Debunking The Link Between Red Meat & Type 2 Diabetes (Avoid This Food Instead) | Dr. Mark Hyman

Sugar and refined carbohydrates is the primary cause of type 2 diabetes. So when you hear the headline, red meat is linked to causing type 2 diabetes, it's BS. Over the years, my perspective on red meat has changed. I used to be vegetarian, vegan, but I've noticed after looking at the literature and the experiments myself, my patients and treating them using this approach of a high quality, low glycemic, fiber rich food and vegetable rich diet with lots of nuts and seeds, good fats, and moderate amounts of healthy animal protein, which I would say is regeneratively raised meat, pasture raised chicken, safely raised fish, regeneratively raised fish, or small fish. It's fine, okay? There's nothing to worry about. Lean red meat doesn't contain sugar. It's not a plausible link to diabetes. And it's sugar and refined starches and grains and ultra processed food that cause diabetes. So how do we think about type 2 diabetes from a functional medicine perspective? What's the root cause? Functional medicine is all about root cause. The root cause is something called insulin resistance. And this comes from eating a diet that's high in sugar, refined flour, grains, ultra processed food. There's no doubt about this. Also from lack of exercise and being sedentary, not moving enough, or being under muscle, right? Muscle is your metabolic spanx, according to my friend JJ Virgin. And how do you address that? Well, you eliminate ultra processed food, processed grains, refined grains and starches, sweets, sugar, sweetened beverages especially, and that improves your blood sugar balance and your insulin sensitivity. And what should you be eating then? Good quality protein and it can be meat. Okay, that's my view of the literature, not my opinion, but it's pretty much evidenced by the randomized controlled trials. Fiber, Fruits, vegetables, nuts, seeds, sometimes whole grains if you're not fully blown diabetic. Healthy fats, olive oil, avocado oil, macadamia oil, none of these will affect your blood sugar. And then you want to use testing to test your fasting glucose, your fasting insulin, your A1C, triglycerides, and other markers to understand of your insulin resistance. Now, I co-founded a company called Function Health. You can go to functionhealth.com We've created an initial test of over 110 biomarkers. It's $499 a year membership and includes testing twice a year. And you get all the metabolic markers you need. You get insulin, which your doctor almost never tests, A1C, your blood sugar, but you also look at lipid particle size, we call lipoprotein fractionation, not just your regular cholesterol profile, but whether or not you have small particles, dense particles, large or small triglycerides, or HDL, all these will tell you about your cardiometabolic health. We also measure inflammatory markers like C-reactive protein and others, so you get a really good understanding of where you're at. So go on and check it out. functionhealth.com. you can use the code young forever if you want to jump the wait list, but it's really a way to get testing to see what's going on with you and what's going on with your diet. So again, test, don't guess. Now, it's no secret that navigating the realm of nutrition has become a challenge for the general public, and even for people like me and health professionals who've been studying this for 30 years. One week eggs are good for us, only be vilified for allegedly raising cholesterol levels the next week. the narrative on dietary fats is no less tumultuous. I wrote a whole book on this called Eat Fat, Get Thin. Some experts say that it's the chief culprit behind heart disease, others say it's critical for overall health and well-being. Well, more recently, a study made headlines linking red meat consumption to an increased risk for type 2 diabetes, leaving the public once again confused and understandably so. And that's why in today's Health Bites episode, we're diving deep into the findings from this paper. and unpacking the study's design flaws, its inaccuracies, and where the researchers got it straight up wrong. The study was entitled Red Meat Intake and the Risk of Type 2 Diabetes in a Prospective Cohort Study of United States Females and Males, published in October of 2023. Now, this was a type of study design. It's important to understand study design because you have to understand science before you can interpret science, and you have to understand the type of studies that are done and which can show cause and effect, and which can show correlation, not causation. For example, every day I wake up and the sun comes up. It's 100% correlated, but it's 0% causal. If I die tomorrow, the sun's going to keep coming up. If I slept through the middle of the day, the sun's going to keep coming up. So it has nothing to do with each other. And essentially, that's what these observational studies like this particular study did. They looked at correlation not causation. And that means that we can't prove cause and effect. So when you hear the headline, red meat is linked to causing type 2 diabetes, it's BS. Okay, we have to look at what the data show and what it doesn't. And these studies are not wrong, they're not bad to do. They're done in order to help us understand what might be a useful avenue for further research, right? They're not the end of the research. They're useful for generating hypothesis. For example, in the study of smoking and lung cancer, they did observational studies, right? They weren't gonna do a randomized controlled trial because they're not gonna put half people on cigarettes and have people on not on cigarettes. So basically they found that there was a 20-fold increase, maybe 10 to 20-fold increase in the risk of lung cancer in smokers. Now to put that in perspective, that's a 1,000 to 2,000% increase in your risk of having a particular disease and that ended up being correct because it was such a strong correlation. Whereas in this Red Meat Diabetes Study to cut to the punch, it was about a 20% increase, right? Which essentially is relatively meaningless. And let's just say 200% increase in a correlation study, you pretty much wanna ignore the data. And Dr. Ioannidis from Stanford has written a lot about this. This is an incredible scientist who's, I dissected the value of different types of studies and what we can learn from them and what we can't. So we have to start out really understanding that the study was not designed by his very nature, which all scientists would agree to prove cause and effect. It's just the nature of science. Okay, so let's get into the study. This is what we call a prospective cohort study. And it's an observational study, a population study, an epidemiological study all means the same thing. Essentially, it studies a group of individuals over time to look at the association between certain exposures, behaviors, diets, and risk factors on specific outcomes. So basically they tracked thousands of people over many, many years, looked at what they ate, and saw if there was a correlation with diabetes, and lo and behold, they found one. But let's talk about the problems with why this may not actually be as clear as a study seems to generate. Now, in this type of study, basically people are identified based on their exposure status, and then they're followed over time to observe and record outcomes. In other words, what did people eat over many decades and what was that diet and was it correlated with any bad outcomes later in life? So you follow people for 30 years, you have them track their diet records, which we'll talk about in a minute, and then you see whether or not a particular food or types of food seems to correlate, not cause, correlate with some bad outcome like diabetes, and that's what they did. And basically the goal is just to assess relationships between various insults, exposures, toxins, smoking, diet, whatever, and outcomes. So it essentially looks for things that may be worth further studying with a randomized control double-blind trial. Okay, this was not done here. Now, it can be helpful, but they say, well, we're gonna control for variables, we'll call confounding variables, which means things that kind of can throw the study off. In other words, we'll talk about this, but for example, there was a study done many years ago by the NIH and the AARP, the American Associated Retired Persons, that looked at meat eating and chronic disease and death and cancer and so forth, they found a big correlation. But that study showed also that the people who ate meat didn't care about their health and smoked more, drank more, ate more calories about in here more day were more overweight, didn't eat fruits and vegetables, didn't exercise, just drank more alcohol, didn't take their vitamins. Of course they had more disease. It wasn't because of the meat. It was just a, we call it a problem that was shown because of these confounding variables. And we'll talk about more about that. Now, this study was published in the American Journal of Clinical Nutrition, and it was published by folks at Harvard who are great scientists, but they're focused on epidemiology, particularly at the School of Public Health, which is where the study was published out of. And unfortunately, people have bias, and the study authors are very biased toward a plant-based diet. And so right off the bat, you kind of look at, all right, well they already have a bias, and that affects the outcome study. so basically the objective of the study was to assess the link between total processed and unprocessed red meat intake and type 2 diabetes, and then to estimate the effect of substituting different protein sources like vegetable proteins, nuts, seeds, beans, grains for red meat and type 2 diabetes risk. So we're doing, but again, just a hypothesis generating study. Now, again, this was a population study. It was based on the Nurses Health Study, which was about 216,000 participants, the first and the second one, and the health professionals follow study. which was including men. Now, the first study started in 1976, female nurses and then another one in '89, female nurses and the health professional study was started in '86. And they followed people for a long period of time. They calculate the amount of years and people and they come up with a number called 5.4 million person-years. So that's pretty good. And what they did was really interesting. They looked at something called a food frequency questionnaire. And this assesses that people's diet every two to four years from the baseline. Now, can you remember what you had last Thursday for lunch? Okay? Can you remember the amount of this or that you had over the last week? Probably not, right? And so these are flawed tools and there's a lot of research and science about how flawed these tools are and how imperfect they are and how often they are very misleading. We see that in this study. So the study findings, right, just to to be clear, and this is association, correlation, not causation. They found between the lowest and the highest red meat intake, there was a risk of diabetes that went up by 62%, right? Not 200%, 62%. Processed meat associated with 51%, and unprocessed red meat was about 40% risk. If you substituted one serving of nuts or beans then your risk was 30% lower. If you substituted for processed red meat, the risk was 41% lower, and unprocessed meat was about 29% lower. So they're basically saying if you had one serving of dairy for total processed or unprocessed red meat, you had a lower risk of type 2 diabetes. Now, this study is really important because it kind of misses a lot of the point. What is the mechanism here? Now, they try to explain some of the mechanisms, but pretty weak. We know that the sugar that you eat, sugar and refined carbohydrates, is the primary cause of type 2 diabetes, not red meat. And ancestrally we've been eating meat for as long as we've been human. I just came back from the Masai population in Africa, as I mentioned on different podcasts. And these people ate the blood, the milk, and the meat of their cows. That was their main diet. They were healthy, they were super thin, they were very fit. and they had no diabetes. I recently visited their community and the Coca-Cola truck drives up every day. They get processed cookies from the local town that are made by the industrial food system. And now they're gaining weight and type 2 diabetes is rampant in this Maasai community in Africa. And it's just heartbreaking to see that within minutes, this entire Coca-Cola truck, a big truck, just was emptied out by the local population, not knowing what they were doing themselves. And they didn't even know that it was connected. so, you know, this basically, this study fueled a lot of clickbait headlines. For example, WebMD said, just two servings of red meat per week raises diabetes risk. Well, that doesn't, it shows that it's correlated but not causing eating red meat. Sir, more than once a week is linked to type two diabetes risk. That's CBS. This is just bad reporting and bad journalism. And the social media was just all over the place, right? Some people were pro-red meat, some people anti-red meat. People are super confused and then nobody knows who to believe. and everybody's distrusting public health and dietary guidelines, and it's just a mess. So I'm gonna try to unpack it for you so you really understand how to think about this and also how to actually know what to believe around this whole issue of red meat and diabetes and what we know. So basically the problem with this study, as we mentioned, is an observational study. And we just cannot draw conclusions from an observational study. It doesn't prove causality. And we have to look at also the limitations of the study. right? There are a lot of limitations. The study authors, for example, as I mentioned, are very biased toward a plant-based diet and veganism. They're, the, how they pick the, the participants of the study, which may not be an issue. Industry funding we want to look at. That probably was an issue here. But there's, there's this thing called recall bias, which is common with food frequency questionnaires. The people are more likely to report healthy food than unhealthy food and, and desserts, sugar, sweetened beverages, alcohol are underreported. This is we're going to put all the references for everything I'm saying in the show notes. So have a look at those. Everything I'm saying is documented, is well researched, and you can kind of dive in, but would take me about 10 hours to cover every study in detail. So basically, you know, I, I thought it was my practice. People overestimate how much extra they exercise and they underestimate how much they eat. It's pretty difficult. By humans are pretty flawed. Now, the 2012 study from red meat consumption and mortality. And they looked at prospective cohort studies from the people who ate a lot of red meat, about the highest 20%, had a 45% high risk of dying from heart disease compared to those who ate the least red meat, the lowest 20%. However, when they looked more closely at the people in these extreme groups, they noticed that besides eating red meat, they had other habits that made them more likely to have heart disease, like don't exercise, they eat too much, they smoke, their cholesterol is worse. Or they maybe had fish consumption which affected their health and risks. For example, maybe the people in their lowest risk group exercised and didn't eat meat, but they also didn't smoke and they also ate healthier food. So you can't quite tell what's going on. So the study supports the idea that eating a lot of red meat is linked to high risk of heart disease. People who choose to eat more or less red meat have other lifestyle issues that influence their health. Now, there are other factors, these confounding variables I mentioned. When you look at confounding variables, they try to control for these, but it's really tough. And they only control what researchers think to control for, and it basically makes it really hard to determine true cause and effect. Like I mentioned with the ARP study, they smoked more, they drank more, they ate less fruits and vegetables, they didn't exercise, they had all these other issues. That's why they had more disease, not because of the meat. So, it's basically, other issues with the study could be design flaws, and maybe the study population is different from the regular population, so it may not be widely generalizable. And also, they do all these weird statistical calibrations to normalize the data, and we're going to talk about what that means. And they did this in that study. There was, I think, a scientist named Roger Williams who said, there's liars, damn liars, and statisticians, or maybe that was Mark Twain, I don't know. But I think it's true, you can kind of manipulate the data to make it show what you want. And that's clearly been done here. And the other thing this study does is it actually supports dietary guidelines to limit red meat consumption. And why does it say that? Well, I mean, the study basically said, our study supports this current dietary recommendations for limiting the consumption of red meat intake and emphasizes the importance of different alternative sources of protein for type two diabetes prevention. But dietary guidelines, just like this study, are heavily based on observational data, the data that can't prove cause and effect. The systematic reviews and meta-analysis of observational data are the weakest types of studies. There's confounders, there's bias, there's a lot of problems with the studies. Often the researchers have ties to industry, the expert panels are not independent. It's a mess. How do we know what to do in science? Well, randomized controlled trials are the gold standard for drawing causal inferences between exposures and the outcomes. For example, you give people placebo or blood pressure drug who have high blood pressure and you follow them for three months and you can see, okay, well did the people taking the placebo lower their blood pressure or the people on the pill? That's a randomized controlled trial and you randomize people so they're not stacking the deck in favor of healthier or sicker population. Now they're hard to do in nutrition because you need to control everything and it's really hard to do. It's great in a lab rat, but it's not really easy in humans because they're what we call free living and they do whatever they want. so you say, well, I want you to eat a low fat diet, or I want you to eat a low carb diet, or I want you to exercise 150 minutes a week, or I want you to not smoke, or I want you to sleep eight hours a night, or whatever you want, you tell them, they're not going to probably do it. And it's hard to do. You'd have to basically put people in a locked metabolic ward and put them there for years and give them the food that they eat and track everything they do in order to actually know what's going on, like a lab rat. But we really can't do that. We can't take, you know, 10, 000 people and feed them a vegan diet and 10,000 people in Feed a Mate omnivore diet, including red meat and healthy foods, follow them for 30 years and give them all the food and track that. It would be billions and billions of dollars and impossible to do. So it's not practical, it's not ethical, it's expensive, it's hard to recruit volunteers for this. And people just, it's hard to do these nutrition studies. So we have to do the best with the data we have, which are systematic reviews and meta-analysis of randomized controlled trials. mechanistic studies, lab studies, there's many different levels of evidence. So you have to look at the total community benefit of all the evidence. So now let's dive into this problem of study design and what was wrong with this paper and why it does not prove that red meat causes type 2 diabetes. So what they did, as I mentioned before, they gave them a food frequency questionnaire. They're highly inaccurate, right? Every two to three years people get asked, what do they eat? And they got a questionnaire, what's your average intake of food and beverage over the last 12 months? You know what you ate over the last 12 months? I couldn't have a clue. I mean, how often do you remember eating X and Y food? Right? Do you eat chicken with the skin on or without the skin? Do you eat hamburgers, hot dogs, processed meats? They give all these questions. They also, you know, kind of weirdly track things like beef, pork and lamb as a sandwich or mixed dish, but no serving sizes were noted. You know, sandwiches and lasagna have also bread and pasta and processed carbs. So is that part of it? we don't know. So they basically kind of looked at, you know, what they were eating. The second issue is, and by the way, I can go way more into these food frequency questionnaires, but just trust me based on the data. We'll put the links in the show notes. They're really highly inaccurate. They've really been proven to not be a good tool for looking at nutritional intakes over time and don't really correlate with a valid metric for tracking outcomes. So right off the bat, it's a tough study to do. the second issue, and I kind of mentioned it, is that the red meat definition included sandwiches and lasagna, which basically were counted twice and as processed and unprocessed red meat. Now, processed red meat is hot dogs, bacon meat sandwiches, sausage, unprocessed red meat is like hamburgers, beef, pork, lamb, a sandwich. So it's kind of weird. They kind of included other foods in the meat. So you have to be clear. The, the third issue is the serving sizes changed over time. And why? Because the, the food frequency questionnaires were different in the different parts of the study. So one was in 1980, one was in '84, one had 61 items, one had 120 items, and they basically changed the definitions of what a serving is, even in these food frequency questionnaires. So it's super confusing. So the nurses in the study asked how often they consumed two slices of bacon. Now the serving size of bacon is one slice, but before it was two slices, right? How do they adjust for this? One serving of processed red meat, it's considered 45 grams. How did they measure it? Did they weigh their lunch meat? Did they take their bologna or salami and put it on a scale? I doubt it. What about chicken, beef, pork, or lamb? They say six to eight ounces was a serving. Today, one serving is three ounces. Did they know this? Did they translate a three ounce serving to a six to eight ounce equivalent? Probably not, and it creates more error in the studies. Issue four in the study was that this is really crazy. They use statistics to massage the data to have the outcome they want. It calls this process calibration. We're calibrating the results using a seven-day weighted diet record and food frequency questionnaire from two other population studies. In other words, they acknowledge that food frequency questionnaires are not that accurate, so they're going to use other ones to correlate and see if they can create this mishmash of data to show what they want. So what they found was that, this is kind of crazy, the calibration doubled the effect for total red meat, processed meat, and unprocessed red meat. So before the calibration, for example, one serving, an increment of total red meat was associated with a 28% high risk of diabetes. After the calibration, it was 47%. Before the calibration, one serving increment of processed red meat, was associated with a 50% high risk of diabetes after it was 101%. So it's like, what are you doing here? Right? So guess what number was reported in the headlines? Not the uncalibrated, but the calibrated number, right? Too much red meat is linked to a 50% increase in type 2 diabetes. Well, in NPR, they didn't really do a good job of doing a review of the study. They didn't do investigative journalism, which I think is sorely lacking. And basically they found that this 50% increase in red meat. So like I said, before the calibration was 28%, after it was 47%. The next issue was the authors compared the lowest intake of red meat to the highest intake, but have historically reported the risk using servings and for example, which is a more quantitative metric. So to explain what that means, in the 2011 paper, another one called Red Meat Consumption and the Risk of Type 2 Diabetes, Three Cohorts of US Adults and an Updated Meta-Analysis, they report a 12% risk of diabetes for one serving and a 32% for processed meat and 14% for total red meat. But this paper compared the highest and lowest intakes claiming a 51% increased risk for eating unprocessed and 101% increased risk for processed and 40% for total. But basically this method using qualitative versus quantitative generated a lot more headline-worthy statistics. In other words, the way they reported this, it just makes it more sensational and look better for the agenda of having a study show that red meat causes diabetes. Another thing with this study is the women in this study, right, the nurse's health study compared to the men in this study, show that the women ate more red meat than the men. Now, this is the first study ever to claim this. Now, typically every other study has shown the opposite. So what does that mean? Well, I don't know, but it just seems to kind of be a a clue that maybe the study is a little wacky and doesn't comport with all the other data we have around meat consumption and being female and male. The next issue was the total red meat intake had a higher risk of diabetes than both processed and unprocessed red meat. So that doesn't make sense, right? How could the total red meat be worse than the individual types of red meat when the total is the sum of both of them, right? So you don't get like 1 plus 1 equals 3. It doesn't make sense. So most studies are looking at the risk associated with red meat show that processed meat is riskier than unprocessed red meat. In total red meat, the sum falls in between, right? So if you have processed red meat being higher risk and unprocessed lower risk, the average risk is going to be lower, right? Counting my combination. But in this study, they found the opposite, which doesn't make any sense. If red meat, this process makes you have a higher risk of diabetes and unpressed red meat lower, then if you add them together, you shouldn't have a higher risk when you combine them. So it doesn't make sense. The next issue of the study was what we call healthy user bias. And I think this is really, really important. Essentially, it's talking about what I mentioned earlier, which is the idea of confounders. this idea of why were the people in the study having more diabetes or not? Was it because of the meat they were eating or a bunch of other habits? The people in this study, when you look at their characteristics, they had much higher body mass index. In other words, they were heavier, they were less physically active, they were more likely to be smokers, and they were less likely to take vitamins. Of course, they're going to have more risk. The healthier people, didn't eat red meat. Why? Because they thought that red meat is bad. That's the propaganda that we have in our society, which is red meat causes heart disease, red meat causes cancer. So we should be eating less meat. In fact, we are, which is really another really important point. When you look at the amount of meat we're eating, it's dramatically decreased over the last 30, 40 years, dramatically because the message in the public health domain has been to eat less meat. But at the same time, what's happened? The risk of diabetes has skyrocketed. Right, just double, triple in different populations. So how could that make sense? Red meat's going down, diabetes going up. Okay, well that's a problem. How do we explain that with this study? What was so interesting to me in this study was that they didn't adjust for body weight or what we call BMI. That's nuts because the group that actually had more diabetes was more overweight. Now, was that attributed to the red meat intake? That's what they say that red meat caused you to gain weight. But there's just no data to support that. I mean, they basically said because the likelihood that weight gain mediates at least part of the association between red meat intake and type 2 diabetes, we did not adjust for adiposity in the primary analysis. In other words, they did not actually account for the fact that the people who ate more red meat were more overweight. Now, a lot of other things can cause that, and particularly they do, particularly ultra-processed foods, sugar, and refined carbohydrates. That's clear from the data, not me. The next issue was grains and sugar were excluded from the characteristics table. That's crazy. How do you actually evaluate the effective diet if you exclude the very thing that's causing diabetes, namely sugar and refined carbohydrates? They just said, oh, we're not gonna include that. Okay, we're not gonna look at that. Why? Well, I don't know, but it doesn't make any sense to me. the next problem with this study is that calorie intake was reported extremely low. Now, this doesn't make sense because people we know eat a certain amount of food. They're not all starving themselves. And in the study, they basically excluded people who ate less than 500 calories a day for women or more than 3,500 calories. They just got rid of them from the analysis. The same thing for men, men who consume less than 800 calories a day or more than 4,200 calories a day were excluded. And you can see how do you get these numbers? It's because the food frequency questionnaires are so problematic. People will do all kinds of things that show that they're not actually truly reporting on how much or what they ate because they're getting all these extremes. Oh, men are eating 800 calories a day or 4,200 calories a day. It doesn't make any sense. But what was really interesting is the average calorie intake for women was 1,200 calories and for men it was 1,600 calories. That's not a sustainable diet for people. They're not going to eat that much. They're going to be starving all the time. So it just shows you the flaw in these food frequency questionnaires. They don't show you what people are actually eating. very low averages for healthcare practitioners. People, basically nurses are on their feet all day. So that just kind of makes me want to throw out the study altogether. Because again, how do you rely on data that's so imperfect where your calorie count is so off? So how do you know what actually people are eating? Now the other thing they do is this statistical kind of dance where they focus on what we call the relative risk, not the absolute risk. Now the relative risk is relative to the other population, how much did your risk go up? So when you see 51% or 61%, that's what we call relative risk. The relative risk isn't 2, right? It's probably not significant in an observational study. The absolute risk is how much is the absolute increase in the risk of that disease in a population. So for example, If the absolute risk of developing a certain disease is 5%, it means that 5 out of 100 individuals in that population are expected to get sick. Now, we did this with, for example, processed meat and colon cancer. We said, oh, your risk of colon cancer goes up by about 20% if you eat bacon and processed food. And this is based on observational data. What did it actually show? Your risk of colon cancer went from 5 to 6%. Now, that's a 20% increase. Right? But your absolute risk goes from 5% to 6% in the total population of getting cancer of the colon if you eat two pieces of bacon a day your whole life. So, okay, what are you going to do with that information? Absolute risk is really important. Now, relative risk, as I said, basically is the probability of an event occurring in one group that's divided by the probability of that occurring in another group. So it's basically a ratio, but not an absolute risk. So if it's over one, there's no difference. If it's one, there's no difference, right? If it's greater than one, it shows an increased risk. And if it's less than one, it shows a decreased risk. For example, we talked about the relative risk of smoking and lung cancer with observational studies where it was a 10 to 20 fold increase, which means a 1,000 to 2,000% increase, right? And heart disease is also a pretty big pretty big risk. If you look at smokers, their risk relative risk is two, as I said, 200%. So smokers have about a twice as high risk of getting heart disease and non-smokers. But relative risk sounds good, but it doesn't actually tell the true story. So when you look at the highest versus the lowest red meat intake in this study, the absolute risk, this is not the relative risk, the absolute risk was your risk of getting diabetes went from 0.32% to 0.52%, which is so little, right? You're talking about two-tenths of a percent increase in your risk of getting type 2 diabetes if you eat red meat. Okay, not a very big risk. When they looked at the relative risk in this study, it sounds much better, right? The highest versus the lowest total red meat intake, showed a risk that was 62% higher of getting type 2 diabetes in the high-risk group versus the lowest intake of red meat versus the highest intake. 62%, not 0.2%. Okay? So it is what I mean by the statistics, right? There's liars, there's damn liars, and there's statisticians. So I think you have to really be careful and look at also absolute risk, not relative risk. this sounds better when you say relative risk if you're trying to prove something. The next issue is there are a lot of vested interests in this study. Walter Willett, who's a study author, great scientist, I know him personally, he's a good guy, but I think he's very biased towards a vegetarian diet, including little to no red meat since the early 90s, and he's been leaning much more towards veganism recently, and he's the leader of the EAT-Lancet section on diet and health, which essentially said we should all be vegan. He's published more than 200 papers on epidemiological studies which show association but can't demonstrate cause and effect. He's, for example, found that red meat is bad for your health, that animal fats are bad for your health, that a diet of grains, fruits, and vegetables and vegetarianism is better for your health. He's also published three books that argue these things. He has multiple serious potential conflicts of interest which cast doubt on his ability to bring a really unbiased viewpoint. to the question of whether vegan or vegetarian diet is preferable for good health. Now, Harvard in general condemns animal foods, pushes plant-based diet. And, you know, when you look at who's funding these studies, you know, the American General of Food and Nutrition that actually published this study receives funding from General Mills, which is a big grain maker, the Mars and Bear, it's just there's a lot of conflicts of interest here. Now, the next issue with the study was what's the mechanism of red meat causing type 2 diabetes, right? They do have some explanations, but they're kind of bogus. And all these mechanisms propose that it's a problem of meat driving issues with insulin sensitivity, causing type 2 diabetes. But it doesn't mention the role of sugar and refined carbohydrates, which is so well established in the research in randomized controlled trials and observational trials. So here's the mechanism. Well, maybe saturated fat injures the beta cell function and insulin sensitivity. Now saturated fat, just for a fact, is not a prominent fat in red meat. It's oleic acid, which is a monounsaturated fat. And that's high in oleic acid are linked to much better cardiometabolic health. Palmitic acid, which is in meat, also maybe linked insulin resistance by inflammation and stearic acid is protective against insulin resistance and doesn't really impact your cholesterol. And there's also something called CLA, which is conjugated linoleic acid, which is very protective against cancer, improving metabolic health and many other things. So the diet saturated fat diabetes connection is a little shaky. And also there's really not a clear mechanism here. And I think meat is relatively low in saturated fat. So that's kind of a, makes the argument a little bit kind of less relevant. There are also many, many meta analyses showing that low carb diets are far more effective than high carb diets for reversing insulin resistance. So there's really so much clarity in the literature that if you take someone who's diabetic and you put them on a low carb diet, they burn more calories, they lose more weight, they potentially reverse their diabetes. The ketogenic diets have been used by a group called Virta Health online and found profound changes in risk reduction to diabetes. For example, 100% get off the main diabetes meds, 90 plus percent get off insulin. there's about a 12% weight loss, 60% get complete reversal of type 2 diabetes, totally normal after being severe diabetics. So this is on a very basic, almost zero carbohydrate diet. In 2006, in the British Medical Journal, low carbohydrate diet showed a lower A1C compared to the high carb diet. The greater the restriction of carbs, the greater the glucose lowering effect. And what was so weird about this study is they didn't even look at carbohydrate intake. which kind of is strange because that's the main thing we know causes diabetes. They also talk about heme iron, how that increases oxidative stress and insulin resistance and pairs beta cell function. But heme iron is more of a proxy for a crappy diet. Again, health user biases we talked about. In a meta-analysis by Fang in 2015, he found that heme iron in the context of a standard American diet was linked to cancer, mainly fast food, fried food, but not in the Netherlands, Canada, Italy, France, Japan, and Sweden, because they generally have a healthier diet. So they're not eating the typical standard American or sad diet. So it's not only what you're eating, it's what you eat it with. The next mechanism they proposed was processed meat having a high concentration of nitrates and as byproducts, and those may promote insulin resistance. These nitrates and nitrates, which are basically food additives, they react to form nitrosamines under high heat, and those are carcinogenic and they can increase insulin resistance. But so is it the processed meat or the way the meat is processed? What are the additives? For example, uncured meats in Italy and Sardinia. I've written a lot about this, have very low rates of diabetes. They ate a lot of this. I was there and I ate lots of prosciutto and homemade cured meats. It was quite a scene. In Ikaria, we had, for example, this meat that was, you know, was cured with all these incredible grape leaves and, you know, all kinds of stuff salt from the ocean and this and that. It was like, it was Great, and they don't have any real risk of type 2 diabetes except when they start eating our diet. So it doesn't mention sugar as a mechanism, which is often consumed with red meat, right? If you're eating processed red meat, you're eating a sandwich, you're eating bun, rolls, sugary drinks. So you can't blame what you don't measure, and it's really unfortunate that we don't have this report in the study because we don't know if the people eating red meat also ate a ton of refined sugar and carbs, likely because they were more overweight, right? so it's just the whole thing is kind of, kind of, I don't know, just kind of a messy, horribly done, misinterpreted study. So. But we know that red meat contains no glucose. It doesn't raise your blood sugar. A little confusing why it would increase your risk of type 2 diabetes. And type 2 diabetes is caused by insulin resistance, by high blood sugar, or floor glycemic control. And basically, red meat has no glucose. Now, let's look at the other body of research, because you can't just look at one study. You have to look at it in the context of everything. Now, red meat consumption has been looked at and there was a study, there was sort of a gold standard study, which is a review of meta-analyses of randomized controlled trials. So it wasn't an observational study, it was a randomized controlled trial. This is published in the European Journal of Clinical Nutrition in 23. We're going to put in the show notes. There was no significant impact of diets that contained red meat versus diets with less or no meat on the following things, insulin sensitivity, Fasting glucose, fasting insulin, A1C, which is basically your average blood sugar, the beta cell function of your pancreas, or GLP-1, which we know now is related to weight metabolism and all the new weight loss drugs like Ozempic or GLP-1 agonists. Red meat results in a significantly lower postprandial glucose level compared to diets with less or no red meat. In other words, when you eat meat, it blunts the response of your blood sugar rise. So these are not observational trials. It's a meta-analysis of randomized controlled trials. So this is completely opposite of what the study showed, but it wasn't reported. What was reported was the study that showed red meat causes diabetes. If you have a negative study, it's usually not reported. Such and such doesn't do this. Well, that's kind of boring. But if, oh, red meat's going to kill you, okay, well let's publish that. Let's get PR on that. What they found was actually, small and marginally significant improvements in insulin sensitivity with red meat intake in type 2 diabetes. In other words, those people who had diabetes and ate red meat had better improvement in insulin sensitivity. Another major study was looking at the effects of total red meat intake on glycemic control and inflammatory biomarkers. Now, inflammation causes diabetes, heart disease, cancer, dementia, and this was a meta-analysis of randomized controlled trials published in Advances in Nutrition in 2021. What did that study show? Well, total red meat consumption for up to 16 weeks did not affect changes in the biomarkers of glycemic control or inflammation in adults free of but at risk for cardiometabolic disease. In other words, if you ate meat for 16 weeks in this randomized controlled trial, it didn't affect any of the biomarkers related to your blood sugar or inflammation who were at risk for heart disease. Well, that's important, right? The results showed no effect of total red meat intake on your blood sugar, insulin, something called HOMA-IR, which is a measure of insulin resistance on your A1C, average blood sugar, on inflammatory biomarkers that we really look at carefully, like C-reactive protein, interleukin-6, TNF-alpha. These are really important biomarkers that correlate with heart disease and cancer and dementia. There were no changes in any of these from these randomized trials that were up to 16 weeks in duration. Now, in this study, the research participants in most of these studies were asked to consume lean and unprocessed red meat, in most of the articles. Now, the quote from the study to review was overall red meat intake does not independently influence changes in cardiometabolic disease risk factors in the short term. For those who should choose to consume red meat, red meat, as with all other protein-rich food sources, should be consumed in the context of a healthy eating pattern high in fruits and vegetables and whole grains and within the energy needs to reduce cardiometabolic disease risk. Fair enough. In fact, just to kind of explain that a little bit more, there was a large study of about 11,000 people who shopped at health food stores. half of them were vegetarian or vegan and half of them ate meat. But they ate meat in the context of a healthy diet. If your meat intake is with hamburgers and fries and Coke, well, it's probably not the hamburger, right? It's all this other stuff. So what they found was that in both these groups who basically could be assumed to eating a healthy diet because they shopped at health food stores, both of their risk of death was reduced in half. Well, how do you explain that? They're basically saying if you eat red meat, in the context of a healthy diet, there's really no big deal. There was another study, again, randomized controlled trials that showed the same thing, right? And this study was titled the Effects of Total Red Meat Consumption on Glycemic Control and Inflammation: A Systematically Search Meta-Analysis and Meta-Regression of Randomized Controlled Trials, blah, blah, blah. It doesn't matter. Basically, it's a randomized controlled trial review. So, what they found in the study was those who ate above what's commonly recommended, which is about 0.5 servings of total red meat a day, which is about three three ounce servings per week does not negatively influence markers of glycemic control or inflammation in groups of adults without diagnosed cardiometabolic disease. In other words, if you don't have heart disease or diabetes and you eat more than the recommended amount of meat, it has no impact on your blood sugar control or inflammatory markers. If you loved that last video, you're gonna love the next one. Check it out here. There's no drug on the that can reverse diabetes. We manage diabetes, which is nonsense, because when you understand how the body works, you can work with it rather than against it and activate these healing systems.