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Obesity Epidemic, Diet, Metabolism, Saturated Fat vs. PUFAs, Energy Expenditure, Weight Gain

Updated: Jan 3


Full auto-generated transcript below. Beware of typos & mistranslations!

Nick Jikomes

Where are you calling in from?


John Speakman 4:55

So I'm calling in from Shenzhen in China, which is So people don't know, locations in China, finance on the mainland on the opposite side of the bay from Hong Kong. So it's way down in the south.


Nick Jikomes 5:10

And can you give people a little bit of background in terms of what kind of scientist you are and what your research interests are? Yeah,


John Speakman 5:18

sure. So I started my career as a basic biologist, sort of evolutionary econ physiologist. So I did a lot of work. Looking at the way animals respond to their environment, how they manage their energy, or their store energy, these these sorts of things. So it became clear that I probably wasn't going to be able to raise enough research funding to keep those things going. But understanding energy balance and physiology of energy balance has two big implications. One is aging research. And the other one is obesity research. And so I started to sort of actively pursue those things, and ended up working on both of them to some extent, and eventually evolved into working not only on laboratory animals, which are extremely convenient for studying these things, but also know doing studies on humans. So I've come along this sort of very long path. It's also been a pretty interesting path. Because I am from the UK Originally, I'm from Manchester. And after my, I did my PhD, and Scotland, and after my PhD, I went to do a postdoc at the University of Aberdeen, that postdoc led into a faculty position. So I then started just going up the ranks in a faculty position, you know, like to a senior lecturer, professor. And then, about 1213 years ago, I had this big dramatic change in my life that we decided we would open an extra lab in China. And so I then moved to Beijing with my wife and one of my kids, and we spent 10 years in Beijing, mostly doing work on on obesity, but still having the lab running in Aberdeen, keeping the aging work going. And then during the pandemic in 2020, I moved from Beijing, down to Shenzhen. And so I'm actually, I'm actually spread about all over the place at the moment, because we we still have a few people still in Beijing. And I still have the lab running in Aberdeen and my main bases here in Xinjiang.


Nick Jikomes 7:58

And in China, is there an increase in obesity, similar to the way the patterns that we've seen in the US in the Western world, or are things very different over there in terms of those things.


John Speakman 8:10

So China's probably about 50 years behind the US in terms of the numbers of obese people, but it's very, there are two big differences between obesity in China, and there'll be stay in the US. So the first big differences, it's principally an issue in males, rather than in both sexes. So Chinese women tend to be extremely culturally resistant to putting on weight and that maybe just a social pressure type thing. But they don't, you don't get enormously large women in China. And the other thing is, it's spatially also very different. So the east coast of China, which is where most of the economic development has happened, has a much bigger problem with overweight and obesity, then the western provinces, which are more rural, they're also in they're also at higher altitude, and there is a link between altitudes and obesity in the US. So whether it's a cultural difference or a development difference, or an altitude difference, it's not really clear, but there is this large difference between the East Coast and the western provinces. Yeah,


Nick Jikomes 9:34

my understanding of the obesity epidemic in the US in the West is that one of the features that has is, you know, people generally cite the late 70s, early 80s as being about the time that that got started. But basically, it was indiscriminate. You saw it and males and females young and old, rich and poor. To what extent is that true? And what are some of these demographic differences? Maybe start to tell us about out where we should be looking in terms of causes.


John Speakman 10:03

Yeah, so that's, that's pretty interesting. So one of the sort of rationales for the work I'm doing is, I mean, which we're still at a very early phase of the epidemic here in China. And also, if you look at other Asian countries as well, they're also very early in the epidemic, there's not much obesity. It's increasing in India, but it's not anywhere near in the US and Southeast Asia is still almost completely protected. So what are the sort of rationales is that if we can work out what what causes things in the US, then we may have a chance of preventing those things happening in Asia and Southeast Asia. So here, it seems, though, that the patterns that are developing are very different than what happened in the US. So we do have these regional differences. We have these big sex differences. But on the other hand, there also seem to be some genetic, physiological differences, that the translation from obesity to diabetes seems to occur much lower BMI is in ancient populations. And so although they have a much lower obesity problem, the diabetes problem in China is about the same kind of manga, the same percent of the population have diabetes in China as they do in the US. And so that's also a kind of confusing, but extremely interesting observation.


Nick Jikomes 11:29

And you mentioned that interesting sex difference in terms of obesity rates between men and women in China. Are there any indications as to what may be driving that are women in China generally trying very hard to stay physically active? Are they trying very hard not to eat certain foods or anything like that?


John Speakman 11:48

I think there's a big social pressure not to become obese and women in China. And I think that manifests itself in various ways that they fly in, prevent weight gain, both by eating less, and potentially exercising more, although I personally think exercising more, it's not likely to be a successful strategy. But it certainly seems to work. I mean, there is a big difference. There are big social differences between females and males in China. So if you look at smoking rates, for example, the average smoking rate in China is about 25%. But in women, it's 2%. And it managed 51%. So there, there are enormous cultural differences and social differences between what men and women do in China that are not reflected in what goes on in the West. So I think it's not, it's not surprising that there are big sex differences in obesity rates.


Nick Jikomes 12:48

Yeah, we'll circle back to your comment on, you know, the role of physical activity and all this. But I want to set up some of the work that you've done recently. First, I just want to discuss obesity as an epidemic a little bit more. When we think about the causes here, there's obviously going to be multiple factors at play. But generally, you hear you know, the thing you probably hear about most is, well, it's about caloric intake, because food is very plentiful. We've created and engineered many, many highly palatable, highly calorically dense foods. And we're simply eating more of these things. And that's, you know, if not the biggest driver, certainly a big driver of this. But another factor here is just just total energy expenditure. And that can come from both deciding to go do things like exercise, it could also come from changes in basal energy expenditure. And so can you unpack those concepts and maybe talk a little bit about sort of the major schools of thought that have gone into thinking about the obesity epidemic, thus far over the past few decades?


John Speakman 13:55

So, I recently went to India, and when I arrived in India, I was questioned by the guy at the immigration. So he's sitting behind the immigration desk, and he says to me, you know, why, why are you here in India? And I said, I'm giving a talk at a conference. So he said, What, what's it about? So I said, it's about obesity. And he said, it takes a size. That's what it is. It's reductions in physical activity. That's what the cause is. And he could see I kind of like Drew breath ready to sort of say, well, I don't think it is exercise that's supposed to get ugly, he immediately jumped at it, and fast food as well. So I think most most people are pretty convinced that it's, it's both sides of the energy balance equation that have been impacted over time. And I think if you speak to anybody who's who's not an expert in the field, that would be the kind of view that it's a combination of changes in the food that we have available. That prompted us to eat more food and changes in our behavior and particularly our physical activity that have reduced our total energy expenditure. So until recently, those were really the two major ideas. And I think for most people, those probably still are the two major ideas about what's happened. And, you know, I mean, if you're online, you see a lot of stuff that people saying It's blindingly obvious, you know, what, what's going on? Why do we need to study this this anymore? So about 25 years ago, we decided to try and put some actual data on top of some of those ideas. So I, my interest is in measuring energy expenditure. And one problem is to measure energy expenditure of people screen living, you know, so So what we're really interested in is not the energy expenditure of somebody lying on a bed, whether a metabolic occurred on their head, we want to know what what's the cost of going about your daily life, because that's what people hypothesize has changed. And in the 1980s, sleep like teenagers, early 90s 1990s, I was involved in development of a method, I didn't invent the method, but I was involved in refining the method for measuring people's energy expenditure when they're free living, so that you would think on the face of it that that's actually really difficult to do, because the way that it's normally done is you wear a mask or something like that, but over over your face, that collects the gases that you're taking in and breathing out. And we measure from the differences in those gases, how much oxygen you consume, and how much co2 You produce. And from those two, we can work out how much energy you're burning. Now, obviously, if you're, you know, if you want to measure your energy expenditure of daily life, wearing a mask on your face is gonna restrict to a large extent, most of the things that you want to do. So we need another approach to it. And there was this really smart guy in the 1950s, called Nathan Lipson at the University of Minnesota. And he came up with this idea that he made this preliminary, well, not preliminary primary observation that the isotopes in carbon dioxide are in equilibrium with the isotopes in water. So what that means is, if I, let's say, I gave you an isotope of oxygen, oxygen, 17, or oxygen 18, and I put that into the water in your body, because of these exchange reactions that happen that oxygen would also called in to the co2 in your body. And so he came up with this idea that if you did that, if you if you got somebody to drink water with heavy oxygen, and then you could measure then the co2 production because you would be able to work out from the reduction in that oxygen 18, how much was getting lost through the co2. But there's a problem because the label the isotopic label is not only getting washed out to the body by the co2, but it's also lost every time you lose some water. And so it's not possible just putting in oxygen 18 or oxygen 17 to work out what your co2 production is. But the really smart idea was well, okay, that water is also tracked by hydrogen. So maybe if we put in a label of hydrogen at the same time, we can use the difference in the elimination of the two isotopes to estimate what the co2 production is. And he did some preliminary experiment with mice very small sample sizes. And the reason that it was a problem doing these experiments. The idea was fantastic, but the isotopes were super expensive. And so he had to beg isotopes from Los Alamos in California to get enough phaser job to just do one experiment or one mouse and show like proof of principle that it would work in 1955. That was and then he published another couple of papers later, but it never went anywhere, just because it was too expensive a technique and actually he published a paper in the early 70s, saying that this would never ever be used on humans because said cost about 10 to $15,000 per person to make a measurement and he couldn't imagine any problem in 1970 That would be worth spending. $15,000 per person. And he's probably correct. I mean, we probably still wouldn't use the technique if it cost $15,000 per person, but the refinements that were made in the 1980s, and 1990s, brought that price down and diamond died. And so now it's possible to do that, for about $900 per person, it depends on the exact protocol that you use, but you can use that technique. And there is actually a company that does it commercially. Now. So if you want to measure your own energy expenditure, you can vote for this company, and they will provide you the isotopes if you drink them, you provide a urine sample. So the beauty of this technique is that after you drink the isotopes, you take an initial sample after they've spread into your body, and but three or four hours, and then you go about your daily life, you just do what you're doing. And then 14 days later, you take another sample, and the divergence of the isotopes tells you how much energy you've spent during that time period. So this is very long way round, to answering your question. But in the sort of early 2000s, around about 2005, we were beaten in larger studies by that, that did use this technique. And so I had a colleague in the Netherlands class visitor, and I said to class, you know, look, you've probably done enough studies on humans that we could go to all your studies, and just pull out all control groups, and look at the decline in energy expenditure over time, because, you know, there is objective evidence that physical activity has declined over time. So we just wanted to translate that into a number and say, has the decline in physical activity been enough to give us enough of a change in energy expenditure? That that could be an important causal factor? And how important is it relative to food intake. So that was the motivation for our initial thoughts on it. And so I went to classes lab for a couple of weeks, and we pulled out all these control studies. And what we found completely to our surprise, was there was absolutely no relationship whatsoever. So if you look between 1990 and 2005, there was no change in energy expenditure whatsoever, and the total energy expenditure, and that and that was just a real shot. Because everybody expected physical activity levels have gone down. There is some data showing late work time and physical activity has declined over time. So it was just like a real shocking results, you know, and I think a lot of people just didn't believe it, you know, they just thought, Well, okay. It's one city in the Netherlands, where there's not enormous levels of obesity, or maybe it's just, you know, it's just an anomaly and it's not.


So weighing forward a bit. And roundabout, maybe about eight years ago, nine years ago, all the people that use it, there's not many people can use this techniques, probably about 10 people in the whole world run labs that can can use this method. And we all happen to be at a conference in Japan. And we were sitting around afterwards, in a solid q&a session that somebody in the audience said, why don't you guys get all your data together and produce a big database. And after the meeting, we were sitting around in the bar, and we said, Actually, that's a really good idea, we should do that. And so we went away. And we were fairly rubbish and naive about how to build databases. And so we had a couple of false starts. And it's really funny, because there's not things that you think about, but you know, things like, differences in the way that people write dates. Yeah. Yeah. Because of the enormous impact on one day, did you do it, you know, and so, you know, like, everybody from the US was using month day year, everybody else would use it? Well, China, they use year month day, Europe, they use day month. Yeah, you know, so. So that was causing all sorts of different issues. And there were lots of other things, you know, people expressing co2 production in liters per day, and some people using it in malls and, and things like that. So anyway, anyway, long story short, we finally got our act together. And we were able to pull together about 6000 data items. And so we thought, you know that that's a good sample, to actually now go in and look in more detail because this is a cross though the whole of the US and Europe so it's no longer restricted to just one city. It's a much bigger sample. And, you know, we can look for Those trends in energy expenditure. So


Nick Jikomes 25:03

so this database captures energy expenditure by using this doubly labeled water. Yes, right. Give me a clearer sense for how exactly is this doubly labeled water administered to people and and how do you measure how much they're drinking and stuff? Yeah,


John Speakman 25:17

so what happens is, you come into the lab, typically, you would have been fasted overnight. And what we do is we give you a glass of water to drink, so the water is enriched in oxygen, 18 and deuterium, these are stabilized stops completely safe, there's no risk that they already exist in your body at a baseline level. And all we're doing is pushing that baseline level up a little bit. So for example, in your body, at the moment, you have 2000 parts per million oxygen 18. When we do that technique, we push that up to about 2200. So there's no physiological impact, and there's no chemical impact of the dose that we give you. But it takes time for that dose to be absorbed by your gut and spread into the water in your body. And so we then wait for a period of about three to four hours. And after about two hours, we get you to urinate to get rid of anything that's in your bladder at that point. And then at about three to four hours, you take another urine sample, and normally take about five mils. But actually it only takes about 50 microliters to do the measurement. So then we take that sample. And Different people use different techniques. And some people just let people go and they come back 14 days later, we actually get people to take a sample every morning. So they take 14 samples through the time course but it's very non invasive, you know, you're just everybody sort of goes for a pee in the morning. So you just take a sample of your pee and put it in a tube. Most people are kind of happy putting it in the freezer, there are some people who are not so happy with doing that. But, you know, generally it's okay, we can get people who are keen on doing this. And then we fit curves to those isotope eliminations in order to estimate how quickly the deuterium and the oxygen plating are coming out. So it's not a an invasive technique in any way, shape, or form. I


Nick Jikomes 27:33

see. So based on how these isotopes are exchanged between water and carbon dioxide, based on how quickly the body so eliminating them, that's going to be it's going to give you a readout of what their total energy expenditure is.


John Speakman 27:48

That's right. That's right. So validation studies have been done by putting people into metabolic chambers for periods of about seven days, where we can actually measure the gas exchange. And then we can compare that directly to the measurements using the isotopes. And that those validation studies have been done continuously since the 1990s. So one interesting thing is that different people came up with different equations for how to calculate the energy expenditure. And those different equations were all in these different studies that were brought together. So one benefit of the database was that we were then able to recalculate everybody's energy expenditure using a single common equation. And we showed that that single equation performance best if you pulled together all the validation studies, so it was kind of nice thing to do pull in the database together, because it allowed us to harmonize a lot of things. And so now, everybody that uses that technique uses this new equation that we derived. So we don't have to sort of correct everything back to the sort of new equation. So we ended up with these six layers of measurements that go back to 1991. And come forward to about 2017, just before the pandemic. And we looked at what happened with energy expenditure. And actually, if you look at the data, if you just like throw the data on the page, then there's no relationship. There's no relationship between energy expenditure through time. But there's a problem. And the problem is that although we're randomly sampling people through time, of course, through time, people are getting bigger. So if you look at the average weight in 2017, it's quite a bit higher than the average weight in 1991. So not only did we have no relationship, we had no relationship but we had a problem because people were getting slightly heavier. And you would actually expect that their expenditure would be getting slightly higher because bigger people expend more energy than then lie to people. Is


Nick Jikomes 29:59

that isn't because they have to do more work to move their body around? No,


John Speakman 30:03

it's It's principally because they have more metabolizing tissue. So if you look at anybody in relationship to their body size, it's a positive positive relationship between the fat free mass and the total body weight. So when people deposit fat mass, they don't deposit only fat mass, they also deposit some lean tissue as well. And so the consequence, and it's the lean tissue where most of the metabolism is happening, there is some metabolism in the fat tissue as well. But the consequence is that if you look across a group of people that differ in their body weight, energy expenditure is higher in the people that are heavier. And so you have to take that away, so that through time, you're asking the question, if we took a person who was 70 kilos through that whole time period, how would their energy expenditure change rather than saying, okay, 1990, we've got a 70 kilogram person in 2017, we've got an 82 kilogram person. And when you do that, it turns out that there is a relationship, there's a negative relationship in both males and females in the adjusted energy expenditure. So that's the energy expenditure, taking away this change in body weight through time.


Nick Jikomes 31:21

I see So. So going back to the 80s, or 90s, forward until just a few years ago, by this measurement, you're saying that people the age adjusted, or excuse me, the weight adjusted energy expenditure has actually gone down? Yes.


John Speakman 31:37

And that contrasted what we found previously in my strength, where we found that it didn't matter, if you took the total energy expenditure, or you took the weight adjusted energy expenditure. You can do various other statistical tricks with the data, it didn't matter in that data. Well, how you did there, Ted was flat. Whereas in the new data, when you look at the large amount of the large amount of data that we have, there was a positive trend in body weight, so we had to remove that. And when you remove that there was a reduction in total energy expenditure. So the initial thought was, okay, well, that's it, you know, that's showing that there's a reduction in physical activity, energy expenditure. And so physical activity is probably a cause. But of course, total energy expenditure consists of several different things. And so it's not quite so easy to just to leap in and say, okay, the total has gone down, therefore, it must be the physical activity that's gone down. And so if you look at, okay, what you spend energy on what your total energy expenditure consists of consists of four things, one of which we generally ignore, which may or may not be an issue, but I'm just going to ignore it, because we always do. So that's the energy cost of thermal regulation. So generally, we assumed that individuals move around in habitats, and they change the places where they live, so that they don't have to pay energy costs of thermal regulation. So we have some evidence that that probably correct, at least in the US, because if you look at energy expenditure in relation to latitude, or differences between summer and winter, there's no, there's nothing. So people in Alaska spend about the same amount of energy as people in Louisiana. And it doesn't matter that Louisiana is 40 degrees warmer, so Centigrade. You know, so So basically, we modify our environment, we use air conditioning to cool ourselves down, we use heating to warm ourselves up. And the environment we're in is approximately constant. And so so there isn't a big thermal regulation effect. That may not be true outside the US, we only have data inside the US. But generally people ignore thermal regulation. And our data tends to suggest that it's an appropriate thing to do. So that leaves three things that are left. So the one is obviously physical activity. We spoke about that a bit so far. But there are two other things. One is called the thermic effect of food. And it has various other names like the heat increment of feeding or specific dynamic action, they're all basically the same thing. And that's the observation that if you eat some food, afterwards, there's a slight increase in your metabolic rate that lasts for a couple of hours and then subside. And so that works out to be around about 8% of the food that you eat. And it's it depends on the composition of the food. So if you've got more protein, you tend to burn off a little bit more. But we can subtract that off by saying well, okay, the total energy expenditure must on average, be balanced by what's being eaten, so we can just take tempers Centaur 8% of the total, and that takes account of the thermic effect of food. So then there's only one other component. And that's the basal metabolism. So that's how much energy you spend when you're completely lying at rest and not doing anything, we can measure that directly using a hug calorimeter. So there's like mask on your face, that's collecting your respiratory gases. And so since you only have two components there, you have the activity, metabolic rate and have the basal metabolic rate. And you can kind of count calculate their energy expenditure on activity by default. So we have the total, we have the basal that we can measure. And by subtracting the basal from the total, we get how much has been spent on physical activity. Now it turned out from those 8000, we from those 6000 data, we only had basal metabolism measurements for about 13 1400, something like that. But that allowed us to directly calculate what the activity energy expenditure was. So we could then show that the total reduction was due to the activity reduction. And, much to our surprise, it turned out not to be the case, that actually, energy expenditure on physical activity has actually gone up slightly. Since when, since the 1990s. Okay. And energy expended on basal metabolism has actually declined and some decline in the total. It's principally because the energy cost of just lying down at rest is lower now than it was 30 years ago, which is completely unexpected. And because people didn't expect that, until we kind of published this paper in 2022. Normally, it suggested that changes in basal metabolism were a potential driver for the obesity epidemic. But now we have this new kid on the block sort of thing that based on metabolism could be a potential obesity driver. And we were interested in, you know how the problem with the double a level of water technique is the first time it was ever used in humans was 99 to one. And there was very little data through the 1980s. So we don't we don't really have any good data before early 90s. And so, of course, people look at that. And they say, Yeah, but the problem with the obesity thing started in the 1960s 1970s. So we were interested in whether based on metabolism, and I'd only gone down recently, you know, since the 1990s, or whether there's a longer trend. And so what we did was a big literature review, where we pulled out all the measurements that have been made in the US and Europe. And should point out that the analysis that we did on the total energy expenditure is restricted to the US and Europe where there's been an obesity epidemic. And so we went right back to the 1920s, when the initial first good measurements were being made based on metabolism. And that trend, it's there through time, all the way from 1920s. right through to the modern day.


Nick Jikomes 38:22

So in so so yeah, I mean, this is sort of puzzling at first glance, it's been going down since the basilica prescod fuddling all the time. What so in principle, what could be the causes for a decrease in basal metabolic rate, what what kinds of factors would make an animal's basal metabolic rate go down?


John Speakman 38:44

So there are there are a few sort of things that are potentially important. So one of the main features that we think is potentially important and explaining the difference in metabolic. If you have two people that are the same portal weight, same bat to lean ratio, but one of them has a higher metabolic rate than the other one, then there are several kind of potential explanatory factors. So when we've looked at animals, it seems to depend to some extent on the sizes of different organs. So if we look back at some, some work we did, like 20 years ago in mice, we measured the metabolic rate, and then we chop them into pieces and looked at the sizes of the different organs. And it turned out liver size was one of the main things that didn't flow into this, this variation once you take out total body weight and competition, so it it's theoretically possible that there's been a reduction in, you know, the size of these metabolically active organs over time and that account for the changes seems unlikely claim, but we're never going to be able to check it because the data is not there in order to test whether, you know, people in the 1920s or 1950s had bigger livers than than we have now. The next main thing is hormonal effects. So one of the main things that influences your metabolic rate is, for example, levels of thyroid hormone. So we know that that's important. We know it's important in humans. But again, we don't have good data on whether there have been trends in thyroid hormone, or any reason to suspect why there might have been changes in thyroid hormone through time. But that's another kind of possibility. And then we're into a sort of gray area of okay, well, what's left, once you've accounted for the organ sizes, and you've accounted for the hormones, what else is end, and one potential thing that has changed over time his diet. And so it's, I mentioned that this thermic effect of food, for example, depends on what you eat. So when you eat more protein, you get a sort of stimulation of your energy expenditure. So maybe your basal metabolism, even though it's measured when you're not eating, and you're what's called post absorptive, it could be that your general habits in terms of what you eat food affects your metabolic rate. So there is actually there is another thing as well, the other potential thing there is things like your immune system. So it could be, for example, that our immune systems were maybe trying to fight off all the diseases that were going around in the 1900s. And that as we eliminated the risk of disease and infection, our immune systems didn't need to be as good or as active. And what happened then was we just started switching off that system. So it will be really interesting to see what happens post Pardon me, but we don't have to have that data yet. But the idea would be that you would decline your immune system, the cost of running your protection against disease, and that might be related to the reduction and basal metabolism. So that's a kind of interesting idea. And there is a bit of data that might support that. So a guy called Sam Urlacher has done some work on hits in South America that are in rural tribes, the Cemani tribe, and looked at based on metabolic rates of individuals that are living out a rural lifestyle where they're exposed to lots of diseases and things like that, compared to ones that have moved into cities where they are then pretty much protected. And what he shows is that kids who make that transition, get a reduction in the metabolic rate. So that's an interesting observation, but not necessarily. I mean, there could be lots of things that cause that not only I mean, like a day shift, for example. So it's not only the immune system that's changing, and in fact, there is other data. So for example, we did some work with animals in the wild, where we dosed them with anti parasite drugs. And what we found actually was when you remove the need to have an immune system, because they didn't have any parasites, and we eliminated them all, absolutely, the metabolism went up. So, you know, it's pretty confusing what's going on there with the immune system. And also, I don't think there were very big differences. There may have been differences between the 1920s and the 2020s. But I don't think there's big differences in


Nick Jikomes 43:54

tinnitus versus Yeah, exactly. For the


John Speakman 43:57

type course that we observe the decline. And so it seems unlikely that that's important.


Yeah. So the big thing we're left with is diet.


Nick Jikomes 44:05

Yes, yes. And you did some experiments in mice that were really interesting, right?


John Speakman 44:11

That's right. So I mean, maybe we should just think about what's changed in the diet first. So if you think back to the 1920s 1930s. So what's happened through time is there's been a big reduction in the amount of fat but we are sorry, in a big a big increase in the amount of fat that we saw, there's been a change, that we've slowly increase the amount of fat. We've also increased the amount of sugar that we eat. But the biggest change is probably the calories we're deriving from fat, but it's not a constant composition of. So what happened is, at the same time that we've increased the total, we've actually reduced the problem portion of that total saturated fat. So in the 1920s, we were probably 90% of calories in fat were coming from saturated fat that are coming from butter and lard and, and things like that, in the 1930s to 50s, we got this take off in on saturated fat, principally coming from Saudi seed oils. And that has now grown to really dominate our intake. And so now the saturated fats are only about 16% of the total. And so we were interested in whether those shifts in the fatty acid content of the fats that are going to be an important driver of the metabolic


Nick Jikomes 45:41

rate. And if I heard you, right, that's quite a remarkable shift, you know, when you go from 90% of the calories of fat coming from saturated fat at the beginning of the 20th century, down to, you know, below 20% today. Yes,


John Speakman 45:57

that's right. So there's an enormous change, and, but it's overlaid on the background of the total is going up as well. Okay, so actually, if you look at the actual amount of saturated fat that's been eaten, it's declined, but not anywhere near as much as that percentage suggests. So we're not going from eating like 90 pounds of larded a year to 16. It's a much smaller effect, but percentage wise, that that's what's happening. And most of that extra that we're eating, it's mostly polyunsaturated fat, principally linoleic acid. So there is that big move. And so what we were interested in is whether


Nick Jikomes 46:44

And so before we go forward, the little ik acid piece, is that primarily coming from thing is that is the driver of that change, because we came up with ways to mass produce things like vegetable oils, and it just became cheap and easy to get. Yeah,


John Speakman 46:58

thankfully. But also, there was, of course, a sort of a health drive as well going on. And so it wasn't just availability, it was that people were told that eating saturated fat is not good in terms of heart disease, and that limiting your saturated fat intake is probably a good idea. So there was a sort of shift towards or away from butter to margerine, those those sorts of things were happening through the 1960s and 1970s. It's interesting, though, that, you know, we might think that, you know, that was all driven from the sort of work that was done in the 1950s. But if you look at the data, the decline and the percent of fat that's coming from butter, and lard starts much earlier, it starts in the 1910s 1920s. And we were not really clear why that is, but it was already happening. It wasn't just like, you know, Ancel Keys came along and said, look, it's really bad eating butter that people stopped eating. And it was a gradual trend, that, in fact, there was no acceleration out during that time period, that it just continued on that same sort of trend. And we increased all these alternative sources. And they they're kind of also a lot of hidden fats and in foods, you know, because we, we use dogs in processed foods and things like that. So we did this most experimental and so one reason to do a mouse experiment is because it's very easy to control what they eat. So the problem with working on humans is you can tell them what to eat, but they have a choice to go away and eat it or not eat it. And so you never really know, when they come back into the lab, whether, you know, the experiment worked or not, unless you keep them captive for a long time. But


Nick Jikomes 48:57

I would imagine as well that for some of these diet induced changes in metabolism, they probably don't happen overnight. They might require extended


John Speakman 49:05

rights, right? Yeah. Right. So so when we did the most experiment, actually, the most experiment was done by some guys at Yelp. And they did an experiment that that's about three months long, so it's equivalent to about 11 years and an issue. And so it's, you know, it's a good amount of time. So if there are changes going to happen, then you expect to see them and what they found was that the change in the metabolic rate, the metabolic rate was mostly related to power mutate some power mutates a saturated fat that's the biggest component and butter a lot. It's it's palmitic acid. So that was pretty interesting, because that's the thing that's relatively gotten down over time. And so it was consistent this changes that we observed in the mice were consistent with the change through time in the human diet, and the slow decline in the metabolic rate through time. So it was all fitting together.


Nick Jikomes 50:13

Okay, so higher intake in mice of the saturated fat, correlated with more energy expenditure, yes.


John Speakman 50:22

And higher intakes of polyunsaturated fat in general. But the major amount of that was linoleic acid, which is also the major component in the human diet, they would correlate it with lower metabolic rate. So there have been some studies in humans that have tried to look at this, and they they paint a sort of fairly mixed picture. So there are some intervention studies lasting a couple of weeks, that suggests maybe there's an increase in relationship to linoleic acid intake. There's some other studies that suggest there's no change, but it may be just the study is not long enough. So it's difficult to tell. In terms of the mice, we'd actually already done a study in 2007, in my own lab, where we fed mice, different diets with different fat proportions. And we'd look for the relationship between individual variability in fatty acid composition of the membranes of their livers, and what their metabolic rate was. And we showed the parameter it was in the liver was a major driver of metabolic rate in the same direction as what we found in the other study.


Nick Jikomes 51:40

Interesting, so more saturated fat, specifically palmitate. More energy expenditure.


John Speakman 51:46

So that's what we found in the My son, and at the moment, we started designing experiments to see cross sectionally, whether that's true in humans, so if we can look at human diets, and find out what people have been eating, measure their metabolism, see whether there's a correlation there, and then try and do some intervention studies. But it may be difficult just doing intervention studies that are kind of long enough.


Nick Jikomes 52:15

And so, from the 90s, to the present, basically the period of time that you you have data with your doubly labeled water experiments, those experiments, again, they showed a decrease in total energy expenditure, which you just told us is mainly coming from a decrease in basal expenditure. Do we Do we know anything? Only coming from?


John Speakman 52:36

Yeah, yeah. Because activity expenditure seems to be actually going up. So locally,


Nick Jikomes 52:40

yeah. So it's, yeah, so it's gone down? Total has gone down despite that, because there's been such a drop of basal expenditure over that period of time. Do we have good data from anywhere on?


John Speakman 52:52

Gonna call for you? Yeah, okay.


Nick Jikomes 52:57

Do we have data on total caloric intake? Like, are we actually eating more calories per day today than we were in the 90s?


John Speakman 53:05

Yeah, good question. So I think that it's extremely difficult to answer. I mean, the problem is measuring food intake is incredibly difficult. And the tools that we have available to do that, and not really good enough to answer the question. So there was a paper recently suggesting that actually, intake has been pretty flat through time, for the last 2030 years. And not convinced that that's correct. If you look at food supply, into the population, that's definitely gone up. And so either the waste levels have gone through the roof, or we're consuming that food. And I think it's probably a combination of both, we're probably wasting more. But I think on balance, we probably are eating significantly more calories than we were 30 years ago.


Nick Jikomes 54:05

So in other words, if that is true, that would obviously mean it's possible for a population to simultaneously decrease their baseline energy expenditure and consume more calories.


John Speakman 54:16

Yeah, absolutely. And I think probably, the major factor driving the obesity is probably that increase in the food intake rather than the reduction in the basal metabolism. So the reduction in the base on may contribute, but I don't think it's the primary driver.


Nick Jikomes 54:37

So another thing I want to ask you about here, that, you know, this has to do with a topic of feeding behavior and the causes of things like weight gain or obesity. It's something I've talked about in the podcast before, which is fairly well known in this research world, which is the so called protein leverage hypothesis. So could you summarize what that is for people and what your take on that is? and whether or not humans are or might be a protein leverage species. Yeah,


John Speakman 55:04

so. So the idea is, is a really neat idea that was produced by this guy, Steve Simpson and David Rubin, Heimer. So Steve is originally from the UK, but works in, oh, maybe it's originally Australia. And I actually was working in the UK, they went back to Australia, but whatever is in Sydney at the moment, and they worked principally on insects, looking at what regulates food intake and low cost Sunday came up with this, this really cool idea. So the idea is that the mindset of everybody, including me, is that we eat food for energy, you know, the reason that that you go out and you eat some food, is to get the energy that's in that food. And people think that there's a regulatory system potentially, in our brains, that clocks how many calories we're consuming, and matches that off against how many calories we're expending. And so we can adjust those two together. And what goes wrong in the obesity epidemic is, is that ability to match and that may be undermined by the composition of the diet, or, or whatever. So that's, that's the way most people think about it, and the field. But what Steven David came up with it was was a completely different idea. And that is, we don't eat food for its energy content, actually, what we eat food for is protein content. So if you imagine a situation, let's imagine you're feeding on a diet, that 15% protein, and you're getting your protein names from that diet, but suddenly, you then get a diet that's only got 5% protein. So in order to meet your protein needs, you would have to eat three times the amount of that through. And that would give you a problem, because they've,


it's


got the same calorie content of the food that's got 15% protein, and you've got to eat three times the number of calories in order to get that same amount. And what you can see is that that's not an enormous shift, you know, 15, down to five, is leading to a 300% change in the food intake. And so it may be that much more subtle changes, you know, from like, 15, down to 30, may be enough to drive the intake up enough to create an obesity epidemic. And so that is, I think, a really, really cool idea that was called the protein leverage hypothesis, because what it's suggesting is that the protein leverages your energy intake. And that's what causes the obesity epidemic. So these small changes. I


mean, I was really


taken with that idea. We did a big experiment in mice about 10 years ago, where we sped mice on diets with very different protein levels going from 30%, down to 5%. And disappointedly, I provided absolutely no support for the idea of at all. So suddenly, in mice, what seems to be happening is they eat for energy, they're eating the food to get its energy. And if you reduce the protein content, they just end up with less protein coming into the system. They don't adjust in any way. But that reduction in protein, so that was slightly disappointing. Whether that's also true for humans or not, I'm not really sure. And whether we could actually detect the slight reduction in protein intake that would be necessary to drive that increased expenditure causing the obesity epidemic. I'm not sure we can even measure that. So I think it's still an open question whether protein leverage is an important factor in humans, and the obesity epidemic. But as far as I'm concerned, in mice, it's pretty much not important.


Nick Jikomes 59:11

And do you think that is, you know, if we think about this in sort of ecological or evolutionary terms, do you think it's plausible that you know, some species, depending on the niches that they're adapted to, might be strongly protein leverage. Others might be weakly protein leverage, others might be fat leverage, and so on and so forth, then perhaps that's why an organism like a mouse, you don't see the results that you were expecting there?


John Speakman 59:33

Yeah, so I think, I mean, that's an interesting idea. The interesting thing is there are some studies that suggest protein leverage is important in mice. And if you look at the difference between those studies on our studies, the primary thing seems to be age. And so if you took a young mouse that's growing, then it seems proteins really important for that mouse and you can imagine Shouldn't why because it's trying to build up how much muscle it has and all its limitations. So it needs protein to do that, then. So protein leverage seems to be important during that growth phase. But once they become an adult, which is the ones that we were studying, there's no effect. And so I couldn't imagine, that could be a general principle that protein leverage is very important for animals during the growth phase, but not important when you know, once they become an adult. If you read Steve's Steve's book on protein leverage, then he has some other examples in the kind of nice ecological examples of animals that go through seasonal shifts, and the amount of protein that's available to them. And the consequence of that is that they are different times of year become enormously fat, because they're trying to get brought in from a resource that that suddenly declined. But then when that goes up, again, they lose all the weight during the summer. So then, so they're not ratcheted up all the time. So I think there are some convincing kind of examples where it might be important.


Nick Jikomes 1:01:08

And do Is there any clear indication that in the US over time, the percent of calories coming from protein has has declined or anything like that? So


John Speakman 1:01:17

if you look at it, it's like spectacularly flat. You know, if you look, if you look at


what percent of protein, what percent of calories are coming from protein, and but actually, you don't need a big change, for it to be important, and we can't distinguish it accurately enough to tell whether there's been enough of a change, you know, so it's just not an answerable question with the data that we have.


Nick Jikomes 1:01:47

And in those experiments, were you guys, the experiments you did in mice, where you showed that dietary fat, but not protein, or carbohydrates was the primary driver of adiposity of gaining weight, gaining fat? Can you talk a little bit more about the results there? And in particular, the specific fat content was mainly one type of fat, like saturated fat or unsaturated


John Speakman 1:02:08

fat? Yeah, right. So so what we did was we came into that experiment wanting to change protein, fat carbohydrate content. So we designed a matrix of about 30 diet, where we could shift those contents. And the initial idea was the basis diet on some commercially available diets from research days that are very widely used. But the problem with those diet says that, as they ramp up the fat content, they change the fabric composition. And that wasn't particularly good. So what we did was we designed a new set of diets that had a saturated to unsaturated ratio, Omega six to Omega three ratio that match the American standard diet. So we fix that in every diet, according to what it's, you know, so what


Nick Jikomes 1:03:05

are those? What are those ratios?


John Speakman 1:03:08

So if you look at like, six, six to three, it's about 14 to one. And the saturated to mono unsaturated polyunsaturated, I think it's about 4747. Something, something I can't remember what the mono and polyunsaturated are, but about half the diet. In the data that that we looked at was coming from independently due by energy or weight, so but if you do buy energy, it turns out, it's about 47%. So we had those different ratios in the diet that match the American standard diet. And then we change the percent fat in the diet and the protein and the carbohydrate. So what what we got was a kind of interesting result that as the fat content got went up, the mice got fatter. But it wasn't a linear relationship. So what happened was, it kind of went up, and then that's about 40%. It flattened off. And actually, as you went above 60%, it started to decline again. So actually, since we did that, so the paper we wrote said that, you know, dietary fat is the only thing that makes mice fat.


But actually, that,


I mean, we got a lot of kickback then from the low carb people, because they will say like, oh, well, you didn't, you didn't take the PAP level high enough, you didn't take the carb. So we've actually done now another synchronizers, where we've taken the carbs right down to zero. And sure enough, it's a peak relationship. So what happens is, as you increase the fat in the diet up to 40%, there's an increase in how fat they get 40 to 60 is pretty flat, and then above 60, it just goes back down again. So once you're up to like 95% of the calories are coming from


fat.


There's virtually no carbs, right? Then it's back down to where it was at the beginning.


Nick Jikomes 1:05:11

So that would be like there would be like a ketogenic diet.


John Speakman 1:05:14

Yeah, so actually, it's very difficult to push mice into mutagenesis because they can, they can make glucose really, really easily on like humans, so, so then they're not called ketogenic diets. But if they were fed to humans, that would be ketogenic. So the interesting thing is, then, it it's like this, like, a diet that is uniquely horrible. So that's where you get like 40 to 60% of your calories from fat, you're getting about 10 to 20% from protein, and the rest is carbohydrate. So what happens is, if you're on that pig, that probably the pig that is most rewarding to eat. And there's some recent stuff in humans suggesting that when we looked in the brains of the mice, what's lit up is all the reward areas in the brain. So when they're eating those a diet, they're getting rewarded for doing that. And they're nice to eat. And, you know, that corresponds to like, pizzas, Oreos, ice cream, all the things that people eat, and they get when they're eating. So the thing is, when you come off the peak of that mountain, you can come off it in two directions, you can come off it by reducing tabs, and you reduce your body weight. And all those people say what makes you fat is eating carbs. Or you can come off it the other way, by going to low fat diets. And all those people says what, what makes you fat is eating fat. But actually, it's both it's the combination of the two that uniquely fattening. So the interesting thing I kind of thought was well, okay, why, why are we wired up that way? Why are we wired to eat these foods, because actually, if you look in nature, then those foods don't exist. You know, some most foods that exist out there are either plant based foods, which are dominated by carbohydrates, high fiber, low fat, are the animal based foods that are very low carbohydrate, high protein, high fat, but there's nothing in that middle zone. There's nothing that's really there. And a couple of people will say to a well, it's, it must be like nuts and seeds and things like that, that they're in there. And we will reworded the total, try and find those. But actually, that doesn't fit. Because if we look at the composition of those, they actually have much more fat than the optimal region. And it turns out that there's only one fruit that fits that profile. Know what it is?


No breast milk.


Nick Jikomes 1:08:05

Interesting.


John Speakman 1:08:05

Yeah. So what I think what I think, is a potential explanation of what's going on there is, when you're an infant, you need to be rewarded for eating that milk. Okay, so that when an infant eats that, it lights up all bits of that braid, and they go, Oh, that's nice. I need to do that again. And I need to get some more of that. Once you wait, and you imagine weaning into an environment 10,000 years ago, those foods don't exist. So there's no, there's no system in place to delete that reward. Because it doesn't matter. You never find food that has that composition, so you never get inappropriately rewarded. And so that system just sits there. From our childhood. It's there for a reason. But then, now in modern society, we have like breast milk fruits.


Nick Jikomes 1:09:01

Yeah, we invented we invented just this macronutrient profile. Yeah,


John Speakman 1:09:06

we invented foods, the mimic breast milk, given the composition, we love them, we, you know, food companies and all we love them, because we buy lots of the products. I don't, you know, I don't buy into the kind of, you know, the big bad food company that is there any I think they just make products that, you know, by trial and error, they find out people like them, and people buy them, so they make more of them because they you know, their motivation is making money. Yep. Yeah, I don't, I don't think they have a plan that, you know, they're gonna make those foods and that could make money and they


Nick Jikomes 1:09:38

just discovered this through an iterative process.


John Speakman 1:09:41

Right, right. And so what happens then is where it's kind of dropped


into this situation where we're rewarded in our brains for eating that food, and that leads to you know, potential overconsumption of those food tags.


Nick Jikomes 1:09:57

So you did your guys's experience It's in rodents. So that, you know, that's a caveat. But assuming that directionally these things are true for humans, what you're basically saying is, if your goal is fat loss, and to lose weight, you, you want to avoid that sort of middle ground, where you've got 40 to 60% of your calories coming from fat, and you either want to turn down the fat or turn down the carbs. But when you're in that middle zone, that's the danger zone for gain.


John Speakman 1:10:26

And if you look at all the people who are online, who are big advocates for low carb diet, that's basically what they've done. They've got fat sitting on the top of that mountain, and they've come off it by going to a low carb diet. And I think, you know, the the interesting phenomenon there is that, it seems that, you know, when you come off that that peak, there are different effects. So it seems that people who come off it on low carb report that they're not as hungry as people that come off it in the opposite direction. So whether that's actually true or not, I'm not sure. But that's definitely reported anecdotally. And, you know, that's maybe something to kind of look up.


Nick Jikomes 1:11:14

Interesting. Well, John, I know that you don't have too much time. Is there anything you want to reiterate from what we talked about? Or any final thoughts you want to leave people with about this general area?


John Speakman 1:11:26

And I mean, I think we covered most of the stuff that I've worked on, particularly in connection with obesity, I think. One, one aspect of my work has been that, you know, the things that turn out to be important that sometimes surprising things that we don't expect. So this BMR effect was was not expected. Nobody had previously predicted that would be important. But it could potentially turn out to be important. So I think the key is just having an open mind about stuff. You know, if you know, there's probably lots and lots of things in this field that we don't know about. And, you know, it's been crazy being very dogmatic about it, you know, that, you know, this is the cause. And this is the solution. And this is what we should do. I mean, I think the basic situation is we're not really clear what the cause is. And we're definitely not really clear what the solution is.


Nick Jikomes 1:12:21

And for the health and metabolism nerds out there who want to measure their own energy expenditure. What was the name of that company that has the doubly labeled water? Yeah,


John Speakman 1:12:32

so that company is called clarify. It's in California and based in California, I'm not I don't have any association with it. So I'm not endorsing the products. But if you do want to get easy access to this technique, that's the only commercial venture that you can go to.


Nick Jikomes 1:12:52

All right, well, Dr. John Speakman, thank you for your time.


John Speakman 1:12:57

Thank you for inviting me. I really enjoyed chatting about this

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