If you are completely unfamiliar with the actual science on obesity you probably think that’s dumb because obesity is caused by high-palatability foods. Read the first page linked if you’d prefer to know why that’s obviously wrong.
I admit to being, at present, persuaded by the high-palatability hypothesis, which I roughly translate into the following thesis: “The general rise in obesity is primarily explained by the rise of highly processed, addicting foods, which raises our natural set point, tricking our bodies into eating more calories than we ‘need’ before feeling full.”
I read the posts you linked (you referred to this one, right?), and I’m not convinced by them, but I’m open to people explaining why they think I’m still wrong.
First I’ll summarize the article briefly, and then respond to each point.
My brief summary
The series begins by outlining 8 mysteries:
Obesity has gotten a lot worse over time
Obesity abruptly got worse some time in the 1970s
There’s good evidence that we’re not winning the war against obesity
Hunter-gatherers don’t become obese
Lab animals and wild animals have also become obese over time
People and animals gain a lot of weight when exposed to palatable foods
People at higher altitudes seem to get obese at a lower frequency
Diets are not effective at reducing obesity, for nearly everyone
The series continues by arguing that CICO (as in calories in, calories out) cannot explain the current crisis, and cites an array of evidence that tries to argue against that model. Given the inadequacy of CICO as a model for weight gain, then, the reason for the current obesity crisis must be due to environmental contaminants, which neatly fit each of the 8 mysteries.
My interpretation of the mysteries
In my opinion, assuming the high-palatability hypothesis, very few of the mysteries are actually “mysteries” in the sense of being surprising.
For example, we can explain mystery 1 by saying that high-palatability foods have become more common over time (duh). We can explain 3 because very few people are effectively targeted by anti-obesity campaigns, and it’s intractable to simply ban high-palatability food (which is probably the only solution that would actually work on a large scale, short of advanced technology). We can explain 4 by pointing out that hunter-gatherers don’t eat high-palatability food. We can explain 6 for obvious reasons. We can explain 8 by pointing out that people don’t have unlimited willpower, and thus, don’t rigidly adhere to a dieting plan when given abundant choices to “cheat” and eat high-palatability food (which is highly addictive).
That leaves mysteries 2, 5 and 7, which I do think call out for more explanation. However,
Mystery 2 is practically equally mysterious under both the environmental contaminant hypothesis, and the high-palatability hypothesis, since by the author’s admission, they have little idea about what chemicals were abruptly introduced into the environment starting in the 1970s. At the same time, I found their argument that foods were palatable before the 1970s to be weak.
Sure, you can name a few palatable foods from before the 1970s (Oreos, Doritos, Twinkies, Coca-Cola), but I don’t find it particularly unlikely that the absolute number and variety of high-palatability foods has increased greatly since the 1970s, given the immense pressure for food corporations to hyper-optimize their food for consumption.
Mystery 5 is only a real mystery if indeed animals under controlled conditions are getting fatter over time. The author presents two sources for this claim.
Source one states in its abstract, “We examined samples collectively consisting of over 20 000 animals from 24 populations (12 divided separately into males and females) of animals representing eight species living with or around humans in industrialized societies.” The palatability hypothesis can elegantly explain what’s going on here. Animals who live near cities are exposed to human trash, and humans throw a lot of high-palatability food away. Animals eat the trash and get addicted to it, raising their set point, causing them to overconsume calories. Animals that live with humans get fed human-produced food.
Source two is about horses, and I lack a coherent explanation for the details. But, this is mostly because I don’t know how common it is for horses to eat hyper-palatable food, as I have very little experience with common horse-feeding practices.
Overall I wasn’t able to find compelling evidence that animals in controlled conditions , that don’t eat high-palatability foods, are experiencing increasing rates of obesity. (Though, of course, I might have missed this evidence in the sources). [Edit: it looks like I was mistaken and the first source includes laboratory rats and mice in the study.]
As far as I can tell, the most surprising mystery is 7. The author presents impressive evidence regarding altitude anorexia, and studies that looked into alternative factors (including carbon dioxide and oxygen).
EDIT: I now think that oxygen is the leading culprit for altitude anorexia, even though the author says it isn’t. Their evidence against the oxygen hypothesis is the following: one study found a small effect, and another study was methodologically flawed. Putting aside the second study, the effect found in the first study was not small at all in my opinion; in fact, it found that people who exercised in a low oxygen environment lost about 60% more weight than those who didn’t! Scott Alexander has written about this and finds the oxygen hypothesis plausible.
Yet, all things considered, I still don’t think that enough alternative hypotheses have been explored to say that mystery 7 is anywhere near conclusive. It’s well-known that obesity rates vary by demographic groups, and that there are genetic confounders involved, and demographic groups are also not evenly distributed between high and low altitudes.
In poorer nations, such as China, it seems highly plausible to me that altitude correlates strongly with access to supermarkets and fast-food restaurants that carry lots of high-palatability foods. Urban centers are generally clustered in low-altitude areas, along coasts and alongside rivers. If people in urban areas are exposed to more high-palatability foods, as opposed to more traditional dishes, then it seems obvious that you’ll find a correlation between altitude and obesity. The contamination hypothesis is not needed to explain this fact.
My take on CICO
Given that I don’t find any of the mysteries very surprising (with the possible exception of 7), I don’t see why the contamination hypothesis falls out as a parsimonious explanation of the data. Admittedly, however, my main disagreement probably boils down to the section on the plausibility of CICO.
Being honest, I found many of the parts of the CICO post to be riddled with misleading statements, sometimes simply confusing CICO with the idea that diets and attempts-to-increase-willpower work (which I emphatically do not believe), or strawmanning CICO into a generic position that absolutely nothing other than calories and exercise matter, or that an excess 3500 calories precisely and linearly adds 1 pound of fat to your body.
Obviously other factors, including genetics, matter. Obviously diets do not work on a large scale. And obviously the formula is not as easy as “eating an extra 3500 calories always means you gain an extra pound, even extrapolated to people eating 10,000 calories a day.” None of these facts are strongly inconsistent with the high-palatability hypothesis as the dominant explanation of the data. In my opinion, these are quibbles, not knock-down arguments.
And, in any case, the author admits,
Sure, consumption in the US went from 2,025 calories per day in 1970 to 2,481 calories per day in 2010, a difference of 456 calories.
That’s a lot! As someone who has very carefully controlled my eating before, I saw first-hand how eating a 500 calorie deficit made me lose weight, and conversely, how eating a 500 surplus made me gain weight. The author seems quick to handwave this fact away, as if a few hundred calories can’t add up over time. Their interlude responding to objections on this point also seems handwavey to me, and doesn’t give any evidence inconsistent with the high-palatability hypothesis.
Conclusion
Given a biologically plausible mechanism, its consistency with practically all the “mysteries”, common sense, and general scientific wisdom (from what I gather), it seems highly likely to me that the high-palatability hypothesis is correct. This, in my opinion, diminishes the case that money should be spent investigating alternative hypotheses (though the value of being proven wrong might be so high that it’s worth it anyway).
Impression: One of the articles also made a point about how certain tribes started becoming obese when exposed to Western culture. The high-palatability food hypothesis explains this reasonably well, whereas I’d need to see more details to imagine how lithium poisoning could have happened through their water supply.
Long ago, when SSC had an article about the altitude/obesity thing, a friend and I looked more closely at the data. I concluded that it seems like the bulk of the effect is explainable by selection effect, since there are very few people who live above a few thousand feet elevation, and they’re probably disproportionately upper class and active. See https://slatestarcodex.com/2016/12/11/open-thread-64-5/#comment-443619 (and the original post at https://slatestarcodex.com/2016/12/05/thin-air/). I’m serious about these selection effects—the data linked in my comment includes BMI values up to 3km or 9,800 feet above sea level. I don’t think there are 10,000 Americans living at that elevation total, and they almost all live in towns that primarily exist to serve wilderness recreation.
When Scott more recently posted about this hypothesis in one of the ACX open threads, one of the SMTM authors answered some questions in the comments. The mechanism tying elevation to pollution is allegedly that elevation is a proxy for how upstream you are in the water cycle, since water will accumulate toxins from the ground or being pumped into the water as it goes. To me, this seems like an extremely loose association. The relationship will depend strongly on how many pollutants are in the local area and how quickly the water loses elevation. Also, where people get their water from may not reflect exactly where they live: Consider Dillon reservoir (https://en.wikipedia.org/wiki/Dillon_Reservoir) at 9,100 feet. This water serves people in Denver, 4,000 feet below, after a fairly direct route through a tunnel and then into the Southe Platte River. The people who live near the reservoir get their water from the Green Mountain Reservoir (https://en.wikipedia.org/wiki/Green_Mountain_Reservoir) over 1,000 feet lower. And both reservoirs are filled largely from snowmelt, with the former being surrounded by generally higher mountains. And there’s clearly a lot of other factors that are visible in the obesity map at the top of Scott’s original post other than elevation—for example, there’s clearly a large drop in obesity from Kansas to Colorado, even though the state border is in a flat area 100 miles from the Rockies. You can also see large differences between New England, the upper Midwest, and the South, despite all those places being the exact same elevation.
Given the exceedingly noisy part that pollution must play in this story, and the extreme selection effects that are required to see a clear relationship between elevation and obesity, I think the latter is a much more likely explanation of the link than pollution.
The mechanism tying elevation to pollution is allegedly that elevation is a proxy for how upstream you are in the water cycle, since water will accumulate toxins from the ground or being pumped into the water as it goes. To me, this seems like an extremely loose association.
I agree, but moreover it looks like it should be an easy theory to test. My guess is that there are basically three routes for contaminants to enter our body and make us fat. The chemicals could be in the air, the water, or our food. If the SMTM authors believe that it’s in our water, then drinking distilled or purified water should make us thinner. Do we have any evidence of this?
When I looked into it, you could see an effect on birthweight for babies born to mothers in high altitudes vs their lower-altitude siblings, and vice versa, which suggests to me something non-genetic is going on. And the effect of altitude on birth weight held up in countries where altitude was associated with both lower and higher income (although that wasn’t the sibling study), which pushes against and doesn’t eliminate income effects.
(I’m not actually sure if e.g. median income is positively associated with elevation in the US, since a bunch of those people are “ski bums” working a series of seasonal jobs at ski resorts, white water rafting companies, etc. I used the word class because I think those people are still disproportionately drawing from upper-class cultures and probably have high education on average, and there are definitely a lot of rich people hanging around as well, and the latter are more likely to live closer to the resorts. Mean income is definitely higher in those areas, though.)
That’s a really neat set of data in that blog post which I will have to go over in more detail later. The effect size doesn’t seem to be that large to me, but maybe I don’t have a good intuition for birth weight; 100 g = 0.2 pounds corresponds to 4% of the low range of what is considered healthy in European babies. And that’s over a fairly wide elevation range of 3,300 feet. So I would be surprised if that could explain the very large difference in adult average BMI, but I could also be totally wrong about how fetal weight translates to adult weight. Given the limitations of “controlling for observables” I’m also still leaning towards selection effects, but the close linear relationship does cast doubt on that idea. I think it casts doubt on the pollution hypothesis too, FWIW, since there’s no way that’s cleanly linear, and it probably fits better with hypoxia but still not perfectly, since air pressure decreases sublinearly with elevation.
The mechanism tying elevation to pollution is allegedly that elevation is a proxy for how upstream you are in the water cycle, since water will accumulate toxins from the ground or being pumped into the water as it goes. [...] And there’s clearly a lot of other factors that are visible in the obesity map at the top of Scott’s original post other than elevation—for example, there’s clearly a large drop in obesity from Kansas to Colorado, even though the state border is in a flat area 100 miles from the Rockies.
Eastern Colorado is topologically very similar to Kansas and I suspect they get more water from wells than the (much more populous) middle of the state.
Mystery 5 is only a real mystery if indeed animals under controlled conditions are getting fatter over time. The author presents two sources for this claim.
Even if it’s true it might however be genetic. Mice that live in a controlled environment where they are protected likely want to put on more fat in preparation for getting pregnant and have less need to spend energy on running around and a lot of other activities in which wild mice burn calories. The effect might be downstream from breeding the same way how the mice were bred to be more susceptible to cancer.
Again, we compared the meta-analytically derived estimates for each of these groups, and find that the laboratory animals show a greater increase in per cent weight gain and odds of obesity than non-laboratory animals
I came across the slime mould article some time ago via the Marginal Revolution blog. I do not find it in the least convincing. It seems to me they have their theory, then cherry pick and misinterpret all evidence to fit.
In short, totally agree with what you’re saying here.
This might just be nitpicking. I disagree with or perhaps don’t understand the “set point” usage that is common here. I see it more as a balance of inputs to the brain from the mouth and stomach/other satiety sensors.
Plain boiled potatoes have a taste pleasure score of 3, and thus a satiation score of 3 from the stomach is required to stop you eating more of them.
Chocolate cake has a taste pleasure score of 8, and so a satiation score of 8 from the stomach is required to stop you eating more.
As you require a stronger satiation score to overcome the pleasure of the chocolate cake, you naturally eat more of it before the satiation score overpowers the pleasure score.
This explains the common experience of feeling full on a healthy dinner, then immediately being able to eat 500kcal of dessert.
Relative to the “set point” idea (or at least my understanding of it), this means if you switch to the only plain boring foods diet (or natural and healthy if you want a positive frame) then you can successfully lose at least some of the added weight. I do find the idea of some permanent regulatory damage plausible.
This dynamic will essentially create different set points on different diets. The whole range of set points for different diets being moved up over time by a hyperpalatable diet, due to it being an unnatural stimuli, does seem plausible.
I admit to being, at present, persuaded by the high-palatability hypothesis, which I roughly translate into the following thesis: “The general rise in obesity is primarily explained by the rise of highly processed, addicting foods, which raises our natural set point, tricking our bodies into eating more calories than we ‘need’ before feeling full.”
I read the posts you linked (you referred to this one, right?), and I’m not convinced by them, but I’m open to people explaining why they think I’m still wrong.
First I’ll summarize the article briefly, and then respond to each point.
My brief summary
The series begins by outlining 8 mysteries:
Obesity has gotten a lot worse over time
Obesity abruptly got worse some time in the 1970s
There’s good evidence that we’re not winning the war against obesity
Hunter-gatherers don’t become obese
Lab animals and wild animals have also become obese over time
People and animals gain a lot of weight when exposed to palatable foods
People at higher altitudes seem to get obese at a lower frequency
Diets are not effective at reducing obesity, for nearly everyone
The series continues by arguing that CICO (as in calories in, calories out) cannot explain the current crisis, and cites an array of evidence that tries to argue against that model. Given the inadequacy of CICO as a model for weight gain, then, the reason for the current obesity crisis must be due to environmental contaminants, which neatly fit each of the 8 mysteries.
My interpretation of the mysteries
In my opinion, assuming the high-palatability hypothesis, very few of the mysteries are actually “mysteries” in the sense of being surprising.
For example, we can explain mystery 1 by saying that high-palatability foods have become more common over time (duh). We can explain 3 because very few people are effectively targeted by anti-obesity campaigns, and it’s intractable to simply ban high-palatability food (which is probably the only solution that would actually work on a large scale, short of advanced technology). We can explain 4 by pointing out that hunter-gatherers don’t eat high-palatability food. We can explain 6 for obvious reasons. We can explain 8 by pointing out that people don’t have unlimited willpower, and thus, don’t rigidly adhere to a dieting plan when given abundant choices to “cheat” and eat high-palatability food (which is highly addictive).
That leaves mysteries 2, 5 and 7, which I do think call out for more explanation. However,
Mystery 2 is practically equally mysterious under both the environmental contaminant hypothesis, and the high-palatability hypothesis, since by the author’s admission, they have little idea about what chemicals were abruptly introduced into the environment starting in the 1970s. At the same time, I found their argument that foods were palatable before the 1970s to be weak.
Sure, you can name a few palatable foods from before the 1970s (Oreos, Doritos, Twinkies, Coca-Cola), but I don’t find it particularly unlikely that the absolute number and variety of high-palatability foods has increased greatly since the 1970s, given the immense pressure for food corporations to hyper-optimize their food for consumption.
Mystery 5 is only a real mystery if indeed animals under controlled conditions are getting fatter over time. The author presents two sources for this claim.
Source one states in its abstract, “We examined samples collectively consisting of over 20 000 animals from 24 populations (12 divided separately into males and females) of animals representing eight species living with or around humans in industrialized societies.” The palatability hypothesis can elegantly explain what’s going on here. Animals who live near cities are exposed to human trash, and humans throw a lot of high-palatability food away. Animals eat the trash and get addicted to it, raising their set point, causing them to overconsume calories. Animals that live with humans get fed human-produced food.
Source two is about horses, and I lack a coherent explanation for the details. But, this is mostly because I don’t know how common it is for horses to eat hyper-palatable food, as I have very little experience with common horse-feeding practices.
Overall I wasn’t able to find compelling evidence that animals in controlled conditions,that don’t eat high-palatability foods, are experiencing increasing rates of obesity. (Though, of course, I might have missed this evidence in the sources).[Edit: it looks like I was mistaken and the first source includes laboratory rats and mice in the study.]As far as I can tell, the most surprising mystery is 7. The author presents impressive evidence regarding altitude anorexia, and studies that looked into alternative factors (including carbon dioxide and oxygen).
EDIT: I now think that oxygen is the leading culprit for altitude anorexia, even though the author says it isn’t. Their evidence against the oxygen hypothesis is the following: one study found a small effect, and another study was methodologically flawed. Putting aside the second study, the effect found in the first study was not small at all in my opinion; in fact, it found that people who exercised in a low oxygen environment lost about 60% more weight than those who didn’t! Scott Alexander has written about this and finds the oxygen hypothesis plausible.
Yet, all things considered, I still don’t think that enough alternative hypotheses have been explored to say that mystery 7 is anywhere near conclusive. It’s well-known that obesity rates vary by demographic groups, and that there are genetic confounders involved, and demographic groups are also not evenly distributed between high and low altitudes.
In poorer nations, such as China, it seems highly plausible to me that altitude correlates strongly with access to supermarkets and fast-food restaurants that carry lots of high-palatability foods. Urban centers are generally clustered in low-altitude areas, along coasts and alongside rivers. If people in urban areas are exposed to more high-palatability foods, as opposed to more traditional dishes, then it seems obvious that you’ll find a correlation between altitude and obesity. The contamination hypothesis is not needed to explain this fact.
My take on CICO
Given that I don’t find any of the mysteries very surprising (with the possible exception of 7), I don’t see why the contamination hypothesis falls out as a parsimonious explanation of the data. Admittedly, however, my main disagreement probably boils down to the section on the plausibility of CICO.
Being honest, I found many of the parts of the CICO post to be riddled with misleading statements, sometimes simply confusing CICO with the idea that diets and attempts-to-increase-willpower work (which I emphatically do not believe), or strawmanning CICO into a generic position that absolutely nothing other than calories and exercise matter, or that an excess 3500 calories precisely and linearly adds 1 pound of fat to your body.
Obviously other factors, including genetics, matter. Obviously diets do not work on a large scale. And obviously the formula is not as easy as “eating an extra 3500 calories always means you gain an extra pound, even extrapolated to people eating 10,000 calories a day.” None of these facts are strongly inconsistent with the high-palatability hypothesis as the dominant explanation of the data. In my opinion, these are quibbles, not knock-down arguments.
And, in any case, the author admits,
That’s a lot! As someone who has very carefully controlled my eating before, I saw first-hand how eating a 500 calorie deficit made me lose weight, and conversely, how eating a 500 surplus made me gain weight. The author seems quick to handwave this fact away, as if a few hundred calories can’t add up over time. Their interlude responding to objections on this point also seems handwavey to me, and doesn’t give any evidence inconsistent with the high-palatability hypothesis.
Conclusion
Given a biologically plausible mechanism, its consistency with practically all the “mysteries”, common sense, and general scientific wisdom (from what I gather), it seems highly likely to me that the high-palatability hypothesis is correct. This, in my opinion, diminishes the case that money should be spent investigating alternative hypotheses (though the value of being proven wrong might be so high that it’s worth it anyway).
Impression: One of the articles also made a point about how certain tribes started becoming obese when exposed to Western culture. The high-palatability food hypothesis explains this reasonably well, whereas I’d need to see more details to imagine how lithium poisoning could have happened through their water supply.
Long ago, when SSC had an article about the altitude/obesity thing, a friend and I looked more closely at the data. I concluded that it seems like the bulk of the effect is explainable by selection effect, since there are very few people who live above a few thousand feet elevation, and they’re probably disproportionately upper class and active. See https://slatestarcodex.com/2016/12/11/open-thread-64-5/#comment-443619 (and the original post at https://slatestarcodex.com/2016/12/05/thin-air/). I’m serious about these selection effects—the data linked in my comment includes BMI values up to 3km or 9,800 feet above sea level. I don’t think there are 10,000 Americans living at that elevation total, and they almost all live in towns that primarily exist to serve wilderness recreation.
When Scott more recently posted about this hypothesis in one of the ACX open threads, one of the SMTM authors answered some questions in the comments. The mechanism tying elevation to pollution is allegedly that elevation is a proxy for how upstream you are in the water cycle, since water will accumulate toxins from the ground or being pumped into the water as it goes. To me, this seems like an extremely loose association. The relationship will depend strongly on how many pollutants are in the local area and how quickly the water loses elevation. Also, where people get their water from may not reflect exactly where they live: Consider Dillon reservoir (https://en.wikipedia.org/wiki/Dillon_Reservoir) at 9,100 feet. This water serves people in Denver, 4,000 feet below, after a fairly direct route through a tunnel and then into the Southe Platte River. The people who live near the reservoir get their water from the Green Mountain Reservoir (https://en.wikipedia.org/wiki/Green_Mountain_Reservoir) over 1,000 feet lower. And both reservoirs are filled largely from snowmelt, with the former being surrounded by generally higher mountains. And there’s clearly a lot of other factors that are visible in the obesity map at the top of Scott’s original post other than elevation—for example, there’s clearly a large drop in obesity from Kansas to Colorado, even though the state border is in a flat area 100 miles from the Rockies. You can also see large differences between New England, the upper Midwest, and the South, despite all those places being the exact same elevation.
Given the exceedingly noisy part that pollution must play in this story, and the extreme selection effects that are required to see a clear relationship between elevation and obesity, I think the latter is a much more likely explanation of the link than pollution.
I agree, but moreover it looks like it should be an easy theory to test. My guess is that there are basically three routes for contaminants to enter our body and make us fat. The chemicals could be in the air, the water, or our food. If the SMTM authors believe that it’s in our water, then drinking distilled or purified water should make us thinner. Do we have any evidence of this?
I have no idea, although I expect any such effect to be a very long-term thing and thus tricky to design and measure.
When I looked into it, you could see an effect on birthweight for babies born to mothers in high altitudes vs their lower-altitude siblings, and vice versa, which suggests to me something non-genetic is going on. And the effect of altitude on birth weight held up in countries where altitude was associated with both lower and higher income (although that wasn’t the sibling study), which pushes against and doesn’t eliminate income effects.
(I’m not actually sure if e.g. median income is positively associated with elevation in the US, since a bunch of those people are “ski bums” working a series of seasonal jobs at ski resorts, white water rafting companies, etc. I used the word class because I think those people are still disproportionately drawing from upper-class cultures and probably have high education on average, and there are definitely a lot of rich people hanging around as well, and the latter are more likely to live closer to the resorts. Mean income is definitely higher in those areas, though.)
That’s a really neat set of data in that blog post which I will have to go over in more detail later. The effect size doesn’t seem to be that large to me, but maybe I don’t have a good intuition for birth weight; 100 g = 0.2 pounds corresponds to 4% of the low range of what is considered healthy in European babies. And that’s over a fairly wide elevation range of 3,300 feet. So I would be surprised if that could explain the very large difference in adult average BMI, but I could also be totally wrong about how fetal weight translates to adult weight. Given the limitations of “controlling for observables” I’m also still leaning towards selection effects, but the close linear relationship does cast doubt on that idea. I think it casts doubt on the pollution hypothesis too, FWIW, since there’s no way that’s cleanly linear, and it probably fits better with hypoxia but still not perfectly, since air pressure decreases sublinearly with elevation.
Isn’t this specific point evidence in favor of SMTM’s hypothesis? Eastern Colorado and Kansas are at similar elevations, but Colorado gets most of its water from rivers that start in Colorado and Kansas gets most of its water from an aquifer (https://geokansas.ku.edu/water-kansas). SMTM suspects aquifers are more contaminated (with lithium?) (https://slimemoldtimemold.com/2021/10/19/a-chemical-hunger-interlude-h-well-well-well/).
I found this,https://www.cohealthdata.dphe.state.co.us/chd/Resources/briefs/Obesity.pdf which shows the east part of Co. as more obese. (Not sure how it compares to Kansas)
Eastern Colorado is topologically very similar to Kansas and I suspect they get more water from wells than the (much more populous) middle of the state.
I created https://skeptics.stackexchange.com/q/52923/196 to fact-check that claim.
Even if it’s true it might however be genetic. Mice that live in a controlled environment where they are protected likely want to put on more fat in preparation for getting pregnant and have less need to spend energy on running around and a lot of other activities in which wild mice burn calories. The effect might be downstream from breeding the same way how the mice were bred to be more susceptible to cancer.
Yes, a reply has come in
I came across the slime mould article some time ago via the Marginal Revolution blog. I do not find it in the least convincing. It seems to me they have their theory, then cherry pick and misinterpret all evidence to fit.
In short, totally agree with what you’re saying here.
My personal thoughts on the many errors in the SMTM theory here should you be interested: https://www.livenowthrivelater.co.uk/2021/09/is-the-obesity-epidemic-a-mystery-part-1/
https://www.livenowthrivelater.co.uk/2021/09/is-the-obesity-epidemic-a-mystery-part-2/
This might just be nitpicking. I disagree with or perhaps don’t understand the “set point” usage that is common here. I see it more as a balance of inputs to the brain from the mouth and stomach/other satiety sensors.
Plain boiled potatoes have a taste pleasure score of 3, and thus a satiation score of 3 from the stomach is required to stop you eating more of them.
Chocolate cake has a taste pleasure score of 8, and so a satiation score of 8 from the stomach is required to stop you eating more.
As you require a stronger satiation score to overcome the pleasure of the chocolate cake, you naturally eat more of it before the satiation score overpowers the pleasure score.
This explains the common experience of feeling full on a healthy dinner, then immediately being able to eat 500kcal of dessert.
Relative to the “set point” idea (or at least my understanding of it), this means if you switch to the only plain boring foods diet (or natural and healthy if you want a positive frame) then you can successfully lose at least some of the added weight. I do find the idea of some permanent regulatory damage plausible.
This dynamic will essentially create different set points on different diets. The whole range of set points for different diets being moved up over time by a hyperpalatable diet, due to it being an unnatural stimuli, does seem plausible.
In case you hadn’t seen it, here’s Yudkowsky on the hyperpalatable food theory.