I noticed something at EAG London which I want to promote to someone’s conscious attention. Almost no one at the conference was overweight, even though the attendees were mostly from countries with overweight and obesity rates ranging from 50-80% and 20-40% respectively. I estimate that I interacted with 100 people, of whom 2 were overweight. Here are some possible explanations; if the last one is true, it is potentially very concerning:
1. effective altruism is most common among young people, who have lower rates of obesity than the general population 2. effective altruism is correlated with veganism, which leads to generally healthy eating, which leads to lower rates of diseases including obesity 3. effective altruists have really good executive function, which helps resist the temptation of junk food 4. selection effects: something about effective altruism doesn’t appeal to overweight people
It’s clearly bad that EA has low representation of religious adherents and underprivileged minorities. Without getting into the issue of missing out on diverse perspectives, it’s also directly harmful in that it limits our talent and donor pools. Churches receive over $50 billion in donations each year in the US alone, an amount that dwarfs annual outlays to all effective causes. I think this topic has been covered on the forum before from the religion and ethnicity angles, but I haven’t seen it for other types of demographics.
If we’re somehow limiting participation to the 3/10ths of the population who are under 25 BMI, are we needlessly keeping out 7/10ths of the people who might otherwise work to effectively improve the world?
I think there are extensions of (1) and (3) that could also be true, like “people at EA Global were particularly likely to be college-educated” and “people who successfully applied to EA Global are particularly willing to sacrifice today in order to improve the future”
EDIT: and just generally wealth leads to increased fitness I think—obesity is correlated with poverty and food insecurity in Western countries
I’m currently doing research on this! The big big driver is age, income is pretty small comparatively, the education effect goes away when you account for income and age. At least this what I get from the raw health survey of England data lol.
The natural first step here is to check whether EA has lower rates of overweight/obesity than the demographics from which it primarily recruits.
I can’t speak much to the US, but in the European countries I’ve lived in overweight/obesity varies massively with socioeconomic status. My classmates at university were also mostly thin, as were all the scientists I’ve worked with (in several groups in several countries) over the years. And it’s my reasonably strong impression that many other groups of highly-educated professionals have much lower rates of obesity than the population average.
In general, I’ve tended to be the most overweight person in most of my social and work circles – and I’d describe my fat level over the past 10 years as, at worst, a little chubby.
If it is the case that EA is representative of its source demographics on this dimension, that implies that it doesn’t make all that much sense to focus on getting more overweight/obese people into the movement. Obviously, as with other demographic issues, we should be very concerned if we find evidence of the movement being actively unwelcoming to these people – but their rarity per se is not strong evidence of this.
(EDIT: See also Khorton’s comment for similar points.)
It’s also probably worth noting that obesity levels in rich European countries are pretty dramatically lower than the US, which might skew perceptions of Americans at European conferences:
I don’t want to overstate this, since my memory of EA San Francisco 2019 was also generally thin. But it is probably something to remember to calibrate for.
I’m skeptical of the comparability of your 2⁄100 and 50-80% numbers; being overweight as judged by BMI is consistent with looking pretty normal, especially if you have muscle. I would guess that more people would have technically counted as overweight than you’d expect using the typical informal meaning of the word.
It could also be that obese people are less likely to want to do conference socializing, and hence EAG is not representative of the movement.
While BMI as a measure of obesity is far from perfect, it mostly fails in a false negative direction. False positives are quite rare; you have to be really quite buff in order for BMI to tell you you’re obese when you’re not.
That is to say, I believe BMI-based measures will generally suggest lower rates of obesity than by-eye estimation, not higher.
Is that so? From the way BMI is defined, one should expect a tendency to misclassify tall normal people as overweight, and short overweight people as normal—i.e. a bias in opposite directions for people on either end of the height continuum. This is because weight scales with the cube of height, but BMI is defined as weight / height².
After reading around a bit, my understanding is that the height exponent was derived empirically – the height exponent was chosen to maximise the fit to the data (of weight vs height in lean subjects). (Here’s a retrospective article from the Wikipedia citations.)
The guy who developed the index did this in the 19th century, so it may well be the case that we’d find a different exponent given modern data – but e.g. this study finds an exponent of 1.96 for males and 1.95 for females, suggesting it isn’t all that dumb. (This study finds lower exponents – bad for BMI but still not supporting a weight/height³ relationship.)
I don’t find this too surprising – allometry is complicated and often deviates from what a naive dimensional analysis would suggest. A weight/height³ relationship would only hold if tall people were isometrically scaled-up versions of short people; a different exponent implies that tall and short people have systematically different body shapes, which matches my experience.
In any case, my claim above is based on empirical evidence, comparing obesity as identified with BMI to obesity identified by other, believed-to-be-more-reliable metrics – those studies find that false positives are rare. Examine.com is a good source, and its conclusions roughly match my impressions from earlier reading, albeit with rather higher rates of false negatives than I’d thought.
I still don’t think you’re wrong. Will is correct when he says that it is more likely someone with a BMI of 25 or lower is actually overweight than someone with a BMI of 25 or higher is just well-muscled, but that isn’t the same as estimating by eye.
The point, as I understand it, is that if you live in a country where most people are overweight, your understanding of what “overweight” is will naturally be skewed. If the average person in your home country has a BMI of 25-30, you’ll see that subconsciously as normal, and therefore you could see plenty of mildly overweight people and not think they were overweight at all—only people at even higher BMI’s would be identifiable as overweight to you.
Will is correct when he says “It is more likely someone with a BMI of 25 or lower is actually overweight than someone with a BMI of 25 or higher is just well-muscled”, but that isn’t the same as estimating by eye.
Relatively minor in this particular case, but: Please don’t claim people said things they didn’t actually say. I know you’re paraphrasing, but to me the combination of “when he says” with quote marks strongly implies a verbatim quote. It’s pretty important to clearly distinguish between those two things.
I agree “BMI gives lots of false negatives compared to more reliable measures of overweight” is not the same thing as “BMI is more prone to false negatives than by-eye estimation” – it could be that BMI underestimates overweight, but by-eye estimation underestimates it even more. It would be great to see a study comparing both BMI and by-eye estimation to a third metric (I haven’t searched for this).
But if BMI is more prone to false negatives, and less prone to false positives, than most people think, that still seems to me like prima facie evidence against the claim that the opposite (that by-eye will underestimate relative to BMI) is true.
I noticed something at EAG London which I want to promote to someone’s conscious attention. Almost no one at the conference was overweight, even though the attendees were mostly from countries with overweight and obesity rates ranging from 50-80% and 20-40% respectively. I estimate that I interacted with 100 people, of whom 2 were overweight. Here are some possible explanations; if the last one is true, it is potentially very concerning:
1. effective altruism is most common among young people, who have lower rates of obesity than the general population
2. effective altruism is correlated with veganism, which leads to generally healthy eating, which leads to lower rates of diseases including obesity
3. effective altruists have really good executive function, which helps resist the temptation of junk food
4. selection effects: something about effective altruism doesn’t appeal to overweight people
It’s clearly bad that EA has low representation of religious adherents and underprivileged minorities. Without getting into the issue of missing out on diverse perspectives, it’s also directly harmful in that it limits our talent and donor pools. Churches receive over $50 billion in donations each year in the US alone, an amount that dwarfs annual outlays to all effective causes. I think this topic has been covered on the forum before from the religion and ethnicity angles, but I haven’t seen it for other types of demographics.
If we’re somehow limiting participation to the 3/10ths of the population who are under 25 BMI, are we needlessly keeping out 7/10ths of the people who might otherwise work to effectively improve the world?
I think there are extensions of (1) and (3) that could also be true, like “people at EA Global were particularly likely to be college-educated” and “people who successfully applied to EA Global are particularly willing to sacrifice today in order to improve the future”
EDIT: and just generally wealth leads to increased fitness I think—obesity is correlated with poverty and food insecurity in Western countries
I’m currently doing research on this! The big big driver is age, income is pretty small comparatively, the education effect goes away when you account for income and age. At least this what I get from the raw health survey of England data lol.
The natural first step here is to check whether EA has lower rates of overweight/obesity than the demographics from which it primarily recruits.
I can’t speak much to the US, but in the European countries I’ve lived in overweight/obesity varies massively with socioeconomic status. My classmates at university were also mostly thin, as were all the scientists I’ve worked with (in several groups in several countries) over the years. And it’s my reasonably strong impression that many other groups of highly-educated professionals have much lower rates of obesity than the population average.
In general, I’ve tended to be the most overweight person in most of my social and work circles – and I’d describe my fat level over the past 10 years as, at worst, a little chubby.
If it is the case that EA is representative of its source demographics on this dimension, that implies that it doesn’t make all that much sense to focus on getting more overweight/obese people into the movement. Obviously, as with other demographic issues, we should be very concerned if we find evidence of the movement being actively unwelcoming to these people – but their rarity per se is not strong evidence of this.
(EDIT: See also Khorton’s comment for similar points.)
It’s also probably worth noting that obesity levels in rich European countries are pretty dramatically lower than the US, which might skew perceptions of Americans at European conferences:
I don’t want to overstate this, since my memory of EA San Francisco 2019 was also generally thin. But it is probably something to remember to calibrate for.
FWIW I see a much higher percentage of overweight EAs in the Bay Area.
I’m skeptical of the comparability of your 2⁄100 and 50-80% numbers; being overweight as judged by BMI is consistent with looking pretty normal, especially if you have muscle. I would guess that more people would have technically counted as overweight than you’d expect using the typical informal meaning of the word.
It could also be that obese people are less likely to want to do conference socializing, and hence EAG is not representative of the movement.
While BMI as a measure of obesity is far from perfect, it mostly fails in a false negative direction. False positives are quite rare; you have to be really quite buff in order for BMI to tell you you’re obese when you’re not.
That is to say, I believe BMI-based measures will generally suggest lower rates of obesity than by-eye estimation, not higher.
https://examine.com/nutrition/how-valid-is-bmi-as-a-measure-of-health-and-obesity/
Is that so? From the way BMI is defined, one should expect a tendency to misclassify tall normal people as overweight, and short overweight people as normal—i.e. a bias in opposite directions for people on either end of the height continuum. This is because weight scales with the cube of height, but BMI is defined as weight / height².
After reading around a bit, my understanding is that the height exponent was derived empirically – the height exponent was chosen to maximise the fit to the data (of weight vs height in lean subjects). (Here’s a retrospective article from the Wikipedia citations.)
The guy who developed the index did this in the 19th century, so it may well be the case that we’d find a different exponent given modern data – but e.g. this study finds an exponent of 1.96 for males and 1.95 for females, suggesting it isn’t all that dumb. (This study finds lower exponents – bad for BMI but still not supporting a weight/height³ relationship.)
I don’t find this too surprising – allometry is complicated and often deviates from what a naive dimensional analysis would suggest. A weight/height³ relationship would only hold if tall people were isometrically scaled-up versions of short people; a different exponent implies that tall and short people have systematically different body shapes, which matches my experience.
In any case, my claim above is based on empirical evidence, comparing obesity as identified with BMI to obesity identified by other, believed-to-be-more-reliable metrics – those studies find that false positives are rare. Examine.com is a good source, and its conclusions roughly match my impressions from earlier reading, albeit with rather higher rates of false negatives than I’d thought.
Thanks for sharing this, I guess it looks like I was wrong!
I still don’t think you’re wrong. Will is correct when he says that it is more likely someone with a BMI of 25 or lower is actually overweight than someone with a BMI of 25 or higher is just well-muscled, but that isn’t the same as estimating by eye.
The point, as I understand it, is that if you live in a country where most people are overweight, your understanding of what “overweight” is will naturally be skewed. If the average person in your home country has a BMI of 25-30, you’ll see that subconsciously as normal, and therefore you could see plenty of mildly overweight people and not think they were overweight at all—only people at even higher BMI’s would be identifiable as overweight to you.
Relatively minor in this particular case, but: Please don’t claim people said things they didn’t actually say. I know you’re paraphrasing, but to me the combination of “when he says” with quote marks strongly implies a verbatim quote. It’s pretty important to clearly distinguish between those two things.
Fair enough. I’ve edited it to remove the quotation marks.
I agree “BMI gives lots of false negatives compared to more reliable measures of overweight” is not the same thing as “BMI is more prone to false negatives than by-eye estimation” – it could be that BMI underestimates overweight, but by-eye estimation underestimates it even more. It would be great to see a study comparing both BMI and by-eye estimation to a third metric (I haven’t searched for this).
But if BMI is more prone to false negatives, and less prone to false positives, than most people think, that still seems to me like prima facie evidence against the claim that the opposite (that by-eye will underestimate relative to BMI) is true.