The Peter Attia Drive - #212 - The neuroscience of obesity ｜ Stephan Guyenet, Ph.D.

00:00:00.000 Hey, everyone. Welcome to the drive podcast. I'm your host, Peter Atiyah. This podcast,

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00:00:41.740 head over to peteratiyahmd.com forward slash subscribe. Now, without further delay,

00:00:47.740 here's today's episode. My guest this week is Stephan Gayanet. Stephan is a neuroscientist and

00:00:55.040 a passionate communicator about the science of primarily obesity, but many aspects of health.

00:01:00.680 His research has focused on neurodegeneration early in his career, and then more recently,

00:01:05.400 the neuroscience of obesity and energy homeostasis. His scientific publications have been cited more

00:01:10.000 than 3,600 times. He's the author of a book in 2017, The Hungry Brain. He's also the founder and

00:01:15.740 director of Red Pen Reviews, which publishes informative, consistent, and unbiased reviews of

00:01:20.100 popular health and nutrition books. He is a review editor at Frontiers in Nutrition. In this episode,

00:01:25.140 we talk about his background and what led him to get to where he is today. We talk about obesity and

00:01:30.260 how it's changed phenotypically over the last thousand years, and specifically looking at US rates

00:01:35.460 of obesity over the past probably 150 years. We talk about what the brain has to do with obesity,

00:01:40.880 the role of leptin and the genes that regulate fat mass and obesity. We talk about the hedonic aspects

00:01:45.760 of food and how our taste today is different than obviously what our ancestors tasted and how energy

00:01:51.200 and caloric density relate to taste and how we potentially select foods. We discuss the carnivore

00:01:56.900 diet and Red Pen's review of the carnivore diet. We speak about the energy balance model,

00:02:02.000 the carbohydrate insulin model, and unifying theories around adiposity. So without further delay,

00:02:06.400 please enjoy my conversation with Stephan Guayene. Hey Stephan, thanks so much for making time. I've

00:02:16.740 been looking forward to this for such a long time, probably since I started a podcast, which has been

00:02:21.200 now we're coming up on four years. I always knew we'd have to sit down. So I'm glad we're finally

00:02:26.000 doing this, albeit not in person, but that's more an artifact of my laziness. I think a lot of people

00:02:31.260 listening to this will be familiar with you and your work, but I think a number of people won't be.

00:02:34.860 So let's tell people a little bit about your path to where you are now, which is sort of being one of

00:02:39.820 the most thoughtful people on the nuances of obesity. What did you study in college? Were you

00:02:44.320 a neuroscience major? Biochem, but I had a neuroscience in mind when I was doing biochem.

00:02:50.520 My idea at the time is that it would provide a foundation for going into neuroscience later,

00:02:56.280 which I'm not sure that reasoning really works out so well, but it worked out okay in the end.

00:03:01.420 And did you go straight from your undergrad to Mike Schwartz's lab or did you do your PhD with

00:03:07.420 Mike Schwartz or a postdoc? Postdoc.

00:03:09.300 Okay. So where did you do your PhD? PhD was with Alice Bada at the University of Washington

00:03:14.580 studying neurodegenerative disease. Interesting. So tell me about that. Was that a detour that

00:03:20.020 was always part of the plan or at that point were you not yet fully interested in obesity?

00:03:25.060 I think more the latter. So I've always been fascinated by the brain, but I didn't know

00:03:31.880 which area of neuroscience I wanted to get into for a long time. I became interested in

00:03:36.660 neurodegenerative disease for a few different reasons. One, they're just absolutely horrible

00:03:41.760 diseases. And two, my grandmother had Alzheimer's disease. And in grad school, I was studying

00:03:49.220 neurodegenerative disease, but I wasn't studying Alzheimer's disease. I was studying a class of

00:03:55.040 neurodegenerative diseases called triplet repeat diseases that includes Huntington's disease or

00:04:00.980 polyglutamine repeat diseases would be another name for them. So Huntington's disease is the

00:04:06.640 most common. That's the most common heritable neurodegenerative disease.

00:04:11.540 It's an absolutely awful disease with almost a hundred percent penetrance, correct? I mean,

00:04:15.680 it's a deterministic gene.

00:04:17.360 Well, it's actually more complex and interesting than that. It's the genetics of it are real

00:04:21.880 interesting because they are non-Mendelian because the length of the CAG repeat actually

00:04:29.740 changes intergenerationally. The weird thing about it is there's these CAG repeats that code for

00:04:36.280 polyglutamines, polyglutamine stretches in the protein, they are unstable in replication. And so what

00:04:43.880 you tend to see is an enlargement of these polyglutamine repeats from one generation to the next. So it has

00:04:51.520 this really weird non-Mendelian pattern. Okay, you asked specifically about penetrance. I think the

00:04:57.440 penetrance actually is pretty high. So in other words, if you have a polyglutamine repeat in the wrong

00:05:03.400 protein of a certain length, yes, very high likelihood you're going to develop the disease. But like

00:05:09.040 anything, it is not 100% fixed. But I don't think we really understand what makes it not fixed. I was

00:05:16.040 studying one of the less common ones called SCA-7, spinocerebellar ataxia type 7. You know, it's an

00:05:24.020 interesting disease. It's a neurodegenerative disease with some relevance to other more common

00:05:29.020 neurodegenerative disease. I used to joke that there were probably more scientists studying it than

00:05:35.040 people with the actual disorder. I don't think that's actually true. But I think you get the

00:05:40.220 point of the joke. And I just wanted to study something with greater impact. I've always been

00:05:47.040 interested in fitness and nutrition, kind of on a personal level. So when I started learning about

00:05:54.780 the neuroscience of obesity, during my PhD work, I got really into it because that was a way to satisfy

00:06:02.940 my criteria for something that's impactful. It's hard to imagine much that's more impactful than

00:06:09.420 that in the world we live in. It's very common. It relates to my interest in fitness and health,

00:06:17.360 and it has a strong relationship with neuroscience. Once I figured that out, which I think to a lot of

00:06:24.000 people is not obvious, the relationship with neuroscience. That's a topic we'll get into.

00:06:28.060 But once I figured that out, I started realizing that not only was this really fascinating,

00:06:32.840 but there was a ton of information in the space that was incredibly enlightening that was not

00:06:39.540 making it to the public. What year did you finish your PhD? 2009, I think. And Mike Schwartz was also

00:06:46.340 at the University of Washington, correct? Correct. At what point as you were wrapping up your PhD,

00:06:51.320 did you connect with Mike, or at least become familiar enough with his work that you thought,

00:06:56.040 you know, this is kind of my finishing school? I'm not sure. I don't remember exactly what all

00:07:02.820 the options were that I was considering, but I was particularly interested in obesity.

00:07:07.780 And staying at the same institution after your PhD is atypical. It's something that I wanted to do in

00:07:15.480 part for personal reasons. I'm not really a big fan of the typical academic thing of,

00:07:21.260 it's almost like a military life. You know, you're moving around like five or more times before you

00:07:26.760 finally settle down. So that was part of it, but Mike was also a really good fit. And there are other

00:07:31.700 labs that could have been a good fit in other places, but Mike's lab was a really good fit and

00:07:36.260 he was willing. So I did that. I feel like the first time you and I met would have been at a

00:07:41.220 conference in 2012. Did you just finish your postdoc? Were you wrapping it up then?

00:07:47.020 That would have been close to the end of it. Yeah. I was postdoc until 2013. So it would have been

00:07:55.000 approaching the end of it. Wow. It's hard to believe that's 10 years ago. I still remember all that

00:07:59.400 stuff pretty well. So let's tell people a little bit about the problem that you work on today.

00:08:03.540 I think everybody knows directionally that obesity is a significant issue, but you can probably

00:08:09.280 quantify this for people a little bit better and help people understand maybe even over a few

00:08:14.780 thousand years, how things have changed in terms of, let's just talk about the phenotype. We're

00:08:19.960 going to obviously talk about the environment and the triggers, but let's just talk phenotypically.

00:08:23.680 How have we as a species, you know, we've been around what, maybe 6 million years in our current

00:08:27.860 rendition, but what's changed over the last thousand years in terms of our phenotype?

00:08:32.500 If we're comparing the body shape of people in modern affluent societies like the United States

00:08:40.080 to what the typical human would have looked like a thousand years ago, I think it's clear that we're

00:08:46.160 much fatter today on average with a much higher percentage of obesity. And a thousand years ago,

00:08:53.220 there was obesity. I mean, we have evidence even from Egyptian mummies that among the wealthy,

00:08:58.860 there was obesity. Not to say that it necessarily was super common, but I don't think it was that

00:09:05.260 uncommon among the wealthy. I think probably for similar reasons that we have obesity today,

00:09:11.360 but certainly the prevalence was much lower. And when we start to get into the more modern

00:09:19.540 historical period where we start to actually get data on this, the first data that we can find on

00:09:26.520 this in the United States, or at least that I have found that is somewhat informative, are from

00:09:32.080 civil war veterans from 1890 and 1900. They did height and weight measurements on middle-aged

00:09:40.120 civil war veterans. So these people were, I think, almost exclusively white men. However,

00:09:46.360 if you compare to the same demographic, so middle-aged white men today, you see that there was almost no

00:09:54.600 obesity back then. And today the obesity rate is something like 45% for that same demographic.

00:10:02.760 And just to be clear, we're defining obesity in the most traditional way, which is the use of body

00:10:07.620 mass index. And we're defining it as a BMI of more than 30.

00:10:11.780 Correct. And so the advantage of BMI is it's really easy to measure and you can calculate it from

00:10:18.320 these really simple measures that go back a long time. Unfortunately, they didn't have DEXA machines

00:10:23.900 in 1890, which would have been, of course, a more informative way of looking at it. But using measures

00:10:30.400 that we can compare over long periods of time, like body mass index, I don't remember the exact numbers,

00:10:35.920 but it was like a few percent low single digits of people actually classified as BMI over 30 at that

00:10:44.760 time, 120, 130 years ago. And then if we look toward more recent data, the first really good data we have

00:10:54.800 starts in the 1960s for the United States. That's when the NHES surveys started, which later became

00:11:01.460 NHANES. And in those surveys, what you see is by the time they started measuring it,

00:11:08.780 it had already gone up from that previous time in the late 1800s, early 1900s.

00:11:16.340 So you're saying, Stephan, that there really wasn't a lot of longitudinal data from 1900 to 1960 to check

00:11:22.860 what that trend line was doing. It was sort of this big effort in 1900 and then another big effort didn't

00:11:27.700 take place till about 1960? I don't know that I'd call it a big effort, but the biggest that I'm

00:11:33.180 aware of in the late 1800s, early 1900s, true representative national sampling started in the

00:11:40.500 1960s and then got better through the 70s. And now we have this NHANES survey methodology that is the

00:11:47.760 best source of evidence that we have. It started getting good in the 60s. And what were those levels

00:11:53.620 there, Stephan, in the 1960s? I don't remember the exact figure, but it's like 12% of U.S. adults

00:12:00.420 had obesity at that time, something like that in the earliest measures. And do you have a sense of,

00:12:06.460 because I'm sure this is going to become more relevant today, what is the term that's used if

00:12:11.000 BMI is over 35? Isn't there a extreme category of obesity, morbid obesity? Is that defined as 35 or 40

00:12:18.060 or something? The terminology has changed to try to avoid stigma. It has been extreme obesity or morbid

00:12:26.760 obesity. I can't remember what the current term is for it, but yeah, there's a category over 35 as

00:12:32.940 well. There's a class system. So class one, class two, class three. So I think that corresponds to 30,

00:12:39.360 35, and 40, if I'm not mistaken. So basically, this progression was not just at the kind of median

00:12:47.000 level, because I'm sure the median BMI was also moving. The mean BMI was also moving. The fraction

00:12:53.320 over 30, and presumably the fraction over whatever that highest threshold is, be it 35 or 40.

00:12:59.100 Yes. And actually, the most extreme changes happened in more severe obesity. Very, very few people had

00:13:06.380 BMIs over 35 in the earliest measures. And then now it's like something like 9 or 10% today of adults.

00:13:16.480 So there has been more movement at the extreme end than at the mean, yes. And that's what happens

00:13:24.840 when a distribution spreads out, which is what happened. If you look at the distribution of BMIs,

00:13:30.500 it used to be a lot tighter, and it just got less tight. So there are still people who are lean,

00:13:36.380 there are still people in every BMI category, just like there used to be. But since it has spread out,

00:13:42.900 you get a disproportionate increase at extreme values.

00:13:47.500 What about underweight? What was the fraction of underweight in 1900? If we would define that,

00:13:52.800 say, BMI below, I don't know what underweight is, is it below 18 or below 20? And then how has that

00:13:58.220 changed over time?

00:13:59.320 Typically, the cutoff is 18.5. And I don't know the answer to your question. I think it was higher

00:14:05.800 than it is today. But I'm not sure about that.

00:14:09.300 When did people first make the connection that there is an association between obesity and adverse

00:14:15.940 health outcomes? When you think back to 1000 years ago, or back with the Egyptian aristocrats,

00:14:22.800 obesity probably would have been a sign of affluence. And I don't think anybody would have looked down

00:14:28.120 upon it too negatively. Back in medical school, I remember learning about gout and how gout emerged

00:14:32.780 around this time. And it was really this disease of excess, right? Excess alcohol, excess sugar,

00:14:38.720 excess protein would manifest itself in gout. And this was the ultimate rich man's disease,

00:14:44.760 basically a sign of affluence. So I can't imagine people were too upset to be obese back then.

00:14:51.120 And of course, today, we take it for granted, despite some of the political pressure to

00:14:55.400 understandably try to destigmatize obesity and somehow now suggest that it's completely healthy.

00:15:01.240 I think the reality of it is it's pretty unambiguous that obesity is indeed associated

00:15:04.620 with poor health outcomes. When did that become clear?

00:15:07.540 I'm not real knowledgeable about the deep history of this. But I know I've heard that there were

00:15:13.220 physicians in ancient Greece and India who recognized that being very heavy was associated

00:15:20.340 with health problems such as having sweet tasting urine, for example, sign of type 2 diabetes or any

00:15:27.680 kind of diabetes. And then there were these insurance life tables in the early 1900s that suggested that

00:15:34.260 people who had obesity had shortened lifespans and greater risk of certain diseases. But it actually

00:15:42.500 became pretty controversial with a series of studies that was published. Catherine Flegel was intimately 0.76

00:15:51.720 involved in this work suggesting that there was actually not the relationship people thought there

00:15:58.100 was between body mass index and mortality. So these studies, this was labeled as the obesity paradox,

00:16:04.900 because what they found is that there wasn't really much of an association between obesity and poor

00:16:11.300 health outcomes. And often if you look at the relationship between BMI and mortality, if you

00:16:19.120 just look at a graph of it, the nadir, the lowest point on that graph was in the overweight range or

00:16:26.260 sometimes even on the low end of the obese range, depending on what the study was. And they were finding

00:16:31.400 this in meta-analyses of millions and millions of people. And so suddenly people were saying, well,

00:16:36.300 maybe higher body fatness is not bad. Maybe it's actually protective. So there's been this big

00:16:42.300 debate about it. I think what has emerged in recent years, especially the last 10 or 15 years,

00:16:49.300 and by the way, let me take a step back. The reason this is called the paradox is because there's all

00:16:54.400 this evidence that excess body fat contributes to all kinds of diseases, type 2 diabetes, cardiovascular

00:16:59.960 disease, certain cancers. And so how could it be protective for mortality when it's driving all

00:17:06.060 these diseases that are the leading causes of mortality? So that's why it's called the paradox.

00:17:10.920 The research that has come out since then is suggesting that it's probably not a paradox,

00:17:16.420 as paradoxes often are not, and that it's an artifact of those observational data. There are probably a few

00:17:23.340 different things going on, but the biggest one is that people who are sick often lose weight. There

00:17:31.020 are many different health conditions that can cause a person to lose weight. Type 2 diabetes,

00:17:35.840 if it's not well controlled, you can be losing weight. Certainly renal failure, COPD, things like that.

00:17:41.940 Yeah, those are great examples. Alzheimer's disease, cognitive decline, those things can cause a person to

00:17:48.040 lose weight. So there are many health conditions that can cause a person to lose weight. And essentially,

00:17:53.080 the concern was that makes leanness look worse than it really is, because you're getting all these

00:18:01.440 people in the lean category that are lean because they're sick. They're not sick because they're lean.

00:18:07.280 Some people have called that reverse causation. David Allison corrected me. It's technically confounding.

00:18:13.940 You and David and I had a nice email exchange about that because we did discuss this. I'll share with

00:18:18.560 you a very glib example. I had shoulder surgery less than three weeks ago. In the 18 days since I've

00:18:24.380 had my shoulder operated on, I've lost nine pounds. I don't know what my BMI was before versus after. I

00:18:30.640 probably went from BMI of 26 to BMI of 24. So on paper, that looks good. I would argue there is

00:18:38.460 nothing about me today that is superior in health to where I was 18 days ago. Of those nine pounds I've

00:18:45.600 lost, I'd be willing to bet seven of it is lean body mass. Again, it's a silly example, but it

00:18:50.380 illustrates that one can see an improvement in BMI with probably a deterioration in body composition

00:18:57.440 and an increase in morbidity. Absolutely. BMI is a crude measure. No doubt about it. It's useful.

00:19:04.880 You talked about this with David Allison in your episode, and I think you guys had a nice conversation,

00:19:09.760 but Cliff's notes is it's useful for a population level study as it can be useful for screening,

00:19:14.480 but it's a crude measure. So how do you get around this issue of confounding or reverse causality?

00:19:22.380 There are some methods that have been developed for this. One of them that I particularly like was

00:19:28.360 developed by Andrew Stokes and his colleagues, and that is the maximum attained weight method.

00:19:36.740 Instead of using the exposure variable, instead of looking for BMI right now,

00:19:44.260 and seeing how that correlates with mortality risk right now, you say, what's the heaviest you've

00:19:49.440 ever been, and how does that correlate with your health outcomes? Essentially, that's saying like

00:19:55.160 whatever health condition you've developed that might have caused you to lose weight,

00:19:59.680 we're screening that out. We're looking before that. And when you look at it that way, you get a

00:20:04.660 sharpening of the association between BMI and mortality, and you find that the nadir,

00:20:09.880 the lowest point shifts to a lower BMI. So essentially, whereas before it looked like

00:20:15.580 maybe overweight was the best, now you see that in the lean range looks the best. And there's a

00:20:22.220 stronger difference, a larger difference between being lean and having obesity in terms of mortality.

00:20:28.740 So it really sharpens things up. And the reason that happens is because when he looked into this,

00:20:34.060 you're excluding a bunch of people who were formerly in the obese or overweight category and went into

00:20:41.100 a lower category. And those people, if you look at their health outcomes, they're terrible.

00:20:47.060 So those people who used to have obesity and now just are overweight or are lean, those people have

00:20:54.580 massively elevated rates of chronic disease and of mortality. They're essentially bringing all this

00:21:00.960 excess mortality into lower weight categories. Why is that, Seven? Because that almost sounds

00:21:06.340 like the worst news you could ever hear, right? It would suggest that if your BMI is 33, all hope is

00:21:12.160 lost, that your fate was sealed the moment you hit that BMI. You know what? Just dig in and eat more

00:21:18.740 Haagen-Dazs because if you bring that BMI down to 26, you don't assume the health of the 26. You bring

00:21:26.340 the health of the 33, which that doesn't sound right either, right? No, it's not right. And this is

00:21:31.900 another limitation of the observational data. It's hard to lose weight. It's hard to lose a lot of

00:21:37.160 weight. It's hard. And it's hard to keep it off. It's hard to go from 35 to 25 BMI. That's a lot of

00:21:42.380 weight loss. Most people, frankly, are not able to achieve that and maintain it through voluntary means.

00:21:48.500 And so these people who are losing weight, it's predominantly unintentional weight loss. This is not

00:21:54.000 people who start a diet and lifestyle plan and lose a bunch of weight. This is predominantly people

00:22:00.280 who are losing weight unintentionally. And as a doctor, I'm sure you know this, when a person starts

00:22:07.440 losing a bunch of weight for no reason, that's probably not a good sign, right? Absolutely. Even

00:22:11.800 if they start off overweight and they're lean, maybe they even look good, that's probably going to start

00:22:16.100 ringing alarm bells. So if you look at studies that have measured the impact of intentionally

00:22:24.000 weight loss on mortality, this has been done both for diet and lifestyle weight loss,

00:22:30.560 randomized controlled trials. So we're talking about a good quality of evidence. And also for

00:22:35.340 bariatric surgery, you see a reduction in all-cause mortality. That's what I was going to ask you. I was

00:22:40.420 going to say, how does bariatric surgery and how does semaglutide affect this? It's too soon to say.

00:22:45.340 But when we start to look at what I think is the most impressive weight loss drug out there,

00:22:50.860 and then of course, when you think about Roux-en-Y gastric bypass, which has been around

00:22:54.580 for a while, it'll be interesting over time to see if that can flip that paradigm.

00:22:59.780 We have data for type 2 diabetes, for people with type 2 diabetes, for semaglutide, and it does reduce

00:23:05.340 all-cause mortality in meta-analyses of randomized controlled trials. So it will be interesting to see

00:23:12.140 whether that extends to people without type 2 diabetes. Obviously, people with diabetes

00:23:16.500 diabetes are probably going to benefit the most from that kind of drug class in terms of the 0.98

00:23:21.620 physiology of it. But there are promising signals that at the very least, it's probably not going

00:23:27.720 to kill you. We go from the 60s to the 70s to the 80s. When does it really, from an epidemiologic

00:23:34.500 standpoint, just completely take off? If I remember what you said a moment ago, back in the 60s,

00:23:40.280 we might have been at 12% obese. And today, it's hard to imagine such a low figure given 40 to 45%

00:23:48.100 today. 43 is the latest. Not that I don't believe it. It's just hard to fathom that nearly half of the

00:23:54.720 U.S. adult population could have a BMI above 30. When did it really hit its stride? This is an

00:24:01.960 interesting question. Probably a lot of people listening will have seen graphs of NHANES data where

00:24:08.080 it kind of spikes around 1980. But the interesting thing about that is that point around 1980 is

00:24:14.300 actually the average date of that survey. But it was actually a multi-year survey. It was a survey that

00:24:22.520 started, I believe, in 76 and ended in 84, something like that. I don't remember the exact years, but it was

00:24:31.580 a range. That's how the NHANES used to be. Today, the range is much narrower, but at the time, it was a

00:24:37.220 broader range. And so what we're seeing is we can turn that into a point and put it on a graph, but

00:24:42.980 really, it represents a range of years. So we don't know exactly when it happened. But if you look at the

00:24:48.120 average value for that, it's, I think, 1978 is the average value for that survey, the average year.

00:24:55.380 But we don't know exactly where in there it started to turn up. And we don't really know how sharp it was

00:25:02.060 because we don't have that resolution. It looks real sharp on the graph. Again, when you make it a

00:25:06.740 single point, it looks sharp. But we don't really know exactly how sharp it is. Anyway, I'm kind of

00:25:12.840 putting a lot of nuance into this. But to answer your question and... Well, it is actually an

00:25:17.180 important point because I know that many people, I've probably been guilty of this myself 10 years

00:25:22.280 ago, would also look at changes in macronutrient composition that occurred around the same time and

00:25:28.080 say, boy, it's hard to uncouple those. But in reality, if they occurred over a different time

00:25:33.800 scale, it might make that correlation a little less robust.

00:25:38.420 We have a sharper focus on the changes in dietary intake because we have annual data from the

00:25:44.800 Economic Research Service, USDA Economic Research Service. The data on BMI are less sharp. So I would

00:25:51.820 say that those two changes are absolutely compatible. And on a logic level, I'm sure they're related.

00:25:57.480 You see big changes happening around the same time in the diet. To give a kind of simpler,

00:26:03.700 hopefully more satisfying answer, sometime around between the late 70s and the early 80s,

00:26:09.600 we see an uptick, an apparent uptick in the obesity rate. So the rate starts to increase,

00:26:17.000 goes up and up and up. And then there's a couple of places where it slightly goes down for a year or two,

00:26:23.180 and then it keeps going up. It looked like it was going to plateau or maybe start going back down.

00:26:28.080 But really, in recent years, it's really just been skyrocketing. So essentially, from somewhere in

00:26:33.880 the late 70s to early 80s to now, we went from something like 15% of obesity to 43% of U.S. adults.

00:26:44.080 And I want to point out something else, too, that I think is relevant. One way I like to think about

00:26:48.540 this is the lifetime risk. So that's just the population prevalence. That includes people who

00:26:54.000 are 20 years old. That's a snapshot. That includes people who may be growing into it.

00:26:58.580 Exactly. If you look at the lifetime risk, I don't know what the exact figure is, but I think it's well

00:27:03.600 over 50%. So I think more than half of U.S. adults will be classified as actually having obesity

00:27:13.040 at some point in their life if the current context is maintained. And you see the same

00:27:18.960 thing for type 2 diabetes. The prevalence of all diabetes is something like 10% or 12%.

00:27:23.280 But if you look at the lifetime risk, it's like double that, maybe even more. I can't remember

00:27:27.980 what the exact figure is, but it's mind-blowing the number of people who will at some point in their

00:27:32.420 life develop type 2 diabetes.

00:27:34.660 If you take a 50-year look at the change in type 2 diabetes prevalence, so the snapshot,

00:27:43.100 I believe it's a five-fold difference in risk over 50 years, the past 50 years. So if you go back

00:27:49.040 50 years ago and look today, just the prevalence delta is 5x.

00:27:52.980 I could believe that.

00:27:54.100 So you have to then look at what does that rate of change tell you about lifetime prevalence? What

00:27:59.320 does it tell you about a person who is only five years old today or a person who's 15 years old

00:28:03.920 today? I haven't done the math, but I would completely agree that their lifetime risk is

00:28:08.880 probably at least one in five of having type 2 diabetes.

00:28:12.640 This has been quantified. I tweeted out a paper about this a while back. And unfortunately,

00:28:17.700 I don't remember the top line figure, but there are actual data on this.

00:28:21.940 What about the rest of the world? Where are they in relation to us? We probably led the way

00:28:26.540 along with a handful of other developed nations. But one of the things that seems to have changed

00:28:32.260 is this is no longer a condition of affluence at the individual level.

00:28:37.160 It really hinges on how we define the term affluent, because if you go to the very poorest

00:28:43.360 people in the world, there still is not a lot of obesity in those places. Places that are really

00:28:48.400 challenged with food security, where the diet is very limited, like subsistence farmers in sub-Saharan

00:28:54.120 Africa, you're still going to see that there's a low prevalence of obesity in those places.

00:28:58.760 Sorry, I think what I meant was at the individual level. So if you look at the United States from

00:29:04.740 the bottom 10% of the population economically to the top 10% of the population economically,

00:29:10.060 is there a difference in obesity there?

00:29:12.720 Bottom 10 to top 10, you would see a difference. If you're looking in tertiles,

00:29:17.720 so just bottom third to top third, there's very little difference actually. If you start slicing and

00:29:23.740 dicing it by sex and race, then you will start to see larger differences emerge. For example,

00:29:30.580 women who are in the top tertile are leaner than women in the bottom tertile, but there's no difference 1.00

00:29:36.900 for men in terms of income. So you can start to find patterns when you slice and dice.

00:29:42.720 My overall feeling, though, is that there is no demographic in the United States that has not

00:29:50.300 gotten a lot fatter over the last few decades. Even though if you look at certain demographics,

00:29:56.060 particularly with regard to education, you're going to see gradients emerge. But even among

00:30:03.120 highly educated people, you're going to see a higher prevalence today than there was 50 years ago.

00:30:09.920 So let's not bring this up to your work. What did you do when you got to Mike Schwartz's lab? How did

00:30:14.620 you begin your re-education around neuroscience as it applies to everything that has to do with

00:30:23.180 obesity? Which let's just talk about this. There's an input side and an output side. Rudy was on the

00:30:29.260 podcast. God's probably been two, three years ago. So maybe it's worth a refresher on the neurobiology

00:30:35.040 of how the different parts of, for example, the hypothalamus can regulate energy expenditure,

00:30:42.300 can regulate appetite, and what we can learn under very, very controlled experimental settings with

00:30:49.220 animals. And then how we can start to think about how that applies to humans with a primitive brain

00:30:55.680 in a modern world, so to speak. I want to take a little step back before getting into that and say,

00:31:01.880 answer the question of what does the brain have to do with obesity at all? Just to make sure we're

00:31:07.900 bringing everybody along. I think it's not obvious to everyone what the brain might have to do with

00:31:13.060 obesity. But I think if you start to think about it, it becomes pretty obvious that the answer is

00:31:18.840 just about everything. And the reason is that the brain is the organ that generates behavior.

00:31:24.680 If you think that behavior of any kind relates to body fatness, how much we eat, how we use our bodies,

00:31:32.780 how we sleep, whether we're stressed or not, if we think any of that relates to body fatness, then

00:31:37.900 we think the brain is laying a role. I think most people would agree that food intake, quantity and

00:31:43.620 quality is pretty important there. The second reason is that the brain actually contains a regulatory

00:31:50.480 system for body fat, for body fatness, I should say, body fat mass. And it's the only known system in

00:31:58.020 the body that does that. And it's located primarily in a part of the brain called the hypothalamus,

00:32:03.980 which is, I forget who described it this way. Maybe it was Herman Ponser. It's like a wad of bubblegum

00:32:08.960 on the bottom of your brain near where your optic nerves cross. So it's this little tiny part of the

00:32:14.840 brain that specializes in homeostasis, maintaining the stability of body systems.

00:32:20.960 I was described as a walnut.

00:32:22.020 A walnut. A walnut. Okay. So just to give you an example, it's the part of the brain that

00:32:27.320 regulates body temperature. And there's a thermostat in there, effectively a thermostat and

00:32:34.800 thermometers. There are thermometers that measure your core temperature. There are thermometers

00:32:39.520 on your skin that measure future threats to your core temperature. Like if you jump into a cold lake,

00:32:46.400 your core temperature doesn't instantly drop, but your brain knows that it will drop because of

00:32:51.940 the temperature sensors in your skin. And so it can respond adaptively. And then that system in

00:32:57.960 the hypothalamus engages a suite of behavioral and physiological responses to maintain temperature

00:33:05.040 homeostasis. On the physiology side, you get vasoconstriction. You get non-shivering thermogenesis

00:33:11.340 through brown fat. You get shivering. And then through the behavioral side, you want to get out of

00:33:16.980 cold water. You want to put a sweater on. You want to drink some hot tea. You want to adopt a heat

00:33:23.000 conserving posture. And through this coordinated physiology and behavior, you get incredible

00:33:29.060 regulation of temperature, of core temperature, I should say, plus or minus one degree Fahrenheit

00:33:34.680 when the exterior temperature could be varying by 50 degrees. It's an incredible regulatory system.

00:33:42.200 And the body fat regulatory system, unfortunately, is not so precise. But I give that as an analogy just

00:33:48.440 to give you a sense of what the hypothalamus specializes in. There's also a regulatory system

00:33:54.740 for body fatness. And a nice name for that is the lipostat. So lipo, fat, stat, the same. And really,

00:34:03.180 we've known about it since 1840. Or we've known there was something going on since 1840 when the

00:34:10.300 Viennese physician Bernard Moore published a case study about a woman who had extreme obesity,

00:34:16.580 rapid onset extreme obesity. He did an autopsy after her death, and she had a tumor in her

00:34:22.040 hypothalamus. And to this day, hypothalamic obesity is a thing that we have to deal with with people with

00:34:29.100 tumors or other damage to the hypothalamus. It often causes extreme obesity.

00:34:33.760 And what's the nature of the obesity? How much of it is due to hyperphagia, excess eating? How much of

00:34:41.160 it is due to loss of activity or even just a shutdown of metabolic rate?

00:34:47.460 If you look at probably the closest experimental analog of hypothalamic obesity, that sort of human-like

00:34:57.640 hypothalamic obesity would be VMH lesion. So this is something that's been done since, I think, the

00:35:04.400 20s. They go in with a very precise instrument called the stereotaxic instrument in animals, and

00:35:11.080 they lesion this part of the hypothalamus called the ventromedial hypothalamus. They're trying to

00:35:16.280 replicate the damage of hypothalamic obesity. As soon as the anesthesia wears off, these animals are

00:35:22.820 cramming food into their faces. And if there's no food in their cage, they'll eat bedding. They will

00:35:29.460 just put anything they can get ahold of into their bodies. And they will continue binging until they

00:35:37.280 have rapidly gained a large amount of weight, and then it will start to plateau off. But they have

00:35:42.580 extreme hyperphagia. The first experiments that were done on this showed that if you restrict them to

00:35:49.420 a normal level of calorie intake, so that of a non-lesioned animal, it prevents the fat gain,

00:35:56.220 suggesting that, I should rephrase that, it prevents the weight gain. So they were just weighing them at

00:36:01.060 the time, suggesting that it's primarily a phenotype of hyperphagia. However, later experiments that were

00:36:10.200 more precise found that it doesn't completely eliminate the weight gain. It only eliminates about 0.98

00:36:16.340 80% of it. And so there is a component coming from energy expenditure, primarily hyperphagia,

00:36:23.480 but there's also an energy expenditure component that's smaller.

00:36:27.280 It's funny. I just remember in medical school, one of the neurobiology professors saying,

00:36:31.780 if you were asked to give up a piece of your brain, if you had to give up like one cubic centimeter

00:36:36.960 of brain tissue, you just fight like hell to make sure you preserve your entire hypothalamus.

00:36:41.920 I agree with that. I would say the brainstem and the hypothalamus, probably not places you want to

00:36:47.880 lose.

00:36:48.780 Let's go a little bit further. You referred to the lipostat. So say a little bit more about

00:36:53.220 what we've learned about this lipostat and what circulating factors might play a role in governing

00:36:58.880 this and what's been learned through some of the work that was done using parabiosis.

00:37:03.520 I'm going to give you the simple version. There is a more complex version that is emerging,

00:37:09.480 but I'll start with the simple version, which is that it is a negative feedback system similar to

00:37:18.000 your home thermostat, similar to the thermostat in your brain in that the hypothalamus measures

00:37:23.940 levels of a circulating hormone called leptin that circulates in proportion to your body fat mass.

00:37:30.320 So the same way your home thermostat measures the temperature in your home, your hypothalamus is

00:37:35.560 measuring the level of leptin in your circulation. Still some controversy about how exactly or where

00:37:42.140 that measuring happens, but the signal gets to the hypothalamus and it uses that to determine whether

00:37:48.620 you essentially have the amount of fat that your hypothalamus wants you to have. So the same way that

00:37:53.840 your thermostat has a set point and your internal thermostat in your body has a set point, your

00:38:00.440 hypothalamus has a certain idea of how much fat it wants you to have on your body. If you deviate from

00:38:06.920 that, it starts to engage a coordinated series of physiological and behavioral responses to restore

00:38:14.280 the previous level of body fat. This system works better at protecting against fat loss than it does

00:38:22.120 against fat gain. And certainly over long periods of time, we see that the average person in a country

00:38:27.620 like the U.S. tends to gain fat. The lipostat is not stopping them, or at least it's not preventing

00:38:33.940 them. It might be resisting, but it's not stopping the process of weight gain. But we see that it actually

00:38:41.560 is quite vigorous at defending against weight loss. And this is part of the cruelty of or the unfairness

00:38:50.480 of how obesity works is that your set point or your defended level of body weight, there's a controversy

00:38:57.980 about what to call that, but whatever it is, it goes up. And so a person with obesity, their body defends

00:39:04.600 against weight loss as if they were starving, just like a lean person losing weight, their body

00:39:11.280 and brain would defend against weight loss. It's literally a starvation response. It's the same

00:39:16.700 behavioral and physiological process that ramps up your hunger, that makes you more focused on food

00:39:22.900 cues, greater cravings. It down-regulates your energy expenditure and does everything it can to try to

00:39:31.920 bring the fat back. So that is a key reason and possibly the primary reason why weight loss is so

00:39:38.820 difficult and so temporary. If there was no regulation happening, weight loss would probably be pretty

00:39:44.780 easy. And weight maintenance certainly would be very easy. But it's not. You see that people tend to

00:39:50.120 regain back to their former level unless they're being really well supported in that weight loss. And even

00:39:57.880 then, there's usually some amount of weight gain, weight regain, I should say. Let's go back to leptin

00:40:02.940 for a moment. So leptin is a hormone. Is it made in the adipocyte? It's made in the adipocyte and

00:40:10.000 secreted in proportion to body fat mass. So the more adipose tissue you have, the more leptin you have.

00:40:17.880 Is it generally pretty static? Does it change with meals or exercise or anything like that?

00:40:23.280 Yes, it does. So over the long run, the amount of leptin in the bloodstream is strongly correlated with

00:40:32.740 fat mass. However, it's also strongly impacted by short-term energy balance. So if you, let's say,

00:40:42.060 cut your calories by 25% for a couple of days, you're going to see a drop in leptin that is

00:40:49.080 disproportionate to your amount of fat mass. So where is the leptin receptor? Is there a leptin

00:40:55.880 receptor in the periphery or are they central? There are leptin receptors in many parts of the body,

00:41:01.800 but the ones that are relevant for body weight regulation are in the brain.

00:41:06.460 Are they in the hypothalamus? There is a high concentration of leptin receptors in the

00:41:10.360 hypothalamus, yes. There are leptin receptors in other parts of the brain too. However, it's not

00:41:18.560 100% clear where the important ones are for body weight regulation. Probably somewhere in the

00:41:24.720 hypothalamus, but there are a lot of different papers where they take mouse models and they knock

00:41:29.100 the leptin receptor out of different cells in the brain. If you knock them out of GABAergic cells,

00:41:35.120 basically you recapitulate animals that don't have the leptin receptor at all in terms of their body

00:41:40.380 weight. GABAergic, that's a major, one of the two big neurotransmitters. That's the main inhibitory

00:41:46.920 neurotransmitter in the brain. And then you can knock it out of certain cell subtypes in the

00:41:51.340 hypothalamus and get big effects. There was a paper suggesting you can just knock it out of AGRP neurons

00:41:57.120 and recapitulate the obesity phenotype of animals that have no leptin receptor. However, that is

00:42:03.880 controversial. Not every paper has shown that. I'm not sure what people who are on the cutting edge of

00:42:10.340 this field would say about where that evidence is. But certainly there are cell populations, and probably

00:42:17.540 the most important ones are in the hypothalamus. There are cells in the brain, probably mostly in

00:42:23.020 the hypothalamus, that are receiving that signal and conveying it to the key cell types that are kind

00:42:30.780 of at the center of this lipostat, which are AGRP neurons. I refer them in my book as MPY neurons just

00:42:38.620 for storyline simplicity, but more commonly they're called AGRP neurons and POMC neurons. So the AGRP,

00:42:46.660 those are the hunger neurons. The POMC are the satiety neurons, or you could think of them as

00:42:52.660 hunger slash body fat increasing neurons. The POMC are the opposite, essentially.

00:42:59.900 What is leptin resistance and how does it manifest? Why does it manifest? And how frequent is it?

00:43:06.000 When leptin was discovered first in 1994 by a team led by Jeff Friedman and Rudy Leibel,

00:43:13.840 they found that this was the gene that was missing in an obese mouse model called the OB-OB mouse.

00:43:22.740 This animal was extremely obese as a result of lacking a defect in the production of this protein.

00:43:29.400 One single base pair that destroyed this protein and caused the loss of function in this massive

00:43:35.380 obesity. And when this was discovered, and also discovered that humans have leptin,

00:43:41.220 then it was like this scientific bonanza. It was like, well, maybe we've discovered the cause of

00:43:46.760 obesity. Maybe people with obesity don't have enough leptin. And so their brains think they

00:43:52.360 don't have enough body fat when really they do. The failure to perceive the body fat, that's what

00:43:58.160 causes obesity in these OB-OB mice. So they started measuring leptin levels in people with obesity.

00:44:05.560 And it turns out they were actually elevated. Yeah. Because it's correlated. We now know it's

00:44:11.640 correlated with fat mass. You know, what's the deal? If this is a hormone that regulates body

00:44:16.820 fatness, why is it that people with obesity have so much of it and it's not suppressing their excess

00:44:24.020 body fat mass? The concept that has been invoked to explain this is leptin resistance. So in the same

00:44:32.640 way that people can develop insulin resistance, where it takes more insulin to do the physiological

00:44:37.120 jobs in the body, people with obesity require more leptin for the hypothalamus to be satisfied.

00:44:46.180 Another way to say that, they require more leptin to avert the starvation response that the brain has

00:44:53.280 where alarm bells start going off because it thinks you don't have enough body fat. So they require more

00:44:59.780 leptin to achieve that state. So we call that leptin resistance, but we don't really know how

00:45:04.740 it works yet. That's just a general term for requiring more leptin to avert the starvation

00:45:11.760 response. But we don't know whether that is something where there's fewer leptin receptors on

00:45:17.260 certain kind of cell, whether there's a downstream signaling impairment in cellular signaling cascades,

00:45:23.520 whether there is a change in cell-to-cell communication. Maybe the cell that's receiving

00:45:28.540 a leptin is getting the message just fine, but there's some kind of downstream change in

00:45:33.680 neural processing where the signal gets clouded or modified. We don't know the answer to that

00:45:39.080 question. It seems like the only thing we know is it's not too low an amount of circulating leptin

00:45:45.040 as evidenced by two things. One, the high circulating levels of leptin and the fact, I think more

00:45:50.660 importantly, that when you give exogenous leptin, it doesn't improve the condition, suggesting that

00:45:55.460 that's not the defect. Yes. You can give high levels of leptin and it will cause weight loss,

00:46:01.240 but it doesn't do much. If you look at leptin signaling, there were some early studies done in

00:46:08.000 animal models suggesting that if you mash up the hypothalamus and you look at what's going on in

00:46:13.280 it broadly on average, you find that the amount of leptin response, the intracellular signaling

00:46:20.160 cascade that's activated by leptin is not really impaired in animals with obesity. It's like

00:46:26.360 they're getting the same leptin signal from a much higher level of leptin. I looked at some twin

00:46:31.940 concordant and discordant studies, identical twin, and I was surprised to see, maybe I shouldn't have

00:46:37.660 been surprised, but I was surprised at how heritable obesity was. It was about 0.7. When you see

00:46:44.160 heritability of 0.7, that tells you something is very, very genetically predetermined. So even though

00:46:51.480 a hundred years ago, virtually none of us were obese and today, let's just call it your lifetime

00:46:57.640 incidence of obesity is 50% and our genes haven't changed in a hundred years. So clearly our susceptibility

00:47:05.440 for obesity has been with us for a great period of time and it is highly, highly preserved. It's just

00:47:13.060 that in the last, whatever, 40, 50 years, we now have matched or mirrored our genes to an environment

00:47:20.380 that is allowing that trait to flourish. What do we know about the genes that regulate obesity

00:47:26.100 or fatness? Let's just talk about it through that lens, I suppose. The meta-analysis of twin studies

00:47:32.140 that I like to cite these days suggests an average heritability of 75%. Wow, that's even stronger.

00:47:39.960 It's massive. And there's some debate about that. But directionally, this is a really big deal.

00:47:45.400 It's very heritable. And a lot of things are very heritable. I think that's one thing we're learning.

00:47:50.800 So you have this very high heritability of body mass index, variation between individuals and body

00:47:57.740 mass index, about 75% of those differences between people is explained by their genetics. That's what

00:48:04.900 that implies. If we look at other methods that have tried to figure out what are the genes that

00:48:11.860 underlie this, what are the genetic differences? These are the genome-wide association studies that

00:48:17.800 I think are particularly informative in this regard. They simply ask the question, if we look at the

00:48:23.660 entire genome and we look at these representative genetic markers where different people have different

00:48:30.260 genetic code called SNPs, single nucleotide polymorphisms, where in the genome, what markers

00:48:36.780 correlate with differences in body mass index. Fortunately, body mass index is really easy to

00:48:42.540 measure. So you can get really big sample sizes in these studies, which you need to get statistically

00:48:48.280 significant results. Because you're looking at, I think, like millions. I don't remember exactly how

00:48:53.960 many, but you're looking at a lot of genomic markers. So you need tremendous statistical power

00:48:58.840 to detect anything with a high level of confidence. So you have these studies. I think the latest is

00:49:04.660 like 800,000 people. The leader of the pack is the height genome-wide association study. I think they

00:49:10.700 have like 3 million. And now they've saturated the heritability. They've gotten all the information

00:49:15.520 they can with that sample size out of what the common genetic variants are that correlate with

00:49:22.860 differences in height. I think with body mass index, we may, in the near future, we may saturate it as

00:49:28.460 well. We may know what are all the common genetic differences that correlate with differences in body

00:49:35.280 mass index. So far, these studies have identified 900 variants that differ. What this suggests is that

00:49:43.800 differences in body mass index between individuals are very complex, genetically very complex. They're

00:49:51.940 determined by a lot of different genes with very small effect sizes. So you get this sorting of all

00:49:59.860 these different genes, and whatever combination you get, lucky or unlucky, determines whether you're,

00:50:06.740 to a large degree, determines whether you are susceptible or not susceptible to obesity in a fattening

00:50:13.000 environment, is the way I would put it. So they have various ways of looking at what these genes are

00:50:19.640 doing, because that's one way you can use these genome-wide association studies that's particularly

00:50:25.220 informative. You could say, what's the underlying biology that makes some people fatter and some

00:50:29.980 people slimmer? And I want to talk a little bit about why this is such an important approach.

00:50:35.660 One is that you're looking at people in their regular, everyday context. This is not an artificial

00:50:41.060 lab scenario. You're just looking at people living their lives and experiencing higher or lower weight,

00:50:47.200 and you're saying what genes correlate with that. So it's very naturalistic. Second, it's very

00:50:53.400 replicable. These studies are highly replicable. In other words, if you do three studies of this

00:50:59.720 nature, you're going to tend to get similar results. So the methodology, it's one of the most rigorous,

00:51:06.300 I would say, in the biological sciences that we have. And the third one is that it's unusually

00:51:12.040 objective as well. It has a higher level of built-in objectivity, resistance to bias compared to other

00:51:19.640 types of investigation, because it's not hypothesis-driven. You're just looking across the whole

00:51:25.340 genome and seeing what pops up. You're not saying, I'm going to focus on the connection between X biological 0.68

00:51:30.560 process and Y outcome. You're just saying, I'm interested in Y outcome, what correlates with it,

00:51:35.380 and let's see what biology pops up. Could be anything. We're just going to see. That really

00:51:40.480 gives you a chance to, I think, check your thinking on what the underlying biology is in various traits

00:51:48.600 and diseases. Part of that comes from the strength of what ultimately makes genetic analyses like

00:51:55.060 Mendelian randomization so powerful, is the genes are randomly distributed. That's what cleans out some

00:52:02.020 of those biases is when you are looking at a million people for whom the genes are randomly

00:52:08.240 spread across them. And you take an unbiased view of the sample, and then you get those results over

00:52:15.860 and over and over again. I think it becomes very powerful. And look, if people are listening to us

00:52:19.820 saying, God, what are these guys talking about? I mean, I think it's just important to understand the

00:52:23.120 big picture here. The big picture here is a thousand years ago, to all intents and purposes,

00:52:27.300 none of us were obese. But that still means, directionally, 50% of us at least had the genes

00:52:34.840 that would allow us to become obese in an obesogenic environment. That's really what we're

00:52:41.320 explaining here, is that there are a highly, highly heritable set of genes that will allow a subset of

00:52:48.280 the population. And actually, one of the things I'm just curious about your thoughts are teleologically,

00:52:52.400 why is it 50%? Why isn't it 100%? Was this just a fluke of evolution? You would almost think that

00:53:00.420 evolution would have wanted everybody to have those genes. Since you want to step back a little bit,

00:53:05.660 I just want to also add, what we're talking about is why some people can effortlessly stay thin,

00:53:11.880 and other people have to really struggle to maintain their weight, and maybe are not able to.

00:53:15.820 That's kind of like the everyday thing that we're trying to explain here, that many people recognize

00:53:20.780 intuitively, that is a thing, that different people have different propensities for becoming obese,

00:53:27.780 for developing obesity, or not. So we can look at the underlying biology, and that's been done.

00:53:33.440 And there are a couple different ways you can do it. One is you can say, what are the genes that seem

00:53:38.540 to be associated with these genomic differences, and where are those expressed? What tissues are those

00:53:44.240 expressed in? There was a paper where they looked at, I think, 43 different traits of all kinds,

00:53:49.880 diseases, personality traits, other stuff. And they asked, what does the tissue enrichment look like?

00:53:57.060 And if you look at body mass index, it looks like psychiatric diseases and educational attainment.

00:54:06.200 All of those are heavily enriched for brain-related genes to a similar degree. So conditions that we know

00:54:14.260 are related to are related to the brain, like educational attainment, how many years of education

00:54:20.340 you've attained, whether you are susceptible to schizophrenia, depression, Tourette's, like all

00:54:27.000 these brain-related conditions. Obviously, the brain shows up in genome-wide association studies for

00:54:32.940 those conditions. And you put those next to body mass index, and you couldn't tell them apart.

00:54:37.180 That's how heavily enriched for brain-related biology body mass index is.

00:54:44.140 And those diseases, by the way, that you just mentioned, are some of the most heritable diseases

00:54:48.100 we see in medicine. I mean, when you look at autism, when you look at schizophrenia,

00:54:52.960 these have heritability indexes of 0.6 to 0.7. They're highly genetic conditions. So there's two

00:55:00.360 things going on, right? Which is you have these parallel things that are highly, highly genetic,

00:55:04.700 and then they're disproportionately concentrated in the brain.

00:55:08.380 That's right. And I don't want to say that it's literally 100% about the brain. I think that's

00:55:13.980 unlikely to be true, but it's certainly the primary signal that emerges across the literature.

00:55:20.660 And so I think that really validates this idea of the brain being important for body fatness.

00:55:26.660 And if we look a little bit deeper at what is going on, for a lot of it, we don't really know.

00:55:32.260 We don't really know exactly how the brain is doing this, what it is about these genes. But we can see

00:55:38.980 that it correlates with certain types of ways of interacting with food. So people that have obesity

00:55:47.220 promoting genes tend to have greater eating drive. They tend to have lower satiety. But this is an area

00:55:55.460 that hasn't really been very well explored yet. So there's a lot we don't know. However, if you look

00:56:00.900 at the monogenic obesity syndromes, so where there's one mutation that causes severe obesity,

00:56:08.340 those really revolve around the leptin brain signaling axis. So those mutations tend to be in

00:56:15.540 leptin, the leptin receptor, melanocortins, melanocortin receptor that are downstream of leptin in the brain.

00:56:22.180 And those types of signals also show up in the genome-wide association studies. But they're not

00:56:27.860 dominant. A lot of this stuff is really general. It's like stuff that affects general neuronal

00:56:33.380 development and neurotransmitters that are involved in a lot of stuff. So I think there's a long way to

00:56:38.980 go before we really understand exactly how those genes are affecting the brain in a way that impacts

00:56:44.980 body fatness. But I do think we can say that differences in body fatness between individuals

00:56:50.420 are primarily determined by differences in how the brain is constructed and how it operates.

00:56:57.060 So, Stephan, let's now go back and try to put all of this in the context we were just

00:57:03.860 ready to get to a moment ago, which is it's 250,000 years ago. For all intents and purposes,

00:57:08.980 we're the same creatures we are now, obviously, minus the environment that we live in. But food

00:57:15.060 and energy are one of our top priorities. I'm not an anthropologist, but it would have to seem to me

00:57:23.060 that security from other tribes and animals and the environment, right, weather, acquisition of energy

00:57:30.660 and reproduction were kind of the only things that would have mattered. There probably wasn't a lot of

00:57:36.420 other stuff that mattered at the time. And acquisition of energy was essential in that

00:57:43.460 it could kill you very quickly if you failed to do that. So acquiring energy, storing energy

00:57:48.660 was the struggle that defined us, probably in the short term much more so than reproduction,

00:57:54.740 which obviously is a huge other contributor here. So we evolved over millions of years

00:58:01.140 and everything you said about leptin now starts to make sense in that environment.

00:58:05.140 Leptin is a signal that says there's not enough energy and that's what should really trigger the

00:58:11.940 response. So in that sense, it's not surprising that leptin isn't doing the opposite. It's not

00:58:17.140 surprising that high leptin doesn't make you want to stop eating. It's who cares? Nature wouldn't have

00:58:23.780 cared about that, but it certainly would care if leptin gets too low. That should be a screaming signal

00:58:28.900 to go and eat. Resist that sign. What do we know about the efficiency with which we store energy?

00:58:34.820 I mean, we haven't really talked about that, but this ability that we have to get fat is kind of

00:58:38.340 a remarkable thing. We don't really store carbohydrates. We can't really store protein,

00:58:43.540 and we don't want to be breaking down muscle to get amino acids. So we do really have to rely on this

00:58:48.820 ability to store fatty acids and excess carbohydrates as fatty acids in a relatively

00:58:54.820 inert structure of white adipose tissue. Yeah. I think Herman Ponser would be a great person to talk to

00:59:00.980 about this. His book is on my list to read, and I definitely plan to have him on to get into this.

00:59:06.180 Yeah. He has some good thoughts. John Speakman has some good thoughts on this as well. Another

00:59:11.140 person I should probably have on the podcast. There are good reasons to have a certain amount of body

00:59:17.700 fat. You know, the basic idea is pretty obvious. You want to have a way to cover your energy needs

00:59:24.580 between eating opportunities. We have other energy reserves. We have glycogen, but they're just far

00:59:30.940 more limited. The thing that's awesome about fat is, first of all, it's a very concentrated source of

00:59:37.700 energy. Dietary fat is nine calories per gram. Carbohydrate is four. Protein is four.

00:59:43.300 It's anhydrous. There's no water. It's literally just pure energy. That was the second thing I was

00:59:49.940 going to say is that it's hydrophobic. And so you can store it without having to hydrate it like you

00:59:56.560 do with glycogen. Glycogen, the weight of glycogen, I think is mostly water. Three or four to one water.

01:00:03.280 Okay. There we go. And then the weight of adipose tissue, even if you include all the interstitial

01:00:09.280 stuff and all that, I think it's like 85, 90% pure fat. So the energy density is just off the charts

01:00:16.340 relative to any other storage method that the body has. And so it makes sense that that's kind of our

01:00:23.340 long-term energy buffer. By the way, just for people who think about EVs and stuff, there's no

01:00:28.720 battery that can come close to the energy density of our fat, just to put that in perspective, or any

01:00:34.940 hydrocarbon for that matter. Yeah, that's right. So I think the importance of that is obvious to

01:00:40.280 have a way to cover times when you don't have as much energy coming in as you would like. And

01:00:47.440 in the evolutionary context, the thing that comes to mind from our modern perspective is whether they

01:00:52.900 find food or not, but there's also the question of illness. And I think that's a really important

01:00:57.320 one. So if we look at the primary causes of mortality in children under five in low-income settings,

01:01:04.000 what we see is that it's strongly related to their weight for height, which is kind of a different

01:01:11.980 way of measuring BMI. And it's also strongly related to disease pressure, especially diseases

01:01:18.040 like diarrhea that interfere with nutrition. If you look at the correlation between weight for height

01:01:24.640 and mortality, there's a massive correlation. So kids who have malnutrition, moderate or severe

01:01:31.180 malnutrition, that's what we call being underweight to a certain degree, they have massively increased

01:01:36.940 mortality because basically if you don't have those energy stores, you can't defend yourself

01:01:41.740 against infections. It's not just about energy. You know, there are other nutrients that are

01:01:47.220 important, vitamin A and some other things, but energy is huge. And so because it's such a huge source

01:01:54.120 of mortality, especially in kids, there's this massive selective pressure to maintain a certain

01:02:00.100 amount of energy storage in the body. So that would be an example of a selective pressure that would

01:02:07.640 select for a certain amount of body fat. And it is interesting in this regard that humans have a lot

01:02:12.920 more fat than our closest primate relatives. So chimps are like mid-single digits fat, and they don't

01:02:21.360 develop obesity. They cannot physiologically develop human like obesity is my understanding. We're kind

01:02:28.440 of special physiologically in our capacity for fat storage. Has anyone ever looked at different

01:02:37.540 ancestral populations, this might be just irrelevant to do because we don't have enough data, where there

01:02:45.060 were different amounts of food scarcity and seeing if there's an inverse relationship between the food

01:02:50.580 scarcity that that population emanated from, whether it's this part of Africa versus that part of

01:02:55.280 Europe, and how that translates into the genetic predisposition to obesity in their modern kin today?

01:03:03.000 I don't know the answer to that. But you understand the question I'm asking? Like... Yeah,

01:03:07.200 does a history with starvation select for more obesity type genes? For even greater obesity today,

01:03:13.300 exactly. I know that John Speakman has argued against this idea. He has pointed out that apparently

01:03:19.740 people with obesity do not survive famines better than lean people, which is kind of counterintuitive.

01:03:26.440 I'm not sure why that would be. I know that's a point that he's made. So anyway, that's about all I

01:03:31.500 know about it. I don't really know the answer to that question. So let's start to talk about the

01:03:36.660 hedonic aspect of food. We have five tastes. We can taste sweet, sour, bitter, salty, and umami. Those are

01:03:47.260 the five things we taste. What's the best way to describe umami to somebody? It's a meaty flavor

01:03:53.680 that is present in cooked meat, bone broth, soy sauce. Okay. So I think people kind of get it. It's

01:04:01.300 distinct from salt, I think is an important point here. Yes. Although they often go together. I know

01:04:06.620 different parts of our tongues have different... We sense, for example, sweet on the very front of our

01:04:10.720 tongue, I recall. But that's about the extent of my knowledge and recollection of where our tongue

01:04:14.300 resides in that. But what does the taste that we experience today, you and I, if we go out to a

01:04:20.320 restaurant, how does that compare to the range of taste that our ancestors experienced? This brings

01:04:26.560 up a topic that I like to talk about because if you look at what hunter-gatherers actually eat,

01:04:33.040 let's say we're looking at contemporary and historical hunter-gatherers where data have been collected and

01:04:38.880 using that as a proxy for types of food that our ancestors would have eaten, it is radically different

01:04:46.540 than what we eat today in many ways. But one of them is the hedonic properties of it. If you look

01:04:54.300 at what the Hadza eat, they go out and kill an antelope. They just like cut off pieces of meat and 1.00

01:05:01.500 throw it in the fire or put it next to the fire in coals. They don't have sauces. They're not putting

01:05:06.500 salt on it. And then they just like cut off the charred parts and eat. And sometimes it's like

01:05:11.780 half raw on the inside. They eat rotten meat, meat that we would consider literally rotten. They will

01:05:18.220 eat. I was just thinking about that the other day, by the way, because I eat so much wild game that I've

01:05:23.460 killed. But I realized like I'm still a baby because, A, I cook it. I don't eat it raw. But more

01:05:30.120 importantly, to your point, I season it, right? Like I use salt. I use pepper. I put lemon on it.

01:05:37.640 I'm sure it would taste fine without those things. It would certainly be edible. I just don't do it.

01:05:43.060 That's right. And if a person, a typical person were to try to eat at a Hadza camp for like a week, 0.97

01:05:50.840 I think it would be really challenging for them. Even meat, as you said, cooked unseasoned,

01:05:55.280 doesn't taste bad. Wouldn't taste as good. But now imagine like the outside is charred. Inside is

01:06:01.900 half raw. You're brushing sand off of it. That's kind of the context. That's the meat. That's like

01:06:07.360 one of the most palatable things they eat. And then we have probably the most palatable thing.

01:06:12.940 Certainly the thing that they really like is honey. But they're not putting it on toast with butter on

01:06:18.520 it. You know, they're literally drinking it straight. With a little jam.

01:06:21.720 They're just taking the honeycomb, eating it and like drinking the honey. So it's a bit of a

01:06:27.160 different scenario. Even there, they eat a lot of baobab. That is a very fibrous fruit that has

01:06:34.280 sweetness to it, but it also has some off flavors. It's not a very sweet fruit. It's not like an apple.

01:06:40.180 Got a lot of fiber. And then there's the tubers, which is another major article of diet. And to be fair,

01:06:46.320 this is their least preferred type of food. Oh, it is. They would rather eat things other

01:06:51.760 than tubers. But they roast these things in the fire. They dig them up. They're these like long

01:06:57.180 stringy things that look like long sweet potatoes. There are multiple species, but that's one of the

01:07:02.700 common ones. And they're so fibrous that they actually have to spit out a wad of fiber after 0.99

01:07:10.220 they're done chewing it. So it's like a sugar cane or something where you suck out the nutrient,

01:07:15.060 but you're spitting out the pure unsoluble fiber. Yeah. And so they're not sitting there

01:07:19.680 sauteing onions on the stove. They're not putting sauces. They're not spicing. They're just taking

01:07:24.940 food out of nature and cooking it and eating it. It's just a radically different type of diet than

01:07:31.940 we're accustomed to. I think in this regard, it's interesting to consider how reward circuits

01:07:39.980 adapt to that. Basically, our brains are set up to not be satisfied with ordinary stuff once we have

01:07:49.520 gotten good stuff, is a simple way to put it. Michael Crash's did a really interesting neuroscience

01:07:55.720 study on this in mice. Mice, normally they eat these unrefined food pellets. That would be like the

01:08:02.340 default diet, but they much prefer these calorie-dense, refined, high-fat pellets. And if you give that to

01:08:09.880 them, they will very much preferentially eat that over the healthier, unrefined pellets. And what happens

01:08:18.060 is they actually neurobiologically devalue, if you look at the circuits, activity of their reward circuits,

01:08:26.620 once they've been exposed to the preferred food, they devalue the less preferred food.

01:08:30.640 So it no longer satisfies them, no longer motivates them in the same way that it did before they were

01:08:37.500 exposed to the highly preferred food. To bring this back to our context, if you have somebody like

01:08:44.000 you or I who's been raised in a context where we have tasty, calorie-dense, easy-to-eat food,

01:08:51.300 and that's how we were raised, then going back to eat food more like how our ancestors would eat

01:08:57.460 is really difficult. Twice you've mentioned the calorie density. So let's now talk about that

01:09:02.000 because that's kind of different from taste. The taste thing is interesting to me. This is something

01:09:07.980 you and I actually remember speaking about probably one of the first times we met, which was, I actually

01:09:12.420 think table sugar is disgusting. Like I truly do. Like if you put a bowl of that white crap in front of 1.00

01:09:18.840 me and said, dip your finger in and eat it, I could maybe do it once, but that's about it. 1.00

01:09:23.380 If you said, just mix it into water and drink it, it's gross. Tastes fine in coffee and tea,

01:09:29.120 but just by itself, it's really disgusting. And similarly, if you just have me eat lard,

01:09:34.820 it's really disgusting. Despite the fact that I was on a ketogenic diet for three years,

01:09:38.880 I never developed a taste for putting coffee and butter and things like that. But I freaking love

01:09:45.900 ice cream. I think ice cream is about one of the most beautiful tastes in the world. Everything

01:09:53.960 about it. And it really isn't that much more than sugar and fat. I mean, yes, there's some flavors

01:09:59.000 to it. And if you make it a coffee ice cream, I like it even more. But so I guess my question is,

01:10:03.560 can you walk me through what my brain is doing when it's tasting sugar, when it's tasting butter,

01:10:10.540 neither of which by itself I find remotely enjoyable, but then when I'm tasting ice cream,

01:10:15.980 because the ice cream is not that much more caloric than the butter. There's something I'm

01:10:20.040 trying to understand here, which is taste and energy density. And how are those figuring out? Because

01:10:25.040 I believe they are instantly rewarding. So I'll give you one other analogy here. I remember when my

01:10:30.580 daughter, who's now 13, turned six months old. And my wife and I were really fastidious about not

01:10:37.480 feeding her any junk. Fortunately, my wife was able to breastfeed. So she didn't have all that formula. 1.00

01:10:42.860 And we were like your typical idiot first parents spent way too much time thinking about what she was 1.00

01:10:47.660 eating, I'm sure. But on her six month birthday, we got her ice cream. So this is kind of an interesting 1.00

01:10:52.600 experiment, right? Like she's never experienced anything like this. So I take a little ice cream cone and I

01:10:58.340 put it up to her face and I still remember where we were sitting in Del Mar when I did this.

01:11:03.080 Stefan, we're talking in milliseconds response from her. Milliseconds. Her eyes opened wider than

01:11:11.740 they've ever opened and she couldn't get into that thing fast enough. So to suggest that that isn't her

01:11:19.020 brain responding is crazy. There's nothing in her periphery in the moment that governed that response.

01:11:25.320 So whatever ice cream loving genes I have, she got them.

01:11:29.760 So I'm going to hard agree on ice cream. It's really for me like almost drug like the effect

01:11:35.180 it has on my brain. This brings up a couple of interesting questions. So you're alluding to

01:11:40.900 the fact that sugar and pure fat are very calorie dense. So if our brains are wired for calories,

01:11:49.560 why are those not very motivating? Which is a great question. So I'll start with that.

01:11:54.720 And the reason is that this starts to get into the complexity of it. There is an optimal concentration

01:12:02.200 of these nutrients that is not 100%. A great way to illustrate this would be with salt.

01:12:08.720 Eating straight up salt is not something that most people would enjoy. Like eating spoonfuls of salt,

01:12:13.980 it's horrible. But at the right concentration, it's excellent. It really enhances food. And so that's

01:12:20.800 actually generally true about all of these nutrients. It's true also about carbohydrate

01:12:25.480 and fat. A term that's been used for that is the bliss point. So there is an optimal concentration

01:12:30.980 for enjoyment and presumably also for reinforcement, which is that dopamine release that sets your

01:12:39.720 motivational drive and helps you learn and form habits. Ice cream, if you take out the sugar,

01:12:48.260 probably wouldn't taste bad without the sugar, but not nearly as good, right? If you take out the

01:12:53.640 fat, eh, fat-free ice cream is not flying off the shelves, even though it does exist. It's really

01:12:59.960 that combination of the two that really puts it over the top. And that's generally true. When you look

01:13:05.880 at the types of foods that are most commonly associated with strong cravings and loss of control over

01:13:13.000 eating, so like addictive-like behavior, you see that generally the foods that are cited are

01:13:18.100 combinations of carbohydrate and fat. Usually there's other stuff involved. There's flavorings,

01:13:23.800 there's salt in the savory items like pizza or french fries. So sweet or savory, generally they're

01:13:31.360 combinations of carbohydrate and fat. Again, it just relates to the fact that there is an optimal

01:13:39.020 concentration of these nutrients in terms of stimulating our reward centers. What you see in

01:13:46.900 modern foods that have been crafted to maximally stimulate enjoyment and motivation, either they've been

01:13:55.760 crafted by food industry or by grandma, passed down through the generations of recipes, what you see is that

01:14:03.280 generally these items are hitting multiple bliss points at the same time. That's just not really a

01:14:09.840 combination you see in nature. You don't see foods that are as reinforcing. The closest we would come is

01:14:18.840 like maybe certain types of nuts would have some carbohydrate and some fat together, but we really

01:14:25.380 don't see anything that really hits the high points as much as the foods that surround us today.

01:14:31.800 Let's go back to our ancestors for a moment. What apparatus was at their disposal subconsciously

01:14:38.500 or consciously to help them understand and prioritize calorically dense food? Because I got to believe that

01:14:45.980 the three things that mattered most, correct me if I'm wrong, would be total calories, protein, and

01:14:53.260 sodium. It can't be an accident that sodium is the only mineral we can taste. That is how I think about

01:14:59.480 it as well. And to break down the energy piece that would come for an animal with a digestive tract like a

01:15:06.180 human, that would come primarily from carbohydrate and fat. So we have carbohydrate, fat, protein, salt, and then 0.76

01:15:14.740 sometimes I add glutamate, umami to that list as well.

01:15:19.860 And this is subconscious? Is this again just part of that stuff that was now so wired into us that

01:15:25.700 yes, you know, we didn't want to eat grass. Like we knew that even though you could get the gastric

01:15:30.820 distension from eating a lot of grass, like a cow could, it was doing nothing for us both. It didn't

01:15:35.720 taste good. So in the short term, it wasn't pleasing. And in the longterm, obviously it didn't

01:15:39.740 satiate us. Yeah, that's right. There's a couple of angles on this one. Obviously humans have cultures. 0.80

01:15:45.860 So we figured out what foods are good over long periods of time, but a key aspect of this is dopamine

01:15:52.160 mediated reinforcement. Essentially our bodies are set up to respond to certain types of nutrients, like the

01:15:59.840 ones you mentioned, and create a motivation and learning response that prioritizes and sets the

01:16:08.240 motivational level on the seeking of those types of foods. Presumably these are the kinds of nutrients

01:16:16.160 that our ancestors would have needed to prioritize to maximize the reproductive success, the currency

01:16:24.320 of natural selection. So essentially we have these motivational systems that were selected to seek

01:16:30.080 certain types of nutrients in the environment. And if you look at the modeling that's been done on

01:16:35.040 foraging behavior in a wide variety of animals and in humans, you see that it revolves around maximizing

01:16:42.880 the energy return rate of foraging. This doesn't describe every species, but it does describe

01:16:48.240 many species. It's amazing to watch it in big cats, for example, where they'll be chasing an antelope and

01:16:55.760 it's literally almost like they have a sensor inside that says, I'm going to stop chasing now because my

01:17:02.640 energy cost is not going to be met by my consumption over this period of time. Absolutely. And these animals, they

01:17:09.840 don't know how to do math. They don't know that they're actually implementing a mathematical equation

01:17:15.200 in their head, but they are. It's just wired into their brains the same way it's wired into us. You can predict

01:17:22.160 hunter-gatherer foraging behavior to a surprising degree just by knowing the calorie return rate of different

01:17:28.240 foraging options. So our brains are very much wired, not just our brains, but our bodies are very much wired around energy

01:17:35.040 acquisition in terms of how our motivation and learning is set up on a non-conscious level.

01:17:41.120 This is very much hardwired. So we have dedicated sensors in the digestive tract. This is all pretty

01:17:47.360 recent research since 2018. They discovered these cells that they named neuropod cells in the small

01:17:55.760 intestine primarily that have receptors for specific nutrients that are directly, these cells are directly

01:18:03.360 hooked up to vagal neurons. So when they detect glucose or amino acids, fatty acids, so that would be

01:18:12.160 carbohydrate, fat, protein, they get the concentration and they start sending signals up your vagus nerve,

01:18:18.480 up to your brain stem. And from there it gets distributed to many parts of your brain, but particularly

01:18:24.400 relevant part is the parts of your brain that have to do with dopamine release onto your reward centers.

01:18:31.760 If the food that you're eating contains a high concentration of these valuable nutrients,

01:18:37.520 particularly in combination with one another, you're going to get a higher level of dopamine release.

01:18:42.720 The more dopamine release you get, the more of a motivation you will develop toward that food.

01:18:49.280 Is it that there are, and maybe this is just to me, I don't know what the literature would say,

01:18:53.920 so this could be incorrect, but in me, like a ribeye is not something I seem to be able to eat

01:19:00.160 into excess. And I feel like I should. Shouldn't I be wired to eat ribeye until I can't stand? Shouldn't

01:19:09.200 I be wired to eat ribeye until the point of vomiting, given how high it is in sodium, fat,

01:19:15.440 and protein, and total calories? Like the only thing it's missing is sugar and fiber and carbohydrates

01:19:22.400 and things like that. But it's easier for me to overeat baked potatoes than it is to overeat a

01:19:28.800 ribeye. And I'm not sure I understand why. Let me just clarify, with a potato, is that with or

01:19:35.360 without toppings? Let's say with. Let's put on butter, sour cream, and salt. So I'm clearly making

01:19:41.440 it much more than the carb, of course. And it has to be crispy skin too, like if I'm going to do it

01:19:46.560 right. You know, I can't be like some lame ass buffet baked potato. It's got to be my style. 0.88

01:19:52.160 I don't know why like a fatty piece of meat is not something I have an amazing, is my experience

01:19:58.400 typical? Would most people be able to just eat ribeyes until they puke? Oh, that's a good question.

01:20:04.160 I really don't know. I will say that when you look at the foods that people cite as the most typically

01:20:13.040 associated with strong cravings and loss of control over eating behavior, meat does not usually come

01:20:19.040 up high on that list. Which seems like it should. I can understand where you're coming from. I don't

01:20:24.400 know whether that's a kind of generalizable phenomenon. I can only speculate about why that

01:20:30.320 might be. So there are a couple of things that come to mind for me. The first is that meat is about

01:20:37.120 75% water. So the calorie density of is actually, it's not low, but it's not especially high unless

01:20:45.440 you're eating a really fatty piece of meat. So that's one thing. If we're comparing it to something

01:20:50.800 like brownie or something like pizza, which is more calorie dense than the steak. The second thing is,

01:21:00.160 it doesn't have any carbohydrates. So it doesn't have that fat carbohydrate combination

01:21:04.320 that is most closely associated with foods that people lose control around. The third thing I would

01:21:12.400 cite is the high protein level. So even though we have this strong protein specific appetite

01:21:20.480 that's been demonstrated in many different species, protein doesn't work the same as carbohydrate

01:21:26.640 and fat. We recognize that that's the case. Protein seems to, it's something that our bodies really

01:21:33.840 want to get enough of, but don't want to get too much of. So there's really a, not only there's a

01:21:38.880 drive to acquire it, but there's a drive to keep it within a certain range and not eat too much. And we

01:21:45.120 see that, you know, if people go on high protein diets, their overall calorie intake will drop.

01:21:51.840 I wanted to talk about the carnivore diet with you a little bit, because I know you guys did a review

01:21:55.840 on a book. It's not a diet I've spent any time really thinking about. So I've basically spoken to,

01:22:02.000 I don't know, a dozen people who have gone on it and without exception, they all lose weight,

01:22:08.080 which I think for some of them is their motivation for doing it. And it must simply be that they just

01:22:13.760 get tired of eating. They just can't take in the number of calories if they're doing it in that

01:22:19.040 format. We don't have any good data on the impact of carnivore diet on weight. There's no

01:22:27.440 randomized controlled trials, but you know, we have these anecdotes of people saying they lose

01:22:32.640 a lot of weight. I certainly don't dispute that. But I think if you came to me with this diet on

01:22:38.640 paper and you asked me, would this cause weight? I would say absolutely, because it has multiple

01:22:43.280 properties that I would expect to make it a particularly effective weight loss diet. One,

01:22:51.040 this is something we could talk about more if you want, but it has zero carbohydrate. If you're on

01:22:56.880 the extreme of the fat to carbohydrate ratio in either direction, that's more slimming than being

01:23:02.640 in the middle. So the most fattening diets are rich in both carbohydrate and fat. So there's zero

01:23:08.800 carbohydrate. You're on the extreme, or I shouldn't say zero, very, very little.

01:23:12.160 Right. Outside of the glycogen in the meat. That's about it.

01:23:14.880 Yeah. There's a little glycogen. So you're on the very extreme end of the macronutrient

01:23:20.720 distribution. It's high in protein. That's also known to contribute to weight loss. You're

01:23:26.800 eliminating almost every type of food. The variety of your diet goes very low. I mean,

01:23:32.080 you can prepare your meat in different ways. You can eat chicken or fish or beef or whatever,

01:23:36.400 but the variety is greatly, greatly reduced. So that's, I think, part of it. And you're cutting

01:23:42.320 out all of these highly processed calorie dense foods that are the foods that I think

01:23:49.360 we could debate about why, but I think everyone agrees that those are foods that drive excess

01:23:55.440 intake and elevated body fatness. So I think all these things together, it's just even on paper,

01:24:02.000 it's a diet that I would very much expect to cause weight loss to a greater degree than your average

01:24:07.920 diet. And while we're on the topic, tell me a little bit about your review of this,

01:24:13.200 because I know you've put some time into this. I don't really plan to do a podcast on the carnivore

01:24:18.320 diet. It doesn't seem to make a lot of sense to me, although I don't dispute that there are people

01:24:22.960 who I think have had very successful outcomes on it with respect to dealing with some of their

01:24:28.320 physical ailments. So maybe it has a role in overcoming some acute illness. And maybe I'm just

01:24:34.640 biased towards thinking plants are valuable. It seems to me that one of the core tenets of the diet is

01:24:40.400 that plants are low grade toxic. Isn't that sort of part of the thesis? The thesis is basically

01:24:46.240 everything is toxic except grass-fed animal foods. Even tap water is considered not optimal.

01:24:57.600 The book spends a lot of time going through the litany of all the potentially harmful compounds in

01:25:02.960 plant foods. And actually, you know what? I sympathize with some of this. I think there is

01:25:07.680 a bias toward thinking if it's in a plant, it's healthy. And I don't think that's true. I think the

01:25:13.680 book is right that that's not necessarily true. There are some plant compounds that, at least for

01:25:20.240 some people, are not so good. And there are well-characterized examples of this. If you eat

01:25:26.320 a lot of spinach, you can get kidney stones from all the oxalate. There are studies suggesting that

01:25:32.800 the glucosinolates in cabbage family plants might contribute to type 2 diabetes. Kidney beans, if you

01:25:41.360 don't cook them enough, they can be really toxic because of the lectins. So it's not like there

01:25:46.240 aren't examples of this. It's definitely true that, to some degree, I think it just gets taken

01:25:53.360 far beyond where the evidence is. And the way to think about how healthy a food is is not to say,

01:25:59.840 does it contain toxins? It's to say, what's the cost-benefit analysis on this food? And most

01:26:06.560 importantly, what are the empirical outcomes that we can see when its impacts on health are directly

01:26:11.520 studied? This is something that I've kind of focused on in my evaluation of some of the ideas

01:26:19.440 that are put forth in the public sphere is that a lot of people who are coming out with, let's say,

01:26:24.800 unusual ideas in this sphere, they take a mechanism and they run with it. Like X toxin is really bad,

01:26:32.240 like lectins, for example, Gundry. Lectins can do XYZ, lectins are in plants, therefore we shouldn't

01:26:38.640 eat these types of plants. And that's really like a bottom-up approach, extrapolating empirical effects

01:26:46.560 on health from mechanism, when really, I think in a complex field like nutrition, it's better to start

01:26:53.200 with the empirical evidence. Oh, we have this study that suggests that there's actually an effect on

01:26:59.920 health. Let's see if we can understand the mechanism. What are some of the biochemical

01:27:05.520 changes that occur in people on a carnivore diet? I mean, the obvious one must be the dyslipidemia,

01:27:11.200 right? Yes. There's a shift toward a ketogenic metabolism because of the fact that it's very low

01:27:20.880 carbohydrate. That would be an obvious shift that occurs. I don't know if I'd use the term

01:27:27.200 dyslipidemia, but one of the potential downsides I focused on in the review that is downplayed by

01:27:34.480 many carnivore diet advocates, including Paul Saldino, is the change in LDL cholesterol and LDL

01:27:42.720 particle count. And again, we don't have great evidence here, and this is kind of the crux of our

01:27:47.920 review of the book on Red Pen Reviews, is simply that there are a lot of claims made that are not

01:27:54.160 supported by any kind of convincing evidence. But we have some evidence. So there's this survey study

01:28:01.360 that was done on something like 2,000 carnivore dieters. I think David Ludwig was involved in that.

01:28:07.840 And they just reached out to people in social media groups, like their Facebook groups and things,

01:28:14.160 and they administered this survey. And one of the questions was, what was your various blood lipid

01:28:21.360 values before and after this diet? And you see that there are changes in positive and negative

01:28:28.880 directions. Triglycerides go down as you would expect. I don't remember what HDL did, but it

01:28:34.880 probably went up. Probably went up. Yeah. And then there was a large increase in LDL cholesterol.

01:28:42.720 And that's a concern, as far as I'm concerned. And I think you would agree. And Paul Saladino himself,

01:28:48.800 I'm not trying to pick on him. I don't want to make it personal, but he's been public about some

01:28:53.600 of this stuff. So I think it's fair to just repeat what he himself has said. But his LDL cholesterol is

01:29:01.120 533 mg per deciliter. And his LDL particle count is also absolutely through the roof. Not everyone

01:29:10.720 responds like that. If you look at the survey data, I think there was a mean increase of like 30 mg per

01:29:16.400 deciliter in LDL, 30 or 40, something like that. So I think it depends on the individual. I think

01:29:23.520 Sean Baker's lipids are fine. He's another carnivore diet guy. Last time I saw his lipids looked just

01:29:29.840 fine. So I think it depends on the individual. But some people do experience a large increase in LDL

01:29:37.120 cholesterol. You know more about this than I do, but that certainly raises red flags for me in terms of

01:29:42.960 cardiovascular risk over the long run. Yeah. The thing I've never understood,

01:29:48.240 and this is probably true of not just carnivore, but ketogenic or anything that does produce that

01:29:53.520 hyper-beta lipoproteinemia. It almost seems to be worn by some as a badge of honor, as opposed to saying,

01:30:00.160 well, maybe this diet is doing a lot of really good things for me. It's improving my insulin

01:30:05.040 sensitivity. I feel better. I have fewer energy swings, but this one thing isn't so good. But

01:30:10.960 here's the thing of all the things that could go wrong. That's about the most treatable one out there.

01:30:16.160 It's very easy to treat elevated ApoB. And this is what we do clinically, right? This is how we

01:30:22.800 treat patients. We have patients who only get better on very, very carbohydrate restricted diets.

01:30:30.640 But then if they develop that pattern, that elevated LDL pattern, we have a choice to make,

01:30:37.440 which is we abandon the diet or we treat the elevated ApoB. And that's not a failure. That's

01:30:42.160 simply using modern medicine to help us achieve the best of both worlds. I think I've always struggled

01:30:47.760 to understand why a person will go on that diet, have an ApoB or LDL go from the 50th percentile to

01:30:56.640 north of the 99th percentile. And instead of being curious about what the implication is,

01:31:02.240 dig their heels in and say, clearly, this is a good thing. And LDL does not cause heart disease.

01:31:06.560 I absolutely agree. It's a dietary ideology. It's an ideology that has emerged to defend a certain

01:31:16.400 type of dietary pattern. These kinds of ideas emerged from the low carb community essentially to

01:31:22.800 defend against the idea that there might be some downside to certain types of low carb diets.

01:31:28.560 And they've been taken to an extreme, I think, in the carnivore community because that's a

01:31:33.920 particularly potent stimulus for increasing LDL. So people don't want to believe that there's a

01:31:40.000 downside to the thing they're doing. I kind of get it. People go on this diet, they lose weight,

01:31:45.840 they feel better. Some people say their skin cleared up or XYZ condition improved.

01:31:51.280 There's all these tangible things they can see that are getting better. They don't want to believe

01:31:56.800 that there's an intangible thing that's actually putting them at severe risk. I say severe risk,

01:32:03.120 I just mean cardiovascular disease is a big risk generally. As you know, this is the number one

01:32:09.840 killer. Cardiovascular disease is a huge big deal, even if it doesn't kill you. It can do really bad

01:32:15.440 things to you physically and cognitively. So it's not a risk you want to be ignoring.

01:32:21.040 It's an irrational part of dietary tribal ideology that is holding people back from experiencing their

01:32:30.640 best health. And it's so treatable. I said that in the review too. I was like, you don't even have

01:32:35.840 to stop the diet. You can just get it treated or you could modify the diet.

01:32:40.800 You see the same sort of equally stubborn ideology at the exact opposite end of the spectrum,

01:32:47.120 where we see these patients that'll go on these incredibly restrictive plant-based diets. And

01:32:53.280 it's usually some combination of micronutrient deficiency and or protein deficiency that's going

01:32:57.920 to be the death of them. But there's no deviating from it. There's no, like, I'm going to supplement with

01:33:04.080 protein shakes. I'm going to take B vitamins I'm going to do. And again, it's the same sort of thing.

01:33:09.040 It's like somehow, if I acknowledge the fact that I need to supplement with these other things to

01:33:14.160 work around a diet that I otherwise like, or that is congruent with a belief system I have around the

01:33:19.760 treatment of animals, which I can respect that. If that's your belief system, then by all means be

01:33:24.080 true to it. But yes, I find it somewhat self-destructive. Absolutely. I think it's very analogous to what we

01:33:30.640 see in certain corners of the vegan diet community. They want it to be best for everything. It's got to be

01:33:35.360 best for the environment and for ethics and for health. It's just very hard to swallow that there

01:33:41.840 might be some downsides. And for the carnivore diet too, you see like they try to justify the

01:33:47.280 environmental aspects of it too. In the carnivore code, he talks a lot about regenerative agriculture,

01:33:55.120 which is a concept that I think is interesting and I support it, but it's a certain, I would say,

01:34:02.320 spin on it that makes it seem particularly favorable. And also there's an underlying assumption that the

01:34:08.160 average carnivore is going to eat nothing but regenerative agriculture beef, which I think is not

01:34:14.240 the case. Let's talk about one more big topic, Stefan, which you've written a lot about. I don't know if

01:34:20.320 you're sick of it or you're still enjoying it, but this idea of energy balance, carbohydrates and insulin

01:34:27.280 and unifying theories around adiposity. Very recently, I heard you and Kevin Hall on a podcast.

01:34:35.280 I don't remember what the podcast was called, but it was a wonderful discussion because I know you

01:34:39.760 well, I know Kevin well, and anytime I can listen to a podcast with people who I know a lot about and I

01:34:46.380 know most of what they have to say, but yet I still pick something up in the discussion. It's fantastic.

01:34:51.180 And that was an example. In it, you guys did a pretty good job, I thought, of really explaining the history

01:34:59.320 of these models, which I think you acknowledged are probably not perfectly named. So there's a little bit

01:35:05.480 of historical baggage that goes into the nomenclature. And anybody who's able to pay attention long enough

01:35:11.800 will realize that there's a lot in common with these models, but there are some fundamental differences that

01:35:18.620 are important to understand. Maybe we could talk a little bit about that. Again, I think this is

01:35:23.860 not a time to be overly simplistic, right? I think this is a time for nuance and it is a time for

01:35:29.300 putting the finer point on the similarities and differences of these models. So maybe just start

01:35:33.920 by explaining, pick the one you want to start with and kind of walk through them. So the two models are

01:35:40.180 the carbohydrate insulin model and the energy balance model. And the carbohydrate insulin model,

01:35:47.060 I just want to get a little more specific with that because there are different versions of this.

01:35:53.060 So this is the one that has been promoted by David Ludwig and particularly in a recent review paper

01:36:01.040 that he published along with some other researchers. The energy balance model in this case is being

01:36:08.400 represented by Kevin Hall, but I would say it has very deep roots in models, similar models that go back

01:36:15.500 decades. Carbohydrate insulin model in its most recent incarnation is a lot more complex than previous

01:36:23.980 inclinations. So I'm going to do my best to summarize it and hit the key points. Essentially, it's the idea

01:36:30.700 that there are things in the diet and in the environment that impact insulin signaling and insulin signaling

01:36:38.780 impacts body fatness. And then that fattening process of insulin signaling on adiposity, then downstream leads to

01:36:51.740 elevated calorie intake and possibly a decline in metabolic rate. So it proposes a reversal of the relationship.

01:37:00.780 This is one of the key aspects I want to highlight. Proposes a reversal of the relationship between

01:37:07.260 energy balance and body fatness. Basically, the energy balance phenotype is downstream of that fattening

01:37:14.940 process instead of being upstream. That really, I think, is a key difference. When we go to the energy

01:37:20.460 balance model, the energy balance is upstream of the fattening process. So basically, we have all these things

01:37:27.340 happening in the environment and physiologically in our bodies. Those signals are impinging primarily on

01:37:33.500 the brain. And then energy balance is a result of primarily that brain activity. And then that is feeding

01:37:41.420 into adipose tissue. So in that context, adipose is body fatness is kind of receiving the excess energy. It's not

01:37:51.180 really the driver of this process. But when excess energy enters the body, it's what mops it up. That's

01:37:57.900 kind of the difference between those two models. Let me say that again, just to make sure we've got this

01:38:03.900 right. So in the former model, in the carbohydrate insulin model, the idea is that the primary cause

01:38:12.140 is the adipose tissue increasing in its fatness, right? The adipose tissue

01:38:18.380 wants more energy that's driven by the external factors, both carbohydrate and otherwise.

01:38:23.740 So in a drive to increase the influx of fatty acid into adipose tissue, you see a reduction in

01:38:32.140 circulating metabolic fuels, which drives an increase in appetite. So intake goes up to accommodate the

01:38:40.940 reduction in circulating metabolic fuels, which is being caused by a drive towards fatness.

01:38:47.500 The conventional model basically says that's happening in reverse. It's saying that the input

01:38:53.260 of fuels into the system leads to an increase in circulating metabolic factors that is now

01:38:58.940 driving energy balance into the fat cell. Is that safe overview? Yes. You said conventional model,

01:39:06.620 though, and I've heard both terms used. So sorry, just I think this is worth a moment to clarify. So if you

01:39:13.100 look at David Ludwig's paper, he contrasts the carbohydrate insulin model against what he calls

01:39:19.660 the energy balance model, which is basically calories in, calories out. None of this is really

01:39:26.220 regulated. It's just however many calories you happen to passively eat or how much you decide to

01:39:31.900 exercise. And then your fat tissue is a result of that. The energy balance model, in contrast,

01:39:40.140 is acknowledging all of this brain regulation of body fat, brain regulation of appetite,

01:39:46.620 and saying actually body fat is a regulated process. However, it's body fatness, I should say,

01:39:53.900 is a regulated variable. However, it's regulated by the energy intake and expenditure via the brain.

01:40:02.780 Got it. Okay. The conventional model, I will say, is not a model that really any obesity researchers

01:40:11.340 currently ascribe to, at least the obesity researchers who are actually studying the mechanisms of body fat

01:40:20.140 regulation. One of the things that Kevin pointed out on this podcast to go further on that, down that

01:40:26.060 thread is the energy balance model does not consider all calories identical. Yeah, it does not presuppose that

01:40:31.820 they're all identical. That's right. In terms of their impact on body fat. So not only do they

01:40:37.500 potentially have different thermogenic effects, they also might have different regulatory effects on

01:40:42.700 compensatory appetite, right? That's right. And I think where we really see this emerging is in animal models.

01:40:50.620 I don't know how relevant this is for humans, but I'm just using it as a general proof of principle that it can

01:40:56.060 happen. You can see in animal models where you can change their diet composition. David

01:41:01.740 Ludwig has shown this for carbohydrate quality. It's been shown for dietary fat as well. And you

01:41:07.420 can actually produce animals that will gain fat independent of calorie intake. So you can actually

01:41:15.020 clamp them at their former calorie intake and they will nevertheless gain fat. At least in principle,

01:41:22.620 those types of effects are possible. I believe Rick Johnson described an experiment like that on my

01:41:27.980 recent podcast with him, which was an isocaloric swap to a very high fructose diet where the animals

01:41:34.940 didn't gain weight, but they fuel partition differently. They got fatter. This was over a long time. This was

01:41:40.780 over nine months. So nine months for a mouse, right? As an eternity. Yeah, absolutely. That has been shown in a

01:41:48.220 number of contexts that that can happen in rodents. I think it's worth pointing out that rodents have

01:41:53.900 their energy expenditure is more plastic than ours. By the way, I want to go back to that. This will tie

01:41:59.660 into what we're about to talk about, but you have a person who weighs 200 pounds, a person who weighs

01:42:04.940 160 pounds of the same height. The 200 pound person loses 40 pounds. They're now 160 pounds. The other

01:42:12.300 person's always been 160 pounds. On the surface, they look identical. In fact, let's pretend they're siblings,

01:42:18.940 but one was obese and he's now post obese. The other was never obese. Let's pretend that that

01:42:25.100 one that lost the 40 pounds has really kind of dialed it in and doesn't yo-yo. He manages to stay there.

01:42:33.500 It's three years later. Are they the same person yet? No, probably not. So Rudy Libel has done studies

01:42:42.780 where I think they've had people out to a year, maybe two years, where they have them weight reduced,

01:42:50.620 and the starvation response, this leptin-dependent starvation response, he hasn't seen any sign that

01:42:58.460 it goes away. Could it maybe be possible under some circumstances? Maybe, but the evidence that I've

01:43:04.220 seen suggests that it is at least not typical. So I want to specify that the set point around which

01:43:13.660 the lipostat regulates can change based on dietary and environmental variables. An example that you'll

01:43:21.740 be familiar with and others probably listening will be familiar with, if you take someone on a typical

01:43:27.180 diet and put them on a low-carb diet, you don't have to tell them to reduce their calorie intake.

01:43:32.940 That will occur spontaneously and they will lose fat and end up, in the typical person,

01:43:40.220 comfortably being at a lower weight. They're not experiencing the starvation response. And you see

01:43:45.900 this on other diets as well. So I think there are things we can do to change the set point. However,

01:43:53.180 that doesn't mean that they are cured. If they went back to their other diet, if they just went back

01:43:58.940 to how they used to be eating, so they're not maintaining this attempt for weight reduction

01:44:04.220 anymore, they generally will go back to where they were. So it's not that there's a durable

01:44:10.460 resetting of the set point to like flipping a switch and resetting, like restarting your computer. It's

01:44:17.900 more like the set point has been modified because it's in a different environment. And as long as you

01:44:23.900 maintain that change, you can maintain the effect. But if the change goes away, then the effect goes

01:44:30.140 away. Where do we think is the greatest window of vulnerability for someone? Just going back to

01:44:35.340 these two hypothetical individuals, let's take the genes out of it. Let's pretend they're identical twins.

01:44:41.500 Born in the same household, they both possess the genetic traits that would allow them in the right

01:44:47.180 environment to become obese. But one of them, let's just say had an injury in high school that kept him

01:44:54.460 home from playing sports. And he ended up playing more video games and kind of eating more. The other

01:45:00.060 one was more active. So that explains why when they're now 40 years old, one's 40 pounds overweight,

01:45:04.540 the other's not. Are there windows in a person's life when they are more susceptible to that resetting of

01:45:13.580 a set point, a higher and higher set point, which it sounds to me like it never goes down. It's a

01:45:17.820 monotonic crank. I honestly don't know. Certainly there is a substantial potential for most people

01:45:27.580 to gain weight at almost any point in life. So I'm not really sure. And by the way, let me say that I

01:45:34.460 think there are other people who could probably answer this question better than me. There are people who

01:45:38.620 have studied the trajectory of weight gain over the lifespan. So part of the issue here is I'm just

01:45:45.740 not that well versed on this literature. One thing I'll point out that is potentially interesting is

01:45:52.540 there may be an influence of the intrauterine environment. So what's going on as you're developing

01:46:01.980 inside the uterus. So there is evidence, I wouldn't call it strong, but there is evidence that women 1.00

01:46:10.380 who undergo bariatric surgery for obesity and lose a lot of weight, their children are at a lower risk

01:46:17.820 of developing obesity than women of similar weight who did not undergo bariatric surgery. And the effect

01:46:25.340 size is large. Wait a second. Meaning two women of the same weight have children. One of them is that 1.00

01:46:34.540 weight naturally. And the other one is weight reduced at that weight secondary to gastric bypass?

01:46:40.140 No, no. Think about two women with severe obesity. One of them has gastric bypass. After that surgery, 0.97

01:46:48.460 they both have children. But starting from different weights, obviously, because the gastric bypass one is

01:46:53.500 weight reduced. Correct. And the children of the woman who had the surgery and had previously lost

01:47:00.700 weight before getting pregnant have a lower risk of obesity. Again, I wouldn't call the evidence strong.

01:47:07.020 What if she achieved that weight loss without gastric bypass? So what if you had two women who were 1.00

01:47:11.020 overweight and one of them lost weight through diet and nutrition? I don't know. I am not aware of

01:47:18.940 data on that. You know, if you wanted me to guess, I would say it would probably be similar. But gastric

01:47:25.900 bypass, is that really the same physiologically as the physiological situation that you get from diet and

01:47:33.260 weight loss, diet and lifestyle? I don't think it is. I think gastric bypass is a unique situation

01:47:39.100 where provided a person doesn't take in liquid calories. It's quite durable. The Roux-en-Y.

01:47:48.460 Obviously, liquid calories can completely disrupt the feedback mechanism there. Kind of similar,

01:47:55.740 by the way, to a GLP-1 agonist. This actually kind of gets back to I've seen patients who take

01:48:02.220 semaglutide who don't lose weight. And the way you can cheat semaglutide is to drink your calories.

01:48:09.660 If you drink massive amounts of calories. Again, this is anecdotal. I don't know that this has been

01:48:13.020 studied. I'm just saying this based on observing a number of patients. But if you continue to drink

01:48:17.580 a lot of alcohol, if you continue to drink juices and things like that, you can sort of bypass some

01:48:23.580 of the GLP-1 effect on the brain, it would seem. That's my only explanation for why I see that.

01:48:29.180 And we do see that definitely with gastric bypass. So who knows about what that would look like.

01:48:34.460 What advice or what insight comes from this as it pertains to a person who's listening to this?

01:48:39.420 And by definition, half the people listening to this are probably at a body weight above where they

01:48:43.420 want to be. What's the takeaway in terms of pregnancy? No, no. Just in terms of overall

01:48:48.940 weight loss. You know, we're sitting here in this environment that is almost deliberately trying

01:48:54.940 to put weight on us. We're not going to get any help from our ancestors because the reality of it is

01:49:00.060 our ancestors didn't care if we gained weight. Quite happy to have us gain weight, actually. They

01:49:05.020 just want to make sure we don't starve. And so what can they do? And more importantly,

01:49:09.660 how do they keep it off? Because as you said, most people can lose weight, but the keeping it off is

01:49:15.820 really, it poses a challenge. I'm going to take this as a question about on the individual level,

01:49:22.380 which I assume is what you meant. There are a couple of different things to think about.

01:49:30.780 For people who have obesity, body mass index, 30, 35, I think it's worthwhile to consider

01:49:38.300 medical treatment. Something like semaglutide, for example, the tools that we have now are just

01:49:45.180 way better than what they used to be. That's a separate topic we could talk about.

01:49:51.100 Semaglutide, as far as we can tell, it's a very safe drug. It causes something like 18 percent weight

01:49:58.380 loss, which is much better than the typical effect you're going to see in diet and lifestyle strategies.

01:50:07.340 But like diet and lifestyle is something you have to maintain. So I think at this point,

01:50:11.900 now that the tools are getting better, particularly now that the tools are getting better,

01:50:16.460 I would recommend seeing an obesity medicine specialist for people who are experiencing

01:50:24.940 substantially impaired quality of life or are really concerned about the health impacts.

01:50:29.420 You know, if we switch the focus to people who might just want to lose a few pounds or who are

01:50:34.140 overweight, where they're not in as serious a situation, your appetite and your body fatness

01:50:40.700 are very much regulated by your brain based on inputs that your brain is receiving. And a lot of

01:50:46.380 that is non-conscious. The approach that I like to take is to try to give the non-conscious brain

01:50:52.780 signals that are going to be more consistent with your goals, signals that are going to tell your brain

01:50:59.100 to regulate things in a more slimming direction. And that way you're not relying on heavy exercise

01:51:07.580 of willpower all the time, which I don't think is really sustainable or effective for most people.

01:51:13.100 You are, instead of setting up a scenario where you have these non-conscious urges that you're having

01:51:19.260 to fight with your conscious brain, you're addressing the non-conscious urges directly. So there is no

01:51:25.020 fight. That's what I prefer. Controlling these signals that your brain is receiving is really

01:51:31.260 important. And there are different ways to do that. One of them is to control your food environment. So

01:51:36.700 the sensory cues in your environment that your brain is exposed to, whether there is food in your

01:51:42.220 immediate vicinity, how tempting that food is, how hard you have to work for it. If you can just grab it and

01:51:48.940 put it in your mouth, that's not as good as if you have to walk into a room and then peel an orange

01:51:55.660 before you can eat it. Just little effort barriers like that. And then with the types of food we're

01:52:01.900 eating, there's a wide variation in the number of calories that it takes to feel satisfied at a meal,

01:52:11.100 depending on what foods you're eating. A typical person sits down and eats food until they feel satisfied,

01:52:18.860 and then they stop eating. That is the intuitive, typical, natural, easy way of interacting with

01:52:25.900 food. But depending on what's on your plate, that point can be reached with vastly different numbers

01:52:31.580 of calories. Is the proximate sign of satiation more a gastric distension function in that immediate

01:52:38.540 cessation mode? I can say that it's important. But if I were to like assign what percentage of the

01:52:45.500 effect is attributable to that, I don't know what percentage I would put on it. Like, is that more

01:52:52.300 than 50%? It's a very complex system. The brain is receiving a lot of signals. Some of them are stomach

01:52:59.100 distension. Some of them are signals from the small intestine about what the nutrient composition is.

01:53:04.780 Some of them are simply or a sensory detection of food properties and stimulating your brain knows,

01:53:13.980 based on the sensory properties, what the nutritional composition of the food is based on prior experience

01:53:19.500 that it has stored. So there's a lot of stuff going on that contributes to ultimately that sensation of

01:53:27.420 satiation would be the proper term for it. And satisfaction that causes us to end meal. Certainly,

01:53:35.100 stomach distension is a biggie. So that relates to calorie density, which is an important determinant of

01:53:40.780 the satiating and satiety promoting properties of food. So in other words, how many calories are there per

01:53:49.100 gram or per volume of this food? If you have a food that has more volume per calories,

01:53:55.340 fills up your stomach more, it stimulates those stretch receptors more that goes up to your brain

01:54:01.260 stem. And that's a signal that opposes further food intake. Protein, so more protein is more 0.98

01:54:09.340 satiating per calorie. Palatability, the better something tastes, the less it fills you up per calorie.

01:54:16.300 And I'm actually not sure how to disentangle that from calorie density. Like what's the independent

01:54:24.220 variable there? And what's the dependent variable? Or is it some of both? I don't know the answer to

01:54:29.420 that, but they're both strongly correlated with lower satiety. I've also seen these experiments

01:54:35.180 where people are drinking from a bowl or a cup and it's being refilled constantly versus one where it just

01:54:41.500 kind of runs out. I mean, what are the differences in how much people consume based on, I noticed this

01:54:46.780 in myself, I put a little too much in the bowl, but I eat it anyway. Cause it's like, oh, I got to

01:54:51.740 finish this thing. And if I had finished it 10 bites earlier, I would have been totally happy.

01:54:56.460 Does that type of behavior factor in the long tail here, or is that just an acute thing that is sort

01:55:01.580 of irrelevant in terms of optimal weight maintenance?

01:55:04.140 I think it's very plausible, but the problem is that stuff comes from Brian Wansink. And so

01:55:09.900 it pretty much got blown up. He was the guy at Cornell that, did he falsify a bunch of data or

01:55:15.020 something? I don't think there is clear evidence that he falsified, but he P hacked a lot of it

01:55:21.180 pretty badly, I think. Oh yeah, really badly. And there are some data where it's not clear where

01:55:27.820 they came from and they're very implausible. I don't know how strong the evidence is that there was

01:55:32.940 actual fabrication. I think there may have been some evidence of that. I don't know where that

01:55:37.260 landed, but basically there were a bunch of problems and yeah, he got blown up. I would say

01:55:42.140 that anything that has his name on it at this point is pretty suspect. The refilling soup bowls

01:55:48.140 was one of his classic experiments. I'm just going to disclose that I did cite one of his studies in my

01:55:53.980 book. So I wasn't immune from getting taken in by some of this stuff. Going back to this energy

01:55:59.900 balance model versus the carbohydrate insulin model. One of the arguments in favor of the

01:56:03.900 carbohydrate insulin model is other examples of growth that are regulated from the hormones out to

01:56:11.900 the intake of energy. And I was thinking about this the other day because I measure my kids. I have

01:56:19.340 three kids and every three months each of them gets a little tick on their closet door. Anybody listening

01:56:25.660 to this who measures their kids at regular intervals? I don't know why I picked three months, but four

01:56:30.220 times a year. The non-linearity of this is unbelievable. They'll go little, little, jump,

01:56:37.100 jump, slow down, jump. It's pretty intense. And that growth correlates with how much they seem to eat

01:56:43.820 during that interval period. Like right now, my youngest, who's not yet five, I think he eats more

01:56:50.220 than the other two combined. And I'm probably not being facetious. He goes to a preschool or a pre-K

01:56:56.620 where they give them breakfast there. He eats two breakfasts at home. Then he goes there and still

01:57:01.980 eats more than all the other kids. I mean, the kid's just an eating machine and he's growing commensurate

01:57:07.900 with that. I think most people would agree. He's not growing because of how much he's eating. He's eating

01:57:13.820 that much because of how much he's growing. So he's responding to growth hormone and all these other

01:57:18.620 things. And I think that's basically the central thrust of this carbohydrate insulin model, right?

01:57:24.220 Which is whether it be sleep disturbances that increase or decrease insulin signaling or foods

01:57:31.740 that stimulate insulin, they're driving that hormonal environment that is driving the increase in food

01:57:39.500 intake. But I think experimentally, what can we say about the differences in these models?

01:57:47.020 Experimentally, you have to think about this in terms of animals and humans.

01:57:51.500 It seems to me that the balance of experimental data would suggest the energy balance model is

01:57:56.860 easier to explain. Would you agree with that? I think so. Although I do want to acknowledge

01:58:02.700 the fact that they're not mutually exclusive. So it has not been ruled out that there could be

01:58:08.140 a contribution from that type of a model. Why is this so important? Is it so important? Is it

01:58:15.420 important to understand this? I suppose the implications have to come down to how we treat the condition?

01:58:22.220 It is important in the sense that if you understand the mechanism of something, it makes it easier to

01:58:29.820 address. If you look at the history of obesity drugs, weight loss drugs, I should say, most of them were

01:58:37.900 discovered in entirely haphazard ways. Dianitrophenol was a high explosive that was used in World War I and

01:58:46.940 somebody figured out if you take it, it makes you lose weight. And it does so by increasing your energy

01:58:52.940 expenditure. So some people manage to cook themselves literally from the inside out. And then you look at

01:59:00.620 other drugs and most of them are psychiatric drugs. They're just repurposed psychiatric drugs

01:59:06.380 that just happen to cause weight loss. Some psychiatric drugs cause weight gain, some cause

01:59:11.020 weight loss. And the ones that cause weight loss, we just said, hey, can we repurpose these? Can we combine

01:59:16.620 them to accentuate the effect? That was kind of most of the history of weight loss drugs. And now for the first

01:59:24.780 time, we have drugs that are safe and effective, FDA approved, I should say we have a drug,

01:59:33.500 Weigavi, aka semaglutide, that is safe and effective and was developed for this purpose based on mechanism

01:59:41.660 from the bottom up. So it wasn't just a haphazard discovery. So we are in a new era now where we are

01:59:49.980 actually designing weight loss drugs based on mechanism, based on an understanding of the

01:59:56.380 biological mechanisms of regulation. Because we're out of the haphazard era and into a more targeted,

02:00:06.060 refined era, we're in a place where it becomes really important to understand mechanism. And, you know,

02:00:11.020 in cardiovascular medicine, I'm sure you recognize this, there are incredible insights that have been coming

02:00:17.500 out of the genetics that have resulted in therapies like the PCSK9 inhibitors. Thank you. I always mix the

02:00:23.420 letters up. That's a great example of it where we first understood the biology and then we came out with

02:00:29.020 the therapy and it works awesome. I think that's the era we are getting into now with obesity. So I think it

02:00:36.300 actually is really important to understand the mechanism. My prediction is over time, these models will

02:00:41.660 have more and more in common. One of the arguments against at least the way the carbohydrate insulin

02:00:48.940 model is typically played out is actually given by semaglutide, which raises insulin in the short

02:00:53.980 run. One of the things we always see when we put patients on this drug is they're going to lose a ton

02:00:59.900 of weight and their insulin levels go up slightly. Now, this tends to resolve over time. Over a long

02:01:04.940 enough period of time, we tend to see insulin come down. But in the short run, for about three months,

02:01:08.300 we see elevations in insulin. And we also know that it's increasing insulin sensitivity. So they're

02:01:16.080 getting really the double effect. But it's hard to reconcile that with a model that would state

02:01:23.380 insulin must go down for weight to go down, for fat to go down. I think that model is just not even

02:01:31.620 plausible at this point. If you want to say, is it a factor? I think that's still in play. But to say

02:01:37.140 this is the determinant, I just don't even think that's plausible at this point, this class of drugs

02:01:42.880 was identified based on its ability to increase glucose-stimulated insulin secretion. That is what

02:01:51.480 GLP-1 does. It's an incretin hormone. So that was the original purpose and why it was used in type 2

02:01:58.460 diabetes management, because it gives people more insulin around meals when they really need it.

02:02:03.420 Because if you just inject insulin, that's a really kind of crude way to manage your blood

02:02:09.260 glucose. It's not time-specific. So GLP-1 gave it that much-needed time-specificity and also had some

02:02:16.300 other beneficial effects. And it was only after that that they figured out that it has this big

02:02:22.760 impact on food intake and body weight. Absolutely, I agree with that. There's just a lot of other

02:02:29.220 literature. I want to like throw the hypothesis of bone though. So if you look at genome-wide

02:02:35.620 association studies on body mass index, they're all about the brain, largely about the brain. If

02:02:42.040 you look at genome-wide association studies on body fat distribution, you're controlling for BMI and

02:02:48.580 you're saying, where is that fat on the body? Those have more of an insulin signal. So insulin pops up

02:02:55.900 pretty prominently in those. In other words, the distribution of fat on the body

02:03:01.480 where it is seems more related to insulin signaling. Correct. The total amount of fat on the body seems

02:03:07.860 more related to energy intake. If I remember what we talked about really at the beginning was it's not

02:03:13.280 just regulated by the brain. It's more on the intake side of the equation. Even to add a little bit of

02:03:18.420 extra nuance on top of that is we're really talking about body mass index. If you consider this idea of

02:03:25.600 energy partitioning, which the carbohydrate insulin model is all about, there could be some of that

02:03:32.020 flying under the radar of body mass index. I don't think the door is closed to that. And the fact that

02:03:37.760 it's showing up in body fat distribution, and now David Ludwig is publishing studies suggesting that

02:03:45.140 there could be correlations between baseline insulin secretion and how much, what proportion of fat loss

02:03:53.120 is lost as fat versus lean tissue, there's a world in which there could be some energy partitioning

02:04:01.280 effect. I just don't think it explains obesity, because obesity is not just energy partitioning.

02:04:07.860 You have a bigger body, you're eating more energy, you're burning more energy, you have more lean mass,

02:04:13.820 more fat. That phenotype is not explained by energy partitioning. But could there be some subtle

02:04:20.960 energy partitioning phenotype that is operating also? Maybe. So that's kind of like my view of how

02:04:29.900 there could be a way that this has validity. And you said something earlier about the more

02:04:36.020 you restrict carbohydrate or the more you restrict fat, typically the more weight you're going to lose.

02:04:41.300 The sweet spot, if you want to gain weight, is to have lots of both of them. How much of that do you

02:04:46.120 think comes down to the hedonic component of how good ice cream tastes? The ubiquity of food choices?

02:04:53.720 Or do you think there's something very unique physiologically going on? You know, you've

02:04:58.180 probably heard of the potato diet. All these diets just sound so stupid. But if you talk to somebody who 1.00

02:05:03.440 just mainlines potatoes all day, they lose weight like crazy. This has been shown really clearly in

02:05:09.320 animal models, which have the advantage of you can get really tight control for a large proportion of the

02:05:14.900 animals' lifespan. John Speakman published a study that is the best one that's been done in animals,

02:05:21.840 where 29 different diets, I believe, and five different strains of mice, they systematically

02:05:27.680 varied the carbohydrate to fat ratio in the diet. And they said, how does that interact with body

02:05:34.320 fatness? And what they saw was, if you start with animals that are on a low-fat, high-carbohydrate

02:05:40.740 diet, and you start replacing that carb with fat, they get fatter and fatter and fatter and fatter and

02:05:45.400 fatter until you hit about 60%. And then you keep increasing the fat and decreasing the carbohydrate,

02:05:53.140 they get slimmer again. And there are studies published, mice lose weight on a ketogenic diet,

02:05:58.900 just like humans do. You can put mice on the diet, you can put rats on the diet, they lose weight.

02:06:03.480 So it's really in the middle that the problem is. Which is ironic, because that's where the standard

02:06:08.920 American diet is. If you just walk into the grocery store and just eat without any filtering,

02:06:14.280 you will eat that wrong combination of fat and carbohydrate. Exactly. And if you look anywhere in

02:06:20.260 the world where people are rich enough and industrialized enough to eat whatever they want,

02:06:25.640 that's generally what you're going to see. At least after a couple decades of cultural adaptation,

02:06:31.400 you're going to see pretty equal proportions of fat and carbohydrate. That's what you see in most

02:06:35.640 parts of the world. So why is that? Well, I think there are some hypotheses that can be considered.

02:06:43.360 And let me just be clear here that this is speculative. So I don't want to present this as

02:06:47.600 the answer. Because I don't think we really know. I think this is primarily an empirical observation

02:06:53.860 that we're trying to explain. But some explanations, you could say maybe it's a physiological effect.

02:07:00.360 So if you're not eating much carbohydrate, your body has to work a little bit harder to synthesize

02:07:08.100 glucose, for example. So there are some physiological ways in which you're increasing the demands a

02:07:13.920 little bit, metabolic demands. Same with very low fat diets, you're slightly increasing metabolic demand.

02:07:22.600 You're going to synthesize more fatty acids. But I don't know. I don't think that's a great explanation,

02:07:27.700 because those metabolic demands are very small.

02:07:31.880 In Speakman's experiments, these were all ad libitum, I assume.

02:07:35.440 Yes.

02:07:35.860 Were they also significantly eating less at the extremes in terms of total energy intake? And

02:07:40.520 were they controlled for protein?

02:07:42.020 I think the answer is yes to both of those, if I'm recalling correctly. I do want to put a little

02:07:47.540 asterisk on that, that sometimes there is not a perfectly tight correlation in rodent studies

02:07:53.140 between energy intake and fat gain. So you can get some results where it's not fully explained

02:07:59.860 by that, or in some cases, not explained at all. Yeah, where was I? What was I saying?

02:08:06.140 Well, I think we're still trying to reconcile why, at the extremes, is it all being driven by less

02:08:12.920 intake? Or is there some increased metabolic cost of living at the extremes?

02:08:17.320 So the physiology would be one, and then the other would be just the neurobiology and the food intake.

02:08:25.840 And I think that's the most satisfying explanation we have right now, is that it is simply more

02:08:31.040 appealing to eat food, more motivating to eat food that has both carbohydrate and fat. I'm not saying I

02:08:39.820 have strong evidence that that's the explanation, but that's kind of the only thing I can think of

02:08:44.960 that explains it. I mean, why else? The metabolic cost of being at the extremes should be pretty

02:08:51.240 modest. It can't explain effects of hundreds of calories a day, which is what's observed when you

02:08:58.040 put people on a very low-fat or a very low-carb diet. Their energy intake declines by hundreds of

02:09:03.500 calories a day right away, automatically. That's the only thing I can think of, is that essentially

02:09:09.980 the food has less implicit value to reward regions of the brain because of how our motivation is

02:09:19.180 determined for certain types of food properties. The food is intrinsically less motivating, and so

02:09:25.540 we eat less of it. That's my best guess as to the main reason.

02:09:31.140 It's not very difficult to take your carbohydrate intake down to 5% to 7%. Like a ketogenic diet will do

02:09:39.200 that, and it's a pretty easy diet to adhere to, especially today. Harder 10 years ago when there

02:09:44.880 were fewer food choices geared towards it, but I'm not necessarily saying it's an overly pleasant diet,

02:09:50.100 but it's not difficult. You don't have to put a huge amount of effort to eat 5% of your calories

02:09:54.820 and carbohydrates today. I don't even know how one would go about getting only 5% of their calories

02:09:59.600 from fat. That is a much harder thing to do, is it not?

02:10:03.660 Yeah, I think it would be very difficult to get that low. When you look at studies that test low-fat

02:10:12.660 diets, some of the lowest fat diets I've seen were in the kind of 10% fat range. I mean, even foods like

02:10:22.040 whole wheat and corn have a fair amount of fat in them. Not a lot of fat, but I don't remember exactly

02:10:29.860 what it is, but not far off from 10% just from those foods that we would call starch foods.

02:10:36.040 So I think it is quite challenging to get that low in fat. You can do it with more refined diets,

02:10:44.060 like semi-purified diets. It's not so hard to do that in rodent studies, but to design a diet that

02:10:51.200 someone will actually eat as a human in a randomized controlled trial or something at that level of

02:10:57.200 fat intake, I think is pretty challenging. And even 15% is not easy. You're really working hard

02:11:03.720 to do it. And I'm not convinced that there are great health benefits to that either. Probably

02:11:08.380 better than being in the messy middle, but it's pretty hard to do. Last thing I wanted to ask you

02:11:13.060 about was Red Pen Reviews. So tell folks a little bit about how long you've been doing that and

02:11:16.660 what's the frequency with which you guys put these reviews out?

02:11:19.500 Red Pen Reviews is a 501c3 nonprofit that publishes the most informative, consistent,

02:11:27.360 and unbiased reviews of popular nutrition books available. And the thing that really makes us

02:11:33.440 unique is that we have developed this semi-quantitative review method, structured review method,

02:11:40.920 that we apply to each book that yields numerical scores for scientific accuracy, reference accuracy,

02:11:49.480 and healthfulness. What this does is it allows us to apply the same rigorous method to all books,

02:11:57.060 such that you know where the numbers are coming from, and you can compare in an apples to apples

02:12:03.140 way between different books. So you could say, I want to know the best book on topic X, and you can

02:12:10.600 literally compare the scores of two books, apples to apples, and choose the one that has the highest,

02:12:16.740 let's say, scientific accuracy. This is a pretty labor-intensive process. So how many do you bang

02:12:21.680 out in a year? It takes us about 40 to 100 hours per book. We've been operating since 2019,

02:12:29.940 and we have 14 reviews. I will say that our pace was quite slow last year due to COVID-related time

02:12:39.120 challenges. We're on target to have probably six to eight reviews published this year. We have some

02:12:47.880 things going on behind the scenes that could potentially greatly accelerate that pace. We're

02:12:53.400 seeking funding. How many folks do you have that review the books? We have a total of, I believe,

02:12:59.480 eight reviewers right now. So each reviewer might do one a year on average? On average, yeah. But the way it

02:13:05.320 turns out is that some people do the majority of reviews, and then other people only rarely do a

02:13:10.800 review. And how do you guys select books for review? We are trying to maximize our impact on public

02:13:18.120 health knowledge and public health. So we really try to pick the books that are most impactful right

02:13:23.840 now. So we're looking for books that are selling the most. We're looking for books that are having the

02:13:28.540 most social media engagement. We're looking for books from authors that are particularly influential.

02:13:33.520 We're really trying to give people information about the things that they are already interested

02:13:41.800 in. So what are some of the recent ones that you guys have published? Which books? Obviously,

02:13:46.760 we talked about The Carnivore Code as one of them. That's one of the recent ones. The most recent one we

02:13:52.440 did was The Volumetrics Diet, Ultimate Volumetrics Diet by Barbara Rolls. Before that, we did The

02:14:00.000 Carnivore Code. I was the primary reviewer on that. We have a primary reviewer and a peer reviewer.

02:14:07.060 Before that, Eat, Drink, and Be Healthy by Walter Willett. Before that, Eat Fat, Get Thin by Mark

02:14:13.520 Hyman. So that's a taste of some of the ones that we've been doing. Given that you've been doing this

02:14:19.720 for three years now, anything surprised you so far? Were there any that you went in thinking,

02:14:24.280 yeah, this seems like it's going to be a pretty good book? And you came away thinking, no,

02:14:27.640 they really didn't get this right? And vice versa, where you went into it thinking this is going to

02:14:31.140 be nonsense. And you came out thinking, actually, they've changed my view on something.

02:14:34.380 One of the things that has really come into focus through the course of this process is that

02:14:42.240 credentials are not a reliable correlate of information quality. So there are people

02:14:49.560 that have MDs like David Perlmutter. He's a board-certified neurologist. And his book,

02:14:59.000 Grain Brain, got the lowest scientific accuracy score of any book we've reviewed. I'm not trying

02:15:04.440 to pick on anybody in particular, but that's just an example of the credentials not lining up with

02:15:10.340 the scientific accuracy. And we've seen that in many cases. Probably there is some correlation there.

02:15:16.620 So I think credentials, they're not completely meaningless. But once you get into people who

02:15:23.100 are highly credentialed, it's just highly variable. Some of their books do really well. Some of their

02:15:28.320 books do really poorly. That's been somewhat of a surprise to me. I think most people who are educated

02:15:35.320 in the sphere know that there's a lot of low-quality information in the sphere, right? But you can't help

02:15:41.560 be shocked sometimes at just how bad the situation is. We know like in science, there's a replicability

02:15:47.660 crisis. So scientists are not infallible. There's problems like this, even in this peer-reviewed

02:15:54.000 literature. But once you get outside of the sphere where there's accountability and you're in the public

02:16:00.540 sphere where there's very little accountability, it's like a free-for-all. And many people, even those

02:16:06.720 who are well-credentialed, share information that is very low quality. Most people have very little

02:16:13.720 ability to detect it. And even somebody like me, who I consider myself knowledgeable, at least in

02:16:19.820 some areas, I can get taken in too. I might read a book and it seems compelling. I'll tell you the

02:16:25.600 carnivore code. It did worse than I expected. As I was reading it, there were parts where I was like,

02:16:31.300 hmm, interesting. I'm going to look into this. This is kind of making sense to me.

02:16:34.340 And it wasn't until I started checking the citations and doing scientific literature

02:16:39.020 searches where I was just, this is not the best interpretation that an unbiased person would come

02:16:44.700 to looking at this body of evidence. There have been many surprises and most of them were updates

02:16:50.000 in the direction of thinking that the state of popular nutrition books is actually even worse than

02:16:56.520 I thought. I'm in the process of trying to finish my book. And one of the things that is so daunting

02:17:02.620 is the fact checking process. And I don't know what an author relies on because I could certainly

02:17:09.580 never rely on my publisher to fact check my book. It's too technical. They don't have people with the

02:17:15.820 knowledge to do the fact check. So I have to have analysts who work for me fact check, but they have

02:17:23.140 to be analysts who had no help in doing the research for the book because you have to get fresh eyes on it.

02:17:29.720 So I think that means my book will come out more accurate than it probably would otherwise. And yet

02:17:35.720 that's very difficult. I just know there's going to be something we get wrong. We're going to either

02:17:40.800 incorrectly cite something or we're going to have misinterpreted it or something like that. And I

02:17:45.760 feel like we're in as good a position as almost anybody can be given the size of our team. And yet

02:17:51.560 it's still very daunting. There's something about a book that is daunting in the sense that you know

02:17:56.280 this, you've written a book from the time you put your last, last, last edit into a book until it

02:18:00.720 hits the shelves is about eight months. Something's going to change in those eight months. So even if

02:18:04.980 it was perfect, the day you finished it, which I think is impossible. Eight months later, it's not

02:18:10.920 let alone two years later, every book's going to have mistakes. But the process that you described

02:18:17.220 is, I guarantee, far more rigorous than most books that are being published in this sphere.

02:18:25.920 And as you said, publishers do not impose a filter on the contents of these books, very little of one.

02:18:33.980 They just simply do not view it as their job to police the claims of authors. So if somebody comes in

02:18:40.160 with an MD, for example, their position is, and this is literally what my publisher told me, they're

02:18:45.900 like, you're the expert. We're not experts. We are not here to check your work. So for me, my process was

02:18:55.440 I sent each chapter out to experts in the field and had them look at it. Does that mean my book has no

02:19:03.860 mistakes? Absolutely not. I've been cataloging my mistakes on my mistakes page on my website, the ones that I

02:19:10.860 know about.

02:19:11.760 I think that's inevitable. And I've sort of accepted the fact that that's going to be the only way I'll sleep at

02:19:16.360 night is just acknowledging 5% of this stuff is going to be wrong. Let's collectively figure out what it is. And

02:19:22.700 let's create a repository where we can put the updates.

02:19:26.160 I think that's absolutely the best attitude, because not only is that a truth seeking attitude, but you are putting

02:19:33.020 yourself in a position where you're not presenting yourself as someone who has to be right to be

02:19:39.640 rational. You're presenting yourself as someone who's trying to get towards the truth, and your audience

02:19:45.040 can help you and help all together to get closer to the truth. And that's kind of the attitude that I

02:19:50.780 like to cultivate as well. One thing I want to mention in this context is that the method that we developed

02:19:57.080 for red pen reviews is available on our website for authors to see. And part of the reason why we do

02:20:05.160 that is because we're trying to help authors write better books. We do random citation checks. That's

02:20:11.300 one aspect of it. We have certain criteria for helpfulness. We have certain criteria for scientific

02:20:16.920 accuracy. And it can't be gamed. I don't think our method can be gamed. If you look at our criteria,

02:20:23.840 and you write a book that you think would score well, that's going to be a good book from an

02:20:28.740 evidence standpoint. I don't think it can be gamed. When I think about me and my book, which came prior

02:20:34.760 to red pen reviews, I would have loved to have this resource. If I had had it, I would have written

02:20:40.080 a book with higher evidence quality. Just like knowing that there's accountability and having a method that

02:20:47.380 helps you turn that into something concrete to improve what you're doing. I like to view

02:20:54.040 our organization as not just being finger wagging at people who make mistakes, also providing a

02:21:00.860 resource to help the information quality be good from the beginning. Are the reviews available to

02:21:07.780 everyone or only to donors? They are freely available to anyone. Awesome. We love receiving donations,

02:21:14.680 but access to our resources does not depend on that. Well, Stefan, this has been super interesting.

02:21:22.320 I always enjoy interacting with you and talking about all of these things. It is kind of amazing

02:21:27.580 how much we still don't know about something that is so ubiquitous and so important. But I also get the

02:21:34.180 sense we're kind of converging. And I do think that these good faith debates that exist between people

02:21:39.500 like you, Kevin, David Ludwig, I think they're really good for the field because I think it's

02:21:46.500 forcing people to be sharper in their thinking. And ultimately, I think getting us closer to

02:21:52.120 theories that are aligning better with experimental evidence. I know my thinking on this has changed

02:21:57.520 quite a bit. And I certainly find now the balance of the evidence more on the energy balance side of

02:22:05.820 the equation. But I constantly enjoy just trying to understand both sides of this. It's very

02:22:11.660 complicated. Again, suggesting that there's more overlap than we probably appreciate.

02:22:16.580 I appreciate you having me on. It was fun to discuss all this stuff.

02:22:20.020 Thanks, Stefan.

02:22:20.900 Thank you.

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02:24:53.280 Thank you for listening.

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The Peter Attia Drive - June 27, 2022

#212 - The neuroscience of obesity ｜ Stephan Guyenet, Ph.D.

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