 In Aaron's little speech that he gave, he was talking about evolutionary mismatches and evolutionary mismatches as a driver of ill, physical and psychological health in the modern world. So what I'm gonna argue in my talk is that one of the big mismatches is calorie intake. Basically, we're eating too many calories today and that's a major driver of non-communicable disease. Oh, sure, sorry. That's a major driver of non-communicable disease. All right, so we got a lot to cover, so let's get started. I'd like to introduce you to a man named Mark Howe. Some of you may have heard of him. He's the head of the Department of Food, Nutrition, Dietetics and Health at Kansas State University and in 2010, he embarked on a very unusual self-experiment. He, for 10 weeks, ate a diet composed primarily of junk food, Twinkies, Doritos, Oreos, Diet Dr. Pepper, things that I don't think anyone in this room would consider healthy, including myself. He ate a modest amount of vegetables, can of green beans here, a couple celery sticks there. He had a protein shake every day and a multivitamin. So overall, a diet that I don't think very many people would consider to be healthy, but there was one little catch and that's that he was eating less than 1800 calories a day, which is eight or 900 calories less than he needs to maintain his weight. So over the course of 10 weeks, he lost 27 pounds, most of which was, almost all of which was fat actually confirmed by DEXA. His blood pressure went down from normal to low normal. His fasting glucose declined by 20%. His LDL cholesterol declined by 20%. His HDL or good cholesterol went up by 24% and his triglycerides went down by 39%. So if you were to take these numbers to your endocrinologist or cardiologist, they would say, you're doing a great job. This is fantastic. So by all objective measures, Mark Hab's health improved on a diet that was primarily junk food because of one little detail and that's the low calorie intake. So I wanna take a moment to acknowledge, I'm not gonna dwell on this, but I just wanna acknowledge that there are a lot of determinants of health and these are just some of them that I've listed here and I'm not trying to say that these are not important or trivialize any of these things, but I do wanna say that I think calorie intake is one of the biggest ones up there with physical activity and genetics in terms of its importance. So let's talk a little bit about the relationship between calorie intake and body fatness. This is the energy balance equation. This is straight from physics. What it states is that changes in the energy content of the body are equal to the amount of energy coming in minus the amount of energy leaving. This is physics arithmetic. I'm not gonna spend any time defending this, but the implication for the human body since body fat tissue is the primary calorie storage organ of the body, changes in the size of fat mass are equal to the amount of energy coming in as food minus the amount leaving from metabolism and physical activity. Let's see if this thing works here. Oh, there we go. Okay, so basically if you eat more calories then you're expending, you're gonna gain weight. If you eat fewer calories than you're expending, you're gonna lose weight, simple. And we know that traditionally living cultures tend to be lean and have a low risk of non-communicable diseases like cardiovascular disease and diabetes. And what I'm gonna argue today is that their low risk of non-communicable diseases in large part is due to their lower calorie intake. But it turns out to be really difficult to measure the calorie intake of non-industrial cultures. It's, in fact, it's nearly impossible. But I did say nearly, not completely impossible, and people have figured out a way to do it. And it relies on the energy balance equation. So basically if we do a little math here, what we can determine is that if there's no change in body weight or composition, calorie intake is equal to calorie expenditure. And what this allows us to do is if we can measure calorie expenditure, we can get a very accurate measure. If we can accurately measure calorie expenditure, we can get a very accurate measure of calorie intake in a weight stable person. And this measuring calorie expenditure accurately in a non-industrial culture is also very, very difficult to do, but there is one way to do it, and it's called the doubly labeled water method. And I'm not gonna go into the details of how that works, but basically what it gives you is an average energy expenditure over a period of time in a person that's just living their everyday life. So they don't have to be in a lab, they're out hunting and gathering and doing their thing, and you're getting an accurate measure of their average energy expenditure over a period of days. So this has only been done once, to my knowledge, in a non-industrial culture, and it was done by a research group led by a man named Herman Ponser at the City University of New York. Ponser and his team traveled to Tanzania to study hunter-gatherer culture called the Hadza. Now, to my knowledge, the Hadza are the only true hunter-gatherers left in the world, and Ponser's team recruited 30 Hadza, so basically these people, let me just take a step back here, these people are not carbon copies of our Stone Age ancestors, but they're the closest living approximation that we have. These people are real hunter-gatherers, they get very little foods from agriculture or industrial sources. Their tools, or many of them are the same tools they've been using probably for millions of years. And so Herman Ponser and his group recruited 30 Hadza men and women and administered this doubly labeled water method and measured accurately their energy expenditure over a period of 11 days while they lived their everyday lives. And the results are really quite extraordinary. They're surprising to everyone, including Herman Ponser and me and pretty much everybody else. It turns out that when you control for body size and body composition, total calorie expenditure in the Hadza is the same as semi-sedentary Westerners. So if you find a semi-sedentary American who's the same size and body composition as a Hadza, they're gonna have approximately the same energy expenditure. So this leads us inevitably to the conclusion that they're lean because they eat fewer calories than we do, not because their energy expenditure is higher, which is pretty surprising. Now this is one measurement in one culture, so I think we can't totally hang our hats on it, but this is the only really accurate measurement that we have in a non-industrial culture and it does suggest that calorie intake is really the side of the equation that is driving their leanness. So let's talk a little bit about the relationship between body fatness and non-communicable disease risk. I think this is an area where there's a lot of confusion right now. And so researchers have known for a long time for more than a century that excess body fatness can drive non-communicable disease like cardiovascular disease and diabetes, but about 20 years ago people started publishing these really provocative papers suggesting that actually under certain circumstances people who carry excess fat mass can have better outcomes than people who are lean. And this started off with papers in the realm of existing cardiovascular disease, existing chronic kidney disease. They found that these people were surviving better. But in 2005, an NIH researcher named Catherine Flegel started publishing studies suggesting that this wasn't just in isolated incidents of people with pre-existing disease, but that actually in the general population, people who are overweight and sometimes even obese have a lower risk of overall mortality than people who are in the lean category. And these are some data here from one of her papers that she published in 2013. This is a meta-analysis of studies that linked BMI to all-cause mortality that included 2.88 million people. So this is a huge meta-analysis including lots of studies. And what we have here on the horizontal axis is the body weight category. On the vertical axis we have the hazard ratio for all-cause mortality. And what you can see is that, and let me just say that all-cause mortality is a really, really significant measure of health because it's really a measure of your overall risk of dying. So it really integrates a lot of information about your health status. So we can see is that relative to lean people, people who are overweight actually have a slightly lower risk of dying according to this analysis. And people who are obese have the same risk as people who are lean. And I've blown up the scale here so we can see the differences, but even at the very obese level, the risk really isn't that high. We're talking about a hazard ratio just over 1.3 relative to a lean person. So this really suggests that body weight, at least within certain limits, is not very strongly associated with mortality. And this caused quite a stir when this was published. And the media loved it, right? This is like a big reversal of what everybody thought they knew. And what I'm gonna argue is that I think that this is misleading finding because of confounding in the way that the data are collected and analyzed. I don't think that the conclusions that have been drawn from this are accurate. And there are two big reasons for that, probably more than that, but the two I'm gonna talk about today are that, first of all, smokers tend to be leaner than non-smokers, but also they have elevated health risks because smoking is really bad for you. And that tends to make leanness look more dangerous than it actually is in these big population studies. And some of these studies have controlled for smoking, some of them haven't. But another factor that I think is even more important is that many illnesses cause weight loss. And so Alzheimer's disease, diabetes, cancer, those things, even subclinically, before they've been diagnosed, can cause a person to lose weight over time. And again, that makes leanness look a lot more dangerous than it probably is. And so you have this, the arrow of causality is going in both directions between body weight and health. So how do we untangle that and specifically look at the arrow of causality from weight to health? So there are a couple of methods that have been developed that are thought to reduce this bias. One of them was developed by a guy named Andrew Stokes at Boston University. And what he said is, well, most of these studies are really starting with a snapshot of a person's weight at a particular time point and then looking at subsequent health outcomes. But what I'm gonna do is I'm gonna look at the maximum attained weight that a person attains over their lifetime. And the idea there is that if you're at your maximum weight, you're probably not currently suffering from some disease that's pushing down your weight. So that kind of skirts around the other direction of causality. And when you analyze the data based on maximum weight, what you find is a curve that looks like this. So this is very different. The lowest risk category is the lean category, then it goes up a little bit in the overweight category and then it goes up quite a lot in the obese and very obese categories. And the scale is very different on this slide than on the previous one. The risk actually is a lot larger associated with higher excess weight. And there are other ways to kind of reduce this bias that have been done. One of them is you use a very long follow-up period. So you measure a person's weight now and then you look at their health in 20 years. And the idea is that if you have a really long follow-up period, whatever disease is gonna kill them is probably not affecting their weight right now. And when you look at it that way, this is from another massive meta-analysis representing millions of people. We have body mass index on the horizontal axis. Just as a reminder, below 18.5 is considered underweight. 18.5 to 25 is considered normal weight. 25 to 30 is overweight and 30 and over is obese. And you can see that the optimum according to this analysis is between 20 and 25. So that's a pretty low BMI. For reference, my BMI is about 21.5. So you can see that the risk increases sharply as you head into the obese category. It's not necessarily that much higher when you're in the lower end of the overweight range according to this analysis. So my opinion is that the best interpretation that we have of these big population studies is that you're better off being on the lower end of the lean range in terms of all-cause mortality. And I think that that conclusion fits nicely with some of the other data that I'm gonna show you later on in this talk. So let's move on to the health impacts of altering calorie intake. This is where we're gonna move away from the big population observational studies and get more into the experimental studies. And we're gonna start by looking at model organisms. Model organisms have some really big advantages because you can really tightly control the experimental conditions and you can look over the course of an animal's lifespan and really look at the entire course of disease development. And if you're gonna look in experimental animals, the best way to do it is in monkeys because monkeys are most closely related to humans or primates, I should say. So these are rhesus macaques and the next two studies I'm gonna talk about are done in rhesus monkeys. So in 1989, researchers at the Wisconsin National Primate Research Center took 46 rhesus macaques, divided them into two groups and for the control group, they fed them an unlimited quantity of a refined calorie-dense diet and then the comparison calorie-restricted group got 30% less of the very same diet. 20 years later in 2009, they published a follow-up study looking at mortality and age-related diseases in these two groups. So I'm gonna show you the mortality first. This is called the Kaplan-Meier survival curve. On the vertical axis, we have the percent of each group that's still alive. Horizontal, we have the age of the animals and so basically the faster the curve drops, the faster that group is dying and you can see there's a modest advantage for the calorie restriction group by this measure but that was not statistically significant. So life span, total mortality was not significantly reduced by this intervention. However, when we look at age-related diseases, you get a much more striking picture. On the vertical axis now, we have disease-free survival basically and you can see that the calorie-restricted group got age-related disease at a much lower rate than the control group and this was particularly striking for diabetes. The control group, 16 of those animals developed diabetes whereas none in the restricted group developed diabetes and we're gonna come back to this a couple times in this talk but type two diabetes is a disease that's very, very sensitive to calorie intake. So pictures are worth a thousand words and these are a couple of pictures that they included in the paper. This is an animal from the control group at the end of the study. You can see this animal really doesn't look very good. It's mostly bald, it's obese and it has really, really poor posture and it's lower back and hip area. In contrast, this is a representative animal from the restriction group and you can see that, well, you can't see that it's not obese but it's not obese, it's lean. It obviously has a lot more fur and its posture is much, much better. So this suggests that if you're gonna eat a calorie-dense, refined diet, you're a lot better off eating less of it. So the next study was also performed in Rhesus Monkeys at the National Institute of Aging and this was a 26-year study and it had two really notable differences from my perspective as opposed to the previous study. First of all, the background diet was a lot healthier. This was an unrefined diet. Second of all, the control group was not allowed to eat just as much of this diet as they wanted. They were fed a number of calories that's considered appropriate for a healthy Rhesus monkey. So these animals were not allowed to become overweight or obese. So we're really comparing animals at a healthy weight eating a healthy diet versus animals that were calorie restricted by 30% relative to that on the same diet. And there was absolutely no difference in total mortality. The curves were pretty much identical between the two groups. And when we look at the total age-related disease burden, this is the same type of graph that I showed before, there's a small difference favoring the calorie restriction group but it wasn't statistically significant. When we look at specific diseases, a little bit more of a nuanced picture emerges. So what we're looking at here is a timeline of disease development in individuals of each group. So on the bottom we have the year, on the top we have a line representing each group and each one of those symbols represents a diagnosis of, in this case, cancer. So I've tallied these up on the right-hand side. The control group developed 12 cases of cancer whereas the restriction group only developed seven cases. And as far as diabetes, control group developed seven cases versus two in the restricted group. So big difference there. And interestingly for cardiovascular disease, there were actually more in the calorie restriction group. And I'm not sure whether that's a statistical fluke or whether that's real, but at the very least it suggests that restriction under these circumstances does not protect against cardiovascular disease under the conditions of this experiment. So what can we learn from this overall? First of all, calorie restriction is very, very healthy when compared to an unlimited quantity of calorie-dense refined food. I think that's very, very clear. The benefits of calorie restriction are more marginal when they're compared to lean animals eating unrefined food. So you really have to kind of dig into specific diseases before you start seeing benefits under those circumstances. So preventing excess fat accumulation is important. Going from lean to very lean is not as beneficial. And diet quality matters. So the quality of the background diet does have an impact on how much it benefits to strict calories. So ultimately what we're most interested in is humans. So let's move on to some human studies. And there are really two big questions here. The first one is what happens when calorie intake and body fatness increase what happens to health? And the second one is what happens when calorie intake and body fatness decrease? So we're gonna start with the first question. There are many, many overfeeding studies, but one of my favorites was published by Erdman and colleagues in 2008. And the reason this is one of my favorites is because it used a moderate, long-term overfeeding protocol. So this is a type of overeating that you actually see in real life. This is 300 to 500 excess calories a day over a period of four and a half months. So they did this in 10 lean men over the course of four and a half months. Their BMI increased from 21.8 to 23.8, so two points. Basically they went from looking like me to having a little bit extra, extra fat. They were not considered overweight at the end of the intervention. They were still in the lean body mass index range. And they did a variety of tests on them to test their, particularly their insulin and glucose physiology. One of the things they did was they administered a 75 gram glucose challenge. And they looked at how much insulin their bodies were releasing to cover that glucose. And they did a before and after comparison. And you can see it here. On the bottom we have the curve from before and on the top we have the curve from after. So after gaining only two BMI points and still remaining technically in the lean range, it took a lot more insulin for them to cover that 75 gram glucose challenge than it did at the beginning. And there's a name for this. This is called insulin resistance. And they did a number of other experiments confirming the development of insulin resistance in these men over the course of overfeeding. And they concluded insulin resistance already develops during weight gain within the normal range of body weight. So at the upper end of the lean range. So now let's look at what happens when calorie intake decreases. One of my favorite studies is the diabetes prevention program study. This is a really, really fascinating study. And I highly recommend everybody take a look at it. It started with over 3,000 pre-diabetic adults with obesity or overweight. People had excess fat, they had metabolic challenges. And they gave them an intensive diet and lifestyle modification program. The goal of this program was to produce 7% weight loss using a low calorie, low fat diet and 150 minutes a week of exercise. So what actually happened? Oops, what did I do there? Okay, we're good. So what actually happened? They lost about nine pounds, 4% of their body weight and only about 58% met the exercise goal at the follow up point of 2.8 years. So this is a really modest intervention. I wanna emphasize that. This is a really modest intervention. So at the end of 2.8 years, the control group, 11% of them developed type two diabetes. So these are people who are on the brink of diabetes. 11% of them developed diabetes over 2.8 years. In contrast, in the lifestyle modification group, only 4.8% of them developed diabetes, representing a decrease of 58% versus the control group. So this result has been replicated multiple times in multiple ethnic and racial groups on multiple continents. It's extremely, extremely robust. And I wanna emphasize that this is not a biomarker. This is actual type two diabetes development that has been largely prevented by a very modest intervention involving reducing calorie intake, increasing calorie expenditure. And at the end of the study, they kinda sliced and diced it to figure out what was going on and what aspect of the intervention was most closely associated with the positive outcomes that they saw. And what they concluded is that weight loss was the dominant predictor of reduced diabetes incidents for every kilogram, 2.2 pounds of weight loss, there was a 16% reduction in risk. So that's huge, that's really huge. And it suggests that eating fewer calories than you're taking in has a very, very powerful effect on diabetes risk, okay? So this is in people who started off overweight or obese. So what about people who are starting off, they're not overweight, maybe they're just at kinda the higher end of the lean body mass index range. What effect does calorie restriction have on them? So I'm gonna show you another study here that I find very interesting. And this study is not a randomized controlled trial, it's an observational study, but it has some features that I think make it pretty informative and differentiate it from most observational studies. It was a study of 18 people practicing calorie restriction and it followed them over a period of six years from the initiation of calorie restriction to the six year mark. And it compared them with a control group that was not restricting calories. And it was particularly focused on cardiovascular disease risk markers. So I'm gonna show you a few graphs and they're gonna look like this. Basically, we have on the horizontal axis, we have the year of calorie restriction. On the vertical axis, we have our variable of interest, in this case, body mass index. And then I've put the control group in as a dotted blue line. The reason I did that is because they don't have serial measurements for the control group, they just have one time point. And so I just added that in as kind of a reference point for people to see about where the control group was during the study. So what you can see for body mass index is that the calorie restricted group started off just on the cusp, just below the cusp of overweight, upper 24 body mass index. And over the course of the study, they dropped down to a BMI of 19.5, which is very lean. I mean, that's quite a bit leaner than I am. That's pretty skinny. If you look at their LDL cholesterol, started off pretty close to controls, pretty close to average, and it dropped like a rock, went way down. This is a major risk factor for cardiovascular disease. If you look at their HDL cholesterol, or so-called good cholesterol, started off lower than the controls, and it went through the roof, increased quite substantially on the over the six years of calorie restriction. And similarly, if we look at systolic blood pressure, it started off really high. I mean, it was above 130. These people were hypertensive, and that was similar to the control group, and it went down to low normal. It really, really plummeted, and it continued to plummet over the course of this study. So I think this is pretty extraordinary, because to me, this suggests that, these are some pretty major cardiovascular disease risk factors. I mean, these things really predict cardiovascular disease incidents, and what this suggests to me, is that these risk markers are very sensitive to calorie intake, and that they may in large part be measures of calorie intake. If you were to take these numbers in your cardiologist, he'd be giving you high fives. These are really big changes in a positive direction. And actually, I wanted to add that they actually measured atherosclerosis directly by measuring carotid intima media thickness, and they found that it was 40% lower in the calorie-restricted group. And now I wanna put a couple of asterisks on this. One of them is that these people were not just restricting calories, they were also trying to eat a nutrient-dense, healthy diet. So there are multiple variables happening here. But I do wanna point out that in the case of Mark Howe, the only thing that those two diets have in common is calorie restriction, not the healthy background diet. So at least some of this benefit, I believe, is attributable directly to calorie restriction and weight loss itself. And also, I don't want people to get the impression that I'm necessarily advocating for counting calories and restricting calories in that way. I think that our ancestors, they obviously didn't count calories and they didn't think about it in terms of calories. They just ate a diet and had a food environment that naturally led to an appropriate calorie intake. And so, I mean, I'm not knocking calorie counting if that's something that works for you, but I don't think that's necessary, and that's not necessarily the lens that I would view this through, and I don't think that's the lens that probably most people in this community would view that through either. So in conclusion, appropriate calorie intake is a cornerstone of health. I think it's one of the major reasons why non-industrial cultures had lower rates of non-communicable diseases than we do today. Being lean tends to be healthier than carrying extra fat. There's probably little benefit to restricting calories if you're already lean and need a healthy diet. I'm not convinced that that's gonna extend lifespan, although it might somewhat reduce the risk of specific non-communicable diseases. And again, I think that this is one of the main reasons for the health of our ancestors. So I'd like to thank all the researchers who made this talk possible, as well as my lovely audience. Thank you for coming today. So we have time for, depending on how long the answers are, a couple of questions. I would love to, you know, chair's privilege to ask the first question. So in the all-cause mortality data that you shared, so I used to be morbidly obese. And one of the, I think, common experiences of somebody who is morbidly obese is pretty dramatic weight fluctuations. So you go on a diet, you lose 20 pounds, you go off the diet, you gain 30. And what I'd really love to know is if in your research, if you found anything that looks at stability of weight as a separate marker, because I think one of the things that you could say in obese and very obese people is it's highly likely that their weight is kind of going all over the place compared to somebody who tends to stay lean. Yeah, that's a really good question. And there are observational data that go both ways. I tend to be more interested in the intervention data. And in particular, there are some animal studies that were done by some of my colleagues suggesting that its fluctuation doesn't really matter that much. I mean, basically what matters is, A, what your weight is. And B, what your trajectory is. And C, where you are relative to your set point. So a person who has obesity can lose a relatively small amount of weight and get major metabolic benefits from that. Whereas someone who, whereas if you're just looking at the general population and you're looking at two people who differ by that same amount of weight, you're not gonna see much of a metabolic difference between them. So if your body feels a little bit starved, you're gonna get a major metabolic response that's in the same direction as you would see in a lean person. And that's why you get these results like diabetes prevention program result where you have really modest weight loss and you have these huge metabolic benefits. So I think, I'm glad you brought that up because I think most people who have tried to lose weight know it's very, very challenging and especially weight maintenance is very, very challenging. And so I think that offers a measure of hope to people who have a really hard time maintaining an actual lean body type. Hi, Seven, I am curious if you think that calorie restriction works best as like a day-to-day eating less thing or if you think that fasting, like three days a month or something either individually or in a period which also engages ketosis and might make more like kind of the ancestral pattern. If you think that would accomplish the same kind of thing. Yeah, so I mean in theory, I like the idea of calorie intake fluctuation. I mean it makes a lot of sense from a kind of hormesis perspective. The data are not really that supportive of it as superior to just regular calorie restriction, constant calorie restriction but the research is ongoing so it's possible that that conclusion could change but that's the evidence that I'm aware of. Thanks. That was a great talk, thank you very much. Thanks. I just had a question between the Flegal study and the Stokes study. Given that muscle is medicine, you know going back to Jamie Scott and the BMI scales a little bit skewed, I mean I'm, I think I'm overweight and I consider myself lean. In the Flegal study, were they using BMI or? Yes, yes they were. So I just kind of tried to simplify it by taking the numbers out of it because they were analyzing by category that corresponded to those words I used but I'm glad you brought this up. I actually meant to mention this in my talk but when you look at these big population studies, BMI is really a reflection of fat mass for the most part, not exclusively but for the most part and I think that if you're pushing up the BMI scale due to higher muscle mass, you're not gonna see those adverse effects and in fact I would expect that you would have a risk reduction because of your higher physical activity level, probably better metabolic health. So I think that, yeah and I think that's especially relevant in this community because you have a lot of people who are strength training and so no, I don't think that if your higher BMI is due to muscle mass, I don't think that you're in a higher risk category. Thank you. How much of this is a calorie story and how much of it is perhaps some overlooked nutrient? Like if you're getting less calories, you could also be eating less methionine, less iron, less lead or any other kind of thing. Perhaps you aren't able to metabolize those with your current diet and when you lower that, your body is able to metabolize it. Yeah, so I mean it's a very difficult hypothesis to conclusively disprove because there's so many potential factors but what I will say is that generally nutrient deficiencies do not cause weight gain. If anything they tend to cause reduced calorie intake and weight loss and when you replace the nutrient you get body mass gain. That's what the overall the literature suggests particularly literature from the agricultural, lit on cows and sheep and chickens and goats and to some extent humans as well. Basically you get a reduction of appetite. And the other thing is that basically you, it almost doesn't matter what diet you use, you see the same effect when you restrict calories. So I think that to me the most, the best hypothesis is that it is actually the calories. Thanks. Mm-hmm. Okay.