[ 00:00:00 ]Dr. Kevin Mackey, welcome to the show. Thank you so much. Glad to be here. Now, I got to tell you how I decided that you were the perfect person, no pressure, to come on the show. I thought to myself, ‘how can we make sense of all the data out there?’ There’s observational data, epidemiology, randomized controlled trials, especially when it comes to nutrition research. I don’t want to embarrass you, but I’m going to read a little bit about your background because it is impressive. You are founder and chief scientist for Midwest Biomedical Research. You specialize in design and conduct of clinical trials in human nutrition, metabolism, and chronic disease risk factor management. You’re an adjunct professor, you’re an eminent scholar in the Department of Applied Health Sciences at Indiana University.

[ 00:00:56 ] School of Public Health. Also, are you ready for this one? You are former president of the National Lipid Association. And again, the list of accolades, you have published more than 300 scientific papers. You function as both an investigator, consultant, statistician. You are a numbers guy. I’m a numbers guy, that’s for sure. Today, I brought you on because I need help. I need help. The world needs help. Clearing up some of the confusion. I’ll do what I can. Okay. Now, just to start, tell us a little bit about your background. Sure. So I started out, I’ll start when I worked in the VA as a scientist. So I was in the Department of Veterans Affairs. Happy there, thought I’d work there for 40 years and retire.

[ 00:01:46 ] Got a new director for the center who said, we’re turning this into a neuroscience center. So he invited me to find other employment. I joined a private research center that was founded by Michael Davidson, a very well-known preventive cardiologist. And then I ran the human nutrition and metabolism research unit there for 10 years. And then I left, started my own private research center, which I sold in 2011. Then founded another private research center, sort of co-founded it. And then we sold that in 2021. So we’ve been busy and we’ve fortunately been able to do a lot of good in terms of developing pharmaceuticals, and a lot of what we did in pharmaceutical development helped fund the research that was really my passion, which is lifestyle and chronic disease prevention.

[ 00:02:36 ] You know, you have published a lot of information on, for example, obviously you’re a former president of the Lipid Association, on cholesterol, red meat, the relationship between these things. And before we dive into that, because we have real questions like, is red meat going to raise cholesterol? How much red meat can we have? Just a number of questions. But before we frame those things up, you have pursued a career in epidemiology. Please tell us what that is and tell us how that plays in the nutrition landscape. Sure. Well, epidemiology, first of all, the word comes from epidemic. So a lot of people think of epidemiology, they think of infectious diseases. But epidemiological methods can be used to study chronic diseases as well. So that’s been my focus. And epidemiology is usually observational research.

[ 00:03:36 ] There are two kinds of observational research. One is sort of descriptive. So let’s say you want to learn about the natural history of the evolution from normal glucose tolerance to type two diabetes. Well, you can just follow people over time and describe what happens. Then you have analytic epidemiology, where you’re comparing groups. And so that’s most of what people think of in epidemiology. And there are two main kinds of studies: Cohort studies. So, you take a group of people, and define them on some characteristic, let’s say body mass index or cholesterol level, or smoking, non-smoking, exercise, sedentary. And then you follow them over time to see if there’s a relationship between that characteristic, an exposure, and the development of a disease. And so that’s one type. The other type is case control.

[ 00:04:32 ] Those are a different kind of study where you start with people with and without the disease, and then you look into their pasts to try and evaluate whether there are factors associated with that disease. So epidemiology is great. Observational research is very helpful for hypothesis generation. It often leads us in the right direction in terms of defining factors. You can look at the risk factors that increase or reduce a person’s risk of disease, but it doesn’t always give you the right answer. Sometimes you get the wrong answer because when you’re looking at groups of people, they have self-selected their exposure. So an example I like to use is vitamin E. So in the 1990s, most cardiologists were taking a vitamin E supplement.

[ 00:05:15 ] And that’s because we had a lot of observational evidence that people who took vitamin E supplements had lower risk of heart disease. Eventually, clinical trials were done, and people were randomly assigned to receive vitamin E or not. And it turns out that vitamin E was no better than placebo with regard to cardiovascular health. And so that’s an example where there was confounding, and bias is a type of confounding, where people who are self-selecting to be in a group like vitamin E users, they’re different from people who self-select to not take vitamin E supplements. And so that was a healthy user effect. And so then we have other examples where there’s an unhealthy user effect. And so epidemiology is really good for hypothesis generation.

[ 00:06:12 ] We can use it to make causal inferences, but we have to acknowledge the limitations of observational evidence. And the gold standard is the randomized controlled trial. Because by randomization, you ensure that the people who get the intervention and those who don’t are similar in terms of their risk of developing the disease. Would it be fair to say that for epidemiology, you ask a question, for example, I don’t know, we’ll take smoking and cancer. In the perfect world, someone will say either you smoked or you didn’t smoke. It’s a yes or no answer. And then what is your, I don’t know, maybe relative risk or risk of actually getting cancer? Then you would take that information that points us in the right direction.

[ 00:07:04 ] We then do, I don’t know, would the next step be mechanistic animal studies and then move to human randomized controlled trials to answer the question, does smoking cause cancer? Well, that’s where you run into a snag because certain things it’s feasible and ethical to run clinical trials on, other things it’s not. So you’re never going to take a group of 14-year-olds, randomly assign one to smoke cigarettes and the other not. So, you know, when we look at epidemiologic evidence, there are these criteria called the Hill criteria, Austin-Bradford-Hill, and there are nine of them, but I really focus on four. So when you look at a relationship, you say, how strong is this association? And for cigarette smoking, the relationship between cigarette smoking and lung cancer.

[ 00:07:53 ] Cancer was very strong. And then you also look at consistency. Do you get the same result in multiple populations, multiple sets of investigators, multiple countries? And the answer there was yes. And then you look at dose response and there was a strong dose response between cigarette smoking. People who smoke two packs a day were more likely to get lung cancer than people who smoked a half a pack a day and people who smoked three packs a day even more likely. So there’s a strong dose response. And then you also look at biological plausibility. Is there a reasonable mechanistic connection that would lead you to believe that this exposure is possibly causing this disease or playing a causal role in the disease? Because most diseases, cardiovascular disease, cancer, and so forth are multifactorial.

[ 00:08:41 ] So, you know, you may have a causal risk factor, but other things contribute as well. So I look very strongly at strength, consistency, dose response, and biological plausibility. And for certain things, you can follow that up with clinical trials. You can’t with smoking. You’d be hard-pressed to get a clinical trial done for parachutes, as an example. And so you then ideally follow up with clinical trials. So, for cholesterol and cardiovascular disease-which is actually where I’m going. For the listener, you guys, I know that this is a heavy kind of data discussion, but the reason it is is because we are going to ask very directly: what is the relationship between red meat and cholesterol? What is the relationship between saturated fat and certain outcomes?

[ 00:09:35 ] But in order for us to do that, we have to be able to show the landscape because there are randomized controlled trials, and then there’s lots of groups that believe, based on epidemiology, which is considered low-quality evidence, that we should make drastic health changes. For example, reduce our consumption of red meat. And that’s where I’m going with all of these questions. And in diet and health, often we don’t have clinical trial evidence. So the best we have is observational evidence and then maybe clinical trials of biomarkers. And so we can try and make inferences from that. I’m not against making recommendations on the best evidence that we have, as long as we acknowledge the limitations and we acknowledge the uncertainty. But frequently, that’s not done.

[ 00:10:23 ] So the recommendations are made, and a recommendation over here is made for something where we have very strong evidence, including clinical trials of outcomes, actual disease occurrence. And then over here, a recommendation is made, but we don’t have those clinical trials. And so no distinction is made, or not enough distinction is made, between the strength of the evidence for one recommendation and that for another recommendation. Dr. We are going to circle back to the 2019 guidelines that you were a part of for the, I think it was for the National Lipid Association, or it was the lipid guidelines. Before we do that, I want to discuss potential biases. How can we think about biases in epidemiology, and how can we account for that?

[ 00:11:10 ] It seems to me that if some, and I have seen this based on individuals who, for example, will say low protein diets. They will take an epidemiological study or a group and completely butcher the data to then, so you can see where my biases lay, and then to then say, well, this is the evidence for X, Y, and Z. Dr., you know, it’s all looking at the strength of the evidence. And for some recommendations, we have strong evidence. For other recommendations, not so strong. And so frequently, Dr. The researchers who have devoted an entire career to an area will have strong opinions, even though the evidence isn’t really there to support those opinions. So you know, the old expression is science and medicine progress one funeral at a time.

[ 00:12:05 ] So the old guard. DR. Science and medicine progress one funeral at a time. What does that mean? That’s interesting. DR. The old guard exits the scene, so to speak, and new ideas then can take hold that weren’t able to take hold until the old ideas kind of ran out. They ran their course. And so you do have bias in terms of people believing in something, whether or not the evidence is there. And then in terms of the observational evidence, you have bias that relates to self-selection. And so one of the challenges, the classic example of this, I’ve told this story many times about going to the International Congress on the Menopause in 1992. And the keynote speaker there started by saying, ‘The question at this point is not whether postmenopausal estrogen or estrogen and progestin protect against heart disease.

[ 00:12:59 ] We have 40 studies observational that show that that is true.’ Now the question is, how does it work? And a short time later, that keynote speaker was shocked at the results from the HERS trial that didn’t support that hypothesis. And then later, the Women’s Health Initiative also did not support that hypothesis. And that particular keynote speaker sadly died from cardiovascular disease, possibly relying a little too heavily on estrogen to protect her. And so, you know, that’s an example where most of what we knew about postmenopausal estrogen or estrogen progestin and health was correct. But the relationship with heart disease turned out to be a little more complicated. And so the epidemiology did not give us the right answer. Similarly with vitamin E. The epidemiology did not give us the right answer.

[ 00:13:50 ] So you have to be concerned that when there’s self-selection, there may be differences in groups with and without an exposure that are important, but it’s impossible to fully deal with that statistically. And that’s why ideally you run a randomized controlled trial. And then, you know, with the Women’s Health Initiative, that seems to have created a lot of problems for the understanding of hormone replacement therapy. Would you say that that’s accurate? Dr. It is. And just to give some examples of why it’s complicated. So that study, the Women’s Health Initiative, used one product. And so, it was a product that was conjugated equine estrogens, complex product with something like 200 steroidal compounds in it, and then medroxyprogesterone acetate. And so, that’s a particular progestin. Would you get the same result?

[ 00:14:47 ] Dr., would you get the same results with a different dose of the estrogen, different dose of the progestin? Would you get the same results with a different estrogen product and a different progestin product? Would you get the same results if you had a topical product as opposed to an oral product? These are all questions that we don’t have answers to. And so that’s one of the challenges that, you know, you run a clinical trial, you get a result, and often it gives you a narrow answer, but it doesn’t give you the full answer. And so again, we have to use all of the evidence that’s available. And so again, we have to use all of the evidence that’s available to make recommendations, and then acknowledge where we have the strongest evidence and where the evidence should be described as having some uncertainty associated with it, so we make a little bit less strong a recommendation.

[ 00:15:33 ] Do you see that in the nutritional science data? Dr. Definitely, I see it in the nutritional science data. And you know, red meat is the example that I think of. I think of it most often because there has been, in observational studies, association between adverse cardiometabolic outcomes and red meat consumption. And so when I look at the evidence, I say, well, strength, consistency, dose-response, and biologic plausibility. Strength, the evidence is, you know, weak to moderate in terms of strength, but it’s there and it’s fairly consistent. Then you look at the dose-response and you say, eh, there isn’t really any evidence. There isn’t really a strong dose-response, but there’s some evidence of dose-response. So you know, I would categorize those three as, you know, being consistent with the possibility of a causal association between red meat consumption and adverse outcomes.

[ 00:16:32 ] But then I go to biologic plausibility and I say, well, consuming red meat, what effect does that have on the known risk factors, the biomarkers that we study for cardiovascular disease? And I use the acronym FLASH. Dr. Yeah. FLASH, G-L-I. So family history, low HDL cholesterol, age, smoking, hypertension, glucose metabolism, lipids and inflammation. Okay. So we’ve done studies, controlled feeding studies, where we provide all of the food and we’ve done meta-analyses as well. And generally speaking, we don’t see adverse effects on these risk factors. So if there is a causal relationship. It’s got to be driven by some mechanism that we don’t understand. The other possibility is. Dr., can you say that again? I just want to stop. Sure. Dr. Because what you’re saying is so meaningful.

[ 00:17:25 ] I was on a recent panel and the moderator strongly believed that red meat caused heart disease. No matter what evidence was presented. And I thought to myself, ‘Um.’ If this moderator, who is a physician, believes this, then what is the way of processing mentally the evidence? And where is the actual evidence? Dr. So, you know, when we look at biomarkers, we don’t see adverse effects. Now there are some mechanisms that have been proposed, TMAO is one. And you know, some others have been proposed, but I would not describe that evidence as strong. So one possibility is that there is a causal relationship and there’s some mechanism or mechanisms that are driving it that we don’t understand. Another possibility is that people who choose to eat a lot of red meat are different from people who don’t.

[ 00:18:29 ] And when you look at people who consume a lot of red meat, you see differences. So they have less healthy lifestyles in general. They’re more likely to smoke, less likely to exercise regularly. Lower fruit and vegetable consumption, lower education level, higher body mass index, et cetera. And you can adjust statistically for many things. But are we sure we’re measuring all of the important things? And are we sure that all of those adjustments are sufficient to deal with all of the residual confounding? I just mentioned earlier two examples, postmenopausal estrogen, progestin, and vitamin E where it was not sufficient. Dr., and both. Postmenopausal estrogen and vitamin E are probably examples of healthy user effects. The people who chose vitamin E or postmenopausal estrogen were healthier than people who chose not to do that.

[ 00:19:21 ] People who eat a lot of red meat may have unhealthy lifestyle behaviors that are contributing to cardiovascular risk and diabetes risk. But that may be what’s driving the relationship, not the red meat itself. You know, you recently published a paper. And again, you’ve published many papers, but I’m just going to read this one. We’ll link it. It’s Beef Consumption and Cardiovascular Risk Factors, a Systematic Review and Meta-Analysis of Randomized Controlled Trials. Now I’m very aware that you publish all the time. I’m not sure how much of this paper you remember, but do you remember quite a bit of it? Dr. For the most part. Okay, great. Dr. I can give you the headline for sure. Okay. So give me the headline.

[ 00:20:08 ] And before you do, I pulled some meat consumption statistics, and I’d love for you to correct me for where I’m right or where I’m wrong. Daily red meat consumption in the U. S. I have here is about 3. 7 ounces a day. Is that true? Dr. Well, so it turns out I did a little more research on this to try and get at the numbers because there are a lot of nuances. So as an example from NHANES, National Health and Nutrition Examination Survey. They take two days of diet recall, and the results differ a bit if you use one day only, or if you use both days. They also differ a bit if you look at different slices of NHANES because it’s ongoing. And so the numbers that I’ve landed on are 4 .

[ 00:21:01 ] 6, 2 . 6, and 1 . 6. So 4 . 6 ounces a day is consistent. So the average consumption of meat, including processed meats, so red and processed meat, poultry and fish, 4 . 6, 2 . 6 ounces a day is average consumption of red and processed meat. And then 1 . 6 ounces a day is the consumption of red, unprocessed red meat. And that’s mostly beef and some pork, but mostly beef. Dr. And so if you look at. Dr. Yeah. If you look at red meat and processed meat, one thing to be aware of is when the discussion is about processed meat, that includes processed red and white meats. So that gets a little confusing. But in the US, Dr. And what would be a processed white meat? Dr.

[ 00:21:53 ] Chicken nuggets. Dr. Is it ham or something? Oh. Dr. Yeah. Dr. KFC. Dr. So. Dr. Okay. Dr. If you look at the relationship and how much unprocessed versus processed meat is consumed, 60%, 40% unprocessed, 40% processed, you know, it’s maybe two-thirds, one-third, 60%, 40%, somewhere in that general ballpark on average. And so one of the problems is in many observational studies, they use food frequency questionnaires that don’t necessarily divide out the unprocessed or minimally processed red meat from other types of meat, which are more processed. I’m more concerned about processed meats because many of them are high in saturated fats, high in salt, and they’ve got preservatives in them that I’m not completely sure we always understand the biological effects of.

[ 00:22:49 ] So what we’ve done in our clinical trials for the most part is studied unprocessed red meat, mostly beef. Dr. And a couple trials, there’s a PREDIMED trial, right? Did you work on that one? Dr. Yeah. So PREDIMED was a big study. It was out of Spain. And PREDIMED and CORDIAPREV are two studies that looked at a Mediterranean diet pattern. So they randomly assigned people to two groups or three groups. In PREDIMED, it was three groups. So it was sort of the traditional advice versus a Mediterranean diet set of advice. And in PREDIMED, there were two Mediterranean diets. One that had olive oil given to the subjects and one that had nuts given to the subjects. The results were the same. And then PREDIMED was primary prevention, so people that didn’t have cardiovascular disease at baseline.

[ 00:23:51 ] CORDIAPREV was secondary prevention, people who did have cardiovascular disease at baseline. They showed essentially identical results, 25% to 30% lower risk of major adverse cardiovascular events. And they were all in the Mediterranean diet groups. So that was good news, but it wasn’t a meat study specifically. Fascinating. Fascinating. Back to this paper, the beef consumption and cardiovascular risk factors. Was there a reason that you felt it was, first of all, necessary to do this? Dr. Well, in part, it was a follow-up. So we had done a lot of studies ourselves on effects of lean meat or beef. We did some pork studies as well. Consumption on the cardiometabolic risk factor profile. And our studies did not show adverse effects. But it’s always compared to what in nutrition? Were you surprised? Dr.

[ 00:24:47 ] For the first study, I was. Can you tell me a little bit about that? Dr. Sure. The very first study, this is a paper that we published in 1999 in Archives of Internal Medicine. And I joined when the study was already ongoing. So I was the one who crunched the numbers for the study. And I expected that in this study where people were being asked to consume six ounces a day of either lean red meat or white meat, you know, poultry and fish. And I thought, going in, that the lean red meat group would look worse in terms of cardiometabolic risk factors than the lean white meat or the white meat group. Dr. How come? Why? Dr. Because that’s sort of, I won’t say it’s exactly what I was trained.

[ 00:25:32 ] I was trained to think. I will say it was more, you know, red meat had been demonized. And so-And this was in 1998? Dr. Yeah. This was, you know, the study, you know, we probably finished the study itself in late 97. So, you know, I thought at the time that, you know, red meat was something that should be avoided. Even you as someone who is looking at epidemiology, because when we think about it, there has to be biological plausibility. Right. Dr. So, there has to be a mechanism of action. Right. So, I thought you eat red meat, your cholesterol level goes up, that is going to produce heart disease. That’s what I thought. I crunched-Dr. Which people still think-People still think. Dr. … in 2024. Yeah.

[ 00:26:18 ] I crunched the numbers, and much to my surprise, no difference between the groups. And this was a good-sized study. We actually did it as a crossover study, so people went through months, I think it was nine months. They went through nine months of having the predominantly red meat diet, and then they went through nine months of having the predominantly white meat diet. Dr. Wow. Nine months. Yeah. Nine months. Dr. Hopefully you guys paid for that. Paid for their food. Expensive. Yeah. Dr. And so, you know, the subjects did get some compensation for being in the study. But in the end, we did two analyses. One on just the first period, so we analyzed it as a parallel study, and then we did an additional analysis on the crossover.

[ 00:27:01 ] So with each person acting as his or her own control, and the results were the same. No difference between red meat and white meat in terms of effects on cholesterol levels. LDL cholesterol was the primary outcome variable. No difference at all. So then I started to really dig into the numbers. And so when you think about things that raise cholesterol levels, saturated fats and dietary cholesterol. Do raise cholesterol levels. Dr. To what degree? Okay. So when it comes to dietary cholesterol, it’s a small effect. So we conducted a meta-analysis on that. We published an American Journal of Clinical Nutrition. And we found exactly the same thing that an investigator named Clark published in 1997. Exactly the same thing, which is every hundred milligrams of dietary cholesterol consumed per day raises LDL cholesterol by about two milligrams per deciliter.

[ 00:28:01 ] I think it’s 1. 93, but you know, let’s call it two. Dr. Two milligrams per deciliter. And is there, you know, the fact that the body generates its own cholesterol, perhaps it raises it for a period of time and does the body then re-regulate to either produce less or excrete more? How does that work? It doesn’t really seem to. Okay. I’m going to get a little bit into cholesterol metabolism here. So. I cannot wait. My producer over there, Matt, is just, he is super excited. He is. On the edge of his seat over there. We all are. Yes. So you have about 2,000 milligrams of cholesterol that go through the intestine each day. And only 10 to 15% of that comes from diet. Most of it comes out in bile.

[ 00:28:50 ] And so you’ve got cholesterol going through the intestine. You’ve also got bile acids that are released into the intestine and they’re made from cholesterol. So some people absorb more cholesterol than others. And so you do have people who are hyper responders. So some people, you give them dietary cholesterol, doesn’t affect their cholesterol level at all. Other people, it affects it quite a bit. It goes up quite a bit. But for most people, there’s this, there’s a modest effect. And, you know, it’s, it’s, it’s not a large effect. And. And in the context of a healthy diet, it’s probably not one of the things that we need to be terribly concerned about as long as you don’t go crazy with consuming dietary cholesterol. And also thinking about the, you know, I’m a physician, I see patients.

[ 00:29:45 ] And so I’m thinking, okay, so for every hundred milligrams consumed would raise LDL cholesterol two milligrams per deciliter. Um, if someone had an LDL cholesterol level of one hundred and we gave them dietary cholesterol, you know, would that have any significant outcome? Or even I was looking at some of the data that 30% of the population has LDL cholesterol above 160, but everybody else, which means 70% of the entire population doesn’t doesn’t. And those numbers are actually a little outdated for reasons that we don’t fully understand. Average cholesterol levels. Yeah. In the U. S have been dropping about a milligram per deciliter per year for decades now. So if you look at the, uh, average LDL cholesterol level in say the 1960s, it was about 160 milligrams per deciliter.

[ 00:30:41 ] Now it’s dropped all the way down close to a hundred. That’s the average in the population just drops and drops and drops. Why I can’t explain that I can explain maybe parts of it. Do you have a hypothesis? You know, I. I really think there are lots of things that I think should be investigated, but I, I wouldn’t say any of them for me reached the level of a hypothesis. So I’m concerned about, you know, um, contaminants in the environment. I mean, certainly there have been some dietary changes, uh, that have been favorable and so that’s contributed some of it, but that can’t explain most of it. Um, so I don’t know, but there are other things I don’t know. So, you know, you’ve probably heard that.

[ 00:31:25 ] Testosterone levels are going down and sperm counts are going down, you know, looking very similar to what we’re seeing with cholesterol levels. I don’t understand why that’s happening. There are some hypotheses. That’s not my area of expertise, but I would say that, um, you know, I think there are things that should be investigated, but I don’t, uh, know how likely it is that any of those things that I’m, you know, concerned about are really causing this drop. I don’t really know what is causing it; could be changes. complicated. There’s definitely, I mean, we’ve discussed this before. We talked about photosynthesis before and how we’re going into relatively high numbers every day, just because we’re already [something]. I mean, yeah.

[ 00:32:10 ] Um, but I don’t have any theory, but what I’m, um, we’ve taught students as, like at the school campus. com to like focus on on animal natures, commencing xenocytosis. Sea, sex datasets, we didn’t generalize and I wasn’t sure that it would work too. Uh. Cholesterol-lowering fatty acids. But if you look at beef fatty acids as an example, so about half, roughly 48% of the fatty acids in beef are monounsaturated, which don’t raise cholesterol. In fact, they tend to lower cholesterol levels. And then the rest is saturated or, you know, tiny amount of polyunsaturated, but most of the rest is saturated. And then you look at the saturated and about a third of it is stearic acid, which doesn’t raise cholesterol levels. So it’s not the fat from beef that is raising cholesterol levels.

[ 00:33:03 ] It’s probably, if there’s an effect, it’s related to the cholesterol content, but the cholesterol in a serving of red meat is not different from the cholesterol in a serving of white meat. And roughly how much cholesterol would be in a serving of? I don’t know. Trying to think back. So in our controlled feeding study, we fed two servings a day of lean beef. And I think that the difference between the groups was about 125 milligrams of cholesterol. So I’d have to look up the amount of cholesterol in a serving. But when you run all the numbers using the equations that have been published to say, what are the effects of fatty acids? What are the effects of cholesterol? You come up with a fairly neutral effect when you compare red meat and white meat.

[ 00:33:54 ] If you compare red meat to nuts or to soy, for instance, that’s a different story. And so it gets a little complicated. And in nutrition, you always have to ask compared to what? Do you think that it becomes myopic when someone will say we’re going to remove red meat because of this very small change in LDL cholesterol number, just for example? Because it’s not just the cholesterol. We’re talking about dietary protein. What else are you going to be eating? Bioavailable zinc, B12, iron. How do we begin to make sense? And I definitely want to discuss this paper because you looked at these cardiovascular markers, including HDL cholesterol, triglyceride, non-HDL, apolipoproteins. Again, being the former president of the National Lipid Association. Sure. So I think we need to be concerned about unintended consequences.

[ 00:34:57 ] So if you say to people, ‘cut back or eliminate red meat from the diet’, you are eliminating some important nutrients that are more difficult to get in other places. So that doesn’t mean that you can’t be a vegan or a vegetarian and have a healthy dietary pattern. You absolutely can. But it just takes a little more effort. And I think especially for older individuals, who may not be getting enough protein, may not be getting enough of these other nutrients that are found in red meat, there may be unintended consequences. And so circling back to our paper, we looked at lipid levels and blood pressure as our primary indicators of a cardiometabolic risk. And essentially what we found is no effect on average on blood pressure or lipids with the exception of a very small effect on LDL cholesterol.

[ 00:35:55 ] But that was a little bit challenging because there was one particular study that seemed to drive that effect. And that study was a weight loss trial. And so if you remove that study, the effect goes away completely. But then if you look at, again, compared to what, compared to poultry, no difference. If you compare red meat to plant-based proteins, then you do see a difference. But I think that that’s not because of a cholesterol-raising effect beyond the dietary cholesterol in red meat. It’s because of a cholesterol-raising effect beyond the dietary cholesterol in red meat. I think it’s because plant proteins do lower cholesterol. Do we know how? And just to take a step back, when I think about dietary proteins, I really think about those amino acids, which whether they come from plants or animals, they are still just amino acids.

[ 00:36:50 ] They’re amino acids. They get broken down. Yep. Right. Is it a fiber contribution? Is it potentially something else? And again, I know where my biases are. My biases are, I believe that we should have a diet. I believe that we should have a diet. I believe that we should have a diet. It’s that includes both plants and animals? So the answer is, we’re not sure about the mechanisms. And I conducted a study where we had a hypothesis that soy protein in particular was increasing the excretion of bile acids. It was, you know, acting as a bile acid binding agent. That was our thought. And so we ran a study and we had sort of three conditions. We had a soy protein condition, we had a milk protein condition, and then we also gave the drug colacevalam, a bile acid sequestrant.

[ 00:37:45 ] Well, it turns out our hypothesis was totally wrong. So, you know, I’ve ruled out one potential mechanism. So what happened is there was more content. Cholesterol lowering, especially non-HDL cholesterol, was lowered more with the soy protein than with the milk protein. Now, this raises a point. Proteins, if you replace carbohydrate with protein, you lower cholesterol levels. If you replace carbs with protein, yes, we saw, yes. Yes, you lower cholesterol levels. And that was true for both the milk protein and the soy protein, but the soy protein had a larger effect. Statistically significant? It was for non-HDL cholesterol. For LDL cholesterol, I think it was 0. 09 or it was very close, but not quite statistically significant. But, you know, the effect was double, essentially.

[ 00:38:40 ] So, you know, this supports the idea and meta-analyses have been done on this. So, plant proteins do seem to lower cholesterol more than animal proteins for reasons I don’t understand, now in the soy study, some people are probably thinking, oh, what about isoflavones? This was a soy protein that had the isoflavones stripped out. So it wasn’t isoflavones, it wasn’t fiber because we gave a protein isolate. That’s fascinating. So I don’t know. I don’t know the reason, but you know, others have shown the same effect that plant proteins have a larger effect, but I’ll emphasize that both animal and plant proteins lower cholesterol compared to carbohydrates. You know, and then it just makes me think, to what level would that be necessary?

[ 00:39:29 ] For example, if someone has a normal cholesterol level and now we are either adding in soy protein or removing, I would never say to remove protein, but swapping these things, would it have a meaningful impact if someone, for example, like my husband has normal cholesterol levels? Well, I think that you have to look at a person’s risk profile. So, you know, we can estimate a person’s risk based on their risk factors. So the things that I mentioned previously, and so some people need to be more concerned than others. Some people have high enough risk that it makes sense to give them drug therapy to lower their cholesterol levels. But for most people, it’s about a healthy lifestyle that includes a healthy dietary pattern, as well as physical activity, getting enough sleep, stress management, avoidance of tobacco; these kinds of things are all important.

[ 00:40:27 ] And you know, the aggressiveness with which you deal with cholesterol should relate to the person’s risk. Higher-risk individuals are going to need more aggressive therapy, whether that’s lifestyle or pharmaceutical therapy. And when it comes to LDL cholesterol and apolipoprotein B, the main protein backbone of lipoproteins that can drive atherosclerosis, lower for longer is better. And so, you know, what we’d like is people to have a healthy lifestyle, maintain healthy levels of LDL cholesterol and apolipoprotein B for an extended period, because it’s not just the level, it’s the length of time that a person is exposed to that level. So even modest changes early in life, if they’re maintained, can translate into big differences. And I’ll give you just one quick example.

[ 00:41:23 ] There’s a class of drugs called the PCSK9 inhibitors, and they were developed because somebody noticed that people who have a genetic variant that reduces PCSK9 activity have slightly lower cholesterol levels. And then people who have a different genetic variant that have a larger reduction in LDL cholesterol levels had much lower risk of cardiovascular disease. And when you say much lower risk, were you looking at APOB levels? Are you looking at Lp(a) levels? How do we think about this stratification? This was specifically LDL cholesterol. That was the lipid variable that was investigated. And so there’s an interesting relationship. So, in drug studies where you use statins or other drugs to lower LDL cholesterol, every 39 milligram per deciliter reduction over five years lowers risk by about 22%.

[ 00:42:23 ] So that’s a lot lower risk. So that’s a lot lower risk. So that’s a lot lower risk. Okay. So slow that down. Say that again for me so that we can all get this. Sure. Every 39 milligram per deciliter reduction in LDL cholesterol. And would that show up in someone’s blood work? Because depending on the lab that you use, it’s variable. Are we thinking about total numbers of LDL cholesterol less than 100? Is that where this 39? 39 is just like, no matter where you start, if you lower it by 39, it lowers your risk by 22% over five years. Okay. So that’s in studies with statins, especially over five years. But in observational studies where you follow people longer with an average of about 12 years, it isn’t 22% reduction.

[ 00:43:05 ] It’s 32% reduction. And then if you look at genetic variants for every 39 milligram per deciliter reduction, that’s driven by a genetic variant, that means that you’ve had a lower level through decades. The reduction in risk is 52%. And so you get about two and a half times the benefit from lifelong exposure to lower levels than you get over five years, which is what we have in drug studies. What percentage of people will have dietary and lifestyle impact? For example, to reframe this question, it seems that the majority of people, again, I’m just speaking as a clinician who sees patients, the majority of people seem to have an LDL cholesterol set point, that this is where they are.

[ 00:44:03 ] Whether we put them on a perfectly curated diet where we swap out, I don’t know, their ultra-processed carbohydrates with protein, regardless, they seem to have a set LDL cholesterol, set ApoB level. They are not going to That is, we’re not moving this by diet. Yeah, you’re not. You can move it some. Maybe 5%. Well, so what I say is a rule of thumb, 3% to 5% for each thing that you do. Okay, so what are the things that you can do to lower LDL cholesterol? Well, one is you can reduce saturated fat and cholesterol intake. To what? Do we have a number? Well, the general recommendations are less than 10% of energy. And so for people with dyslipidemia, the recommendation is usually to try and drop it by 5%.

[ 00:44:57 ] So drop it down into the sort of 5% to 7% of calories from saturated fats. What percentage of people do you think have issues with LDL cholesterol that are genetic versus dietary related? Well, I think most of it has a genetic component. And so you’ve got lots of genetic influences. So everybody kind of has a level where, you know, on a given diet, they’re going to end up at this level. So then you can change diet in certain ways. You can reduce saturated fat and cholesterol levels in the diet. You can increase intake of things that lower cholesterol, and that would be unsaturated fats and proteins. So unsaturated fats are mono and polyunsaturated fats, polyunsaturated fats. Now you’re going to get hate mail from the people on. The internet who hate seed oils.

[ 00:45:53 ] It’s okay. But we got thick skin over here, especially Matt. He’s doing lots of microneedling. He’s improving his dermis. Yeah. So, polyunsaturated fats lower LDL cholesterol. Do we know the dose necessary? Well, we did a study. And so, in the study that we did, which was controlled feeding, again, we provided all of the food. And that, by the way, guys, I’ve done controlled feeding studies. It is an enormous amount of effort. It is. And, by the way, Dr. Kevin, someone is packing those meals. And, by the way, when I was in my undergraduate, I was that person. Yes. And so, we had people come in every day for breakfast. We fed them breakfast and then we gave them lunch and dinner and then would come in the next day, except on Fridays where they would get enough food for the weekend.

[ 00:46:39 ] So we did this and we were comparing two oils, extra virgin olive oil and corn oil. Corn oil is high in linoleic acid and omega six polyunsaturated. Fatty acid and olive oil is high in monounsaturated oleic acid. So here’s the good news. They both lower cholesterol. So about 11% with the corn oil and about three and a half percent with the olive oil. But there was also good news for the olive oil in that it lowered blood pressure and heart rate slightly. So that’s interesting. Yeah. And the same thing was shown in the predimed study. Do we know why? I, my suspicion is it relates to polyphenols that are in extra virgin olive oil. And that’s one of the reasons that extra virgin olive oil may be marginally better than more processed olive oil because it’s still got more of the polyphenols in it.

[ 00:47:36 ] So that’s my hypothesis, but I don’t know for sure. And so, you know, they both lowered cholesterol levels, olive oil, lowered blood pressure and heart rate, but corn oil lowered LDL cholesterol more. So, you know, about 11%. And. And so, um, you know, I think that the dose that we used was four tablespoons, 54 grams, that’s quite a bit, but, um, I think that what people can do is if you’re using butter, you can trade that out for olive oil or corn oil or soybean oil or canola oil, if you’re using, uh, you know, more saturated fats and cooking, they can be traded out for more unsaturated fats. Um, so I mentioned saturated fat and cholesterol in the diet, reduce that, increase unsaturated fatty acids, increase protein.

[ 00:48:32 ] There’s a bit more of an effect of plant protein than animal protein. These are all things that you can do. On top of that, you can supplement the diet or consume dietary sources of viscous fibers. And what are examples of those? So the, the example. People will be most familiar with is Metamucil, and I usually don’t use brand names, but everybody knows that. Yeah. Just people are going to ask. Yep. So we’ll find alternatives for you, but, um, also barley notes have beta-glucan, which is a viscous fiber. Yeah. Also, um, there are some other laxative type products, uh, that contain methyl cellulose, which is a viscous fiber. And we’ve studied that and it lowers cholesterol, and then you can also add plant sterols and stanols.

[ 00:49:20 ] To the diet, each one of these things that you do gives you three to 5% reduction. And I’ll add one more thing, which is if you lose, if you have some excess body fat, you reduce excess body fat that will also lower cholesterol levels. So when you start stacking these things, you can get up to a fairly good size reductions. So David Jenkins and colleagues in Toronto, they have what they call the portfolio approach where they combine a low saturated fat diet, nuts, um, viscous fiber and soy protein. And with that in a controlled setting, they got a 30% reduction in LDL cholesterol, but when people were free living, they were only able to maintain half of that. So about a 15% reduction. It’s so interesting. You know, I had, um, Dr.

[ 00:50:12 ] Christy Ballantyne, come on, who, you know, also now amazing, amazing guests. And we were discussing the same thing. Similar hair. Style. Yes. Yes. And he was saying that the majority of the time he only sees a 5% change from diet. Yeah. Um, you know, I don’t know, again, I love the idea that some of these things can be compounded and I just, I I’m wondering, um, do we see that across the population or again, Christie was like, well, you know, you can change these things. And diet, but he said what he really cared about, which it was, I was shocked because again, he’s a lipidologist. I was shocked. He said what he really cares about carbohydrate control. Yeah. Carbohydrate control is important. So tongue in cheek, I talk about the four white poisons.

[ 00:51:05 ] So the four white poisons are saturated fat, salt, added sugars, and refined starches. Now we aren’t trying to eliminate these things from the diet, but the average American diet has more of these things than would be considered optimal. Is the average diet roughly 70% of those things? Uh, so. Or let’s say 70%. Uh. So, so roughly 50% of calories are coming from carbohydrate, but a large portion of that carbohydrate is added sugars and refined starches. And so, you know, what we recommend is emphasizing whole grains, fruits and vegetables, nuts, seeds, legumes, non-tropical oils, and then. No palm oil. Palm oil is not optimal because it’s higher in saturated fat, coconut oil, also higher in saturated fat. So the tropical oils are higher in saturated fat.

[ 00:51:59 ] Now, again, it’s always compared to what, and palm kernel oil is another one high in saturated fat. So our preference is to move people toward non-tropical oils. And that doesn’t mean you can’t have any of these things, just they should be consumed in moderation. And when Christie is talking about 5% reduction, my guess is, is that he’s referring people to a dietitian. They get counseling, they go home, they get about a 5% reduction and they probably aren’t stacking these things. They’re probably not emphasizing unsaturated fatty acids and, um, cutting back very much on saturated fatty acids and cholesterol. They’re probably not reducing their refined starches and added sugars. So much, um, because especially refined starches and added sugars, they mainly affect triglyceride levels.

[ 00:52:58 ] And so what you see when you reduce dietary carbohydrate from added sugars and refined starches, you mainly see triglyceride levels going down. Um, so, you know, again, whole grains, fruits, and vegetables, nuts, seeds, legumes, non-tropical oils, minimize the four white poisons. Yeah. And then when it comes to, um. Um, animal proteins, um, I’m much less concerned about animal proteins, except to say, uh, not really based on strong evidence. I’m a little more concerned about processed meats, you know, the sausages and the bolognese. Um, and, uh, so they’re often sources of saturated fat and salt, so they, you know, carry with them some of those four white poisons. And I actually, I greatly appreciate you laying out those items, because the listener, you guys, you, they’re interested in the science and they want to know what they can do.

[ 00:53:56 ] I was looking at where are we getting the majority of saturated fats from our diet? Yeah. The majority of saturated fats are really coming from mixed dishes. So, that’s one of the challenges. There isn’t one thing you can point to. So it’s mostly. I landed on one food group. Did you? Mixed dishes and desserts. Desserts. Pizza and saturated. And baked goods. Yeah. And baked goods. Um, pizza is a little more complicated. I agree. I agree. But I, here’s what I was thinking. I was thinking, okay, so we’re hearing this overarching message that we need to remove the amount of red meat or high-quality protein. I mean, this is, again, this is what I’m interfacing with, which is why I believe so strongly. It’s important to have experts like yourself on.

[ 00:54:43 ] And the messages that we’re hearing is decreased dietary cholesterol, which I know that they took cholesterol out of the guidelines in 2010. But the saturated fat thing could be a real issue. And then what’s happening is I think people are pinning red meat, whether it’s lean red meat or not, or white meat or any of these animal proteins as saturated fat. When you had also mentioned that roughly 50% of the fat in these items are polyunsaturated. And so that those are kind of. Monounsaturated. I’m sorry. Monounsaturated. And I just think we have to get really clear because the unintended consequences of these. These overarching themes can be devastating to an aging population. I agree. I am concerned, especially as people are moving from middle-aged into older ages about getting adequate protein.

[ 00:55:31 ] And there was recently a publication that was addressing this issue of dietary protein, specifically in people with kidney disease. And so we know that in advanced kidney disease, you do have to restrict protein. Right. Right. Right. Most people with kidney disease have less advanced disease. And so the question is, do they need to be restricting protein? And so this was an observational study, but they looked at people with and without kidney disease and they looked at total mortality in relation to protein intake. And the recommendation for protein intake is at least 0. 8 grams per kilo of body weight per day. And so. They looked at 0. 8 as kind of the reference point, and then they looked at each 0. 2 increase. So they went from 0.

[ 00:56:28 ] 8 all the way up to 1. 6. And what they found is that with higher intake of protein in these older individuals, there was lower total mortality. And that was especially true in people who are at least 75. And so I am really concerned about middle-aged and older people. Not getting sufficient protein intake. I don’t think 0. 8 is optimal. I think that something between 1. 2 and 1. 6 is my best estimate of what is likely to be associated with favorable health outcomes, not just mortality, but there’ve been other studies that have looked at protein intake in middle age and various health-related outcomes later in life and higher protein intake from both animal and plant proteins is associated with more favorable health outcomes. Do you, are you in the social media sphere?

[ 00:57:31 ] Do you see what goes on online? Do you, do you actually witness, I mean, a lot of academics maybe take a step back, but do you see what is going on out there? I do. And it’s, you know, it’s distressing because, you know, I’m a strong free speech advocate and having said that, I read a lot of things online where I just shake my head and say, no, that’s not what the evidence shows. And in fact, that’s often the opposite of what the evidence shows. And seed oils is a real hot topic. I would love to hear what your take is, what you’re hearing, what the rhetoric is versus what the evidence supports. So the claim is that if you consume. Seed oils that are high in linoleic acid and omega-6 polyunsaturated fatty acids, that which will increase inflammation.

[ 00:58:26 ] And we know that chronic inflammation contributes to many diseases, diabetes, cardiovascular disease, cancer, et cetera. Okay. So here’s where that breaks down. That’s based on a mechanism where the assumption is that if you consume a lot of linoleic acid, it’ll be converted to arachidonic acid. And then arachidonic acid is the precursor for these compounds, prostaglandins and leukotrienes that are pro-inflammatory. Okay. It looks fine on paper. The reality is that there are two problems with that. One is that pathway to convert linoleic acid to arachidonic acid saturates at a very low level of linoleic acid intake. So, what does that mean? Exactly. That means that, you know, you will increase arachidonic acid levels. If you start very, very low in linoleic acid, you consume more, you’ll get more arachidonic acid up to a point after which you get no increase in arachidonic acid.

[ 00:59:27 ] Regardless of how much you are taking in, because the body doesn’t have the enzymes or the capacity to be able to, to keep converting, to keep converting to these leukotrienes and other various metabolites. Right. So that’s the first problem. Second problem. Is there a dose that we know of out of curiosity? Uh, it’s about 2% of energy where it saturates. 2% of, you know, I always wonder about the percentage questions. Um, and I, I struggle with it a lot because we talk often about percentage of protein calories, percentage of saturated fat. But if someone is having a 12,000 calorie diet versus a 4,400 calorie diet, those numbers are so variable. Yeah. And, and so that’s an average and there’s variation around it. So that’s the first problem.

[ 01:00:12 ] The second problem is you look at all of the studies done in humans. And when you feed increased linoleic acid, you get no increase in biomarkers of inflammation, like C-reactive protein is kind of the prototype for that. You just don’t see it. And so we’ve done studies. Other people have done studies. They do not show any increase in biomarkers of inflammation. And so the idea that you’re having inflammation driven by increased linoleic acid intake just does not comport with the evidence from studies. And humans. Secondly, when we look at the observational evidence, the more linoleic acid people consume, or the more they have in their bloodstream, um, in biomarker studies, the lower their risk of cardiovascular and other diseases. And then what is really lacking is randomized controlled trials.

[ 01:01:10 ] I wish we had those. We have some, but they’re all very old and hard to interpret. And so the evidence, with its limitations, would be consistent with the idea that higher intake of seed oils lowers risk of adverse cardiometabolic outcomes, not increasing risk. Where do you think that people have gone so wrong with it? Uh, you know, it’s, it’s, it’s fascinating. I mean, I would say that they’re probably unnatural, um, again, whether that’s good or bad. I do know that for example, animal fats used in cooking. It’s drastically been reduced since the fifties. We seem to be turning towards seed oil use. Is that, is that true? Yeah, I think there’s more seed oil use and you know, my mother used to save the bacon grease and the hamburger patty, um, fat in a jar and reuse it.

[ 01:02:08 ] Uh, you know, we don’t do that anymore. So we don’t wait. We’re not supposed to do that. I’m just kidding. That I’ll check your cabinet. We’re not supposed to do that. So. Um. You know, I would say that, uh, you know, there are lots of things that have changed over time. And so what often happens is people come up with a mechanism and it’s plausible, but then you have to look at the evidence and say, does the evidence support the importance of that mechanism? Because very often there are other mechanisms. As an example, linoleic acid lowers LDL cholesterol levels. We know that that’s beneficial. Um, you know, I’m not averse to the. Were you surprised by that? The seed oil conversation? I was. Yeah. You were.

[ 01:02:51 ] Because, and you know, so the American Heart Association as an example, put out a statement and the, the statement essentially said you should be replacing saturated fats with polyunsaturated fats because they have the most beneficial effects in animal studies, observational studies, limited clinical trial evidence, and they lower cholesterol more. So, um, you know, these things. Did you agree with that statement? I did. Okay. These things take on a life of their own on the internet and you have very influential, charismatic people who are talking mostly to people who don’t have the background to be able to interpret their suggestions. And you end up with a lot of people believing that seed oils are terrible when the evidence doesn’t support that. Now, if I see evidence that leads me to believe the opposite is true.

[ 01:03:45 ] Yeah. You know, the famous quote, um, is, uh, a reporter criticizing someone, uh, John Maynard Keynes, uh, was, uh, supposedly the person who said this and the reporter said, well, you said this, and now you’re saying that why, why the difference? He said, well, when the data change, I changed my mind. What do you do, sir? Um, if I see the data that lead me to believe that, uh, that things are different from what I think the evidence supports. Now. I’ll change my mind, but, uh, lots of people would, you know, be very resistant to changing their minds. I think we see that a lot. Um, at least I certainly see that. And, you know, before we move on to other topics, I want to summarize some of the things that we’ve spoken about thus far.

[ 01:04:34 ] The first thing that we talked about is this idea of red meat or, um, animal proteins. I mean, this, this paper was beef. And your final take on this is that beef does not, it’s not your final take. I mean, obviously this is collaborative effort, but based on the data that, um, unprocessed beef, generally speaking, does not increase cardiovascular disease risks. Or at least does not worsen the risk factor profile. Um, and again, where I get hung up is if there is. Okay. If there’s going to be some increase in cardiovascular risk associated with eating red meat, there should be a mechanism that would explain that. And to my satisfaction, no one has explained a mechanism that would account for what we see in observational studies, leading me to believe that the relationship may be driven by the company that red meat keeps.

[ 01:05:38 ] People who eat a lot of red meat have other lifestyle habits that are possibly driving their increased risk. Which, which absolutely makes sense. And then the, uh, additional follow-up that you feel is important is that if somebody has issues with cholesterol, LDL cholesterol, or ApoB, that there is evidence to support reducing saturated fat in the diet. Again, this is not pointing the finger at, uh, red meat or various items. It seems that the majority of saturated fat comes from processed food meals, and that there may be some evidence to reduce that, but we haven’t determined to what amount. For example, uh, well, if you take the average intake in the U. S you cut it in half, you’ll get about a 3-5% reduction in LDL cholesterol.

[ 01:06:33 ] So that’s not nothing, but it’s not a huge effect. And then if you start stacking those other things, you get more reduction, but you know, you’re not going to drop by lowering saturated fat and cholesterol intake, you’re not going to drop LDL cholesterol by 20% for most people, for most people. And I’m really glad that you mentioned that. What is the average, the recommendation currently is 10% saturated fat. I’m not sure where that less than 10%, less than 10%. I’m not sure actually where that number came from. The evidence then I read is that the average American is eating around 11%. We’re at about 11% now and that’s come down. So in the time I’ve been in the field, it’s come down from about 14% to 11% on average.

[ 01:07:14 ] Which is fascinating. Because. Heart disease is on the rise. Well, heart disease dropped for decades. And then after 2015, it started ticking up. And so we don’t understand all of the reasons for that. But one of the reasons likely relates to increased prevalence of obesity and diabetes. Right. Because that’s two of the reasons. And then I also think that there’s been a shift away from adequate control of lipids. In clinical medicine. So I think for people at highest risk, you know, they’re the ones who are going to benefit the most from aggressive lipid management. But that’s not for everybody. You know, you have to separate people who are low risk, people who are primary prevention, but maybe an intermediate risk.

[ 01:08:07 ] And then people who are at high or very high risk, the people at high and very high risk, they have the most to gain from aggressive lipid management. Management. Other people who are at lower risk, it’s mostly about lifestyle. And then if the risk increases enough, then you start thinking about drug therapy. And I think that that’s a really good differentiator because it’s fascinating to me that we make a blanket recommendation that 10% or less of the diet should be in saturated fat. And I was looking at some of Volick’s work, and he looked at saturated fat that I think was anywhere from, I don’t remember the exact number, but it went up to 86 grams per day. Calories were controlled. Do you know the paper that I’m looking at?

[ 01:08:56 ] Maybe it was-Well, and the variable there that’s kind of confounding is weight changes. So Jeff Volick, he’s amazing in the sense that he long-term can maintain this very low-carbohydrate diet. And we started to talk about carbohydrate-restricted diets. Oh, we’re getting there, my friend. We’re getting there. So the challenge in evaluating the evidence is that in clinical trials, most people can’t follow a very low-carbohydrate diet for too long a period. They stick with it for a few weeks, maybe a few months, but then they start to drift. And so when you’re comparing two groups, a very low-fat ketogenic-type diet, and a very low-fat ketogenic-type diet, and a very low-fat ketogenic-type diet, and a higher-carbohydrate diet that’s restricted in calories, what happens is carbohydrate intake starts drifting up in the ketogenic or very low-carbohydrate group.

[ 01:09:53 ] And so then the question is, well, how much of the narrowing in things like weight loss relates to diet drift and people not really adhering to the low or very low-carbohydrate diet? Yeah. I think it’s a really good point. And I can’t help but think about how these groups had a tremendous, tremendous ingestion of saturated fat, and they didn’t see meaningful changes in lipids. And maybe it was calorie control. Have you seen the paper that I’m talking about? If it’s the one I’m thinking about, there were weight changes. And so one of the problems is if you get into negative energy balance, that drops cholesterol levels. And so-Regardless. Regardless. And so that’s a confounder. And having said that, there is some evidence that with lower carbohydrate diets, people can eat a bit more saturated fat without raising their LDL cholesterol.

[ 01:10:53 ] I’m a fan of sort of moderate carbohydrate intake. So the Cordyoprev and the Predimed studies, Mediterranean diet, that was about 40% of energy from carbohydrate. That’s less than average in the U. S. And so when you get below that, you’re going to have a lot of fat. And so that’s a confounder. And so when you get below 40 and you get to very high levels of carbohydrate intake in observational studies with all of the caveats that have to go along with that, you start to see increased mortality at the extremes. Below 40, above 60, you start to see increased mortality. And so, you know, I’m a fan of reducing added sugars and refined starches, focusing more on whole grains, fruits and vegetables, nuts, seeds, legumes, non-tropical oils.

[ 01:11:38 ] My joke is I have that tattooed on my forearm. I really hate that. And so I’m a fan of reducing added sugars and refined starches, focusing more on whole grains, fruits and vegetables, nuts, seeds, legumes, non-tropical oils. But I don’t, but I say that in a talk and then people want to see my tattoo. So what I, you know, say is some carbohydrate restriction I think is reasonable. And then the question is, what do you replace it with? And I think some combination of protein and unsaturated fatty acids is reasonable and, you know, consistent with the evidence we have from actual randomized controlled trials. Do you think there is going to come a point where we can, instead of percentages of calories, just let’s take, I don’t know, saturated fat, for example.

[ 01:12:18 ] So if someone is on, and, you know, we mentioned this offline before, for example, if someone is on a 12,000 calorie diet, then 10% or less of that would be what, 12 grams of saturated fat? Well, let’s see. So, you know, 10% would be 1,200 calories. You know, it’s nine calories per gram of fat. So let’s just divide by 9. That’d be, you know, 12, 13 grams. Yeah. Versus a, someone who’s on a 4,400 calorie diet, then we’re looking at 10% of calories. So around 44 grams of saturated fat. And so I’m just trying to wrap my head around that if it is a, based on a percentage, and I, I understand that it’s for general recommendations, but in my mind, I think it’s a, it’s a, it’s a, it’s a, it’s a, it’s a, it’s a, it’s a, it’s a, it’s a, it’s a, I think I’ll give an example.

[ 01:13:11 ] For carbohydrates, we know everything above in a sedentary person or someone who’s not exercising in that moment, that a carbohydrate load of beyond 50 grams will probably generate some moderately robust insulin response, right? If we keep carbohydrates under a certain gram amount, but we, but to say that it’s 10% or less, then that means for someone like me, it’s 12 grams of saturated fat versus someone like my husband, it’s 44 grams of saturated fat. And then I can’t help take it one step further and thinking if something is so bad, there has to be, I don’t know, a lethal dose of it, like an LD50. Yeah. And this is where it gets complicated because it’s not just the amount of saturated fat. It’s also what else is being consumed.

[ 01:14:00 ] So it’s that ratio of saturated to unsaturated fats that’s driving it as well. And so in your husband’s case, for example, he may eat, you’re calling them out. So he may be eating, you know, 44 grams of saturated fat, but he might also be eating, you know, 70 grams of unsaturated fat. And that would be very different from someone who is eating, you know, a lot of sugars and, you know, refined starches, you know, a lot of white bread and pastries. And so, you know, we use percentage of energy just because it’s something that we can relate to in terms of a standard because everyone has a certain set of needs for energy to maintain a stable body weight.

[ 01:14:52 ] And so everything is done relative to that, just so that, you know, you can make a comparison between someone who is five feet tall and someone one foot shorter. Okay. Yeah. I wasn’t estimating your height, but you know, somebody, you know, I, I see plenty of people who, um, I, I see 260-pound, uh, you know, a 260-pound guy. And then the next person I’ll see will be a 110-pound woman. And of course their dietary needs are going to be very different, but we have to relate it to something. And energy intake is just one way to do that. Yeah. And I, and I think that there are limitations to that. And, um, you know, the other aspect of that is, um, you know, you know, you know, you know, you know, you know, the thing that you highlighted for us so far thus far is that seed oils seem to really get a bad rap yet.

[ 01:15:46 ] The evidence doesn’t support that. Do you think in some space, it would, or potentially we’re just looking at the wrong thing? Um, I’m not sure I follow the question exactly. So in some space, so if I was a biased person, which I am, um, and I think, okay, we all have our biases. We do. This is as long as we’re aware of them, then, and we’re honest about it, then I think that that is what matters where I have to say, there are groups, you know, Harvard and these various groups, I think are very disingenuous about honesty in terms of transparency. Like for example, the nurse’s health study, um, which we can definitely circle back to because I think it’s important for the general population, but I would love to believe that seed oils are a problem.

[ 01:16:32 ] Just why? Because they’re unnatural. I don’t know. I don’t know if I want to give it to my kids, but I’m also very open to the idea that I am totally wrong. Well, and you know, in the end, all you can do is examine the totality of the evidence. And so we, you know, have to look at what are the observational studies show? What are the randomized controlled trials show? What are the animal studies show? What are the mechanistic connections between these things? And then make a judgment. So it’s always a judgment. And unfortunately, um, it’s not always clear. And so experts can review the same evidence and come to different conclusions. And I have no problem with that. Where I do have a problem is where people are promoting ideas that are just simply not supported by the evidence.

[ 01:17:22 ] And that’s where I get frustrated, but I’m also a free speech advocate. So I defend their right to say things that I think are crazy, which is hilarious. What do you think that we do if there is someone who’s out there listening going, I’ll give you an example. I had someone on my team come to me and say, ‘You know what, my doctor told me I’m eating too much red meat, uh, and that I should go plant-based, and this is a true story, you know?’ And I said, ‘Well, did you read my book? No, I didn’t, I didn’t say that.’ Um, how does someone who just wants to do the right thing, how, how can they think about it with this influx of information hearing from various experts who, for example, I think a lot of the nutrition data is based on observational epidemiology without the caveat that we do have randomized control trials, for example, the ones that you’ve done.

[ 01:18:21 ] And again, you don’t care either way what the result is. Um, how does someone surf that? Yeah, it’s a challenge and I, I don’t have a good answer because it is confusing. And you mentioned the Harvard group and, um, I know some folks in the Harvard group well, and there are certain things that they are certain ideas that they’re promoting that I agree with completely. So, you know, as an example, the unsaturated fats, um, you know, I align my interpretation aligns with theirs when it comes to things like unprocessed red meat, I have more questions and more doubts. They seem more, more certain about adverse effects. I, on the other hand, um, say, well, I acknowledge that these relationships are present where I get hung up is explained to me, the biologic plausibility and how that would work biologically.

[ 01:19:19 ] And also convince me that it is not the other habits that go along with eating a lot of red meat. What do you do when, again, I’ve been in this situation, um, you, I make that statement. I, I ask that question and then epidemiology is then brought back in or a, uh, data set information is not made publicly available for someone like yourself, like a statistician or somebody else to be able to evaluate that. Do you think that it’s interesting that it then just seems to circle back to data sets that are unavailable or, um, again, circle back on the low quality evidence? Well, this may be changing because NIH funded studies, I, I think the new regulations, I’m not sure exactly when they go into effect, they may already be in effect are saying that you’re gonna have to make your data available.

[ 01:20:15 ] But then the question becomes, well, what’s the mechanism? Because if you just throw it out there for anyone to look at, there can be abuses. And so there, what do you mean? Tell me, tell me more about that. Well, people who have an agenda can use a data set and use it. Yeah. Yeah. Yeah. Yeah. Yeah. Yeah. Yeah. Yeah. Yeah. Yeah. Yeah. Yeah. Yeah. Yeah. It in a way that is selective or inappropriate and generates, uh, results that support their agenda that, you know, may not be real. Have you seen that happen? Um, I, I have, I, I happen to be the co-editor of a journal. What journal? Which one? The Journal of Clinical it’s the national association. I did not know you were co-editor of that. I am co-editor.

[ 01:20:55 ] I’m in the presence of a celebrity right now. So we get a lot of papers. And about 50% of them, we reject, you know, right off the bat; they’re just don’t meet our standards. And then, you know, a certain number go out to associate editors and to reviewers to evaluate. And in that 50% that we reject, um, some portion of them, I suspect fraud, um, you know, you can’t be sure, but some portion, uh, I suspect, uh, are, you know, using approaches to try and tip the balance toward a certain conclusion with, you know, just as an example, if you run a model and you have these covariates that you adjust for, well, you can play around with the model and take covariates out, add covariates in, uh, physical activity is a covariate where you can.

[ 01:21:53 ] Um, express it in various ways. And so, you know, maybe if you express it one way, then the results look a little better for what you’d like to say. And when you express it another way, so that’s, uh, basically scientific misconduct. You know, ideally what you do is: this is what we’re going to do, and we’re going to get whatever results we get. And then we may run sensitivity analyses and subgroup analyses and so forth to try and better understand the data. But. But it’s not appropriate to fiddle with the model until you get a result that supports your agenda and then publish that. And to be fair, things like that, in which you are not the co-editor of the journal, um, and even in some extremely reputable journals, go ahead and publish those things.

[ 01:22:46 ] Maybe because they don’t have a background in nutritional sciences. Again, nutrition science is different than. Mechanistic data it’s, it’s a, it’s different or they don’t know, um, because a lot of those things that are done are done in the background and you don’t really know all of the steps that the investigator took, you know, what they’re presenting, but you don’t know how they fiddled with things to make it look better for whatever conclusion they want to draw. And, you know, it’s a small percentage of people who will do that, but it’s not zero. And. So that is a challenge. Um, and I’m not in any way, you know, the Harvard group in particular, I’m not suggesting that they do that. Um, but I am suggesting that there are groups who will do that.

[ 01:23:35 ] And so, that’s why you do have to have some system in place to ensure that people who want access to a dataset have a legitimate reason and legitimate hypotheses to evaluate. And so I don’t know what the solution is, because if you throw it up there for anyone. Then there are potential abuses, so you have to have some mechanism, but if you’re going to require, as an example, a proposal to go in and be evaluated by a committee, well, somebody’s got to pay that committee for their time and just, it’s such a burden to then go through and, you know, there’s some tier one journals that published something about higher protein, increasing IGF-1 and cancer risk.

[ 01:24:19 ] And then, um, when excellent experts got ahold of these data sets and reran statistics, it was totally inaccurate, completely butchered yet this particular journal article then spread like wildfire. Yep. Just recently there was a scandal. Uh, one of the top researchers in Parkinson’s disease apparently had published a lot of fraudulent data. Um, so, you know, these things happen. And they’re really problematic when they do. So you do want to have some guardrails in place to minimize the possibility of that happening. On the other hand, you also want some transparency, and you’ve probably heard about the reproducibility crisis in science, you know, Johnny and he, he and Edie’s at Harvard, um, says, you know, probably some tiny fraction of what’s published can be reproduced.

[ 01:25:18 ] And so it’s important to not only publish results, but then also to have other people replicate those experiments to show that, yes, this is a reproducible effect. I personally have been involved in studies where we did a study and then we did a replication study, and we had a terrible time getting the replication study published because the results were the same as the first study. And so the criticism was, this is not novel, so we’re not going to publish it. And of course my response is no, no, you’re supposed to publish. Public replication studies. That’s the way it’s supposed to work, but it’s hard. You know, this is actually a really great place to address this idea of funding. Um, I think that there’s a lot of misconceptions out there.

[ 01:26:09 ] For example, when there is a study that is funded by, um, X, uh, association or this various ways. Of funding. And I listened to one of your interviews and I love what you said, and you said you can pay for the researcher, but you can’t pay for the results. Yeah. What I always say is, ‘I guarantee the process.’ I don’t guarantee the results. Talk to me about that or what they are. Well, I’ve had a lot of funding from industry and from commodity boards and pharmaceutical companies and so forth. And what I say is, you know, we promise that we will. Write a study protocol, we will follow that protocol and we will be transparent about, um, anything that goes wrong during the study, which sometimes happens.

[ 01:27:04 ] Um, and so I can guarantee the process, but the results are the results. And so what I won’t do in most circumstances is bury results if it didn’t turn out the way the sponsoring company or organization wanted it. I still want to go out there and publish it. Now, there are some studies we do that are kind of proprietary things. Like if they’re looking at a new formulation of something and they just want to see if this formulation works as well as the old formulation. And then we say, ‘we’re not going to publish those results.’ This is proprietary and we’re doing it for a specific purpose. But when we’re evaluating health-related outcomes, um, our position is, uh, you should publish the results and make them available to the public sometimes with some caveats.

[ 01:27:51 ] Around timing as it relates to a product or what have you. But for the most part, it’s; we did the study, we want the results to be published. Do you still find on social media that there’s a lot of pushback about that? That people will say, oh, in their analysis of this study, that their response will be that this study isn’t valuable because it was funded by X, Y, and Z. Well, that’s the funny thing. Um, you know, that happens all the time. I know. And then I say, well, I’m going to die of natural causes. Right. Because before NIH funds a study like this, so somebody’s got to fund it. You know, if you want the research done, someone has to pay for it.

[ 01:28:28 ] And so, you know, what I say is: You know, Warren Buffett talks about, you can spend, you know, 30 years building a reputation and ruin it in five minutes. So I’ve spent a long time building a reputation for doing good science. And I’m not going to put that at risk by doing anything that is ethically suspect. And so people come to me; they know that. That they’re getting someone who’s going to guarantee the process, but not guarantee the results, and whatever the results are, you know, that’s what they are. And that’s really valuable, which is one of the reasons, again, I was so excited to have you on it and have some of these conversations because, again, we have more access to information than we’ve ever had before. It’s a fire hose.

[ 01:29:13 ] Yeah. It’s a fire hose. However, we have more access to misinformation or individualized information that individuals believe themselves to be experts and old when they’re not. Right. And then the people that suffer are the people that are vulnerable. Right. To that. And that is a challenge. And, you know, like I keep saying, well, I strongly believe in free speech and the right of people to say things I think are crazy. I also am concerned about people who will believe something. You know, I’ve. I’ve recently seen lots of things about, oh, I had breast cancer and, you know, I didn’t go through this evidence-based. I went to an alternative practitioner and, you know, and I’m fine now. And I don’t personally in that case have the ability to evaluate the claims that were made.

[ 01:30:13 ] But I will say it makes me awfully nervous. And I really am concerned about, you know, information. That is not based on good evidence being promoted to people who then make choices that are based on misinformation, even though, again, strong free speech advocate. Absolutely. And I think that nutrition is really a big space where that exists. You know, there’s this overarching discussion between calories in calories out, carbohydrate insulin model. I think that this seems to be ongoing. Do you have thoughts on or potentially concerns about just the interpretation of, say, for example, the carbohydrate insulin model? Again, for me, we care about body composition. Yeah. And so I respect some of the people who are strong advocates of the carbohydrate insulin model. David Ludwig is an example of someone who I think is a good scientist.

[ 01:31:18 ] I think my own opinion is that people who advocate the carbohydrate insulin model kind of just take it too far. I think there’s some truth in it, but I also think they take it too far. And would you say that it is the idea that it doesn’t matter about the calories, that if you are having carbohydrates, if we were to say what the carbohydrate insulin model is, how would you describe that? I mean, the basic idea is that, you know, high insulin. So when you eat carbohydrate, you’ll get an insulin response and the purpose of that insulin response is to take the glucose that’s in the bloodstream. So carbohydrates broken down to glucose, it’s a little more complicated than that. But let’s say broken down to glucose that’s absorbed into the bloodstream.

[ 01:32:06 ] The insulin response is to get that glucose out of the bloodstream and into cells. And so the carbohydrate-insulin model is basically that excessive insulin is going to cause deposition of fat. And result in appetite signals being increased. And so when you have a high-carbohydrate diet, that’s going to drive increased appetite and a hormonal drive to lay down fat. So that’s the basic idea behind it. And other people can probably describe it more eloquently than I think you did a great job. Well done. That’s the basic idea. And I do think that excessive carbohydrate, especially high glycemic index carbohydrate. Is problematic, you know, so I think that the response with whole grains, nuts, seeds, legumes, et cetera, is different from highly processed refined starches and added sugars.

[ 01:33:06 ] I also think that, um, sugars have their own set of issues. So fructose, so, um, sucrose, uh, table sugar or high fructose corn syrup is basically 50% glucose. 50% fructose, fructose, uh, goes to the liver. It’s preferentially oxidized. And so that’s reducing the liver oxidation of fat. And so there is a hypothesis that when you reduce liver oxidation of fat, that will result in signals to increase the liver fat oxidation. And the outcome, wait, so the, the fructose. That is ingested the primary sugar in fruits or which again, depending on the actual load, um, or high fructose corn syrup is really, I think where you’re going with that. Yeah, I, I don’t like a big distinction between sucrose and high fructose corn syrup, as long as the high fructose corn syrup is roughly 50/ 50, like sucrose is, um, which, which most is, um, you know, fructose is sweeter than glucose.

[ 01:34:17 ] So when you consume high fructose corn syrup, um, you know, you’re, you’re trying to create a, a sweet taste essentially. And, um, you know, I do think that overconsumption of things like sugar, sweetened beverages, um, does affect appetite in a way that favors overconsumption. Um, and so with fructose, I also think physiologically, there are some challenges that, uh, fructose seems to drive de novo lipogenesis. And then in addition, it, it may affect appetite signaling in ways that are different from glucose. Um, so, you know, it, the answer is it’s complicated. And I think some of these things are reasonable hypotheses that need further testing, but I do think there’s pretty good evidence. Um, and this is a place where I agree with the Harvard group that a high intake of sugar, sweetened beverages is a risk factor for excess weight gain.

[ 01:35:19 ] And I think we probably all would agree that there are challenges with highly processed foods that are, uh, overindulgent and high fructose corn syrup. Um, I, I definitely think that we’re all recognizing that. I had a veterinarian years ago who said, ‘Feed your dog this, not that,’ you know, ‘this is palatable, but not too palatable.’ And that your dog will like better. But your dog will overeat and gain weight over time. And, uh, I think that that is true. If we have a highly palatable diet, um, that is high in things like added sugars, refined starches, um, and highly processed low in fiber, uh, that is going to tend to, uh, favor overconsumption. You know, um, there’s so much more that we could talk about and.

[ 01:36:19 ] I would be thrilled to have you on back for a part two. Are there any closing statements? Again, we dressed, um, the saturated fat red meat. We touched on the carbohydrate insulin model. I’m so glad that you brought up seed oils. I learned something because again, my bias is, well, it can’t be good despite what I’m seeing, but you know, I, I certainly learned that. Are there again, um, maybe ideas or concepts that you’d like the listener to know? Well, one is that I think lifestyle is incredibly important, but in terms of people’s risk of heart disease and diabetes, we know a lot about risk factors and what things you can control, whether that be through lifestyle or, uh, medication if necessary, or in some cases, even, uh, surgery.

[ 01:37:12 ] If someone, uh, has a body mass index of 44, um, you know, they may not be able to lower their risk sufficiently with lifestyle. They may need drug therapy or even surgery to lower their weight. So we know a lot about these risk factors for cardiometabolic disease. And so the most important thing from my standpoint is to have a healthy lifestyle, but then control those risk factors. And that’s where you work with a physician or other clinician dietitian to help figure out what each individual can do to make sure, sure, that they are controlling those risk factors, keeping the risk of diabetes, heart disease, stroke, et cetera, kidney disease, uh, as low as possible. And would you say there’s a primary, um, intervention standpoint?

[ 01:38:03 ] So what I’m hearing you say is that let’s say someone is controlling those variables. And I do know that you do, um, and have research for, uh, pharmacological agents, which by the way, we use in clinical practice, because for example, these GLP ones, I’ve never seen anything work more effectively. Well, I I’ve spent 30 years studying pharmacotherapy for obesity. 25 years was incredibly frustrating with drugs that had dangerous side effects or didn’t work very well. And all of a sudden, you know, semaglutide and tirzepatide are on the scene and it’s a totally different outcome. And so there’s a lot of work to be done to understand the health implications, but so far, what we’re seeing is, you know, reduced cardiovascular disease, risk, reduced risk of kidney disease, um, improvement in, uh, osteoarthritis in the knee.

[ 01:38:56 ] Um, I mean, you know, so far it it’s looking good. Um, but you know, the ideal thing is to prevent the obesity to begin with. Uh, absolutely. Do you think, um, I’m, I’m very happy to hear you say that because we see that again, I’m obviously not doing research with these, uh, agents, but in clinical practice, we are seeing people that. That have struggled a lifetime. Oh yeah. And then of course you have, um, you know, the information highway start talking about all the, the negatives and I, we don’t see that, uh, again, they’re, they’re not that new on the scene, by the way. Well, 2005 was the first one, um, that was approved, uh, but it didn’t produce much weight loss. It was, you know, for diabetes.

[ 01:39:42 ] So, you know, it wasn’t until the most recent drugs that you saw. Right. So with some of glutide, about 15% body weight loss with trisepatide, about 20% body weight loss. And then there’s a new G3 drug that’s in development. Well, the new one, I’m not sure it has a name. Okay. Um, it, um, actually it does, it doesn’t have a brand name yet, but it’s retatrutide. That’s right. And it helps impact liver fat. Yep. And so all of these drugs, anything that produces significant weight loss will reduce liver fat. And so it’s not surprising that these drugs are producing significant weight loss and then also reducing liver fat. They also reduce inflammation. So. And is that because they’re reducing excess adiposity or are there other mechanisms of action?

[ 01:40:31 ] I think there are probably multiple mechanisms. So if you look at the SELECT trial, for instance, which showed some of glucagon-like peptide reduced cardiovascular disease risk, there was some weight loss, but it wasn’t really dramatic. It was about 9%. And, uh, yet there was a very large reduction. And C-reactive protein, so 40-ish percent reduction in C-reactive protein. And if you look at the relationship between the C-reactive protein reduction and weight loss, it wasn’t strong. So that suggests that there are other mechanisms that need to be worked out. But I think that’s part of the benefit of these drugs is reducing inflammation. And are you seeing, I don’t know if you’ve looked at this, but the body composition, weight loss effects, there’s a lot of discussion around the effect on skeletal muscle.

[ 01:41:17 ] The data that I’ve seen seems to be, again, this is only mechanistically, but it seems to actually improve skeletal muscle health. Well, yeah, that’s a little bit complicated. So, um, you don’t say, you know, so roughly 25 to 35% of the weight that is lost, whether we’re through lifestyle or GLP-1 receptor agonists is lean body mass. And typically about 50% of lean body mass is skeletal muscle mass, but with a lot of variation around that. And then when people lose weight, well, up until recently, we didn’t see a lot of weight loss in people. So now we’re seeing more weight loss. The percentage of the weight loss that’s lean body mass is about the same as you see with lifestyle, but people are losing more weight.

[ 01:42:01 ] So losing more lean body mass, but we don’t have really good studies on how much of that is skeletal muscle mass. So that remains kind of a question mark. And then the second issue there is when you lose body fat, you lose, uh, intramuscular fat, and that sometimes improves function. And so you may have less skeletal muscle mass, but what’s there is functioning better. And so when you, you know, look at the data, it’s limited right now, and we need more data. And this is especially important because so many millions now of people are taking these medications that we really need to better understand what is happening in terms of their effect on body composition. And it may be different according to diet.

[ 01:42:50 ] You know, some people maybe may have a terrible diet and then they just less of the terrible diet. Now they’re losing muscle mass. Whereas someone else may be consuming a higher quality diet, adequate protein exercising. And so they have less skeletal muscle mass loss, even though, you know, they may also be losing lean body mass, um, that is appropriate. Um, because. You know, as, as you get smaller, you don’t need as much of lots of things, skin for instance. I think it is, it’s interesting and they are here to stay. Would you agree with that? That we are just going to get generation after generation. That’s what I expect. I expect it’s, it’s gonna be like, uh, a lot of things where we see generation one, generation two, generation three, and, you know, then when the reasonably effective ones go generic, then the question is gonna be, well, you know, how do these newer entrants differentiate themselves?

[ 01:43:50 ] And, you know, fortunately, when you have generic competition, that’s when the cost goes down and they become more accessible to people. Do you have any concerns about these agents from a health standpoint? What I would say is that with any medication, there is potential risk. And so, you know, nothing is risk-free. And so, um, Lane Norton has this great expression, ‘shoot the alligator closest to the boat.’ We know that. When somebody has a very high body mass index, that they’re at increased risk for many adverse outcomes. So we know that reducing body weight will lower that risk. We don’t maybe fully understand the long-term effects, you know, of taking a GLP-1 receptor agonist for, you know, 25 or 30 years, but we do understand the long-term effects of obesity.

[ 01:44:37 ] And so I’m with Lane, shoot the alligator closest to the boat. Um, I, I actually really love that because I, I think one of the, there is. A black box warning on the, on these GLP-1s, uh, last time I checked, it was there and it was this increase in, um, thyroid cancer, in medullary cancer. And I was very concerned about that. And then looking at what they are saying, where that came from, it’s really some of these rodents, animal studies, which rodents have different densities of thyroid. Different densities of those receptors in the thyroid. I mean, some of them. So that falls into the category of a theoretical risk. Um, and you know, would I be shocked to find that there is some increase in risk?

[ 01:45:24 ] No, but I also know that obesity is associated with many types of cancers and bariatric surgery is associated with 50-ish percent reduction in the risk of a cancer diagnosis. So I, I say, you know, we may not know exactly what the balance of risks and benefits is, but. What I know now. I was there late though. So what I know now just suggests to me that the benefits are, you know, outweighing the risks for people who are appropriate candidates. Person who’s not an appropriate candidate is someone who is going to a wedding and six weeks and wants to lose a few pounds to fit into a dress. That’s not an appropriate use for these medications. I think it’s it again. It’s so, um, enlightening, and I’m so glad to hear you again.

[ 01:46:10 ] My bias. I’m so glad to hear that you agree that while these are theoretical risks, you know, again, these drugs have been used by endocrinologists; release the, you know, semaglutide for at least 10 years. Yeah. Yeah. And like I said, the first one was in 2005. So it’s almost 20 years that it’s been available in clinical practice. Wouldn’t we see if there was, you know, for example, fen-phen wasn’t, I don’t think it was on the market very long. This was a stimulant that caused some kind of valve disease. PTSD from that. Our clinic. Oh, it was your fault. No, I understand. Totally our fault. No, our clinic did a fen-phen study and then this issue with heart valve defects came out. And so then we had to bring all of the people back for serial echocardiography.

[ 01:47:01 ] It was, you know, and it was so terrible because, again, that was one of the first drugs that really worked or it was a combination of two drugs that really worked. And so. These people really happy with the results, you know, except, you know, not when your heart valves, uh, stop working properly. So I, you know, I, I, I think that, um, again, we we’ve got roughly 20 years of experience with the class, but not necessarily at the doses and with the particular agents that are being used now that produce significant weight loss. So we’ve got experience with use of them for management of diabetes, but we have. Less experience at the doses and with the agents where they’re producing significant weight loss. Well, Dr. Kevin Mackey, it has been such an honor and privilege. I’m so grateful that you were willing to take the time to share your knowledge. The world definitely needs to hear more of you. So thank you so much for coming on. Thank you so much for having me and all of the kind words.