KempyKolibri

It’s certainly possible that there are long term side effects from GLP-1 agonists, but we can only go with the data we have. The five year data (which definitely has limitations in terms of the kind of inferences we can draw from it) is suggesting around a 4x reduction in mortality at the 5 year mark in non-diabetics IIRC (https://pubmed.ncbi.nlm.nih.gov/39171569/).

The changes in behaviour are also really interesting. Even after cessation of the drug, it seems like many patients keep healthier eating patterns and while they do put on weight, they tend to settle on a lower weight than baseline before intervention.

So we should absolutely keep an eye on outcomes as time goes on, but so far the results are overwhelmingly positive. These drugs are saving lives and the new ones in the pipeline look significantly more effective. It’s an exciting time to be alive!

I would say that the evidence on red and processed meat and CVD and CRC is at least a “B”, so we’re meeting your goalposts here.

When we look at the totality of the evidence via meta analysis, we see effect sizes in the 10-20% range for IHD. If 20% change in one of the leading killers in the western world is “small” to you then fair enough, but I’d suspect that’s a fairly proprietary use of the word that wouldn’t accord with what most people mean when they use it.

I’m not sure what variables you think are uncontrolled in these studies, you’ll have to be specific about which uncontrolled variables you think are having an effect.

https://www.tandfonline.com/doi/full/10.1080/10408398.2021.1...

What are the criteria you believe are required to establish causal risk between an exposure and an outcome?

> The error bars suggest there is too much in-population variance to come up with useful general guidelines.

I’m not sure I’d agree there. What’s the argument for that?

Presumably the increased cardiovascular disease risk from animal protein in general, most evident in processed meat, then red meat, then other sources in order of effect size.

Not so sure about cancer risk outside of the colorectal cancer risk associated with processed meat and unprocessed red meat.

I actually think the consensus in the scientific field is fairly well established, but media reporting likes to have good guys and villains, so the message “good in some contexts, not so good in others” is quickly discarded.

Good overview from 4 years ago here, but nothing in it is outdated. All references in the description: https://youtu.be/G1NZNKn9DG8

The evidence that high levels of serum cholesterol are associated with negative health effects is overwhelming.

The relationship between dietary cholesterol and health is more nuanced and depends on context. When you take the context into account, the results of these studies all tend to concord with one another.

This just sounds like a semantic disagreement. I believe the evidence base presented in the paper is a pretty fair representation of the field, and justifies the authors’ statement:

> the totality of the evidence supports the recommendation to limit SFA intake to <10% TDE for the general healthy population

I would call this pretty good evidence. Perhaps you wouldn’t but, as I say, that’s probably just a semantic disagreement.

Maybe? Wondering whether they’re referring to the lipid hypothesis, diet heart hypothesis or, as you say, the contribution of dietary cholesterol to serum cholesterol.

I wouldn’t consider any of those to be myths, FWIW.

It’s not the cholesterol itself that’s “good” or “bad”, but there are lipoproteins in the body that transport the cholesterol that have differing effects on CVD risk.

The evidence would suggest that dietary cholesterol does increase CVD risk, but the impact really tails off quickly. So if you have little to no dietary cholesterol, consuming eggs will likely raise your blood lipids. If you already have some dietary cholesterol, the impact on blood lipids will likely be small. However, I think there are genetic differences that can change the risk profile significantly.

I suspect that the main modifying effects of frying would be: 1. increasing saturated fat intake 2. increasing calorie intake

What’s “the cholesterol myth”?

We have pretty good evidence that increasing consumption of saturated fat increases risk of cardiovascular disease, so I’m not sure why we’d think frying eggs in lard and butter would be health promoting above frying them in a processed vegetable oil.

Agree that there are a lot of unknowns. Kevin Hall is carrying out some illuminating studies on the issue but, by his own admission, there’s simply not enough funding to do this at pace or scale.

I think we have some experimental evidence to suggest that at least some of the UPF associations are due to texture - those foods that you can basically inhale without chewing seem to drive higher caloric intake. We also have an incredibly strong signal of mass gain from sugar sweetened beverages which are also easy to consume with minimal effort.

I think it’s likely that cultural and economic factors play into this too. Japan has the same proliferation of UPFs, yet does not suffer the same obesity effects as the West does. There are probably a number of things that play into this: Japan has an incredible children’s food education policy, and they presumably have a different culture around food (many western cultures emphasise a “finish your plate or you’re ungrateful” approach).

I also have an intuition that the rise of two income households raising children is a factor in this. It’s a lot to ask of a couple that they both hold down full time jobs while cooking the kind of meals that used to be the domain of a stay-at-home parent.

Really interesting area to think about in terms of research and policies, but as you say we just don’t have strong evidence at the moment.

In the meantime it’s great that GLP-1 agonists are available to reduce the damage done, but it’s a shame we have to resort to such things in the first place.

There’s some evidence of a reduction of intima-media thickness of both common carotid arteries through a… less intense diet.

https://www.ahajournals.org/doi/full/10.1161/STROKEAHA.120.0...

Yes, high SFA diets are associated with increased risk of CVD via atherosclerosis as a result of the increase in ApoB concentration in the blood (response to retention hypothesis).

This review paper is a really good overview of the model, and it's actually pretty approachable: https://academic.oup.com/eurheartj/article/41/24/2313/573522...

Anecdotal, but if you follow carnivore diet groups on Facebook/IG etc you'll frequently see posts from people with TC over 500mg/dl. For example, the carnivorecringe IG account posted someone's labs in December who had a TC of 669 and an LDL of 558.

It's quite possible that it's a combination of diet and genetics, but people can quite easily get to incredibly harmful LDL levels with diet alone.

Edit: here's a case study of someone getting to TC of 488.7mg/dL. I think you'll struggle to get higher quality data than case studies because these kinds of diets are (thankfully) fairly uncommon and no ethics board is going to sign off on an intervention study that's likely to raise blood lipids by this kind of level.

https://academic.oup.com/jes/article/5/Supplement_1/A37/6240...

I think there are some concerns around PFAS, for example: https://www.mdpi.com/1660-4601/14/7/691

Not really across the research but my suspicion would be that if there are issues associated with non-stick, it’s likely to be PFAS driven.

There was a good discussion about the evidence on PFAS that I watched a while back, but I cannot find it for the life of me, sorry.

> I am interested in the things you've said and linked, and my opinions have changed, but I think I'm well past what I am able to follow or interested to continue.

Ok, that's unfortunate but obviously your prerogative! I will try to post some more lay-friendly links in this response that may convey my points more straightforwardly.

> if the CAC score measures something is it always definitely plaque buildup? Because then repeated CAC scores have the potential to be good for telling if plaque buildup is changing over time in response to dietary changes in people with non-zero scores and CAD.

No, it can measure plaque density. Additionally, since calcified plaques are more stable than soft plaques, it can actually go up while risk goes down. We see this occur on some statin regimes, where we have boatloads of data showing statins reduce risk, yet we can see CAC scores go up as soft plaque is stabilised into calcified plaque.

I'm not saying CAC is without its merits, but you are stretching credulity beyond breaking point to suggest that because one cardiologist claims that reducing dietary fats doesn't show a reduction in CAC scores, it therefore disproves the lipid hypothesis. CAC has too many caveats to use it to make such bold inferences, even if we get to the wild epistemic standards required to think one cardiologist's claims are sufficient to overturn decades of well-conducted research. Additionally, as I've stated elsewhere, it still wouldn't be evidence that arterial wall damage or inability to repair damage is required for ASCVD, which, let's remember, is the reason we're even talking about this in the first place.

There's quite an interesting discussion about the pros and cons of the CAC here. Suffice to say, it's not suitable to stand up the kind of arguments you're making: https://www.youtube.com/watch?v=gxIeRUbHauw

> Because when someone you don't like cites multiple meta-analyses of RCTs you handwave it away with a Twitter thread where he "runs away from an argument chef's kiss"

No, that's not why I dismiss Mason's claims. I dismiss Mason's claims because he says "this meta analysis says this" and then when you look at the MA it says nothing of the sort. It's false to claim that I'm handwaving away the evidence itself.

> I know of Ben Goldacre's Bad Science, I see plenty of HN links about the reproducibility crises in science about the ways of p-hacking and manipulating data, about the broken incentives to publish and get funding, about the complexities of statistical analysis, things I can't argue through. Medical experts are incentivised to push treatments, academic experts are incentivised to push dodgy results, it's not easy for people who like and care about this stuff to say what's "high quality data" or isn't, let alone me. One can't handwave away measuring the amount of plaque buildup in the heart and say "that's not a measure of the amount of plaque buildup in the heart" as easily. If people change X and their heart health measurably improves, and X isn't reducing dietary fat, that should mean something.

I think it's really worth taking a second to think about what you're saying here. Some points of order first:

- The reproducibility crisis is about some fields of science re-running individual studies and finding that when they do so, they cannot reproduce the original findings.

- p-hacking is about altering the methodology of a study post-hoc to generate statistically significant findings when such findings were not present under the original methodology.

- the objection of the complexities of statistical analyses, I presume, is an objection based on the fact that when using statistical analyses to try to account for confounders and systematic bias, sometimes these analyses are poorly conducted and thus fail to mitigate these biases.

- "Medical experts are incentivised to push treatments" is presumably an objection that individuals publishing papers may have an implicit or explicit bias that causes them to over or understate the significance of a given finding, or record data incorrectly.

So your argument appears to be: "Ok, so you've provided evidence that LDL is a risk for CVD based on over 200 prospective cohort studies (that is, the results have been successfully produced literally hundreds of times), mendelian randomisation studies, and randomised controlled trials including more than 2 million participants with over 20 million person-years of follow-up and over 150 000 cardiovascular events. However, I believe it's likely that if we were to re-run those studies again, we would not be able to reproduce those results.

“I'm also concerned that p-hacking and systematic bias is so consistently prevalent within all of these studies that it affects the summated findings so profoundly, and consistently in the same direction, that we cannot trust the findings to be accurate. Additionally, the individuals conducting these studies are all incentivised to push treatments and therefore we should believe it to be more likely than not, without any evidence to actually demonstrate this, that these individuals are biasing the results because of these incentives.

“It's not easy for lay people like me to ascertain whether these data from the top of the evidence hierarchy (that is, the evidence least likely to be affected by bias) are high quality, so we have to find a source of evidence that is less likely to be affected by such bias. To achieve this, I propose that we throw all the above data out, and instead trust the claims of a single cardiologist, who's written a blog post on his website about how serum cholesterol is irrelevant when it comes to cardiovascular disease risk.

“After all, p-hacking can't take place when the evidence is so poor that there are no p-values, calculations of statistical significance, or even recorded data from which one could calculate p-values.

“After all, you can't make errors in your statistical analyses if you don't perform any statistical analyses.

“After all, your attempts to control for bias can't go wrong if you don't attempt to control for bias.

“After all, 'One can't handwave away measuring the amount of plaque buildup in the heart and say "that's not a measure of the amount of plaque buildup in the heart" as easily. If people change X and their heart health measurably improves, and X isn't reducing dietary fat, that should mean something,' despite the fact that there are studies that do measure plaque buildup in the heart and show that it is affected by serum cholesterol. I believe that we can handwave it away when it's published in a peer reviewed journal, but we can't do so when it's a blog post on a cardiologist's website. This is the most reliable way to make sound scientific inferences.”

I don't even understand how one can reach these conclusions. I've tried my absolute best to interpret what you've said generously, but there's only so much I can do given material like this.

This whole line of reasoning is also far closer to what you’re accusing me of - instead of discussing what the data show, we should just “trust the experts”. We can’t analyse Dr Davis’ data because he doesn’t even provide any, but we should just assume he’s telling the truth because he’s a cardiologist and therefore so well paid that he has no motivation to be wrong. We should ignore the evidence I’ve provided because it’s harder for laypeople to understand than this supposed expert just saying “trust me, I ran some CAC tests”.

> presumably somewhere is a researcher or practitioner who has done many CAC measurements and has studied whether cutting dietary fat changes the score or not, at this point I am not going to look for it.

I've already provided you even better evidence than that: a pooled analysis of studies where SFA is replaced with PUFA and cardiovascular events and coronary deaths are reduced. You don't need to go looking, I gave it to you: https://pubmed.ncbi.nlm.nih.gov/19211817/. If you want a more consumable version, here's an excellent podcast on it (all their stuff is good, you should see if there's anything else there of interest to you: https://sigmanutrition.com/episode481/).

It's a shame, but not entirely surprising that you no longer desire to continue the discussion. Fundamentally, I think you will always run into issues until you re-assess your underlying epistemic framework when it comes to assessing evidence. Until you do so, reading studies will be largely pointless as you have no reliable tools to interpret those studies. You're running before you can walk.

If you're interested, the Cut Through Nutrition podcast is quite a nice primer on how to think about nutrition science research, I'd highly recommend working through the episodes. Once you've internalised the concepts, it becomes a lot easier to see how quacks like Mason and Davis are operating, even without a great deal of domain-specific knowledge. Podcast is here: https://podcasts.apple.com/gb/podcast/cut-through-nutrition/...

Have a good week!

Genuinely unsure how this is relevant in any way.

I probably should never have entertained the Dr Davis derail. The whole bringing up of this character was your attempt to answer my question "What’s the evidence that [atherosclerosis] only takes place in individuals with arterial wall injury or without the ability to repair damage?"

Your response was "Some people live a long time with high(er) fat diets and no heart disease". But this is not evidence that atherosclerosis only takes place in individuals with arterial wall injury or without the ability to repair damage. That could equally be evidence that some people are genetically less predisposed to arterial retention, regardless of arterial wall injury, for example. There are plenty of hypotheses that negate your proposed one that are equally likely on the evidence you've provided. So this whole thread is just a tangent that doesn't engage with the core question. That said, here goes:

My point on CAC was that your entire argument hinges on being able to look at a CAC score and say "this score is a reliable indicator of whether a person has coronary artery disease". But if you're under 40 and actually have CAD, there's a 58% chance that when you get your test results back, it will show 0 CAC (even though you have CAD!). So demonstrably, CAC is a poor proxy for CAD, and so a lynchpin proposition in your argument is clearly false. Whether the numbers look different when read a different way is irrelevant. The above is true, and demonstrates how CAC is not a reliable metric.

> I don't think Dr Davis has said serum cholesterol is irrelevant, the statement I linked is that dietary fat removal doesn't stop CAC score increasing.

Literally from the article you linked: "Can you look at your cholesterol and say “Oh, my cholesterol is 240. I must have heart disease.”? No, of course not — cholesterol is virtually worthless when it comes to predicting heart disease"

So he says exactly that, unless you're willing to quibble over a semantic difference between "virtually worthless" and "irrelevant".

> Why we should believe him is that he's got a feedback loop with a measuring machine

It's not just "why should we believe him", it's "why should we believe him over meta-analyses of RCTs, and other high quality data?" Look at where "expert opinion" and "case reports" (which is the evidence you're citing, if we're being generous) sits relative to the MAs of RCTs that I'm bringing to the table on the hierarchy of evidence (https://en.wikipedia.org/wiki/Hierarchy_of_evidence). It's not clear to me why you're throwing out robust evidence with comparatively low risk of systematic bias and relying on bottom-tier evidence instead. Can you please explain to me why this is a superior epistemic framework?

> He's a quack selling a book?

Yes. I'd take a quack to be anyone wearing the coat of science while violating the standards of modern science. Whether or not he stands to gain (or cares about) the money his book makes isn't relevant to that claim, it's based entirely on the nature of what he has to say/publish.

Indeed, going back to the previous point, dismissing the enormous body of high quality evidence showing LDL cholesterol is a causal agent in atherosclerosis by referring to serum cholesterol measurement as "virtually worthless" merely because of his own personal experience, with the plethora of biases that entails, is textbook quackery. The fact that he's published a pop science book that blames many of the ills of the world on wheat with no evidence to back up such an assertion is just the cherry on top.

So I don't need to speculate why he's a quack, and his salary doesn't alter my point. Maybe he does it because being a number one bestseller satisfies his ego in a way nothing else can. Maybe having that accolade means he can charge more for his cardiology services, so there's an indirect financial benefit. Maybe he genuinely believes wheat is the devil's food? I don't really care, my point is that his output suggests he's not a sound practitioner of the scientific method.

Your entire argument here seems to boil down to "there's this guy who sees patients and he says they're not leaving his practice and they're getting better, how would he have patients if everything he says about heart disease wasn't true?" This is wild, the kind of arguments I see from homeopathy advocates. We should always aim for the evidence base most likely to be free from bias. That is not one clinician's account of how they do things.

On no, not the DiNicolantonio paper. I really need a copy & paste thing on hand to go over all the wild logical leaps this paper makes but alas, I don't. I'm going to try to keep it brief by just focusing on what's relevant to the discussion.

> That is condeming oxidised serum fats, not oxidised dietary fats, but it appears to be condemning "omega-6-rich vegetable oils" in the diet because they are more likely to oxidise in the body(?)

We can just bypass that entire speculation, because to get there we've already made a logical leap, namely assuming that oxLDL is even something we should care about. All the evidence suggests that the oxidation of LDL almost entirely occurs within the arterial wall (https://pmc.ncbi.nlm.nih.gov/articles/PMC2924812/). When LDL is retained, oxidation is practically inevitable. The important thing is number of ApoB tagged particles.

So what would we expect to see in the real world if this hypothesis (that oxLDL is not an independent risk factor) was the case? Well, presumably if we adjusted oxLDL for ApoB, we would see the risk association disappear, since all oxLDL would be doing is just proxying for "amount of LDL", and the oxidation itself is not driving the risk. What do we actually see when we do this? When we perform a mutual adjustment of oxLDL and ApoB, and the association of risk from oxLDL disappears: https://pubmed.ncbi.nlm.nih.gov/16949489/ So even if the speculation that PUFAs increase oxLDL count were valid (and I'm not granting it is), it would appear to be irrelevant as far as risk of CVD goes.

> your position boils down to "Science is only for experts, and only the experts I choose, not those they believe the wrong things so they're quacks, trust me" which is .. disagreeable.

That's not my position at all. Please try to employ the principle of charity when interpreting my position, or this is going to be very slow going, and likely unproductive.

My point is that when you look at mechanisms, you're peering at one tiny part of a process of thousands (or more) moving parts. Just stringing together a bunch of those mechanisms into a narrative doesn't provide any kind of sound basis for making an inference about human health outcomes because it ignores every other mechanism at play. For example: mechanistically, exercise induces oxidative stress. I could do as you did above and string it together into a theory about how exercise is bad for your health, but I hope you'd agree that I'd be making a false inference.

My point is not that we then throw our hands up and say "I guess I'll leave science to the experts". I never said that. I said we have to base our inferences off the summation of all the mechanisms at play.

How do we do that? By looking at human outcome data (prospective cohort studies, mendelian randomisation, RCTs). Why don't we think exercise is unhealthy, despite the oxidative stress mechanism? Because we have human outcome data that shows the benefits of exercise. That is, we look at the exposure we're interested in (exercise) and the outcome we actually care about (say, mortality, or cardiovascular disease). Do people who exercise more have lower mortality rates when potential confounders are accounted for? If so, we have good reason to believe exercise is beneficial. This is how we should look at replacing SFA with PUFA. When we do that, what happens to the things we actually care about (heart disease, mortality etc)? Overwhelmingly, we improve outcomes. Why should we prize mechanisms above human health outcomes? It doesn't make sense to me.

> When you say fat quality, do you mean PUFA vs SFA?

Yes.

> Let's be clear that I'm lost in the details of SFA, PUFA, linoleics

The position I take is: - There seems to be a point, around 10% total energy from saturated fats, where risk increases significantly. Either side of that, changes to SFA still make a difference, but not to the same degree. - When it comes to reducing SFA, replacement is important. Replacing SFA with PUFA seems to be the most beneficial approach.

In prospective cohort studies, each 5%E from SFA replaced with PUFA resulted in a 13% lower risk of CVD events, and a 26% reduction in coronary deaths. In RCTs, we see a 21% reduction in CVD events when substituting PUFA in for SFA (https://www.cochranelibrary.com/cdsr/doi/10.1002/14651858.CD...). In general the reduction in risk seems to come out at about 20-30% depending on study characteristics. Considering CVD is one of the top killers in the Western world, I think that's something worth paying attention to.

My understanding is that insulin resistance leads to increase DNL in the liver, so you end up with a greater production rate of LDL particles, but each one contains less cholesterol. I’m not woke on the mechanisms, but there’s a review paper here if you’re interested: https://www.sciencedirect.com/science/article/abs/pii/S10501...

Re: the twitter conversation: the diet heart hypothesis is specifically about replacing saturated fat with polyunsaturated fat. If you just reduce overall fat, you may even be making that P:S ratio worse. In the case of the WHI it means that the study is essentially null by default on that issue.

Dietary cholesterol is an interesting one - basically there is a significant effect of dietary cholesterol on serum cholesterol, but only when you go from very low to low levels. After that, the effect tails off dramatically. So in the general population you might not expect a 30% reduction to make a significant difference.

Additionally, you have to consider the overall picture. Maybe the reduction in dietary cholesterol did have a small beneficial effect, but the fact that the intervention group ended up with lower PUFA consumption than the control group meant this reduction was overshadowed by that effect.

There’s no evidence that oxidised fats in unsaturated fats are a cause for concern for health. Aside from that I don’t think stringing together a bunch of mechanisms and speculating about them is a particularly useful way to carry out science.

What we care about is actual outcomes from actual interventions. So yes, I agree that in those with metabolic disease and insulin resistance, we should address this issue. The evidence seems to suggest this is best done by losing weight. If there’s a certain dietary pattern that helps someone do that, great. If it’s a GLP-1 agonist, go for it. Whatever works.

But we also know that fat quality affects CVD risk too, and by a decent amount. So within whatever dietary pattern one settles on, replacing SFA with PUFA would also be a good idea. We can do both!

Depends on your age. In this study, in those under 40 with obstructive coronary artery disease, 58% had a CAC of zero. So it can be a dreadful risk marker in some scenarios: https://jamanetwork.com/journals/jamacardiology/fullarticle/...

Your Dr Davis just appears to be one person saying something is the case, without providing any evidence for it. I don’t see why we should believe his claims that serum cholesterol is irrelevant over the incredibly robust evidence I’ve brought to the table.

I agree that the two things don’t add up, but why wouldn’t we then just favour the higher quality evidence? Seems like Davis is a quack with historical form for just making things up without any evidence in order to sell a product: https://www.healthyeating.org/blog/detail/rdn-s-book-review-...

Haha. You may be built like Schwarzenegger, but you’ll always be a soyboy (</sarcasm>). I think people find veganism threatening so like to mock those that adhere to those principles instead of performing some soul searching.

> 3 kids in kindergarten and school

I see you have chosen the path of perpetual illness and insomnia.

As I said, happy to move onto AA once we’ve closed off the n3:n6 ratio thing. So do you have any evidence that the ratio is an issue in humans, or do you concede there’s no such evidence currently?

Hot damn, you’re totally on the money. Fair play to you. An island of sanity in a sea of “but we’ve eaten fatty meat for thousands of years.”

Based. I know you might just be taking the agnostic position for the sake of the conversation, but the evidence overwhelmingly suggests 6 servings of carbs would massively improve your ACM risk: https://www.sciencedirect.com/science/article/pii/S000291652...

That could be 3 servings of whole grains and 3 servings of fruit and veg. Sounds good, though I’d go further and suggest more fruit & veg if possible.

It sounds like you find speculation based on anecdotes more compelling than evidence from higher up the evidence hierarchy. That’s obviously your preference and you’re welcome to it.

When I’m discussing an issue and my interlocutor ends up having to bite a bullet like “I think MMR vaccines might contribute to autism based on speculation and the reports of people on the internet”, then I’m happy to take my hands off the wheel - it’s now clear their standards of evidence are very low.

Since you’ve openly admitting to it then I’ve achieved what I came to do:

1. See if I’m wrong in my view (it doesn’t seem like I am)

2. Ensure that anyone reading can see that in order to believe seed oils are harmful, one has to have a completely wild epistemic framework. You’ve admitted you think MMR vaccines might contribute to the development of autism based on a completely evidence-free view that such vaccines might be “the straw that breaks the camels back.”

I think this conversation has probably run its course - you believe things based on what I would consider anti-scientific reasoning, as you’re welcome to do. I don’t think wild speculation is a useful tool for making inferences about the world. We’re unlikely to bring each other round to our own views on this, I suspect.

I read those papers and I don’t see any compelling evidence anywhere in there that n6s are toxic. The first one is just discussing burn patients and yes, we consume more n6s than we used to. But that’s not evidence of toxicity.

The COVID one is disappointing. I was expecting a longitudinal study where they perhaps hadn’t adjusted for confounding variables like obesity, etc. Unfortunately, the reality is far worse.

The only human outcome data they seem to have is a cross-sectional analysis where (as far as I can tell, correct me if I’m wrong) they just looked at gross consumption at a national level of different FA types, then saw if there was an association with COVID mortality. This is an insane way to test the hypothesis “consumption of n6 increases Covid mortality.” It just isn’t evidence at all.

I would take evidence to be something that is expected on a given hypothesis and not the negation of that hypothesis. For example, “we see the sun rise in the sky” is not evidence supporting the hypothesis “the sun orbits the earth”, because it would also be expected on the negation of that hypothesis, for example under another hypothesis: “the earth orbits the sun”.

In this case, we can think of any number of hypotheses that negate the hypothesis “n6 consumption increases covid mortality”. For example, “n6 consumption proxies for junk food consumption and population obesity, which increases COVID mortality.” The outcomes of the study are equally expected on both hypotheses. The outcomes they’re seeing could be explained by this alternate hypothesis, for all we know.

Fundamentally, though, there’s actually a much bigger issue here - the data are just cross-sectional. We have no idea if the increased COVID mortality is even taking place in the people that consumed more UFA - the data just don’t tell us!

This leads to an awkward bullet-bite one has to make in order to make a causal inference from data like these: you would also have to affirm that smoking increases lifespan. Unadjusted cross-sectional data shows that countries with greater cigarette consumption have longer lifespan (http://web.archive.org/web/20220325085356/http://www.thefunc...). Now, clearly this is not because of the beneficial effects of smoking. Perhaps it’s because more cigarette consumption occurs in those countries that are wealthier. The point is, cross sectional data is unsuitable for making causal inferences like this.

The rest is just mechanistic speculation and animal studies, not something that can be extrapolated to human outcomes (more about why later). So the study doesn’t actually show any negative health outcomes in humans from n6 consumption.

The next study is literally a study of cheetahs. Might be of interest if you’re a cheetah, or deciding on your pet cheetah’s diet. But we’re talking about human health here.

And then the final paper suffers from the issue of earlier one - trying to make a causal inference based on cross-sectional data. We have zero idea if the individuals suffering from SAP are even the ones consuming more n6s. Again, if we are to find this convincing evidence of n6 toxicity then we also have to grant that cigarette consumption increases lifespan.

A commonality in these studies is that they try to back up the cross sectional data with animal modelling and in vitro studies, but we have to bear in mind that the best data we have on translation of animal studies to human outcomes suggests the success rate is atrocious. The confidence interval for toxicity studies in animal studies translating to human outcomes includes .5, so you may well be better off tossing a coin than you are relying on animal studies to make inferences about human health outcomes: https://translational-medicine.biomedcentral.com/articles/10...

To sum up, this seems to be a collection of data from the lower end of the evidence hierarchy, none of which is even in the category of data suitable to provide information about what is healthful or harmful to humans. I don’t see why we would find this convincing evidence of n6 toxicity on its own, even before we get into all the much higher quality evidence pointing to benefits from n6 consumption.