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feat: reorganized articles
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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.
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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.
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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.
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**Key points:**
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- eTRF seems to improve glucose disposal and insulin sensitivity.
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- eTRF seems to improve feelings of satiety and fullness.
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- eTRF seems to be anti- and pro-inflammatory in different ways.
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- eTRF seems to perturb blood lipids in a negative way.
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- eTRF seems to be more physiologically stressful.
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**References:**
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[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)
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#patreon_articles
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#nutrition
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#disease
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#fasting
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#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.
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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.
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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.
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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.
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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/).
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**Key points:**
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- Phytate may help those with hemochromatosis avoid symptoms of iron overload.
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- Phytate seems to help mitigate the burden of AGEs in diabetic patients.
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- Eating more phytate may make you better at mitigating its harmful effects.
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- There are many promising benefits of phytate that are being actively researched.
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**References:**
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[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/)
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[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/)
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[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)
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[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/)
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#patreon_articles
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#nutrition
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#disease
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#antinutrients
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#phytate
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#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.
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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?
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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.
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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).
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**Key points:**
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- Phytate-rich foods do inhibit the absorption of minerals from other foods in the diet.
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- The phytate-to-mineral ratio of the diet is a decent proxy for overall mineral status, but is likely due to inappropriate food pairing.
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- Pairing phytate-rich foods with mineral-rich foods is the most relevant consideration regarding the inhibition of mineral absorption.
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- Food avoidance on the basis of phytate is probably unjustified.
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- Soaking, vitamin C, and perhaps even meat itself can improve the bioavailability of minerals from phytate-rich foods.
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- Many phytate-rich foods are healthy and nutritious in ways unrelated to their mineral content.
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**References:**
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[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)
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[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)
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[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)
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[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/)
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[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)
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[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)
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[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)
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[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)
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#patreon_articles
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#nutrition
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#disease
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#antinutrients
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#phytate
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#clownery
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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**Key points:**
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- There are case reports of oxalate-induced illness and death in the literature.
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- These case reports almost universally involve individuals with pre-existing health conditions.
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- These case reports also almost universally involve juicing, blending, or otherwise processing high oxalate foods.
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- Star fruit is the only whole food associated with oxalate-induced illness, but only really in people with chronic kidney disease.
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- High oxalate mono-diets are fucking bad for you.
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**References:**
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[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)
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[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/)
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[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/)
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[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/)
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[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/)
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[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/)
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[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/)
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#patreon_articles
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#nutrition
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#antinutrients
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#oxalate
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#clownery
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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.
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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.
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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/).
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![[1-33.png]]
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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.
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![[1-32.png]]
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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/).
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![[1-31.png]]
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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/).
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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.
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![[Pasted image 20221123153414.png]]
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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.
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![[Pasted image 20221123153420.png]]
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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.
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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.
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**Key points**
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- It has been suggested that artificial sweeteners cause weight gain.
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- Human experiments shows that artificial sweeteners tend to lead to weight loss.
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- Artificial sweeteners do no increase plasma glucose or plasma insulin.
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**References:**
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[1] [https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4135487/](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4135487/)
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[2] [https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6313893/](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6313893/)
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[3] [https://pubmed.ncbi.nlm.nih.gov/24862170/](https://pubmed.ncbi.nlm.nih.gov/24862170/)
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[4] [https://pubmed.ncbi.nlm.nih.gov/27956737/](https://pubmed.ncbi.nlm.nih.gov/27956737/)
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[5] [https://pubmed.ncbi.nlm.nih.gov/19221011/](https://pubmed.ncbi.nlm.nih.gov/19221011/)
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#patreon_articles
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#nutrition
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#disease
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#obesity
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#artificial_sweeteners
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#metabolic_syndrome
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#type_2_diabetes
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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.
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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".
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![[1-79.png]]
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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.
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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.
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||||
|
||||
![[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
|
||||
|
|
@ -1,44 +0,0 @@
|
|||
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
|
||||
|
|
@ -1,36 +0,0 @@
|
|||
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
|
||||
|
|
@ -1,25 +0,0 @@
|
|||
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
|
||||
|
|
@ -1,51 +0,0 @@
|
|||
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
|
||||
|
|
@ -1,48 +0,0 @@
|
|||
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
|
||||
|
|
@ -1,35 +0,0 @@
|
|||
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
|
||||
|
|
@ -1,53 +0,0 @@
|
|||
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
|
||||
|
|
@ -1,33 +0,0 @@
|
|||
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
|
||||
|
|
@ -1,39 +0,0 @@
|
|||
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
|
||||
|
|
@ -1,36 +0,0 @@
|
|||
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
|
||||
|
|
@ -1,28 +0,0 @@
|
|||
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
|
||||
|
|
@ -1,72 +0,0 @@
|
|||
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
|
||||
|
|
@ -1,54 +0,0 @@
|
|||
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
|
||||
|
|
@ -1,42 +0,0 @@
|
|||
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
|
||||
|
|
@ -1,52 +0,0 @@
|
|||
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
|
||||
|
|
@ -1,51 +0,0 @@
|
|||
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
|
||||
|
|
@ -1,65 +0,0 @@
|
|||
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
|
||||
|
|
@ -1,65 +0,0 @@
|
|||
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
|
||||
|
|
@ -1,36 +0,0 @@
|
|||
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
|
||||
|
|
@ -1,25 +0,0 @@
|
|||
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
|
||||
|
|
@ -1,64 +0,0 @@
|
|||
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
|
||||
|
|
@ -1,162 +0,0 @@
|
|||
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
|
||||
|
|
@ -1,47 +0,0 @@
|
|||
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
|
||||
|
|
@ -1,45 +0,0 @@
|
|||
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
|
||||
|
|
@ -1,78 +0,0 @@
|
|||
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
|
||||
|
|
@ -1,97 +0,0 @@
|
|||
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
|
||||
|
|
@ -1,45 +0,0 @@
|
|||
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
|
||||
|
|
@ -1,72 +0,0 @@
|
|||
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
|
||||
|
|
@ -1,24 +0,0 @@
|
|||
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
|
||||
|
|
@ -1,81 +0,0 @@
|
|||
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
|
||||
|
|
@ -1,45 +0,0 @@
|
|||
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
|
||||
|
|
@ -1,58 +0,0 @@
|
|||
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
|
||||
|
|
@ -1,43 +0,0 @@
|
|||
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
|
||||
|
|
@ -1,32 +0,0 @@
|
|||
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
|
||||
|
|
@ -1,44 +0,0 @@
|
|||
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
|
||||
|
|
@ -1,55 +0,0 @@
|
|||
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
|
||||
|
|
@ -1,147 +0,0 @@
|
|||
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
|
||||
|
|
@ -1,30 +0,0 @@
|
|||
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
|
||||
|
|
@ -1,165 +0,0 @@
|
|||
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
|
||||
|
|
@ -1,41 +0,0 @@
|
|||
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
|
||||
|
|
@ -1,45 +0,0 @@
|
|||
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
|
||||
|
|
@ -1,42 +0,0 @@
|
|||
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
|
||||
|
|
@ -1,41 +0,0 @@
|
|||
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
|
||||
|
|
@ -1,46 +0,0 @@
|
|||
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
|
||||
|
|
@ -1,30 +0,0 @@
|
|||
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
|
||||
|
|
@ -1,41 +0,0 @@
|
|||
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
|
||||
|
|
@ -1,36 +0,0 @@
|
|||
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
|
||||
|
|
@ -1,87 +0,0 @@
|
|||
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
|
||||
|
|
@ -1,39 +0,0 @@
|
|||
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
|
||||
|
|
@ -1,68 +0,0 @@
|
|||
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
|
||||
|
|
@ -1,51 +0,0 @@
|
|||
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
|
||||
|
|
@ -1,54 +0,0 @@
|
|||
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
|
||||
|
|
@ -1,64 +0,0 @@
|
|||
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)
|
||||
|
||||
#patreon_articles
|
||||
#nutrition
|
||||
#disease
|
||||
#weight_loss
|
||||
#low_carb
|
||||
#low_fat
|
||||
|
|
@ -1,48 +0,0 @@
|
|||
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)
|
||||
|
||||
#patreon_articles
|
||||
#nutrition
|
||||
#disease
|
||||
#LDL
|
||||
#dietary_cholesterol
|
||||
#ApoB
|
||||
#animal_foods
|
||||
|
|
@ -1,76 +0,0 @@
|
|||
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/)
|
||||
|
||||
#patreon_articles
|
||||
#meat
|
||||
#coronary_heart_disease
|
||||
#nutrition
|
||||
|
|
@ -1,45 +0,0 @@
|
|||
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.
|
||||
|
||||
#patreon_articles
|
||||
#keto
|
||||
#dietary_guidelines
|
||||
#nutrition
|
||||
|
|
@ -1,60 +0,0 @@
|
|||
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
|
||||
|
|
@ -1,34 +0,0 @@
|
|||
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)
|
||||
|
||||
#patreon_articles
|
||||
#disease
|
||||
#LDL
|
||||
#ApoB
|
||||
#proteoglycans
|
||||
#LDL_retention
|
||||
|
|
@ -1,51 +0,0 @@
|
|||
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/)
|
||||
|
||||
#patreon_articles
|
||||
#nutrition
|
||||
#chocolate
|
||||
#LDL
|
||||
#stearic_acid
|
||||
#polyphenols
|
||||
#metabolism
|
||||
|
|
@ -1,50 +0,0 @@
|
|||
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]]
|
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|
||||
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.
|
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|
||||
For this reason I conducted my own meta-analysis of cheese intake and CVD risk, just for fun.
|
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|
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![[Pasted image 20221123152812.png]]
|
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|
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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
|
||||
|
|
@ -1,77 +0,0 @@
|
|||
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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