To establish a cause/effect relationship requires experiment. For argument's sake, let's say some sort of change in nutrient content of meat caused scientists to suspect increased red meat consumption contributed to the global increase in obesity and diabetes. Evidence from animal experiments suggests that an arachidonic acid might be part of the problem.
Monogastrics such as poultry and swine have much higher levels of arachidonic acid in their fat and lean tissues than ungulates. The below narratives suggest a correlation between monogastric meat consumption and obesity/diabetes epidemic.
(2016) "The ω-6 series of fatty acids, which includes arachidonic acid (ARA, C20:4) and its precursor linoleic acid (LA), constitute a growing part of the lipid intake in western diets for the last 40 years. The first cause of this trend is the higher consumption of animal products. White meat especially provides the highest quantities of dietary ARA." (web search - Thomas Dietary arachidonic acid)
Excerpt from Page 56 of 'Omega Balance' by Australian zoologist Anthony Hulbert, PhD (2023) "The contribution of pork and poultry' to animal-sourced foods was 20 percent in 1961 and 41 percent in 2018…Between 1961 and 2018 there was a dramatic worldwide increase in the supply of fats from sources that have very low omega balances. Fat from 'pork and poultry' was greatest in North America for the entire 1961-2018 period, while for Australia and South America, the contribution from 'pork and poultry' was the World average level in 1961 and showed the greatest absolute increases (about 16 g) over this period to be similar to North America and Europe in 2018. There was negligible change in Africa over this period."
(2023) “Poultry meats, in particular chicken, have high rates of consumption globally. Poultry is the most consumed type of meat in the United States (US), with chicken being the most common type of poultry consumed. The amounts of chicken and total poultry consumed in the US have more than tripled over the last six decades… Limited evidence from randomized controlled trials indicates the consumption of lean unprocessed chicken as a primary dietary protein source has either beneficial or neutral effects on body weight and body composition and risk factors for CVD and T2DM. Apparently, zero randomized controlled feeding trials have specifically assessed the effects of consuming processed chicken/poultry on these health outcomes.” (web search - Poultry consumption and human cardiometabolic health)
I made up an information sheet consisting of the above narratives strung together along with excerpts from articles about arachidonic acid research and commentary. Our daughter and her husband, who own a fitness center, gave me permission to leave copies at the front counter for patrons to take home and read. The current manager recently told me that he and his fellow weight lifters were impressed with what I said about chicken meat. After shifting their major protein source from chicken to fish, all reported improved performance and less joint inflammation post workout. (web search - Hulbert The under-appreciated fats of life)
This confirms that it is impossible to analyze data without a perfectly defined hypothesis, itself developed according to a theory built on solid knowledge.
So, if it isn't possible to do an RCT (and long-term multi-decadal lifestyle studies aren't possible as RCTs), then throw out any conclusions from the only practical kind of study that can be done? Isn't this throwing the baby out with the bathwater?
If this were to be widely adopted, I guess studies would be dominated by Big Pharma or the Ag industry or whatever, since they could fund lots of studies and thus dominate the studies that feed into an analysis like this, assuring the outcome.
It seems like this is a software problem. As long as scientists have to perform a bespoke analysis, often a copy/paste from whomever taught them statistics, we will continue getting mostly ambiguous results. It seems there should be some open source effort by software engineers to create some semi-universal scientific analysis program that runs _all_ reasonable analyses instead of just the one or two the scientists are aware of.
I guess that in most cases it's not about completely different methods - which often depend on the available data - but more about the assumptions: models, estimates, significance, censoring, etc.
But I agree with the principle: if researchers - and journals - acknowledged that their analysis is just one in a million, lots of things in medicine and health policy would improve.
Seeing results from a variety of specifications provides additional information on how robust the results are. I've used bootstrapping in some of my analyses. Bootstrapping provides information on whether the results will be robust with respect to different samples. However, the problem with observational studies is that biases are introduced because people self-select rather than being randomized into treatment or control groups. I don't see how this new methodology compensates for self selection bias.
This is very interesting. It should set the floor for any future publication of a “positive association”. And hopefully this will become the standard for observational research. Do a test for association in multiple ways….then tell us why you chose those particular ways out of the total denominator of possible options….and tell us the results of each of those ways. Then if you find a significant portion of those pathways still points to a significant association….THEN you might have my curiosity. I suppose it would be a retrospective randomization of potential confounders….of sorts.
I think the value of this approach is that it demonstrates the fact that observational studies are essentially worthless. The elephant in the room with observational studies is the quality of the data. Nutritional data is especially unreliable. I don't really understand how one can generate a quadrillion ways to analyze a data set that contains two variables but I am glad to see evidence that any given study can be disregarded. In this case I give them credit for coming to the right conclusion---that consumption of red meat has nothing to do with health or disease. This valuable insight needs to be extended to include everything else humans consume. But we already knew this from the considerable research that delineated the processes of digestion and absorption of nutrients---one of the best worked out areas of physiology.
"In this case I give them credit for coming to the right conclusion---that consumption of red meat has nothing to do with health or disease." No, that is the wrong conclusion and is not the one reached by Wang et al. I find it depressing to see their discussion misrepresented with this kind of conclusion, one which is completely unwarranted and an example of "spinning knowledge out of ignorance" in the form of nullism: Inferring there was no effect when the correct inference is the data can't answer the question of whether there is an effect or what direction it might go.
This kind of misrepresentation also occurs routinely in randomized trials when a result with p>0.05 is described as "the trial showed there is no effect" but the interval estimate actually shows that clinically important effects cannot be ruled out using the same "nonsignificance" criterion. It seems that the compulsion to draw conclusions about an effect will override correct interpretations, revealing a problem deeper than any statistical limitation of data: Human allergy to uncertainty. That allergy will lead to misinterpretation of more sophisticated analyses in the same manner as conventional analyses.
Specification-curve analysis and other methods long predating it (such as sensitivity analysis, bias analysis, and uncertainty analysis) exemplify what has been known by some for decades: Once we account for all the uncertainty sources, including uncertainty about which model to use as well as about uncontrolled confounding and measurement errors, the most we can conclude is that dietary questionnaire data provide little to no useful information about the effects of specific dietary components or nutrients. There have been over a quarter-century of such demonstrations; e.g., for one using different methodology and data, see 'When should epidemiologic regressions use random coefficients?' Biometrics 2000;56:915-921.
Thank you for your usual thoughtful and well-reasoned reply. Perhaps I should have phrased it differently. I was referring to the author's description of the article's conclusion. In my opinion it is logistically impossible to carry out a scientifically valid study on diet and disease in a free-living population. My opinion that consumption of red meat has nothing to do with health or disease is based on existing knowledge about the physiology of the human digestive system and the pathophysiology of disease.
Thank you for your measured reply. I nonetheless think it is too sweeping to say "it is logistically impossible to carry out a scientifically valid study on diet and disease in a free-living population." There have been trials in which dietary interventions have been randomized among otherwise "free-living" participants. I suspect you meant that purely observational studies without interventions do not yield trustworthy estimates of diet and nutrient effects. While that is often the case, such studies have yielded vital clues about diseases from nutrient deficiencies (e.g., scurvy, pellagra, goiter) and excesses (e.g., toxicities from oversupplementation) in special situations.
The problem I see is that such situations are uncommon in most modern populations, and so researchers have turned to studying relations too subtle for observational studies and even feasible trials to discern in general populations. The nutrient ranges in those populations may include suboptimal values, but those are not manifested by obvious syndromes that can easily rise above noise and bias and then confirmed as deficiencies via experimental interventions.
To be fair and honest, I fail to see how your claim that "consumption of red meat has nothing to do with health or disease is based on existing knowledge about the physiology of the human digestive system and the pathophysiology of disease" is any different in its excessive certainty from the opposing claims that consumption of red meat has much to do with health or disease, claims that proponents also say are based on existing knowledge about the physiology of the human digestive system and the pathophysiology of disease. There are proponents in both directions, making similar declarations that extol and condemn red meat. Few consider that there are likely important differences across individuals and populations (e.g., based on age, physical activity, pregnancy, lactation, etc.).
A range of opinions does not mean that some middle ground of "no effect" is correct; it means that there is no scientific consensus (just as there is none about say dark matter/dark gravity), and that excessive certainty in any position is the phenomenon we should be most worried about. When I look at the studies and reviews about specific diet components and nutrients (including trials) it seems more like an inkblot test, with various sides projecting what they are already convinced of or want to believe onto data that can be analyzed, criticized and interpreted in manifold ways. Perhaps that excessive certainty is (again) just the human allergy to uncertainty, which must dominate when effects are not obvious. Even the enormous adverse effects of smoking on health were argued about for centuries; when evidence finally reached an overwhelming level in the 1950s it was still met with ferocious resistance among some academics - including RA Fisher, who also rejected observational studies of causality. Given that history, the idea that such studies could force consensus about optimal nutrition and health seems naive indeed.
I plead guilty to an excessive degree of certainty. Perhaps the difference is due to our different perspectives. I assume that you are a research scientist and, as such, are rightfully concerned with absolute precision. I was in clinical practice of medicine for about forty years---mostly cardiology but also a fair amount of Internal Medicine. Patients would want to know whether they should restrict their diet or, more importantly, whether they should take medications to prevent diseases and they often did not deal well with uncertainty. Given the degree to which they were subjected to an overwhelming amount of media promotion for certain drugs I may have tried to balance the argument with some over statement on my part. Obviously I didn';t have the time to go into long statements of physiological justification for every recommendation I made.
I could do so for the claims I made here about diet and health and the admonitions against red meat but that would require more than a brief comment.
SG had a tantrum over nothing. They She He found it “depressing” that YOU came to a conclusion of status quo when SG didn’t say there was a reason to conclude anything. You must never come to a conclusion that could make research funding more difficult and make the work less needed or valued. So shame on you ENC. 🤪
I probably missed it, but how long did this study take and what was the cost? I have a feeling they are both prohibitive to the prelaunch of new medications. And like someone else posted, would a trial of this magnitude be valuable in studying the effects of eggs, coffee, red wine, blueberries, etc.?
This sounds so promising to a non scientist like me. I have wondered before whether information this is easier to find with AI. Couldn't you give these parameters to a computer and have them reveal the highest quality data? And, presuming no bias, wouldn't the computer want to find the quality data?
I couldn't care less what the "scientists" concluded. I eat more meat than anything else. For decades these clowns have told us that eggs, dairy, coffee, fats, cholesterol or something was dangerous to our health. The only thing that is dangerous is listening to this clown show of pretend experts.
What if they studied red meat from a cure perspective? What cases of disease can be cured with red meat? What cases of disease can be cured by stopping consumption of red meat? This is no longer a "statistical study" it has been reduced to a study of counting actual cases. No complex variations of statistics are required.
However these "real" studies face mountains of illogic.
First of all, cured is not medically defined for any disease that might be cured with red meat. Cured is not medically defined for any nutrition deficiency.
Second, cured is not defined for any disease caused by toxic effects of red meat. Cured is not medically defined, at present, for any "poisoning" disease.
And in addition, cured is only medically defined for approved medical treatments. Stopping or adding red meat is not an approved medical treatment.
Even when people are cured, each cure is a single case, an anecdote. And anecdotal cures are not valid in Evidence Based Medicine. "CURED" is not even medically defined in EBM.
In summary, even cures that occur cannot be detected. They are out of scope.
The study might be expanded to show "benefits" or "harms" to patients who were not consuming red meat - provided by consumption or red meat, and benefits or harms to patients who are consuming red meat - provided by stopping consumption of red meat. Then we could take next steps to analyze why red meat provides harms, in what situations, and why it provides benefits in some situations. But the answers are pretty obvious. People who are suffering a wide variety of nutrient deficiencies can receive benefits from consuming red meat. We already know this, so there is no point in the study. On the other hand, people who are eating too much of all foods would receive some benefits - by stopping consumption of red meat if that was the only change in their diet. They might also be harmed by the change - obese people tend to be malnourished in specific ways and cutting red meat could exacerbate these cases.
But... These are real cases. Each real case is a story that can be analyzed individually to come to a conclusion. Conclusions can be collected and analyzed collectively, but for one problem.
Single cases, single stories are anecdotes and anecdotal evidence is not considered valid in Evidence Based Medicine.
I concluded a while ago that observational studies aren’t worth the electricity it takes to store them. They give authoritarians a rational to rule over us: pressure us to spend money, force us to wear masks, take vaccines we don’t want, close down businesses. They do this even when RCTs are available that paint a very different picture.
One motivation is to create the illusion that they are protecting us from the dangers of the world, unlike their opponents. First decide the policy, then select from a near infinite number of studies that justify the policy. This isn’t a conspiracy, it’s just the lowbrow behavior that emerges from a less than ethical establishment.
The other great motivation is money. Observational studies bring lots and lots of money: useless tests, therapies, and pharmaceuticals. People waste hours of their lives watching meaningless videos, with lots of impressive jargon, claiming this or that based on observational studies.
The most disgusting aspect of this is that when a rare bird comes along who tries to warn the public: Vinay Prasad, Tracy Hoeg, Gilbert Welch, Robert Whitaker, Clare Craig, the attack machine tries to destroy them, and the attackers are usually MDs.
We live in predatory world; you had better learn to protect yourself.
My name for it is 'policy based evidence' - with the desired policy in mind peck around like a demented chicken to find enough evidence and expert opinion to shore it up and sell it to the politicians and media.
But it requires a high level of groupthink too; the last thing you want is some dissident type banging the table and going on about *proper* evidence, especially when they turn out to be right! It's essential these individuals are eased out of the organization one way or another.
By the way a close cousin of this practice is 'consent manufacturing'...
Early in the pandemic, all the health care professionals told us masks don’t work. They based that on a series of RCTs that had been done over the years, showing no benefit. But policy makers started insisting that we should wear masks anyway. All of a sudden science had decided that masks work after all. In fact, the head of the CDC at the time declared that masks work better than vaccines, and the vaccines hadn’t even been invented yet. He was probably right in strange way: 0 > -1.
What was this new science? Scott Atlas, the one honest person in the covid policy team tells us. He asked Deborah Birx why the sudden turnaround. She said her team had discovered 2 mask wearing barbers, infected with covid, but didn’t infect a total of 139 of their clients tested. So, the most influential health care professional in the county, advisor to the president, discarded decades of RCTs in favor of an uncontrolled observational study with an N of 2.
And soon we had forced masking. People who objected were politicizing, didn’t believe in science, didn’t care about others. If they can bend science that badly, that easily, there is no limit to how science can be distorted, and our corporate media plays along.
Yes, I regard the public masking requirements as more likely to be counter productive, because the false certainty it can give to high risk individuals in high exposure situations.
It's far better to reduce prolonged face to face contact indoors where possible, but OTOH there's no need for hiding at home 24/7 due to silly lockdowns either.
Probably the best place for it is done or directed by healthcare professionals usually in healthcare settings like hospitals and carehomes. But only as the situation really requires it - not letting families seeing dying loved ones due to the lunatic policies of health administrators is unforgiveable.
I enjoyed reading this post of yours but cringed and had rigors when I saw you use the latest "buzzword du jour" -- I refer to this SPACE thing. All of a sudden, and for mysterious reasons, plenty of folks no longer talk or write about (for example) some development in the field of cardiology; instead they feel compelled to use the precious verbiage, "cardiology space". Ditto for just about every other discipline or work activity that can be imagined for the human race.
Instead of saying that I took my Allen Edmonds loafers to a competent shoe repair shop last week, it is apparently now de rigueur to say instead, "I took my Allen Edmonds loafers last week to a guy who is very active these days in the shoe repair space". If you think I am being hyperbolic here, please think again! The unctuous, highly paid cretins who dominate healthcare administration in our country have recently added the noun SPACE to their list of automatic bullshit terminology. In other words, using the noun "space" is now a big fad in the Healthcare Administration SPACE. God help us. Please.
I am with you on the overuse of the term space. There are a gazillion others too. But I give Dr Mandrola a pass. Language has its fashions and trends and often without thinking we end up including these expressions in our own language. I have been living in Texas for 28 years and have resisted saying Y’all. I actually made a conscious effort not to, and now after all that effort Y’all is used by everyone everywhere. I look to Dr Mandrola only for medical expertise not language use. Although I think my red line is “chest feeding”. Chest feeding is actually on the CDC website last time I looked. I hope they have removed it in embarrassment and shame. Pregnant people. There’s another one. These new trendy expressions deny biology and logic. “Space” is more of a business expression. It replaces “market”. Both space and market turn medicine into a profit and loss business (and let’s not go there right now). Anyway, I am on team Mandrola, team logic, and team science. How about that, I just deployed a trendy language usage!
I know this isn't the point of your article, but nevertheless it's important to always examine all aspects of validity. With nutritional epidemiology, a major flaw is the way food intake is measured. The usual methods are food records, food frequency questionnaires, and 24-hour recalls; and they are often not done continuously. These methods are known to be quite unreliable. They also don't consider the fact food is not eaten in isolation, but within a food matrix that can vary across individuals and also affect outcomes. Regardless of the type(s) of analyses chosen, garbage in = garbage out.
Let's not even asked what kind of red meat it was. because I believe that the quality of the meat makes a difference. And also, potential comorbidities of those who died. I mean, come on, what is the point of this analysis when you're taking so many general statements about what you're studying?
I always wonder this too when I see ‘red meat causes X’ stories. Is it really the red meat per se, or by saying ‘red meat’ is it people eating a lot of burgers, sausage, and bacon that are also eating potato salad and mac n cheese and plenty of booze with the red meat? Is lean red meat ever studied on its own?
I was speaking more of grass fed beef not what you buy in the grocery store. I haven't bought meat in the grocery store for at least 10 years. I advise against it.
AND if you go out and eat (which I don't) what kind of "meat" are you eating? You have NO idea!
Years ago the Wall Street Journal published a sushi expose that tested the DNA of various super-expensive varieties of sushi from high end establishments. Duh: you most certainly do not get what you pay for.
To establish a cause/effect relationship requires experiment. For argument's sake, let's say some sort of change in nutrient content of meat caused scientists to suspect increased red meat consumption contributed to the global increase in obesity and diabetes. Evidence from animal experiments suggests that an arachidonic acid might be part of the problem.
Monogastrics such as poultry and swine have much higher levels of arachidonic acid in their fat and lean tissues than ungulates. The below narratives suggest a correlation between monogastric meat consumption and obesity/diabetes epidemic.
(2016) "The ω-6 series of fatty acids, which includes arachidonic acid (ARA, C20:4) and its precursor linoleic acid (LA), constitute a growing part of the lipid intake in western diets for the last 40 years. The first cause of this trend is the higher consumption of animal products. White meat especially provides the highest quantities of dietary ARA." (web search - Thomas Dietary arachidonic acid)
Excerpt from Page 56 of 'Omega Balance' by Australian zoologist Anthony Hulbert, PhD (2023) "The contribution of pork and poultry' to animal-sourced foods was 20 percent in 1961 and 41 percent in 2018…Between 1961 and 2018 there was a dramatic worldwide increase in the supply of fats from sources that have very low omega balances. Fat from 'pork and poultry' was greatest in North America for the entire 1961-2018 period, while for Australia and South America, the contribution from 'pork and poultry' was the World average level in 1961 and showed the greatest absolute increases (about 16 g) over this period to be similar to North America and Europe in 2018. There was negligible change in Africa over this period."
(2023) “Poultry meats, in particular chicken, have high rates of consumption globally. Poultry is the most consumed type of meat in the United States (US), with chicken being the most common type of poultry consumed. The amounts of chicken and total poultry consumed in the US have more than tripled over the last six decades… Limited evidence from randomized controlled trials indicates the consumption of lean unprocessed chicken as a primary dietary protein source has either beneficial or neutral effects on body weight and body composition and risk factors for CVD and T2DM. Apparently, zero randomized controlled feeding trials have specifically assessed the effects of consuming processed chicken/poultry on these health outcomes.” (web search - Poultry consumption and human cardiometabolic health)
I made up an information sheet consisting of the above narratives strung together along with excerpts from articles about arachidonic acid research and commentary. Our daughter and her husband, who own a fitness center, gave me permission to leave copies at the front counter for patrons to take home and read. The current manager recently told me that he and his fellow weight lifters were impressed with what I said about chicken meat. After shifting their major protein source from chicken to fish, all reported improved performance and less joint inflammation post workout. (web search - Hulbert The under-appreciated fats of life)
This confirms that it is impossible to analyze data without a perfectly defined hypothesis, itself developed according to a theory built on solid knowledge.
So, if it isn't possible to do an RCT (and long-term multi-decadal lifestyle studies aren't possible as RCTs), then throw out any conclusions from the only practical kind of study that can be done? Isn't this throwing the baby out with the bathwater?
If this were to be widely adopted, I guess studies would be dominated by Big Pharma or the Ag industry or whatever, since they could fund lots of studies and thus dominate the studies that feed into an analysis like this, assuring the outcome.
It seems like this is a software problem. As long as scientists have to perform a bespoke analysis, often a copy/paste from whomever taught them statistics, we will continue getting mostly ambiguous results. It seems there should be some open source effort by software engineers to create some semi-universal scientific analysis program that runs _all_ reasonable analyses instead of just the one or two the scientists are aware of.
I guess that in most cases it's not about completely different methods - which often depend on the available data - but more about the assumptions: models, estimates, significance, censoring, etc.
But I agree with the principle: if researchers - and journals - acknowledged that their analysis is just one in a million, lots of things in medicine and health policy would improve.
Seeing results from a variety of specifications provides additional information on how robust the results are. I've used bootstrapping in some of my analyses. Bootstrapping provides information on whether the results will be robust with respect to different samples. However, the problem with observational studies is that biases are introduced because people self-select rather than being randomized into treatment or control groups. I don't see how this new methodology compensates for self selection bias.
This is very interesting. It should set the floor for any future publication of a “positive association”. And hopefully this will become the standard for observational research. Do a test for association in multiple ways….then tell us why you chose those particular ways out of the total denominator of possible options….and tell us the results of each of those ways. Then if you find a significant portion of those pathways still points to a significant association….THEN you might have my curiosity. I suppose it would be a retrospective randomization of potential confounders….of sorts.
I think the value of this approach is that it demonstrates the fact that observational studies are essentially worthless. The elephant in the room with observational studies is the quality of the data. Nutritional data is especially unreliable. I don't really understand how one can generate a quadrillion ways to analyze a data set that contains two variables but I am glad to see evidence that any given study can be disregarded. In this case I give them credit for coming to the right conclusion---that consumption of red meat has nothing to do with health or disease. This valuable insight needs to be extended to include everything else humans consume. But we already knew this from the considerable research that delineated the processes of digestion and absorption of nutrients---one of the best worked out areas of physiology.
"In this case I give them credit for coming to the right conclusion---that consumption of red meat has nothing to do with health or disease." No, that is the wrong conclusion and is not the one reached by Wang et al. I find it depressing to see their discussion misrepresented with this kind of conclusion, one which is completely unwarranted and an example of "spinning knowledge out of ignorance" in the form of nullism: Inferring there was no effect when the correct inference is the data can't answer the question of whether there is an effect or what direction it might go.
This kind of misrepresentation also occurs routinely in randomized trials when a result with p>0.05 is described as "the trial showed there is no effect" but the interval estimate actually shows that clinically important effects cannot be ruled out using the same "nonsignificance" criterion. It seems that the compulsion to draw conclusions about an effect will override correct interpretations, revealing a problem deeper than any statistical limitation of data: Human allergy to uncertainty. That allergy will lead to misinterpretation of more sophisticated analyses in the same manner as conventional analyses.
Specification-curve analysis and other methods long predating it (such as sensitivity analysis, bias analysis, and uncertainty analysis) exemplify what has been known by some for decades: Once we account for all the uncertainty sources, including uncertainty about which model to use as well as about uncontrolled confounding and measurement errors, the most we can conclude is that dietary questionnaire data provide little to no useful information about the effects of specific dietary components or nutrients. There have been over a quarter-century of such demonstrations; e.g., for one using different methodology and data, see 'When should epidemiologic regressions use random coefficients?' Biometrics 2000;56:915-921.
Thank you for your usual thoughtful and well-reasoned reply. Perhaps I should have phrased it differently. I was referring to the author's description of the article's conclusion. In my opinion it is logistically impossible to carry out a scientifically valid study on diet and disease in a free-living population. My opinion that consumption of red meat has nothing to do with health or disease is based on existing knowledge about the physiology of the human digestive system and the pathophysiology of disease.
Thank you for your measured reply. I nonetheless think it is too sweeping to say "it is logistically impossible to carry out a scientifically valid study on diet and disease in a free-living population." There have been trials in which dietary interventions have been randomized among otherwise "free-living" participants. I suspect you meant that purely observational studies without interventions do not yield trustworthy estimates of diet and nutrient effects. While that is often the case, such studies have yielded vital clues about diseases from nutrient deficiencies (e.g., scurvy, pellagra, goiter) and excesses (e.g., toxicities from oversupplementation) in special situations.
The problem I see is that such situations are uncommon in most modern populations, and so researchers have turned to studying relations too subtle for observational studies and even feasible trials to discern in general populations. The nutrient ranges in those populations may include suboptimal values, but those are not manifested by obvious syndromes that can easily rise above noise and bias and then confirmed as deficiencies via experimental interventions.
To be fair and honest, I fail to see how your claim that "consumption of red meat has nothing to do with health or disease is based on existing knowledge about the physiology of the human digestive system and the pathophysiology of disease" is any different in its excessive certainty from the opposing claims that consumption of red meat has much to do with health or disease, claims that proponents also say are based on existing knowledge about the physiology of the human digestive system and the pathophysiology of disease. There are proponents in both directions, making similar declarations that extol and condemn red meat. Few consider that there are likely important differences across individuals and populations (e.g., based on age, physical activity, pregnancy, lactation, etc.).
A range of opinions does not mean that some middle ground of "no effect" is correct; it means that there is no scientific consensus (just as there is none about say dark matter/dark gravity), and that excessive certainty in any position is the phenomenon we should be most worried about. When I look at the studies and reviews about specific diet components and nutrients (including trials) it seems more like an inkblot test, with various sides projecting what they are already convinced of or want to believe onto data that can be analyzed, criticized and interpreted in manifold ways. Perhaps that excessive certainty is (again) just the human allergy to uncertainty, which must dominate when effects are not obvious. Even the enormous adverse effects of smoking on health were argued about for centuries; when evidence finally reached an overwhelming level in the 1950s it was still met with ferocious resistance among some academics - including RA Fisher, who also rejected observational studies of causality. Given that history, the idea that such studies could force consensus about optimal nutrition and health seems naive indeed.
I plead guilty to an excessive degree of certainty. Perhaps the difference is due to our different perspectives. I assume that you are a research scientist and, as such, are rightfully concerned with absolute precision. I was in clinical practice of medicine for about forty years---mostly cardiology but also a fair amount of Internal Medicine. Patients would want to know whether they should restrict their diet or, more importantly, whether they should take medications to prevent diseases and they often did not deal well with uncertainty. Given the degree to which they were subjected to an overwhelming amount of media promotion for certain drugs I may have tried to balance the argument with some over statement on my part. Obviously I didn';t have the time to go into long statements of physiological justification for every recommendation I made.
I could do so for the claims I made here about diet and health and the admonitions against red meat but that would require more than a brief comment.
SG had a tantrum over nothing. They She He found it “depressing” that YOU came to a conclusion of status quo when SG didn’t say there was a reason to conclude anything. You must never come to a conclusion that could make research funding more difficult and make the work less needed or valued. So shame on you ENC. 🤪
That was the most measured tantrum I've ever encountered cA. ;)
I probably missed it, but how long did this study take and what was the cost? I have a feeling they are both prohibitive to the prelaunch of new medications. And like someone else posted, would a trial of this magnitude be valuable in studying the effects of eggs, coffee, red wine, blueberries, etc.?
Stay tuned to tomorrow’s podcast. We discuss that question. Teaser. It’s not super hard.
This sounds so promising to a non scientist like me. I have wondered before whether information this is easier to find with AI. Couldn't you give these parameters to a computer and have them reveal the highest quality data? And, presuming no bias, wouldn't the computer want to find the quality data?
I couldn't care less what the "scientists" concluded. I eat more meat than anything else. For decades these clowns have told us that eggs, dairy, coffee, fats, cholesterol or something was dangerous to our health. The only thing that is dangerous is listening to this clown show of pretend experts.
What if they studied red meat from a cure perspective? What cases of disease can be cured with red meat? What cases of disease can be cured by stopping consumption of red meat? This is no longer a "statistical study" it has been reduced to a study of counting actual cases. No complex variations of statistics are required.
However these "real" studies face mountains of illogic.
First of all, cured is not medically defined for any disease that might be cured with red meat. Cured is not medically defined for any nutrition deficiency.
Second, cured is not defined for any disease caused by toxic effects of red meat. Cured is not medically defined, at present, for any "poisoning" disease.
And in addition, cured is only medically defined for approved medical treatments. Stopping or adding red meat is not an approved medical treatment.
Even when people are cured, each cure is a single case, an anecdote. And anecdotal cures are not valid in Evidence Based Medicine. "CURED" is not even medically defined in EBM.
In summary, even cures that occur cannot be detected. They are out of scope.
The study might be expanded to show "benefits" or "harms" to patients who were not consuming red meat - provided by consumption or red meat, and benefits or harms to patients who are consuming red meat - provided by stopping consumption of red meat. Then we could take next steps to analyze why red meat provides harms, in what situations, and why it provides benefits in some situations. But the answers are pretty obvious. People who are suffering a wide variety of nutrient deficiencies can receive benefits from consuming red meat. We already know this, so there is no point in the study. On the other hand, people who are eating too much of all foods would receive some benefits - by stopping consumption of red meat if that was the only change in their diet. They might also be harmed by the change - obese people tend to be malnourished in specific ways and cutting red meat could exacerbate these cases.
But... These are real cases. Each real case is a story that can be analyzed individually to come to a conclusion. Conclusions can be collected and analyzed collectively, but for one problem.
Single cases, single stories are anecdotes and anecdotal evidence is not considered valid in Evidence Based Medicine.
To your health Tracy
Author: A New Theory of Cure
I concluded a while ago that observational studies aren’t worth the electricity it takes to store them. They give authoritarians a rational to rule over us: pressure us to spend money, force us to wear masks, take vaccines we don’t want, close down businesses. They do this even when RCTs are available that paint a very different picture.
One motivation is to create the illusion that they are protecting us from the dangers of the world, unlike their opponents. First decide the policy, then select from a near infinite number of studies that justify the policy. This isn’t a conspiracy, it’s just the lowbrow behavior that emerges from a less than ethical establishment.
The other great motivation is money. Observational studies bring lots and lots of money: useless tests, therapies, and pharmaceuticals. People waste hours of their lives watching meaningless videos, with lots of impressive jargon, claiming this or that based on observational studies.
The most disgusting aspect of this is that when a rare bird comes along who tries to warn the public: Vinay Prasad, Tracy Hoeg, Gilbert Welch, Robert Whitaker, Clare Craig, the attack machine tries to destroy them, and the attackers are usually MDs.
We live in predatory world; you had better learn to protect yourself.
My name for it is 'policy based evidence' - with the desired policy in mind peck around like a demented chicken to find enough evidence and expert opinion to shore it up and sell it to the politicians and media.
But it requires a high level of groupthink too; the last thing you want is some dissident type banging the table and going on about *proper* evidence, especially when they turn out to be right! It's essential these individuals are eased out of the organization one way or another.
By the way a close cousin of this practice is 'consent manufacturing'...
One of my favorite examples:
Early in the pandemic, all the health care professionals told us masks don’t work. They based that on a series of RCTs that had been done over the years, showing no benefit. But policy makers started insisting that we should wear masks anyway. All of a sudden science had decided that masks work after all. In fact, the head of the CDC at the time declared that masks work better than vaccines, and the vaccines hadn’t even been invented yet. He was probably right in strange way: 0 > -1.
What was this new science? Scott Atlas, the one honest person in the covid policy team tells us. He asked Deborah Birx why the sudden turnaround. She said her team had discovered 2 mask wearing barbers, infected with covid, but didn’t infect a total of 139 of their clients tested. So, the most influential health care professional in the county, advisor to the president, discarded decades of RCTs in favor of an uncontrolled observational study with an N of 2.
And soon we had forced masking. People who objected were politicizing, didn’t believe in science, didn’t care about others. If they can bend science that badly, that easily, there is no limit to how science can be distorted, and our corporate media plays along.
Yes, I regard the public masking requirements as more likely to be counter productive, because the false certainty it can give to high risk individuals in high exposure situations.
It's far better to reduce prolonged face to face contact indoors where possible, but OTOH there's no need for hiding at home 24/7 due to silly lockdowns either.
Probably the best place for it is done or directed by healthcare professionals usually in healthcare settings like hospitals and carehomes. But only as the situation really requires it - not letting families seeing dying loved ones due to the lunatic policies of health administrators is unforgiveable.
Great post. I still wish there were awards for scientific papers with punny titles.
Good grief no. The entire field of scientific enquiry has been distorted by the desire to run trials with cool acronyms ;)
Gorf I'm with you! But alas, I love a good acronym.
I enjoyed reading this post of yours but cringed and had rigors when I saw you use the latest "buzzword du jour" -- I refer to this SPACE thing. All of a sudden, and for mysterious reasons, plenty of folks no longer talk or write about (for example) some development in the field of cardiology; instead they feel compelled to use the precious verbiage, "cardiology space". Ditto for just about every other discipline or work activity that can be imagined for the human race.
Instead of saying that I took my Allen Edmonds loafers to a competent shoe repair shop last week, it is apparently now de rigueur to say instead, "I took my Allen Edmonds loafers last week to a guy who is very active these days in the shoe repair space". If you think I am being hyperbolic here, please think again! The unctuous, highly paid cretins who dominate healthcare administration in our country have recently added the noun SPACE to their list of automatic bullshit terminology. In other words, using the noun "space" is now a big fad in the Healthcare Administration SPACE. God help us. Please.
Add “reach out” to the hip new terminology that gags me every time I hear it (as in, “Reach out to us if you need help”). Jeez!
Tomayto - tomahto..
I am with you on the overuse of the term space. There are a gazillion others too. But I give Dr Mandrola a pass. Language has its fashions and trends and often without thinking we end up including these expressions in our own language. I have been living in Texas for 28 years and have resisted saying Y’all. I actually made a conscious effort not to, and now after all that effort Y’all is used by everyone everywhere. I look to Dr Mandrola only for medical expertise not language use. Although I think my red line is “chest feeding”. Chest feeding is actually on the CDC website last time I looked. I hope they have removed it in embarrassment and shame. Pregnant people. There’s another one. These new trendy expressions deny biology and logic. “Space” is more of a business expression. It replaces “market”. Both space and market turn medicine into a profit and loss business (and let’s not go there right now). Anyway, I am on team Mandrola, team logic, and team science. How about that, I just deployed a trendy language usage!
I'm glad yawl decided against going into the Yawl Space.
I love the yawl space. I'd love a space yawl even more.
I know this isn't the point of your article, but nevertheless it's important to always examine all aspects of validity. With nutritional epidemiology, a major flaw is the way food intake is measured. The usual methods are food records, food frequency questionnaires, and 24-hour recalls; and they are often not done continuously. These methods are known to be quite unreliable. They also don't consider the fact food is not eaten in isolation, but within a food matrix that can vary across individuals and also affect outcomes. Regardless of the type(s) of analyses chosen, garbage in = garbage out.
Let's not even asked what kind of red meat it was. because I believe that the quality of the meat makes a difference. And also, potential comorbidities of those who died. I mean, come on, what is the point of this analysis when you're taking so many general statements about what you're studying?
I always wonder this too when I see ‘red meat causes X’ stories. Is it really the red meat per se, or by saying ‘red meat’ is it people eating a lot of burgers, sausage, and bacon that are also eating potato salad and mac n cheese and plenty of booze with the red meat? Is lean red meat ever studied on its own?
I was speaking more of grass fed beef not what you buy in the grocery store. I haven't bought meat in the grocery store for at least 10 years. I advise against it.
AND if you go out and eat (which I don't) what kind of "meat" are you eating? You have NO idea!
Years ago the Wall Street Journal published a sushi expose that tested the DNA of various super-expensive varieties of sushi from high end establishments. Duh: you most certainly do not get what you pay for.