#368 ‒ The protein debate: optimal intake, limitations of the RDA, whether high-protein intake is harmful, and how to think about processed foods | David Allison, Ph.D.

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Week is David Allison.

David, returning for his third conversation on the Drive is a world renowned scientist and award winning scientific writer who has been at the forefront of obesity research for the last 20 years and is currently the Director of the Children's Nutrition Research center at Baylor College of Medicine. I wanted to have David on because protein has become one of the most contentious and confusing topics in nutrition today. What was once a fairly straightforward subject has now turned into a debate full of conflicting claims, dogma, unnecessary controversy and a whole lot of name calling. David brings both a deep understanding of the science and a clear eyed perspective on how to separate evidence from opinion. This is part one of a two part deep dive on protein and next week I'll be joined by Rhonda Patrick for part two, after which we'll put this protein discussion to rest once and for all. In this episode we discuss the historical cycle of demonizing macronutrients and why protein has recently become the focus the origins and limitations for the RDA for protein and what the evidence suggests about optimal intake for health, longevity and performance Conflicts of interest in nutrition science and why transparency around data, methods and logic matter much more than funding sources the challenges of conducting high quality nutrition studies, including the debate over crossover designs, the limits of epidemiology and the underfunding of rigorous trials compared to pharmaceutical trials what the evidence really says about higher protein intake, muscle protein synthesis and whether concerns about harm are supported by actual data how to think about processed and ultra processed foods including definitions, heuristics and and the question of whether they're inherently harmful or simply a convenient villain and finally, the difficulty of tackling obesity through public health, the limits of current approaches and whether future solutions may rely more on drugs like GLP1 agonists or broader societal changes. So without further delay, please enjoy my conversation with David.

All.

Right.

Hey, David, thanks for coming back. This was probably the shortest trip you've made here, right? You've got a new home.

Yeah, I got a great new gig at the Children Nutrition Research center in Houston, Texas, and Baylor College of Medicine and Texas Children's Hospital. I'm having a great time. So it was just a nice, easy car ride over here.

Very well. Well, we're going to actually start by talking about something that, believe it or not, I don't want to talk about because I'm kind of sick and tired of talking about it. And I'm going to apologize in advance to all the listeners because if they've been listening at all, they're probably sick and tired of hearing about this. But unfortunately, this is a topic that has gone from being what I would consider pretty straightforward to somewhat contentious. And I'm going to do my best to refrain from speculating on the reasons why it's become contentious, although I have many views on that and many views on the people who choose to make it contentious, which I'll also refrain from. But let's just try to dive into the arguments around the macronutrient that is more in the crosshairs than any other today, which is protein. And that's kind of interesting when you consider the arc of your career. It was certainly easy to understand how people demonized fat and then they demonized carbs. And here we are today, coming full circle, we're demonizing protein. Where do you place that in the arc of the historical lens of nutrition?

It shows many things, but at some level, it's almost perfectly predictable, which is we all eat. We eat every day. Eating is part of our sustenance, but it's part of culture, family, certainly part of economics, identity, social class, religion, and so on. And so it's fun to talk about. And there's lots of motivations, motivations people recognize and motivations they may not recognize. And that leads always to this attention on it. That attention drives a big economic engine of food sales. So there's lots of interest in this and lots of stakes in this, if you'll pardon the pun. So people shift. And it's not even just the macronutrients. This week it's seed oils, and next week it's phytoestrogens and soybean feminizing youth. And it's one thing after another where people look for the villains and the heroes and the angels and the demons in food. Only three macronutrients, so they keep looping around. Protein has become in the last few years, almost a fever pitch of enthusiasm and excitement from one part of the community. And it's driving sales and it's driving behavior. And some people, like me, are having fun with it. And then I think there's always that group that sees other people having fun or making money and heaven forbid, doing something that might be seen as the easy way out or the contrived or constructed way out as opposed to the so called natural way out of doing something. And then that upsets them, that offends them. You're not being prudent, you're not taking the natural course, you're not taking the old fashion course. You're having too much fun, you're trying too hard to achieve big things. We don't like that. So we're going to try to pooh, pooh it or shut it down or minimize it. And I think that's where things are.

So presumably at some point this will no longer be relevant and no one will talk about it and we'll move back to fats being the bad thing. Although I guess we're kind of there with seed oils to your point. But let's talk a little bit about protein. So a lot of the consternation stems, I think, from a debate around the RDA and the recommendation of 0.8 grams per kilogram of body weight. Do you want to tell folks a little bit about where that came from? Where does this ubiquitous recommendation that we consume 0.8 grams of protein per kilogram of body weight? So again, just to put that in perspective, I weigh 180 pounds, so that is probably 82 kilos. So I should be eating about 60 to 65 grams of protein according to the RDA. It's the middle of the day. I've had 60 grams of protein today, so I could basically stop eating protein for the rest of the day now, right?

Yeah, some people would say that now. Others, I don't know if I would go so far as to say at the other extreme, but a more active proponent of the importance of not only greater amounts of protein, but particular types and distributions and so on would be somebody like Don Layman. And he might say, I hope I'm not inappropriately putting words in his mouth. But I think he might say, peter, you actually need to be eating protein at least three or four times a day. Yeah.

Because that 60 was in one sitting, by the way.

Right. And at each of those sittings, you probably want to hit about 30. I emphasize that word about. It's not like there's some mathematical proof that there's some hard threshold, and certainly not for you, who is 20% bigger than me, that your hard threshold will be the same as my hard threshold, but in the neighborhood of 30. Right off the bat, if you follow that advice, you'd need to be having double that amount of protein, and you'd have to have it distributed differently. And if you haven't distributed the way you currently did, it'd be more than double. So I think there are a lot of people who disagree with that. The history is people at some point recognized that we needed protein to live. The key indicator of that was nitrogen. And people looked at nitrogen balance. How much did you take in? How much did you excrete? And they found that people could achieve nitrogen balance, or at least sort of ordinary, normal people of the time at about that level. No one ever proved, demonstrated, or I think, even claimed that that was the best amount or the upper limit, or it was just that's probably enough to maintain nitrogen balance, which probably means it's compatible with survival. And if you think about the early days, that was pretty important. Europe couldn't reliably feed its population until two things were entered into Europe. One was guano, bat poop, fertilizer, and the other was potatoes. And when after the Columbus hit Hispaniola, and eventually what came back was, among other things, guano and potatoes, suddenly Europe could feed its population. But it took a while for the potatoes to catch on. Louis XV actually wore potato boutonniere to get people to think they were kind of safe. Two Polish scientists in 1928 published a paper in which they had two young people. They never said they were the young people, but I kind of suspected perhaps they were one man, one woman. And for six months they fed them nothing but potatoes. A little bit of fat to cook the potatoes in and a little bit of fruit to avoid deficiencies. So the only source of protein for practical purposes was the potato. And what they showed was nitrogen balance was perfectly fine. And despite sort of this quote, unquote, bad carbohydrate, or at least some people think it's a bad carbohydrate. No one got diabetes. They didn't gain weight.

How many calories did they eat a day?

Don't remember that. But they were sort of roughly normal weight, thin people of the time. So probably, I would guess a little more than 2,000, 2,000, 2,000. 500 somewhere in that neighborhood. As I said, they did nitrogen balance studies and they were perfectly fine. But that's entirely different than saying what if they were older people? Or what if they were pregnant? Or what if they were recovering from a bicep tendon tear or what if they were bodybuilding. Those are all very.

Or what if they were active.

Yeah.

So when we go back and look at some of the USDA based studies on this topic and we wrote about this. So the subjects for this study were, if my memory serves correctly, lean, inactive, sedentary young men who are, I think.

You said, about £150 if I recall.

Yep. Yeah, maybe even a bit lighter. But yeah, about that. So these are guys that weighed 65 to 70 kilos, very inactive. And nitrogen balance was demonstrated in them that you could achieve it at 0.8 grams of protein per kilogram. So again, let's just do the math, make it easy. Say 50 grams of protein was able to keep these folks in nitrogen balance. It's interesting that everything you said, this is true of, I think, clinical research. You have to look at the population that is studied and ask the question, how do I differ from that population? Am I bigger? Am I training? Do I have a more ambitious goal than not dying or not wasting away? And I don't want to minimize those goals because you alluded to the fact that for the vast majority of human history, not dying was an amazing goal. Living to the next day, to the next harvest, to the next season was essential for 99.99% of human history. So this idea that being optimal or thriving, it's a very, very modern luxury.

We have, it's both modern and ancient all at once. So yes, you are correct. But also the idea that there are different kinds of goals that we optimize is actually the very nature of evolution what's being selected. And Steve Simpson and David Raubenheimer from Down under, from Australia, studies something called the protein leverage hypothesis. We may want to come back to at some point. What they've shown is that what at least some animals do in experimental settings they're able to set up is they consume enough protein to optimize their genetic fitness, meaning how many of their genes they're able to transmit to the next generation, which is if you want to win the evolutionary game, that's your goal, which is different than living a lot longer. That's winning the personal game, but not your genes games. So yes, it matters. And it may be that we now want to shift a little from one toward the other. And it may even change during the course of life. It may be that at one point in life, my goal is to be as perhaps big and strong as I can. Maybe at another point in life, it's too slow aging. I may have different strategies for those two different things.

Before we go any further, I should have done this at the outset, but I realize that some people are going to be watching us on video and they won't hear the introduction where I'll have made this point. But we should both disclose that we're involved with a company called David Protein that makes protein bars, because we're going to be talking about protein today and unrelated but related. We're also going to talk about processed food, which I think is a very interesting topic. This is a company that makes high protein bars, which are by definition processed. And so I just want to make sure everybody listening understands that I'm involved in that company. You're an advisor as well, and I'd like to hear your thoughts to the argument that says, well, Peter and David, you guys can't really have an open and honest discussion about this topic because you have this conflict of interest. I mean, I have my own thoughts on an argument like that, but I'd like to hear yours.

Sure. Just a couple of factual points of clarification. So, yes, I have a grant from and have been a paid advisor to the David Protein Company. Second, the David and David Protein is not my David. I don't own the company. I like the bars. I eat them. And every time I take one out at a meeting or something, someone will look at me and say, how vain are you? You have your own personalized bars with David printed a big. I said, no, it's not me, it's Michelangelo's David. The idea is, you eat the bar, you'll look like that, David. But I've also. We had a protein conference we ran about six months ago. It was amazingly successful. The degree of interest from academia and industry and others are tremendous. We must have had somewhere on the order of 50 different companies contribute. So I'll disclose that as well. So I have a lot of interest in this. I've had funding from National Cattlemen's Beef association, pork producers and other groups with interests in protein. In terms of the idea of does that make us trustworthy or not? I distinguish that from trusted. Whether or what makes us trusted, that's somebody else's judgment. Trust me or don't trust me however much you want, that's up to you. Trustworthy, I think, has to do with the processes. And my colleagues and I, we have a saying we've sort of coined and we like to use a lot. And we say in science, three things matter. The data, the methods used to collect the data, which give them their probative value, which shows what they mean, and the logic connecting the data to conclusions. And everything else is tangential. And so some people who don't have the goods on an argument will resort to other things. They'll resort to ad hominem attacks, they'll resort to innuendo, they'll resort to quips. Quips are great. Innuendo and ad hominem attacks, not so great, in my view. But none of those are dispositive. And when we think about things, we can really declare things known or not known. No one needs to argue about your conflicts of interest. If you say that I can prove that there's a greatest prime number, and people say, well, no, Euclid proved there isn't. And I don't have to say, maybe you're paid for by the prime number company or something, I can just say, here's the proof and you're wrong, and there's no point in discussing anything else. The prime number company.

Think of the value, David, of prime numbers. If they were finite, can you imagine how much the value of 3, 5, 7, 11, 13, like those numbers would increase in value so much more if they became finite.

Think today of like Bitcoin decoding and encoding Bitcoin.

Yeah, that's a very elegant explanation, and I think it's worth reiterating that point, which is, at the end of the day, the three things that matter are what are the data, how were the data collected, what were the methods used to collect them? And then what is the string of logic that connects those data to their conclusions? And all of these things should be quite transparent. Now, you've chosen a career, a field of inquiry, in which it can be more difficult to do all of the above than in, say, genetics or biochemistry or particle physics, where one of those steps is, in your case, particularly difficult, and that is the manner in which data are collected. In other words, I don't think nutrition scientists are at a loss for logic, but where I think they struggle, if they're studying humans at least, is collecting these data can be really challenging, really expensive. The species of interest is not amenable to close quarters for long periods of time, which is how you would obviously run a controlled experiment in a biological setting. So this is maybe more of a philosophical question, but what is the future of Nutrition Science. We're going to come back to the main topic, but this is just such an interesting tangent. Do you believe that there is a much brighter future, a step function and improvement in the quality of nutrition science that lies ahead with AI, synthetic data collection or creation rather? Is there something that could fundamentally change nutrition science in terms of how we go about gathering data so that we could be potentially less reliant on epidemiology, which I'm sure we will discuss the shortfalls of today?

I think the answer is things will get better whether it's a step function or not. I'm not so sure I want to expand or add to the branch you've thrown in and add a parallel branch, which is. I think there are two reasons why nutrition science is so fraught. One you've pointed out is the methodologic challenge. Can we collect the kind of data we really want with the kind of methods we really want? The other part is the social aspect which you've hinted at until we've gotten to this point, which is why is it so emotional? Why do people attack each other? Why do people go beyond the data? And I think I see that in any area. The more that area of inquiry is related to economics, religion, social values, personal experiences, the more you get the emotion and the deviation from logic and so on. And we see it in whatever people study, child rearing, same sex marriage, anything that has that emotional valence, that everyday experience and so on, leads to more bringing in of non scientific points of view. So I think that's something we have very strongly. And then I think the other we have is the methodologic challenge of collecting the data. I see benefits on both fronts, but I think both will be slow. I don't think in many cases it's going to be a simple thing of if we could just fix that, if we could just figure out how to measure food intake in free living people, well, and we're on the horizon, then everything will be okay. That's important. I hope we do figure out how to measure food intake well in free living people, but that alone will not be a solution, a sufficient solution. What I think on the front of the emotional piece is it's going to come slow. When you look at the arc of history of much of human endeavor, at least from my point of view and the point of view of I think people like Steven Levitt and so on, you look over the long haul, things are always getting better. You smooth the function a little bit, murder rates are way down, violence Rates are way down, education rates are way up, lifespan is up, et cetera, et cetera. Freedom is up. But there are lots of ebb and flow. So we may be in a little bit of an ebb and flow now, but I do hope that things will get better, as they always have some more and more rationality. And that's something that as a scientist, I feel very strongly about. As scientists, we focus too much on immediate trust in science and saying we need to get more trust in science and on immediate issues. How do we get trust in this issue about vaccines or drugs or what have you, instead of saying, how do we get trust in the scientific process? How do we maybe risk losing a battle? Maybe I'm not going to convince people today that what I think about food additives or vaccines or protein or something is quote, unquote, the right answer. And I have to live with that. But if I can convince them that I'm an honest broker and here's how science works and we can work together through science in the long run, I think that's better and I think that's coming and something we need to focus on. In terms of the nutrition per se, we have so many challenges, but as a methodologist, I like challenges. Job security and it's fun. I like figuring things out. So we can't randomize to everything. So how do we get causal inference? We can't blind every aspect of diet. And if we could, we'd be missing some of what we're trying to study because some of the effects of diet involvement, the effects of perceiving what you're eating, some of the effects of this drink I'm drinking is how it tastes. And if you blind me to it, then you've taken away that potential effect. There are issues of measurement. How do you know what I really ate? There are issues of adherence. If you tell me to drink one of these every day, do I actually do it? Do I drink one and only one as you've instructed? There are issues of duration. Could you get me to drink it now and measure Something in me 15 minutes later? Sure. Could you get me to drink one every day for the next 20 years and measure stuff? Difficult. There are issues of the model organism. One thing is we're going to talk about longevity a little bit. Somebody once said to me, you never want to study longevity in an organism that lives as long as you do. It's a bit of a challenge. If you and I at our age were to start, especially mine, I'm a little older than you were to start a big study and say, I want to study 20 year olds and give them different nutrition and see who lives longer and that'll help me figure out for myself what to eat. I'll be dead long before the study is in and not be able to benefit from it and also not be able to find the answer. And maybe we want answers before 60 years from now. So those are just a few and I could go on and on. Those are just a few of the many challenges we have in nutrition and I think we're going to chip away at them. But a lot of it's going to have to be settling for various rough inferences to say this information, I need to recognize its limits. I need to be honest with the public about the limits. I need to say, I haven't shown this unequivocally, but it looks like this is the most reasonable answer now or the most supported answer now. And I'm willing to accept that. But let's be honest, it's not demonstrated. Great example of that. You're seeing the feud in the literature now between Kevin hall and, and David Ludwig on the use of crossover designs as an example and crossover designs in which you give person, let's say diet A followed by diet B and you give other people a randomized to diet B followed by diet A. They have an Achilles heel that is not there for, let's say, parallel groups where it's just some get diet A and some get diet B. And that is you can have what's called carryover effects. And it turns out I've started to study this. Tip my hat to David Ludwig who pointed the issues out to me and I hadn't fully comprehended them before, that there's almost no way around it.

Even with a washout between the crossover.

Not an absolute way. You get into what I call argument land. You can say, come on, David, it was a blinded drug I gave and I know the kinetics of it and I know it's out of the system by this date. How could it possibly be having this? And I could say, well, Peter, you're probably right, it's a good argument, but the validity still depends on your argument. It's not an absolute a priori proof. And if I said, well, maybe what the drug did is it permanently changed something in that person.

And we should just explain for listeners why this is an important discussion in science, especially in human trials and especially in human trials with nutrition, because there's a real statistical power and I don't use that in the Beta sense of the word. But a statistical gift that comes from being able to do a crossover in that you can now leverage a student T test, for example, as a very powerful statistical tool that allows you to use fewer subjects and therefore a fraction of the cost. So I'm guessing, I don't follow this debate, by the way, but I'm going to guess that you're going to say Kevin hall favors a crossover. Not to speak for Kevin, but I would bet the reason Kevin favors it is because the type of work Kevin does is insanely expensive. He's putting patients in metabolic chambers, and therefore the fewer patients that he needs to do that with, the easier he can do his work. Is that basically the argument?

You're absolutely correct. And when you said statistics in the or power, rather in the beta sense, that is what it is. It is statistical power. The probability of rejecting the null hypothesis if the null hypothesis is false, which is 1 minus beta, the type 2 error rate, there's actually a little bit more. But I think 90 plus percent of the motivation is what you've described the other as. Actually, Kevin pointed out to me in some dialogue we were having was sometimes it's just throughput. Even if I had infinite money, I can't put people through the procedure fast enough because there's only so many chambers. Someone else pointed out to me it could be patient availability. If you said, I'm studying this in this rare population, I can't get 1,000 people even if I had the money, because they don't exist, I can only get 10 or 20 people. So all of those things strongly favor the crossover, which in almost all circumstances will be much more statistically powerful, meaning you can get the same amount of precision out of many fewer subjects. But the problem is that you have this carryover, and so that the difference between the two groups who get treatment A and treatment B in the second period could be a function of the true effect of treatment A versus Treatment B in the second period, or could be an effect of what treatment A and treatment B did in the first period, carrying over. And now you don't have a clean estimate of the effect of treatment A or treatment B anymore. Now what you can do is what you said is a washout. If you said, I understand how this thing works and it's a molecular effect, it's not a social effect, it's not learning, it's not a surgical thing, and then cut a piece of their anatomy out that doesn't reverse this thing is completely reversible, it's completely Blinded, I gave a long enough washout. Then by that argument, you can say, I rule it out. But you can never say I absolutely rule it out if you're dealing with things other than that, where you can't have a long enough washout. Or it might be a psychosocial effect or a learning effect or some permanent effect, anything from bariatric surgery to something like an allergen which may permanently sensitize the body. I know people say MRNA vaccines, maybe the MRNA hangs around for a while. Is that a permanent effect? Or a vaccine itself is a, we hope in some cases is a permanent effect, like a measles vaccine. All of those things, they're not gonna wash out. So those are things where the crossover has a limit. And the question is, does that mean you try to do what David Ludwig is, I think, arguing again, I hope I'm not inappropriately putting words in his mouth, is saying they're just invalid. Just either don't use them at all or you can only use them in this way. And if you get what looks like it might be a period by treatment interaction, then discard the study, it's invalid, so on. Or do you say, which I think Kevin would say and I would side with, is accept the limitations of the study. It doesn't mean it's a flawed or incorrect study. It means it's a limited study. And as long as you point those limitations out, you may or may not want to accept it. In the same sense, if you have an observational epidemiologic study. I think most of us, again, there are exceptions, but most of us would not say, never do one again, they have zero value. What we'd say is they're not invalid studies in and of themselves. What they do is they leave open alternative explanations for findings other than causation. Could be some bias of measurement error, it could be some bias of sampling, it could be some reporting bias, it could be some confounding, et cetera, et cetera. And we say as long as you acknowledge those, then the study shows what it shows. It's weak inference, but it's not nothing. And I think the same thing is with crossover. And we may have to accept that with lots of stuff, that's the idea of nutrition. We may have to accept there are these limitations of our knowledge. So, for example, if you do a study of cheddar cheese made in Wisconsin versus some appropriate control and you say, look, this is what the effects I get of this. And so therefore cheese consumption has this effect, I said, well, Peter, Are you sure it's cheese consumption in general, or is it just cheddar cheese? Is it just cheddar cheese made in Wisconsin or is it any cheddar cheese? Is it only cheddar cheese when eaten with these other things or these? And I think that's something that's so hard to control in nutrition that we'll wind up with these statements of saying, it looks like it's cheddar cheese in general, and maybe we can do some other studies to suss it out, or it looks like it's cheese in general, but we'll always have this sort of saying, this looks like what it is. Here's a good recommendation. But it's not absolute knowledge.

Well, with that, let's go back to where we started, which is the RDA for protein consumption. Now, many folks, Don Layman and others have argued that the RDA is insufficient if you're actually trying to optimize health, and if you're actually in pursuit of another agenda, which might be avoiding sarcopenia later in life, achieving your peak in physical performance. That's not the peak of physical performance. Right. But if your objective is beyond survival, you might want to have more. And the numbers for what more tends to be seem to converge in the ballpark of 1.2 to 1.6 grams per kilogram if you're trying to go for a minimum effective dose, but easily up to 2. So what is your best aggregation of the data on where you start to reach diminishing returns? I hesitate to talk this way because it's the way I think, but I know it's not the way others do. I always think about the concavity of a curve. So the more concave down it is, the more negative the second derivative, the quicker you get to that point of diminishing return. It just means the curve is shaped that way. And so most things in biology work that way. They're not positive second derivatives, where the more you do, the better it gets. And the rate at which it gets better goes up. That's very rare. So what is your gestalt on the optimal zone based on all of the above?

Yeah. I think it's important to distinguish between concave downward or a curve that doesn't keep accelerating. A decelerating curve curve with a negative second derivative versus non monotonic. Those can be non monotonic, but it's not the same thing. So one is the diminishing returns. It keeps going up, but it goes up ever more slowly. And there may be a point at which it never reaches. And that point that it never reaches may not be 100% of whatever it is you're thinking about. That's different than saying it else actually goes down at some point. So a lot of things go down at some point.

That's right.

Too little will kill you. Too much will kill you.

And that's actually more common in biology. Right. So too much thyroid hormone, too little thyroid hormone, a very bad thing.

Too few calories. Too many calories.

That's right.

In the case of protein, if we're thinking about it not in an absolute sense, but as a percent of calories, let's just say, and let's assuming your calories are at an appropriate level for whatever it is you want to your life. What I think we can say with pretty good confidence is there's some level that's too low. I think we can also say with pretty good confidence that there's some level above the RDA that with very, very rare exceptions perhaps is at most not worse than, and in the vast majority of cases likely better than the RDA level. You might think of it as the real base level, like economy rental. And then there's the higher end good rental. And then there's something further out there where I would say there's less certainty. And that's where probably a little more of the debate is. So there's not no debate between the base level and what I'm saying is closer to the perhaps I don't want to use the word optimal because that implies a dip, but superior, known superior level, little debate in between, but not so much in my view. And then there's more debate about beyond the known superior level and a lot of uncertainty there. I think the evidence is very clear that when you go from the RDA level of 0.4 ish grams per pound or 0.8 ish grams per kilogram up into roughly double or even a little bit more of that, roughly 2. I know no evidence of harm in any group other than perhaps again the very rarest folks. And even that would typically not be protein in general. It would be specific types. So if you said to me phenylketonuric can't have phenylalanine, okay, fine, someone who's got allergy to whey protein can't have whey protein. But that does mean protein in general. I know of no evidence for harm even in people with chronic kidney disease or anything else. I think there's lots and lots of evidence for benefit in at least medium term observable Phenomena like body weight, like appetite control, like bone strength, muscle and so on for people to be consuming more. And I think it's especially true in people who are recovering from injury, bodybuilding, looking for performance in athletics, looking for strength, who are older, who are growing, all of those things.

I mean, sometimes, David, I think it's easier to flip it and just say, why don't we just identify all the people who don't benefit from a higher amount of protein than the rda? Because I worry that when we start to carve out a bunch of categories and say if you're in one of these categories, you should be consuming more, you're always going to kind of miss something or someone might not identify. So, for example, you've used the term bodybuilder. Most people would never identify themselves as a bodybuilder because when they think bodybuilder, they think of the caricature type bodybuilder we see on a magazine cover when you're at the airport that doesn't actually look anything like what you want to look like. But the truth of the matter is it's hard for me to imagine, I don't know that I can think of one of my patients, let me just start with that as a sample size. One of my patients who doesn't need to, at a minimum, work hard to maintaining their muscle mass. And many of my patients are working hard to add muscle mass. And so what differentiates them from a bodybuilder? The difference is the bodybuilder, of course, has the benefit of using super physiologic doses of androgens, consuming basically training all day and doing nothing but optimizing around that. But the reality of it is we're all sort of bodybuilders. Everybody's a bodybuilder if they're really thinking about it. In the lens of what are we on this earth for? We're on this earth to create the most robust body we can have and it doesn't have to look like it's bulging with muscles. First of all, most of us couldn't achieve that if we wanted to, notwithstanding the fact that most of us could never achieve it anyway. Let's think through who should be consuming the rda.

I would say with rare exceptions, the answer is probably no one.

Okay? I mean, that's a very important statement.

There are rare exceptions. It goes back to goals. You might say you might find people, in fact, not might. I think you almost certainly would who say, I don't care about any of those things. You Just mentioned, the only thing I care about is saving the planet. And my thing is I should eat as little as possible and as little protein as possible and as little animal product as possible. For that, somebody else could say, my goal is to be nearer to God, and this gets me nearer to my God in my way. Someone else, my goal is an aesthetic. I want to look like a heroin addict in a doorway in Manhattan in 1970. That's your aesthetic. But those people are rare.

I think it's really important for people to understand that this argument around the RDA is adequate and that's what you need to eat. And anybody who is suggesting you eat more than that is wrong. We have to actually flip the question and say, okay, who is best served by eating at the RDA versus, say, 2x the RDA at 1.6 grams, which for me would put me at 150 to 160 grams of protein per day instead of 60.

I think here's where we get into that issue of recognizing the limits of our knowledge and then being able to wrangle with them rationally as opposed to irrationally state the limits of our knowledge. So I put up a LinkedIn post and I put up many about protein in the last 12 or more months.

Yeah, we'll link to them all in the show notes here so that people can kind of. I don't want to make this a discussion where we're plowing through paper, because that's already been done, and we'll link to all those things. But yes, I'll make sure that everyone goes back to them. So feel free to reference specific ones so they'll have access to them immediately.

And one of them, I included, a quotation was from one of my old mentors in graduate school, Harold Uecker, who famously said, I'm a data nut. Students gave him a T shirt that said that. And he would say, show me the data. It was time, I think, of that Jerry Maguire movie being popular. Show me the money. He was like, show me the data. So what I sort of said is, people keep raising these questions of harms. I said, show me the data. Can anybody send me? And it was sincere. I said, this is an open call. And I sent it to some of the top people in the world, including those who are a little bit hesitant on protein intake or denigrated. And I said, can anybody send me one or more papers that are intervention studies, not observational ones, that are in humans, ideally randomized, but I'll take an intervention, even if it's not randomized, but it's gotta be controlled. Controlled intervention study in humans feeding different levels of protein in which the different levels of protein intake are separable from other effects that show deleterious effects on a clinically or intrinsically meaningful endpoint. Don't show me that this molecule changed or this gut microbiota changed. What do I do with that? Why do I care that that gut microbiota changed? Nobody cares about those things intrinsically. We care about them only insofar as if they give us heart attacks or strokes or earlier or later death or greater strength or make us better looking. We care about how long we live, how good we look, how we feel our strength, what we can do. We don't intrinsically care about whether this molecule in our body is higher than that molecule or this gut microbe. And I said, can anybody send me one? Nobody.

I was on part of that thread, David, and wasn't there one paper that did surface that was a TPN trial, Total parenteral nutrition in patients in the icu?

I think there were some, I think that Dudley Laming sent, and Dudley's a great scientist and a good friend who studies protein mainly in mice and other things, but also a little bit in humans. And I think he cited a couple of references and I think they were from Luigi Fontana, if I recall correctly. And there was some short term trials in patients with cancer and I don't remember all the details.

Yes, I'm working my hardest to give an honest look because I think what you did is the right thing to do, which is, look, guys, we're having religious debates on social media where people are using their Twitter platforms to like lambast people they disagree with and call them names and do all this sort of nasty stuff. Why don't we just do this like grownups and show me the data. And so the data is show me human clinical trial intervention studies that demonstrate the deleterious effects of quote, unquote high protein. And yeah, the only thing that I saw was you took these patients who were very, very sick in the icu, so sick that they can't consume enteral nutrition, which means they can't eat because they're probably ventilated and their guts aren't even working, so you can't actually put feeding tubes in them. So you use a central line, you put a intravenous catheter into one of the major central veins in their body and you give them all of their nutrition through that conduit, which is called parenteral nutrition. And with total parenteral nutrition, you are chemically crafting the exact composition of what they consume, exactly how much glucose, exactly how much fat, what type of fat, how much protein, what type of protein, what micronutrients, et cetera, et cetera. And again, I don't remember the exact study, but it showed that there was no benefit to a higher protein diet. And this was counterintuitive. Now that I'm remembering it, I believe the study sought to ask the question, wouldn't patients in the intensive care unit benefit from a higher protein diet because they're very catabolic. The body is incredibly catabolic in that setting. And so I think the surprising outcome of that study was that the patients on the higher dose of protein did know better. If my memory serves me correctly, they didn't do worse. Am I remembering that correctly?

If my memory also serves me correctly, there was no statistically significant effect on what I would call an intrinsically clinically important outcome. There wasn't a statistically significant effect on lifespan.

Right. And in that patient population, death, mortality is the most important outcome. There are other things. Days in the icu, days on the ventilator, those things all matter tremendously. But you're looking at such a sick population that's on the precipice of death that when you look at ACM or all cause mortality, you're going to get some interesting and valuable insights.

And we're also going to have to really dig into this idea of when we've got different sources of data and none of which are the data we really want. What we really want is the randomized controlled trial in tens of thousands of people. So we can look at subgroups and we'd have a lot of power. We want perfect adherence, we want it free living, we want it in people eating foods under the circumstances about which we're gonna make claims. Most of us are not asking, well, if I am on TPN and unconscious and being tube fed by a surgeon, then what most of us are saying, when I go to the grocery store and decide what I wanna bring home for dinner tonight, then what? And those are not the same thing. So we won't have that. We'll have lousy epidemiologic studies with lousy self reported data. Follow large groups for long periods of time and causal inference will be fraught. We'll have mouse studies in which we're not sure we can generalize from the mouse to the human. We'll have short term studies of people being tube fed. We want to talk about long term studies of people eating ordinary foods in ordinary ways. And we're going to have to sort of think about if they all line up perfectly. Smoking is an example of that, where almost everything lines up. You may not have the perfect study you want, but the cell stuff, the mouse stuff, the animal stuff, the epidemiology, the clinical trials, we get people to stop smoking, they all line up to say, smoking's really bad, don't smoke. If they all line up, great, then it's easy. If they don't all line up, we also have to start to talk about how strong is each piece of evidence, both in terms of its generalizability to what we really want, as well as in and of itself, is it strong? And I think those studies that we've just described are not especially dispositive. To me.

Yeah, I think another type of inquiry that can be misinterpreted, but there's a great analogy for it is around the dose response curve for muscle protein synthesis as protein dose increases. There was a study that was referenced that looked at as you went from 0.8 to 1 to 1.2 to 1.4 to 1.6 grams of protein per kilogram of body weight. What did the rate of muscle protein synthesis do? In other words, where did you start to achieve the plateau and beyond which you were not going to get more? And what I think this study demonstrated was that in less trained individuals, you will achieve higher levels of mps for lower amounts of amino acids. But again, two things stand out here. The first is be careful what patient population you're looking at in the study and make sure it applies to you. So in an individual who's training an hour a day, I don't think they can compare themselves to someone who went from sitting on a couch to training 90 minutes a week.

Very different.

The other place, I would say that there's a perfect parallel there. And I want to make sure everybody who's trying to figure out what bucket they belong in can sort of do the mental gymnastics here. If you take an untrained individual, a person who is 100% sedentary, which sadly is is the majority of people in the United States, and you put them on a fitness regimen of three 30 minute whole body workouts a week, take that sedentary person, I take them into a gym and I get them to push around weights 30 minutes three times a week, not to failure, not to profound exhaustion, there is no desire to maim them or make it such that they can't get out of bed the next day, Will they achieve a training benefit? Will they achieve some benefit? And the answer is unbelievably unbelievable benefit. David, if you put me into their workouts, would I achieve any benefit? I would argue virtually none. Why? Why the difference?

Well, because you're already sort of on the asymptote. Right. It's like anything else. Take someone who's never had any value of it and you get a big benefit. Give a mouse that has no leptin, just a tiny little bit of leptin, and it immediately starts to slim down quite a lot. Give a mouse that has a normal amount of leptin a little bit more, you're going to observe almost nothing. Give a kid who's been studying algebra for an hour a day, vigorously and diligently, an extra 10 minutes of studying algebra, you're probably not going to get that much benefit. Give a kid who's never been exposed to algebra at all 10 minutes a day of tutoring algebra, probably start to get some real benefits soon.

By the way, that's a beautiful example. When I hear people say you don't need much more protein than 0.8 because of that study, you know what it makes me think? That's like telling a kid they only need to study algebra 10 minutes a day if they want to master it.

Absolutely. One of the things that irks me about the field of nutrition, and I don't know the solution to this, it goes back a little bit to the challenges we have, but this is really an economic challenge, not an intrinsic challenge. Look at the sample sizes of studies in nutrition in general, randomized controlled trials of nutrition in general, especially of things like protein intake. And then look at the sample sizes of studies of statins, randomized control of statins, GLP1 agonists, vaccines, et cetera. They're different by multiple orders of magnitude. It's not uncommon to read these studies saying, well, we're interested in the effects of protein consumption on African American women over age 50 with diabetes and without. So we had six in each group. Six in each group. You had 60,000 over there in that pharma study. And so we have really weak data on this. And so it's not surprising that often we don't show these big effects.

This is important. David, I'm sorry to interrupt. I want to tie this back to the discussion we had around disclosures. There's sort of a reason that virtually everybody in nutrition science is taking some money from food industry. Now. There are someone who works at the NIH who is funded entirely at The NIH Kevin obviously doesn't need. Is Kevin back at the nih, by the way?

Not to my knowledge. Okay.

Anyway, but most everybody who's at a university is cobbling together money from both the government and industry, and that's demonstrated by the belt and suspenders bootstrapping approach that comes into nutrition science studies, which are not well funded. So maybe just explain why is it that it's easy to fund a Pharma study with 60,000 people in it, and it's hard to get the funding to study 600 people in a nutrition study?

The first question is very simple. It's the economic model of it. Pharmaceuticals are patentable. And the way our country works is in general, you cannot market a pharmaceutical without the FDA's approval. And the FDA will generally not give approval unless you've met their bar for having demonstrated as the act of Congress for the FDA's structure mandates. They must have a reasonable basis for concluding that the benefits outweigh the harms under proposed conditions of use. And so the FDA says this is what it's going to take to convince us, and it's going to be these big randomized controlled trials as well as a few other things. And so the companies say we've got to do it. Then there's the economic model that makes it feasible for them to do it in most cases. Sometimes the reason we don't have certain drugs is, is not because they can't be made. It's because the pharma companies say it's not worth it for us because we won't make enough money to offset the development platform. That's a problem there. But in any case, in other situations, like a GLP1 agonist, it does. So they develop them, they spend hundreds of millions of dollars. They do them to the utmost rigor. They're probably the most rigorous human health studies done on the planet these days.

To your point, if you're willing to spend, let's say it's 2 billion today, 3 billion, whatever the number is, 10 years and a couple billion dollars is an enormous investment, but if you can recoup it, it's worth it. How do you recoup that in nutrition science?

You don't. Their margins in the food industry are much lower. They often can't patent stuff quite so easily. It's hard to patent a grapefruit, right? So if you're the grapefruit sellers and you want to do some study, you're not going to patent grapefruit, even though you may have some benefit from it. So that creates a problem which sometimes leads to why people want supplements and things so that maybe they can get some patent protection. But even that can be limited at times. You don't have the economic model for it. And so they just don't. I don't have the numbers at my fingertips. I don't know if anybody does. But if you said to me, we're going to take all the money spent on research looking at the effects of food, not how do you make food, not how do you make a better chocolate bar or a better macaroni and cheese or something, but what are the effects of eating that chocolate bar or macaroni and cheese? And you added it up across every single commodity group, the Dairy Council, the egg board, every single food company, every dietary supplement company, and you added all of what they spend on research. I would be very surprised if it exceeds a billion dollars across the entire country. So there's very little money, relatively speaking, there. They don't have the economic wherewithal to do it. They also don't have the mandate to do it. My group, 20 plus years ago, we did the first randomized controlled trial ever commissioned of their products by the Frito Lay company. And my gosh, were they scared about this. Didn't know what they were getting into. It turned out we compared chips fried in corn oil to low fat chips and cookies and crackers and things to traditional chips and cookies and crackers that had more saturated fat and trans fat. And the idea was, is low fat better than corn oil? And the answer was no. Assuming you can control your calories, you're better off eating the full fat corn oil chips.

What about the saturated. The high saturated fat and the trans fat are probably the worst.

Yeah.

What were the outcomes?

CVD type outcomes. So biomarkers, obviously, with the exception, I think, of triglycerides. My recollection is the traditional trans fat sat fat were worse. I think the low fat, high carb was worse for triglycerides and the high fat corn oil type stuff was better for everything that's published in ajcn. Marie Pierre Saintonge was the first author of that. And it was interesting, the criticisms we got. Again, it was. Marion Nestle was one of the few critics and it was typical. Never touched the science. They never said, well, the design was wrong or the measurements were wrong. It was like, well, they were funded by industry. And I call this. This was her words. I call this a calorie distractor. If you have something to say about the science, why don't you Stick to the science and do that instead of quips and ad hominem attacks. But that's all we got anyhow. So the food industry traditionally has not done a lot of this. These studies are expensive. That study we did, I don't remember the exact number, but it's probably in the neighborhood, especially if we inflated it to today's cost. Might be getting close to a million dollars or something. But that's nothing compared to what we talked about with pharma. The other issue is the other big funder is nih. And nih, I think both, has seen often these things as something the industry should fund. Well, I mean, if it's their selling it, let them fund it. That's one. Sometimes it's not seen as really deep big science. Yes, it's practically interesting, Dr. Allison, but where's the big deep scientific hypothesis? And then the last thing is, in my opinion, here's clearly an opinion, the misprioritization of funding. And this is something that now we see the NIH addressing very vigorously. Again, I would agree with some of what they're doing. I disagree with some of what they're doing. But Jay Bhattacharya, he's a real smart guy and he with others are trying to say, let's repurpose some of the funding. Less here, more here. And I look at the observational epidemiology, which can be very expensive in nutrition. And I think the new information yield, and I underline that phrase, new information is often very low. If somebody else comes out with a new study tomorrow and says we did another one and it was a million subjects and we measured the food intake as carefully as we can with self report in this population. We had a couple of biomarkers and there's something interesting about this. And here's what we showed with protein intake and longevity. I don't care which direction it's in. You showed greater longevity, you showed lesser longevity. I already knew it was a question. You haven't answered the question for me. You gave me a little thing to scratch my head about, maybe, but it didn't really move the needle.

Let's talk a bit about the epidemiology in this space. So I think everybody listening to this podcast knows what epidemiology is and we've talked a lot about the limitations of it and what a healthy user bias is. But give us the landscape of how epidemiology has looked specifically at this question of the relationship between protein intake and outcomes of health. What are some of the near unique or particular circumstances of epidemiology that lend itself to confusion here.

I think the most important thing that I want to say is a sort of a, maybe a little bit of a weird kind of left turn on this. But I think the greatest limit or problem with the nutrition epidemiology in a context like we're discussing now, or in this exact context of protein consumption and things like longevity and long term major health is the opportunity cost. It's that we're spending the money, and often a non trivial amount of money, these big epidemiology studies can be very expensive and we're not spending it. Therefore, in the big randomized, well done, controlled clinical trials, that's, I think, the biggest problem. If you said to me, well, we did some epidemiology, there's something we can glean and it's interesting and fun and there was no cost. Okay, what if you say we did that, but we could have done one really good, or maybe 10 medium sized randomized controlled trials for that? That was a big loss. Now, in and of themselves, if we just stick to the epidemiology, you and many others frequently and correctly point out the issue of confounding. We all say correlation is not necessarily causation. The example of ice cream consumption and murder rates is trotted out. We say, you know, more ice cream consumption associated with more murder rates. Guess what? It's heat. People eat more ice cream, it's hot, they murder more when it's hot. All true, all fine. But that's actually just a tiny piece of it. There's so much more. There's the measurement problem. And that measurement is not random. And even if it was random, it's usually not taken into account. If it was random and we knew it was random and we took it into account statistically, we could make the problem kind of go away. But it's often not random. It may be correlated. People who eat more of this may systematically bias their reporting down than people who eat less of that. There's selection bias. People may choose to be in the study or not choose to be in the study and that may affect things. There's what's called collider bias. I control for something and I think I'm doing a good thing by that. But in fact, I've created an inadvertent association. I could go on and on with statistical obscura.

What do you think are the three most important biases that impact this particular question? When asked through an epidemiologic lens, I.

Think it's the confounding, particularly, but not only by culture and socioeconomic status and social class education. Second would be the measurement error in particular, again, the non random measurement error. And then I would probably say some selection biases that are a little hard to specify. Miguel Hernan at Harvard is perhaps one of the most thoughtful people on talking about the other ways these biases can creep in, in terms of when people start the study, who gets in the study, and when we consider their exposure as occurring. He does some ways to try to correct that. He thinks that's more important than confounding. So I think those are probably the three biggest ones. Those are the intrinsic issues. I think the other one, which is very big but not intrinsic, is I'm going to say honesty. And maybe that's a little too strong. But I think it's the honesty, or maybe the sincerity, perhaps is a better way of saying it, the sincerity of reporting by the investigators. I don't think many investigators are lying in an explicit sense, but I do think there are both intentional and unintentional efforts at distorting. That is, people want to tell a story and they emphasize some things and de emphasize others. They hide some things and don't hide others. So it's not an explicit lie, but there's a manipulation of the information.

And why do you think the editors at journals are unable to address that in the review process?

For the majority of editors, it's lack of ability, lack of resources, and lack of courage. For a minority of editors, it's limitations on the ability to really go in and suss it all out. So the New England journals of the world, the sciences of the world, the jammers of the world, they have the resources within reason and the sophistication to sort of go after this, but they can't get everything. Often when I think about the idea of peer reviewing, but also to some extent the editorial review, which has a little more teeth than the peer reviewers themselves, I look at it like restaurant reviews. If Zagat or whoever goes in to review a restaurant or somebody give him Michelin stars, they can tell you, did they like the offerings on the menu? Was the food tasty? Did it look good? Was the service good? They're not going back and doing a microbial count in the kitchen. They're not checking how often the chef washed his or her hands. Those are things you need a health inspector who's got some authority, who can do spot checking, surprise visits, who's got equipment and so on. That's what you need there. And I think peer reviewers are like restaurant critics. Well, does it look good? Is it interesting? As a peer reviewer, I can't go back and look at everybody's raw data. In some cases we'll see something that looks funny. And then through the journal we're doing a couple of these now. We will get the raw data from people and then we often see things that are quite funny. And we often get a lot of fights with reviewer authors who don't want to let us look at their raw data. And kind of tells you something.

Where is AI in this process? I mean, why are we not or are we using LLMs to serve as peer editors?

Short answer is we are. Long answer is we're at the stage of infancy and amateurishness with it. So it's coming, it'll get better and better. But we can do some very simple things. Now people look for these so called tortured phrases. When you find these phrases that kind of look like a word salad, that's sort of a hint often that you've got something plagiarized or just fabricated. We can look in some circumstances for things that literally don't add up. So some people made something called the Grim Test, I forget what, it's an acronym. But it's basically when, you know, let's say you have a Likert scale and you know you have a certain number of subjects, then the mean of that scale can only have certain values. And if you say, hey, it doesn't have one of those values, something must be wrong. Those are examples.

And do we know if these AI agents, these peer review agents, I'll call them, are being trained on known fraudulent manuscripts? Because we certainly have an abundance of things that were demonstrated to be frauds. So it would be, I assume, a reasonable thing to do to start training these AI agents on that to start identifying the patterns again.

The answer is yes, but very much in its infancy.

Okay, who's leading the charge on this?

I don't know if there's one person who's leading it. I think James Heathers, who's now got a position. Part of the challenge with a lot of these so called data sleuths is it's hard to get paid to do that. So I get paid to be. I was a paid dean and now I'm a paid center director and kind of in my spare time I do a little sleuthing. People like James Heathers, where it's more his full time gig, it's hard to get paid. But retraction watch, set something up for him, See he's one. Tracy Weisberger over in Europe is another. There's a woman whose name I unfortunately going to mispronounce, but who's a Dutch scientist who came up with something called Statcheck. And Statcheck, if the statistics are reported in the format of the American Psychological association, which is free, clear format, has software that will specifically go and make sure those all check. So those are some examples, but there are many others that people are working on.

What do you think is the most compelling piece of epidemiologic data against the idea of exceeding the rda?

I don't think there are any compelling observational epidemiologic data. When I think of the things where you've got relatively hard endpoints, relatively large sample sizes, usually they've not looked at hard, big thresholds. And even if they have, they've looked more continuously at protein intake. Even if they have, I can show you studies in either direction. Studies that make it look like more protein is beneficial and studies that look the other way. And I don't think any of them are dispositive. I think protein intake is highly confounded with social class as well as type of protein intake.

Let's flip the question now again, which is, okay, I'm gonna argue that lower protein is better because I've just demonstrated you are not gonna starve to death at. Let's just round up and call it 1 gram per kilogram of body weight. Peter, you should be eating 85 grams because I know that that is safe. But I don't know that if you double that that you're not gonna get cancer. So what can we say about high protein diets and cancer or heart disease?

So what I think we can say is absolute knowledge is beyond us in this context, but we can have reasonable degrees of certainty, certainty for practical purposes as long as we need to be open with them. One of the things that I often get frustrated with in nutrition science and some other elements of scientific community is we say science is always evolving and the public needs to understand that it's not something wrong. When we, in their view, flip flop and we change our mind. We change our mind when new data become available. Well, that's true, but then the implication is we were honest with the public all along in saying this is what we think. Today, it's not absolutely certain. And the one thing that always just stands out in my mind is early 1990s Michael Jacobson, Dr. Michael Jacobson PhD Nutrition Scientist, Director of something called center for Science in the Public Interest there's the word science in it, coming out on national TV on a camera holding a plate of fettuccine Alfredo outside an Italian restaurant after a new report had come out on composition of what people ate in Italian restaurants got huge press. And as he holds it out to the camera, he says, this is a heart attack on a plate. This is a heart attack on a plate is not a tempered statement that says, this is what I think we know today, but it could change later. So I think we need to be more honest about that.

What was he referring to that was causing the heart attack in that?

I think the implication was the saturated fat or maybe the saturated fat and sodium. So in any case, I think we need to do better with that. I know of no compelling evidence for harm. That doesn't mean there couldn't be any. But I know of no compelling evidence for harm. I know of no studies showing that humans get more cancer with this. I think we need to be skeptical of the mouse studies, the epidemiologic studies, for reasons I've indicated. I think at some point we need to recognize, as people did. When I put up that LinkedIn post and I said, show me the data, can anybody send me one? Many people responded with something akin to, I can't show you that study, David, but can you show me the complement or the opposite study that meets all your criteria and shows there isn't harm? And the answer may be no, I'm not sure. But what I can say is at some point when you've looked enough and you've failed to see harm, where is the burden of proof? So if you don't have a really strong a priori rationale, now we can argue about that. There probably is legitimate debate. You might legitimately say, I have a strong aprior rationale, there isn't harm. And Dudley Laming might say, I have a strong a priori rationale, there is harm and you're entitled to your opinion. Those are opinions. And then we can both look and say, well, neither one of you has the absolute definitive data. At what point? Where's the burden of proof? And I think right now the notion is the burden of proof is on those who want to argue for higher protein intake. Well, the evidence isn't clear enough to show that the RDA is too low. To which I would reply, well, the evidence isn't clear that it is isn't. Now, where does the needle point? Where does prudence point? And I don't think the status quo is necessarily what's always prudent. Saying, leave everything the way it is is always the best way. Sometimes it is. But in this case, I think we've left it alone long enough. I think it's time to say we've looked and looked and looked. If I look at a thousand swans and I cannot find a black swan, does that mean that no black swans exist? Of course not. But if I looked at 10,000 black swans, if I sent a helicopter in the air and we scoured and we looked with binoculars, if I sent teams of undergraduate students to walk around ponds and measure look for every black swan, if I put drones with cameras out and I have failed time after time after time to find a black swan, at one point, say, maybe for practical purposes, I can say black swan's probably not something we need to worry about.

Yeah, I think that is probably the most logical way to frame this, which is, I do not believe we're ever going to get a dose toxicity study for protein the way we do for figuring out what the LD50 of a drug is, where you push the toxicity and you figure out, okay, at this dose, we will kill 50% of people. So the real question becomes, what would be the bracket you would put around for 90% of the population to exist within this range is an appropriate way to interact at the grocery store? To your point, what's the problem we're trying to solve here? The people listening to us don't care about most of what we've said today. I mean, we had to say it, but they actually just want to know. Look, man, I'm really confused because I'm reading people who have a lot of piss and vinegar in what they're saying on this topic. How much protein should I be eating? What should my family be eating? Should I be avoiding protein in my kids? Should they not be eating snacks with protein? Whatever the argument is. So our guidance to our patients is pretty straightforward, and it varies based on their preference. We have some patients who are vegetarians, who have been lifelong vegetarians, who can't stand the feel of meat. This is not like a belief that they have that meat is bad for them. They genuinely don't like meat. We have other patients who won't eat any animal products. So they're going to have a harder time reaching the upper limits of protein consumption. And so with those people, we're just trying to nudge them as high as we can get them. And that's probably not going to get much higher than about 1.2 grams per kilogram of body weight. But the guidance we're giving people is we really like to see you at about 1.6 to 2. It's an easy heuristic. It's easy to remember, too, because you're basically consuming almost a gram per pound of body weight. So how would you advise people based on the. Tell me the. For all intents and purposes, you don't need to worry about Black Swan's argument.

So let's separate the idea of what I think people ought to do if they have these goals that most of us have, like live longer, be stronger, be healthy, et cetera. How do I think we should tell them to achieve that? The latter one I'll loop back to in a minute, but I'm not really the expert on that. But the former one, what I would say is I think you and I are largely aligned on this. I would say if you just want to survive, or if you just want to survive, the RDA is probably okay for most people. But if you want to thrive in these goals that most of us share, then I would aim for in the neighborhood of 2 grams per kilogram per day per person spaced out throughout the day.

So, for example, if you want to pass, you should study this many hours per day and you will get a C, right? But if you want to have the best shot at getting into the best college you could get into because you want to study engineering, you should probably study this much, and you're probably going to need to try to get A's.

Great analogy. My uncle, my great uncle, who was a professor from the old country and the old school and a philosophy professor, when his kids would come home in America from school, he would say, good, now playtime's over. Now you sit down and we study Latin and math and logic, and you do the real work. And then there's probably yet another example. You may know that in South Korea, they actually had to pass some laws recently, or chose to pass some laws recently that I forget the details of them, but that students could only study so much because they're really starting to get worried of students just going too far. And I think those are good examples. To me, it's sort of like the RDA for protein intake is like what my uncle saw the American schools as. It's like, yeah, this is just enough to pass high school and do something. The next level up is what my uncle did, which was we're going to really do some work and get you closer to an optimal level. Maybe what some students do is maybe go too far. But I also think it's interesting to see in what way were they going too far? Did anybody ever say or show that if you study algebra or anything else 12 hours a day instead of 2 hours a day, it directly causes harm? And I don't know of anything like that. Now, if you said to me, if you study algebra or whatever for 12 hours a day, ipso facto, you are not exercising, you are not socializing, you may be not sleeping enough, et cetera, then you have a problem. It's not the direct effect of the studying, it's the substitution effect. Right? So if I literally drank, I handed you a drink when we came in. One of my favorite playtime things. I love to play with these different protein products and have fun with them. And this is a drink that has 20 grams of protein and 90 calories, almost pure protein. And there are other things like that. If you or I were to say, I just want as much protein as I can, so I'm just going to live on that stuff, there would be no, to my knowledge, no direct harm. I'm not worried about my kidneys shutting down or something. But I would say, well, wait a minute. Did you have any vitamins and minerals? Did you have any pleasure from eating other foods? Did you have enough energy to work out hard by not having any carbohydrate? Maybe a little carbohydrate would make you work, able to work a little harder. So I think there are other losses, but beyond those other losses, or if you get a fatty acid deficiency because you have an nadalinolic acid, beyond the losses, I don't know of any risk. So to me, I look at it and say, life support, basic maintenance, RDA, strong evidence for thriving. 2ish above 2, probably more benefit. But you're starting to hit the asymptote. I don't know that it's going to come down. I don't know of anything that says that it's not going to be monotonic. That's going to turn around. But diminishing benefit and then starting to get into more costs of economic costs, of buying fancy products, of the cost of your time and attention on it, the costs of not eating something else you might like. I know you and I have both, I don't know, struggled with is the right word, but wrangled with fruit. We both like fruit and we've both played with diets at times where we've minimized the consumption of fruit for other goals. And yet both perhaps come back to it a little bit and said, I don't want to give up Fruit. And those are examples, I think, where there's some optimization, but I see no harm. And I think the more refined your goals are, then the more it's reasonable to push it a little bit. If I wanted to win the Olympics, I'm more motivated to push it. For me, if I can lift one more pound of weight on the bench press, who cares? But if I'm trying to win the Olympics, then it matters.

So let's pivot from here into the extension, the logical extension, I think, of where we're going, which is not just as it pertains to protein, but to a broader discussion around processed foods. So this is also a very, very hot topic today. So I want to just talk about it broadly and then we can talk about protein as a subset of this because obviously a lot of processed foods are optimized around protein and not just pleasure. But I will say I have read quite a bit on this topic and I've read some pretty compelling arguments on all sides that if you just took processed and ultra processed foods off the market, people would be better. You would force a change in the system that would lead to healthier outcomes. And of course, I've read other very compelling arguments that say, look, if you actually correct for caloric intake, there's nothing per se that is wrong with a processed food, at least to the first order, second order, potentially. Let's maybe start with just some of the definitional stuff. What separates a processed food from an ultra processed food?

There's not a single accepted definition. The most commonly used classification system is called nova. It's very controversial for many reasons, some social, some scientific, some linguistic or definitional. It has to do with degrees of steps and the types of steps and so on involved. These are very popular topics because they give us a new demon. We talked earlier about the importance of demons. Kelly Brownell, who as much as anybody has been one of the leading thinkers in the field of obesity research in the last half of the 20th century.

Is he at Yale still?

No, no, he moved to Duke years ago and I think he may be semi retired now. But anyway, really good thinker and I can remember being in a meeting with Kelly. He and I were both speakers. The meeting was convened by leaders in the food industry. They were inviting him and this is just as he was ramping up the rhetoric of toxic environment, toxic food environment, the epidemiologic environment, the public health environment argument. This was when it had just begun emerging. The NHANES three and then the later NHANES data was suddenly this Wake up call for the country. Yeah, we knew there was obesity, and we knew it was getting worse. We didn't realize how rapidly it had started to get worse in the last couple of decades. And now there was this hype, this panic. And Kelly spoke, and he said, we need social movement here. He said, we can't do it on our own. I've been the behavioral psychologist type. He himself struggles with obesity. It's not education. The guy's brilliant. He's enormously educated. But he still struggled, as did many other people of a similar degree of education and expertise. And he said, we're treating this too much as an individual problem. He said, you've got companies like McDonald's who have a goal of nobody should ever be more than X minutes away from McDonald's if they're driving in the United States. And he said, that's a problem. It's a problem when I'm driving down the street and I'm being assaulted by all the signage and so on. And he said, we need to change this. We need a social movement. Now. He's looking at all these executives from the food industry, and he says, history shows us over and over that social change happens when there's a villain. He says, we need a villain. And he says, guess who it is. You. So that was the start of this villainization.

What year was that?

I don't remember exactly, but I would say it was mid-90s. And it was Michael Mudd, who was from Kraft at the time, convened that meeting. Good meeting.

And he's like, I invited this guy.

Michael had courage. Anyway, so that was that start of it. And now ultra processed is just a great way to demonize stuff. It's just another demon. We're off of soybean oil, maybe phytoestrogens. We dealt with fat for a while. We dealt with sugar for a while. Those are still floating around.

Let's give folks a couple of examples of processed versus ultra processed. So, like, dried fruit is processed?

Sure. Virtually everything we eat is processed.

Yeah, almost everything you eat is processed. But how do you then cross the chasm to ultra processed?

Even if you say there's a single definition, like Nova, I can't recite for you the exact criteria, but it's the number of steps, it's the degrees of steps, it's the types of steps.

Most things that come in a package are now viewed as ultra processed.

That's right. Number of ingredients, number of steps. But you're right. Dried fruit, even fruit that's cut up is processed wine. Is processed. Cheese is processed. Milk is homogenized, sometimes it's pasteurized. Hopefully almost everything meat is processed. And for that matter, I don't want to eat a lot of certain unprocessed foods. There's lots of evidence that unprocessed dairy products cause a lot of harm. So processing is good.

Now, let's talk about the state of the evidence, because again, a good story goes a long way. I mean, our ancestors. And to be clear, my view on this is that the story is much more nuanced than the one I'm about to lay out. But the one I'm about to lay out makes sense, and I get it. We didn't evolve eating ultra processed foods, let alone processed foods. And ultra processed foods are engineered to be highly palatable. And part of that engineering process also makes them calorie dense. Because part of making things hyper palatable is putting in a lot of sugar and a lot of fat. So it's not that the food companies who make these things are trying to make us fat. They're not trying to hurt us. Marlboro's not trying to hurt you with cigarettes. They just want you to smoke them forever. It's an unfortunate consequence of the product. So they really want to create something that tastes remarkable that you just want to keep buying over and over again. And the problem is you're going to end up eating more of it in terms of calories because of the very nature of the product they're trying to sell you. So clearly this is a problem. We can't have these foods around because we can't eat them in moderation. We're going to overeat them. This is one thing we can agree on. Overconsumption of calories always leads to bad things relative to what your needs are. So again, that number is variable by individual. But for any given individual, eating more than they require leads to physiologic harm. So by that logic, why are we having this discussion? Why don't we just get rid of ultra processed foods?

Wow, you've given me so much to work with. One thread I just want to throw out quickly. We may or may not have time and interest in coming back to it is the idea that fewer calories are better, at least to a point. To a point is true. But one of the things, particularly with protein, is we look at some of these studies that people are citing. So I realize I'm sort of looping back to our prior conversation, but these are from the mouse looking at longevity. And it's interesting they're very dependent on ambient temperature. So the studies of caloric restriction in general and protein restriction in particular, which show benefit, are much more present at 22 degrees Celsius, which for a mouse is a thermogenic challenge, thermoregulatory challenge, as opposed to thermoneutral conditions, roughly 27 to 30 degrees Celsius. We don't live our own lives in chronic cold, so we'll leave that out there and say it depends on the conditions. There's several threads you've allowed me to pick up here. One has to do with the idea of categories. All categories are social constructs. We often hear that said about things like race. It's true. Race is a social construct, so is furniture, so is vaccine, so is medicine, etc. What you choose to use as a category and how you choose to define membership in that category is a judgment call. And it's not intrinsically written in stone what that should be. They're useful or not useful for your purposes. That's the first thing to point out. So, same thing as ultra processed. There's not a correct definition of ultra processed. You can define it any way you want. The words mean what we say they mean. Once you've defined it clearly, then we can say, what's its value? How can we use it? What's its utility? Second thing I would say is, as with any category, if it permits a lot of variability in that category, which ultraprocess certainly does, it starts to get a little silly to talk about the overall category because you say so. Wait a minute. You want me to consider a meal replacement shake in the same category as I consider a Big gulp in a 711 in the same category, I consider a chocolate bar in the same category. I consider TPN nutrition. These are all arguably ultra processed and very different things. And I think we want to talk about the things. The next thing I want to bring up is what are we trying to do with it? And this is probably intellectually most important. If you say to me, David, what I am looking for is a heuristic. And this loops back to something I said we'd address later or earlier I mentioned. I said we'd come back to it. The distinction between how much protein do I think somebody ought to eat for a certain goal versus how would I tell them to eat it or what would I tell them about? And those are two different things. If you said, david, I just want something I can tell people so that when I tell them this, it has a beneficial effect. Does telling them not to eat ultra processed foods or to eat as few of them as possible. Defining ultra processed in this way help? The answer is might help a lot. It might vary a little bit depending on how you said it. We need more studies. We need to figure out. My guess is, as with everything else, it won't last long. So you could tell them not to drink sugar sweetened beverages. You could tell them not to eat fettuccine Alfredo because it's a heart attack on a plate. All these things have a small effect for a while and usually not so much for a long term, but it might help. We need to study that. That says nothing, however, about the effects of the food per se. If you said no, David, my goal is to tell people about the foods they should eat, if they actually ate them, what the effects would be. My goal is to determine the effects of foods. Then I would go back to a statement from a wonderful book called A Fly in the Ointment by someone named Joe Schwartz. And Dr. Schwartz, who's a food scientist, says something like, there is a motto. Repeat after me. The effect of substances in the body depends on their molecular structure, not their ancestry. So if you give me this molecule or a collection of them to eat and you extracted that molecule from some berry and it's natural, or you synthesize that molecule in a laboratory, but in the end it's the same molecule. We agree. I mean, you could try to synthesize it, might have some slight difference, but let's assume it's literally the same molecule and it's the same structure. You give it to me in liquid form. In liquid form or in gaseous form, whatever it is. If you say these are going to have different effects because of where they came from. Seems to me we're in homeopathy now. This makes no sense.

My favorite example of this is natural sugar versus processed sugar, which is. I don't know if the people who say this are ignorant of what fructose and glucose are or if it's deliberate marketing shenanigans.

I think it's a mixture of deliberate marketing shenanigans, but it's also the marketing of ideas, not just food products, by people with particular philosophical and other bents who are anywhere from just to make themselves famous to push a philosophical thing, to push an anti industry thing, whatever it is. But yes, I agree with that. And there's so many others. Natural Vanillin versus synthetic Vanillin. If it's still Vanillin, it's Vanillin. There's a wonderful Book by Alan Levinovitz called Natural, in which he will blow away every common conception of what natural is and what its value is. And he talks about the idea of lots of people want the natural vanilla. Most of the vanilla flavoring we get in this country is not so called natural from the vanilla plant. But if it was, it would probably have a much worse environmental impact than the other sources. So it's not always so simple. In any case, I think Schwartz is right. It's not the ancestry. So whether you give me the molecule and it was locally grown or or not locally grown, organic or not organic, ultra processed or not ultra processed, it's the molecules and their structure that matter, conditional upon the molecules. And the structure doesn't matter where it came from.

But in defense of the argument that ultra processed foods must be worse, if you look at the ingredient list, David, the sheer number of molecules there would suggest we're playing Russian roulette here. I don't recognize half the names of the things on the bag of Doritos. I'm making that up. I haven't looked at a bag of Doritos in a while.

Corn, corn, oil, salt and spices. Maybe not a great example.

You could certainly find an ultra processed food at the grocery store in which you cannot comprehend 50% of what's in it.

That's right.

And you don't really know the dose either, because the only thing that the FDA requires is that you list them in order of abundance. But it could be that the first one represents 99% of it and the other 12 represent 1% of it. And even amongst that there's an uneven distribution, et cetera, et cetera. And it could be that these are just preservatives and color additives and they have no physical bar, but you just don't know. Point is, when I eat an apple, or even if I eat a processed apple in the sense that it's been pre cut up or it's just a dried apple. That's dried apple chips, where I can look at the ingredient list and it says apples, I gotta be safer than if I'm eating. Come on. 20 things of which I can't pronounce.

13 of them, if that's the logic of your thinking. I have a great product I'd like to sell you. It's gluten free, it's seed oil free, it's not ultra processed, it's free of any harmful thing, it's chemical free, has no chemicals in it. I call it vacuum. And I would like to sell you this vacuum. And basically that means nothing because we are chemicals. As my friend Ferg Clydesdale, who's the former head of the nutrition food science department at UMass Amherst, used to say, the whole purpose of eating is to get chemicals into the body to replace the chemicals the body loses through the process of living. All food is chemicals. We are chemicals. When you eat that apple and you say, I understand it, that's apple, unless you have a lot of chemical knowledge I don't have, and most people don't have, you don't understand that any better than you understand something else that says benzoate phosphate or what have you in it. You just think you do because you think you understand what an apple is at a chemical level. You understand what it is at a fruit level, maybe, but not at a chemical level. There are many chemicals in an apple and an orange that you or I couldn't pronounce. And that if someone wrote out what the chemicals are, we would say, what is that scary sounding thing? And we also know that things that we think of as natural can be just as harmful. Foxglove, hemlock, Socrates killed by being forced to drink all natural hemlock. It was all natural, very harmful. So poisons, drugs often come from natural things. There's also a misperception that what we think of as natural is somehow has been around for thousands of years, and in some cases it's true. In many cases it's not. So the oranges and the apples and the grains that you're eating today were largely not around years ago. They've been bred, even if it's not transgenic. They've been bred by ordinary breeding things. The cows, the chickens, the pigs have been bred to be different. They are not indigenous species. All the chicken, all the cow, all the pig that we eat in this country, the soybeans, none of that's indigenous. They're all invasive species. Turkey that's indigenous to North America, pecans and black walnuts, but not the other walnuts that they love so much in the Mediterranean diet over there. They're not American. I think this is all silliness. The only thing that's artificial here is our creation of these categories. And we should just recognize that we create the categories. Let's make them meaningful and useful. So back to ultra processed foods. If you said to me, I'm just looking to give my patients or my friends or my mom or myself a hint, a heuristic, there are lots of heuristics that don't, don't require that classification, right? But There are also lots of heuristics that work, even though there may be some illogic embedded in them or some incompleteness or some variability. If you said to me, for example, don't talk to people on the street who look like this, if I was your kid and you said, look, you're walking down the street, you're in a big city, someone comes up, asks you have a match, just keep walking. It's probably a good heuristic. They probably don't really want a match, but some might. And you might miss some, but it's not a bad way to stay safe. Similarly, if I said to you, you know what, don't eat anything from the center aisles at the grocery store, or as little as you can, get as much as you can from the periphery, the dairy, the produce, the meats, the fish and so on, you might be better off. You will wind up eating less ultra processed foods, you'll wind up eating less energy dense foods in many cases, et cetera, et cetera. But that doesn't mean there's something intrinsic about the periphery of the aisles. Doesn't mean if I took Twinkies and put them in the periphery and I took fat free Greek yogurt and I put it in the middle, that suddenly it becomes bad and Twinkies become good. It's a heuristic and it might work for you. To the extent you can stick to it and to the extent it's correlated with these things, it might work. But it says nothing about the causal effect of being in the periphery or the central aisle. And I think as long as we take ultra processed foods at that level, hey, power to you. In the same sense as if we were talking to that person back with the protein said, how do you explain it to them? Maybe you don't say eat 2 grams per kilogram because that's too hard. You have to use the metric system and Americans hate the metric system. And you have to do math and so on and you have to count stuff. But if you just said, make sure you have two servings of lean fish per week and one serving of lean this and eat some egg whites and so on, maybe that works. And we all have our own foods. During World War II, they tried to get Margaret Mead. They hired Margaret Mead, the federal government, to try to get people to eat more organ meats because they wanted to send the steak and all to the soldiers overseas. Didn't work. Even Margaret Mead couldn't get people to eat a lot more organ meats. I happen to love organ Meats and some of my go to protein sources are chicken gizzards. Fantastic protein to calorie ratio and I love them. A lot of people look at that and go, no, we need to figure out the way to get people to do this. But it's the food that matters, not this. Now if we go back to those idea of wanting to understand the food, the effects of the food, then I think working with ultra processed food is just silly. I think it's not a meaningful category. I think any attempts to say let's find the right definition, I wouldn't even bother. I don't even think it's worth even discussing. I would say is let's talk about the substances in the food. What is the effect of eating dried apples or what is the effect of eating things with this composition? Or what is the effect of eating bottled wine or dried dates or grilled chicken gizzards? That's I think, where the knowledge is.

I want to continue on this point a little bit more from a public health perspective. I think we could sit here and convince ourselves, I think quite easily and everybody else that at the individual level the heuristic of don't eat ultra processed foods is simply not helpful. It's too coarse a tool to parse out. Too nuanced of a subject is the bottom line.

Right.

I'll go 10%, some percent of the way with you on that. I would say it's a very suboptimal tool. There are probably better tools. There certainly could be better tools. I don't think it would be very effective and I don't think it would be effective for the long term.

You're talking at the level of the individual or at society. Because I want to distinguish these.

Either one, I think at the heuristic level. And what I mean by that again is nothing to do with causation or really understanding the foods. If you said give me a rule and it's different for you. You're very sophisticated, you have a lot of knowledge. If you were to say to my dad when he was alive, who was a smart man but probably intentionally kept himself not too smart about nutrition so he could feign ignorance and then make the choices he wanted for him, something like that might work a little bit. It would only work a little until he got sick of it and bored with it and until good marketers were smart and said, we'll market you things that skirted the definition of ultra processed. So we could say not an ultra processed food, but that still had the same degree of fat. Sugar, calories and whatever. David Kessler said this nicely in some of his work. He makes the distinction between I think he says ultra processed and ultra formulated. And he says ultra processed. Waste of time.

Waste of time as a terminology, as.

A thing we should focus our attention on for helping people. He says ultra formulated is better because then it talks about what's in the food process. Talks about the process. I don't care how you got there, I want to care where you got to. And so that's one way of making the thinking a little better.

Do you think that there are public health solutions to the metabolic situation we're in as a country?

If you define public health solution as things that exclude things we really consider clinical, usually like pharmaceuticals and surgery, and you say things where there's palpable and demonstrable success at present, I would say no, it's painful to say that, but I would say that after. Depending on your point of view, after roughly 50 years of looking at this. No, I just put up a LinkedIn post about a. One of the latest papers that came out of this group, I think, was an Australian group that just said, we looked at all the parent training type stuff with kids and obesity and a big meta analysis of study after study after study of year after year after year. There's nothing there.

You could argue that the only area in which public health has changed the course of societal health in this country, smoking cessation seems to be a success. There have been public health measures.

Oh, I thought you were only in obesity.

I'm now trying to talk about other areas. So I'm saying smoking cessation efforts at the policy level, so excise taxes, advertising laws, rules for where you can smoke, those have appeared to have a significant reduction in the number of people.

Yeah, great one.

So we've got some wins in public health. Why do you think public health has been unsuccessful in this arena? And it can't be for a lack of trying.

It can't be for lack of trying at all. It may be for lack of trying in a little more intelligent and unbiased manner. I think there's two really big reasons. One is intrinsic to the problem. One can never start smoking. For some people, as difficult it is, one can abandon it entirely. One can't never start eating and one can't, for practical purposes, abandon it entirely. So it's a different problem. You've got a very strong intrinsic push there. I mean, it's so linked to our survival. It's a hard goal to manipulate. I think it's intrinsically just very, very difficult. We like our freedom, we like our variety. I don't want to give up my freedom and variety. If somebody were to say, if we eliminated all of these choices or you're only allowed to shop on Monday or you're only allowed to buy X calories, it's like rationing in a war because some people are obese. Even though I myself have struggled with my weight, I would say I don't want to live in that world. I don't want to give up my freedom of choice, even if it means I and some other people are going to struggle with our weight. So I think there's some real intrinsic difficulties. Everything we do in the public health realm almost seems like either we can't get it to stick or we didn't think through enough. If it stuck, it would work, or it's like whack a mole. That is, you get me to consume fewer calories here or expend more energy there and then I expend less here or consume more there. So I think that's the intrinsic problem. And then I think the other problem is that we started off with the obvious stuff. We looked for the keys under the lamppost because that's where the light was best. We said, ah, school based approaches, farmer's markets, walking trails, calories on the menu. So on good ideas, all good ideas, nudge. We tried them. None of them really seemed to work meaningfully. At the beginning that was fine. What I think we have is a failure of courage, honesty and creativity to say we've shown that none of those things have large, demonstrable, meaningful effects. We've not shown that none of them could ever have any effect under any circumstance. But I think for practical purposes we've shown that those things don't have large demonstrable, meaningful effects. And I think it's time to stop pretending that they might and proposing and funding the next study that's only a trivial variant on the many, many such studies that went before and were shown to not be successful. I think we need to start taking radically different views and say the next time someone comes and says I've got this parent based or school based or community based idea, tell us how it's radically different than what's gone before. Not trivially different.

Do you have any radical ideas that if you ignore the challenges or issues around implementation you would want to implement?

I think you asked me this once before and I'm going to change my answer slightly, but not that much. I think before I said two Things if you really want to decrease suffering now for some subset of the population for which we could afford it, make bariatric surgery freely available and then for investing in research, invest in research on the effects of general quality of upbringing and general education especially, but not only for women and girls. I'm going to stick with the second one. Say we still need that. We need to look at what are the effects of general education, not nutrition education, general education, general parent training, general security, financial and other kinds of security. Growing up on obesity levels. That would be my research public health piece.

Sorry, what's the hypothesis there?

The hypothesis that general education security, so that you're not constantly worried about can I pay the bills, Will I be able to get food at all? General good parenting, which delivers whatever psychological benefit it delivers, there's, I would say, at minimum circumstantial evidence that all of those things lead to reductions in obesity and diabetes decades later. The two best studies I know of this are, it's called the Moving to Opportunity study funded by the Department of Housing and Urban Development and the Abecadarian study done by the Rameys, Craig and Sharon Ramey.

But of those three things, isn't education and financial well being higher today than it was 50 years ago? The third one, parental support, is probably less today. There are probably more broken families today. But two of those three are better today than 50 years ago, aren't they?

I'm not sure. I don't want to say they're better, but I think there's tremendous disparity. So the quality of the education and security and so on that some people get is very different than others. And I think Confucius famously said we are not concerned about poverty, we are concerned about differentials of wealth. It's possible that the public health solution to obesity is becoming a Marxist. I'm not sure we all want to volunteer, but I think some of these things are worth looking at. We do see that there seem to be these long term benefits in studies. As I said, I mentioned what I think are the two best, but they're not the only ones where they weren't meant to be. Primarily nutrition obesity studies.

But how does that explain what you see in the Middle east, for example, where you have countries that are remarkably wealthy? There is no poverty. Obviously there is disparity in wealth between the very affluent, which is effectively everybody, and then the ultra affluent families aren't broken, everybody is educated. And yet obesity and diabetes rates are greater than Even in the U.S. yeah.

I think there's at least two ways to look at that. One way is the idea of interaction.

I'm talking about Gulf nations.

Obviously not the same exposures may not have the same effects in one place or another. For example, we consistently see that in less developed countries, poorer countries, less industrialized countries, greater wealth is associated with greater obesity. We consistently see in more industrialized, wealthy countries, greater wealth and education, especially among adult women, tends to be associated with lesser obesity. So you have the interaction. The other is, as you and I had said earlier, the strength of the evidence. One of the things people frequently like to say is when you say, well, we think temperature has this effect and they say, what about those people in Iceland? They don't have. Well, alcohol is this. Yes, but those people over there, they drink a lot and they don't have. They're different. They're different in many ways. We don't know that. You know, any one factor has to explain why Qatar has this versus Samoa or something. But I think it's a good hypothesis. So that's what I would look at at the public health level in what we think of as traditional public health. Now with the GLP1 agonist related drugs and some other drugs being as profoundly beneficial as they appear to be, I think we're going to get to the point where it's going to be hard. I think we're already asking the question and I think it's going to be hard not to take the question seriously of should it almost be the default that is just like we've asked the question and people give different answers, but we ask the question, should it be that the default is you get this vaccine when you're a kid, that you get your teeth fluoridated at the dentist, that it's not. Maybe some people should get that. I think we are at the point where we're saying as these drugs continue to be tested and experienced, if we continue to see the effects we're getting, are we getting to the point where we should start to say, you know what, that idea of the poly pill that came up decades ago where young adults, even if you don't have diabetes, obesity, hypertension, et cetera, you'd get a low dose diuretic, low dose metformin, et cetera, low dose statin, orthopormists probably still should do that, and then say, anybody get a low dose GLP1 agonist related drug and we'll roll it out and we'll pay for it, and anybody in the country who wants it can get it, or almost anybody. I think that may be the future.

I'm too hungry having this discussion. So David, thank you for making the trip down. As always, it's a pleasure.

Truly my pleasure. Peter. Let's keep doing it.

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