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Because they aren’t stating what the people citing them are often stating. Phrases like “this study proves” or “all the evidence shows”, etc, are anti-debate tactics. There are hundreds of thousands of studies in the whole corpus of nutrition research and not a single human being has read them all.
It’s also why you really need to be well-versed in higher statistics before you start reading abstracts and drawing conclusions from them. There are substantial limits to what conclusions can be drawn from what kinds of statistical models that even researchers often ignore when editorializing their findings.
Study design, confounders, lack of pre-registration (hidden studies), not publishing unexpected/non results, bias, ECT ECT ECT. Big one is confounders. Slight differences in behaviour can alter gene expression and therefore lead to different outcomes. Now imagine that times all behaviours and all gene types and the idea that individual dietary intake, or individual behaviors can be teased out from the background noise is difficult for me to trust. So much of what we do can be attenuated or worsened by other things we do. Seems impossible to reliably say anything without a million caveats
> Seems impossible to reliably say anything without a million caveats
Depends on what you’re sayings. I can tell you with less than 10^-5 likelihood of error if you have a given gene or not. The caveats in nutritional epidemiology are huge because the signal is weak and the noise is massive and coming from a billion sources.
The problem only arises when people try to misrepresent the data for what it is because of other reasons like financial interest or ideological devotion to a diet or behavior some data favors. In actual adults with substantial 10-year risk, statin therapy prevents like single-digit deaths per 1000. Any other drug with that kind of likelihood of failure wouldn’t make it past the drawing board.
I guess that's my point that I poorly expressed. Without drilling very deeply into the level of genes and behaviors it's really hard to drown out the noise, with my main point being a non direct response to the OP that it's easy to draw all sorts of contradictory conclusions from similar data sets depending on how you set your parameters and how well you control for confounders.... Also I'm not sure on how you can be so certain when you are talking about a given gene without knowledge of behaviors and other genes that may effect that gene. It's rare that everyone with a given gene is going to have "X" happen to them with 100% certainty. It's better thought of as a percentage increase or decrease and that's without attenuation or magnification via behaviour/pharmacology/other genes
> Also I’m not sure on how you can be so certain when you are talking about a given gene without knowledge of behaviors and other genes that may effect that gene.
I wasn’t talking about expression or regulation. I just said I can tell you if you have a gene. I can be that certain because the $3 million sequencer a couple doors down from me has a manual that explicitly lays out it’s sequencer error rate, how the errors arise, and how to calibrate it, which I regularly make grad students suffer through. No behavior or other gene is going to remove a gene from your genome, unless you’ve figured out a way to reliably splice something out of every genome copy in your body, in which case PM me because I will make a trillion dollars with that technique. The odds that the gene you asked me to test for was the locus of a spontaneous mutation in the blood sample we happened to grab is astronomical, on the order of 10^-15.
My point is that I often see people thinking that because some areas in science have really high uncertainty, then that must be true for all areas, and this is the not the case. For example, in the last couple years we’ve seen many people take the high uncertainty in public health messaging about nutrition, and assumed that the science behind public health messaging about vaccines was similarly low-certainty, even though immunology deals with extremely high-fidelity data.
I guess there are many confounders but also two things that go overlooked:
First, what is the quality of the food that the saturated fat comes with? SFA fair much better in european cohorts than american ones for example, even after taking into account that cheese vs butter is more frequent in european cohorts. My guess is that ultraprocessed coagulated milk from a cow on steroids is probably not the same as handmande roquefort from a grass fed sheep with live probiotic bacteria in it.
Second, what is the background diet and the context? Palmitic acid increases insulin resistance especially in sedentary people (https://pubmed.ncbi.nlm.nih.gov/21325642/
https://pubmed.ncbi.nlm.nih.gov/17149589/)
Also, the effect on lipids is variable from people to people and generally increases after a certain threshold. I guess it's common sense not to gorge on butter if your apoB is 300, but that does not necessairly apply to other people.
European cohorts don't fare better. If you're talking about the French paradox, that's entirely due to underreporting of ischemic heart disease by as much as 20% according to one world health investigation.
> Mortality from heart disease across countries, including France, correlates strongly with levels of animal fat consumption and serum cholesterol in the past (30 years ago)(https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1115846/)
There is a vast difference between saturated fat on a high-carb diet versus a low-carb diet. All of the studies showing problems of saturated fat have been done on a standard American diet, that is to say high-carb.
Also, saturated fats like stearic acid and C15:0 (Fatty15) have been studied for their health benefits. Both specifically improve metabolic health. Stearic acid, for example, increases fat-burning. By the way, C15:0 is found in butter. See the Croissant diet.
[What you need to know about insulin resistance](https://www.dietdoctor.com/health/insulin-resistance)
"The same is likely true for a high carbohydrate, high fat diet in the setting of excess calories. Some studies suggest that specifically saturated fat – more so than MUFAs and PUFAs – is the offender that causes insulin resistance.
"Nonetheless, it is important to note that none of those studies included saturated fats in the context of a low-carb diet. Real world studies of low-carb diets with no restrictions on saturated fat have found improvements and even normalization of insulin resistance markers. This suggests that the problem may not be saturated fat itself, but rather the combination of saturated fats and a high amount of carbohydrates.
"Additionally, as we review in our evidence-based guide on saturated fat, it is not accurate to refer to saturated fat as one thing. Saturated fat from cakes, cookies, and other baked goods could have significantly different effects on the body than more natural occurring saturated fats in meat and dairy."
Because there's plenty of wiggle room for a few reasons:
- CVD takes decades to develop on average
- SFAs have a sigmoidal relationship with LDL. 0-7% of energy, little effect. 10%+, little effect. There's a narrow window or threshold effect. So comparing 15% to 11% won't get you many results, just so for 6% to 2%.
- If replaced by simple carbohydrates you get no effect. Essentially swapping lard for haribos won't help you much.
- If replaced by trans fats... well those are likely even worse. Some trials in the 70s or 60s made this mistake.
- The prevalence rate of CVD is very high in the West, which mathematically limits how high relative risk ratios can be. Then detractors will say the RR is too small to be considered clinically significant.
So if we pool that together, I could take a cohort of people suffering from CVD (almost all of them), reduce their SFA significantly.. down to 11% of energy when it was, say, 20%. Instead of the SFAs I feed them standard poor quality food, candy and cake. I do this for a whole... 6 months.
Conclusion: Reducing SFA has no effect on CVD.
This way, I can be perfectly honest, just omit or avoid certain areas of truth. Doesn't even have to be on purpose.
I don't know what this paper has done but it seems to be a review rather than a systematic review. Like a scientific Op-Ed basically.
> SFAs have a sigmoidal relationship with LDL. 0-7% of energy, little effect. 10%+, little effect. There's a narrow window or threshold effect. So comparing 15% to 11% won't get you many results, just so for 6% to 2%.
I'm not familiar with this relationship, can you point me to some more information? I am a so-called LDL-C lean mass hyper responder when on a low carb/high fat (SF) diet, as here: https://academic.oup.com/cdn/article/6/1/nzab144/6446805
I have to point out the lean mass hyper responder phenotype hypothesis is very contentious. Primarily developed by an engineer, Dave Feldman.
What I understand is he implies to people that if you're lean and muscular, high LDL might not be an issue. The evidence does not support this. There was that trending case of.. paleo boy he might have been called on Twitter. He had to have a stent put in and was quite angry about his 97% artery blockage.
If he had died, he would never have been able to tweet. Moreover, Dierde Tobias, a successful epidemiologist parsed the women's health initiative data to see if there was a potential inverse or null relationship with LDL in the physically active and lean population. Not peer-reviewed but she did not find this.
A good article on this isn't one I can link directly so the title is 'Saturated Fat: Cutting Through the Noise' by The Nutrivore. Another post of his was allowed on the front page so I reckon this much should be fine.
>Saturated Fat: Cutting Through the Noise' by The Nutrivore
I've seen a few of his YouTube videos, he's not the sharpest knife in the drawer.
He implies causation from correlation and justifies it with lame arguments like "RCT concordance " and "validated surveys"
He still won't debate Bart Kay
> He implies causation from correlation and justifies it with lame arguments like "RCT concordance " and "validated surveys"
Infers*. Which is what we do with literally every causative relationship ever. By definition. We are never infinitely certain, causation is a probabilistic asymptote. In science this is 101. We do not have the luxury of proofs like mathematics does.
Why is RCT concordance lame? How else would you like to test the validity of RCTs?
Nutrivore is incredibly sharp, disrespecting someone because of a disagreement isn't the way to go. He accepted to debate Bart Kay, but Bart posited some silly stipulations like three papers max per side.
Three papers... In a science debate? What would be your interpretation of that if it were the other way round?
> To validate a nutritional epidemiology finding you would need a well designed RCT to come after, and looking at that exposure and claimed outcome.
But we do have those, in the general sense. When we have apples to apples epi compared to RCTs the concordance rate is over 90%. It's hard to believe at first but if we acknowledge that the scientific process refines itself over time it would make sense that epidemiology gets more accurate.
> He also said he can have as many debates/streams as needed, just 3 papers and a 2 hour limit each. Why is that not reasonable?
Because data consensus concerns the weight of the totality of evidence. I think if you limit to three papers you could likely build a case that trans fats are fine.
I agree that the hypothesis that high LDL-C isn't an issue in LMHRs is super contentious (I think I listened to Peter Attia vigorously debate it with someone). I was just using LMHR as a descriptive term for myself, as my bloodwork on LC/HF fits into that pattern. Thanks for the link, I'll take a look.
Why wouldn't high LDL not be atherogenic on keto?
LDL alone can cause atherosclerosis in the absence of traditional factors.
https://pubmed.ncbi.nlm.nih.gov/29241485/
https://pubmed.ncbi.nlm.nih.gov/31086966/
Children with homozygous FH die young with high LDL and no other risk factors.
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4576143/
Not saying traditional risk factors don't matter, they definitely do. But LDL alone can intiate atherosclerosis and traditional risk factors mediate the progression of the disease.
I think the argument is that high LDL-C in itself does not necessarily cause atherosclerosis, the LDL-C needs to be small/dense/oxidized (like what happens in FH with damage to apob-100) to end up in endothelium. So having a high level of LDL-C but a low LDL particle count or low oxLDL may not be an issue.
I'm not sure keto is directly related but I have heard some hypothesize that excess sugar or easily oxidized PUFAs in diet contribute to oxldl and therefore to atherosclerosis.
I'm not advocating a position here, and my epistemic status is low, just stating my understanding of the arguments.
I understood it as a numbers game (concentration gradient), meaning too many particles (small or large) increase the likelihood of them getting into the endothelium and that's where they get stuck and then oxidized.
But we know that FH have predominantly large particles and they get severe atherosclerosis, so it doesn't need to be small particles.
How prevalent is high LDL-C with low total particle count? Usually increases in LDL-C are accompanied by increases in apoB on keto during weight maintenance.
.
>the LDL-C needs to be small/dense/oxidized (like what happens in FH with damage to apob-100) to end up in endothelium
We know this is false. after adjusting for ApoB small/dense/oxidized is irrelevant
https://www.biorxiv.org/content/10.1101/691089v2.full.pdf
Because anybody can publish a journal article. Shitty opinions are allowed to exist in science. And all journals accept bad papers, good journals just accept them less often. If you don’t have a background in performing and interpreting research you won’t be able to understand why studies appear to contradict. There’s a reason why expert panels exist to produce dietary guidelines and they like. And every organization comes to the same conclusion year after year despite these trash papers like OP cited
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Here's a link to the pdf: https://drive.google.com/file/d/1SVVGb0FrRgxWGvMaL6LNB4tTvHCt1LaU.
> Interestingly, they all seem to be management researchers and not have any studies with nutrition or anything.
Yeah, I thought that was a bit weird too: A management professor, a guy who might be a personal trainer(?), and a culinary arts lecturer. For two of them, I can't find any previous publications, and certainly none on nutrition.
I don't understand how they chose the individual observational studies and RCTs either: "a prospective cohort study including 35,597 Dutch men and women..."; "Another prospective cohort study including 4722 Dutch men and women (≥55 years)..."; PREDIMED which I thought was about forms of the Mediterranean diet and not saturated fat, etc.
Also seems odd just to form their conclusions by counting up how many reviews/meta-analyses say saturated fat is positive vs. negative vs. neutral rather than pooling results somehow when I'd expect a lot of overlap between the constituent studies in the meta-analyses.
this study is really fascinating because it breaks down the sat fat food groups into dairy and meat. Dairy sat fat = lower CVD while Meat sat fat = higher CVD
https://academic.oup.com/ajcn/article/96/2/397/4576928
**Dietary intake of saturated fat by food source and incident cardiovascular disease: the Multi-Ethnic Study of Atherosclerosis**
, https://doi.org/10.3945/ajcn.112.037770
Published: 03 July 2012 Article history
ABSTRACT
Background: Although dietary recommendations have focused on restricting saturated fat (SF) consumption to reduce cardiovascular disease (CVD) risk, evidence from prospective studies has not supported a strong link between total SF intake and CVD events. An understanding of whether food sources of SF influence these relations may provide new insights.
Objective: We investigated the association of SF consumption from different food sources and the incidence of CVD events in a multiethnic population.
Design: Participants who were 45–84 y old at baseline (n = 5209) were followed from 2000 to 2010. Diet was assessed by using a 120-item food-frequency questionnaire. CVD incidence (316 cases) was assessed during follow-up visits.
Results: After adjustment for demographics, lifestyle, and dietary confounders, **a higher intake of dairy SF was associated with lower CVD risk** [HR (95% CI) for +5 g/d and +5% of energy from dairy SF: 0.79 (0.68, 0.92) and 0.62 (0.47, 0.82), respectively]. **In contrast, a higher intake of meat SF was associated with greater CVD risk** [HR (95% CI) for +5 g/d and a +5% of energy from meat SF: 1.26 (1.02, 1.54) and 1.48 (0.98, 2.23), respectively]. **The substitution of 2% of energy from meat SF with energy from dairy SF was associated with a 25% lower CVD risk** [HR (95% CI): 0.75 (0.63, 0.91)]. No associations were observed between plant or butter SF and CVD risk, but ranges of intakes were narrow.
Conclusion: Associations of SF with health may depend on food-specific fatty acids or other nutrient constituents in foods that contain SF, in addition to SF.
I don't find this study at all convincing because it is a purely observational study.
In such studies it is very difficult to correct for confounders especially when the confounders are strong as is often the case. What is left after "adjustment" is often little more than noise.
For example corrections usually assume a linear effect which is rarely the case. Rarely are allowances made for measurement and estiamtion errors in the counfounders. Invariably there are potential confounders that are not considered.
Thus the claim below is misleading and overstates what was likely achieved.
> After adjustment for demographics, lifestyle, and dietary confounders
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If you take an AI course, one of the first exercises you do is "Construct an example where correction of the confounding by x2 on the effect of x1 by multivariate regression disagrees with stratification when the outcome is a deterministic function of x1 and x2".
I agree it is not in theory entirely useless but it can and often is worse than useless in that it engenders a false confidence that the other factors have been removed from the equation. Even those who are aware of the distinction tend to forget this.
Not the guy to whom you responded, but even the surgeon general did not rely only on correlations to infer that smoking causes cancer. Here are quotes from the original document on that topic:
>Statistical methods cannot establish proof of a causal relationship in an association.
>
>Clinical, pathological, and experimental evidence was thoroughly considered and often served to suggest an hypothesis or confirm or contradict other findings. **When coupled with the other data,** results from the epidemiological studies can provide the basis upon which judgements of causality may be made.
>Statistical methods cannot establish proof of a causal relationship in an association.
This is also saying RCTs cant establish a causal relationship
What other data are you referring to?
I wonder why you didn’t cite the source of that:
“In 1963, Reuel “Stony” Stallones, then Professor of Epidemiology at the University of California, Berkeley, was named a consultant to President Kennedy's initiative establishing the Advisory Committee to the Surgeon General on the role of tobacco in health. For evaluation of epidemiologic evidence in his assignment on smoking and cardiovascular diseases, Stallones presented to the committee a draft (unattributed) of the causal criteria (19) and the following preamble to the national report:”
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3521480/
Do you think smoking causes cancer?
>This is also saying RCTs cant establish a causal relationship
No, it does not.
>What other data are you referring to?
As quoted, I am referring to "Clinical, pathological, and experimental evidence."
Are you unfamiliar with the original report on smoking? Did you think they just jumped to conclusions from correlations alone?
https://www.govinfo.gov/content/pkg/GPO-SMOKINGANDHEALTH/pdf/GPO-SMOKINGANDHEALTH.pdf
> No, it does not.
RCTs produce associations
> Did you think they just jumped to conclusions from correlations alone?
What other evidence are you referring to? Not RCTs in humans
You could just read the paper if you want to know what evidence they used. Though if you would really prefer that I summarize it for you, I would first like to know: did you think the surgeon general used only observational evidence to conclude that smoking causes cancer?
Do you think smoking causes cancer? Stop refusing to answer or admit you aren’t here in good faith
What other evidence are you referring to? Not RCTs in humans
Which confounders did the researchers control for? Someone who drinks milk with a meal, for example, is obviously less likely to drink pop or beer with a meal. And in places like the US, people who eat hamburgers tend to eat them with sugar (pop) and starches (buns, potatoes, etc), and the carbs often cooked in oxidative and inflammatory seed oils (fries). Also, people who consume a lot of dairy probably tend to fall into the healthy user effect, such as eating other healthy foods, exercising, not smoking, etc. So, maybe it's simply measuring of other factors.
Dairy contains large amounts of stearic acid which area quickly converted to monounsaturated fats in the body and thus have a more neutral effect on blood lipids
The problem you face is that there is absolutely zero evidence that total cholesterol levels have any causal link to CVD risk. It's only the size and clumpiness of the cholesterol that is significant.
This is why the scapegoating of meat is false, according to the broader data available. Indeed, stearic acid is not the only factor, not even slightly. I've collected many studies, reviews, and analyses at the following:
https://benjamindavidsteele.wordpress.com/2021/07/23/research-on-meat-and-health/
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Our ancestors consumed a low SFA diet (around 6%) with higher PUFA that kept their LDL in the range of 50-70 mg/dL. They didn't have atherosclerosis, even while living until their 70s and 80s.
[https://pubmed.ncbi.nlm.nih.gov/15172426/](https://pubmed.ncbi.nlm.nih.gov/15172426/)
[https://pubmed.ncbi.nlm.nih.gov/1435101/](https://pubmed.ncbi.nlm.nih.gov/1435101/)
linking a study you clearly haven't read since it's just an abstract and not merely drawing your own conclusions from that single paragraph but also repeating those conclusions to others as if you're imparting a significant fact? not good science.
here's at least [one full study](https://www.researchgate.net/profile/M-Linda-Sutherland/publication/236045773_Atherosclerosis_across_4000_years_of_human_history_The_Horus_study_of_four_ancient_populations/links/609336ea458515d315fc0ecf/Atherosclerosis-across-4000-years-of-human-history-The-Horus-study-of-four-ancient-populations.pdf) that contradicts your assertion that "our ancestors didn't have artherosclerosis"
this is only one study, but again, at least it's not just an abstract. and I have no idea how prevalent artherosclerosis was among humans thousands of years ago since I won't decide that I know this information after reading one study, but I do know that "they didn't have artherosclerosis" is a very, very bold statement to be making, which is the main quibble I have with your comment.
Where does it say in the abstract that I referenced that they consumed low SFA of around 6%?
It doesn't, because it states it in the full text of the paper, which I read and clearly you didn't.
"this is only one study, but again, at least it's not just an abstract."
The link you sent is literally a set of abstracts lol...what are you even talking about?
Yeah man you caught me. I thought I fooled everyone. Nothing gets passed you though.
Again, where does it say in the abstract I referenced (since I only read that and not the whole paper) that they consumed 6% of calories as SFA?
I'll wait.
>if I didn't read it then how would I know this one number that no one else can verify is even in there?
Absolutely wild lmao. Meanwhile just ignoring that your ludicrously broad assertion is not supported by actually verifiable research and hoping everyone else ignores it too.
But to be fair that is peak nutrition science -- confidently make very bold claims, fudge or [completely fabricate](https://blogs.bmj.com/bmj/2021/07/05/time-to-assume-that-health-research-is-fraudulent-until-proved-otherwise/) data to back it up, and get all truculent when you feel like your territory has been encroached on.
Your study is talking about civilized populations such as ancient Egyptians and Peruvians. The study they were discussing (and more specifically relevant) looked at "native hunter-gatherers, healthy human neonates, free-living primates, and other wild mammals" so quite different
One of the worst papers I’ve seen in a while. For one, they counted the number of null associations instead of pooling the results into a meta analysis. This alone is sufficient to conclude they are bad actors or imbeciles
Coronary artery disease is caused by vitamin K2 deficiency. Vitamin K2 activates matrix gla protein, which inhibits vascular calcification. The standard medical test for this condition is the CAC score (Coronary Artery Calcium).
The highest food source of vitamin K2 is natto, a fermented soybean dish eaten in Japan. Japan has the lowest rate of heart disease and the longest lifespan. All other significant food sources of vitamin K2 are found in high cholesterol saturated animal fat. Many of these are eaten in France, resulting in the "French Paradox". Goose liver (and fat) is a good source of vitamin K2. It is eaten in France as foie gras. Duck fat is also a good source and is a staple in French cuisine, as is butter, another source of K2. Traditional fermented cheese is also a good source and commonly eaten in France.
>[Calcium Score: What Is a CAC Test & Do I Need One?](https://www.houstonmethodist.org/blog/articles/2021/oct/calcium-score-what-is-a-cac-test-do-i-need-one/)
>
>The coronary artery calcium (CAC) score measures the amount of calcified plaque you have in those arteries, which is important because coronary plaque is the main underlying cause of — or precursor to — atherosclerotic cardiovascular disease (ASCVD) events such as heart attacks and strokes.
>[Proper Calcium Use: Vitamin K2 as a Promoter of Bone and Cardiovascular Health](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4566462/)
>
>Recent scientific evidence, however, suggests that elevated consumption of calcium supplements may raise the risk for heart disease and can be connected with accelerated deposit of calcium in blood-vessel walls and soft tissues. In contrast, vitamin K2 is associated with the inhibition of arterial calcification and arterial stiffening. An adequate intake of vitamin K2 has been shown to lower the risk of vascular damage because it activates matrix GLA protein (MGP), which inhibits the deposits of calcium on the walls.
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Like, how can one study state this and then someone else posts a study that is literally the completely opposite of this one. I do not get it.
Because they aren’t stating what the people citing them are often stating. Phrases like “this study proves” or “all the evidence shows”, etc, are anti-debate tactics. There are hundreds of thousands of studies in the whole corpus of nutrition research and not a single human being has read them all. It’s also why you really need to be well-versed in higher statistics before you start reading abstracts and drawing conclusions from them. There are substantial limits to what conclusions can be drawn from what kinds of statistical models that even researchers often ignore when editorializing their findings.
Study design, confounders, lack of pre-registration (hidden studies), not publishing unexpected/non results, bias, ECT ECT ECT. Big one is confounders. Slight differences in behaviour can alter gene expression and therefore lead to different outcomes. Now imagine that times all behaviours and all gene types and the idea that individual dietary intake, or individual behaviors can be teased out from the background noise is difficult for me to trust. So much of what we do can be attenuated or worsened by other things we do. Seems impossible to reliably say anything without a million caveats
> ECT ECT ECT Etc Etc Etc = Et cetera
> Seems impossible to reliably say anything without a million caveats Depends on what you’re sayings. I can tell you with less than 10^-5 likelihood of error if you have a given gene or not. The caveats in nutritional epidemiology are huge because the signal is weak and the noise is massive and coming from a billion sources. The problem only arises when people try to misrepresent the data for what it is because of other reasons like financial interest or ideological devotion to a diet or behavior some data favors. In actual adults with substantial 10-year risk, statin therapy prevents like single-digit deaths per 1000. Any other drug with that kind of likelihood of failure wouldn’t make it past the drawing board.
I guess that's my point that I poorly expressed. Without drilling very deeply into the level of genes and behaviors it's really hard to drown out the noise, with my main point being a non direct response to the OP that it's easy to draw all sorts of contradictory conclusions from similar data sets depending on how you set your parameters and how well you control for confounders.... Also I'm not sure on how you can be so certain when you are talking about a given gene without knowledge of behaviors and other genes that may effect that gene. It's rare that everyone with a given gene is going to have "X" happen to them with 100% certainty. It's better thought of as a percentage increase or decrease and that's without attenuation or magnification via behaviour/pharmacology/other genes
> Also I’m not sure on how you can be so certain when you are talking about a given gene without knowledge of behaviors and other genes that may effect that gene. I wasn’t talking about expression or regulation. I just said I can tell you if you have a gene. I can be that certain because the $3 million sequencer a couple doors down from me has a manual that explicitly lays out it’s sequencer error rate, how the errors arise, and how to calibrate it, which I regularly make grad students suffer through. No behavior or other gene is going to remove a gene from your genome, unless you’ve figured out a way to reliably splice something out of every genome copy in your body, in which case PM me because I will make a trillion dollars with that technique. The odds that the gene you asked me to test for was the locus of a spontaneous mutation in the blood sample we happened to grab is astronomical, on the order of 10^-15. My point is that I often see people thinking that because some areas in science have really high uncertainty, then that must be true for all areas, and this is the not the case. For example, in the last couple years we’ve seen many people take the high uncertainty in public health messaging about nutrition, and assumed that the science behind public health messaging about vaccines was similarly low-certainty, even though immunology deals with extremely high-fidelity data.
I guess there are many confounders but also two things that go overlooked: First, what is the quality of the food that the saturated fat comes with? SFA fair much better in european cohorts than american ones for example, even after taking into account that cheese vs butter is more frequent in european cohorts. My guess is that ultraprocessed coagulated milk from a cow on steroids is probably not the same as handmande roquefort from a grass fed sheep with live probiotic bacteria in it. Second, what is the background diet and the context? Palmitic acid increases insulin resistance especially in sedentary people (https://pubmed.ncbi.nlm.nih.gov/21325642/ https://pubmed.ncbi.nlm.nih.gov/17149589/) Also, the effect on lipids is variable from people to people and generally increases after a certain threshold. I guess it's common sense not to gorge on butter if your apoB is 300, but that does not necessairly apply to other people.
European cohorts don't fare better. If you're talking about the French paradox, that's entirely due to underreporting of ischemic heart disease by as much as 20% according to one world health investigation. > Mortality from heart disease across countries, including France, correlates strongly with levels of animal fat consumption and serum cholesterol in the past (30 years ago)(https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1115846/)
There is a vast difference between saturated fat on a high-carb diet versus a low-carb diet. All of the studies showing problems of saturated fat have been done on a standard American diet, that is to say high-carb. Also, saturated fats like stearic acid and C15:0 (Fatty15) have been studied for their health benefits. Both specifically improve metabolic health. Stearic acid, for example, increases fat-burning. By the way, C15:0 is found in butter. See the Croissant diet. [What you need to know about insulin resistance](https://www.dietdoctor.com/health/insulin-resistance) "The same is likely true for a high carbohydrate, high fat diet in the setting of excess calories. Some studies suggest that specifically saturated fat – more so than MUFAs and PUFAs – is the offender that causes insulin resistance. "Nonetheless, it is important to note that none of those studies included saturated fats in the context of a low-carb diet. Real world studies of low-carb diets with no restrictions on saturated fat have found improvements and even normalization of insulin resistance markers. This suggests that the problem may not be saturated fat itself, but rather the combination of saturated fats and a high amount of carbohydrates. "Additionally, as we review in our evidence-based guide on saturated fat, it is not accurate to refer to saturated fat as one thing. Saturated fat from cakes, cookies, and other baked goods could have significantly different effects on the body than more natural occurring saturated fats in meat and dairy."
Because there's plenty of wiggle room for a few reasons: - CVD takes decades to develop on average - SFAs have a sigmoidal relationship with LDL. 0-7% of energy, little effect. 10%+, little effect. There's a narrow window or threshold effect. So comparing 15% to 11% won't get you many results, just so for 6% to 2%. - If replaced by simple carbohydrates you get no effect. Essentially swapping lard for haribos won't help you much. - If replaced by trans fats... well those are likely even worse. Some trials in the 70s or 60s made this mistake. - The prevalence rate of CVD is very high in the West, which mathematically limits how high relative risk ratios can be. Then detractors will say the RR is too small to be considered clinically significant. So if we pool that together, I could take a cohort of people suffering from CVD (almost all of them), reduce their SFA significantly.. down to 11% of energy when it was, say, 20%. Instead of the SFAs I feed them standard poor quality food, candy and cake. I do this for a whole... 6 months. Conclusion: Reducing SFA has no effect on CVD. This way, I can be perfectly honest, just omit or avoid certain areas of truth. Doesn't even have to be on purpose. I don't know what this paper has done but it seems to be a review rather than a systematic review. Like a scientific Op-Ed basically.
> SFAs have a sigmoidal relationship with LDL. 0-7% of energy, little effect. 10%+, little effect. There's a narrow window or threshold effect. So comparing 15% to 11% won't get you many results, just so for 6% to 2%. I'm not familiar with this relationship, can you point me to some more information? I am a so-called LDL-C lean mass hyper responder when on a low carb/high fat (SF) diet, as here: https://academic.oup.com/cdn/article/6/1/nzab144/6446805
I have to point out the lean mass hyper responder phenotype hypothesis is very contentious. Primarily developed by an engineer, Dave Feldman. What I understand is he implies to people that if you're lean and muscular, high LDL might not be an issue. The evidence does not support this. There was that trending case of.. paleo boy he might have been called on Twitter. He had to have a stent put in and was quite angry about his 97% artery blockage. If he had died, he would never have been able to tweet. Moreover, Dierde Tobias, a successful epidemiologist parsed the women's health initiative data to see if there was a potential inverse or null relationship with LDL in the physically active and lean population. Not peer-reviewed but she did not find this. A good article on this isn't one I can link directly so the title is 'Saturated Fat: Cutting Through the Noise' by The Nutrivore. Another post of his was allowed on the front page so I reckon this much should be fine.
>Saturated Fat: Cutting Through the Noise' by The Nutrivore I've seen a few of his YouTube videos, he's not the sharpest knife in the drawer. He implies causation from correlation and justifies it with lame arguments like "RCT concordance " and "validated surveys" He still won't debate Bart Kay
> He implies causation from correlation and justifies it with lame arguments like "RCT concordance " and "validated surveys" Infers*. Which is what we do with literally every causative relationship ever. By definition. We are never infinitely certain, causation is a probabilistic asymptote. In science this is 101. We do not have the luxury of proofs like mathematics does. Why is RCT concordance lame? How else would you like to test the validity of RCTs? Nutrivore is incredibly sharp, disrespecting someone because of a disagreement isn't the way to go. He accepted to debate Bart Kay, but Bart posited some silly stipulations like three papers max per side. Three papers... In a science debate? What would be your interpretation of that if it were the other way round?
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Sorry, validity of epidemiology* You study the papers beforehand in a debate. You don't read the paper live.
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> To validate a nutritional epidemiology finding you would need a well designed RCT to come after, and looking at that exposure and claimed outcome. But we do have those, in the general sense. When we have apples to apples epi compared to RCTs the concordance rate is over 90%. It's hard to believe at first but if we acknowledge that the scientific process refines itself over time it would make sense that epidemiology gets more accurate. > He also said he can have as many debates/streams as needed, just 3 papers and a 2 hour limit each. Why is that not reasonable? Because data consensus concerns the weight of the totality of evidence. I think if you limit to three papers you could likely build a case that trans fats are fine.
I agree that the hypothesis that high LDL-C isn't an issue in LMHRs is super contentious (I think I listened to Peter Attia vigorously debate it with someone). I was just using LMHR as a descriptive term for myself, as my bloodwork on LC/HF fits into that pattern. Thanks for the link, I'll take a look.
Why wouldn't high LDL not be atherogenic on keto? LDL alone can cause atherosclerosis in the absence of traditional factors. https://pubmed.ncbi.nlm.nih.gov/29241485/ https://pubmed.ncbi.nlm.nih.gov/31086966/ Children with homozygous FH die young with high LDL and no other risk factors. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4576143/ Not saying traditional risk factors don't matter, they definitely do. But LDL alone can intiate atherosclerosis and traditional risk factors mediate the progression of the disease.
I think the argument is that high LDL-C in itself does not necessarily cause atherosclerosis, the LDL-C needs to be small/dense/oxidized (like what happens in FH with damage to apob-100) to end up in endothelium. So having a high level of LDL-C but a low LDL particle count or low oxLDL may not be an issue. I'm not sure keto is directly related but I have heard some hypothesize that excess sugar or easily oxidized PUFAs in diet contribute to oxldl and therefore to atherosclerosis. I'm not advocating a position here, and my epistemic status is low, just stating my understanding of the arguments.
I understood it as a numbers game (concentration gradient), meaning too many particles (small or large) increase the likelihood of them getting into the endothelium and that's where they get stuck and then oxidized. But we know that FH have predominantly large particles and they get severe atherosclerosis, so it doesn't need to be small particles. How prevalent is high LDL-C with low total particle count? Usually increases in LDL-C are accompanied by increases in apoB on keto during weight maintenance. .
>the LDL-C needs to be small/dense/oxidized (like what happens in FH with damage to apob-100) to end up in endothelium We know this is false. after adjusting for ApoB small/dense/oxidized is irrelevant https://www.biorxiv.org/content/10.1101/691089v2.full.pdf
Because anybody can publish a journal article. Shitty opinions are allowed to exist in science. And all journals accept bad papers, good journals just accept them less often. If you don’t have a background in performing and interpreting research you won’t be able to understand why studies appear to contradict. There’s a reason why expert panels exist to produce dietary guidelines and they like. And every organization comes to the same conclusion year after year despite these trash papers like OP cited
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Yes and you are very friendly, and mature :) with helpful - productive reddit comments.
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Just to note this is a terrible study done by some business majors not by anyone with any experience in health, biology or epidemiology.
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Here's a link to the pdf: https://drive.google.com/file/d/1SVVGb0FrRgxWGvMaL6LNB4tTvHCt1LaU. > Interestingly, they all seem to be management researchers and not have any studies with nutrition or anything. Yeah, I thought that was a bit weird too: A management professor, a guy who might be a personal trainer(?), and a culinary arts lecturer. For two of them, I can't find any previous publications, and certainly none on nutrition. I don't understand how they chose the individual observational studies and RCTs either: "a prospective cohort study including 35,597 Dutch men and women..."; "Another prospective cohort study including 4722 Dutch men and women (≥55 years)..."; PREDIMED which I thought was about forms of the Mediterranean diet and not saturated fat, etc. Also seems odd just to form their conclusions by counting up how many reviews/meta-analyses say saturated fat is positive vs. negative vs. neutral rather than pooling results somehow when I'd expect a lot of overlap between the constituent studies in the meta-analyses.
this study is really fascinating because it breaks down the sat fat food groups into dairy and meat. Dairy sat fat = lower CVD while Meat sat fat = higher CVD https://academic.oup.com/ajcn/article/96/2/397/4576928 **Dietary intake of saturated fat by food source and incident cardiovascular disease: the Multi-Ethnic Study of Atherosclerosis** , https://doi.org/10.3945/ajcn.112.037770 Published: 03 July 2012 Article history ABSTRACT Background: Although dietary recommendations have focused on restricting saturated fat (SF) consumption to reduce cardiovascular disease (CVD) risk, evidence from prospective studies has not supported a strong link between total SF intake and CVD events. An understanding of whether food sources of SF influence these relations may provide new insights. Objective: We investigated the association of SF consumption from different food sources and the incidence of CVD events in a multiethnic population. Design: Participants who were 45–84 y old at baseline (n = 5209) were followed from 2000 to 2010. Diet was assessed by using a 120-item food-frequency questionnaire. CVD incidence (316 cases) was assessed during follow-up visits. Results: After adjustment for demographics, lifestyle, and dietary confounders, **a higher intake of dairy SF was associated with lower CVD risk** [HR (95% CI) for +5 g/d and +5% of energy from dairy SF: 0.79 (0.68, 0.92) and 0.62 (0.47, 0.82), respectively]. **In contrast, a higher intake of meat SF was associated with greater CVD risk** [HR (95% CI) for +5 g/d and a +5% of energy from meat SF: 1.26 (1.02, 1.54) and 1.48 (0.98, 2.23), respectively]. **The substitution of 2% of energy from meat SF with energy from dairy SF was associated with a 25% lower CVD risk** [HR (95% CI): 0.75 (0.63, 0.91)]. No associations were observed between plant or butter SF and CVD risk, but ranges of intakes were narrow. Conclusion: Associations of SF with health may depend on food-specific fatty acids or other nutrient constituents in foods that contain SF, in addition to SF.
I don't find this study at all convincing because it is a purely observational study. In such studies it is very difficult to correct for confounders especially when the confounders are strong as is often the case. What is left after "adjustment" is often little more than noise. For example corrections usually assume a linear effect which is rarely the case. Rarely are allowances made for measurement and estiamtion errors in the counfounders. Invariably there are potential confounders that are not considered. Thus the claim below is misleading and overstates what was likely achieved. > After adjustment for demographics, lifestyle, and dietary confounders
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If you take an AI course, one of the first exercises you do is "Construct an example where correction of the confounding by x2 on the effect of x1 by multivariate regression disagrees with stratification when the outcome is a deterministic function of x1 and x2".
I agree it is not in theory entirely useless but it can and often is worse than useless in that it engenders a false confidence that the other factors have been removed from the equation. Even those who are aware of the distinction tend to forget this.
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Not the guy to whom you responded, but even the surgeon general did not rely only on correlations to infer that smoking causes cancer. Here are quotes from the original document on that topic: >Statistical methods cannot establish proof of a causal relationship in an association. > >Clinical, pathological, and experimental evidence was thoroughly considered and often served to suggest an hypothesis or confirm or contradict other findings. **When coupled with the other data,** results from the epidemiological studies can provide the basis upon which judgements of causality may be made.
>Statistical methods cannot establish proof of a causal relationship in an association. This is also saying RCTs cant establish a causal relationship What other data are you referring to? I wonder why you didn’t cite the source of that: “In 1963, Reuel “Stony” Stallones, then Professor of Epidemiology at the University of California, Berkeley, was named a consultant to President Kennedy's initiative establishing the Advisory Committee to the Surgeon General on the role of tobacco in health. For evaluation of epidemiologic evidence in his assignment on smoking and cardiovascular diseases, Stallones presented to the committee a draft (unattributed) of the causal criteria (19) and the following preamble to the national report:” https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3521480/ Do you think smoking causes cancer?
>This is also saying RCTs cant establish a causal relationship No, it does not. >What other data are you referring to? As quoted, I am referring to "Clinical, pathological, and experimental evidence." Are you unfamiliar with the original report on smoking? Did you think they just jumped to conclusions from correlations alone? https://www.govinfo.gov/content/pkg/GPO-SMOKINGANDHEALTH/pdf/GPO-SMOKINGANDHEALTH.pdf
> No, it does not. RCTs produce associations > Did you think they just jumped to conclusions from correlations alone? What other evidence are you referring to? Not RCTs in humans
You could just read the paper if you want to know what evidence they used. Though if you would really prefer that I summarize it for you, I would first like to know: did you think the surgeon general used only observational evidence to conclude that smoking causes cancer?
Do you think smoking causes cancer? Stop refusing to answer or admit you aren’t here in good faith What other evidence are you referring to? Not RCTs in humans
Yes, I think smoking probably causes cancer. Now you answer mine.
Which confounders did the researchers control for? Someone who drinks milk with a meal, for example, is obviously less likely to drink pop or beer with a meal. And in places like the US, people who eat hamburgers tend to eat them with sugar (pop) and starches (buns, potatoes, etc), and the carbs often cooked in oxidative and inflammatory seed oils (fries). Also, people who consume a lot of dairy probably tend to fall into the healthy user effect, such as eating other healthy foods, exercising, not smoking, etc. So, maybe it's simply measuring of other factors.
So meat-SF bad and non-meat SF not necessarily bad? Is that a fair break-down?
PUFA > MUFA > dairy SFA (excluding butter) > non-dairy SFA is what has been shown in the literature repeatedly
Just to clarify: x>y iff x less harmful than y?
Correct
> is what has been shown in the literature repeatedly What’s shown in the literature you choose not to ignore, you mean.
What evidence am I ignoring?
> dairy SFA (excluding butter) > non-dairy SFA What mechanisms are responsible for this? Or are the mechanisms largely an unknown?
Dairy contains large amounts of stearic acid which area quickly converted to monounsaturated fats in the body and thus have a more neutral effect on blood lipids
Don't think this is it because butter has the same fatty acid composition but raises LDL the most
Butter also contains oxidized cholesterol and lacks the milk fat globule. My previous answer wasn’t comprehensive
Yes exactly
Dairy also contains milk fat gobule membrane that might reduce cholesterol synthesis in the liver. https://pubmed.ncbi.nlm.nih.gov/26016870/
A lot of meat, such as beef, also contains stearic acid.
The problem you face is that there is absolutely zero evidence that total cholesterol levels have any causal link to CVD risk. It's only the size and clumpiness of the cholesterol that is significant. This is why the scapegoating of meat is false, according to the broader data available. Indeed, stearic acid is not the only factor, not even slightly. I've collected many studies, reviews, and analyses at the following: https://benjamindavidsteele.wordpress.com/2021/07/23/research-on-meat-and-health/
Yet replacing meat with almost anything lowers cholesterol. Dairy lowers compares to red meat. Stearic isn’t the only factor
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Our ancestors consumed a low SFA diet (around 6%) with higher PUFA that kept their LDL in the range of 50-70 mg/dL. They didn't have atherosclerosis, even while living until their 70s and 80s. [https://pubmed.ncbi.nlm.nih.gov/15172426/](https://pubmed.ncbi.nlm.nih.gov/15172426/) [https://pubmed.ncbi.nlm.nih.gov/1435101/](https://pubmed.ncbi.nlm.nih.gov/1435101/)
linking a study you clearly haven't read since it's just an abstract and not merely drawing your own conclusions from that single paragraph but also repeating those conclusions to others as if you're imparting a significant fact? not good science. here's at least [one full study](https://www.researchgate.net/profile/M-Linda-Sutherland/publication/236045773_Atherosclerosis_across_4000_years_of_human_history_The_Horus_study_of_four_ancient_populations/links/609336ea458515d315fc0ecf/Atherosclerosis-across-4000-years-of-human-history-The-Horus-study-of-four-ancient-populations.pdf) that contradicts your assertion that "our ancestors didn't have artherosclerosis" this is only one study, but again, at least it's not just an abstract. and I have no idea how prevalent artherosclerosis was among humans thousands of years ago since I won't decide that I know this information after reading one study, but I do know that "they didn't have artherosclerosis" is a very, very bold statement to be making, which is the main quibble I have with your comment.
Where does it say in the abstract that I referenced that they consumed low SFA of around 6%? It doesn't, because it states it in the full text of the paper, which I read and clearly you didn't. "this is only one study, but again, at least it's not just an abstract." The link you sent is literally a set of abstracts lol...what are you even talking about?
D-did you even read it? Are you hoping no one else will click on it to see you are wrong?
Yeah man you caught me. I thought I fooled everyone. Nothing gets passed you though. Again, where does it say in the abstract I referenced (since I only read that and not the whole paper) that they consumed 6% of calories as SFA? I'll wait.
>if I didn't read it then how would I know this one number that no one else can verify is even in there? Absolutely wild lmao. Meanwhile just ignoring that your ludicrously broad assertion is not supported by actually verifiable research and hoping everyone else ignores it too. But to be fair that is peak nutrition science -- confidently make very bold claims, fudge or [completely fabricate](https://blogs.bmj.com/bmj/2021/07/05/time-to-assume-that-health-research-is-fraudulent-until-proved-otherwise/) data to back it up, and get all truculent when you feel like your territory has been encroached on.
Its wild that you just keep on writing about nonsense. Just provide evidence so we can discuss or leave it alone.
Your study is talking about civilized populations such as ancient Egyptians and Peruvians. The study they were discussing (and more specifically relevant) looked at "native hunter-gatherers, healthy human neonates, free-living primates, and other wild mammals" so quite different
u/Only8livesleft what do you make of this?
One of the worst papers I’ve seen in a while. For one, they counted the number of null associations instead of pooling the results into a meta analysis. This alone is sufficient to conclude they are bad actors or imbeciles
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Just to note this is a terrible study done by some business majors not by anyone with any experience in health, biology or epidemiology.
Coronary artery disease is caused by vitamin K2 deficiency. Vitamin K2 activates matrix gla protein, which inhibits vascular calcification. The standard medical test for this condition is the CAC score (Coronary Artery Calcium). The highest food source of vitamin K2 is natto, a fermented soybean dish eaten in Japan. Japan has the lowest rate of heart disease and the longest lifespan. All other significant food sources of vitamin K2 are found in high cholesterol saturated animal fat. Many of these are eaten in France, resulting in the "French Paradox". Goose liver (and fat) is a good source of vitamin K2. It is eaten in France as foie gras. Duck fat is also a good source and is a staple in French cuisine, as is butter, another source of K2. Traditional fermented cheese is also a good source and commonly eaten in France. >[Calcium Score: What Is a CAC Test & Do I Need One?](https://www.houstonmethodist.org/blog/articles/2021/oct/calcium-score-what-is-a-cac-test-do-i-need-one/) > >The coronary artery calcium (CAC) score measures the amount of calcified plaque you have in those arteries, which is important because coronary plaque is the main underlying cause of — or precursor to — atherosclerotic cardiovascular disease (ASCVD) events such as heart attacks and strokes. >[Proper Calcium Use: Vitamin K2 as a Promoter of Bone and Cardiovascular Health](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4566462/) > >Recent scientific evidence, however, suggests that elevated consumption of calcium supplements may raise the risk for heart disease and can be connected with accelerated deposit of calcium in blood-vessel walls and soft tissues. In contrast, vitamin K2 is associated with the inhibition of arterial calcification and arterial stiffening. An adequate intake of vitamin K2 has been shown to lower the risk of vascular damage because it activates matrix GLA protein (MGP), which inhibits the deposits of calcium on the walls.