__KLdCHhHlOjspZVH-fUGaecCKLpbVws0R.png]]
Personally, I’d like to see better exposure contrasts than this. But it’s some of the only prospective data we have on this specific question. Additionally, there is an analysis of another prospective cohort study showing an increased risk of gastric cancer with increasing fried food consumption from less than twice per week to greater than twice per week [5](https://pubmed.ncbi.nlm.nih.gov/29429272/).
However, referring back to the analysis of the LA Veterans trial from Dayton et al. (1969), the intervention group did not see a statistically significant increase in the risk of digestive cancers despite the fact that heated vegetable oils were liberally included in their diets [6](https://pubmed.ncbi.nlm.nih.gov/4100347/).
_“Vegetable oils were incorporated into the experimental diet in the form of filled milk,* imitation ice cream, "unsaturated" margarine, special sausage products, and filled cheeses. Vegetable oils were used liberally in cooking and baking. Meat fat was minimized by the use of specially trimmed lean cuts. Further dietetic details are given in a separate publication._
_*Filled milk is ordinary fresh milk from which butterfat has been removed and replaced by another fat, in this instance soybean or safflower oil.”_
It may be useful to just cut to the chase and investigate the relationship between cancer and dietary ACR itself. Luckily, there is a fairly recent meta-analysis by Pelucchi et al. (2015) that investigated the association between dietary ACR and eight different cancer subtypes [7](https://pubmed.ncbi.nlm.nih.gov/25403648/). The meta-analysis only found a non-significant increase in the risk of kidney cancer with increasing dietary ARC.
However, a later meta-analysis of prospective cohort studies by Jiang et al. (2020) explored this particular relationship in greater depth and discovered no increase in renal cell carcinoma risk with increasing dietary ACR [8](https://pubmed.ncbi.nlm.nih.gov/32077494/).
![[0qoul9ESAnkpaP_s_mm0LYUcTL7MgDjE30RIlvc3z2RnAbs7tVwsz4l_ODCm0JTNxd4vd5hjbZVTrvKOOTijk3pR-yUKhWb7vB3z.png]]
Additionally, Adani et al. (2020) also produced a number of dose response curves investigating the relationship between ACR and the risk of breast, endometrial, and ovarian cancer [9](https://pubmed.ncbi.nlm.nih.gov/32169997/). Not only did their analysis show no increased risk of any of the investigated cancers with increasing ACR exposure, they actually found an inverse association between ACR exposure and the risk of breast cancer.
It could also be worthwhile to explore some other disease endpoints. In a systematic review by Sayon-Orea et al. (2015), the association between heated oils and a number of disease outcomes was thoroughly investigated [10](https://pubmed.ncbi.nlm.nih.gov/26148920/). Overall, their analysis found that even when highly unsaturated oils were used, there was a consistently lower risk of disease when using PUFA-rich cooking oils as opposed to SFA-rich cooking oils.
![[CwjedKwEdHg9L6O6RYYHxE7bSVxt5bsqOxCQjZDIlOrDmifKgk-lmX6NhH9xeB32a7wSbJOlknoBngnR5n_uU-DKdRvjvm1zM7Ju.png]]
Paying attention to the annotations below the forest plot, we see from Rastogi et al. (2004) that even heated SU lowers the risk of cardiovascular disease (CVD), despite being exceedingly high in ACR [11](https://pubmed.ncbi.nlm.nih.gov/15051601/). We can also see from Kabagambe et al. (2005) that when heated palm oil (PO) is primarily replacing heated SO, we see a statistically significant increase in the risk of CVD [12](https://pubmed.ncbi.nlm.nih.gov/16251629/). This being in spite of the fact that heated SO can have up to 70% more ACR compared to PO.
We also see inconsistent findings with fried foods. These foods seem to increase the risk of type 2 diabetes mellitus (T2DM) and obesity, but not CVD. However, we might expect this to be the case, as many fried foods are hyperpalatable, and statistical adjustment for total energy intake may not be sufficient to fully capture potential confounding due to overconsumption [13](https://pubmed.ncbi.nlm.nih.gov/15251058/)[14](https://pubmed.ncbi.nlm.nih.gov/12571660/). As such, it may not be possible to explore this relationship robustly.
To better explore the relationship between ACR and CVD, it could be interesting to explore the association between fried potato products and disease risk. This is because fried potatoes have some of the highest ACR levels of common foods [15](https://pubmed.ncbi.nlm.nih.gov/33338370/). Fried potatoes are also one of the largest sources of dietary ACR in most countries [16](https://pubmed.ncbi.nlm.nih.gov/16708866/).
I was unable to find any decent data on potato chip consumption and disease outcomes, but I was able to find data on french fries [17](https://pubmed.ncbi.nlm.nih.gov/27680993/). In this study of two prospective cohorts by Larsson and Wolk (2016), it was observed that daily consumption of either french fries or fried potatoes did not increase the risk of any CVD-related endpoint when compared to weekly consumption.
Altogether, the case for dietary ACR increasing the risk of any particular disease is weak at best, and is null more often than not. There does not seem to be a robust evidential basis for the suggestion that heated vegetable oils increase the risk of cancer in particular either.
There is, however, evidence that despite the load of dietary ACR, vegetable oils continue to be consistently inversely associated with many diseases. Not to mention the fact that if the ACR content of vegetable oils was really such a danger, we would not expect to see the strong inverse associations between heated vegetable oils and disease risk.
**Key points:**
- Humans seem to detoxify acrylamide very rapidly.
- Acrylamide is not significantly associated with an increased risk of cancer.
- The benefits of vegetable oils seem to largely survive cooking/heating.
**References:**
[1] [https://pubmed.ncbi.nlm.nih.gov/27374529/](https://pubmed.ncbi.nlm.nih.gov/27374529/)
[2] [https://pubmed.ncbi.nlm.nih.gov/16492914/](https://pubmed.ncbi.nlm.nih.gov/16492914/)
[3] [https://pubmed.ncbi.nlm.nih.gov/19166901/](https://pubmed.ncbi.nlm.nih.gov/19166901/)
[4] [https://pubmed.ncbi.nlm.nih.gov/30674467/](https://pubmed.ncbi.nlm.nih.gov/30674467/)
[5] [https://pubmed.ncbi.nlm.nih.gov/29429272/](https://pubmed.ncbi.nlm.nih.gov/29429272/)
[6] [https://pubmed.ncbi.nlm.nih.gov/4100347/](https://pubmed.ncbi.nlm.nih.gov/4100347/) 
[7] [https://pubmed.ncbi.nlm.nih.gov/25403648/](https://pubmed.ncbi.nlm.nih.gov/25403648/)
[8] [https://pubmed.ncbi.nlm.nih.gov/32077494/](https://pubmed.ncbi.nlm.nih.gov/32077494/)
[9] [https://pubmed.ncbi.nlm.nih.gov/32169997/](https://pubmed.ncbi.nlm.nih.gov/32169997/)
[10] [https://pubmed.ncbi.nlm.nih.gov/26148920/](https://pubmed.ncbi.nlm.nih.gov/26148920/)
[11] [https://pubmed.ncbi.nlm.nih.gov/15051601/](https://pubmed.ncbi.nlm.nih.gov/15051601/)
[12] [https://pubmed.ncbi.nlm.nih.gov/16251629/](https://pubmed.ncbi.nlm.nih.gov/16251629/)
[13] [https://pubmed.ncbi.nlm.nih.gov/15251058/](https://pubmed.ncbi.nlm.nih.gov/15251058/)
[14] [https://pubmed.ncbi.nlm.nih.gov/12571660/](https://pubmed.ncbi.nlm.nih.gov/12571660/)
[15] [https://pubmed.ncbi.nlm.nih.gov/33338370/](https://pubmed.ncbi.nlm.nih.gov/33338370/)
[16] [https://pubmed.ncbi.nlm.nih.gov/16708866/](https://pubmed.ncbi.nlm.nih.gov/16708866/)
[17] [https://pubmed.ncbi.nlm.nih.gov/27680993/](https://pubmed.ncbi.nlm.nih.gov/27680993/)
#patreon_articles
#nutrition
#acrylamide
#vegetable_oil
#fried_foods
#disease
#type_2_diabetes
#cardiovascular_disease
#obesity

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💻 Hyperblog/Blogs/Patreon/Is Eating Red Meat as Bad as Smoking.md Executable file
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Many in the vegan world have drawn many dubious parallels between animal food consumption and cigarette smoking. However, red meat and smoking is the only comparison that I've seen that actually seems to have a spark of validity to it. Omnivores, please hear me out, haha.
It all started when I stumbled across this meta-analysis investigating the effects of low to moderate smoking on coronary heart disease (CHD) risk [1](https://pubmed.ncbi.nlm.nih.gov/29367388/). If we turn our attention to men, we see that the relative risk of CHD with smoking one cigarette per day is 1.48 (1.30 to 1.69). 
![[1-75.png]]
This is interesting, because it is often claimed by a great number of diet quacks from all corners of the internet that if a relative risk is below two, then the result is noise. However, with smoking and CHD, that goalpost isn't met until smoking rates exceed 20 cigarettes per day. That's a lot. Are we really willing to say, on the basis of these risk ratios that smoking 1-5 cigarettes per day is just noise, and doesn't increase risk? If the answer is "no", then I'd like you to consider the next piece of evidence carefully.
Moving on, let's look at this Japanese cohort study investigating the relationship between CHD and red meat in both men and women [2](https://pubmed.ncbi.nlm.nih.gov/33320898/). Let's stick to comparing men to men, so that we're actually comparing apples to apples as best we can. As we can see, the relative risk of CHD with increasing red meat intake is actually higher than it is for smoking, at 1.51 (1.11 to 2.06).
![[1-74.png]]
Now, I know what you're going to say. Perhaps red meat is merely a correlate for other unhealthy behaviours, like it is here in the West. I'm afraid not. Healthy and unhealthy behaviours were extremely well balanced between the quartiles of red meat intake. In fact, it seems that red meat consumption was, rather counter-intuitively, a correlate for many _healthy_ behaviours.
![[Pasted image 20221123155039.png]]
Among the behaviours that trended in a presumably unhealthy direction, they did not differ by much. For example, differences in fruit intake were equal to approximately 1/3 of a bite of an apple. Differences in egg consumption were equal to about a 1/6 of an egg. Vegetables differed by a few leaves of spinach. There is no persuasive evidence that the healthy user bias is confounding here.
This is also the reason why I did not select a meta-analysis on the association between red meat and CHD, even though those meta-analyses also tend to show an increase in risk [3](https://pubmed.ncbi.nlm.nih.gov/29039970/). 
![[Pasted image 20221123155050.png]]
However, many cohorts in this particular meta-analysis could still be confounded by the healthy user bias. Also, not all of the cohort studies in this meta-analysis used particularly robust adjustment models, either. In this instance, I would trust a single, well-designed, well-powered prospective cohort study over an entire meta-analysis of prospective cohort studies on the same research question. 
In conclusion, I do believe that intakes of red meat exceeding approximately 90g/day do actually robustly associate with the risk of CHD, and the effect size is not terribly dissimilar to that of smoking one cigarette per day. However, it is unclear what sort of effect the healthy user bias could be having on the relationship between CHD and smoking. Unfortunately, prospective cohort studies investigating smoking and disease outcomes rarely report (or even adjust for) many of those covariates.
**Key points:**
- The relative risk of CHD with smoking one cigarette per day is 1.48 (1.30 to 1.69).
- The relative risk of CHD with eating >90g of red meat per day is 1.51 (1.11 to 2.06).
- There is no obvious reason to weight the validity of these findings differently.
**References:**
[1] [https://pubmed.ncbi.nlm.nih.gov/29367388/](https://pubmed.ncbi.nlm.nih.gov/29367388/) 
[2] [https://pubmed.ncbi.nlm.nih.gov/33320898/](https://pubmed.ncbi.nlm.nih.gov/33320898/) 
[3] [https://pubmed.ncbi.nlm.nih.gov/29039970/](https://pubmed.ncbi.nlm.nih.gov/29039970/)
#patreon_articles
#nutrition
#meat
#red_meat
#smoking

72
💻 Hyperblog/Blogs/Patreon/Is Grass-Fed Carnivore Viable Globally.md Executable file
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There have been a handful of papers published investigating the environmental effects of holistic management (HM). The most prominent was a 2020 paper by Rowntree, et al., which suggested that within the context of a HM system, cattle farming would seem to be carbon negative [1](https://www.frontiersin.org/articles/10.3389/fsufs.2020.544984/full). However, there are some issues with this paper. Let's go through some of them now.
Firstly, the paper reads as though we're measuring the effect of cattle grazing on soil carbon sequestration (SOC) on pasture land over a twenty year period. The illustrate this in **Figure 1**:
![[Pasted image 20221123155140.png]]
However, what they don't explicitly state in the paper is that these data are cross-sectional. This needs to be inferred from reading their methodology. In actuality, each datapoint within **Figure 1** represents a completely different area of land, if not completely different farms.
The number of years represents the number of years each area of land had been grazed. We're not actually investigating temporal changes in SOC over a single area of land. Even the language within the paper gives the impression that we're investigating changes in SOC over time:
> _"Although there was very little difference in soil C stock between year 0 and year 1, we elected to include this in the model as a true year 0 site. We also experienced dry, difficult sampling conditions in year 13, enabling collection of two intact soil cores."_
In my view, this language is deceptive and can easily give the reader a false impression about the methodologies used.
Secondly, I'm fairly confident that Rowntree, et al. only used 20 years worth of pastured land in their model was because current estimates of SOC via grazing show diminishing returns beyond that point [2](https://www.sciencedirect.com/science/article/pii/S0301479714002588). Of course this also means that there is pretty shallow cap to the SOC potential of HM.
![[Pasted image 20221123155145.png]]
Thirdly, Rowntree, et al. erroneously attributed all of the SOC (equal to -4.4 kg CO₂-e kg CW⁻¹ per year) to cattle, despite the fact that the farming operations also contained poultry, pigs, sheep, goats, and even rabbits. These other animals actually required exogenous feed, meaning that the feed originated from outside of the farm itself. 
Overall, poultry actually represented the largest single proportion of production on the farms. How they think they are able to attribute the SOC purely to cattle is beyond me. This actually means the net negative SOC figure of -4.4 kg CO₂-e kg CW⁻¹ is completely invented, based on ridiculous assumptions that nobody should take seriously. In their aggregated estimates, WOP was actually carbon positive in net.
Lastly, each area of farmland started as a previously degraded area of land with virtually no vegetation. In order to transition the degraded land to grazing land, not only were the cattle fed exogenous hay for the first three years, but the first three years also involved annual grass seeding via aerial dispersion with planes. 
This is highly problematic, as there is no control. We don't know what the land would look like if it were only seeded and not converted to grazing land. It could actually be the case that the cattle on that land may be detracting from the quality and the SOC potential. We can't know, and this is yet another reason to question the assumption that the cattle on the farm were carbon negative.
Additionally, something that is often overlooked when grazing systems are argued for is the opportunity cost of pasture land. While it may be true that grazing agricultural methods are closer to being carbon-neutral than conventional animal agricultural methods, it is also true that at least half of current pasture land could be made significantly more carbon negative if reforested [3](https://www.nature.com/articles/s41893-020-00603-4).
![[Pasted image 20221123155149.png]]
In this model, we're looking at carbon sequestration along gradations of animal agriculture, from business-as-usual to completely vegan. As you can see, as we substitute forests for grazing on pasture, there is a stepwise increase in carbon sequestration potential. Not only that, but even if we attempted to scale grazing agriculture globally, it would barely even be worth it.
In a comprehensive report entitled "Grazed and Confused?", the global per-person yield of animal protein from grazing agriculture was estimated in a number of scenarios [4](https://www.oxfordmartin.ox.ac.uk/publications/grazed-and-confused/). In the first scenario, they modeled a situation wherein all available grasslands were repurposed for grazing. This model yielded around 7-18g/day per person of animal protein. In the second scenario, they modeled a situation that was similar to the first, but livestock diets could be supplemented with plant agriculture waste. This model yielded 11-32g/day of animal protein per person, globally. However, this particular estimate is not relevant to a carnivore world.
They also modeled a third scenario that assumed all pasturable land on Earth would be repurposed for grazing. This scenario is not very relevant, because it was altogether implausible that such a thing can be done. But this model yielded around 80g/day of animal protein per person.
If people require 2000 kcal/day on average, and pasture-raised beef is an average of 161 kcal per 100g, this means we would need a minimum of 3-35 Earths worth of space to feed the world on pasture-raised beef. In the context of HM, the numbers must be multiplied by 1.5 in order to account for the additional space required over the continuous grazing methods assumed in the calculation. This gets us to 4.5-52.5 Earths.  
![[Pasted image 20221123155200.png]]
Even if we were not to go carnivore, the highest estimate from within the plausible scenarios would still leave us about 42% short of meeting current global animal protein intakes of 55g/day. This would require about 1.72 Earths worth of space, which is not a tenable solution to animal food security, or food scarcity in general. There are a few solutions, though.
The first option would be to savagely curtail the population size through anti-natalist legislation, but I don't think anyone would consider that to be terribly ethical. The second option would be to try to increase the amount of pasturable land off-world. This could be achieved by either terraforming Mars or constructing either orbital or stellar megastructures, such as O'Neill cylinders or a Dyson sphere. None of these options are practical, though.
However, plant-exclusive or near-plant-exclusive agricultural systems has the capacity to reduce our agricultural footprint down to a range that cope with long-term population growth [5](https://online.ucpress.edu/elementa/article/doi/10.12952/journal.elementa.000116/112904/Carrying-capacity-of-U-S-agricultural-land-Ten). 
![[1-86.png]]
In conclusion, it does not appear as though grazing agricultural systems such as HM can adequately provide us with viable solutions for global food security that would also insulate us from the typical environmental pitfalls of animal agriculture. Grazing agricultural systems consume an enormous amount of land, and likely do not scale to a point where we could avoid plant agriculture altogether. As global food energy demands cannot currently be met with a carnivore-based agricultural system.
**Key points:**
- Grazing animal agricultural systems do not scale such that global food energy demands could be met on a carnivore diet.
- The current literature supporting regenerative animal agricultural methods such as holistic management are riddled with errors and dishonesty.
- Extensive reforestation of current pasture land is likely the best long-term strategy for global carbon sequestration.
**References:**
[1] [https://www.frontiersin.org/articles/10.3389/fsufs.2020.544984/full](https://www.frontiersin.org/articles/10.3389/fsufs.2020.544984/full)
[2] [https://www.sciencedirect.com/science/article/pii/S0301479714002588](https://www.sciencedirect.com/science/article/pii/S0301479714002588) 
[3] [https://www.nature.com/articles/s41893-020-00603-4](https://www.nature.com/articles/s41893-020-00603-4) 
[4] [https://www.oxfordmartin.ox.ac.uk/publications/grazed-and-confused/](https://www.oxfordmartin.ox.ac.uk/publications/grazed-and-confused/) 
[5] [https://online.ucpress.edu/elementa/article/doi/10.12952/journal.elementa.000116/112904/Carrying-capacity-of-U-S-agricultural-land-Ten](https://online.ucpress.edu/elementa/article/doi/10.12952/journal.elementa.000116/112904/Carrying-capacity-of-U-S-agricultural-land-Ten)
#patreon_articles
#environment
#beef
#carnivore

24
💻 Hyperblog/Blogs/Patreon/Ketogenic Diets and Bone Mineral Density.md Executable file
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As some of you may know, I'm in the processes of writing a meta-analysis for publication. If all goes well it should be published by late 2021. It will investigate low carbohydrate diets as they relate to a number of different biomarkers. This is one biomarker I don't expect will make it in to the publication, but it is super interesting nonetheless. So I'll share the results with you guys here.
It's relatively well accepted that the state of ketosis is characterized by a set of metabolic processes which could, in theory, lead to a reduction in bone mineral density (BMD). These metabolic processes include a slightly higher acid load in the blood as well as an upregulation of gluconeogenesis. Another possible pathway is through possible disruptions to cellular calcium efflux.
There's quite a bit of debate about whether or not ketogenic diets could actually lead to reduced bone mineral density over time. The level of debate about this is actually pretty hilarious considering we have plenty of good data on the subject. Luckily, I'm unemployed as fuck and I have plenty of time on my hands to investigate such questions in depth, haha.
I managed to find six randomized controlled trials investigating ketogenic diets as they relate to BMD. Here are the results:
![[1-3.png]]
Results were not statistically significant. Overall, there is a non-significant trend toward ketogenic diets lowering BMD (P=0.24).
I also threw in some non-ketogenic data. For clarification, Brehm 2003 includes both three month and six month data for their low carb subjects. At three months the subjects were ketogenic. They were no longer ketogenic at six months, but still eating a low carbohydrate diet. For this reason their three month data is included in the first subgroup, and their six month data is included in the non-ketogenic subgroup.
**Key points:**
- There are good reasons to suspect that ketogenic diets may reduce bone mineral density.
- When meta-analyzed, the available data seems to suggest that ketogenic diets don't seem to lower bone mineral density.
#patreon_articles
#keto
#bones
#disease
#nutrition

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💻 Hyperblog/Blogs/Patreon/Logical Fallacies on Nutrition-Twitter, Part 1.md Executable file
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Simply stated, logical fallacies are errors in reasoning or thought that are so common that they have their own names. Some can be quite obvious, while others are obnoxiously subtle. So, to help us all understand when these fallacies occur, I'm going to use the nutrition Twittersphere as a case study for many of these fallacies. So let's get into it!
**Appeal to Nature Fallacy**
This fallacy occurs when someone suggests that something is preferable merely because it is natural or occurs in nature. Here we see MacroFour imply that natural diets are preferable for maintaining calorie balance, because other animals don't need to rely on calorie-tracking to maintain their weight. Even if it were true that other animals do not require calorie-tracking to maintain their weight, that doesn't tell us anything about best practices for human beings.
![[Pasted image 20221123145556.png]]
**Appeal to Ignorance Fallacy**
This fallacy occurs when someone suggests that something is true merely because it has not yet been falsified. Here we see CoachChris suggesting that vegetable oil products are considered suspect and/or harmful until they have been investigated in all possible contexts. This essentially creates an unfalsifiable hypothesis that leaves vegetable oil products being forever damned regardless of how beneficial they are actually found to be.
![[Pasted image 20221123145608.png]]
**Appeal to Emotion Fallacy**
This fallacy occurs when someone suggests that something is true merely because they believe it to be. Here we see Barry Pearson suggest that his diet, which significantly elevates his LDL, must be good for him because he believes that LDL is actually beneficial. But of course, elevated LDL is a significant, independent risk favour for a number of vascular diseases.
![[Pasted image 20221123145614.png]]
**Appeal to Worse Problems Fallacy**
This fallacy occurs when someone dismisses the severity of a problem merely because there are worse problems that exist. Here we see Defender interrupt a conversation about adequate sources of B12 on a vegan diet with the suggestion that our discussion is made trivial in the light of the horrors of animal agriculture. Yes, animal agriculture is horrible, and it should eventually be brought to an end. But that doesn't negate the fact that implying that vegans can get adequate B12 from the soil residue on their carrots is dangerous bullshit.
![[Pasted image 20221123145620.png]]
**Argument from Incredulity Fallacy**
This fallacy occurs when someone suggests that something is either true or untrue merely because they cannot personally understand or comprehend how it could not be either true or untrue. Here we see Elie Jarrouge, MD, suggest elevated LDL on a low carb diet can't possibly be bad if it occurs in the context of commensurate improvements in everything else.
![[Pasted image 20221123145624.png]]
**Motte and Bailey Fallacy**
This fallacy occurs when someone suggests something fallacious, but substitutes a less controversial version of their position once their fallacious thinking has been exposed. Here we see CoachChris make the claim that margarine is toxic. When pressed on the issue, he eventually flips his position and makes the claim that he's merely questioning the validity of the current evidence base regarding margarine and human health. The latter position is much easier to defend than the former position.
![[Pasted image 20221123145629.png]]
![[Pasted image 20221123145633.png]]
**Appeal to Tradition Fallacy**
This fallacy occurs when someone suggests that something is preferable merely because it has a long-standing history of being done. Here we see MacroFour suggest that we should eat like our grandmas, because our grandmas might not be able to recognize the foods we're currently eating.
![[Pasted image 20221123145637.png]]
**Exception Fallacy**
This fallacy occurs when someone extrapolates from an exceptional case to make generalizations across all cases. Here we see Dr. Jay Wrigley suggest that gluten increases the prevalence of certain autoimmune disorders. The implication being that since gluten is the catalyst for autoimmune flairs in those with celiac disease, gluten must also increase instances of other autoimmune disease due to its association in epidemiology. When in reality, already having an autoimmune disease is a risk factor for developing any number of other autoimmune diseases, and gluten likely plays no independent role in the development of other autoimmune diseases.
![[Pasted image 20221123145641.png]]
**Sunk Cost Fallacy**
This fallacy occurs when someone persists with a behaviour merely because they are invested in it, even if that behaviour continues to produce negative outcomes for them. Here we see Bret Scher, MD, suggest that increasing LDL is of little concern so long as a number of other things are also improving. He's suggesting that we commit to a particular behaviour, even if that behaviour produces negative outcomes. It is likely that he should be working toward also lowering LDL in his patients when it is indicated. 
![[Pasted image 20221123145652.png]]
**Appeal to Authority Fallacy**
This fallacy occurs when someone suggests that something is true merely because an authority deems it true. Here we see MacroFour defend a position on the basis of Tim Noakes' credentials, rather than the veracity of the empirical claims being made.
![[Pasted image 20221123145656.png]]
**No True Scotsman Fallacy**
This fallacy occurs when someone changes the criteria required for credibility. Here we see David Diamond suggest that a particular study can't be counted as a credible investigation into low carbohydrate diets because not only were the carbohydrate intakes were not low enough, the blood ketone levels were not high enough. However, the subjects in the paper were actually ketogenic to a statistically significant degree due to consuming less than 50g/day of carbohydrate. 
![[Pasted image 20221123145700.png]]
**Non-Sequitur Fallacy**
This fallacy occurs when someone suggests that something is true based on completely unrelated evidence. Here we see Dr. David Unwin suggest that type 2 diabetes is caused by postprandial blood glucose excursions. It is true that high glycemic index foods typically cause higher blood glucose excursions. However, whether or not these blood glucose excursions are the cause of type 2 diabetes is a completely separate claim that needs completely different supporting evidence.
![[Pasted image 20221123145706.png]]
#patreon_articles
#twitter
#logic
#fallacies
#nutrition

45
💻 Hyperblog/Blogs/Patreon/Marker or Mediator (Part 1), High Density Lipoproteins.md Executable file
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On the back of my recent [article](https://www.patreon.com/posts/does-keto-heart-47567091) detailing the power of the triglyceride (TG) to high density lipoprotein cholesterol (HDL) ratio with regards to predicting cardiovascular disease (CVD) risk, I figured I'd take this opportunity to start a new series. In this new series, I will be discussing a number of different biomarkers and their relationship to associated disease states. 
Sometimes biomarkers are just disease correlates, and contribute nothing to disease risk in and of themselves. Other times, these biomarkers directly contribute causally to the development of a particular disease state. First up we have HDL. Is HDL a marker or a mediator? Let's find out.
The association between elevated HDL and lower CVD rates dates all the way back to the Framingham Heart Study [1](https://pubmed.ncbi.nlm.nih.gov/3196218/). It was observed that HDL seemed to have particular predictive power with regards to coronary heart disease (CHD). Having low HDL seemed to dramatically increase the risk of CVD and CHD. However, the association was much stronger with CHD.
![[Pasted image 20221123155244.png]]
At this point, some will astutely point out that correlation does not equal causation. There have since been a number of investigations into HDL's role in the prevention of CVD, using much more sensitive methodology. This typically comes in the form of Mendelian randomization (MR) studies. 
MR is a type of epidemiology that investigates the relationship between genes and health outcomes. MR studies are typically more robust than prospective cohort studies, but less robust than randomized controlled trials. 
The idea is based on an assumption that genes are randomly distributed in the population, and not everyone has all of the gene variants you may be interested in. So, not only do you get likely get a cleanly randomized group to observe, you also get a control group to which you can compare. This is a very elegant form of epidemiology.
In the case of HDL, we're observing people with genes that specifically modulate HDL up or down, and seeing how that affects the risk of CVD. This gives us the ability to make stronger causal inferences, because these HDL markers are genetically mediated and less vulnerable to residual confounding after adjustments are made.
When we investigate the relationships between HDL and CVD through the lens of MR, we see that the association completely dissolves [2](https://pubmed.ncbi.nlm.nih.gov/32203549/)[3](https://pubmed.ncbi.nlm.nih.gov/32113648/).
![[Pasted image 20221123155250.png]]
![[Pasted image 20221123155253.png]]
In blue we see the association between HDL and CVD in epidemiology, and in red we see the association as it is divulged using MR. As we can see, despite the powerfully protective effect HDL initially appeared to have using traditional methods of epidemiological investigation, the results of the MR studies would seem to contradict it. The results would seem to indicate that risk is actually following apolipoprotein B more than anything, as I discussed in the last article.
In conclusion, HDL in and of itself likely has very little independent causal role in the development of, or protection against, CVD.
**Key points:**
- Higher HDL has been associated with lower risk of CVD in observational literature.
- However, more robust Mendelian randomization studies divulge no causal, protective link between HDL and CVD.
**References:**
[1] [https://pubmed.ncbi.nlm.nih.gov/3196218/](https://pubmed.ncbi.nlm.nih.gov/3196218/)
[2] [https://pubmed.ncbi.nlm.nih.gov/32203549/](https://pubmed.ncbi.nlm.nih.gov/32203549/)
[3] [https://pubmed.ncbi.nlm.nih.gov/32113648/](https://pubmed.ncbi.nlm.nih.gov/32113648/)
#patreon_articles
#disease
#HDL
#cardiovascular_disease
#LDL
#ApoB

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💻 Hyperblog/Blogs/Patreon/Marker or Mediator (Part 2), Trimethylamine N-oxide.md Executable file
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There is a sizable community of vegans out there comprised of those who believe that the gut-derived metabolite trimethylamine N-oxide (TMAO) uniquely predisposes people to cardiovascular disease (CVD). It's understandable why they might be attracted to an idea such as this, as it is typically animal products like eggs that tend to increase markers of TMAO status [1](https://pubmed.ncbi.nlm.nih.gov/24944063/).
![[1-67.png]]
On its own this shouldn't mean very much to us. But meta-analyses have showed pretty robust associations with elevated TMAO status and both inflammation and CVD [2](https://pubmed.ncbi.nlm.nih.gov/32462890/)[3](https://pubmed.ncbi.nlm.nih.gov/31918665/). In the case of inflammation, it has been observed that TMAO and C-reactive protein tend to move in tandem and associate together strongly.
![[1-65.png]]
As for CVD, the association is similarly tight. In this meta-analysis assessing the relationship between TMAO and CVD, the higher your TMAO status, the higher the rates of CVD.
![[1-66.png]]
For a long time, these data contended to reconcile a lot of associations between certain dietary patterns and CVD outcomes. When markers like low density lipoproteins could not explain associations between different animal foods and CVD, it was often TMAO that came to the rescue to reconcile the data. That is until a method of investigation known as mendelian randomization (MR) was used to investigate the relationship [4](https://pubmed.ncbi.nlm.nih.gov/31167879/).
MR is a type of epidemiological investigation that aims to investigate the relationship between genetically mediated characteristics and outcomes. Generally speaking, these methods are stronger than prospective cohort studies, but weaker than randomized controlled trials. In the case of LDL, MR has proven itself to be highly valuable [5](https://pubmed.ncbi.nlm.nih.gov/30694319/).
When the relationship between higher levels of genetically mediated TMAO status and CVD is investigated through the lens of MR, it tells us a different story.
![[Pasted image 20221123145942.png]]
As we can see, elevated TMAO status does not robustly associate with any of the measured CVD outcomes, which included atrial fibrillation, coronary artery disease, myocardial infarction, and stroke. These results suggest that TMAO is not a mediator of risk, but its tight association with CVD outcomes might make it a good marker of CVD risk.
However, if you were still so inclined to try to reduce TMAO as much as possible, there are some practical solutions (and no you don't need to go vegan, lol). According to a recent crossover study, TMAO concentrations are a function of whether or not your diet has sufficient whole plant foods [6](https://pubmed.ncbi.nlm.nih.gov/32780794/).
![[Pasted image 20221123145949.png]]
When subjects started off eating high-plant diets, they did not experience an increase in TMAO when switching to a high-animal diet. However, TMAO increased dramatically when subjects were started on the high-animal diet, and the effect was abolished with a high-plant diet.
In conclusion, TMAO is a reasonably good predictor of CVD outcomes. Possibly due to it being elevated as a consequence of diets very high in animal foods and very low in plant foods. However, TMAO itself does not seem to mediate CVD risk.
**Key points:**
- It has been claimed that TMAO increases the risk of cardiovascular disease.
- TMAO is very strongly associated with cardiovascular disease.
- TMAO loses all predictive power when investigated using more robust methods.
- TMAO is a cardiovascular disease marker, not a cardiovascular disease mediator.
**References:**
[1] [https://pubmed.ncbi.nlm.nih.gov/24944063/](https://pubmed.ncbi.nlm.nih.gov/24944063/)
[2] [https://pubmed.ncbi.nlm.nih.gov/32462890/](https://pubmed.ncbi.nlm.nih.gov/32462890/) 
[3] [https://pubmed.ncbi.nlm.nih.gov/31918665/](https://pubmed.ncbi.nlm.nih.gov/31918665/) 
[4] [https://pubmed.ncbi.nlm.nih.gov/31167879/](https://pubmed.ncbi.nlm.nih.gov/31167879/)
[5] [https://pubmed.ncbi.nlm.nih.gov/30694319/](https://pubmed.ncbi.nlm.nih.gov/30694319/)
[6] [https://pubmed.ncbi.nlm.nih.gov/32780794/](https://pubmed.ncbi.nlm.nih.gov/32780794/)
#patreon_articles
#tmao
#cardiovascular_disease
#nutrition
#animal_foods
#choline
#vegan_talking_points

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💻 Hyperblog/Blogs/Patreon/Mechanistic Circle-jerking (Part 1), Polyphenols and LDL.md Executable file
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I don't spend a lot of time speculating about mechanisms and how they might relate to human health or disease outcomes, but I felt compelled to write this one. A while ago I compiled a [meta-analysis](https://www.patreon.com/posts/olive-oil-and-39379256) investigating the relationship between olive oil consumption and cardiovascular disease (CVD) in prospective cohort studies. The analysis showed a 24% reduction in CVD risk and a 31% reduction in stroke risk with increasing olive oil consumption.
Recently I was asked whether or not canola oil would be better than extra virgin olive oil (EVOO) for CVD-related outcomes in humans. It's actually difficult to say. Canola oil is higher in polyunsaturated fat (PUFA), which has the reliable effect of reducing CVD risk in humans. But EVOO seems to do the same, despite the fact that it has a pretty neutral effect on low density lipoproteins (LDL) in humans. LDL is by far the best risk predictor we have for CVD beyond age. So, if olive oil doesn't reliably lower LDL, but it lowers CVD, how might it do this?
Firstly, according to [Phenol Explorer](http://phenol-explorer.eu/), EVOO is much, much higher in polyphenols than canola oil.
**EVOO:**
![[1-41.png]]
**Canola oil:**
![[Pasted image 20221123155814.png]]
In a previous [article](https://www.patreon.com/posts/why-does-ldl-33915357) that I wrote almost a year ago, I explain the mechanism by which LDL causes CVD. They bind to structures called proteoglycans in the subendothelial space. Once bound, the LDL oxidize and are taken up by immune cells. Eventually, the immune cells get overwhelmed, die, and the result is an atherosclerotic lesion.
Polyphenols appear to have many effects on LDL in particular. These effects could help explain the cardio-protective effects of EVOO despite the fact that EVOO does not reduce the total concentration of LDL. I suspect that EVOO exerts its effects on reducing CVD risk by modifying LDL _behaviour_, rather than LDL concentration.
In a human experiment investigating the effects of polyphenols from pomegranate juice on LDL behaviour, up to 60% of the subjects saw reductions in the binding of LDL to proteoglycans during ex-vivo testing [1](https://pubmed.ncbi.nlm.nih.gov/10799367/). The aggregated effect was null, but researchers noticed that the cohort could be divided into responders and non-responders. Meaning that some people got a reliable benefit of the pomegranate juice polyphenols, while others did not. Perhaps this could relate to people coming into the study with different baseline levels of polyphenols already. Who knows.
![[1-40.png]]
It has also been demonstrated that certain polyphenols can bind to the apolipoprotein-B moiety of the LDL particle itself, and thus favourably alter the LDL's behaviour [2](https://www.sciencedirect.com/science/article/abs/pii/S0003986120305981?via%3Dihub). Among the polyphenols studied, some originate from olive oil and can protect LDL from oxidation. So, it could be the case that polyphenols from olive oil could not only attenuate proteoglycan-binding by LDL, they may also protect the LDL from oxidation. 
This is potentially beneficial for two reasons. Firstly, if fewer LDL bind to proteoglycans, there is a reduced chance that those LDL will oxidize and thus contribute to foam cell formation and plaque buildup. Secondly, if an LDL particle does become bound to a proteoglycan, increasing the lag-time to oxidation increases the chances that the LDL particle could dissociate from the proteoglycan and return to circulation.
**Key points:**
- Olive oil is associated with reductions in heart disease despite the fact that it does not seem to have a reliable effect on atherogenic lipoprotein concentration.
- The polyphenols in foods like olive oil could modify lipoprotein behaviour, rather than concentration, such that the lipoproteins themselves become _less_ atherogenic.
**References:**
[1] [https://pubmed.ncbi.nlm.nih.gov/10799367/](https://pubmed.ncbi.nlm.nih.gov/10799367/)
[2] [https://www.sciencedirect.com/science/article/abs/pii/S0003986120305981?via%3Dihub](https://www.sciencedirect.com/science/article/abs/pii/S0003986120305981?via%3Dihub)
#patreon_articles
#nutrition
#LDL
#olive_oil
#polyphenols
#oxLDL

32
💻 Hyperblog/Blogs/Patreon/Mechanistic Overhyping (Part 1), Dairy and Diabetes.md Executable file
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I've slowly become a fan of more plant-focused diets since I escaped the clutches of low carb lunacy. The data is hard to argue with— the more plants you have in your diet, the better your health outcomes are likely to be. However, there are some pretty loud voices in the plant-based/vegan community that love to promulgate utter nonsense.
First up we have Evan Allen, a prominent plant-based physician who apparently has a bone to pick with saturated fat (SFA). Regardless of the evidence quality, he seems more than willing to toss out anything that can make any SFA look bad. Here's a recent gem from him:
![[1-12.jpg]]
He basically links to some [mechanistic research](https://bmcgenomics.biomedcentral.com/articles/10.1186/s12864-020-07003-0) about palmitate's interactions with β-cells. He then extrapolates to human outcomes and cobbles together an anti-dairy narrative, suggesting that dairy fat causes type II diabetes (T2DM). Listen, there are many legitimate reasons to be against the consumption of dairy. Palmitate-induced lipotoxicity in pancreatic β-cells is not one of them.
Luckily, we don't even need mechanisms to investigate how dairy affects human health. If we refer to the epidemiology, we see that going from the lowest to highest intakes of dairy products actually reduces the risk of T2DM [1](https://pubmed.ncbi.nlm.nih.gov/23945722/). 
![[Pasted image 20221123150148.png]]
Overall, dairy consumption yields about a 7% reduction in T2DM risk. Maximal reductions in risk appear to be obtained within the first 100g/day. It's not a huge effect, but it's real. The effect certainly doesn't show that higher and higher intakes of dairy show greater and greater increases in risk. The opposite it seen.
This is why we can't extrapolate from mechanisms to human outcomes. In the vast majority of cases the mechanisms do not pan out, and human outcome data directly contradicts those mechanistic hypotheses.
**Key points:**
- It is claimed that palmitate is "toxic" to pancreatic β-cells due to some mechanistic interactions between the two.
- This is used as the basis for the claim that dairy products cause type II diabetes.
- However, aggregated human outcome data and dose-response curves support an inverse association between dairy consumption and type II diabetes.
**References:**
[1] Dagfinn Aune, et al. Dairy products and the risk of type 2 diabetes: a systematic review and dose-response meta-analysis of cohort studies. Am J Clin Nutr. 2013 Oct.  [https://pubmed.ncbi.nlm.nih.gov/23945722/](https://pubmed.ncbi.nlm.nih.gov/23945722/)
#patreon_articles
#dairy
#type_2_diabetes
#clownery
#nutrition
#disease

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💻 Hyperblog/Blogs/Patreon/Mechanistic Overhyping (Part 2). Protein and Cancer.md Executable file
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Next on the chopping block is a YouTuber named Gojiman. He appears to be a poop-obsessed nutrition science PhD candidate who thinks his credentials imbue him with absolute authority on any topic related to nutrition. Suffice it to say, he's bit of a wanker and a major pseudoscience peddler.
In a video he published to YouTube last year, he describes how he will never consume a high protein diet because of how higher protein diets stimulate a hormone called insulin-like growth factor 1 (IGF-1). He believes the consumption of protein will increase IGF-1 levels in the body to dangerous levels and lead to cancer. Seems straight forward. But is it true?
Well, first off let's look at the human outcome data on dietary protein and the general risk of cancer [1](https://www.bmj.com/content/370/bmj.m2412). As we can see from the dose response graphs below, no source of protein was correlated with cancer risk to a statistically significant degree. 
![[Pasted image 20221123150240.png]]
Lower intakes of both total protein and plant protein were both associated with an increased risk for all-cause and cardiovascular disease mortality. Modest intakes of animal protein were inversely associated with all-cause and cardiovascular disease mortality, and positively associated at higher levels. However, it is plausible this could be confounded by higher saturated fat intakes with increasing animal protein intakes.
There is no clear association between total, animal, or plant proteins and the risk of cancer. In fact, higher intakes of plant protein trend toward a reduction in risk. If the goalpost is protein, why aren't all protein sources correlated? Why don't any of them reach statistical significance? A legitimate criticism would be that these are reflecting mortality rather than total incidence. Fair. But I've yet to see any meta-analyses which include dose-response curves for dietary protein and cancer incidence, rather than mortality.
But, on to the basis for his claim. The evidence he uses to support his claim is a mendelian randomization study that showed that higher, genetically mediated levels of IGF-1 associated with an increased risk of colorectal cancer. It's odd that he uses this to extrapolate effects out to all cancers. But let's just use colorectal cancer as the goalpost. A meta-analysis was conducted to ascertain the effects of total protein intake on the risk of colorectal cancer in particular [2](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5591555/).
![[Pasted image 20221123150247.png]]
Although they could not perform a dose-response analysis, they did perform a bunch of subgroup analyses, including gender, protein type, study design, geography, and cancer type. No statistically significant correlations were found in any of the data.
But let's wrap this up by looking at this mendelian randomization study. The first quintile to strongly and consistently associate with risk was quintile five. The average circulating IGF-1 levels in this subgroup was 25.8nmol/L. This translates to about 197.3ng/mL. This is well above the median reference range for IGF-1 in at-risk age groups. So how applicable is this to diet? 
I managed to find a single study in the relevant age categories investigating the relationship between IFG-1 and protein intake [3](https://academic.oup.com/ajcn/article/81/5/1163/4649659). The highest levels of protein intake yielded a maximum IGF-1 level of 173ng/mL. Not quite up to our reliable risk-generating 197.3ng/mL. 
In conclusion, can we say that high protein diets cause cancer? Probably not. I'm not sure the data is there to necessarily support that. Certainly there are dietary sources of protein that associate strongly with cancer, but that's not the same as protein itself. I think it is plausible that in those who are sufficiently genetically predisposed, higher protein intakes may add to the total pool of risk for certain cancers perhaps. But I don't think the data supports a direct link between total dietary protein and total cancer.
**Key points:**
- A cocky coprophilic YouTuber named Gojiman claims that dietary protein causes cancer through increased IGF-1.
- His supporting evidence is a mendelian randomization study which shows that enormous levels of IGF-1 that seem potentially unattainable through diet alone.
- Population data does not divulge an association between total protein and total cancer.
- Perhaps if one is genetically predisposed to high IGF-1 levels, the highest levels of protein intake could add to one's total risk.
**References:**
[1] Naghshi, et al. Dietary intake of total, animal, and plant proteins and risk of all cause, cardiovascular, and cancer mortality: systematic review and dose-response meta-analysis of prospective cohort studies. BMJ 2020.  [https://www.bmj.com/content/370/bmj.m2412](https://www.bmj.com/content/370/bmj.m2412) 
[2] Renxu Lai, et al. The association between dietary protein intake and colorectal cancer risk: a meta-analysis. World J Surg Oncol. 2017. [https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5591555/](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5591555/) 
[3] Susanna C Larsson, et al. Association of diet with serum insulin-like growth factor I in middle-aged and elderly men. Am J Clin Nutr. 2005 May. [https://academic.oup.com/ajcn/article/81/5/1163/4649659](https://academic.oup.com/ajcn/article/81/5/1163/4649659)
#patreon_articles
#nutrition
#disease
#protein
#cancer

55
💻 Hyperblog/Blogs/Patreon/Mechanistic Overhyping (Part 3), Oils, Nuts, and LDL.md Executable file
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This week's harebrained mechanistic nonsense comes to from Anna Borek, the "ScepticalDoctor" on Twitter. She contends that nuts are preferable to olive oil for cardiovascular disease (CVD) prevention due to their supposed superior effects on LDL cholesterol (LDL-C).
![[Pasted image 20221123150315.png]]
So let's take a look at the study she's referencing [1](https://pubmed.ncbi.nlm.nih.gov/21421296/). As we can see, almonds certainly do reduce LDL-C relative to baseline to a statistically significant degree.
![[Pasted image 20221123150318.png]]
However, this isn't the whole story. Let's see what happens when we compare between-group differences in LDL-C lowering. Here we see olive oil compared to either almonds or walnuts. As we can see, despite the statistically significant change from baseline we saw from almonds in the previous analysis, we see there is no statistically significant between-group differences.
![[Pasted image 20221123150323.png]]
But let's say there was a statistically significant within-group and between-group difference in LDL-C changes that benefitted nuts. Does this actually mean nuts carry a higher risk of CVD? Maybe not.
Two extremely comprehensive mendelian randomization studies divulge that risk is not tracking LDL-C [2](https://pubmed.ncbi.nlm.nih.gov/32203549/)[3](https://pubmed.ncbi.nlm.nih.gov/30694319/). Risk unambiguously tracks a protein on the LDL particle called apolipoprotein B (ApoB). Luckily, this paper also reports ApoB concentrations in addition to LDL-C. Here are the within-group changes, as well as the between group changes, in ApoB.
![[Pasted image 20221123150330.png]]
![[Pasted image 20221123150333.png]]
No statistically significant differences at all. Which is actually pretty interesting. Neither olive oil nor nuts actually lower ApoB to a statistically significant degree. However, both olive oil and nut consumption both lower CVD mortality to the same degree in prospective cohort studies [4](https://pubmed.ncbi.nlm.nih.gov/27916000/)[5](https://pubmed.ncbi.nlm.nih.gov/31856379/).
![[Pasted image 20221123150338.png]]
![[Pasted image 20221123150340.png]]
So, in conclusion, consume both. They both reduce risk. Don't tolerate dry-ass salads. Dress them with olive oil if you so please. Don't tolerate bland oatmeal. Dress it with nuts. There is no persuasive reason to avoid either on the basis of CVD prevention.
**Key points:**
- It has been asserted that nuts are preferable to olive oil for CVD prevention due to a superior capacity to lower LDL-C.
- Almonds do lower LDL-C more than olive oil relative to baseline.
- Both nuts and olive oil lower CVD risk to approximately the same degree.
- CVD risk primarily tracks ApoB, not LDL-C.
- Neither nuts nor almonds raise or lower ApoB to a statistically significant degree.
**References:**
[1] N R T Damasceno, et al. Crossover study of diets enriched with virgin olive oil, walnuts or almonds. Effects on lipids and other cardiovascular risk markers. Nutr Metab Cardiovasc Dis. 2011 Jun. [https://pubmed.ncbi.nlm.nih.gov/21421296/](https://pubmed.ncbi.nlm.nih.gov/21421296/)
[2] Tom G Richardson, et al. Evaluating the relationship between circulating lipoprotein lipids and apolipoproteins with risk of coronary heart disease: A multivariable Mendelian randomisation analysis. PLoS Med. 2020 Mar 23. [https://pubmed.ncbi.nlm.nih.gov/32203549/](https://pubmed.ncbi.nlm.nih.gov/32203549/)
[3] Brian A Ference, et al. Association of Triglyceride-Lowering LPL Variants and LDL-C-Lowering LDLR Variants With Risk of Coronary Heart Disease. 2019 Jan 29. [https://pubmed.ncbi.nlm.nih.gov/30694319/](https://pubmed.ncbi.nlm.nih.gov/30694319/)
[4] Dagfinn Aune, et al. Nut consumption and risk of cardiovascular disease, total cancer, all-cause and cause-specific mortality: a systematic review and dose-response meta-analysis of prospective studies. BMC Med. 2016 Dec 5. [https://pubmed.ncbi.nlm.nih.gov/27916000/](https://pubmed.ncbi.nlm.nih.gov/27916000/)
[5] V P Campos. Effects of a healthy diet enriched or not with pecan nuts or extra-virgin olive oil on the lipid profile of patients with stable coronary artery disease: a randomised clinical trial. J Hum Nutr Diet. 2020 Jun. [https://pubmed.ncbi.nlm.nih.gov/31856379/](https://pubmed.ncbi.nlm.nih.gov/31856379/)
#patreon_articles
#nutrition
#disease
#nuts
#vegetable_oil
#LDL
#cardiovascular_disease

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💻 Hyperblog/Blogs/Patreon/Mechanistic Overhyping (Part 4), John McDougall on Dairy and Health.md Executable file
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John McDougall just released [a video](https://www.youtube.com/watch?v=txfU_bdI8hU) illustrating the dangers of dairy in the diet. Personally, I think this video illustrates the dangers of not knowing what the fuck you're talking about, haha. Let's dig in.
McDougall's first empirical claim regarding the effects of dairy on health for which he provides a supporting reference starts at [17:26](https://youtu.be/txfU_bdI8hU?t=1046). Essentially he references an analysis from 20 years ago to support the claim that dairy has no benefit to bone health in humans in randomized controlled trials (RCT), particularly post-menopausal women [1](https://pubmed.ncbi.nlm.nih.gov/10966884/). He claims that nobody else has published such a review in 20 years. This is untrue. I think what he means is that nobody else has published such a review with findings he liked.
There have been many reviews in the last twenty years. The first meta-analysis investigates dairy intakes as they relate to bone growth trajectories in children in RCTs [2](https://pubmed.ncbi.nlm.nih.gov/18539555/). The findings divulge that baseline calcium is relevant at the time of the intervention. Studies wherein participants had higher baseline calcium intakes at the time of the intervention were less likely to see a benefit. We should expect this finding. Ultimately it would seem that dairy is an adequate delivery system for nutrients that support bone health, like calcium.
![[Pasted image 20221123150502.png]]
The second investigates bone mineral density specifically in post-menopausal women [3](https://pubmed.ncbi.nlm.nih.gov/32185512/). The results are quite similar. Increasing dairy products in the diet yields better bone growth trajectories, even in post-menopausal women. Pooled results are statistically significant across the board.
![[Pasted image 20221123150508.png]]
Lastly, the third meta-analysis is investigating the relationship between dairy and markers of bone health in RCTs [4](https://clinicalnutritionespen.com/article/S2212-8263(12)00055-3/abstract). The analysis is not limited to any particular subset of the population. The results showed a statistically significant increase in bone mineral content with increasing dairy consumption.
![[Pasted image 20221123150513.png]]
As an interesting aside, one of the included studies specifically investigated cow's milk compared to soy milk [5](https://pubmed.ncbi.nlm.nih.gov/22282300/). They found a statistically significant increase in both hip and femoral head bone mineral density with cow's milk.
![[Pasted image 20221123150517.png]]
Both the cow's milk and the soy milk contained 250mg of calcium. This could suggest an additional, beneficial property of milk in particular, such as additional protein.
At [19:32](https://youtu.be/txfU_bdI8hU?t=1172), McDougall goes on to isolate a single study from the review he cites [6](https://pubmed.ncbi.nlm.nih.gov/3838218/). He takes great care to let you know that the authors are "employed" by the dairy industry. Whatever that means. He claims that the results show a greater loss of bone for the dairy group, which is untrue. It is clearly shown that the P value for every diet condition is "NS" or "non-significant."
![[Pasted image 20221123150525.png]]
But we don't have to take the author's word for it. We can take the means and standard deviations provided and analyze the data ourselves.
![[Pasted image 20221123150529.png]]
There is no statistically significant differences between the groups using either assessment of bone mass. The results are not statistically relevant, nor clinically relevant. This is a pretty significant error on McDougall's part. As a researcher himself, he should know better than to misreport findings to his lay-audience the way he has here.
At [21:05](https://youtu.be/txfU_bdI8hU?t=1265) McDougall cites a very recent epidemiological study purportedly showing no association between bone health or hip fracture risk with increasing dairy consumption. However, the authors themselves offer an explanation:
> _Given that there were no significant differences in calcium supplement use across dairy intake groups, it is likely that dairy intakes across SWAN participants did not influence total calcium intake of participants sufficiently enough to impact overall femoral neck and lumbar spine BMD outcomes._
This should sound familiar. Basically what they're saying is that calcium supplementation was so widespread in their cohort, that isolating an effect of dairy would be challenging. We discussed above how baseline calcium intake matters.
But this is all beside the point. This is a single epidemiological study that presents some methodological and interpretive challenges. We have RCT data on this very question, cited above. Overall dairy consumption improves markers of bone health in post-menopausal women.
From [21:48](https://youtu.be/txfU_bdI8hU?t=1308) to [26:03](https://youtu.be/txfU_bdI8hU?t=1563), McDougall goes on a long, poorly supported rant about the acid-base balance of the diet. Essentially his position is that animal foods (particularly dairy) provide an acid load to the body that leeches calcium from our bones. Right off the bat, if this were true we would not see all of the benefits of dairy to bone mineral density and/or bone mineral content in the meta-analyses of RCTs cited above. His mechanistic speculation doesn't pan out in the real world.
Dietary acid load does not associate with poorer bone health outcomes in epidemiology, and the association does not meet the Bradford Hill criteria for causality based in epidemiological data [7](https://pubmed.ncbi.nlm.nih.gov/21529374/). No study in the analysis actually found a benefit to alkaline diets, and the total pooled results are null (P=0.5)
However, there is _some_ validity to the idea. Back in 2014, it was discovered that the negative effects on bone sometimes seen with foods that have a high dietary acid load is modulated by the presence or absence of calcium itself [8](https://pubmed.ncbi.nlm.nih.gov/23873776/). The negative effects are only seen in those consuming insufficient dietary calcium. This means that high dietary acid load foods are not necessarily detrimental to bone health in those already consuming adequate calcium.
Now we move on to the "serious" part of the conversation at [26:03](https://youtu.be/txfU_bdI8hU?t=1563). He presents a whole whack of bullet-points detailing the supposed harms of dairy. Let's take a look.
![[Pasted image 20221123150541.png]]
We can essentially lump these claims up into four disease categories; obesity, type 2 diabetes (T2DM), cancer, and cardiovascular disease (CVD).
Let's start with obesity. Observational research typically shows that high-fat dairy protects against overweight and obesity [9](https://pubmed.ncbi.nlm.nih.gov/22810464/). However, in one of the only RCTs on the subject, the opposite effect is seen [10](https://pubmed.ncbi.nlm.nih.gov/33184632/). High fat dairy seems to encourage weight gain.
Because full-fat dairy may contribute to weight gain, it is plausible that full-fat dairy may also contribute to T2DM, cancer, and CVD. However, that's just an extrapolation. Let's take a look at the current evidence. For T2DM, after adjustments for energy intake, we see low-fat dairy appears to be protective, whereas high fat dairy appears to have no association at all [11](https://pubmed.ncbi.nlm.nih.gov/23945722/).
![[Pasted image 20221123150548.png]]
For cancer, it gets complicated. Extensive analyses have been done investigating the relationship between dairy and cancer [12](https://pubmed.ncbi.nlm.nih.gov/30782711/). We have to remember that cancer isn't just a single disease. It is many diseases.
![[Pasted image 20221123150552.png]]
Ultimately dairy appears to be a mixed bag of risks and benefits, just like any other food. The cancer that shows the most obvious effect is prostate cancer. But let's also remember that, just as cancer is not a single disease, dairy is not a single food either. Dairy is many foods.
![[Pasted image 20221123150556.png]]
When we consider the effects of dairy on prostate cancer when stratified by source, a truly puzzling picture emerges. It is completely unclear what aspect of the dairy is conferring the effect. Is it the fat? No. Is it the protein? No. Is it the lactose? No. What in the world is going on here? Virtually all of the risk is being conveyed through soft cheese and milk. But wait, there's more! Milk is the primary source of the benefits for colorectal cancer! Truly, truly fascinating results. But lets say both are 100% true. Well, maybe just replace the milk and soft cheeses in your diet with fibre, and reduce your red meat intake to make up for the losses in colorectal cancer benefits. That way we can avoid the risk to prostate cancer. Who knows. Whatever the case, cancer risk does not seem to be a general effect of dairy.
Last up, we have CVD. I've already covered dairy and CVD [here](https://www.patreon.com/posts/when-saturated-42924072). So I won't rehash it now. Long story short, it's the same as the cancer results. It depends on the source of dairy and the type of CVD.
From [26:53](https://youtu.be/txfU_bdI8hU?t=1613) to [30:10](https://youtu.be/txfU_bdI8hU?t=1810), McDougall makes a series of rapid fire empirical claims that are difficult to corroborate, investigate, or verify. But the next hilarious claim occurs at [32:41](https://youtu.be/txfU_bdI8hU?t=1961), where he attempts to scare us with the fact that there is a maximum white blood cell count quality control threshold for dairy products. He deliberately refers to the white blood cells as "pus cells" in order to scaremonger. Listen, just because there are white blood cells in dairy foods doesn't actually mean they're bad for us. There's trace fecal matter on lettuce. I'm still going to eat lettuce.
McDougall spends an enormous amount of time, [33:31](https://youtu.be/txfU_bdI8hU?t=2011) to [45:15](https://youtu.be/txfU_bdI8hU?t=2715), talking about how dairy acts as a vector for the transmission of zoonotic diseases. Absolutely true. Virtually all of the infectious disease risk associated with food production are zoonotic in origin [13](https://pubmed.ncbi.nlm.nih.gov/32219187/). So, McDougall does have a point. Animal food production, distribution, and consumption, all come with an inherent risk of exposure to zoonotic pathogens. But, what's the alternative? People need adequate nutrition, which in many cases cannot be obtained without foods of animal origin. For now, it seems the juice is worth the squeeze, and the risk of foodborne illness is probably worth it on a population level.
McDougall continues with an egregious act of cherry-picking at [46:35](https://youtu.be/txfU_bdI8hU?t=2795). He cites a study conducted on constipated children [14](https://pubmed.ncbi.nlm.nih.gov/9770556/). He then claims that the study showed that removing cow's milk from the diets of constipated children cured 68% of them. This is a half-truth. The study was conducted on children who may have been specifically enrolled on the basis of an existing diagnosis or suspicion of cow's milk intolerance. The authors acknowledge this limitation, and the potential risk of bias.
![[Pasted image 20221123150607.png]]
McDougall speculates that it's actually a result of cow's milk protein. However, this has been investigated [15](https://pubmed.ncbi.nlm.nih.gov/23340316/). Altering the cow's milk protein casein has no effect on constipation in children.
At [51:02](https://youtu.be/txfU_bdI8hU?t=3062), McDougall makes the outrageous assertion that the cow's milk protein predisposes populations to type 1 diabetes. The only evidence for this claim that I could find was a single narrative review paper specifically investigating A1 β-casein [16](https://pubmed.ncbi.nlm.nih.gov/28504710/). Probably the most persuasive evidence they present is a regression model exploring the relationship between A1 β-casein exposure by country and type 1 diabetes.
![[Pasted image 20221123150613.png]]
What I find interesting here is that this seems to be tracking more than just country of origin. It seems to be tracking ethnicity, too. It could be that countries with populations more likely to get type 1 diabetes are also more likely to consume dairy. It would be impossible to know without doing similar regressions within each population itself.
Again, from [52:09](https://youtu.be/txfU_bdI8hU?t=3129) to [57:15](https://youtu.be/txfU_bdI8hU?t=3435), McDougall treats us to a long, passionate rant about the devastating effects of dairy without providing a single citation. Instead, the bottom righthand corner of his slides are marked with "search at: [pubmed.gov](https://www.pubmed.gov/)." Well, Dr. McDougall, that which is asserted without evidence can be dismissed without evidence.
The last claim I'll touch on occurs at [1:00:51](https://youtu.be/txfU_bdI8hU?t=3651). He claims that the "Canadian Dietary Guidelines 2019" encourage cessation of dairy foods. This is not true. Firstly, there's no such thing as the Canadian Dietary Guidelines. Canada has "Canada's Food Guide." Secondly, yogurt can clearly be seen on the plate used to showcase Canada's Food Guide. 
Additionally, McDougall claims that Canada's Food Guide encourages us to ditch milk in favour of water. This is also not true. In fact, they specifically list white milk as a healthy alternative to water [here](https://food-guide.canada.ca/en/healthy-eating-recommendations/make-water-your-drink-of-choice/).
![[Pasted image 20221123150649.png]]
Canada's Food Guide also includes recipes. Many of which include dairy foods such as cheese, which can be seen [here](https://www.canada.ca/en/health-canada/services/canada-food-guide/tips-healthy-eating/meal-planning-cooking-healthy-choices/recipes.html). They also include many dairy foods as healthy sources of protein, which can be seen [here](https://food-guide.canada.ca/en/healthy-eating-recommendations/make-it-a-habit-to-eat-vegetables-fruit-whole-grains-and-protein-foods/eat-protein-foods/).
In conclusion, Dr. John McDougall is a dubious source of nutrition information, haha.
**Key points:**
- Dairy improves bone health in humans, including postmenopausal women.
- High fat dairy products may encourage weight gain.
- Many dairy foods are protect against type 2 diabetes and cardiovascular disease.
- Certain dairy foods provide a combination of risks and benefits for different cancers.
- Dairy is a vector for zoonotic foodborne pathogens.
- There is no clear evidence that dairy generally increases the risk of constipation in children.
- Canada's Food Guide does not encourage the cessation of dairy food consumption.
**References:**
[1] [https://pubmed.ncbi.nlm.nih.gov/10966884/](https://pubmed.ncbi.nlm.nih.gov/10966884/)
[2] [https://pubmed.ncbi.nlm.nih.gov/18539555/](https://pubmed.ncbi.nlm.nih.gov/18539555/) 
[3] [https://pubmed.ncbi.nlm.nih.gov/32185512/](https://pubmed.ncbi.nlm.nih.gov/32185512/) 
[4] [https://clinicalnutritionespen.com/article/S2212-8263(12)00055-3/abstract](https://clinicalnutritionespen.com/article/S2212-8263(12)00055-3/abstract)
[5] [https://pubmed.ncbi.nlm.nih.gov/22282300/](https://pubmed.ncbi.nlm.nih.gov/22282300/) 
[6] [https://pubmed.ncbi.nlm.nih.gov/3838218/](https://pubmed.ncbi.nlm.nih.gov/3838218/)
[7] [https://pubmed.ncbi.nlm.nih.gov/21529374/](https://pubmed.ncbi.nlm.nih.gov/21529374/) 
[8] [https://pubmed.ncbi.nlm.nih.gov/23873776/](https://pubmed.ncbi.nlm.nih.gov/23873776/) 
[9] [https://pubmed.ncbi.nlm.nih.gov/22810464/](https://pubmed.ncbi.nlm.nih.gov/22810464/) 
[10] [https://pubmed.ncbi.nlm.nih.gov/33184632/](https://pubmed.ncbi.nlm.nih.gov/33184632/) 
[11] [https://pubmed.ncbi.nlm.nih.gov/23945722/](https://pubmed.ncbi.nlm.nih.gov/23945722/) 
[12] [https://pubmed.ncbi.nlm.nih.gov/30782711/](https://pubmed.ncbi.nlm.nih.gov/30782711/) 
[13] [https://pubmed.ncbi.nlm.nih.gov/32219187/](https://pubmed.ncbi.nlm.nih.gov/32219187/) 
[14] [https://pubmed.ncbi.nlm.nih.gov/9770556/](https://pubmed.ncbi.nlm.nih.gov/9770556/) 
[15] [https://pubmed.ncbi.nlm.nih.gov/23340316/](https://pubmed.ncbi.nlm.nih.gov/23340316/) 
[16] [https://pubmed.ncbi.nlm.nih.gov/28504710/](https://pubmed.ncbi.nlm.nih.gov/28504710/)
#patreon_articles
#dairy
#bones
#disease
#clownery

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💻 Hyperblog/Blogs/Patreon/Nutrients of Lesser Concern.md Executable file
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If you spend much time in the nutrition corner of social media, you may have noticed that there is an enormous amount of talk about nutrient deficiencies. It seems as though everyone is running deficient in something— vitamin D, calcium, zinc, etc. In some cases it may be true, sure. It may also be a decent recommendation to monitor your status of certain problem nutrients. But, did you know there are nutrients you probably never have to worry about?
I made a couple of interesting discoveries relating to nutrient deficiencies while attempting to research nutrient depletion-repletion studies. As it turns out, just as there are nutrient deficiencies that are relatively common, there are also nutrient deficiencies that almost never happen. There are certain nutrients that are very, very rarely associated with deficiencies.
Those nutrients are:
- Vitamin B5
- Choline
- Manganese
- Phosphorus
Deficiencies of vitamin B5, manganese, and phosphorus have only ever been produced in metabolic wards. Meaning that we've only observed clinical deficiencies of these nutrients when we've locked people up and only feed them diets devoid of those nutrients.
Deficiencies in choline are somewhat different. We first discovered that choline was required in the diet when patients receiving intravenous nutrition were fed choline-free formulas. That should say something about how common choline deficiencies are likely to be. We had to feed bed-ridden people choline-free diets intravenously to even discover that this nutrient was essential to get in the diet. 
It's been shown that 10% of the population require approximately double the AI of choline if they are deficient in riboflavin. But that's highly conditional and not a general effect. All in all it doesn't seem like choline deficiencies typically present themselves spontaneously in the population. Likely choline isn't much to worry about either. As I discuss [here](https://www.patreon.com/posts/elusive-choline-33684646), choline requirements depend on a large number of other nutritional factors and are incredibly difficult to characterize.
**Key points:**
- Deficiencies in vitamin B5, manganese, and phosphorus almost never happen in free-living humans.
- Deficiencies in choline are difficult to characterize because choline requirements largely depend on overall diet quality.
#patreon_articles
#nutrition
#disease
#nutrients
#vitamin_b5
#choline
#manganese
#phosphorus

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💻 Hyperblog/Blogs/Patreon/Nutritional Epidemiology Checklist.md Executable file
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Evaluating nutritional epidemiology can be a right pain in the ass, and tons of studies get chucked around to support all sorts of claims. Here I have compiled a quick and dirty checklist for evaluating nutritional epidemiology, specifically prospective cohort studies. I've divided the checklist into two categories: "mandatory" and "cherry on top". The "mandatory" checklist contains study characteristics that **must** be assessed. The "cherry on top" list contains study characteristics that would be nice to assess, but aren't required. Enjoy!
**MANDATORY:**
**☐ Is there a meta-analysis of the research question?**
If you can find a meta-analysis on the same research question which includes either cohort studies or randomized controlled trials, you might not even need to look at this particular cohort study, as it would likely just be superseded by the findings of the meta-analysis.
**☐ What does the background population look like?**
Each population will have its distinct characteristics that could influence the results and could make comparisons with other cohort studies in other populations challenging.
- **☐ Is the age range appropriate for the endpoint?**
Be sure that the mean/median age of the population being investigated is appropriate for the endpoint of interest. For example, heart attacks generally occur between the ages of 55-75, but if the median age of the population in your cohort is 45, you're not going to be likely to see a statistically significant association with the exposure.
- **☐ Are the incidence rates sufficiently high?**
You may need to investigate other bodies of evidence to get a handle of what sorts of incidence rates are to be expected given a certain population and participant number. Once you have a handle on that, you can evaluate whether there is doubt as to whether the incidence rates would be sufficiently high to see a statistically significant result.
- **☐ Is the exposure contrast sufficiently wide?**
Here we're just referring to the contrast between low and high intakes. For example, 10g versus 30g of chicken or 5g versus 200g of red meat. You may need to investigate other bodies of evidence to get a handle of what sorts of exposure contrasts typically present statistically significant associations with risk. Once you have a handle on that, you can evaluate whether there is doubt as to whether the exposure contrast would be sufficiently high to see a statistically significant result.
- **☐ Is there something circumstantial about this cohort study?**
Some studies are idiosyncratic and use bizarre, unorthodox methodology. In order to get a handle on how to assess this, you'll have to run many, many cohort studies through this checklist.
- **☐ Do other cohort studies tend to find contradictory results?**
Maybe this cohort study is an oddball. If it appears to be done either worse or no better than many others that find contradictory results, then the results shouldn't really move our needle much. If this cohort is special in that the methods are quite superior to other cohort studies on similar research questions, then this cohort study should be given more weight.
**☐ Are there a sufficient number of participants?**
You may need to investigate other bodies of evidence to get a handle of what sorts of participant numbers are desirable, given the follow-up time and incidence rates. Once you have a handle on that, you can evaluate whether there is doubt as to whether the participant numbers would be sufficiently high to see a statistically significant result.
**☐ Is there sufficient follow-up time?**
Follow-up time goes hand-in-hand with other variables, such as population age. For example, stroke generally occur between the ages of 70-90. Let's say the median age of the population in your cohort study is 55, and there is 15 years of follow-up. It's not clear that there is sufficient follow-up time to reliably detect statistically significant associations with risk.
**☐ How is the exposure being analyzed?**
The farther the authors' analysis gets from using continuous variables, the poorer the resolution of the analysis. It's typical to see variables represented as quintiles or quartiles in cohort studies.
- **☐ continuous (best, but somewhat uncommon)**
Analyzing continuous variables is generally superior to analyzing discrete variables, like quintiles.
- **☐ discrete variables (standard/sub-optimal)**
Analyzing quintiles of variables is generally superior to analyzing tertiles of variables. The lower the number of quantiles, the lower the resolution.
- **☐ dichotomized (poor)**
Almost anything will usually be better than analyzing dichotomized variables. However, some variables are truly dichotomous and cannot be represented any other way. For example, hyperlipidemia at baseline as either true or false, and is thus a definitionally dichotomous variable.
**☐ What was the measurement method for the exposure?**
There are only a few different ways to measure nutritional exposures that are considered robust. Pay close attention to which measurement method was used, because it can often be the Achille's heel of the input data itself.
- **☐ validated biomarkers (best exposure measurement)**
As long as the biomarker has been validated, meaning that it can be used as a good proxy for nutritional intake, then biomarker data is the cat's ass of intake measurement methods. Biomarker data should be favoured in all cases. 
- **☐ validated food frequency questionnaires (best self-report method)**
Validated FFQs are also excellent, but secondary to biomarkers. But they're gold standard and still provide very good intake estimates in most cases.
- **☐ 28-day food diaries (sub-optimal)**
If less robust methods are used, such as 28-day food diaries, try to ascertain how many repeat measurements were taken during the follow-up time. The lower the number, the lower our credence should be in the data.
- **☐ 24-hour records/recalls (poor)**
Measurement methods like this are bottom of the barrier, and their utility as an intake measurement method questionable if chronic, longer latency period diseases are being investigated. Sometimes the measurement method is as simple as a phone call and a short conversation about what the participant ate within the last 24 hours, lol.
**☐ What was the measurement for the endpoint?**
The endpoint measurement method will depend on whether the endpoint is soft (change in a risk factor) or hard (disease event or death). These methods won't change a whole lot, but sometimes some researchers will throw you a curveball.
- **☐ medicals records**
Standard methodology for assessing both hard and soft endpoints.
- **☐ death records**
Standard methodology for assessing hard endpoints.
- **☐ biomarkers (assays, etc.)**
Standard methodology for assessing soft endpoints.
- **☐ some other fuckery**
Here is where the curveballs will be thrown. Sometimes the endpoints are very questionably measured, such as deaths being confirmed via a phone call to the next-of-kin. Recently, there was also a cohort(ish) study published out of Harvard on the carnivore diet, wherein the participants self-reported all of their endpoint data. Methods like this should lower our credence in the results.
**☐ Is the adjustment model comprehensive?**
The adjustment model is at the heart of the application of the author's causal model. The variables that the authors posit as being potentially confounding or covarying will be included in the model as a means of achieving what's called conditional exchangeability. Without getting it's the potential for over-adjustment, a general heuristic is that the more comprehensive the model, the better. But with caveats.
- **☐ Are there plausible confounders and covariates missing?**
You may need to investigate other bodies of evidence to ascertain whether or not the adjustment model is indeed comprehensive. If there are any variables not included for which a sound causal inference can be made, that should lower our credence in the results, so long as such variables would be sufficient to explain the effect size observed.
- **☐ Did the authors adjust for mediators or moderators?**
Mediators are variables that lie within the causal pathway between an exposure and an endpoint. Moderators are variables that influence the causal pathway between an exposure and an endpoint. Adjusting for mediators and moderators typically has the effect of rendering associations non-significant. This should be avoided, unless the authors are specifically trying to test for mediator or moderator effects.
**☐ Are the research questions and assumptions transparent?**
This should be self-explanatory. It's sub-optimal if authors are not transparent about what their even attempting to investigate, and how.
- **☐ Well-defined endpoints**
The endpoints should be clear. For example, the endpoint of cardiovascular disease should be defined in terms of the endpoints that comprise it, such as stroke, hypertension, ischemia, etc. Ideally these endpoints are identified using ICD identifier codes.
- **☐ Well-defined exposures**
Just as endpoints should be clear, so should be the exposures. For example, a cohort study could be investigating red meat, but if no attempt is made to qualify what that means, interpretation can be challenging. Red meat could include processed meat, or even pork in some cases. Without clear definitions, it's uncertain what specific exposure the association could actually tracking.
**☐ Was there a dose-response analysis performed?**
This isn't mandatory, but it really does help when trying to ascertain the shape of the risk curve.
- **☐ Did the analysis show a dose-response?**
If there was a dose-response, keep the shape of the risk curve in mind. Ascertain whether or not it is consistent with other results from other bodies of evidence. If this is the first dose-response analysis you've seen on this research question, use these results as the standard against which future research will be compared.
**☐ Did the authors perform any sensitivity analyses?**
If there is evidence of significant imprecision in the results, typically characterized by unusually wide confidence intervals, the authors may attempt a sensitivity analysis. Basically the authors will test the influence of different variables, such as stratifying the results by sex, age, or region.
**☐ Did the authors preregister?**
If yes, read the preregistration to see if their stated methods match the methods used in the paper. If they don't, suspect fuckery. If they do, great. If there is no preregistration, it should lower your credence in the results slightly. If there is both no preregistration and an unusual finding, that should moderately lower your credence in the results.
**CHERRY ON TOP:**
**☐ Did the authors provide a transparent causal model?**
Something as simple as a directed acyclic graph is extremely helpful in understanding the authors' causal model. It's not necessarily, but it makes it clear if there is anything obvious missing, or if there are relationships that you were unaware of before. The relationships aren't always obvious by just reading the adjustment model.
**☐ Is the raw data and analysis code available for public access?**
Very rarely does this happen, but it is nice when the authors are transparent about these things.
**☐ Did the authors avoid affirming the null?**
This is a bit tongue-in-cheek, but if the authors say things like "no association" or "X does not cause Y", that should raise some red flags in your mind about the authors.
**☐ Is there a plausible biological mechanism?**
This is certainly not required for causal inference, but it is nice to have some sort of biologically plausible mechanism with some supporting data behind it.
**☐ Was their a power analysis?**
Rarely clearly seen in nutritional epidemiology of any sort, but if available it could shed some light on non-significant results.
**☐ Did the authors correct for multiple comparisons?**
The more endpoints you measure, the higher the need for a multiple comparisons correction method. If the authors measure an unusually high number of endpoints but do not disclose such a correct, your credence in the results should probably be slightly lower. It's not a make-or-break proposition, though.
#patreon_articles
#epidemiology
#cohort_studies

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💻 Hyperblog/Blogs/Patreon/Nutritional Ketosis and Muscle Hypertrophy.md Executable file
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A commonly misunderstood concept in the low carb world is the balance between muscle anabolism and muscle catabolism. The ketogenic diet (KD) has the capacity to perturb this balance negatively, though it is not guaranteed. This is because different macronutrients affect both lean body mass (LBM) and fat mass (FM) differently when considered in isolation. Let me explain.
- **Protein** is both anabolic and sparing to LBM, but catabolic to FM.
- **Carbs** are sparing of LBM and FM, but anabolic to neither.
- **Fat** is catabolic to LBM, but anabolic to FM.
When we enter into nutritional ketosis, we deplete liver glycogen and must synthesize glucose by breaking down protein and liberating amino acids (AA). This can be protein in the diet or protein on our body. Eventually we can use other substrates like glycerol and aldehydes to synthesize glucose, but the contribution of AAs to gluconeogenesis (GNG) will always be substantial. This is why we sometimes hear low carb advocates claim that carbs are "non-essential". This is because when we don't eat them, we synthesize them.
However, we cannot rely entirely on dietary protein to satisfy our body's entire demand for glucose. For example, if our acute need for glucose exceeds our capacity to digest, absorb, and metabolize AAs from our diet to glucose, we will be pulling those amino acids from our skeletal muscle instead [1](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3636601/). 
Even if we could satisfy 100% of our glucose requirements with dietary AAs in the fed state, we still have to sleep at some point. During sleep, we're fasting by definition and relying on endogenous AAs to synthesize glucose. When protein and calories are matched between a KD and a non-ketogenic diet (nKD), a nKD will typically be more sparing of LBM [2](https://www.ncbi.nlm.nih.gov/pubmed/30335720)[3](https://www.ncbi.nlm.nih.gov/pubmed/22283635). 
All this being said, it is certainly possible to gain muscle on a KD, despite the catabolic stimulus being very strong. It is likely that we merely need to provide adequate protein and a sufficiently robust anabolic stimulus, like resistance training [4](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6724590/). It is likely that protein needs are going to be higher on a KD in order to achieve the same balance between anabolism and catabolism that can be achieved on a nKD. A KD will always cost us anabolic potential even if it does result in net _increases_ in LBM. Meaning that even if we made gains, we probably could have made more gains, or we could have made the same gains with less effort, on a nKD. 
Ultimately, either we're spending dietary AAs on glucose instead of spending them to build muscle, or we're breaking down already built muscle by liberating AAs to spend on glucose. Glucose isn't free. Either way we lose anabolic potential.
**Key points:**
- Muscle hypertrophy occurs when anabolism outweighs catabolism. 
- We have an obligate need to catabolize lean tissue while in ketosis.
- Ketogenic diets unavoidably cost us anabolic potential by default.
- Amino acids used to make glucose cannot be used to build muscle.
- Typical gains are still achievable in ketosis, but require extra protein.
**References:** 
[1] Claire Fromentin, et al. Dietary Proteins Contribute Little to Glucose Production, Even Under Optimal Gluconeogenic Conditions in Healthy Humans. Diabetes. May 2013.  [https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3636601/](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3636601/)
[2] Greene, DA, et al. A Low-Carbohydrate Ketogenic Diet Reduces Body Mass Without Compromising Performance in Powerlifting and Olympic Weightlifting Athletes. J Strength Cond Res. December 2018. [https://www.ncbi.nlm.nih.gov/pubmed/30335720](https://www.ncbi.nlm.nih.gov/pubmed/30335720)
[3] Wood, RJ, et al. Preservation of fat-free mass after two distinct weight loss diets with and without progressive resistance exercise. Metab Syndr Relat Disord. June 2012. [https://www.ncbi.nlm.nih.gov/pubmed/22283635](https://www.ncbi.nlm.nih.gov/pubmed/22283635)
[4] Antonio Paoli, et al. Ketogenic Diet and Skeletal Muscle Hypertrophy: A Frenemy Relationship? J Hum Kinet. August 2019. [https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6724590/](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6724590/)
#patreon_articles
#nutrition
#disease
#keto
#hypertrophy
#exercise
#protein

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💻 Hyperblog/Blogs/Patreon/Olive Oil and Cardiovascular Disease (An Independent Analysis).md Executable file
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Co-authored by [Alan Watson](https://twitter.com/Alan_Watson_).
There is a flavour of vegan whole-foods purists who claim that any added fat in the form of oils increases the risk of cardiovascular disease (CVD). Despite massive evidence to the contrary, you often hear this rabble chanting "no oil— even olive oil!" as a mantra. But is this true?
Well, I decided to do a meta-analysis on olive oil consumption in order to see if this enthusiasm for dry-ass salads was justified. I combed the literature for any prospective cohort studies or prospective randomized trials investigating rates of CVD as a function of olive oil intake. It was slim pickings, but I managed to find a handful of studies. So, let's get into it.
**Inclusion Criteria:**
- Prospective cohort studies or prospective randomized trials investigating the relationship between olive oil and CVD.
- Endpoints (events, mortality, incidences, etc) directly related to CVD, coronary heart disease, ischemic heart disease, or myocardial infarction are all acceptable.
- Risk estimates stratified from lowest to highest olive oil intakes.
**Exclusion Criteria:**
- Studies pooling results across multiple cohorts from different countries.
- Studies that report irrelevant endpoints (e.g. stroke, cerebrovascular disease, atrial fibrillation, etc.)
- Studies investigating the same cohorts as other included studies. Tie-breakers are decided based on differences in study quality (e.g., chosen subgroups, endpoints, multivariate adjustment models, etc).
A total of 11 studies were collected from the scientific literature via PubMed search. Four studies were excluded due to reporting irrelevant endpoints (stroke and conception difficulty). One study was removed due to a having a duplicate cohort.
**Results:**
Altogether there were six studies that met all of the inclusion criteria. Overall, the highest levels olive oil intake per day associated with a reduced risk of CVD (RR 0.76 [0.61-0.96], P=0.02). These findings support the hypothesis that higher intakes, as opposed to lower intakes, of olive oil associate with a decreased risk of CVD. This lends support to the recommendations of typical Western dietary guidelines to consume olive oil as a means of lowering one's risk of CVD.  
![[Pasted image 20221123150840.png]]
Another analysis was performed which included stroke.
![[Pasted image 20221123150843.png]]
Overall the results are consistent with the previous results. The highest levels of olive oil intake associate with a reduced risk of total CVD, including stroke (RR 0.77 [0.67-0.90], P=0.0008).
A final subgroup analysis was conducted and limited to just stroke and cerebrovascular disease events.
![[Pasted image 20221123150848.png]]
When only considering stroke and cerebrovascular disease events, higher intakes of olive oil associated with potent reduction in risk (RR 0.69 [0.54-0.88], P=0.003).
In conclusion, these results favour regular consumption of olive oil to reduce the risk of CVD. There also appears to be an additional benefit for reducing the risk of stroke.
#patreon_articles
#nutrition
#disease
#olive_oil
#cardiovascular_disease

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💻 Hyperblog/Blogs/Patreon/Overthinking Protein Distribution for Muscle Gains.md Executable file
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I've received a few private messages over the last year from people asking me if protein distribution matters for muscle protein synthesis (MPS) or muscle hypertrophy. The answer is, yes and no. But mostly no. Let's discuss.
In the fitness world we hear all sorts of stories about how we need to meticulously plan and space these crazy high-protein per meals throughout the day in order to magically unlock our MPS and gAiNz. While protein distribution _does_ have an effect on relative MPS, protein distribution is in no way limiting for MPS or muscle hypertrophy in absolute terms.
Probably the best study that we have on this topic investigated the effects of protein distribution on MPS by dividing people into three groups [1](https://pubmed.ncbi.nlm.nih.gov/23459753/). One group received two meals containing 40g of protein spaced six hours apart. Another group received four meals containing 20g of protein spaced three hours apart. The last group received eight meals containing 10g of protein spaced ninety minutes apart. 
![[Pasted image 20221123151015.png]]
Overall, the group receiving 20g of protein every three hours had the biggest increase in MPS. However, if you look carefully, all three diet conditions actually achieved a statistically significant increase in MPS. They all increased MPS, it's just that the protocol that fed 20g of protein per meal every three hours showed an optimal response. 
![[Pasted image 20221123151022.png]]
These findings are further supported by other research investigating protein distribution and MPS. One of the only other studies on this subject compared "even" protein intakes throughout the day to "skewed" protein intakes throughout the day [2](https://pubmed.ncbi.nlm.nih.gov/24477298/). In the EVEN group, subjects consumed three meals containing 30g of protein spaced evenly apart. In the SKEW group, subjects consumed 10g of protein for breakfast, 15g for lunch, and 65g for dinner.
![[Pasted image 20221123151028.png]]
However, measuring 24-hr MPS is not the same as measuring actual muscle hypertrophy over time. Luckily, we have data on this as well. In a study wherein protein distributions were skewed heavily toward later in the day (similar to the previous study we just discussed), both the evenly distributed group (HBR) and the skewed group (LBR) saw an increase in muscle mass overall [3](https://pubmed.ncbi.nlm.nih.gov/32321161/). Predictably, the group with evenly distributed protein did better.
![[Pasted image 20221123151033.png]]
The bottom line is that protein distribution is not limiting for absolute changes MPS or muscle hypertrophy. Whether you prefer to eat one or two high-protein meals in a day or lots of low-protein snack-like meals while you're resistance training, that's fine. You likely won't gain muscle mass as fast as you would if you optimized the protein distribution, but you will still gain. Period. Do whatever suits you, as long as you hit your total protein targets (discussed [here](https://www.patreon.com/posts/protein-targets-44006622)).
**Key points:**
- Protein distribution is not limiting for muscle protein synthesis or muscle hypertrophy.
- Consuming three meals, each containing ~0.5g/kg body weight of protein, is optimal.
- Hitting your total daily protein target is most important for muscle mass gains.
- How you distribute your protein is less important for muscle mass gains.
**References:**
[1] [https://pubmed.ncbi.nlm.nih.gov/23459753/](https://pubmed.ncbi.nlm.nih.gov/23459753/)
[2] [https://pubmed.ncbi.nlm.nih.gov/24477298/](https://pubmed.ncbi.nlm.nih.gov/24477298/)
[3] [https://pubmed.ncbi.nlm.nih.gov/32321161/](https://pubmed.ncbi.nlm.nih.gov/32321161/)
#patreon_articles
#protein
#exercise
#hypertrophy
#nutrition

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💻 Hyperblog/Blogs/Patreon/Overthinking Protein Timing for Muscle Gains.md Executable file
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So, I had this awesome plan of gathering a bunch of studies investigating the effect of pre- and/or post-workout protein consumption on muscle hypertrophy during resistance training. I was going to scour the literature for studies that controlled for protein so I could fire up RevMan and write this cool, unique blog article about the anabolic window. But, after a hilarious [public shaming](https://twitter.com/kevinnbass/status/1400884888224428032?s=20) on Twitter, I discovered that the exact analysis I was planning on doing has already been done, but better than I could have done.
Basically the idea behind the so-called "anabolic window" is that shortly after resistance training, the affected muscle tissue is primed to rebuild itself, and providing protein during this period of time maximizes muscle protein synthesis (MPS). This is said to produce either more mass, more strength, or both. However, many studies that investigate this question are asymmetrically dosing protein between groups, with one group consuming a bolus of extra protein within the anabolic window.
Clearly this is problematic, because it confounds the effect. If there is an increase in MPS observed, is it due to the fact that one group is getting more protein overall? Or is it due to the fact that one group is consuming that protein within the anabolic window? Or is it some combination of the two? Thankfully, the [muscle Gods](https://twitter.com/mackinprof/status/1400880367704346626?s=20) have ascended me to a new plane of existence by granting me a link to this meta-analysis on protein timing and hypertrophy [1](https://pubmed.ncbi.nlm.nih.gov/24299050/).
Their literature search did not uncover very many studies that had actually controlled for protein intake between groups. Only about four papers out of a couple dozen actually met that criteria. But, here is the overall, unadjusted effect of protein consumption within the anabolic window.
![[1-63.png]]
The analysis would suggest that there is a statistically significant effect of eating protein within the anabolic window on measures of hypertrophy. Which would seem to make sense. But keep in mind that the vast majority of these studies are not controlling for protein. 
Limiting the analysis to the four studies that did control for protein could potentially produce issues with regards to statistical power. The resistance training literature is usually so wishy-washy that a great many studies may be required to observe some effects.
A secondary analysis was done that attempted to adjust for total protein between groups. This way we could estimate what the effect might be, had the included studies actually controlled for protein in the first place. It certainly isn't going to be perfect, but I think it is likely sufficient to inform us as to the potential effect of protein timing on hypertrophy.
![[1-64.png]]
When adjusting for total protein between groups, the effect of the "anabolic window" seems to be nullified. Which isn't surprising to me, really. I had concluded in my [previous article](https://www.patreon.com/posts/overthinking-for-49333926) on protein distribution that eating your total daily protein in an unbalanced distribution (such as one or two meals per day) does not nullify the effect of total protein on hypertrophy. While eating in a balanced distribution would appear to be optimal, you'll gain lean mass no matter how you distribute your daily protein.
The anabolic window should be viewed differently. There is a period of time ranging from about three to four hours before your workout to three to four hours after your workout wherein protein ingestion maximizes MPS [2](https://pubmed.ncbi.nlm.nih.gov/23360586/). However, eating outside of this window is not limiting for hypertrophy, as long as your total daily protein requirement is met.
In conclusion, it appears once again that simply hitting your total daily protein target is of greater importance than micromanaging your protein intake in some contrived way. Unless you're an elite athlete or striving to eek out the most gains possible, muscle hypertrophy is not that complicated— lift heavy things until your muscles feel fatigued and eat sufficient protein. If you'd like to know more about what sufficient protein could mean for you, I have also [written about this](https://www.patreon.com/posts/protein-targets-44006622) subject previously.
**Key points:**
- It has been suggested that protein ingestion needs to be target around the time of your workout in order to make gains.
- In reality, merely hitting your total recommended target for protein in a day is far more important.
- As long as you are hitting your protein target and providing a sufficient anabolic stimulus through resistance training, you will make gains.
**References:**
[1] [https://pubmed.ncbi.nlm.nih.gov/24299050/](https://pubmed.ncbi.nlm.nih.gov/24299050/) 
[2] [https://pubmed.ncbi.nlm.nih.gov/23360586/](https://pubmed.ncbi.nlm.nih.gov/23360586/)
#patreon_articles
#nutrition
#exercise
#protein
#hypertrophy

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💻 Hyperblog/Blogs/Patreon/Sugar-Sweetened Beverages and Metabolic Syndrome.md Executable file
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The idea that sugar-sweetened beverages (SSBs) uniquely cause metabolic syndrome (MetS) is an idea that seems to circulate around low carbohydrate diet camps, and was primarily spearheaded by researchers like Robert Lustig and David Ludwig. However, how robust are the data?
If we look at associations between SSBs and MetS, we see a fairly linear increase in risk that is pretty striking [1](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7348689/). Even more striking is the lack of association between MetS and other liquid sources of sugar, like with fruit juices.
![[1-48.png]]
However, I've criticized epidemiological findings relating specific foods to outcomes of this nature, particularly type 2 diabetes (T2D). Despite the best efforts on the part of the researchers, sometimes the data are not robust enough to allow for an adequate adjustment for certain confounders. 
In this case, adjustments for energy intake simply aren't able to fully capture the effect of calories on MetS and T2D risk, which I have previously discussed [here](https://www.patreon.com/posts/dietary-fructose-31876052). An adjustment for energy intake should reduce the association between a food and MetS or T2D to null. I'll explain why.
We have randomized controlled trials feeding different types of SSBs and measuring MetS-related outcomes in both eucaloric and ad libitum conditions [2](https://pubmed.ncbi.nlm.nih.gov/27023594/)[[3]](https://pubmed.ncbi.nlm.nih.gov/32696704/). Essentially, under eucaloric (weight maintaining) conditions, SSBs do not really adversely affect measures of MetS. However, when people are given SSBs and allowed to consume them ad libitum (at their own leisure), people tend to overconsume them (because they're fucking delicious and poorly satiating). When SSB consumption results in a calorie surplus, risk factors of MetS tend to worsen.
Rigorously controlled human experiments divulge that increases in body fat as a consequences of SSB overconsumption are perfectly predicted by calories [4](https://pubmed.ncbi.nlm.nih.gov/3165600/). In this experiment, fruit juices were used to achieve a profound calorie surplus in humans. The degree of fat accumulation was perfectly predicted by total calories. So, we can say with confidence that SSBs aren't affecting adiposity independent of calories.
![[1-47.png]]
In fact, one group of researchers used varying levels of high fructose corn syrup (HFCS) or sucrose in an isocaloric, hypocaloric (weight loss) diet [5](https://pubmed.ncbi.nlm.nih.gov/22866961/). There were five different diet conditions— 10% HFCS, 20% HFCS, 10% sucrose, 20% sucrose, and a eucaloric control with added exercise. They discovered no statistically significant between-group differences in weight loss, and weight loss was also predicted by calorie intake.
In conclusion, do SSBs "cause" MetS? To the extent that SSBs contribute to excessive caloric intake, I would say yes. That is to say, of those who currently have MetS, the ones who would **not** have developed MetS had it _not_ been for the SSBs in their diet, we can say that the SSBs were causal in the development of their MetS. However, SSBs are likely not unique here. Any food would increase the risk of MetS if it was overconsumed to a sufficient degree.
**Key points:**
- SSB consumption associates with MetS even after adjustments for energy intake.
- In human experiments using SSBs, changes in MetS risk factors are a function of weight changes and calorie intake.
- Epidemiology often fails to adequately capture the effect of calories on certain disease outcomes.
- SSBs cause MetS to the extent that SSBs contribute to excessive caloric intake.
**References:** 
[1] [https://pubmed.ncbi.nlm.nih.gov/32644139/](https://pubmed.ncbi.nlm.nih.gov/32644139/)
[2] [https://pubmed.ncbi.nlm.nih.gov/27023594/](https://pubmed.ncbi.nlm.nih.gov/27023594/)
[3] [https://pubmed.ncbi.nlm.nih.gov/32696704/](https://pubmed.ncbi.nlm.nih.gov/32696704/)
[4] [https://pubmed.ncbi.nlm.nih.gov/3165600/](https://pubmed.ncbi.nlm.nih.gov/3165600/)
[5] [https://pubmed.ncbi.nlm.nih.gov/22866961/](https://pubmed.ncbi.nlm.nih.gov/22866961/)
#patreon_articles
#nutrition
#metabolic_syndrome
#type_2_diabetes
#sugar_sweetened_beverages
#sugar
#non_alcoholic_fatty_liver_disease

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💻 Hyperblog/Blogs/Patreon/The Benefits of High Fibre Diets.md Executable file
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Since I escaped the clutches of low carb zealotry, I've warmed up to a lot of conventional ideas about what constitutes a generally healthful diet. I've changed my positions on saturated fat, vegetable oils, sugar, carbohydrates, calories, etc. All of which I've discussed at length on my blogs and social media. I've also changed my views on dietary fibre, despite not really discussing it that much in the past.
As I write this, I am of the opinion that dietary fibre is critically important for long-term human health, despite it technically not being an essential nutrient. My current diet gives me about 30-50g/day of fibre on average. The DRI for fibre is 38g/day for men and 25g/day for women. But, I was curious to know if there was any evidence that perhaps higher intakes could yield additional benefits.
I stumbled across this systematic review and meta-analysis of dietary fibre intakes and cardiovascular disease (CVD) and coronary heart disease risk (CHD) [1](https://pubmed.ncbi.nlm.nih.gov/24355537/). As I read through it I was struck by these graphs, which illustrate the estimated effect of dietary fibre intake on CVD and CHD risk. 
![[1-1.jpg]]
They suggested that we have at least one study (marked as red bars) suggesting that fibre could confer a benefit to CVD and CHD risk reduction all the way up to >60g/day. I'd never heard of intakes that high being studied before.
I managed to track down the paper [2](https://pubmed.ncbi.nlm.nih.gov/23543118/). The fibre intakes were estimated using two different methods. One method yielded an estimated intake of ~63g/day, and multivariate analyses showed that intakes this high could reduce CVD risk by ~40% and CHD risk by ~30%. Huge numbers. 
In groups whose fibre intakes approximated the DRI, CVD risk was reduced by ~40% yet again, but CHD risk was only reduced by 20%. Still huge numbers, but this could suggest benefits to consuming fibre at levels that exceed the current DRI.
**Key points:**
- Meeting the DRI for fibre intake confers consistent benefits to CVD and CHD risk.
- There is evidence that suggests eating even more fibre could confer additional benefits.
**References:**
[1] Diane E Threapleton, et al. Dietary fibre intake and risk of cardiovascular disease: systematic review and meta-analysis. BMJ. 2013 Dec. [https://pubmed.ncbi.nlm.nih.gov/24355537/](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3898422/)
[2] Diane E Threapleton, et al. Dietary fibre and cardiovascular disease mortality in the UK Women's Cohort Study. Eur J Epidemiol. 2013 Apr. [https://pubmed.ncbi.nlm.nih.gov/23543118/](https://pubmed.ncbi.nlm.nih.gov/23543118/)
#patreon_articles
#nutrition
#disease
#fibre
#cardiovascular_disease

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💻 Hyperblog/Blogs/Patreon/The Elusive Choline Requirement.md Executable file
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There is no doubt that choline is an essential nutrient. Without it, lots of terrible things happen to the human body [1](https://www.ncbi.nlm.nih.gov/pubmed/19874943). But, despite knowing this, choline escapes having a recommended dietary allowance (RDA). Instead, choline has an adequate intake (AI) of 425mg/day for women and 550mg/day for men [2](https://www.ncbi.nlm.nih.gov/books/NBK114308/). An AI is set in place of an RDA when there is insufficient evidence or confidence that an RDA can be estimated. 
So what gives? Why is it so hard to quantify choline requirements in humans? It's because choline requirements can very easily fluctuate wildly on a daily basis. In a lot of ways, your choline requirement is determined by genetics, nutritional status in general, and your dietary choices. Many nutrients can be expected to lower one's choline requirement through the lowering of homocysteine: vitamin B2, vitamin B6, vitamin B9, vitamin B12, betaine, and methionine can all work to lower a person's choline requirements [3](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2714377/)[4](https://www.ncbi.nlm.nih.gov/pubmed/12190367)[5](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3610948/)[6](https://www.ncbi.nlm.nih.gov/pubmed/15916468) Additionally, certain dietary choices increase your choline requirements: fat intake, calorie intake, alcohol intake, and fructose intake can all be expected to increase your requirement for choline due to choline's role in facilitating hepatic triglyceride efflux [7](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4230213/)[8](https://www.ncbi.nlm.nih.gov/pubmed/22338037).
Since everyone's diet and genetics are different, everyone needs a different amount of choline [9](https://www.ncbi.nlm.nih.gov/pubmed/27342765). Someone who is homozygous for the T allele of the C677 MTHFR genotype is going to require an enormous amount of choline, but could perhaps lower this requirement with vitamin B2. Someone with fatty liver will likely require more choline than average. Someone abstaining from alcohol on a low-sugar, low-fat diet with lots of protein is likely to need much less dietary choline than the previous two examples.
What would a diet look like if you wanted to maximally reduce your choline requirement? Based on the nutrients that can be expected to lower the requirement, you'd want to consume plenty of low-sugar fruits and vegetables, low-fat legumes and other whole grains, starchy tubers, lean meats, liver, nutritional yeast, and very little dietary fat. 
But what about eggs? Eggs are a good source of choline, but on some level could be self-defeating since the food is high in fat. It might actually be a better strategy to just maximally reduce your choline needs and get smaller amounts of choline from lots of other sources, such as low fat seafood, certain whole grains, or even something like homemade mushroom soup.
**Key points:** 
- Choline requirements are difficult to characterize, but we know a minimum requirement exists.
- Genetics can either decrease or increase choline requirements in certain contexts.
- Dietary choices that increase B-vitamins, betaine, and protein likely decrease choline requirements.
- Dietary choices that increase the intakes of fat, calories, sugar, and alcohol likely increase choline requirements.
**References:**
[1] Buchman AL. The addition of choline to parenteral nutrition. Gastroenterology. 2009 Nov. [https://www.ncbi.nlm.nih.gov/pubmed/19874943](https://www.ncbi.nlm.nih.gov/pubmed/19874943) 
[2] The Institute of Medicine. Dietary Reference Intakes for Thiamin, Riboflavin, Niacin, Vitamin B6, Folate, Vitamin B12, Pantothenic Acid, Biotin, and Choline. National Academies Press. 1998. [https://www.ncbi.nlm.nih.gov/books/NBK114308/](https://www.ncbi.nlm.nih.gov/books/NBK114308/) 
[3] Marie A. Caudill, et al. Choline Intake, Plasma Riboflavin, and the Phosphatidylethanolamine N-Methyltransferase G5465A Genotype Predict Plasma Homocysteine in Folate-Deplete Mexican-American Men with the Methylenetetrahydrofolate Reductase 677TT Genotype. J Nutr. 2009 Apr. [https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2714377/](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2714377/) 
[4] Schnyder G, et al. Effect of homocysteine-lowering therapy with folic acid, vitamin B12, and vitamin B6 on clinical outcome after percutaneous coronary intervention: the Swiss Heart study: a randomized controlled trial. JAMA. 2002 Aug. [https://www.ncbi.nlm.nih.gov/pubmed/12190367](https://www.ncbi.nlm.nih.gov/pubmed/12190367) 
[5] Marc P. McRae. Betaine supplementation decreases plasma homocysteine in healthy adult participants: a meta-analysis. J Chiropr Med. 2013 Mar. [https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3610948/](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3610948/) 
[6] Olthof MR, et al. Effect of homocysteine-lowering nutrients on blood lipids: results from four randomised, placebo-controlled studies in healthy humans. PLoS Med. 2005 May. [https://www.ncbi.nlm.nih.gov/pubmed/15916468](https://www.ncbi.nlm.nih.gov/pubmed/15916468) 
[7] Danxia Yu, et al. Higher Dietary Choline Intake Is Associated with Lower Risk of Nonalcoholic Fatty Liver in Normal-Weight Chinese Women. J Nutr. 2014 Dec. [https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4230213/](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4230213/)
[8] Guerrerio AL, et al. Choline intake in a large cohort of patients with nonalcoholic fatty liver disease. Am J Clin Nutr. 2012 Apr. [https://www.ncbi.nlm.nih.gov/pubmed/22338037](https://www.ncbi.nlm.nih.gov/pubmed/22338037)
[9] Ganz AB, et al. Genetic impairments in folate enzymes increase dependence on dietary choline for phosphatidylcholine production at the expense of betaine synthesis. FASEB J. 2016 Oct. [https://www.ncbi.nlm.nih.gov/pubmed/27342765](https://www.ncbi.nlm.nih.gov/pubmed/27342765)
#patreon_articles
#nutrition
#disease
#choline

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💻 Hyperblog/Blogs/Patreon/The Heuristics of Weight Loss.md Executable file
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Human beings eat according to heuristics, meaning that we apply principles to our decision-making regarding food consumption. Some people eat merely to satisfy hunger, or they eat for pleasure. Some people merely avoid animal foods when they eat. Others eat anything as long as it low in saturated fat. These days, a great many people eat to lose weight, and that is the focal point for a lot of dietary controversy on the internet. Many principles are heralded as panaceas for weight loss.
Low-carb fanatics will tell us that sugar and insulin make us fat, so avoiding carbohydrates necessarily leads to weight loss. Vegans will tell us that animal products make us fat, and that avoiding animal products necessarily leads to weight loss. Ray Peat acolytes will have us believing that polyunsaturated fats make us fat. People who are really into the gut microbiome will sometimes try to convince us that diets high in saturated fat will spill endotoxin into our blood and cause us to gain weight. Wow— so many different opinions. Pretty much all of them are bullshit, and at the end of the day, calories drive weight gain or weight loss.
It is true, however, that employing any one of these strategies will usually guide one to significant weight loss. But why? Let's explore the foods that are statistically most likely to lead to weight gain. According to the Dietary Guidelines Advisory Committee, these are the foods from which Americans derive a majority of their calories:
- Grain-based desserts
- Yeast breads
- Chicken and chicken-mixed dishes
- Soda, energy drinks, and sports drinks
- Pizza
- Alcoholic beverages
- Pasta and pasta dishes
- Mexican mixed dishes
- Beef and beef-mixed dishes
- Dairy desserts
Notice anything interesting? Whether we're low-carb, vegan, paleo, or carnivore, almost everything on that list is off-limits. If we're vegan, we must avoid over half of the list. If we're low-carb, we have to avoid more than half of the list as well. If we're paleo, we have to avoid virtually everything on that list except for the meat. Virtually all roads that lead to excluding these calorie-dense foods lead to weight loss as well. I interpret this to mean that if we make a conscious effort to mostly avoid junk food, we'll probably lose weight and have better outcomes. I made a post about this [here](https://www.patreon.com/posts/do-processed-us-31529282).
There's nothing magical about any one of these approaches. They all force us to employ some sort of restraint that causes us to reduce our caloric intake unconsciously (ostensibly by limiting junk foods). What they all have in common is restricting calorie-dense junk food. We shouldn't really be against anybody employing any one of these approaches, because they all more or less work (depending on the individual). Just remember that they all work for the same reason. 
The funny thing is that once we understand how and why these principles work, we can probably include some junk food in our diet at little cost. If we know it boils down to calories we have incredible leeway with what we actually include in our diet. If one wishes to track their caloric intake, it becomes really easy to budget for junk food and maintain your weight, or even lose weight. At the time I'm writing this, I'm six weeks into a cut and I ate a Twix bar today. I'm still under my 1600 kcal cap for today, and I'm still losing weight steadily. The Twix bar contains sugar, saturated fat, animal foods, plant foods, and refined grains. But because I'm controlling calories I don't gain any weight from it, and because my diet is primarily whole foods I have a lot of low-calorie, filling foods to fall back on if I get hungry.
**Key points:**
- There are many explanations for obesity, but most of them are bullshit.
- Excess calories from hyper-palatable, Western junk food likely drives obesity.
- Limiting junk food is something almost all popular weight loss diet have in common.
- Over-eating is difficult on a diet consisting only of whole foods.
#patreon_articles
#nutrition
#disease
#weight_loss
#healthy_diets
#obesity

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💻 Hyperblog/Blogs/Patreon/The TLDR Healthy Diet.md Executable file
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Many of you guys contacted me and asked me to distill my recent [video](https://www.patreon.com/posts/vlog-4-building-53314386) on building a healthy diet down into something easier to understand. So I took the opportunity to add more foods and food categories, such as alcohol, coffee, and chocolate. 
As I suspected, the results are largely consistent with the guidelines, but there are some key differences. I also hope to build this over time as I get more foods, food groups, and endpoints to add to the list. Enjoy!
**OVERWHELMINGLY POSITIVE**
- Coffee/Tea (<580ml/day)
- Fruit (>220g/day)
- Legumes (>160g/day)
- Nuts (>20g/day)
- Unsaturated Fat (>28g/day)
- Vegetables (>200g/day)
- Whole Grains (>100g/day)
**MOSTLY POSITIVE**
- Cheese (>20g/day)
- Cocoa (<25g/day)
- Fish (>120g/day)
- Milk (~500ml/day)
- Mushrooms (>20g/day)
- Soy (>40g/day)
- Yogurt (>230g/day)
**MOSTLY NEUTRAL**
- Eggs (<4/week)
- Lean Meat (~100g/day)
- Unfried Potatoes (~60g/day)
- Refined Grains (<90g/day)
**MOSTLY NEGATIVE**
- Alcohol (<20ml/day)
- Fried Potatoes (<60g/day)
- Saturated Fat (<22g/day)
- Sodium (<2000mg/day)
**OVERWHELMINGLY NEGATIVE**
- Processed Meat (<1g/day)
- Red Meat (<20g/day)
- Sugary Drinks (<150ml/day)
**Results:**
These results are excluding the "Mostly Negative" and "Overwhelmingly Negative" groups. Interestingly it checks all of the boxes. Complete essential nutrition is achieved, including adequate fibre and low saturated fat. Shockingly, the diet also seems to provide adequate choline, 6.5g of omega-3, and over 5g of potassium! This diet is ballin' straight outta fucking control!
![[1-68.png]]
![[1-69.png]]
**References:**
[1] [https://pubmed.ncbi.nlm.nih.gov/29666853/](https://pubmed.ncbi.nlm.nih.gov/29666853/) 
[2] [https://pubmed.ncbi.nlm.nih.gov/31584249/](https://pubmed.ncbi.nlm.nih.gov/31584249/) 
[3] [https://pubmed.ncbi.nlm.nih.gov/31278047/](https://pubmed.ncbi.nlm.nih.gov/31278047/) 
[4] [https://pubmed.ncbi.nlm.nih.gov/28324761/](https://pubmed.ncbi.nlm.nih.gov/28324761/) 
[5] [https://pubmed.ncbi.nlm.nih.gov/27517544/](https://pubmed.ncbi.nlm.nih.gov/27517544/) 
[6] [https://pubmed.ncbi.nlm.nih.gov/28671591/](https://pubmed.ncbi.nlm.nih.gov/28671591/) 
[7] [https://pubmed.ncbi.nlm.nih.gov/30061161/](https://pubmed.ncbi.nlm.nih.gov/30061161/) 
[8] [https://pubmed.ncbi.nlm.nih.gov/25646334/](https://pubmed.ncbi.nlm.nih.gov/25646334/) 
[9] [https://pubmed.ncbi.nlm.nih.gov/31970674/](https://pubmed.ncbi.nlm.nih.gov/31970674/) 
[10] [https://pubmed.ncbi.nlm.nih.gov/28655835/](https://pubmed.ncbi.nlm.nih.gov/28655835/) 
[11] [https://pubmed.ncbi.nlm.nih.gov/28446499/](https://pubmed.ncbi.nlm.nih.gov/28446499/) 
[12] [https://pubmed.ncbi.nlm.nih.gov/29039970/](https://pubmed.ncbi.nlm.nih.gov/29039970/) 
[13] [https://pubmed.ncbi.nlm.nih.gov/30801613/](https://pubmed.ncbi.nlm.nih.gov/30801613/) 
[14] [https://pubmed.ncbi.nlm.nih.gov/29141965/](https://pubmed.ncbi.nlm.nih.gov/29141965/) 
[15] [https://pubmed.ncbi.nlm.nih.gov/29210053/](https://pubmed.ncbi.nlm.nih.gov/29210053/) 
[16] [https://pubmed.ncbi.nlm.nih.gov/28397016/](https://pubmed.ncbi.nlm.nih.gov/28397016/) 
[17] [https://pubmed.ncbi.nlm.nih.gov/29978377/](https://pubmed.ncbi.nlm.nih.gov/29978377/) 
[18] [https://pubmed.ncbi.nlm.nih.gov/29987352/](https://pubmed.ncbi.nlm.nih.gov/29987352/) 
[19] [https://pubmed.ncbi.nlm.nih.gov/28592612/](https://pubmed.ncbi.nlm.nih.gov/28592612/)
[20] [https://pubmed.ncbi.nlm.nih.gov/31055709/](https://pubmed.ncbi.nlm.nih.gov/31055709/) 
[21] [https://pubmed.ncbi.nlm.nih.gov/26997174/](https://pubmed.ncbi.nlm.nih.gov/26997174/) 
[22] [https://pubmed.ncbi.nlm.nih.gov/21162794/](https://pubmed.ncbi.nlm.nih.gov/21162794/) 
[23] [https://pubmed.ncbi.nlm.nih.gov/24691133/](https://pubmed.ncbi.nlm.nih.gov/24691133/) 
[24] [https://pubmed.ncbi.nlm.nih.gov/31915830/](https://pubmed.ncbi.nlm.nih.gov/31915830/) 
[25] [https://pubmed.ncbi.nlm.nih.gov/31754945/](https://pubmed.ncbi.nlm.nih.gov/31754945/)
[26] [https://pubmed.ncbi.nlm.nih.gov/34165394/](https://pubmed.ncbi.nlm.nih.gov/34165394/)
#patreon_articles
#dietary_guidelines
#whole_foods
#healthy_diets
#nutrition
#disease

39
💻 Hyperblog/Blogs/Patreon/Visualizing Nutrient Ratios.md Executable file
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There are many so-called "optimal" micronutrient ratios that have been described in the literature. However very few of them have any sort of real validation with regards to human physiology, let alone human health outcomes. Often times ratios are simply reflecting having either too much of one nutrient or not enough of another nutrient, and not actually reflecting a particular ratio that nutrients need to be maintained within.
For example, with the omega-3 to omega-6 ratio, virtually all of the negative associations with a low omega-3 to omega-6 ratio can be explained by having insufficient omega-3 intakes. Rather than higher omega-6 intakes being harmful, the skewed ratio is merely reflecting that one nutrient intake is inadequate. All the ratio does is confuse the issue, because lowering omega-6 to within an "optimal" omega-3 to omega-6 ratio doesn't address the inadequate omega-3 intake.
I'm usually not a big fan of ratios in nutrition for reasons that I explained in [this](https://thenutrivore.blogspot.com/2020/01/measuring-nutrient-density-calories-vs.html) blog article. Ratios don't give you enough information. Foods that are enormously high in both nutrients could get similar scores to foods that are dismally low in both nutrients. For example, 100/10=10, and 1/0.1=10. Both of these examples give us identical scores, but there is an order of magnitude difference between the input values.
Nevertheless, the academic debate around these ratios continues. But the least I could do to add some sanity to the debate is to help us visualize the ratios in a more productive way. So I've prepared a series of charts using a selection of common nutrient ratios. The charts are set up to actually tell us which types of foods are highest in whichever nutrient, in order to actually optimize the ratios.
**Omega-3 vs Omega-6**
![[Pasted image 20221123151445.png]]
**Vitamin E vs Polyunsaturated Fat**
![[Pasted image 20221123151451.png]]
**Polyunsaturated Fat vs Saturated Fat**
![[Pasted image 20221123151458.png]]
**Potassium vs Sodium**
![[Pasted image 20221123151503.png]]
**Calcium vs Magnesium**
![[Pasted image 20221123151508.png]]
**Calcium vs Phosphorus**
![[Pasted image 20221123151511.png]]
**Zinc vs Copper**
![[Pasted image 20221123151516.png]]
#patreon_articles
#nutrients
#nutrition

68
💻 Hyperblog/Blogs/Patreon/Vitamin A, Are Animal Foods Just Chopped Liver.md Executable file
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Is it necessary to consume animal foods to meet sufficiency of vitamin A? Some people in the nutrition space seem to think so. Proponents of so-called "ancestral diets" such as Chris Masterjohn and Chris Kresser have been squawking about this idea like a couple of demented parrots for years, but is there any merit to it?
The argument essentially goes like this:
There is genetic variation in the activity of the BCO1 enzyme, which is responsible for converting carotenoids into to active form of vitamin A, retinol. Therefore, plant foods are an unreliable source of retinol in those of us with these genetic variants, because they won't be able to convert enough.
Cool story. It definitely seems as though there could be physiological plausibility for this hypothesis. But, let's see how it plays out in meatspace. No pun intended.
Right off the bat, we can easily locate research wherein retinol status is ascertained in people with these genetic variants [1](https://pubmed.ncbi.nlm.nih.gov/19103647/). It seems as though even the people with the worst impairments maintain adequate retinol status, despite only getting an average of a measly 133mcg/day of retinol.
The only thing that appears to change is that the ratio of beta-carotene to retinol, which is increased based on the exact type of genetic variation in the conversion rate. But it doesn't appear as though much else actually changes. In fact, the entire variance in the population sample in this study had fasting plasma retinol within the reference range. The authors themselves commented that all volunteers had adequate serum vitamin A concentrations.
Additionally, a rather recent study published in 2020 found no differences in retinol status between BCO1 genotypes in a population consuming extremely low amounts of preformed retinol [14](https://pubmed.ncbi.nlm.nih.gov/32560166/). Again, virtually all study participants were within the reference range for plasma vitamin A, and plasma retinol concentrations did not vary between genotypes. In fact, vitamin A deficiency was correlated similarly with lower plasma carotenoid concentrations and plasma retinol concentrations.
So, it does not actually seem to be the case that having these genetic variants meaningfully affects retinol status. There is a more parsimonious way of reconciling these data, though. It just means the rate of conversion is probably slower. The shape of the conversion curve is likely just longer and flatter in so-called "impaired" genotypes, but it's very likely the case that and the area under that conversion curve is likely the same.
It's akin to the difference between low glycaemic carbohydrates and high glycaemic carbohydrates when matched for calories. The rates of absorption between the two yield differently shaped curves. The low glycaemic curve is long in duration and low in concentration in the postprandial window, while the high glycaemic curve is short in duration and high in concentration in the postprandial window. However, the area under both of these curves is identical.
This is likely analogous to the conversion rates between so-called "imapired" genotypes and wildtype genotypes. Those with the so-called "impaired genotypes" are simply converting for longer, but much less at a time, whereas those with the wildtype genotypes are converting for a shorter period of time, but much more at a time. But the total amount converted between the two genotypes is likely close to equivalent.
But, we can take this a step further and actually see what happens when we try to correct vitamin A deficiency using dietary carotenoids in human subjects [2](https://pubmed.ncbi.nlm.nih.gov/15883432/)[3](https://pubmed.ncbi.nlm.nih.gov/17413103/)[4](https://pubmed.ncbi.nlm.nih.gov/9808223/)[5](https://pubmed.ncbi.nlm.nih.gov/10584052/)[6](https://pubmed.ncbi.nlm.nih.gov/15321812/)[7](https://pubmed.ncbi.nlm.nih.gov/16210712/). On the whole, eating foods rich in carotenoids reliably improves and/or normalizes vitamin A status. Even foods that have been genetically engineered to have higher levels of carotenoids reliably improve vitamin A status in humans [8](https://pubmed.ncbi.nlm.nih.gov/19369372/).
As a side note, the only cases of vitamin A toxicity (hypervitaminosis A) from whole foods that I could find in the literature involved the consumption of preformed retinol from liver [9](https://pubmed.ncbi.nlm.nih.gov/25850632/)[10](https://pubmed.ncbi.nlm.nih.gov/21902932/)[11](https://pubmed.ncbi.nlm.nih.gov/10424294/)[12](https://pubmed.ncbi.nlm.nih.gov/31089689/)[13](https://pubmed.ncbi.nlm.nih.gov/3655980/). In one case, a child died from consuming chicken liver pate sandwiches. I could find no case reports of vitamin A toxicity related to carotenoids.
**Key points:**
- Genetic impairments in the conversion of carotenoids to retinol do not seem to impact retinol status or make deficiency more likely.
- Dietary carotenoids from whole plant foods can easily maintain adequate retinol status.
- The only case reports of vitamin A toxicity from whole foods are attributable to liver consumption.
**References:**
[1] W C Leung, et al. Two Common Single Nucleotide Polymorphisms in the Gene Encoding Beta-Carotene 15,15'-monoxygenase Alter Beta-Carotene Metabolism in Female Volunteers. FASEB J. 2009 Apr. [https://pubmed.ncbi.nlm.nih.gov/19103647/](https://pubmed.ncbi.nlm.nih.gov/19103647/) 
[2] Paul J van Jaarsveld, et al. Beta-carotene-rich Orange-Fleshed Sweet Potato Improves the Vitamin A Status of Primary School Children Assessed With the Modified-Relative-Dose-Response Test. Am J Clin Nutr. 2005 May. [https://pubmed.ncbi.nlm.nih.gov/15883432/](https://pubmed.ncbi.nlm.nih.gov/15883432/) 
[3] Judy D Ribaya-Mercado, et al. Carotene-rich Plant Foods Ingested With Minimal Dietary Fat Enhance the Total-Body Vitamin A Pool Size in Filipino Schoolchildren as Assessed by Stable-Isotope-Dilution Methodology. Am J Clin Nutr. 2007 Apr. [https://pubmed.ncbi.nlm.nih.gov/17413103/](https://pubmed.ncbi.nlm.nih.gov/17413103/) 
[4] S de Pee, et al. Orange Fruit Is More Effective Than Are Dark-Green, Leafy Vegetables in Increasing Serum Concentrations of Retinol and Beta-Carotene in Schoolchildren in Indonesia. Am J Clin Nutr. 1998 Nov. [https://pubmed.ncbi.nlm.nih.gov/9808223/](https://pubmed.ncbi.nlm.nih.gov/9808223/) 
[5] G Tang, et al. Green and Yellow Vegetables Can Maintain Body Stores of Vitamin A in Chinese Children. Am J Clin Nutr. 1999 Dec. [https://pubmed.ncbi.nlm.nih.gov/10584052/](https://pubmed.ncbi.nlm.nih.gov/10584052/) 
[6] Marjorie J Haskell, et al. Daily Consumption of Indian Spinach (Basella Alba) or Sweet Potatoes Has a Positive Effect on Total-Body Vitamin A Stores in Bangladeshi Men. Am J Clin Nutr. 2004 Sep. [https://pubmed.ncbi.nlm.nih.gov/15321812/](https://pubmed.ncbi.nlm.nih.gov/15321812/) 
[7] Guangwen Tang, et al. Spinach or Carrots Can Supply Significant Amounts of Vitamin A as Assessed by Feeding With Intrinsically Deuterated Vegetables. Am J Clin Nutr. 2005 Oct. [https://pubmed.ncbi.nlm.nih.gov/16210712/](https://pubmed.ncbi.nlm.nih.gov/16210712/) 
[8] Guangwen Tang, et al. Golden Rice Is an Effective Source of Vitamin A. Am J Clin Nutr. 2009 Jun. [https://pubmed.ncbi.nlm.nih.gov/19369372/](https://pubmed.ncbi.nlm.nih.gov/19369372/) 
[9] Yosuke Homma, et al. A Case Report of Acute Vitamin A Intoxication Due to Ocean Perch Liver Ingestion. J Emerg Med. 2015 Jul. [https://pubmed.ncbi.nlm.nih.gov/25850632/](https://pubmed.ncbi.nlm.nih.gov/25850632/) 
[10] E Dewailly, et al. Vitamin A Intoxication From Reef Fish Liver Consumption in Bermuda. J Food Prot. 2011 Sep. [https://pubmed.ncbi.nlm.nih.gov/21902932/](https://pubmed.ncbi.nlm.nih.gov/21902932/) 
[11] K Nagai, et al. Vitamin A Toxicity Secondary to Excessive Intake of Yellow-Green Vegetables, Liver and Laver. J Hepatol. 1999 Jul. [https://pubmed.ncbi.nlm.nih.gov/10424294/](https://pubmed.ncbi.nlm.nih.gov/10424294/) 
[12] Martha E van Stuijvenberg, et al. South African Preschool Children Habitually Consuming Sheep Liver and Exposed to Vitamin A Supplementation and Fortification Have Hypervitaminotic A Liver Stores: A Cohort Study. Am J Clin Nutr. 2019 Jul. [https://pubmed.ncbi.nlm.nih.gov/31089689/](https://pubmed.ncbi.nlm.nih.gov/31089689/) 
[13] T O Carpenter, et al. Severe Hypervitaminosis A in Siblings: Evidence of Variable Tolerance to Retinol Intake. J Pediatr. 1987 Oct. [https://pubmed.ncbi.nlm.nih.gov/3655980/](https://pubmed.ncbi.nlm.nih.gov/3655980/)
[14] Sophie Graßmann, et al. SNP rs6564851 in the BCO1 Gene Is Associated with Varying Provitamin a Plasma Concentrations but Not with Retinol Concentrations among Adolescents from Rural Ghana. Nutrients. 2020 Jun [https://pubmed.ncbi.nlm.nih.gov/32560166/](https://pubmed.ncbi.nlm.nih.gov/32560166/)
#patreon_articles
#nutrition
#disease
#vitamin_a
#nutrients
#nutrient_deficiency
#animal_foods
#clownery

51
💻 Hyperblog/Blogs/Patreon/Vitamin B6 on a Vegan Diet.md Executable file
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It has been suggested that a plant-based diet leaves one vulnerable to certain nutrient deficiencies. While I believe that this is true, I also believe that these concerns are incredibly overblown. The typical nutrients of concern are: vitamin B12, vitamin D, calcium, iron, and zinc. However, I'm not actually persuaded that any of these nutrients are uniquely concerning on a vegan diet in the general population. 
Research investigating B12 status in vegans comes up mixed, but in populations wherein supplementation is widely practiced, serum B12 does not significantly differ from that of omnivores [1](https://pubmed.ncbi.nlm.nih.gov/26502280). It is also not clear that merely being vegan makes much of a difference for vitamin D status [2](https://pubmed.ncbi.nlm.nih.gov/19339396). Maintaining adequate calcium status as a vegan is merely about consuming an adequate amount of calcium-rich foods [3](https://pubmed.ncbi.nlm.nih.gov/12491091). Lastly, I'm not convinced that iron and zinc are of general concern. It hasn't been persuasively demonstrated that animal food restriction uniquely predisposes to iron or zinc deficiency [4](https://pubmed.ncbi.nlm.nih.gov/27880062)[5](https://pubmed.ncbi.nlm.nih.gov/23595983). 
Food selection is king. When people are making improper food selections to target these nutrients, of course deficiency can occur [6](https://pubmed.ncbi.nlm.nih.gov/14988640). On a vegan diet, we don't get iron from fruit and vegetables unless we're eating a lot of black olives, haha. Soaked legumes and cooked whole grains would be better choices in that regard. 
However, there is one nutrient that I did stumble across that appears to be consistently problematic across vegan populations. Vitamin B6 deficiency seems to loom over various vegan and vegetarian populations, despite more than adequate intakes [7](https://pubmed.ncbi.nlm.nih.gov/16925884)[8](https://pubmed.ncbi.nlm.nih.gov/16988496)[9](https://pubmed.ncbi.nlm.nih.gov/1797957). There are plausible mechanisms by which vitamin B6 could be limiting on a vegan diet without supplementation, which I write about [here](https://thenutrivore.blogspot.com/2019/05/animal-nutrients-part-1-vitamin-b6.html). 
Essentially, vitamin B6 from plant foods typically comes in the form of pyridoxine glucoside, which is significantly less bioavailable than free pyridoxine or preformed pyridoxal [10](https://pubmed.ncbi.nlm.nih.gov/2843032)[11](https://pubmed.ncbi.nlm.nih.gov/9237945). Some of the only decent non-animal sources of vitamin B6 are avocados, bananas, and perhaps lentils. Not even nutritional yeast, which is usually a B-vitamin powerhouse, has a decent amount of vitamin B6.  So, it's slim pickings for adequate sources if you're avoiding animal foods. But this might not be enough. While factoring in bioavailability it would take either four average bananas per day to meet sufficiency for vitamin B6, or four California variety avocados per day. For many people there are barriers to doing either consistently.
I'm not trying to say that vitamin B6 will necessarily become a problem on a vegan diet. My perspective on this is that those following diets that severely restrict animal foods should probably find it prudent to consider adding vitamin B6 as pyridoxal-5-phosphate to their supplementation regimen as a precaution.
**Key points:**
- Vitamin B12, vitamin D, calcium, iron, and zinc aren't overly concerning on vegan diets.
- Nutritional adequacy on a vegan diet can mostly be met with proper food selection.
- Vitamin B6 deficiency is very common in both vegan and vegetarian populations. 
- Vitamin B6 from non-animal foods is not particularly bioavailable to humans.
- Supplementing with vitamin B6 as P-5-P would be prudent on vegan diets.
**References:**
[1] R Schüpbach, et al. Micronutrient Status and Intake in Omnivores, Vegetarians and Vegans in Switzerland. Eur J Nutr. 2017. Feb. [https://pubmed.ncbi.nlm.nih.gov/26502280](https://pubmed.ncbi.nlm.nih.gov/26502280/)
[2] Jacqueline Chan, et al. Serum 25-hydroxyvitamin D Status of Vegetarians, Partial Vegetarians, and Nonvegetarians: The Adventist Health Study-2. Am J Clin Nutr. 2009 May. [https://pubmed.ncbi.nlm.nih.gov/19339396](https://pubmed.ncbi.nlm.nih.gov/19339396/)
[3] Kathrin Kohlenberg-Mueller and Ladislav Raschka. Calcium Balance in Young Adults on a Vegan and Lactovegetarian Diet. J Bone Miner Metab. 2003. [https://pubmed.ncbi.nlm.nih.gov/12491091](https://pubmed.ncbi.nlm.nih.gov/12491091/)
[4] Lisa M Haider, et al. The Effect of Vegetarian Diets on Iron Status in Adults: A Systematic Review and Meta-Analysis. Crit Rev Food Sci Nutr. 2018 May. [https://pubmed.ncbi.nlm.nih.gov/27880062](https://pubmed.ncbi.nlm.nih.gov/27880062/)
[5] Meika Foster, et al. Effect of Vegetarian Diets on Zinc Status: A Systematic Review and Meta-Analysis of Studies in Humans. J Sci Food Agric. 2013 Aug. [https://pubmed.ncbi.nlm.nih.gov/23595983](https://pubmed.ncbi.nlm.nih.gov/23595983)
[6] Annika Waldmann, et al. Dietary Iron Intake and Iron Status of German Female Vegans: Results of the German Vegan Study. Ann Nutr Metab. 2004. [https://pubmed.ncbi.nlm.nih.gov/14988640](https://pubmed.ncbi.nlm.nih.gov/14988640)
[7] A Waldmann, et al. Dietary Intake of Vitamin B6 and Concentration of Vitamin B6 in Blood Samples of German Vegans. Public Health Nutr. 2006 Sep. [https://pubmed.ncbi.nlm.nih.gov/16925884](https://pubmed.ncbi.nlm.nih.gov/16925884/)
[8] D Majchrzak, et al. B-vitamin Status and Concentrations of Homocysteine in Austrian Omnivores, Vegetarians and Vegans. Ann Nutr Metab. 2006. [https://pubmed.ncbi.nlm.nih.gov/16988496](https://pubmed.ncbi.nlm.nih.gov/16988496/)
[9] N Vudhivai, et al. Vitamin B1, B2 and B6 Status of Vegetarians. J Med Assoc Thai. 1991 Oct. [https://pubmed.ncbi.nlm.nih.gov/1797957](https://pubmed.ncbi.nlm.nih.gov/1797957/)
[10] R D Reynolds, et al. Bioavailability of Vitamin B-6 From Plant Foods. Am J Clin Nutr. 1988 Sep. [https://pubmed.ncbi.nlm.nih.gov/2843032](https://pubmed.ncbi.nlm.nih.gov/2843032/)
[11] H Nakano, et al. Pyridoxine-5'-beta--glucoside Exhibits Incomplete Bioavailability as a Source of Vitamin B-6 and Partially Inhibits the Utilization of Co-Ingested Pyridoxine in Humans. J Nutr. 1997 Aug. [https://pubmed.ncbi.nlm.nih.gov/9237945](https://pubmed.ncbi.nlm.nih.gov/9237945/)
#patreon_articles
#nutrition
#disease
#nutrient_deficiency
#nutrients
#vitamin_b6
#vegan_talking_points

54
💻 Hyperblog/Blogs/Patreon/Vitamin K2, Preventative, not Curative.md Executable file
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Observational research suggests that dietary vitamin K2 intake is powerfully protective against certain forms of cardiovascular disease. Particularly diseases of arterial calcification [1](https://www.ncbi.nlm.nih.gov/pubmed/15514282)[2](https://www.ncbi.nlm.nih.gov/pubmed/27927636)[3](https://www.ncbi.nlm.nih.gov/pubmed/31103344). However, recent randomized controlled trials involving nutritional doses of vitamin K2 in the form of MK-7 discovered that vitamin K2 actually, if anything, worsens the progression of pre-existing arterial calcification [4](https://www.ncbi.nlm.nih.gov/pubmed/31387121)[5](https://www.ncbi.nlm.nih.gov/pubmed/31529295). But, how can this be? How can a nutrient that is so protective be so ineffective against the disease that it is so good at preventing? I will attempt to reconcile these two seemingly contradictory findings.
Essentially, I suspect it is precisely because vitamin K2 is also very effective at building bone and keeping bones strong. This is because vitamin K2 activates a protein, osteocalcin, secreted by special cells in our bones, called osteoblasts. These special cells use this activated protein to lay down and form new bone. 
Many lines of evidence suggest that arterial calcification is an active bone-forming process mediated by osteoblasts, or osteoblast-like cells, found near the endothelium [6](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC208734). This is supported by the fact that atherosclerotic lesions are often found to have bone-remodeling proteins inside them in and around sites of calcification [7](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3423589).
If arterial calcification is an active process, akin to bone formation, that is mediated by osteoblasts, the question becomes, why would we _not_ expect vitamin K2 to accelerate the progression of arterial calcification? Vitamin K2 is effective in the building and maintenance of bone. Once the arterial calcification is there, it is very possible that it is functionally no different than other bone structures in the body and vitamin K2 will act on it just the same.
However, I'm not convinced that this means that vitamin K2 supplementation should necessarily be contraindicated for those with higher coronary artery calcification (CAC) scores. Let me explain.
If one has a higher degree of CAC, it is very unlikely that one would be able to reliably regress it with any dietary or pharmacological intervention at all. At least not with any known strategy. No diet, nutrient, or drug has ever been shown to flat-out regress CAC in humans. However, it may be the case that depending on the extent of your CAC, your risk profile may be better served by increasing the burden of CAC, rather than reducing it.
Now, I'm not saying having CAC is necessarily a good thing, and if we had an intervention that actually did regress CAC safely and effectively, I would probably fully support that. But, currently it is much more complicated than that, and sometimes more calcification is better for your risk profile [8](https://www.ncbi.nlm.nih.gov/pubmed/29301708).
Here is a graphic from the paper:
![[Pasted image 20221123151723.png]]
As you can see, the risk of rupture (seen in red) is lowest in people with either no CAC score or the highest CAC score. For all intents and purposes, they're roughly equal. This means your chances of getting a heart attack are, on average, greatest during the initial stages of CAC development.
Vitamin K2 may be relevant here, and I still believe it is very likely preventative. However, perhaps getting a higher CAC score is bad reason to stop talking vitamin K2, as it may help to reduce window of time in which the plaque is most vulnerable.
**Key points:**
- Vitamin K2 may help to prevent arteries from calcifying.
- Vitamin K2 may accelerate the progression of preexisting CAC.
- Those with the highest and lowest CAC scores have the lowest chances of a heart attack.
- Vitamin K2 may help ensure greater plaque stability by increasing the burden of CAC.
**References:**
[1] Geleijnse JM, et al. Dietary intake of menaquinone is associated with a reduced risk of coronary heart disease: the Rotterdam Study. J Nutr. November 2004. [https://www.ncbi.nlm.nih.gov/pubmed/15514282](https://www.ncbi.nlm.nih.gov/pubmed/15514282) 
[2] Nagata C, et al. Dietary soy and natto intake and cardiovascular disease mortality in Japanese adults: the Takayama study. Am J Clin Nutr. February 2017. [https://www.ncbi.nlm.nih.gov/pubmed/27927636](https://www.ncbi.nlm.nih.gov/pubmed/27927636) 
[3] Zwakenberg SR, et al. Circulating phylloquinone, inactive Matrix Gla protein and coronary heart disease risk: A two-sample Mendelian Randomization study. Clin Nutr. May 2019. [https://www.ncbi.nlm.nih.gov/pubmed/31103344](https://www.ncbi.nlm.nih.gov/pubmed/31103344) 
[4] Zwakenberg SR, et al. The effect of menaquinone-7 supplementation on vascular calcification in patients with diabetes: a randomized, double-blind, placebo-controlled trial. Am J Clin Nutr. October 2019. [https://www.ncbi.nlm.nih.gov/pubmed/31387121](https://www.ncbi.nlm.nih.gov/pubmed/31387121) 
[5] Oikonomaki T, et al. The effect of vitamin K2 supplementation on vascular calcification in haemodialysis patients: a 1-year follow-up randomized trial. Int Urol Nephrol. November 2019. [https://www.ncbi.nlm.nih.gov/pubmed/31529295](https://www.ncbi.nlm.nih.gov/pubmed/31529295) 
[6] Terence M, et al. Doherty. Calcification in atherosclerosis: Bone biology and chronic inflammation at the arterial crossroads. Proc Natl Acad Sci U S A. September 2003. [https://www.ncbi.nlm.nih.gov/pmc/articles/PMC208734](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC208734) 
[7] Bithika Thompson and Dwight A. Towler.  Arterial calcification and bone physiology: role of the bone-vascular axis. Nat Rev Endocrinol. September 2013. [https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3423589](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3423589)
[8] Mori H, et al. Coronary Artery Calcification and its Progression: What Does it Really Mean? JACC Cardiovasc Imaging. 2018 Jan. [https://www.ncbi.nlm.nih.gov/pubmed/29301708](https://www.ncbi.nlm.nih.gov/pubmed/29301708)
#patreon_articles
#nutrition
#disease
#coronary_artery_calcification
#cardiovascular_disease
#vitamin_K2
#clownery

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💻 Hyperblog/Blogs/Patreon/Weight Loss, Low Carb or Low Fat.md Executable file
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A meta-analysis from 2017 investigated the differential effects of low carb (LC) and low fat (LF) diets on measures of energy expenditure and fat mass loss [1](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5568065/). Some time ago, David Ludwig PhD implied in a Twitter post that if the meta-analysis was stratified by duration, the longest studies would end up favouring low carb diets. He took the tweet down only moments after posting it. He likely knew that he was potentially making a bold assumption and came to his senses. 
For some reason, I anticipated him removing the tweet and I decided to save it. 
![[Pasted image 20221123151853.png]]
I then contacted Kevin Hall, the lead author of the meta-analysis in question. I asked if I could have access to the raw data so that I could stratify his included studies by duration. He was extremely polite and accommodating, and passed me his data. We had a lengthy back-and-forth about the data, and the implications of diet composition on fat mass loss. He was a pleasure to speak with.
After inputting the data and digging through each study individually for duration information, I broke Kevin Hall's meta-analysis up into four subgroups: <1 week, 1-2 weeks, 2-4 weeks, and >4 weeks. Here are the results.
**Figure 1**
LC vs. LF (Body Fat Changes)
![[Pasted image 20221123151857.png]]
**Figure 2
**LC vs. LF (Energy Expenditure Changes)
![[Pasted image 20221123151901.png]]
For body fat changes, the results start off statistically significant in favour of LF diets for study durations under four weeks.  At four weeks and greater, the results are completely null. One interesting observation is that the P-value steady increases as the trial duration increases. Meaning that LF diets have an advantage in the short term, but are likely a total wash in the long term.
For energy expenditure (EE) changes, things get complicated. Results are statistically significant in favour of LF diets for studies under one week in duration and between two to four weeks in duration. However, beyond four weeks there is a statistically significant increase in EE in favour of LC diets. The pooled results suggest that LC diets could increase EE by ~103 kcal per day. Sounds like it could be a victory for LC diets here. Or maybe not.
Let's get practical here. ~103 kcal/day is about 11.4g of fat per day. Which translates to one pound of fat ever 39 days. That's 9.3lb per year. Nothing to write home about, really. But it's an effect, for sure. However, there are some troubling issues with two papers in subgroup four of Figure 2.
Firstly, Ebbeling et al, 2012 measured EE using a method known as doubly-labeled water (DLW). This essentially involves giving subjects water that contains uncommon isotopes of both hydrogen and oxygen. You can then measure the rate at which these isotopes leave the body, though breath and urine, and calculate someone's metabolic rate. 
The only trouble is that the amount of CO2 that subjects evolve on LC diets is different than it is on LF diets. Kevin Hall himself has published on his issues in the past [2](https://www.biorxiv.org/content/10.1101/403931v1). Ebbeling et al, 2012 reported weak differences in CO2 production between LC and LF based on DLW. The massive effect on EE is only seen when they use their calculated model, wherein the RQ differences are calculated based on the food the subjects were provided. This model assumes perfect diet adherence, and could potentially overestimate the effect of the LC diet on EE.
![[Pasted image 20221123151907.png]]
Just for the sake of curiosity, let's remove Ebbeling et al, 2012 from the forest plot.
![[Pasted image 20221123151911.png]]
As we can see, 99.8% of the weight is coming from a Hall et al, 2016. There is an additional issue with this study as well. Their measurements of EE showed a steady decline toward a null effect, but the study duration wasn't sufficient to see the regression in EE through to the end. By day 20, some subjects were showing a decrease in total EE. It is also worth noting that the bulk of the effect is seen within the first 10 days of the study, and did not take four weeks to achieve.
![[Pasted image 20221123151917.png]]
But let's assume the effect is real, and turn a blind eye to the limitations I've discussed. The estimated difference in EE without Ebbeling et al, 2012 would be equal to about ~57 kcal per day in favour of LC diets. That is approximately 6.3g of fat burned per day— equal to ~5lb per year. Is this an advantage? Technically yes. Practically, probably not. But it might be something—  practically meaningless. But something nonetheless.
Overall, the two studies that contribute the most statistical weight to subgroup four in Figure 2 have methodological limitations that make it difficult to tell if the effect we're seeing would actually pan out over time. My guess is that they probably wouldn't. Personally, I'm not sure if I'm willing to give this subgroup the benefit of the doubt, given the limitations I've discussed. 
For me, the effects of macronutrient composition on fat loss and energy expenditure remain an open question. If you're persuaded by the results, feel free to trumpet a victory for LC diets. However, I think the celebrations are premature.
**Key points:**
- It has been suggested that low carb diets could independently increase energy expenditure and thus increase fat mass loss if given enough time.
- When stratified by study duration, low carb diets show no detectable advantages on fat mass loss, but a statistically significant increase in energy expenditure.
- However, these findings could be the result of methodological shortcomings within the primary studies that contribute the most statistical weight.
**References:**
[1] Kevin D. Hall and Juen Guo. Obesity Energetics: Body Weight Regulation and the Effects of Diet Composition. Gastroenterology. Feb 2017.  [https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5568065/](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5568065/) 
[2] Kevin D. Hall, et al. Potential Bias of Doubly Labeled Water for Measuring Energy Expenditure Differences Between Diets Varying in Carbohydrate. Biorxiv. Aug 2018.  [https://www.biorxiv.org/content/10.1101/403931v1](https://www.biorxiv.org/content/10.1101/403931v1)
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#nutrition
#disease
#weight_loss
#low_carb
#low_fat

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💻 Hyperblog/Blogs/Patreon/What About Dietary Cholesterol.md Executable file
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It's extremely common to hear (especially in the low-carb/ketogenic dieting sphere) that dietary cholesterol (DC) has next to no effect on serum cholesterol or lipoproteins. But is this true? Well, it may depend on who you're measuring.
Let's look at this graph.
![[Pasted image 20221123152033.png]]
As we can see, DC intakes that go from average, around 300mg/day, to 500mg/day would have a negligible effect on total cholesterol (TC) levels [1](https://www.ncbi.nlm.nih.gov/pubmed/1534437). So of course when we study the average population, we see confusing effects of DC on cardiovascular disease (CVD) endpoints [2](https://www.ncbi.nlm.nih.gov/pubmed/26109578). The effect of DC on CVD can easily be lost in the noise.
An astute paleo-dieter might point out that this is measuring TC, and that much of the effect may be represented in HDL cholesterol (HDL-C). Which would ostensibly be a good thing, according to some. So, let's investigate this.
![[Pasted image 20221123152038.png]]
This graph represents changes in LDL-C as a function of increasing DC [3](https://www.ncbi.nlm.nih.gov/pubmed/30596814). As you can see, going from the average of 300mg/day to any quantity of DC above it yields no significant changes in LDL-C. However, going from 0mg/day to 300mg/day increases LDL-C by almost 10mg/dL. This isn't nothing. It's a meaningful change, and the two graphs cohere well.
But, just to hammer this home, let's check out HDL-C. 
![[Pasted image 20221123152041.png]]
DC does, as my dad would say, "sweet piss-all" to HDL-C. Which effectively means that for the average person, LDL-C is soaking the brunt of DC's impact. But let's not all go vegan and drop our DC intakes to zero just yet. There's definitely more to this story.
Numerous studies have demonstrated that it's not so much the cholesterol in LDL that is the problem, it's the LDL particles (LDLp) themselves [4](https://www.ncbi.nlm.nih.gov/pubmed/30694319)[5](https://www.ncbi.nlm.nih.gov/pubmed/21392724). When adjusted for the number of LDLp, the association between LDL-C and CVD becomes virtually null. Personally, I take this to mean that if dietary cholesterol isn't raising LDL particles, it probably isn't increases CVD risk.
**Key points:**
- Studies finding null effects of DC on CVD may be confounded by baseline DC intakes.
- DC increases LDL cholesterol on average.
- DC doesn't increase HDL cholesterol on average.
- LDLp causes CVD, not LDL-C, so DC may not be a big deal after all.
**References:**
[1] Hopkins PN. Effects of dietary cholesterol on serum cholesterol: a meta-analysis and review. Am J Clin Nutr. 1992 Jun. [https://www.ncbi.nlm.nih.gov/pubmed/1534437](https://www.ncbi.nlm.nih.gov/pubmed/1534437)
[2] Berger S, et al. Dietary cholesterol and cardiovascular disease: a systematic review and meta-analysis. Am J Clin Nutr. 2015 Aug. [https://www.ncbi.nlm.nih.gov/pubmed/26109578](https://www.ncbi.nlm.nih.gov/pubmed/26109578)
[3] Vincent MJ, et al. Meta-regression analysis of the effects of dietary cholesterol intake on LDL and HDL cholesterol. Am J Clin Nutr. 2019 Jan. [https://www.ncbi.nlm.nih.gov/pubmed/30596814](https://www.ncbi.nlm.nih.gov/pubmed/30596814) 
[4] Ference BA, et al. Association of Triglyceride-Lowering LPL Variants and LDL-C-Lowering LDLR Variants With Risk of Coronary Heart Disease. JAMA. 2019 Jan. [https://www.ncbi.nlm.nih.gov/pubmed/30694319](https://www.ncbi.nlm.nih.gov/pubmed/30694319) 
[5] Otvos JD, et al. Clinical implications of discordance between low-density lipoprotein cholesterol and particle number. J Clin Lipidol. 2011 Mar. [https://www.ncbi.nlm.nih.gov/pubmed/21392724](https://www.ncbi.nlm.nih.gov/pubmed/21392724)
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#nutrition
#disease
#LDL
#dietary_cholesterol
#ApoB
#animal_foods

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💻 Hyperblog/Blogs/Patreon/What RCT Shows That Any Animal Foods Are Bad.md Executable file
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This is a question that I've encountered in many debates and discussions that I have had with people who argue for the health value of animal products. When asked to elaborate on why they have formed these beliefs, their answers will generally cash out into an appeal to nature fallacy. I won't be covering why appeal to nature fallacies are bullshit here, though.
Today I'm going to be talking about an actual randomized controlled trial that did substitute non-animal foods for animal foods and did actually show a massive reduction in heart disease risk. This, of course, is the Lyon Diet Heart study (LDHS) [1](https://pubmed.ncbi.nlm.nih.gov/7911176/).
This study has also been used as a launching pad for many motivated claims about the so-called deleterious effects of vegetable oils, as the investigators made a point of reducing the linoleic acid (LA) content of the experimental diet. We'll get into why that's bullshit in a moment.
Firstly, let's talk about the study. This was a moderately sized randomized controlled trial that aimed to investigate the relationship between a Mediterranean dietary pattern and secondary prevention of acute myocardial infarction (AMI). That means the subjects had already had a single AMI at baseline.
One of the primary aims of the trial was to increase the omega-3 content of the experimental diet specially by providing a margarine that was high in alpha-linolenic acid. But, let's check out what else these people were eating.
![[1-96.png]]
The experimental diet differed from the control diet by an extra bite of: bread, legumes, vegetables, and margarine, and one fewer bite of meat, delicatessen, butter, and cream. Even through the differences in daily intake were equal to about a bite per food group, the aggregate of that would be largely equal to substituting one or more plant-based meals per week for one or two animal-based meals per week.
This substitution was commensurate with a 73% decrease in the risk of AMI. The total subject number and event rates were also decently high given the 2.25-year mean follow-up of the trial. So it's probably not likely that we're just seeing the result of poor statistical power here.
![[1-97.png]]
So, the next time somebody asks you for such a study, this is the paper that should come to mind. To my knowledge, this is the only time this particular research question has been investigated in this way.
For those who subscribe to appeal to nature fallacies, what should be most striking about the results is the fact that processed foods actually comprised quite a bit of the substitution for the experimental group. Yet, a significant risk reduction was still observed.
However, for me personally, the most interesting result was that the difference in AMI risk occurred without significant differences in LDL. Which leads me to one more thing before we finish. The researchers actually did make an attempt to reduce LA in the experimental diet.
> _At randomisation, the diet of the experimental group (table 3) was assumed to be that of controls, ie, close to the prudent diet of the American Heart Association (total lipids, 31 % energy; saturated fats, 105%; polyunsaturated/saturated ratio, 078). Eight weeks later, the experimental group had decreased their intake of saturated fat, cholesterol, and_ _**linoleic acid**_ _while increasing that of oleic and alpha-linolenic acid._
This fact has been used by many motivated reasoners to argue that the reduction in LA explains the reduction in events despite no significant differences in LDL. However, considering how many dietary changes there were in this study, to chalk the results up to a difference in linoleic acid intake seems pretty reductionist and silly, in my view.
See, linoleic acid intake was only about 7.7g/day in the experimental group. So if the difference in risk was explained by this difference in LA intake, it would mean that consuming more linoleic acid than this would increase your risk of AMI. But we know from wider research that this is just ridiculous [2](https://pubmed.ncbi.nlm.nih.gov/32428300/)[3](https://pubmed.ncbi.nlm.nih.gov/30488422/)[4](https://pubmed.ncbi.nlm.nih.gov/25161045/). In a systematic review an meta-analysis by Hooper et al. (2018), these were the author's conclusions about LA and AMI:
> _In spite of its limitations, the weak evidence we collected in this review appears to suggest that omega-6 fats are not harmful. There is no evidence for increasing omega-6 fats to reduce cardiovascular outcomes other than myocardial infarction. Although the potential benefit of omega-6 fats in reducing myocardial infarction remains to be proven, increasing omega-6 fats may be of benefit in patients with high risk of myocardial infarction._
It is absurdly reductionist to suggest that the differences in outcomes in the LDHS are attributable to the differences in LA intake. But, to hammer this home, we can actually use the stronger contrary evidence to create a defeater for this position with a pretty hilarious modus tollens:
<div style="text-align: center">
<font color="CC6600">
<b>P1)</b></font> If increasing LA beyond 7.7g/day increases AMI risk, then increasing LA beyond 7.7g/day doesn't lower AMI risk..
<br />
<font color="CC6600">
<b>(P→¬Q)</b>
<br />
<b>P2)</b></font> Increasing LA beyond 7.7g/day lowers AMI risk.
<br />
<font color="CC6600">
<b>(Q)</b>
<br />
<b>C)</b></font> Therefore, increasing LA beyond 7.7g/day doesn't increase AMI risk.
<br />
<font color="CC6600">
<b>(∴¬P)</b>
<br />
<br />
</font>
</div>
In conclusion, it is unlikely that the results on the LDHS are attributable to reductions in LA in the experimental group. It is more likely that the 73% reduction in AMI risk in the experimental group is attributable to replacing animal products with healthier foods.
**Key points:**
- The only study that broadly investigated the effect of animal food replacement on acute myocardial infarction found a 73% reduction in risk.
- It has been argued that the reduction in linoleic acid intake was responsible for the effect, but it's extremely unlikely.
**References:**
[1] [https://pubmed.ncbi.nlm.nih.gov/7911176/](https://pubmed.ncbi.nlm.nih.gov/7911176/) 
[2] [https://pubmed.ncbi.nlm.nih.gov/32428300/](https://pubmed.ncbi.nlm.nih.gov/32428300/) 
[3] [https://pubmed.ncbi.nlm.nih.gov/30488422/](https://pubmed.ncbi.nlm.nih.gov/30488422/) 
[4] [https://pubmed.ncbi.nlm.nih.gov/25161045/](https://pubmed.ncbi.nlm.nih.gov/25161045/)
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#meat
#coronary_heart_disease
#nutrition

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💻 Hyperblog/Blogs/Patreon/What Would Keto Dietary Guidelines Look Like.md Executable file
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There has been much talk about whether or not the guidelines should include low-carbohydrate or ketogenic options. Especially from higher-impact folks within the low-carb community, such as Nina Teicholz and Zoe Harcombe.This might be surprising to some of you, but this is actually a subject about which I agree with low-carb community.
I do actually feel strongly that the acceptable ranges of both fat and carbohydrates in the guidelines are unnecessarily constricted. The guidelines should probably include low carbohydrate options. So, I thought it would be a fun exercise to try to reconstruct the guidelines to accommodate a low-carbohydrate ketogenic dietary pattern.
Let's take a look at the current guidelines for adults between the ages of 19-59:
![[1-88.png]]
Right off the bat, it is clear that this exercise will necessarily involve eliminating some food groups from consideration. I'll also have to include some other food groups, and adjust others. Here's a list of modifications that I made:
- 1) Starchy Vegetables and have been removed.
- 2) Grain group replaced with Healthy Fats group.
- 3) Nuts and Seeds have been moved from Protein Foods to Healthy Fats.
- 4) Fruit was renamed to Fatty Fruit and was included in Healthy Fats.
- 5) Cocoa Products added to Healthy Fats.
- 6) Dairy was replaced with Plant Milks.
- 7) Plant Protein Products added to Protein Foods.
- 8) Oils was changed to Unsaturated Oils
Most of these changes should be relatively self-explanatory. Largely the changes are aiming to replace healthy carbohydrate sources with healthy fat sources. However, there are a few of changes that probably require some unpacking:
- Change number five was to both appease the saturated fat loving low carb nuts, as well as to include an additional healthy high-fat food.
- Change number six was actually to lower carbohydrates, because unsweetened plant milks are almost universally lower in carbohydrates than actual dairy milk.
- Change number seven was because many animal foods are simply too high in saturated fat to be compatible with a guidelines-compliant ketogenic diet at the levels consumed in the original guidelines.
Here are the guidelines after my changes:
![[1-89.png]]
I tried to formulate these new keto-friendly guidelines to be consistent with the existing guidelines in spirit, meaning that they are cognizant of the primary recommendations. For example, the above formulation will typically produce a diet that is under 10% of energy as saturated fat, under 10% of energy as added sugar, under 2500mg per day of sodium, and restricts alcohol.
Here is an example of a 2000 kcal day of eating according to our hypothetical ketogenic guidelines, as well as the nutritional breakdown:
![[Pasted image 20221123152402.png]]
![[Pasted image 20221123152406.png]]
Despite being primarily plant-based, the diet provides under 35g/day of net carbohydrates. Also, despite having almost 142g/day of dietary fat, the diet also provides under 22g/day of saturated fat. Saturated fat can also be taken down further simply through the omission of the chocolate, so it's not a big issue at all in my view. The diet also provides very little dietary cholesterol, which is also in keeping with the spirit of the guidelines.
In conclusion, I think it is indeed possible to achieve a healthy ketogenic diet that aligns well with the recommendations provided by the dietary guidelines. I hope one day such a diet could be included in the guidelines, particularly as ketogenic diets continue to gain traction in the general population. With more people pursuing ketogenic diets, the more pressing it will become to have official guidance on the matter.
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#keto
#dietary_guidelines
#nutrition

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💻 Hyperblog/Blogs/Patreon/When Saturated Fat Reduces Heart Disease Risk.md Executable file
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I missed one week's blog article earlier this month due to writing the [meta-analysis of low carb diets](https://thenutrivore.blogspot.com/2020/10/low-carbohydrate-diets-and-health.html). So, this week gets two articles to make up for it.
I've written extensively about how the risk of cardiovascular disease (CVD) conferred by saturated fat (SFA) can easily be lost in the means. That is to say certain, less rigorous statistical analyses that have previously been performed on SFA as it relates to CVD tend to hide dose-dependent effects. This has been a significant obstacle to effective public health communication on the health risks of higher SFA diets. 
However, even when these analyses are done well, there are nuances that are lost. Considering SFA as a broad category actually hides instances wherein certain sources of SFA seem to reduce the risk of CVD. In this article I'll go over some high-SFA foods that are actually beneficial to CVD risk.
**Cocoa Products**
A meta-analysis in 2018 found that the consumption of cocoa products was associated with a decreased risk for all CVD endpoints, including stroke [1](https://pubmed.ncbi.nlm.nih.gov/30061161/). Their findings indicate that cocoa product consumption achieved a maximal risk reduction at 50g/week, and the association was null beyond 100g/week.
![[Pasted image 20221123152504.png]]
However, a meta-analysis published in the previous year performed two separate analyses related to CVD [2](https://pubmed.ncbi.nlm.nih.gov/28671591/). This can have advantages over considering all CVD endpoints together as a composite endpoint. The first analysis was for coronary heart disease (CHD), and the second analysis was for stroke. 
![[Pasted image 20221123152509.png]]
Their dose-response curve for CHD finds no upper limit to the risk reductions of cocoa product consumption. From the lowest to highest intakes, cocoa product consumption lowers the risk of CHD by 10%.
![[Pasted image 20221123152513.png]]
Just for fun, we can also look at their findings for stroke. There is also no upper limit to the risk reductions of cocoa product consumption that are observed. From the highest to the lowest intakes, cocoa product consumption reduces stroke risk by 16%.
**Non-Homogenized Dairy**
Starting with the most obvious example, cheese is consistently associated with lower rates of heart disease. A meta-analysis from 2017 generated two dose response curves— one for CVD and another for CHD [3](https://pubmed.ncbi.nlm.nih.gov/27517544/). 
![[Pasted image 20221123152518.png]]
For CVD (left), we see maximal risk reductions around 35g/day. Results become null beyond 80g/day. That's an enormous amount of cheese! For CHD, (right), there is no upper limit to risk reductions at all, despite daily intakes being as high as 120g. That's over a quarter pound of cheese per day, and over 22g of SFA!
Similar to that of cheese, yogurt consumption has been shown to associate with dose-dependent reductions in CVD as well, though not as powerfully [4](https://pubmed.ncbi.nlm.nih.gov/31970674/).
![[Pasted image 20221123152523.png]]
The highest yogurt intakes were close to a pound of yogurt per day. Sweet jumping Jesus that's a lot of yogurt, and likely around 10g of SFA. Yet, yogurt confers a ~13% reduction in CVD risk.
**Key points:**
- Saturated fat consumption is associated with higher rates of heart disease.
- There are sources of saturated fat that are inversely associated with heart disease.
- Higher chocolate, cheese, and yogurt intakes associated with lower rates of CVD.
**References:**
[1] Yongcheng Ren, et al. Chocolate consumption and risk of cardiovascular diseases: a meta-analysis of prospective studies. Heart. 2019 Jan. [https://pubmed.ncbi.nlm.nih.gov/30061161/](https://pubmed.ncbi.nlm.nih.gov/30061161/)
[2] Sheng Yuan, et al. Chocolate Consumption and Risk of Coronary Heart Disease, Stroke, and Diabetes: A Meta-Analysis of Prospective Studies. Nutrients. 2017 Jul. [https://pubmed.ncbi.nlm.nih.gov/28671591/](https://pubmed.ncbi.nlm.nih.gov/28671591/)
[3] Guo-Chong Chen, et al. Cheese consumption and risk of cardiovascular disease: a meta-analysis of prospective studies. Eur J Nutr. 2017 Dec. [https://pubmed.ncbi.nlm.nih.gov/27517544/](https://pubmed.ncbi.nlm.nih.gov/27517544/)
[4] Xiang Gao, et al. Yogurt Intake Reduces All-Cause and Cardiovascular Disease Mortality: A Meta-Analysis of Eight Prospective Cohort Studies. Chin J Integr Med. 2020 Jun. [https://pubmed.ncbi.nlm.nih.gov/31970674/](https://pubmed.ncbi.nlm.nih.gov/31970674/)
#patreon_articles
#nutrition
#disease
#dairy
#chocolate
#cheese
#yogurt
#cardiovascular_disease

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💻 Hyperblog/Blogs/Patreon/Why Does LDL Cause Heart Disease.md Executable file
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We've all heard that LDL causes heart disease, and it is actually true. But why? The short answer is that evolution sucks at selecting out physiological traits that are detrimental to our health if they occur after reproductive age. The long answer is quite a bit more complicated.
Essentially, each LDL particle in your bloodstream has on it a protein called apolipoprotein beta-100— ApoB for short. This ApoB protein is made up on amino acids in a particular sequence, because it needs to be able to bind to LDL receptors in various tissues to be pulled out of circulation and used. But, there is a downside. ApoB is built in such a way that it has a similar binding affinity for other structures in the body as well, not just the LDL receptor. 
In the artery, we have an endothelium, which is a thin layer of cells that separate the arterial lumen from the sub-endothelial space. These endothelial cells don't always fit tightly together, so many objects in our blood have the capacity to penetrate the endothelium and enter the sub-endothelial space. This isn't actually a problem in and of itself. All sorts of objects and molecules flow in and out of that space all day through small cracks in our endothelium—  not a big deal. However, ApoB has a unique affinity for structures in the sub-endothelial space called proteoglycans [1](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC508856/). 
Proteoglycans are long hair-like structures that line the subendothelial space. ApoB uniquely binds to these structures. ApoB binding to proteoglycans serves no meaningful physiological function, but is the initiating event that causes atherosclerosis [2](https://www.ncbi.nlm.nih.gov/pubmed/22176921). We know this because there have been mouse experiments wherein ApoB has been modified such that it doesn't bind to proteoglycans, but it still binds the LDL receptor.
![[Pasted image 20221123152557.png]]
The mice with modified ApoB get much, much less atherosclerosis [3](https://www.ncbi.nlm.nih.gov/pubmed/12066187)[4](https://www.ncbi.nlm.nih.gov/pubmed/14726411). You can drive their LDL sky high and virtually nothing happens. In the end it all comes down to the absolute ApoB concentration in the blood.
**Key points:**
- Native ApoB is necessary to initiate atherosclerosis.
- Modifying ApoB such that it doesn't bind to intimal proteoglycans inhibits the development of atherosclerosis.
- Get your ApoB checked.
**References:**
[1] J Borén, et al. Identification of the principal proteoglycan-binding site in LDL. A single-point mutation in apo-B100 severely affects proteoglycan interaction without affecting LDL receptor binding. J Clin Invest. 1998 Jun. [https://www.ncbi.nlm.nih.gov/pmc/articles/PMC508856/](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC508856/) 
[2] Fogelstrand P and Borén J.  Retention of atherogenic lipoproteins in the artery wall and its role in atherogenesis. Nutr Metab Cardiovasc Dis. 2012 Jan. [https://www.ncbi.nlm.nih.gov/pubmed/22176921](https://www.ncbi.nlm.nih.gov/pubmed/22176921) 
[3] Skålén K, et al. Subendothelial retention of atherogenic lipoproteins in early atherosclerosis. Nature. 2002 Jun 13. [https://www.ncbi.nlm.nih.gov/pubmed/12066187](https://www.ncbi.nlm.nih.gov/pubmed/12066187) 
[4] Flood C, et al. Molecular mechanism for changes in proteoglycan binding on compositional changes of the core and the surface of low-density lipoprotein-containing human apolipoprotein B100. Arterioscler Thromb Vasc Biol. 2004 Mar. [https://www.ncbi.nlm.nih.gov/pubmed/14726411](https://www.ncbi.nlm.nih.gov/pubmed/14726411)
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#disease
#LDL
#ApoB
#proteoglycans
#LDL_retention

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💻 Hyperblog/Blogs/Patreon/Why Doesn't Chocolate Increase LDL.md Executable file
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It's December! Which means that many of us are likely to be sucking down discount chocolate like it's going out of style, haha. So, as a special Christmas blog article, I'll be discussing why you might not need to worry about what that chocolate is doing to your LDL. Enjoy!
First off, chocolate does not seem to increase LDL, despite it being loaded with saturated fat. But why? Since chocolate is basically just two main ingredients (ground cocoa and cocoa butter) we should explore this question by looking at the effects of these ingredients together as well as in isolation, one at a time.
In the aggregate, cocoa products like chocolate counterintuitively tend to lower LDL in humans [1](https://pubmed.ncbi.nlm.nih.gov/21559039/). However, a handful of studies have attempted to investigate potential explanations for this phenomenon, and have isolated a few components within the cocoa products themselves to have LDL-lowering properties [2](https://pubmed.ncbi.nlm.nih.gov/18716168/)[3](https://pubmed.ncbi.nlm.nih.gov/15190043/). 
Grassi et al. (2008) investigated the effects of dark chocolate on LDL and blood pressure compared to white chocolate, which is excellent methodology if you want to isolate the effect of the cocoa itself. This is because white chocolate is basically just sweetened cocoa butter without the ground cocoa. Ultimately the researchers found that the dark chocolate lowered LDL by 7%, as well as improved blood pressure.
Engler et al. (2004) employed a similar methodology, but using low-flavanol verses high-flavanol cocoa drinks. For both the intervention and control groups, the within-group differences in LDL were non-significant. However, the between group treatment effect was statistically significant.
Altogether this would suggest that ground cocoa is at least one of the components of chocolate that could plausibly contribute to its LDL-lowering effects.
Now on to cocoa butter. The primary saturated fat in cocoa butter is stearic acid, which hasn't really been persuasively shown to increase LDL in controlled human feeding studies [4](https://apps.who.int/iris/handle/10665/246104). But why is this? To answer this, we have to explore what happens to stearic acid once it is consumed.
Rodríguez-Morató et al. (2020) recently elucidated plausible explanations for the neutral effect of stearic acid on blood lipids by feeding subjects radio-labeled stearic acid to determine its metabolic fate [5](https://pubmed.ncbi.nlm.nih.gov/32998517/).
Basically, the mechanism seems to be twofold. Firstly, much of the stearic acid seems to be readily converted to oleic acid and palmitoleic acid, which are LDL-lowering monounsaturated fats. The minority of the stearic acid is converted to LDL-raising palmitic acid.
![[1-83.png]]
Secondly, stearic acid seems to be preferentially esterified to cholesterol to form cholesteryl esters, which is a similar mechanism to the one that is responsible for the LDL-lowering effects of polyunsaturated fat.
Interestingly enough, this study is probably one of the most well-controlled stearic acid feeding experiments ever done, and it showed that feeding stearic acid actually lowered LDL by 13%. However, LDL was quite high to begin with in this subject pool. For normolipidemic subjects, the effects of stearic acid on LDL would likely be non-significant.
In conclusion, dark chocolate and cocoa products may be high in saturated fat, but they actually tend to lower LDL through a constellation of mechanisms. These mechanisms likely include pleiotropic effects of polyphenols, inhibited enterohepatic cholesterol circulation by dietary fibre, and unique biochemical properties of the stearic acid found in cocoa butter.
**Key points:**
- Cocoa products like dark chocolate tend to lower LDL.
- Cocoa itself tends to lower LDL via polyphenols and fibre.
- Cocoa butter doesn't tend to raise LDL due to unique effects of stearic acid.
**References:**
[1] [https://pubmed.ncbi.nlm.nih.gov/21559039/](https://pubmed.ncbi.nlm.nih.gov/21559039/) 
[2] [https://pubmed.ncbi.nlm.nih.gov/18716168/](https://pubmed.ncbi.nlm.nih.gov/18716168/) 
[3] [https://pubmed.ncbi.nlm.nih.gov/15190043/](https://pubmed.ncbi.nlm.nih.gov/15190043/) 
[4] [https://apps.who.int/iris/handle/10665/246104](https://apps.who.int/iris/handle/10665/246104) 
[5] [https://pubmed.ncbi.nlm.nih.gov/32998517/](https://pubmed.ncbi.nlm.nih.gov/32998517/)
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#nutrition
#chocolate
#LDL
#stearic_acid
#polyphenols
#metabolism

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💻 Hyperblog/Blogs/Patreon/Why Not Eat Both.md Executable file
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My decision to [meta-analyze](https://www.patreon.com/posts/olive-oil-and-39379256) olive oil and cardiovascular disease (CVD) was prompted by a few exchanges I had with a few no-oil vegans. For those who are unaware, there is a flavour of veganism that espouses the complete avoidance of all oils on the basis that oils, regardless of the variety, increase the risk of cardiovascular disease. However, if this narrative was true, my meta-analysis likely would not have found a dose-dependent decrease in CVD risk with higher and higher olive oil intakes.
The official dietary recommendations are to replace saturated fat (SFA) with unsaturated (UFA) oils. But no-oil vegans take this a step further and suggest that we should avoid all added fats and perhaps even nuts and seeds. They recommend that we consume whole food carbohydrates (WFC) instead. However, WFCs are not always found to be as effective for CVD prevention as UFAs [1](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4593072/).
![[Pasted image 20221123152759.png]]
There is some evidence that replacing dairy fats with WFC actually decreases CVD risk more than UFA oils [2](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5081717/). However, that same analysis also divulged that UFA oils protect against stroke to a greater degree than WFC.
![[Pasted image 20221123152803.png]]
There are some issues with this analysis. The primary issue being that all dairy fat is lumped together rather than delineated by type. It is well understood that butter increases CVD risk, whereas cheese does not. A proposed mechanism for this effect is the presence of the milk fat globule membrane in whole dairy foods [3](https://pubmed.ncbi.nlm.nih.gov/26016870/). Homogenization, churning, or any other process that breaks down this membrane seems to predispose the food to perturbing blood lipids.
For this reason I conducted my own meta-analysis of cheese intake and CVD risk, just for fun. 
![[Pasted image 20221123152812.png]]
It appears as though eating more cheese is preferable to less cheese. While it is true that the results for butter and CVD can come up null [4](https://pubmed.ncbi.nlm.nih.gov/27355649/). If you look into the included cohorts, it is revealed that even the lowest butter intakes are typically occurring in the context of high SFA intakes anyway. 
However, cheese intake in my included cohorts is also typically occurring in the context of high SFA intakes. However, the risk reductions persist. Suggesting that the food is beneficial despite its SFA content.
But, back to the two previously mentioned papers. In one paper, we see that replacing SFA with UFAs such as monounsaturated fats (MUFA), and especially polyunsaturated fats (PUFA), decrease CVD risk more than WFC. In the other paper, we also see that PUFA decreases risk of stroke more than WFC, and has nearly the same magnitude of effect at reducing CVD risk as WFC as well. Are we really going to break balls over a 4% difference in risk reduction? I wouldn't.
In conclusion, the takeaway message is clear. **EAT BOTH**. Eat WFCs _and_ UFAs to potentially achieve a maximal benefit. Lastly, as a relevant caveat, it's also probably not rational to fear cheese on the basis of its SFA content either. So, hell, eat all three!
**Key points:**
- There is a group of vegans who espouse complete abstinence from all added oils.
- However, unsaturated oils reduce heart disease more than whole grains when compared to saturated fats.
- Unsaturated oils also reduce stroke more than whole grains when compared to dairy fat.
- As a caveat, cheese likely reduces heart disease regardless of its saturated fat content.
- Eat whole grains, unsaturated oils, and cheese to confer greater reductions in heart disease risk.
**References:**
[1] Yanping Li, et al. Saturated Fat as Compared With Unsaturated Fats and Sources of Carbohydrates in Relation to Risk of Coronary Heart Disease: A Prospective Cohort Study. J Am Coll Cardiol. 2015 Oct. [https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4593072/](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4593072/)
[2] Mu Chen, et al. Dairy fat and risk of cardiovascular disease in 3 cohorts of US adults. Am J Clin Nutr. 2016 Nov. [https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5081717/](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5081717/) 
[3] Fredrik Rosqvist, et al. Potential role of milk fat globule membrane in modulating plasma lipoproteins, gene expression, and cholesterol metabolism in humans: a randomized study. Am J Clin Nutr. 2015 July. [https://pubmed.ncbi.nlm.nih.gov/26016870/](https://pubmed.ncbi.nlm.nih.gov/26016870/) 
[4] Laura Pimpin, et al. Is Butter Back? A Systematic Review and Meta-Analysis of Butter Consumption and Risk of Cardiovascular Disease, Diabetes, and Total Mortality. PLoS One. 2016 June. [https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4927102/](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4927102/)
#patreon_articles
#nutrition
#vegetable_oil
#whole_foods
#whole_grains
#nuts
#clownery
#disease

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💻 Hyperblog/Blogs/Patreon/Zoe Harcombe.md Executable file
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This is an open letter to the British Journal of Sports Medicine, and a direct request for a correction/retraction of Zoe Harcombe's meta-analysis of saturated fat and coronary heart disease mortality in prospective cohort studies.
Essentially, there are three fundamental issues with the [paper](https://bjsm.bmj.com/content/51/24/1743.long) that I believe invalidate the conclusions. 
- **The authors did not actually test their hypothesis**
Firstly, the included cohort studies were not investigated in a manner that tests the hypothesis stated in the objectives of the paper. One of the two stated objectives was to investigate the validity of the US and UK dietary guidelines to keep daily saturated fat (SFA) intake below 10% of energy. However, the included cohorts are not meta-analyzed in a manner that could actually test this. In order to test the validity of the US or UK dietary guidelines' recommendations to keep SFA under 10% of energy, cohorts would need to be stratified such that one subgroup has an intake range that crosses the threshold of 10% of energy as SFA. 
In other words, one subgroup would need to consist of cohorts that are consuming <10% of energy as SFA in the lowest 'tiles of intake and >10% of energy as SFA in the highest 'tiles of intake. Thus crossing the threshold of effect presupposed by both the US and UK dietary guidelines.
However, the cohorts in the paper are summated strictly to test for a completely linear relationship with no subgrouping or stratification of any kind. The paper concludes that the findings do not support the US and UK dietary guidelines, yet the authors made no attempt to actually test either the US or UK dietary guidelines. Both the US and UK dietary guidelines presuppose a non-linear relationship between cardiovascular disease (CVD) and SFA intake. 
The US dietary guidelines recommend that daily SFA intake be kept under 10% of energy [1](https://health.gov/sites/default/files/2019-10/DGA_Cut-Down-On-Saturated-Fats.pdf).
![[Pasted image 20221123152845.png]]
However, in addition to the recommendation to keep daily SFA intake below 10% of energy, the UK dietary guidelines give recommendations based on absolute intakes of SFA in grams per day [2](https://www.nhs.uk/live-well/eat-well/eat-less-saturated-fat/).
Both the US and UK dietary guidelines presuppose that consuming under 10% of energy as SFA is safe, but consuming above 10% of energy as SFA is unsafe and is associated with an increased CVD risk. The UK dietary guidelines additionally presupposes that consuming under 20g per day or 30g per day of SFA for women and men respectively is safe, but consuming intakes above those limits is unsafe and is associated with an increased CVD risk. 
The authors only tested for a linear relationship by pooling all of the cohorts together. Therefore, the conclusions cannot logically follow from the methods, nor the results. Nor do the methods logically follow from the objectives specified by the authors. There was no investigation based on intakes of SFA as a percentage of calories or as absolute intakes of SFA in grams per day.
Also, the UK dietary guidelines regarding recommended intakes of SFA are only directed toward those in the 19-64 years age group. Thus, the cohort in the 60-79 years age group from [Xu 2006](https://pubmed.ncbi.nlm.nih.gov/17023718/) cannot be used to test the hypothesis. This cohort is not within the age range toward which the UK dietary guidelines are directed.
- **The authors are investigating the wrong endpoints**
Secondly, during the time in which this paper was written and published, the US and UK dietary guidelines suggested that daily intakes of SFA over 10% of energy increase CVD and/or heart disease risk [3](https://health.gov/sites/default/files/2019-09/2015-2020_Dietary_Guidelines.pdf)[4](https://www.nhs.uk/live-well/eat-well/different-fats-nutrition/). 
![[Pasted image 20221123152953.png]]
![[Pasted image 20221123152956.png]]
Also, the original US dietary guidelines published in 1977 also emphasized heart disease risk as the primary endpoint targeted by their recommendations [5](https://naldc.nal.usda.gov/download/1759572/PDF).
![[Pasted image 20221123153002.png]]
 Whereas the original UK dietary guidelines published in 1983 emphasize both heart disease risk and mortality [6](https://pubmed.ncbi.nlm.nih.gov/6136848/).
![[Pasted image 20221123153008.png]]
However, the authors only investigated coronary heart disease (CHD) mortality. This endpoint is not explicitly given higher priority over any other CVD related endpoint by either the US or UK dietary guidelines at the time the paper was published. 
I would conclude that the authors' inclusion/exclusion criteria are not structured in a fashion that actually investigates the recommendations put forth by either the US or UK dietary guidelines. The authors' inclusion/exclusion criteria need to be restructured to suit the hypothesis stated in their objectives.
The ambiguity of the US and UK dietary guidelines, both past and present, may necessitate the use of multiple meta-analyses with differing inclusion/exclusion criteria, such that different endpoints are investigated individually. Alternatively, a single-meta-analysis with inclusion/exclusion criteria that are loose enough to capture many different CVD-related endpoints may be sufficient. Nevertheless, merely selecting CHD mortality as the only relevant endpoint is arbitrary and should be corrected.
- **Two of the included cohorts can't be used to test the hypothesis**
Lastly, two of the included papers cannot be included in the meta-analysis if the meta-analysis is to actually test both the US and UK dietary guidelines correctly. The papers [Boniface (2002)](https://pubmed.ncbi.nlm.nih.gov/12122556/) and [Pietinen (1997)](https://pubmed.ncbi.nlm.nih.gov/9149659/) do not report SFA intake as a percentage of energy. Nor can that data be calculated or inferred based on any other data included in either paper. There is no way to precisely know what percentage of calories were SFA within these two cohorts. Therefore they cannot be included in a meta-analysis that requires that information in order to test their stated hypothesis.
However, we _can_ actually investigate the relationship between absolute intakes of SFA and CHD mortality. Absolute intake data for SFA was either included in each paper, or could be calculated based on other data that was included in each paper. This allows us to specifically investigate the UK dietary guidelines to limit SFA intake to below 20-30g/day.
- **My subgroup analysis of the authors' meta-analysis**
Figure 3 represents the authors' included cohorts, limited strictly to those that can be used to test either the US or UK dietary guidelines. The included cohorts support the UK dietary guidelines to keep SFA intake under ~25g/day for people between the ages of 19-64. A statistically significant increase is risk is seen. Conversely, no statistically significant increase in risk is observed when testing the US dietary guidelines, however only two studies are being analyzed in that subgroup.
**Figure 1**
![[Pasted image 20221123153223.png]]
Based on these findings and the inconsistencies within this manuscript, I request that the authors either correct these inconsistencies or that the manuscript be retracted on the basis of these inconsistencies and methodological errors. Thank you very much for your time and patience!"
[Supplementary Data](https://docs.google.com/spreadsheets/d/13HI3D5A34wkakXPMHwCB0sVjP3bEeBTvnLhbjeu8PLM/edit?usp=sharing)
Reply from the BMJ (July 8th, 2020):
![[Pasted image 20221123153305.png]]
#patreon_articles
#nutrition
#disease
#saturated_fat
#cardiovascular_disease
#clowns
#clownery
#debate
#zoe_harcombe

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💻 Hyperblog/Work/coronary heart disease.md
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# Coronary Heart Disease
Coronary heart disease (CHD) is a condition where the coronary arteries, which supply oxygen-rich blood to the heart muscle, become narrowed or blocked due to the buildup of plaque, known as [[atherosclerosis]]. This reduction in blood flow can cause chest pain (angina), shortness of breath, and other symptoms. This can be caused by various factors including genetic predisposition, poor [[lifestyle]] habits, such as following a [[standard american diet]], and underlying medical conditions.****
Coronary heart disease (CHD) is a condition where the coronary arteries, which supply oxygen-rich blood to the heart muscle, become narrowed or blocked due to the buildup of plaque, known as [[atherosclerosis]]. This reduction in blood flow can cause chest pain (angina), shortness of breath, and other symptoms. This can be caused by various factors including genetic predisposition, poor [[lifestyle]] habits, such as following a [[standard american diet]], and underlying medical conditions.
**Key features of coronary heart disease:**

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💻 Hyperblog/Work/seed oil claims - cholestasis.md
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## Rebuttal
While partially true, this claim counts as a [[red herring]], because it's not actually seed oils simpliciter that causes [[cholestasis]]. In the [[LA Veterans Administration Hospital Study]], the seed oil group had a dose-dependent increase in gallstones [(1)](https://pubmed.ncbi.nlm.nih.gov/4681896/). However, the most parsimonious way of explaining the effect is through hepatic [[phytosterol]] elimination leading to gallstones, not [[linoleic acid]] [(2)](https://pubmed.ncbi.nlm.nih.gov/9437703/)[(3)](https://pubmed.ncbi.nlm.nih.gov/27812789/).
While partially true, this claim counts as a [[red herring]], because it's not actually seed oils simpliciter that causes [[cholestasis]]. In the [[LA Veterans Administration Hospital Study]], the seed oil group had a dose-dependent increase in gallstones [(1)](https://pubmed.ncbi.nlm.nih.gov/4681896/). However, the most parsimonious way of explaining the effect is through the elimination of hepatic [[phytosterols]], leading to gallstones, not [[linoleic acid]] [(2)](https://pubmed.ncbi.nlm.nih.gov/9437703/)[(3)](https://pubmed.ncbi.nlm.nih.gov/27812789/).
Some seed oils, such as corn oil (the primary seed oil investigated in the LA Veterans trial), have extremely high concentrations of [[phytosterols]] [(4)](https://pubmed.ncbi.nlm.nih.gov/31404986/). At the doses investigated, this may be expected to cause issues, but these are not doses that people typically consume, even on the [[standard american diet]].
Some seed oils, such as corn oil (the primary seed oil investigated in the LA Veterans trial), have extremely high concentrations of phytosterols [(4)](https://pubmed.ncbi.nlm.nih.gov/31404986/). At the doses investigated, this may be expected to cause issues, but these are not doses that people typically consume, even on the [[standard american diet]].
---