# It’s Probably Not Lithium

This post has been recorded as part of the LessWrong Curated Podcast, and can be listened to on Spotify, Apple Podcasts, Libsyn, and more.

A Chemical Hunger (a), a series by the authors of the blog Slime Mold Time Mold (SMTM) that has been received positively on LessWrong, argues that the obesity epidemic is entirely caused (a) by environmental contaminants. The authors’ top suspect is lithium (a)[1], primarily because it is known to cause weight gain at the doses used to treat bipolar disorder.

After doing some research, however, I found that it is not plausible that lithium plays a major role in the obesity epidemic, and that a lot of the claims the SMTM authors make about the topic are misleading, flat-out wrong, or based on extremely cherry-picked evidence. I have the impression that reading what they have to say about this often leaves the reader with a worse model of reality than they started with, and I’ll explain why I have that impression in this post.

# (Preamble) A brief summary of their hypotheses

The SMTM authors have recently (a) summarized their hypotheses on how lithium exposure could explain the obesity epidemic. The first hypothesis is that trace exposure is responsible:

One possibility is that small amounts of lithium are enough to cause obesity, at least with daily exposure.

And the second one is that people are intermittently exposed to therapeutic doses:

[E]ven if people aren’t getting that much lithium on average, if they sometimes get huge doses, that could be enough to drive their lipostat upward.

I am going to argue that neither of those is plausible. I address the plausibility of the second hypothesis in the next section, and the plausibility of the first one in the rest of the post.

# Lithium exposure in the general population is extremely low, even at the tails, in the majority of countries for which we have data

A few days ago, the SMTM authors published a literature review (a) on the lithium content of food. They conclude that, whereas the existing literature isn’t great, “[i]t seems like most people get at least 1 mg [of lithium] a day from their food, and on many days, there’s a good chance you’ll get more.” They also say it seems plausible that people are intermittently exposed to doses of lithium within the therapeutic range through their diet.

However, their literature review pretty much only includes studies that are outliers in the literature. Moreover, they use a misleading threshold for the therapeutic range of lithium. I’ll explain.

## The studies in SMTM’s literature review of lithium levels in food are pretty much all outliers

In 2006, France conducted its second Total Diet Study (henceforth TDS). Across 1,319 food samples, the highest lithium concentration found was 0.6 mg/​kg, in water. That’s not the highest average concentration among food groups – it’s the highest concentration of any single sample they tested. (For context, a standard clinical dose of elemental lithium is about 200 mg/​day, or 1 gram/​day of lithium carbonate.)

Similarly, New Zealand’s 2016 TDS examined 1,056 food samples and the highest concentration it found in any single sample was 0.54 mg/​kg (in mussels).

Canada makes the raw data of its Total Diet Study publicly available (a), and they too measure the lithium content of their food. The maximum level reported is 1.1 mg/​kg (in table salt, which is presumably rarely consumed in kilogram quantities) across 479 food samples, with the mean being 25 µg/​kg and the median 11 µg/​kg. Here’s a histogram of the data:

Excluding table salt, the maximum value in the rest of the dataset (N = 476) is 0.4 mg/​kg, in mineral water.

Total Diet Studies in other countries report similarly low levels. Using data from the UK’s 1994 TDS (which included 400 food samples), the mean daily lithium intake among adults was estimated to be 17 µg/​day, more than 50 times lower than SMTM’s estimate of “at least 1 mg a day”. In Northern Italy, a research group that analyzed 908 samples of food from 2016 to 2017 has estimated that the mean dietary intake is 18.15 µg/​day, and an older study in the same area, with 248 food samples, estimated daily dietary intake to be 29.9 µg. Those numbers are similar to estimates from France, which range from 11 µg/​day to 48 µg/​day, and to estimates from New Zealand’s 2016 TDS, the upper bound of which is 0.31 µg per kilogram of body weight per day, or 31 µg/​day for a 220 lb adult.

(Notably, dietary lithium intake in Vietnam, which is extremely lean compared to all other countries mentioned here, is estimated to be 0.285 µg per kilogram of body weight per day, perfectly in line with these other estimates.)

I haven’t been able to find TDS data from other countries. The United States, notably, does not track lithium in its own TDS.[2] But there are a few smaller studies available, neatly summarized by Van Cauwenbergh et al. (1999) (including one from the US, in the last row):

Notice that none of those studies estimates anything as high as “1 mg a day.”

Older sources not included in that table suggest that Finnish diets provide 35 µg/​day of lithium, Turkish diets 102 µg/​day, and American diets 60-70 µg/​day.

SMTM’s review of lithium in food (a) does not include any of these studies; instead, it largely relies on old data from a single author from Germany, a country which, as we can see in the chart above, is a clear outlier. So, unsurprisingly, the numbers that you see in SMTM’s review are way higher than the numbers I found in my own research. The lowest estimate their review even mentions, as a lower bound, for daily lithium intake in the general population, is 128 µg.

To be clear, I don’t think that their data is wrong. It makes sense for lithium concentration to vary a lot in time and space. [3] And whereas the SMTM authors based their literature review mostly on old German studies, the studies I found were from Canada, France, New Zealand, Italy, the UK, Belgium, etc. and a lot of those are very recent. But it is odd that they exclusively talk about outliers, and make conclusions such as “[i]t seems like most people get at least 1 mg a day from their food” based on those outliers.

I have attempted to make a comment on SMTM’s post linking to many of those studies, but they have not approved the comment. I have also attempted to contact them on Twitter (twice) and through email, but have not received a reply. All of this was over one week ago, and they have, since then, replied to other people on Twitter and approved other comments on their post, but haven’t commented on this. So I have no idea why their literature review excludes these studies.

[ETA: on July 5, a week after the publication of this post, they released a post (a) addressing five of the studies I’ve mentioned here (and completely ignoring the rest). I replied to this new post in these comments.]

(Notably, the SMTM authors say in the post that “the smart money is that Anke’s measurements [Anke being the German author most of their review is based on] are probably all lower than the levels in modern food.” If my data from Canada, New Zealand and Italy, all of which is from after 2015, counts as “modern,” then that prediction seems to have turned out horribly wrong.)

Their literature review was misleading in other ways as well; I explain how in my addenda.

People eat about 2 kg of food per day. So it seems that, at least in New Zealand, Canada and France, in order to consume 1.2 mg of lithium in a day you’d need to spend the entire day eating nothing but the most lithium-rich of the 2,851 food samples tested in those three countries combined (excluding salt). And even that value is still 100 times lower than a low therapeutic dose (which, as I’ll explain below, is about 100 mg/​day of elemental lithium). So SMTM’s hypothesis that people are intermittently exposed to doses of lithium within the therapeutic range through their diet seems very implausible, at least in those countries (in which, just to make it clear, the obesity epidemic has definitely arrived (a)). [4]

This isn’t, and could not be, conclusive evidence that people don’t intermittently consume therapeutic doses of lithium in those countries. The distribution of lithium concentration in food could be so discontinuous that knowing the maximum value out of the nearly 3,000 samples we have from France, Canada and NZ doesn’t give us much information about what obese people in those countries are likely to have encountered in their lifetime. But the hypothesis that people are intermittently consuming doses that high (at least in those countries) would have to do a lot of work in order to be consistent with our observations.

## 30 mg/​day is not a relevant cutoff

In addition to exclusively mentioning studies with unusual findings in their literature review, the SMTM authors use a subtle sleight of hand to argue that intermittent exposure to therapeutic doses of lithium through food could be the cause of the obesity epidemic. They first say that lithium therapy causes weight gain, citing Vendsborg et al. (1976), in which the average daily elemental lithium dose was 200 mg (SD 8 mg), and also citing this review paper, in which the lowest serum lithium concentration of any patient seems to have been 0.45 mEq/​L. Then, later, they claim that the lower end of the therapeutic range of lithium is 30 mg/​day, citing a guy on Reddit saying that he takes that much and also has bipolar II, and then they conclude their argument by saying that food could plausibly sometimes contain 30 mg doses of lithium per serving (again, using studies with unusual findings as evidence for this last part).

I say this is a “subtle sleight of hand” because 30 mg/​day has doubtful usefulness as a cutoff for a therapeutic dose. As far as I can tell, no patients in the weight gain studies cited by the SMTM authors seem to have been taking a dose as low as 30 mg/​day.

Moreover, every (a) source (a) tells (a) you (a) that (a) the (a) therapeutic (a) range (a) of (a) serum (a) lithium (a) concentration starts at 0.4 mEq/​L (most often 0.6 mEq/​L) (seriously, just Google “lithium therapeutic range”, the same numbers are everywhere). And unless you’re >65 or have really bad kidneys, 30 mg/​day is not enough to get you there – the average adult between the ages of 20 and 65 needs more than three times as much (about 100 mg/​day of elemental lithium, or 535 mg of lithium carbonate) to reach 0.4 mEq/​L. People over 65 and those with unusually bad kidneys need lower doses, but that hardly helps to explain the obesity epidemic, since people are much more likely to gain weight when they’re young. (Yes, older people do tend to be fatter (up to a certain age) but the rate of change of excess weight is highest in young adulthood.)

Similarly, Googling “lithium dose range” reveals that every single website says that the lowest daily dose is at least 600 mg of lithium carbonate (112.2 mg of elemental lithium), with some (a) sources (a) saying it is as high as 900 mg (168 mg of elemental lithium).

In practice, patient compliance with psychiatric treatment is often not perfect, so there are some people with lower lithium serum concentrations in some studies. However, studies with patients who have low average serum lithium concentrations – under 0.6 mEq/​L – seem to find only very modest increases in body weight (or even body weight decreases for patients switching from higher doses)[5]. Moreover, patients with serum lithium concentrations that low experience higher relapse rates, so doctors tend to aim for higher serum lithium concentrations when toxicity is not an issue. The SMTM authors do not address any of that, but rather consistently guide the reader into thinking that a 30 mg/​day dose can be expected to lead to therapeutic benefit and weight gain.

## (Briefly) Lithium in air and water

The Canadian government has a page (a) with a lot of information about lithium, including concentrations found in the air. From the looks of it, if you breathe outdoor air at the 95th percentile of lithium concentration in Canada, by doing so you will consume 2.86 nanograms of lithium per day. This number is really low, and the numbers for indoor air are even lower, so we probably shouldn’t worry about this. The data we have for the US is similar (though unfortunately, it’s a lot older).

As the SMTM authors have gone into (a), the USGS has measured (a) the lithium concentration of thousands of samples of groundwater in the United States, finding an average of 19.7 µg/​L, a median of 6.9 µg/​L and a maximum of 1.7 mg/​L across 3,140 samples of groundwater from used wells. Values tend to be similar or lower in other countries, except for Chile and Argentina, where they’re much higher.

Importantly, lithium concentrations vary a lot according to lithology and climate, so it seems implausible that people in e.g. humid regions are consuming crazy doses of lithium from their water, as this figure displaying the cumulative distribution of lithium concentrations by climate demonstrates:

(Source: Figure 2 from this paper.)

And this is important, because a lot of the highest-obesity states, such as those in the South, are in humid regions:

Even not taking that into account, however, it seems implausible that a large fraction of the US population is getting therapeutic doses of lithium from their groundwater — even intermittently — given that the maximum concentration across 3,140 samples was found to be only 1.7 mg/​L, and given that the average person has only lived for about 15,000 days.

## Serum lithium concentration data, just like food data, is strong evidence against the hypothesis that people are exposed to high doses of lithium

The data we have for serum lithium concentration in the general population is probably measured at the trough too (i.e. early in the morning, before people have had any water or food). So with some caveats,[6] it probably makes sense to compare those values directly.

The Canadian Health Measures Survey found that the median whole blood lithium concentration was 0.000068 mEq/​L in a nationally representative sample of 5,752 subjects, with data collected from 2009 to 2011. Whole blood lithium concentrations are 65% the value of plasma concentrations (a), which are in turn similar to those in serum, so that corresponds to a serum concentration of 0.0001 mEq/​L. This value is 4,000 times lower than the lower end of the therapeutic range, and the 95th percentile (0.00029 mEq/​L) is 1,383 times lower.

Given that we have two percentiles, we can estimate the parameters of the underlying distribution, and thus its mean and (e.g.) 99.99th percentile, if we assume that it has a certain shape. Under the assumption that the distribution is lognormal, the average and 99.99th percentile of serum lithium concentrations in that Canadian study are 0.00013 mEq/​L and 0.001 mEq/​L – respectively, 3,000 times and 400 times lower than the low end of the therapeutic range. This is what the distribution looks like, if we sample from it 100,000 times:

(Feel free to look at my code in this Google Colab notebook.)

If we assume that serum lithium concentration is Pareto-distributed instead, then the 99.99th percentile is 0.0045 mEq/​L, still 89 times lower than the low end of the therapeutic range.

The second-largest study of serum lithium concentrations in the general population that I found was this one (N = 928, data collected around 2010 in Germany), in which the median is 0.000138 mEq/​L and the 91.7th percentile is 0.0003 mEq/​L. Plugging those numbers in the same code, we find a 99.99th percentile of 0.0011 mEq/​L in a lognormal distribution and 0.0055 mEq/​L in a Pareto distribution, the latter of which is still 73 times lower than a therapeutic dose.

Some places have much higher lithium exposure. In northern Chile, where the highest drinking water concentrations of lithium in the world were found in the 1970s, serum concentrations were only about two orders of magnitude lower than the therapeutic range; a more recent study in nearby northern Argentina, which likewise has extremely high levels of lithium in its rivers, found similar (but a bit lower) levels. And, as we’ve gone into before, some older studies from Germany suggest that lithium levels were quite high in food at the time the measurements were made. Moreover, in the Canary Islands, average dietary lithium consumption has been estimated at 3.7 mg/​day.

But I think it’s important to point out this data from Canada, France, New Zealand, etc., because the obesity epidemic is a pretty global problem that has definitely reached those countries, and that is worse in Canada (31% obese in 2016) and NZ (32%) than in Chile (29%), Argentina (29%) or the Canary Islands (20.1%), despite the first two countries having much lower average lithium exposure.

## Clinical doses of lithium cause a lot more side effects than just weight gain

But let us suppose for a moment that people are inadvertently taking therapeutic doses of lithium from their food/​air/​water/​whatever every few months or years. There’s still another problem with the lithium hypothesis: why aren’t people getting the other lithium side effects?

### Hand tremors

This Cochrane review found that lithium greatly increased the incidence of hand tremors (OR 3.25, 95% CI 2.10 to 5.04; N = 1241; k = 6) among patients taking the drug for a few weeks to control acute mania.

### Hypothyroidism

Hypothyroidism is about six times more common in patients on lithium. And notably, its prevalence through time and space doesn’t seem to follow the pattern of obesity. It hasn’t been consistently becoming more common over time, and global rates of the disease don’t seem correlated with obesity rates, with thin countries like China and Brazil having higher prevalences. Moreover, it is more common in old age, whereas weight gain is more common in youth.

### Diabetes insipidus

But perhaps the most specific side-effect of clinical doses of lithium is acquired nephrogenic diabetes insipidus.

This disease is not well-known, so I’ll explain what it is. Diabetes insipidus (henceforth DI) is a disease characterized by polyuria (peeing a lot), polydipsia (increased thirst and fluid intake), and abnormally low urine concentration. Polyuria and polydipsia are also found in untreated diabetes mellitus, hence the similar name, but DI has nothing to do with blood sugar.

Most cases of DI in the general population are caused by abnormally low secretion of vasopressin (aka antidiuretic hormone, which gives the signal to concentrate urine); this type is called “neurogenic” or “central.” The type of DI that lithium causes is called “nephrogenic,” and is instead caused by the kidneys becoming unable to respond to vasopressin. Someone with either of those types will pee out a lot of clear urine even after a long period of fluid deprivation — but those with neurogenic DI function normally if they are given desmopressin, so it’s easy to tell those types apart.

Nephrogenic DI seems to be extremely rare in the general population. The NHS website says (a) that the prevalence of any kind of DI is 1 in 25,000, and that DI is nephrogenic in nature in “rare cases.” Acquired (non-hereditary) nephrogenic DI is so rare that lithium therapy is literally its most frequent cause.

How common is diabetes insipidus in patients on lithium therapy? In Vendsborg et al. (1976), 30% of patients had it. Subclinical symptoms of the disease, such as abnormal urine concentration ability, are more common, affecting 54% of 1,105 unselected patients in this study. Notably, the second top post of all time on the r/​Lithium subreddit is this (a):

Those symptoms can set in early on with lithium treatment – in Forrest et al. (1974), maximum urine concentration was much lower after 8-12 weeks on lithium than before (Cohen’s d = 3.84, an extremely huge effect size), and such impairment has been found after four weeks of lithium treatment in rats.

It’s true that we don’t know to what extent those side effects happen if you take high doses of lithium intermittently rather than chronically, but note that the exact same argument applies to weight gain.

### Weight gain is associated with other lithium side-effects

Moreover, there’s evidence that diabetes insipidus and hypothyroidism might play a role in the weight gain caused by lithium, making it unlikely that lithium exposure in the general population would cause a lot of weight gain in the absence of those other side effects. In Vendsborg et al. (1976), weight gain was much greater among those with greatly increased thirst than among those without:

and much greater among those with clinical diabetes insipidus than among those without:

Vestergaard et al. (1980) report a similar finding. Those studies note that increased thirst can cause weight gain by increasing the consumption of caloric drinks.

On top of that, weight gain is a well-known symptom of hypothyroidism.

(Note: I have attempted to make some of those points in the comment section of SMTM’s last post about lithium, but they never approved my comment. (They did approve some comments made after mine.) There is no mention of diabetes insipidus anywhere on SMTM’s website.)

# Even therapeutic doses of lithium don’t cause enough weight gain to explain the obesity epidemic

How much weight gain does lithium even cause, on average? The SMTM authors have cited figures from Vendsborg et al. (1976) and Vestergaard et al. (1980), and I found a number of others (Versteergard et al. (1988), Mathew et al. (1989) and Armond (1996)) in my own research:

All of those studies are observational and none other than the last one has a control group. Patients with bipolar disorder often take antipsychotics and antidepressants in addition to mood stabilizers such as lithium, and the patients in these studies are no exception. In the first two studies, for instance, only a minority of patients were taking lithium alone. Antipsychotics cause weight gain, and the same is true of several antidepressants that were available when those studies were conducted (e.g. TCAs and the MAOI Nardil), so lithium alone probably causes less weight gain than those numbers suggest.

Weight gain does not seem to be constant throughout the duration of lithium treatment; it instead slows down or even stops at some point, as the figures below, from Versteergard et al. (1988) and Kerry et al. (1970), respectively, illustrate:

I mentioned these studies despite their methodological flaws because they have the longest follow-up times I’ve ever found in the literature (and because the SMTM authors cited some of them). What do meta-analyses of RCTs have to say?

I searched Embase for systematic reviews and meta-analyses on the effects of lithium on weight gain, [7]and found 3. This one, from 2012, finds that patients on lithium are almost twice as likely to experience clinically significant weight gain (defined as gaining 7% of your body weight) as patients on placebo (k (number of studies) = 5). The two studies that reported patients’ serum lithium concentrations found values of 0.8 ± 0.3 mEq/​L and 0.66 ± 0.27 mEq/​L; the other studies said that patients were expected to have serum concentrations of at least 0.8 mEq/​L.

The second result was a Cochrane Review, which found that people on lithium for acute mania were a bit more likely to gain weight (OR 1.48, 95% CI 0.56 to 3.92; n = 735, k = 3); though the reviewers say that there is “insufficient evidence” that lithium had any effect. This review only included patients in the mental hospital for mania, however, so the average duration of treatment was probably really short.

Oddly, the third result I found was a 2022 systematic review and meta-analysis that says that weight gain during lithium treatment is not statistically significant from zero, and is significantly greater in shorter studies than in longer ones (k = 9, n = 991). Compared to placebo, the meta-analysis finds that lithium causes less weight gain (k = 3, n = 437). I don’t buy this paper’s conclusion, but I think this is nonzero evidence that lithium causes somewhat less weight gain than some other studies suggest.

So lithium seems to cause an average of zero to 6 kg of weight gain in the long term. And strikingly, the upper end of that range, although large, is only half the amount of weight the average American adult has gained since the early 70s, which, according to my analysis of NHANES data (which is all in a public Google Colab notebook) is about 12 kg (~26.4 lb), and as high as 15.7 kg (~34.5 lb) for people in their 30s. (The median American adult gained about the same amount of weight.)

And it’s not as if Americans were that thin in the early 1970s! 47% of adults were overweight and 14.5% obese (a). In contrast, obesity rates are under 3% in traditional societies that engage in foraging or subsistence farming. Moreover, there is substantial (a) evidence (a) that Americans gained a lot of weight before 1970. It’s hard to know the overweight and obesity rates of the general population back in the 19th century, because there was no NHANES back then, but we do know that men at elite colleges (a) (source), Citadel cadets (a) (source) and veterans all started getting substantially fatter in the early 20th century.

I feel the need to stress this, because the SMTM authors claim (a) that there was an abrupt shift in obesity rates in the late 20th century, a claim that is probably based to some extent on an artifact of the definition of BMI (a), and so some people reading this might have the impression that 1970s Americans were really thin or something, when they really weren’t.

Anyway, so the 12 kg average weight gain since the early 70s is not the whole story. A 5’9” man with a BMI of 21, which is higher than the average for the Hadza (independently of gender or age), for Citadel cadets born in the 1870s, and for men entering Amherst, Yale, or Harvard in the 19th century, is 19.5 kg (43 lb) lighter than the average college-aged American man today. Moreover, a 5’9” man with the average BMI of 19th-century veterans in their 40s is a whopping 22.5 kg (49.5 lb) lighter than the average American man of the same age and height today.

So even if everyone in the US were consuming therapeutic doses of lithium without knowing it, that would leave most of the secular increase in body weight unexplained.

This can also be seen in studies that report the obesity rate or average BMI of patients taking lithium back when obesity rates were low. Chen & Silverstone (1990) (a review article that has been cited by SMTM) reviewed some studies reporting either of those figures, and in none of them was the obesity rate greater than 25% – even though most of those patients were probably on antipsychotics and/​or TCAs as well. So it’s difficult to imagine how lithium exposure could explain why the obesity rate is greater than 30% in several countries.

# Lithium weight gain seems to (perhaps) be dose-dependent even at therapeutic doses

Furthermore, there’s some evidence that weight gain on lithium is dose-dependent even at therapeutic doses.

Gelenberg et al. (1989) randomized 94 patients on lithium therapy to either a normal or a low dose in a double-blind trial. They found that patients on the low-dose group were about half as likely to report worsening weight gain.

Abou-Saleh and Coppen (1989) likewise randomized 91 patients on lithium therapy to either maintain their dosage or decrease it by up to 50%. The group with the lowest dosage lost 0.9 kg, whereas the highest-dosage group gained the same amount of weight.

Keller et al. (1992) performed the same kind of study, and found that patients in the normal-dose group were more likely to report weight gain than those in the low-dose group.

Moreover, in Vendsborg et al. (1976), one of the observational studies we’ve talked about, there was a 0.44 correlation between lithium dosage and weight gain.

Not all studies find such a dose-dependence – Mathew et al. (1989) did not find one. But the patients in this study had a low serum concentration (0.54 mEq/​L on average) and they barely gained any weight (as I’ve mentioned, their average BMI increased by 1 kg/​m over the course of 4.7 years). Vestergaard et al. (1980) and (1988) do not find it either. So this seems to be something that might exist, but we’re not sure.

It seems noteworthy, however, that the studies with the best methodology (the first three studies I mentioned, which were randomized double-blind trials) all found dose-dependence. Moreover, when scientific papers say that some association has not been found, often what they mean is that it just hasn’t reached an arbitrary significance threshold. Since Mathew et al. (1989), Vestergaard et al. (1980) and (1988) do not provide any actual data on the amount of weight gained by patients as a function of dosage, for all we know that could be what is going on.

Somewhat relatedly, Rinker et al. (2020) randomized 23 patients with multiple sclerosis to take either placebo or a low dose of lithium (150–300 mg/​day of lithium carbonate, ~30-60 mg/​day of elemental lithium) for a year in a crossover trial. 13 patients complained of weight gain, but the other 10 complained of weight loss.

# Genes that influence BMI do not tend to be expressed in the kidneys (which govern lithium secretion)

If the obesity epidemic were caused by lithium, we should probably expect poor kidney function to predict weight gain, since it strongly predicts serum lithium concentration. But the genes that affect obesity are primarily expressed in the nervous system, and the urogenital system doesn’t stand out at all:

# The evidence that trace doses of lithium exert significant effects is actually pretty weak

The SMTM authors say (a):

There’s lots of evidence (or at least, lots of papers) showing psychiatric effects [of lithium] at exposures of less than 1 mg [...]. If psychiatric effects kick in at less than 1 mg per day, then it seems possible that the weight gain effect would also kick in at less than 1 mg.

I’d like to point out that Gwern has looked into this (a) and concluded that the evidence that such low doses of lithium cause psychiatric effects is actually fairly weak.

# Mysteries that lithium cannot explain

A Chemical Hunger opens up with a list of mysteries related to the obesity epidemic. I don’t endorse the list – for one, “wild animals are becoming obese” seems to have been pretty much made up (see the fourth point in this comment), and all evidence we have that “lab animals are becoming obese” is exactly one (1) unreplicated paper co-authored by a guy that has been involved in numerous controversies regarding his conflict of interest with the processed food and restaurant industries.[8]

However, some of the mysteries are genuinely true and interesting – for instance, that obesity rates are much lower in high-altitude areas, and that human food is unusually palatable. And lithium does not seem to explain either of those mysteries.

(Note that a theory of the obesity epidemic does not need to explain these mysteries. They could very well be a result of factors completely unrelated to the secular increase in BMI since the early 20th century. But I feel like some people might believe that the lithium hypothesis neatly explains all of SMTM’s mysteries, when it doesn’t.)

## Altitude

Using publicly-available data from the USGS and the Open Elevation API, I found that across 1,027 domestic-supply wells (all wells whose coordinates were available), the correlation between altitude and log(lithium concentration) is 0.46. I also checked the correlation between altitude and topsoil log(lithium concentration) in the United States, with data I found here, and, again, it was positive (0.3). So lithium exposure is probably higher, rather than lower, in high-altitude areas in the United States (which, as a reminder, have lower obesity rates).

## Palatable human food

To the extent that the mystery is that human food is unusually palatable, and not just that it’s unusually fattening, it’s hard to see how that could be explained by lithium — or any other contaminant, for that matter — being in the food, unless the contaminant happens to be tasty.

## Youth (Not mentioned in their blog post series)

As I mentioned before, people gain excess weight much more rapidly when they’re young, at all BMI levels. I think this deserves to be deemed a mystery. And, importantly, it is the opposite of what you would expect if lithium were the cause of the obesity epidemic, because among patients on lithium therapy, controlling for their dosage, young people have lower serum lithium concentrations. In the general population, too, it has been found both in Canada and Germany that serum lithium concentration increases with age.

This doesn’t make the lithium hypothesis impossible – weight gain might be primarily determined by lithium consumption or throughput rather than by serum concentration at any given time. But I think it’s still clearly the case that a positive association between advanced age and weight gain is more likely in worlds in which the lithium hypothesis is true than in worlds in which it is false, and given that the association goes the other way in our world, we should update against the lithium hypothesis accordingly.

# Conclusion, bets and bounties

When I imagine a world in which the obesity epidemic is caused by environmental lithium exposure, this is what I expect it to look like:

• some places in the Andes and the Canary Islands have way higher obesity rates than everywhere else,

• Vietnam has an obesity rate closer to that of New Zealand,

• old people are more likely to gain excess weight than young adults,

• there is a nephrogenic diabetes insipidus epidemic,

• unexplained hand tremors are common,

• genes that affect obesity are disproportionally expressed in the kidneys (in addition to the central nervous system),

• hypothyroidism rates are going up,

• countries and age groups with higher hypothyroidism rates also have higher obesity rates,

• therapeutic doses of lithium cause at least ~20 kg of weight gain on average, and

• people with chronic kidney disease sometimes mysteriously die of lithium toxicity.

As far as I can tell, none of those things are true. So my credence that lithium exposure plays a major role in explaining the obesity epidemic is very low, something like 0.1%.

## Bets

Several months ago, my husband publicly challenged the SMTM authors to a bet on their contamination theory of obesity. They have declined to bet. I’d like to remind them that the bet offer is still active.

## Bounties

I am offering a $40 bounty for each Metaculus or Manifold Markets question about the contamination theory of obesity that both I and the SMTM authors agree to be a good test of some aspect of the theory. I’ll pay for up to 5 questions. This bounty expires 90 days after the publication of this post. I am also offering a$300 bounty for anyone who writes a comment convincingly arguing that the lithium concentration data from the large and recent studies I found from France, Canada, Italy and New Zealand isn’t a good indication of how much lithium people in those countries get from their food, and that it’s actually quite likely that the average dietary intake in those countries is closer to 1 mg/​day for a normal-sized adult. Pointing out minor caveats to the interpretation of those studies would not count (though it’s definitely welcome), you have to argue that the data I found is very weak evidence that dietary lithium consumption is on the order of 10-50 µg/​day instead of 1 mg/​day in those countries. This bounty expires 90 days after the publication of this post.

Right now, whether and to whom this last bounty is paid out is fully up to my judgment. But I am also offering a $50 meta-bounty for whoever comes up with better, objective criteria for that bounty. This meta-bounty expires in 90 days, and if it is fulfilled, then the$300 bounty will expire 90 days after the fulfillment of the meta-bounty.

Update: Austin Chen has offered to match these bounties (in Manifold Markets currency).

# Acknowledgments

Thanks to Holly Elmore, Katherine Worden, Philipp Risius, @Willyintheworld and my husband Matthew Barnett for helpful comments and suggestions in earlier drafts of this post.

I do not speak for anyone other than myself, and all errors are my own.

## Animal products don’t have that much lithium, according to data from France, Canada and Italy

SMTM found, in their food literature review, that animal foods have quite a bit of lithium. They think that that might explain why vegetarian and vegan diets lead to some weight loss. Quoting from their post:

Pretty much everything we see suggests that animal products contain more lithium on average than plant-based foods. [...] It’s interesting, though not surprising, to see such a clear divide between plant and animal foods. In fact, we wonder if this can explain why vegetarian diets seem to lead to a little weight loss and vegan diets seem to lead to a little more, and also why neither of them work great.

However, this horribly fails to replicate in the Total Diet Studies that I’ve found in my research. For instance, the food item with the highest lithium concentration in the second French Total Diet Study is… definitely not something that vegans are known for not eating:

The first French Total Diet Study likewise found that meat (2 µg/​kg), milk (6 µg/​kg) and ultra-fresh dairy products (4 µg/​kg), among other animal foods, had a lot less lithium than fruits (7 µg/​kg), vegetables (14 µg/​kg), miscellaneous cereals (20 µg/​kg), nuts and oilseeds (22 µg/​kg), and Viennese bread (37µg/​kg), among other plant-based foods.

Moreover, in the Canadian TDS (a), all of the top 10 foods in average lithium concentration are vegan, as are all but 3 of the top 20, as you can see in this Google Colab notebook:

In the large Italian study I have mentioned before, the highest lithium concentration was found in fish/​seafood (median 19.10 µg/​kg) (the same finding as the first French TDS) but legumes (15.43 µg/​kg) and cereal (14.83 µg/​kg) also had a lot of lithium, whereas meat products (3.41 µg/​kg), eggs (3.87 µg/​kg) and dairy products (4.78 µg/​kg) all had low levels. This other study from Italy found that fruits and vegetables (33 µg/​kg) and cereals and tubers (31 µg/​kg) were the food groups with the highest lithium concentrations.

So it doesn’t look at all like there is a “clear divide” between plant and animal foods.

## We *do* have data on the lithium content of processed food

Again from SMTM’s literature review of the lithium content of food:

One thing we didn’t see much of in this literature review was measurements of the lithium in processed food.

We’re very interested in seeing if processing increases lithium. But no one seems to have measured the lithium in a hamburger, let alone a twinkie.

Fortunately, this is incorrect — Canada has measured the lithium in hamburgers, and the concentration they found was 58.8 ± 6.2 µg/​kg. They also measured the lithium content in pizza (42.66 ± 16 µg/​kg), French fries (26.77 ± 20.8 µg/​kg), hot dogs (25.49 ± 3.9 µg/​kg), chicken nuggets (10.78 ± 3.4 µg/​kg), fried rice (12.11 ± 2.8 µg/​kg), prepackaged sandwiches (27.14 ± 1.3 µg/​kg), and other types of fast food.

France, too, has measured the lithium concentration of a variety of processed food items, in its first and second Total Diet Studies.

## Factual inaccuracies and misrepresentation of sources in SMTM’s posts about lithium

Since we’re already here, I decided to point out and correct a few claims that the authors of SMTM have made in posts about lithium that are not supported by their own sources.

### No, Texas counties with higher lithium levels are not more obese

In Part VII: Lithium (a), the SMTM authors say:

In Texas, a survey of mean lithium levels in public wells across 226 counties (Texas has 254 in total) found lithium levels ranging from 2.8 to 219.0 ng/​mL. Now Texas is not one of the most obese states — but it tends to be more obese along its border with Lousiana [sic], which is also where the highest levels of lithium were reported.

However, if you look at the source, their map of lithium levels across Texas counties actually says the opposite – that counties along the border with Louisiana have lower lithium levels than other counties (though it’s a bit confusing because on the map darker areas represent lower levels):

Someone else has already pointed this out in the comments of that post, several months ago, as have I, on a 05/​08/​2022 Twitter thread tagging the SMTM authors, but the post has not been fixed, and the authors have not acknowledged or addressed the error in any way.

When you calculate the correlation between log(water lithium levels) and log(obesity %) in Texas, you find that it is −0.13.

### No, obesity in the West Bank was not 50% in men in 2003

Also from Part VII: Lithium (a):

obesity in the West Bank is pretty high — as high as 50% in men in 2003!

Again, that is not supported, but is instead contradicted, by the authors’ source. It says:

The prevalence of obesity was 36.8 and 18.1% in rural women and men, respectively, compared with 49.1 and 30.6% in urban women and men, respectively.

I pointed that out in a comment, but they have not edited their post.

### No, you did not find hints that people on Samos Island are about as obese as Americans

From Interlude H: Well Well Well (a):

in our first post on lithium, we found hints that people on Samos Island are about as obese as Americans.

Their first post on lithium (a) in turn says:

In Greece, lithium levels in drinking water range from 0.1 ng/​mL in Chios island to 121 ng/​mL on the island of Samos, with an average of 11.1 ng/​mL. Unfortunately there’s not much data on the prevalence of obesity in Greece, but we can conduct some due diligence by checking a few of these endpoints. Samos, with the highest levels, is the obvious place to start. On Samos, 10.7% of children aged 3-12 are overweight, compared to 6.5% on the island of Corfu. A full 27% of high schoolers on Samos island were overweight in 2010, and 12.4% were obese. In comparison, about 12.5% of American high schoolers were obese in the same period.

The comparison with American high schoolers in that paragraph is not appropriate. The US uses a different method for defining childhood obesity than the rest of the world. Remember that the definition of obesity in adults (BMI 30 kg/​m) is a bad fit for children and adolescents, who tend to be naturally thinner, so obesity cutoffs are rather defined by percentiles. And whereas the US uses cutoffs based on data from American children (a), the Samos island paper uses cutoffs adopted by the International Obesity Task Force, which are different.

I have attempted to point this out by making a comment on their post, but they have not approved the comment.

Moreover, Chios and Samos, despite their very different drinking water lithium levels, have rather similar obesity rates: 10% of teenagers in Chios are obese and 25.5% are overweight.

### (Added on July 7, 2022) No, dry weight is not the same thing as fresh weight

In a post (a) that was published a week after this one (and which I address in these comments), the SMTM authors say the following:

Hullin, Kapel, and Drinkall (1969) found more than 1 mg/​kg [of lithium] in salt and lettuce, and up to 148 mg/​kg in tobacco ash. [...] Magalhães et al. (1990) found up to 6.6 mg/​kg in watercress at the local market.

They present those studies as contradicting the Total Diet Studies I’ve found (which report usually a few tens or hundreds of micrograms per kilogram of lithium in food) but fail to mention that both Hullin, Kapel, and Drinkall (1969)‘s estimate of lithium concentration in lettuce, and Magalhães et al. (1990)’s estimate of lithium concentration in watercress, had the dry weight of those plants as the denominator, not their fresh weight. This is important because both of those plants are known to be 90%+ water by weight, and Total Diet Studies report lithium content per unit of fresh weight, so those estimates are not at all comparable.

Later on in the post, they claim that some food in Brazil has more than 1 mg/​kg in lithium concentration, a claim that is probably based on Magalhães et al. (1990) (the only study they cite that seems to be from Brazil), and use that as evidence that the Total Diet Studies are wrong. And, again, that is very misleading. The very paper they cite explicitly estimates that you would need to eat 400 g of watercress per day to consume 70 µg/​day of lithium (unless you go out of your way to feed more lithium to those plants as they’re growing, which is an experiment they report in the paper), which implies a fresh weight lithium concentration of 175 µg/​kg.

I have asked them on Twitter to fix this, and they haven’t yet.

Relatedly, several of the other estimates of high lithium concentration in food that they mention have dry weight as the denominator (those from Borovik-Romanova (1965) and those from Ammari et al. (2011)), but they nevertheless present them as contradicting Total Diet Studies.

# Errata

• I had originally failed to specify that the dose given to patients in Rinker et al. (2020) was 150–300 mg/​day of lithium carbonate (~30-60 mg/​day of elemental lithium). I fixed this around 8:40 PM Pacific Time on 06/​28/​2022 (the day of this post’s publication.)

1. ^

They also think that other contaminants could be responsible, either alone or in combination.

2. ^

The SMTM authors point out that one of their sources cites a 1985 EPA estimate that dietary lithium intake among Americans is 0.650 to 3.100 mg per day. However, the original source cannot be found, and this 1995 article on the EPA’s website about environmental lithium exposure makes no mention of such an estimate. It instead says,

A wide range of estimates for daily dietary intake of lithium has been reported. Several authors report estimates for the average daily dietary intake of lithium, ranging from 0.24 to 1.5 μg/​kg-day (Noel et al., 2003; Clarke et al., 1987; Hamilton and Minski, 1973; Evans et al., 1985; Clark and Gibson, 1988). A much higher estimate for daily intake from food and municipal drinking water ranging from 33 to 80 μg Li/​kg-day was reported by Moore (1995).

Moore et al. (1995) in turn seem to base their estimate of dietary lithium intake on Bowen (1979) (page 253), which estimates the following concentrations of lithium in living tissue (in mg/​kg of dry matter): “Land plants: 0.5-3.4. Edible vegetables: 0.8-1.3. Mammal muscle: 0.023.” These estimates are substantially older than ~all of the other ones I’ve found, and their country of origin is unclear.

Moore et al. (1995) then multiply those numbers by the amount of mass from each of those types of tissue that people consume on average per day (“0.34 kg meat, 0.39 kg dairy products, and 0.76 kg vegetable and grains,” according to the USDA).

The USDA report does not indicate that those are numbers for dry matter consumption. So Moore et al. (1995) seem to be multiplying the lithium concentration in dry matter by the mass of fresh matter of each type of food that people consume per day, if I’m understanding correctly. If that is what is going on, Moore et al. (1995)’s numbers substantially overestimate dietary lithium consumption, since fresh mass tends to be a lot greater than dry mass for a lot of foods.

3. ^

They can also vary depending on the method used to make the estimate. Schrauzer (2002) mentions a lot of unpublished, very high (but still mostly < 1 mg/​day) estimates of dietary lithium intake that are based on hair concentration rather than actual measurements of lithium in food.

Interestingly, the highest estimate this source mentions is for people in China, a country famously known for its devastatingly high obesity rate.

4. ^

Let’s examine the matter more quantitatively. The SMTM authors think that the distribution of lithium concentration in food is lognormal (a). Since we have Canada’s raw data, we can estimate the parameters of the lognormal distribution by using scipy.stats.lognorm.fit (a). Doing so, I estimate that 1 in 1,000,000 food samples in Canada has more than 3.2 mg/​kg of lithium. Human life expectancy is about 30,000 days, and people probably don’t consume more than 33 different food items every day, so this is more than a person would realistically encounter in a lifetime.

How well does that model fit the data? Running a Kolmogorov-Smirnov test reveals that it’s quite a good fit, and a way better fit than the heavier-tailed Pareto distribution. But if we want, we can ditch the assumption that the distribution is lognormal, and use kernel density estimation instead. Doing so, I estimate that 1 in 1,000,000 food samples have more than 1.1 mg/​kg of lithium, when I use the default parameters of sklearn.neighbors.KernelDensity.

5. ^

Note, however, that I’ve found only a few studies in which the average serum concentration was that low.

6. ^

The caveat is that patients on lithium therapy may have higher trough levels as a fraction of their peak levels.

So how should we adjust the data, in light of that? It seems, from lithium pharmacokinetics studies, that 24 hours after a single high dose, serum lithium concentration should be only two to six times lower than it was at its peak. Lithium might be cleared more rapidly at lower levels, for all we know, so these data must be interpreted in context – with food, water and air lithium concentration data in mind.

7. ^

My search string was “lithium:ti AND ‘weight gain’:ab,ti AND ([cochrane review]/​lim OR [systematic review]/​lim OR [meta analysis]/​lim)”. Embase requires institutional access; if you don’t have that you can search PubMed instead, which, like Embase, allows you to restrict your search to systematic reviews and meta-analyses. PubMed has fewer studies than Embase, but for this specific query it yielded the same relevant results.

8. ^

The guy is David B. Allison. I’d care less about the conflict of interest if that paper had ever been replicated at all, but it hasn’t. Moreover, a few months ago, I investigated whether the most popular strain of lab mice has been getting more obese since 2000, using publicly available data, and found that it hasn’t.

• I found this very convincing (pending SMTM response). Thank you.

• 28 Jun 2022 23:02 UTC
45 points
30 ∶ 11

+1.

Someone may have made this point somewhere else already, but there’s really no mystery in Americans getting fatter if we condition on the trajectory of mean calorie intake. Mean calorie intake has gone up by about 20% from 1970 to 2010 in the US, and mean body weight apparently went up by around 15% in the same period.

If we make a simplification and assume that you expend energy at a rate proportional to your body mass (reasonable because work has units of ), we would roughly expect that increasing your calorie intake by 20% permanently would mean you either have to dissipate this energy in the form of excess sweating etc. or you have to store it somehow. If we make a further simplification and assume you don’t compensate for your excess calorie intake by excess heat dissipation (which seems roughly correct empirically), we end up with your body mass having to eventually go up by 20% so that your new energy expenditure matches your higher calorie intake.

In other words, a naive picture of the energy balance of the human body suggests we should expect long-term calorie intake and long-term body mass to be roughly proportional to each other. This is close to what we find empirically: 20% increase in mean calorie intake together with a 15% increase in mean body mass from 1970 to 2010. Any difference here can be explained away by short-run convergence dynamics, which tend to be much more complicated than the long-run energy balance relations.

Here’s a passage from Slime Mold Time Mold that supports this:

Partly this is because once you gain weight, you burn more calories (because it takes more energy to move and maintain physiological function) and you need to eat more calories to maintain your weight. Studies show that people with obesity eat and expend more calories than lean people. From this study, for example, consider this sentence: “TDEE was 2404±95 kcal per day in lean and 3244±48 kcal per day in Class III obese individuals.” From this perspective, the average daily consumption per Pew being 2,481 calories per day doesn’t seem like much — that’s about what lean people expend daily. Obese individuals generally burn 3000+ kcal/​day, and while not every modern person is obese, it does make the increase from 2,025 calories per day in 1970 to about 2,481 calories per day in 2010 look relatively small.

Global warming is a good analogy here. In the long run we know e.g. the greenhouse effect should lead to a higher global mean temperature because of the energy balance of the Earth’s climate system. However, in the short run there are many places that can soak up energy: deep ocean dynamics, for instance, cause convergence to climatic equilibrium to take time on the order of hundreds or thousands of years. The human body is similar.

This might seem obvious to some people but Slime Mold Time Mold has said before that the increase from ~ 2000 kcal to ~ 2400 kcal in mean calorie intake is small. The exact quote from them is below:

It’s true that people eat more calories today than they did in the 1960s and 70s, but the diﬀerence is quite small. Sources have a surprisingly hard time agreeing on just how much more we eat than our grandparents did, but all of them agree that it’s not much. Pew says calorie intake in the US increased from 2,025 calories per day in 1970 to about 2,481 calories per day in 2010. The USDA Economic Research Service estimates that calorie intake in the US increased from 2,016 calories per day in 1970 to about 2,390 calories per day in 2014. Neither of these are jaw-dropping increases.

It’s indeed small compared to the overfeeding studies they consider (which can involve people going up to 10,000 kcal/​day in calorie consumption) but those studies are short-term and as a consequence are mainly informative about convergence dynamics and not about equilibrium sensitivities.

They later tried to address this because people picked up on it and eventually said “well, even if the 20% increase explains the obesity epidemic, that still leaves the question of why people are eating more open”. I think this is bizarre: to me it’s quite obvious that in the long run more calorie intake has to lead to higher body mass, though not necessarily in a proportional way as I’ve idealized above. They should have been focusing on the causal channel going through calorie intake from the start. Instead, it seems like to them this was a secondary channel to fall back on.

Edit: I want to point out how disturbing it is that both the post itself and my comment have been receiving many downvotes from people who don’t think it’s worth their time to explain what they think is wrong with either of them. If you want to carry on doing that then more power to you, but it’s a mode of behavior that lowers my opinion of LW as a forum, especially when the agreement karma is available to express disagreement.

• They later tried to address this because people picked up on it and eventually said “well, even if the 20% increase explains the obesity epidemic, that still leaves the question of why people are eating more open”. I think this is bizarre: to me it’s quite obvious that in the long run more calorie intake has to lead to higher body mass, though not necessarily in a proportional way as I’ve idealized above. They should have been focusing on the causal channel going through calorie intake from the start. Instead, it seems like to them this was a secondary channel to fall back on.

Calorie intake does lead to higher body mass, and 20% is a big increase. I do not disagree with you, there. However, something made people eat 20% more calories, be it palatable foods, lithium (though, now, probably not), PFAS, etc.

My hope (desperate hope, really) is if we can find the cause of the 20% increase, we can reverse the obesity trends.

• I agree with you—something is indeed making people eat more and all the interesting questions are about what that is.

I wouldn’t have written my comment if Slime Mold Time Mold had not initially claimed that 20% is a small increase and contrasted it with various overfeeding studies to “demonstrate” how it could not be an important causal node in explaining the obesity epidemic. This argument was particularly bad because they neglected to draw the important distinction between equilibrium effects and transitory or convergence dynamics.

• Yeah, I definitely agree − 20% is a big increase. 400 extra calories over a year (assuming 3500 calories = 1 pound) is an extra 41.7 pounds per year.

I was so excited by A Chemical Hunger when it was coming out. Oh, well.

• 400 extra calories over a year (assuming 3500 calories = 1 pound) is an extra 41.7 pounds per year.

In reality, you’ll stop gaining weight at some point if you increase your caloric intake once and never change it again, because your energy expenditure will rise.

But even taking that into account, it does seem to me that 456 extra kcal per day is way too much.

Here’s an illustrative calculation. Herman Pontzer has the following equations relating body weight to total daily energy expenditure in his book (figure 3.4):

The average woman in the US weighed 65.5 kg in the 1970s, and 78 kg in the 2010s, so this predicts a TDEE increase of only 134 kcal for women. For men, the figure is 160 kcal. Those numbers are about a third of 456 kcal. So yes, a 456 kcal in average daily energy intake would be a jaw-dropping increase.

Of course, this 456 kcal number is based on self-report data, so it’s not likely to be that accurate. Stephan Guyenet mentions a better estimate on The Hungry Brain based on food disappearance data from the USDA, which is only 218 kcal/​day, much closer to my estimates of how much TDEE has changed.

I agree with Eliezer et al. that CICO by itself cannot explain the obesity epidemic, but “a 456 kcal increase is not that much” is a bizarre argument.

• If something is making fat cells want to expand more and give up fat less easily, a corresponding lack of glucose or triglycerides in the bloodstream will, obviously, cause people to eat more. Early studies in overfeeding before the obesity epidemic showed that you had to overfeed people a LOT to make them gain a small amount of weight, which was immediately lost after overfeeding stopped. This is how human metabolisms used to work, before something broke them.

Imagine somebody with cancer, maybe before surgery existed and people would just walk around with giant tumors. The tumor increases your weight. The metabolic input to increase the tumor has to come from somewhere. If you measure the food intake of the person with the tumor, they’ll probably eat more, maybe possibly exercise less, over that period. It doesn’t mean they can cure their cancer by eating moderately less in proportion to how much dietary intake increases when you have a tumor; eating less would make them hungry and less active, but wouldn’t shrink the tumor, which can just go on growing regardless.

People are getting fat, so they have to eat more.

Trust me, we’ve tried eating only untasty food. It’s not that.

• I think saying “we” here dramatically over-indexes on personal observation. I’d bet that most overweight Americans have not only eaten untasty food for an extended period (say, longer than a month); and those that have, found that it sucked and stopped doing it. Only eating untasty food really sucks! For comparison, everyone knows that smoking is awful for your health, it’s expensive, leaves bad odors, and so on. And I’d bet that most smokers would find “never smoke again” easier and more pleasant (in the long run) than “never eat tasty food again”. Yet, the vast majority of smokers continue smoking:

• A personal observation regarding eating not tasty food:

I served in the Israeli army, eating 3 meals a day on base. The food was perfectly edible… But that’s the best I can say about it. People noticeably ate less—eating exactly until they weren’t hungry and nothing more than that, and many lost a few kilos.

• Adding my anecdote to everyone else’s: after learning about the palatability hypothesis, I resolved to eat only non-tasty food for a while, and lost 30 pounds over about four months (200 → 170). I’ve since relaxed my diet a little to include a little tasty food, and now (8 months after the start) have maintained that loss (even going down a little further).

• What sorts of non-tasty food did you eat? I don’t really know what this should be expected to filter out.

• This sounds like a pretty intense restriction diet that also happens to be unpalatable. But the palatable foods hypothesis (as an explanation for the obesity epidemic) isn’t “our grandparents used to only eat beans and vegan sausages and now we eat a more palatable diet, hence obesity.” It’s something much more specific about the palatability of our modern 20th/​21st century diet vs. the early 20th century diet, isn’t it? What’s the hypothesis we could test that would actually help us judge that claim without inadvertently removing most food groups and confounding everything?

• I’m going to bury this a bit deeper in the comment chain because it’s no more indicative than Eliezer’s anecdote. But FWIW,

I am in the (very fortunate) minority who struggles to gain much weight, and has always been skinny. But when I have more tasty food around, especially if it’s prepared for me and just sitting there, I absolutely eat more, and manage to climb up from ~146 to ~148 or ~150 (pounds). It’s unimaginable that this effect isn’t true for me.

• Yeah, that sounds right—with a non-broken metabolism, eating lots and lots of tasty food that’s just prepared and sitting there, to your heart’s content, should totally result in about 4 pounds of weight gain, all the way up to 150 pounds.

That’s how everybody’s metabolisms used to work.

• Do you have any empirical evidence for either of the following?

1. Farmers were historically wrong to think that free-feeding their animals would tend to fatten them up, OR they didn’t believe it has that effect.

2. Prior to the more recent novel contaminants, humans are an exception among animals in this general trend, that free-feeding tends to fatten animals up.

• Actually I’d ask about the effect of free-feeding non-domesticated animals on ecologically realistic food, rather than free-feeding cows bred to gain weight using grains.

• Why “ecologically realistic food”? And which types of realism are you going to pick?

Overfeeding and obesity are common problems in pets, which are mostly not bred to gain weight the way cows are.

My family has kept many kinds of animals. If you give bunny rabbits as much veggies as they want, a large fraction becomes obese. And guinea pigs too. And for their own favorite foods, tropical fish do too. Cats too.

In fact, I have never noticed a species that doesn’t end up with a substantial fraction with obesity, if you go out of your way to prepare the most-compelling food to them, and then give that in limitless amounts. Even lower-quality, not-as-compelling foods free-fed can cause some obesity. Do you even know of any animal species like this?!

If there is large variation in susceptibility (which there would be) to the ostensible environmental contaminant, there should be species that you can free-feed and they don’t get obesity.

• Just adding my own anecdote here, literally every time that I can recall overeating out of my own volition, it was because the food was tasty or otherwise satisfying. The connection between how tasty a food is, and how likely I am to overeat it, is such a strong connection that it might as well be treated as a law of nature.

• Doesn’t sound obviously true for me? I obviously won’t overeat food if it’s disgusting, but I’d say I’m more likely to overeat rice cakes than chocolate, for example. A lot of milder foods feel easier for me to overload on.

• That’s interesting. One caveat I should add is that I was referring to calorie overconsumption, as opposed to volume overconsumption. Rice is not very calorie dense, making it relatively easy to become full without eating many calories.

• Yeah, I was thinking of calories too. I think I could eat way too many rice cakes, reliably, day in and day out. Whereas eating even one Hershey’s bar starts to approach the level where I’d feel sick from the amount of chocolate, and want less of it around me in the future.

• How are we defining tasty foods? I’m sure if the entire world voted, chocolate would clearly be more in the “tasty food” category than rice cakes, but perhaps you really like how rice cakes taste?

• I think people are reading into my comment plenty of things that I didn’t say. My only actual claim is that the 20% increase in calorie intake is sufficient to “explain” or “account for” the increase in body mass from 1970 to 2010. It’s not small and the claim by SMTM that it’s small is inaccurate.

Your comment is about why people would be taking in more calories and I don’t think I have any special insight into that issue. I just don’t think SMTM has any special insight to it either. Your argument is obviously logically possible but I wouldn’t bet a lot of money that it would turn out to be the right explanation.

• I’ll try rephrasing, somewhat overstating the strength of the reasoning (taking it from probabilistic to logical) in case that causes a basic idea to be clearly communicated that was obscured by probabilism.

If an increase in calorie intake was itself sufficient to produce an increase in fat mass in otherwise metabolically high-functioning adults, we’d have seen a different result from pre-obesity-epidemic experiments in overfeeding. This rules out the direction of causality “mere overeating” → “obesity”.

Any hypertrophy of fat cells, in turn, will causally require more nutritional intake to feed the hypertrophy, just like a cancer growing, or any other body part growing, will require more nutritional intake. So once you observe a cancer or a huge fat cell mass or any other diseased body part growing, you already know the person already took in that much food, both to grow the cancerous body part and sustain it; you shouldn’t be surprised to look back at the cancer patient’s caloric consumption record and find an excess; so finding that excess consumption shouldn’t update you at all about the cause of the malevolently growing body part.

You’re taking causality that must at least run from “fat cell hypertrophy” → “excess consumption” and already fully explains away the presence of an observed correlation, and then adding on a causal postulate that runs the other way—a direction of causality that would be theoretically possible in a world with no overfeeding experiments one way or the other, though not supported even there, since there is no otherwise unexpected observation which it explains; but which in our world is ruled out by the results of overfeeding experiments, which tested the results of experimental-intervention-produced excess calorie consumptions in metabolically healthy individuals before the obesity epidemic.

To further oversimplify the oversimplification: the logic you’re deploying for obesity would also work to conclude that overeating causes cancer, and therefore Proves Too Much.

The only reason why “overeating caused this huge fat mass to grow inside my body” sounds more plausible than “overeating caused this huge tumor to grow inside my body” is that the former theory follows the Sin Theory of Obesity in which obesity is a punishment for the sin of gluttony, while the latter theory is incongruent with simple just-world hypotheses as of the 21st century in Western societies. Both are ruled out by experiments showing that (in metabolically healthy individuals before the obesity epidemic) a randomized experimental intervention to add overeating does not produce obesity any more than it produces tumors.

• The only reason why “overeating caused this huge fat mass to grow inside my body” sounds more plausible than “overeating caused this huge tumor to grow inside my body” is that the former theory follows the Sin Theory of Obesity

I think the first sounds more plausible because the story “humans store caloric excess as fat in times of plenty and burn it off in times of scarcity” is the kind of thing that we should have as a hypothesis-under-consideration before we look at the link between calorie intake and body mass. Whereas “humans store caloric excess as cancer” (or as fetuses) isn’t. And if that story is true, then “eating lots of caloric excess causes lots of fat to be stored” isn’t automatically true, but again it’s definitely something we should have under consideration.

So if your line here is meant to be taken a priori—that is, if you’re saying “even without actually looking at the link between caloric intake and body mass, there’s no reason to believe overeating-causes-fat any more than you’d believe overeating-causes-cancer”, then it seems just wrong.

Maybe you meant it a posteriori? Something like “okay but overeating studies show that eating lots of caloric excess doesn’t by default cause lots of fat to be stored, so you no longer have a plausible explanation”?

But then at least two other reasons come to mind for why overeating-causes-fat might still seem more plausible than overeating-causes-cancer. One is that someone might not believe that studies show what you think they show. Another is that someone might just be bad at propagating updates. Currently, these both seem more likely to me than your “sin theory” theory.

• I strongly disagree with this interpretation of those overfeeding studies. From what I can tell (though I couldn’t access every study SMTM cites), “overfeeding” is usually defined relative to the output of one of the typical BMR/​TDEE estimation formulas given a person’s parameters, not based on actual measurement of a subject’s TDEE. Those formulas are fine for a baseline guess, but even the most accurate ones are going to be substantially off in either direction for a fair number of people! Some of the difference is unaccounted-for NEAT, some of it is differences in absorption efficiency, some of it is probably other factors we don’t understand yet. Given the known reality of interpersonal variation in what your actual calories in and out are relative to their naive estimates, some subjects not gaining weight while “overfeeding” is exactly what you’d expect to see.

A fun fact: my estimated “effective TDEE” is (averaged over months) pretty consistently around 3300 cal/​day for the past 18 months—rarely more than +/​- 100 cal/​day off in either direction—whereas the best formula I could find (using my body fat %, as actually-measured by a DEXA scan) says it should be something more like 2600-2800 cal/​day. This is based on weighing my body daily and recording the caloric intake from actually-everything I eat, almost always weighing food when necessary rather than coming up with estimates.

• I think I understood what you’re saying the first time around and again I agree that your account of things is certainly possible, but even in your case the tumor or fat mass has to be sustained by calorie consumption from the outside. The increase in calorie intake we’ve seen is about the amount we would have expected if someone had just told us that people are 15% fatter on average without any increase in exertion or heat dissipation to compensate for that.

Another way to say this is that I’m just making a claim about the conditional expectation E[average body mass increase | average calorie consumption increase = 20%] and pointing out this expectation is not far off from the actual observed body mass increase we see. In that sense the increase in calorie intake can account for the increase in body mass in correlational terms. The question of why both of these variables went up, though, is difficult and their level is obviously not determined by this argument.

Externally, why people feel the need to keep eating until they become obese is not a question with a clear (to me) answer. It could be because there is some process that’s operating in the body that’s taking priority over other activities and hoarding a lot of the energy intake to produce fat cells, which I think is your story. However, it could also be that some part of the brain is malfunctioning and leading the lipostat to be poorly calibrated. It could also be that the food you’re eating messes with the natural feedback loops in your body that are supposed to make you feel full when you’ve eaten enough.

I think this question is interesting and your account is logically possible. I just think that

1. I don’t have any special insight into which account is right, and

2. I don’t think your particular explanation is favored that much over other competing explanations.

I don’t think the overfeeding experiments provide strong evidence for your scenario, though I agree that they should be a Bayesian update in favor of accounts in that broad neighborhood. What would convince me is experiments which involve smaller increases in calorie intake but sustained over much longer periods of time, on the order of a year or so. If such experiments failed to find an effect that would be a strong update for me towards your view. Right now I buy the cancer analogy on conceptual grounds but I don’t think we have enough evidence to conclude obesity is like cancer in this regard, though it very well could be the case.

To give an analogy of my own, the overfeeding studies look similar to attempts to settle disputes about which programming languages are best for productivity by asking undergraduates to complete some simple tasks in them over the course of a few weeks. What really matters is how you do when you’re working with big and complex software in the real world that has to be developed and maintained by large teams with turnover for years, sometimes decades; but that obviously doesn’t lend itself to a simple experimental design so people still keep arguing about it.

• Retrying again:

By the same reasoning:

“Pregnancy” probably isn’t a thing. “Pregnant” people eat around 500 more calories per day. This is sufficient to explain all the weight gain from “pregnancy” without supposing anything other than thermodynamics at work—anyone who eats an extra 500 calories per day will probably gain that much weight over the course of 40 weeks.

• I think Ege’s alleging that SMTM presented two causal graphs:

1. calories → ? → weight gain

2. calories → weight gain

Ege’s saying that 2 is simpler and sufficient, so we don’t need to posit a ? in the middle.

You’re pointing out that we still need to address a third causal graph:

1. ? → calories → weight gain

Edit: And maybe that there’s also a scenario where ?, calorie intake, and weight gain are all in some complex interrelationship. Maybe contaminants cause more fat deposition and less energy and more hunger, thereby increasing weight gain per calorie, increased calorie intake, and increased contaminant intake via food. Or something.

Ege’s agreeing with you, but wants to emphasize that this is compatible with criticism of SMTM’s alleged emphasis on graph 1.

Note: I say “alleged” only because I’m sidestepping evaluating the truth of Ege’s claim. Just trying to clarify what it is (AFAICT).

• I don’t agree with this presentation of what I’m saying.

I’m not terribly sure what SMTM means when they say “the increase in calorie intake is small”, but all possible interpretations of their claim seem wrong. For instance, one plausible interpretation in causal graph lingo is “if you applied the do operator on calorie intake and raised it by 20%, we would have seen an increase in body mass that’s significantly smaller than what we’ve actually seen”. I think this claim is wrong, basically for long-run energy balance reasons.

I’m not saying anything else about the structure of the causal graphs, which could be arbitrarily complicated and involve arbitrarily many nodes and dependencies. I’m just saying that if you apply the do operator on calorie intake and raise it by 20% then you’d get an increase in mean body mass that’s about as big as what we’ve seen.

• Thanks for clarifying that I misrepresented your view. Based on your response here, you’re pointing out that there’s a strong correlation between increased caloric intake at the population level, and increased obesity. You are also saying that the explanations you’ve read from SMTM for why this correlation exists seem wrong, and also that they underestimate the magnitude or importance of the caloric intake.

WRT Eliezer’s arguments, you seem to be agreeing that there may be some underlying force(s) causing that increased caloric intake. However, you are very uncertain about which, if any, of the hypothesized forces(s) are the true causes of increased caloric intake.

Eliezer and others seem to be perhaps mistakenly interpreting you as denying the existence of, or “need for,” a deeper explanation for increased caloric intake and consequent weight gain. You are confused about why they are making this mistake.

Is that a more accurate account of your position?

• Yes, this summary is accurate.

I’m not sure who is “to blame” for the miscommunication but I suspect I simply was not clear enough in my top comment. Now it’s likely too late to clear up the issue for most readers as they won’t be following the developments in this thread.

• I’m just saying that if you apply the do operator on calorie intake and raise it by 20% then you’d get an increase in mean body mass that’s about as big as what we’ve seen.

This is “assuming there’s no link “increased calorie intake → increased energy expenditure”″, right? I think one of the things Eliezer is saying is that there seems to have been such a link in the past and now there isn’t /​ it’s much weaker.

• That’s not quite true—there is at least the naive link that a higher equilibrium body mass leads you to expend more energy in daily activities even if you exercise the same amount as before. In my very naive model I assume these are directly proportional, but Natalia cites some better research that does a log-linear regression of calorie expenditure on equilibrium (I think? I didn’t check this part) body mass which seems to be more accurate empirically.

I think it’s unclear whether we had the link you mention in the past, too. We definitely had a correlational link: people who did hard labor and ended up exercising a lot every day took in much more calories, as we would expect, and they were generally not obese. However, I think my argument would work just as well in the past if you just applied the do operator on calorie intake per day and looked at the causal impact on equilibrium body mass, as I don’t think there’s evidence that there’s a big downstream link from calorie intake per day to exercise.

• You left out weight gain->calories, as in the pregnancy example, and calories ← X → weight gain.

• I don’t understand why you’re “retrying”. I already agree with your point and you not saying “yes, you already agree with me” is quite confusing to me. As I say in my comment:

Externally, why people feel the need to keep eating until they become obese is not a question with a clear (to me) answer. It could be because there is some process that’s operating in the body that’s taking priority over other activities and hoarding a lot of the energy intake to produce fat cells, which I think is your story.

Do you think this characterization of your position is unfair or wrong? If so, why?

As far as I can see the only object-level point I disagree with you about is that I don’t think the evidence for obesity being like cancer or pregnancy is as strong as you seem to think it is. It’s definitely possible for it to be like that but I would bet against it at even odds. I explain this here:

I don’t think the overfeeding experiments provide strong evidence for your scenario, though I agree that they should be a Bayesian update in favor of accounts in that broad neighborhood. What would convince me is experiments which involve smaller increases in calorie intake but sustained over much longer periods of time, on the order of a year or so. If such experiments failed to find an effect that would be a strong update for me towards your view. Right now I buy the cancer analogy on conceptual grounds but I don’t think we have enough evidence to conclude obesity is like cancer in this regard, though it very well could be the case.

On top of that I also have a separate disagreement with you about emphasis in the context of my comment, since the point of my top comment is to draw attention to 400 kcal/​day not being a small increase in calorie intake. You agree with me about this but you just don’t think it’s worth focusing on, probably because you think it’s a trivial observation. I still think it’s something that should be corrected given that SMTM explicitly said that it’s a small increase.

• As far as I can see the only object-level point I disagree with you about is that I don’t think the evidence for obesity being like cancer or pregnancy is as strong as you seem to think it is.

Some people certainly are obese because of literal cancer and literal pregnancy. We seem to have strong evidence for that.

The interesting question is about how much of the obesity pandemic is explainable by such factors and not whether evidence for such factors exists.

We certainly don’t see enough pregnancy and cancer to explain the obesity epidemic but there might be other factors that are similar but harder to see. Thermodynamic arguments don’t help us rule out other effects that are similar to pregnancy/​cancer.

• I agree with everything you said, so again I’m confused why you thought you should make this comment.

I feel like I don’t really disagree with most of the commenters but they either think I do disagree with them or that I did a very bad job of communicating exactly what my point was. It’s hard for me to understand.

• (The thread continues to look to me like what I described here https://​​www.lesswrong.com/​​posts/​​7iAABhWpcGeP5e6SB/​​it-s-probably-not-lithium?commentId=NxzEfuyGfuao25mrx

i.e. Yudkowsky is responding to the part of your original comment where you said

there’s really no mystery in Americans getting fatter if we condition on the trajectory of mean calorie intake

)

• I still stand by this claim, again with the caveat that you take it as a correlational use of the word “explain” (which is not at all uncommon e.g. when talking about “fraction of explained variance” and so forth) and not one that suggests a causal explanation of the form “people wanted to eat more food, so they ate more food, so they got fatter as a result”.

• Ok. My main point is just to clarify that other people are reading you as talking about explanation in general, not just strictly correlational explanation (if that’s what’s happening).

I do also think that’s not a great use of the word “explain” and “mystery”, because it’s not why the colloquial word is useful. The colloquial words “explain”/​”mystery” are useful because they index “more information and ideas given/​needed about this”. So just because X correlationally explains Y, and X is true, doesn’t mean there’s no mystery about Y.

• I never said there’s no mystery about Y, just that there’s no mystery about Y being true conditional on X being true.

It’s a fair point that my usage of “explain” and “mystery” confused some people but I’m not too sure how else I would have made my point. Should I have said “people today are eating about as much more compared to the past as we would expect given how much fatter they’ve gotten”?

• That’s clearer to me, yeah. It’s unambiguous that it’s about conditional prediction (“we would expect given”) rather than explanation-in-general.

• In your original comment, you wrote:

Someone may have made this point somewhere else already, but there’s really no mystery in Americans getting fatter if we condition on the trajectory of mean calorie intake.

Read literally, this says: There’s a mystery of why intake went up. Conditioned on intake up, there’s no mystery of why fat went up. I think this isn’t right. If we agreed that sustained high intake implies weight increase, it’s still not right. That’s because conditional probability isn’t the same as explanation, and if there’s a mystery, what we’re after is explanation. That’s one of the points of the tumor example: If fat causes intake, then saying “there’s no mystery about fat” is pointing away from the explanation of intake, which is that fat causes intake and something causes fat.

They later tried to address this because people picked up on it and eventually said “well, even if the 20% increase explains the obesity epidemic, that still leaves the question of why people are eating more open”. I think this is bizarre: to me it’s quite obvious that in the long run more calorie intake has to lead to higher body mass, though not necessarily in a proportional way as I’ve idealized above. They should have been focusing on the causal channel going through calorie intake from the start. Instead, it seems like to them this was a secondary channel to fall back on.

Taken literally, this seems to be consistent with beliefs of people who disagree with you? It’s just that they have different conclusions about the causality going through calorie intake. Interpreted that way, I don’t see how this statement is consistent with saying “there’s really no mystery in Americans getting fatter”.

On the other hand, I think it’s just true that conditioned on the increase in calorie intake there’s no mystery in the increase in body mass. I don’t understand why you’re disputing this point. You can say this is not an interesting observation (which I agree with, though as far as I can tell SMTM did not, which is why I wrote my comment) but I don’t see how you can say it’s not right.

My impression is that some people are engaging in a bizarre combination of steelmanning SMTM’s point while strawmanning my own. SMTM didn’t make the best version of the claim they could have made, they made the actual claim that I quote in my post. I think their claim is wrong. Do you disagree with this or not?

• Meta: my interest here is to see if there are miscommunications here that I can clear up. I’m not carefully following the object-level debate. (In particular, I think that you Ege should feel extremely free to ignore what I’m saying as unhelpful to you; if I’m not helping you understand what’s happening in the thread then I’m not doing what I’m trying to do.)

On the other hand, I think it’s just true that conditioned on the increase in calorie intake there’s no mystery in the increase in body mass. I don’t understand why you’re disputing this point.

(Note: you did mention causality in the passage I quoted: “They should have been focusing on the causal channel going through calorie intake from the start.” That’s not a claim about what causes what, but it is a claim about what questions are the right questions to ask.)

I’m pointing at the word “mystery”. I’m saying that to me, “mystery” means “explanation wanted”. I’m saying that just because P(X|Y) is high, doesn’t mean Y is a good explanation of X. (For a silly example, setting Y=”X and 2+1=3″ makes P(X|Y) = 1 and is obviously doesn’t explain anything.) I agree (based on my preconceptions, ~0 independent data) that P(body mass high | high sustained intake in the wild) is high. My read of some of the comments on your comment, e.g. Yudkowsky’s, is that they are taking you to be saying “high intake explains fat, such that there is no further interesting question about fat, though there may be further questions about why high intake”, based on the passages from your comment I quoted. Reading your comment closely, you didn’t actually say that, if by “conditional on Y, there’s no mystery about X” you mean “P(X|Y) is high”. In fact, what you said is consistent with believing that “Alice is fat” explains (in the contextually relevant sense) that “Alice has high intake”, and you recommend that if you believe this then you should “focus[] on the causal channel going through calorie intake”, i.e. investigate why Alice is fat in order to explain her high intake.

SMTM didn’t make the best version of the claim they could have made, they made the actual claim that I quote in my post. I think their claim is wrong. Do you disagree with this or not?

I don’t know. I think your argument makes sense, but the actual situation is going to be more complicated.

• Do you know, if we also observe an obesity-epidemic in the subgroup of people who average 25k+ in daily steps? That step-requirement is a good, high standard of “metabolically healthy” to isolate.
I belong in that group these days and it feels natural, relaxed and I feel far more energetic than when I was averaging 7k daily steps and was the sedentary nerd cliché, about a year ago. Now I am a nerd, who takes two walks per day, almost never sits and either stands or uses his office treadmill when on the computer.
Even before, I never really got fat. But I feel, that I might not have been “metabolically healthy”, because now I feel better. So I strongly suspect that a far higher than average step-count is a hard requirement for being “metabolically healthy”.

• I hear that “pregnant” people also do less mountain-climbing, even if they were exercising healthily before. No wonder they gain weight! Do we even need to postulate “pregnancy” as a condition, when their caloric intake and reduced exercise seems adequate to explain all of the observed weight gain?

• I was not responding to your pregnancy-argument, but to your post higher up in this subthread from 3 days ago. The threading makes this a bit confusing.
Also should have specified what I was responding to the last paragraph:
”Both are ruled out by experiments showing that (in metabolically healthy individuals before the obesity epidemic) a randomized experimental intervention to add overeating does not produce obesity any more than it produces tumors.”

Is there actually an obesity epidemic among people who walk more than 25k steps per day? (or is something like that currently known).

EDIT:
I suppose my hypothesis is:
Living a non-sedentary lifestyle meaning less than 20 minutes of sitting per day, 25k-ish steps per day somewhat equally spread out over all waking hours makes the “weight-gain -=> obesity”-phenomenon impossible, because it’s a sufficient requirement for robust metabological health.
If that was true, it might not answer what is behind the obesity epidemic.
But that’s what I would study, to check if it’s a cure or reliable prevention.

I’d say 90% chance of this being true, but mostly on intuition and with high model uncertainty.
And I don’t know, if we know enough to answer this question, because non-sedentary lifestyles like that are fairly niche in all Western societies. But I recently figured out, that they’re not all that hard to adopt.

EDID2: Actually, I’d say the 90% applies to it being “reliable prevention”. No clue, how curative that would be.
I never had to really lose more than a couple kg of fat. [and “had to” is really exaggerating a lot]
From what I observe, it seems somehow impossible for really fat people to become not fat, despite heroic struggles which have always been strange to observe from the outside.

• Is there any solid evidence that walking 25k steps per day will solve the obesity epidemic? I ask this because it’s genuinely a remarkable claim, one that if verified and implemented would save huge numbers of lives and hundreds of billions in medical expenses. The literature mostly seems to indicate that increased exercise doesn’t have dramatic effects on obesity.

• There is not. That’s why I was asking him if he knows. I was not interested in the effect of exercise. Exercise means, you do some activity a couple times per week.
I’m interested whether the obesety epidemic only affects the sedentary populatrion.
And if being or becoming non-sedentary is protective or curative.
25k steps for me means, that my treadmill is running constantly when I’m on my computer.
This is not really exercise. Movement is just my default state.

In that way, I have become closer to what an EAA-hunter-gatherer, than to a sedentary office worker does with his body.
[or I would, if this had been my lifetime norm instead of something I still get used to]
If the human body was sold as a machine, the sedentary lifestyle probably would void your warranty, because it’s rather extreme (dis)usage. Sedentary people being unhealthy is not surprising.
It’s surprising that some sedentary people aren’t.

Anyway, “being in near-constant motion” is too specific/​complicated a metric.
So I’d just look for a step count high enough, that’s only feasibly doable by a non-sedentary person like me. Though, I guess any daily jogger can probably match or exceed 25k steps per day.
The group of people whose 80th quantile waking hour still has >1k steps.
That’s probably the better proxy, come to think of it.

• All right, here’s my crack at steelmanning the Sin of Gluttony theory of the obesity epidemic. Epistemic status: armchair speculation.

We want to explain how it could be that in the present, abundant hyperpalatable food is making us obese, but in the past that was not so to nearly the same extent, even though conditions of abundant hyperpalatable food were not unheard of, especially among the upper classes. Perhaps the difference is that, today, abundant hyperpalatable food is available to a greater extent than ever before to people in poor health.

In the past, food cultivation and preparation were much more labor intensive than in the present, so you either had to pay a much higher price for your hyperpalatable food, or put in the labor yourself. Furthermore, there were fewer opportunities to make the necessary income from sedentary work, and there wasn’t much of a welfare state. Thus, if you were in poor health, you were much more likely in the past than today to be selected out of the class of people who had access to abundant hyperpalatable food. Obesity is known to be a downstream effect of various other health problems, but only if you are capable of consuming enough calories, and have access to food that you want to overeat.

Furthermore, it is plausible that some people, due to genetics or whatever, have a tendency to be in good health when they lack access to abundant hyperpalatable food, and to become obese and thus unhealthy when they have access to abundant hyperpalatable food. Thus there is a feedback loop where being healthier makes you more productive, which makes hyperpalatable food more available to you, which makes you less healthy, which makes you less productive, which makes hyperpalatable food less available to you. Plausibly, in the past, this process tended towards an equilibrium at a much lower level of obesity than it does today, because of today’s greater availability of hyperpalatable food to people in poor health.

It is also plausible that our technological civilization has simply made considerable progress in the development of ever more potent gustatory superstimuli over the past century. This is a complex optimization problem, and it’s not clear why we should have come close to a ceiling on it long before the present, or why just contemplating the subjective palatability of past versus present-day food would give us conscious awareness of why we are more prone to overeating the latter.

Both of these proposed causes are consistent with pre-obesity-epidemic overfeeding studies of metabolically healthy individuals failing to cause large, long-term weight gain: They suggest that the obesity epidemic is concentrated among metabolically unhealthy people who in the past simply couldn’t afford to get fat, and that present-day food is importantly different.

• [ ]
[deleted]

• Adderall worked for you. It didn’t work for me.

• Adderall caused weight gain for me, and anecdotally also for a close friend of mine. Wellbutrin works, though, at least for me personally.

Lots of drugs have effects that vary wildly between different individuals (and they may even sometimes cause paradoxical effects), so I’m not sure that variance in response to amphetamines is necessarily that much of a hint about what is causing the obesity epidemic. If semaglutide works universally, or nearly so—and early studies are very promising—then that might be a strong hint as to what is causing the obesity epidemic.

• If semaglutide works universally, or nearly so—and early studies are very promising—then that might be a strong hint as to what is causing the obesity epidemic.

Relatedly, this seems to be the distribution of weight changes on 15 mg of tirzepatide + lifestyle interventions, compared to lifestyle interventions alone (over 72 weeks, I think):

• This guy says it’s fructose, plus salt and MSG. “Nature puts a “survival switch” in our bodies to protect us from starvation. Stuck in the “on” position, it’s the hidden source of weight gain, heart disease, and many other common health struggles. But you can turn it off.” I think he’s on to something; since I’ve been following his recommendations, I’ve been able to lose weight again ( ~9 kg since the end of April).

• there’s really no mystery in Americans getting fatter if we condition on the trajectory of mean calorie intake. Mean calorie intake has gone up by about 20% from 1970 to 2010 in the US, and mean body weight apparently went up by around 15% in the same period.

I feel like you’ve missed SMTM’s central point. Sure, people are eating more. The main question is why people eat more. For example, I used to weigh 172 pounds in the Philippines 4 years ago; now I weigh about 192 in Canada. I used to think my overweight best friend was overfeeding me (well, he did), but since he moved away two years ago, I’ve actually gained weight somehow. I have a mild sense of being hungrier here. Presumably I am eating more, but why?

(Having said that, it looks like OP has done great work and this is a big red flag:)

I have attempted to make a comment on SMTM’s post linking to many of those studies, but they have not approved the comment. I have also attempted to contact them on Twitter (twice) and through email, but have not received a reply. All of this was over one week ago, and they have, since then, replied to other people on Twitter and approved other comments on their post, but haven’t commented on this. So I have no idea why their literature review excludes these studies.

...Note: I have attempted to make some of those points in the comment section of SMTM’s last post about lithium, but they never approved my comment....

...I have attempted to point this out by making a comment on their post, but they have not approved the comment....

• (Having said that, it looks like OP has done great work and this is a big red flag:)

I have attempted to make a comment on SMTM’s post linking to many of those studies, but they have not approved the comment. I have also attempted to contact them on Twitter (twice) and through email, but have not received a reply. All of this was over one week ago, and they have, since then, replied to other people on Twitter and approved other comments on their post, but haven’t commented on this. So I have no idea why their literature review excludes these studies.

This isn’t the core of why I think you think that’s a red flag, but for the record I don’t think a week is that much time to respond to public criticism. I have many important emails I don’t reply to for longer.

• FWIW, the first time I contacted them about those studies was 15 days before the publication of this post.

• I was thinking about comment approval more than response [and to make that clearer, I appended to my quotation above]. I’ve been perma-declined myself, not fun. Unfortunately if it’s approved now there will be a question as to whether it was approved now in response to an ultra-popular LW post.

• I didn’t downvote you, I think you are eloquently arguing your point here! But I’m not entirely sure that the SMTM take is quite as bad as you make it out to be.

An average of 400 extra calories a day isn’t small on its own, but I think the SMTM argument is that it’s small compared to historical variation in caloric intake, and small compared to variation among humans in general today. In other words: there were likely times and cultures historically where average calories consumed was higher or lower than today by more than 400 calories—why wasn’t there an obesity epidemic previously when caloric intake was higher? Why, 100 years ago, were not the people eating 400 extra calories a day all obese?

I clearly found it more a more compelling argument that you do. Like you, I read the SMTM contaminant argument as essentially saying “historically there has been some process that kept calories consumed and calories expended in relative sync; that process has been disrupted”—and the argument that “400 calories per day explains the weight gain” isn’t really a counterargument to this?

I’ll point out one more aspect that I think you may want to consider. You write: “to me it’s quite obvious that in the long run more calorie intake has to lead to higher body mass”—but this is a statement that is somewhat circularly derived from today’s observations. 100 years ago, when very few people were obese, this statement might not be obvious at all. One might instead conclude that people with higher calorie intakes are compelled to burn more calories through manual labor, exercise, heat generation + sweating, etc.

Lastly, and obviously you know this on some level, but the fact that increased food consumption correlates with obesity, does not imply that that consumption causes obesity. SMTM argue that some external factor causes obesity; if so, increased food consumption would be a result of the body trying to maintain that weight. As you note, a 15% increase in body mass requires a 20% increase in caloric intake to sustain—if an external factor is increasing the lipostat, we would observe exactly what we observe today as well. It’s dangerous to point the causal arrow in either direction without more evidence.

And, speaking of evidence: the overfeeding studies are interesting in part because they at least resolve the question of whether and how much short-term overeating causes body mass increases; you’re 100% correct that they don’t resolve the question of whether long-term overeating also causes body mass increases, and it would be super interesting to see if a long-term (say, 1 year) 400-calorie increase in consumption (that somehow doesn’t come from changes in diet; maybe just eat an extra 20% at every meal?) causes weight gain.

As far as I know, no one’s run a long-term weight gain study—but we do have the super confusing result that a 30-40% decrease in calories is hard to sustain and the resulting weight loss plateaus at about a 10% decrease [0], suggesting that there’s more going on than the simple linear relation.

• An average of 400 extra calories a day isn’t small on its own, but I think the SMTM argument is that it’s small compared to historical variation in caloric intake, and small compared to variation among humans in general today. In other words: there were likely times and cultures historically where average calories consumed was higher or lower than today by more than 400 calories—why wasn’t there an obesity epidemic previously when caloric intake was higher? Why, 100 years ago, were not the people eating 400 extra calories a day all obese?

Variation among humans can be caused by variation in their metabolism (or variation in how much they exercise) that changes the amount of energy they expend per unit mass without being inconsistent with the energy balance argument. There’s a lot of place variation in the cross section can come from other than calories consumed—I don’t think that’s actually that relevant to understanding trends in obesity. Energy balance can hold at any level of calorie intake so the question is why you settle on one point of equilibrium and not all the others, given that you’re the one making the decisions about how much to eat.

As for historical data, I’m not convinced there’s ever been a time when mean calorie intake in a reasonably large country was ever as high as it is in the US today. There’s of course been plenty of variation but I’d expect the variation to show up in body mass if it were sustained.

I clearly found it more a more compelling argument that you do. Like you, I read the SMTM contaminant argument as essentially saying “historically there has been some process that kept calories consumed and calories expended in relative sync; that process has been disrupted”—and the argument that “400 calories per day explains the weight gain” isn’t really a counterargument to this?

I’m not really convinced by the claim that what’s happening now is historically unprecedented and I think most of the work there is being done by summarizing the phenomenon in terms of obesity statistics instead of mean body mass. I think if we looked at the historical trajectory of mean body mass it would not really look like anything exceptional is happening today in terms of some fundamental balance process being thrown off.

I want to repeat: the point of my comment is not that “why are people eating more now?” is a question that shouldn’t be answered; it’s that the claim about 400 kcal being too small of an increase is just wrong. If you agree with that then you should just agree with my comment because that’s the only claim I make.

As far as I know, no one’s run a long-term weight gain study—but we do have the super confusing result that a 30-40% decrease in calories is hard to sustain and the resulting weight loss plateaus at about a 10% decrease [0], suggesting that there’s more going on than the simple linear relation.

I think my argument says nothing about how hard to sustain a decrease in calorie intake is—it’s consistent with your body making arbitrarily strong protests at having to burn its stores of fat and try to induce you to eat more to compensate. I’m agnostic on that point and I think it’s obviously an interesting question to look into.

• Farm laborers historically ate a lot of calories just to be able to get through their days. Their calories weren’t very appetizing, but they had to eat a lot because they burned a lot.

• That makes sense to me but I’d really need to see the data on how many calories they ate in 1700. I notice I would still be surprised if an average farm laborer in 1700 in prime age ate more than 2400 kcal/​day. It’s not really relevant to my main point but if you have some data proving that I would be interested to see it.

• Per Jeffrey L. Singman, Daily Life in Medieval Europe, Westport, Connecticut: Greenwood Press, 1999, P. 54 − 55 (and text copied from https://​​stores.renstore.com/​​food-and-drink/​​dietary-requirements-of-a-medieval-peasant), “A prosperous English peasant in the 14th century would probably consume 2 − 3 pounds of [rye, oats, or barley] bread, 8 ounces of meat or fish or other protein and 2 − 3 pints of ale per day”, which works out to about 3500 to 5000 calories per day.

That same page lists various farm chores as burning 1500-7500 calories over an 8 hour period, so assuming some mix of those plus the normal base calorie burning easily adds up to over 3500 calories.

This blog post (https://​​www.worldturndupsidedown.com/​​2011/​​08/​​how-many-calories-did-they-eat-in-day.html?m=1) looked at a shopping list from the 1860s and found that men ate about 3500 calories per day while women ate about 2500 calories per day. I’m not sure what audience this was aimed at (farmers? factory workers?) but clearly it’s more than 2400 calories per day.

This post (https://​​oureverydaylife.com/​​321257-the-peasant-diet.html) cites “research published at Eastern Kentucky University” to say that “an average medieval person burned between 4,000 and 5,000 calories per day … A typical diet for peasants delivered between 3,500 and 4,500 calories, about or just under the need.”

If you’d like I can do more academic research, but these independent sources all roughly corroborate each other so I’m personally satisfied.

One note is that the food eaten historically was much less appealing to eat. I don’t think they were eating 3 pounds of bread because they really liked oat bread, but rather that they needed it to survive doing hard manual labor for 8 hours a day.

• Thanks, that’s interesting. Intuitively I would not have expected them to be burning so many calories.

• Reported numbers vary quite a bit (perhaps in part because the physical activity intensity of training or warfighting also varies), but you might be interested to know that soldiers in training or active duty might hit something like 4000-5000 kcal/​day in energy expenditure, maybe thousands more for outlier people and/​or circumstances.

• How much did city dwellers in the early 20th century eat? There must have been a period when people were not doing so much manual labor but before the obesity epidemic.

• A lot of city dwellers then were doing manual labor (factory lines, construction), but I’m really not sure about the office workers from them. It’s a good question!

• I think you are missing my point—which EY also makes above—that you are concluding that the calorie consumption increase causes obesity when in fact none of the evidence you provide supports pointing the causal arrow in that direction specifically.

We know obese people eat more, and we know that the greater fat mass has greater nutritional requirements.

The interesting question is not whether 400 calories are associated with the weight gain, clearly people are more obese now and also they eat 400 more calories on average, no one is disputing this. The interesting question is whether those 400 calories cause the weight gain or are caused by the weight gain. You are implying the former but there is not a lot of evidence in support of it—and other posters in this thread are chiming in with other evidence suggesting that 400 calories daily is well within normal historical variation, which is SMTM’s point that “400 extra calories causes weight gain” would be weird.

• I think you are missing my point—which EY also makes above—that you are concluding that the calorie consumption increase causes obesity when in fact none of the evidence you provide supports pointing the causal arrow in that direction specifically.

No I’m not. I don’t understand why people are jumping to this conclusion—I said several times that “the only claim I’m making is X” but people keep attributing to me claims that are not X.

The interesting question is not whether 400 calories are associated with the weight gain, clearly people are more obese now and also they eat 400 more calories on average, no one is disputing this. The interesting question is whether those 400 calories cause the weight gain or are caused by the weight gain.

As I’ll repeat here again, the whole point of my comment is to question SMTM’s claim that a 20% increase in calorie intake is small. It’s not small. I agree otherwise that the interesting question is what caused people to shift from one equilibrium to another and talking about energy balance doesn’t help clear up that point. It’s just not the point I’m trying to make, though.

• I think we are getting caught up in the definition of “small”. My original point earlier is that 400 calories is small compared with historical variation and variation among humans. Your original point is that 400 calories is more than enough to explain the weight gain and thus isn’t “small”. Those are different definitions of small, and are both true: 400 calories is small compared with historical and present variation among humans AND 400 calories is enough to explain the extra weight.

But the latter is obvious; clearly those 400 calories explain the weight gain, because people aren’t suddenly metabolizing air or water or other calorie-free inputs into extra weight, those fat cells are creating fat from calories people consume. I suspect people are ascribing other claims to you because “400 calories is not small—it’s enough to explain the excess weight” is only a useful claim in this context (“this context” being “what causes obesity?”) if you are also making the causative claim.

You insist you are not making the causative claim—so what exactly are you arguing re: the question of “what’s causing the weight gain?”

• I mean, obviously the causal chain of weight gain is often going to go through caloric intake, but that doesn’t make caloric intake the root cause. For example, birth control pills, stress, and soda machines in schools all cause weight gain via increased caloric intake, but are distinct root causes.

• As I said in my original comment, this might seem obvious to you but unfortunately it’s not obvious to everyone. In addition, it’s also not necessarily correct: you can get fatter because you expend less energy too. I think empirically it seems like just looking at calorie intake and assuming the energy expenditures are fairly flat is a decent story but that’s definitely not a conclusion you can reach a priori.

• I wonder if the macronutrient rates shifted. This would influence the total calories you end up with because absorption rates are different for different macronutrients. How the food is processed also influences absorption (as well as the total amount of calories that may not be reflected on the package).

If these factors changed, calories today don’t mean exactly the same thing as calories in 1970.

Since FDA allows a substantial margin of error for calories, maybe producers also developed a bias that allows them to stay within this margin of error but show fewer calories on the package?

Maybe this is all controlled for in studies, dunno, I just did a couple of google searches and had these questions.

• Edit: I want to point out how disturbing it is that both the post itself and my comment have been receiving many downvotes from people who don’t think it’s worth their time to explain what they think is wrong with either of them.

With +305 karma at the time of this writing the post has a very high karma count. If you look through recent post the only posts with higher karma are AI risk posts written by very senior people (Eliezer and
Paul Christiano).

Without an easy way to look it up it wouldn’t surprise me if +305 karma puts the post in the top 20 posts by karma that exists on LessWrong2.0.

• Ege Erdil was referring to a flurry of downvotes that this post got within ~30 minutes of being posted. I don’t remember the exact number, but at the time he made that edit the karma count was quite low due to them.

• When I made the edit this was not the case and the post was getting quite a lot of downvotes. Apologies for not including a timestamp. It was like 30 minutes to 1 hour after the post had been published and at some point I think the post had more people that had voted on it than it had net karma with a couple of strong upvotes that I knew had been thrown into the mix, including my own.

• I’ve downvoted this comment; in light of your edit, I’ll explain why. Basically, I think it’s technically true but unhelpful.

There is indeed “no mystery in Americans getting fatter if we condition on the trajectory of mean calorie intake”, but that’s a very silly thing to condition on. I think your comment reads as if you think it’s a reasonable thing to condition on.

I see in your comments downthread that you don’t actually intend to take the ‘increased calorie intake is the root cause’ position. All I can say is that in my subjective judgement, this comment really sounds like you are taking that position and is therefore a bad comment.

(And I actually gave it an agreement upvote because I think it’s all technically true)

• I think the people who believe my comment is unhelpful aren’t understanding that the content in it that seems obvious to them is not obvious to everyone.

• [ ]
[deleted]
• 29 Jun 2022 2:07 UTC
21 points
6 ∶ 0

That’s a fantastic post thank you. How likely do you reckon it is that the obesity epidemic is driven, at least in part, by another contaminant that is not lithium?

• My credence that that is the case is much higher than that lithium is a major cause of the obesity epidemic. I wouldn’t be too surprised if contaminants explained ~5-10% of the weight that Americans have gained since the early 20th century.

The arguments for contaminants that seemed most appealing to me at first (lab and wild animals getting fatter) turned out to be really dubious (as I briefly touch upon in the post), which is why I’m not more bullish on it.

• I think they’re a proponent of the ‘too palatable food’ theory.

• Isn’t the “too palatable food” theory ridiculously easy to test, once you define what “too palatable” means? Assuming that we grant the “obesity epidemic is caused by changes in diet over the 20th century” you’d just need to switch people to an unrestricted-calorie diet that mirrors the homemade foods that our ancestors ate in the early 1900s and see if their satiety plummeted. (Here in the US that would still be a pretty diverse and filling diet that includes lots of meat, potatoes and pie.) I am skeptical that this would work (at the effect size needed to explain the obesity epidemic) but I’d love to see it tested.

• I’ve been following the SMTM hypothesis with great interest; don’t have much to add on a technical level, but I’m happy to pay a $200 bounty in M$ to Natália in recognition of her excellent writeup here. Also—happy to match (in M$) any of the bounties that she outlined! • Will SMTM answer NCM’s post criticizing their Lithium theory? <https://​​manifold.markets/​​NuñoSempere/​​will-smtm-answer-ncms-post-criticiz> • The SMTM authors just released a post (a) addressing some of the Total Diet Studies I found, where by “addressing” I mean that they picked a handful of them (5) and pretended that they are pretty much the only studies showing low lithium concentrations in food. (They don’t mention this blog post I wrote, nor do they mention me.) Their post does not mention any of the following studies that were mentioned in my post, and that found low lithium concentrations in food: Given that they say that the 5 TDSs they picked “disagree with basically every other measurement we’ve ever seen for lithium in food” (and repeat this point quite a few times in their post) it does not seem that they have read my post yet. • On top of picking 5 of the ~20 estimates I mentioned to claim that low estimates of dietary lithium intake are “strictly outnumbered” by studies that arrive at much higher estimates, they also support that claim by misrepresenting some of their own sources. For example, • They say that “Magalhães et al. (1990) found up to 6.6 mg/​kg in watercress at the local market,” but the study reports that as the lithium content per unit of dry mass, not fresh mass, of watercress (which the SMTM authors do not mention). This makes a big difference because Google says that watercresses are 95% water by weight. • They do the same thing with Hullin, Kapel, and Drinkall (1969). They do not mention that this study dried lettuce before measuring its lithium concentration, and reported lithium content per unit of dry mass. Google says that lettuce is 95% water by weight too, so this matters a lot. They also mention a lot of other dry mass estimates, such as those from Borovik-Romanova (1965) and Ammari et al. (2011). This time they do disclose that those estimates are for dry mass, but they nevertheless present those estimates as contradicting Total Diet Studies, as if they were measuring the same kind of thing, when they are not. Notably, they say “Duke (1970) found more than 1 mg/​kg in some foods in the Chocó rain forest, in particular 3 mg/​kg in breadfruit and 1.5 mg/​kg in cacao,” and fail to mention that most of the foods in Duke (1970) have less than 0.5 mg/​kg of lithium. Also, only one of the examples SMTM used to claim that the Total Diet Studies are “outnumbered” actually attempted to quantify dietary lithium intake,[1] whereas almost all of the studies I’ve mentioned do that. This is important because a lot of the sources they cite that we don’t have access to (there are several of those) could be measuring lithium concentration in plant dry matter, as a lot of their sources that are available do, in which case seemingly high concentrations do not imply high dietary consumption. Moreover, a lot of their post is focused on speculating that ICP-MS (the technique used by most studies) systematically underestimates lithium concentration. However: All of those find very low concentrations of lithium in food. Moreover, they themselves mention a paper that uses ICP-MS and finds high concentrations of lithium in food in Romania (Voica et al. (2020)). These studies are a substantial fraction of all of the studies on lithium concentration in food that we have. So it seems to me that their whole focus on ICP-MS, and their claim that it “gives much lower numbers for lithium in food samples than every other analysis technique we’ve seen,” does not seem warranted. Again, I don’t think that studies that find high concentrations of lithium in food are necessarily wrong. There is no market pressure for food to have 1 µg/​kg rather than 1000 µg/​kg of lithium, or the other way around, the way that there is market pressure for meals to have e.g. carbohydrate/​fat ratios and energy densities within a specific optimal range. Consumers do not care about whether lithium concentration is 1 µg/​kg or 1000 µg/​kg. And we know that lithium concentration in e.g. water varies a lot according to lithology and climate, so we shouldn’t expect this to be uniform around the world. So I don’t see how it must be the case (as the SMTM authors claim) that all studies that find low concentrations are wrong. 1. ^ The example was Schrauzer (2002), which bases its estimates on hair concentration rather than actual food measurements. Ken Gillman says that this paper “has a lot of non-peer-reviewed and secondary references of uncertain provenance and accuracy: it may be misleading in some important respects.” Also, interestingly, as I mentioned in my post, the highest estimate Schrauzer (2002) provides for dietary lithium intake is from China, not really a country with a huge obesity problem. (Note that the Ken Gillman blog post has a typo: it says that the “typical total daily lithium intake from dietary sources has been quantified recently from the huge French “Total Diet Study” at 0.5 mg/​day,” a value that is 10x too high.) • Not having time to read all of your papers, do they have the same methodology SMTM points out as being suspect in the post you linked, or do they cover a broader range of methodologies? • Given that you’ve tried to contact them and they haven’t responded, this reflects poorly on them. When you tried to contact them, was it reaching out to talk? (A call might help in some ways, e.g. letting them probe your evidence and reasoning, and helping them reconnect to truth-seeking.) • Several months ago, my husband publicly challenged the SMTM authors to a bet on their contamination theory of obesity. They have declined to bet. I’d like to remind them that the bet offer is still active. SMTM’s response in that Twitter thread (about how it does not make sense to make a bet like this, given that it would create a financial disincentive for them to reveal disconfirmatory findings) seems to make sense to me (especially given that the proposed bet is$1,000—not counting the additional stakes offered by another person in the thread—which exceeds SMTM’s monthly Patreon earnings of ~$800). In general, it seems to me that betting in a case where one of the parties to the bet is expected to face decisions about actions which will affect the resolution of the bet does not make very much sense. You imply that SMTM’s failure to take up the best is relevant to the question of whether we should believe their claims, but to me it seems rather like good epistemic hygeine for them to refuse the bet. Do you disagree? • I think that aspects of their current funding situation make them substantially more prone to perverse incentives than that bet would. That’s as may be, but does not really change the fact that the bet would also create perverse incentives. Patreon is not their main source of funding. It seems that they’ve received hundreds of thousands of dollars in donations through other methods. Good information, thank you. • I am OK betting smaller amounts. I said “up to”$1000.

• I pretty strongly disagree with your takes in that Twitter thread (though agree on the object level that you offered <$1000 too). I think the core point of “we want to find the truth here, and creating incentives against finding the truth seems not worth it if it could damage truth seeking” seems obviously reasonable. This incentive exists even at smaller amounts of money. I don’t think things like pre-registration are good solutions to this—a clinical trial can maybe register clear rules to follow and a success criteria, in a way that “try to do research + literature reviews on a hard question and understand it better” can’t (Also, clinical trials obviously have major biases due to publication incentives which makes their research much lower quality). In order for not taking the bet to be a meaningful downwards update, you need to be able to fully decouple “making an epistemic bet given your best guess about reality” from all of the second-order effects of how the bet affects other relevant things. I think the response “I am not capable of this decoupling, and so refusing this bet is not a strong statement about my epistemic beliefs or confidence in them” is extremely reasonable. • He’s also significantly more combative in that thread than I would expect in the context, which leads me to wonder whether there’s more going on there. • Going through it again, I think I was about as combative as you’d expect someone who strongly disagrees with the object-level theory to be. Maybe I could have worded things more nicely. But seriously, there’s not something more going on here. • I also thought it was (plausibly) a ‘friendly challenge’ – we should be willing to bet on our beliefs! And we should be willing to bet and also trust each other to not defect from our common good. • The challenge did specify [emphasis mine]: up to$1000

• 29 Jun 2022 4:47 UTC
13 points
4 ∶ 0

I wonder if one reason SMTM might be advocating improbable theories, and not accepting bets, is because they are intentionally persuing improbable theories. Their post on scurvy seems to make the point that you need to check things even if they seem improbable, as the truth sometimes turns out to be something that seemed improbable.

I (perhaps charitably) assumed they did not believe the lithium theory per se, but thought it was worth a more detailed look—having previously argued that the bar for that should be lower than others think.

I thought the lithium theory and the potato diet were just two of many possible things they might be looking into, with the idea being that they advocate a broader search generally.

• It’s very clear to me that it’s fine (and often great!) to investigate implausible theories. It just seems to me that the SMTM authors are doing a very bad job at actually pursuing the truth, as demonstrated by the facts that, e.g.

1. they wrote a “literature review” that only includes studies that are outliers, refused to address the fact that they are outliers, and are actively trying to prevent their readers from knowing that (by refusing to approve my comment on their post despite having had the time to approve several comments that were made afterward)

2. they have misrepresented their sources several times (as I show in this section and this comment) and have refused to correct their posts after being told about it

3. they seem oddly uninterested in all of the other common side effects that lithium causes at therapeutic doses, even though it’s very easy to know that those side effects are significant by merely reading the Wikipedia page on lithium salts

4. they seem oddly uninterested in whether therapeutic doses of lithium cause enough weight gain to explain the obesity epidemic

I also think it would be more helpful if they told readers their credences on their hypotheses, and what led them to reach those credences. But this is a minor point compared to the 4 above.

• It just seems to me that the SMTM authors are doing a very bad job at actually pursuing the truth

I think – personally – you’re holding them to an unrealistically high standard!

When I compare SMTM to the/​a modal person or even a modal ‘rationalist’, I think they’re doing a fantastic job.

Please consider being at least a little more charitable and, e.g. ‘leaving people a line of retreat’.

We want to encourage each other to be better, NOT to discourage them from trying at all! :)

• 2 Jul 2022 15:46 UTC
−1 points
0 ∶ 6
Parent

I think you’re making an unsupported inferential leap in concluding “they seem oddly uninterested in …”.

I would not expect to know why they haven’t responded to my comments, even if I did bring up a good point – as you definitely have.

I don’t know, e.g. what their plans are, whether they even are the kind of blogger that edits posts versus write new follow-up posts instead, how much free time they have, whether they interpreted a comment as being hostile and thus haven’t replied, etc..

You make good points. But I would be scared if you ‘came after me’ as you seem to be doing to the SMTM authors!

• I agree. Their ‘candidate explanations’ felt unsatisfying when I got to them, because they spend so much time building up what a good explanation would necessarily feel like. Maybe that was the goal, but if it was, they didn’t make it explicit.

• More plausible model for why in present day so many are overweight:

--cheap calories that taste good widely available with very low effort to obtain

--tasty food is, other things equal, an easy exploit to reward /​ motivation loops, so it tends to get used in exactly this way which results in excess calorie consumption and of course this is habit forming. there is probably also a lower threshold to “get into” food vs something else in this class like drugs since eating is already universal and not taboo or otherwise particularly regulated.

--fewer obligatory opportunities for caloric expenditure to balance intake possibly mostly as a result of modern transport and trend toward less need for physical labor in general

Maybe this is off-base, and it may not apply to the lithium hypothesis, but it seems there are a lot of really implausible ideas for why obesity is common which are motivated by a desire to not blame the obese person. Common perceptions of agency might infer that the above model blames the consumer, but the intention is exactly the opposite; since it’s predictable that humans in the above environment will tend to act this way, who can blame them?

• I was, and still am, tho much less, excited about the contamination theory – much easier to fix!

But I think I’m back to thinking basically along the lines you outlined.

I’m currently losing weight and my model of why is:

• I’m less stressed, and depressed, than recently, and I’ve been able to better stop eating when I’m satiated.

• I’m exercising regularly and intensely; mainly rock climbing and walking (with lots of decent elevation changes). It being sunnier and warmer with spring/​summer has made this much more appealing.

• I’m maybe (hypo)manic (or ‘in that direction’, i.e. ‘hypohypomanic’; or maybe even ‘euthymic’). I’m guessing recent sunlight-in-my-home changes triggered this (as well as the big recent drop in stress/​depression).

I would love to see a study of weight gain in modern hunter-gatherer people that provides an experimental group with ‘very palatable’ food. I think I would be willing to bet that they would gain some weight.

I do also suspect that hunter-gatherers engage in a LOT of fairly strenuous physical activity. Walking – and living in a dense urban walkable city (in my case NYC) – does seem like maybe one of the most feasible ways to try to match that much higher level of overall physical activity. (Rock climbing is also pretty strenuous!)

• 5 Jul 2022 21:27 UTC
12 points
3 ∶ 0

Curated! This is a fantastic response, in-depth yet readable, and considering many different angles of attack. I personally found the widespread lack of the other associated side-effects of lithium to be the most convincing single point, but it’s the multiple lines of attack together that pushes me to disbelieve the lithium hypothesis.

I really like the vision for doing science on the blogosphere that Slime Mold Time Mold has, that includes readable and detailed online collections of scientific mysteries combined with active research (outside of academia), and I have respect for people who do the work to make their vision a reality. It unfortunately seems to me like the clues they put together had a lot of false-positives and missed a lot of evidence, and this critique seems compelling to me personally on this issue.

I note I will appreciate any further checks of Natalia’s post and claims in the comments, and if someone ends up with a different view and writes a further post in this conversation (e.g. the folks from Slime Mold Time Mold!) I’d enjoy curating such a post.

(By the way, this is our first curated post that is a podcast at-the-time of curating, so all the people on the mailing list can also listen to it on Spotify/​Apple Podcasts/​Libsyn/​etc, which I’ve edited into the top of the post.)

• This is why I am default skeptical of any non-mainstream medical argument made to me. If someone is feeding me bullshit or bad data I will not be able to tell. If you don’t have the expertise or the patience to actually look at the source data, an argument based on lies or bad data, as SMTM seems to have made, sounds just as convincing as one based on good data. (Especially if you’re trying to sell me something!)

• Only somewhat related, as it’s anecdotal: I’ve been taking ~12mg elemental lithium daily for the last ten or so years, without any noticeable weight gain.

• I think it is worth adding that there is some evidence that not all lithium salts are the same. What this means for obesity is probably unknown.
Lithium orotate is more potent, effective, and less toxic than lithium carbonate in a mouse model of mania (biorxiv.org)

• A PSA for those who might like to have less body fat: a number of observational and experimental studies find that the energy density of your diet (as in, calories per gram) is a very, very good predictor of ad libitum caloric intake. I doubt that an increase in the caloric density of our diets fully explains the obesity epidemic—there’s probably something to the “hyperpalatability” idea (though hyperpalatable foods are almost always very energy dense too), habitual nicotine and THC intake trends probably matter, I’d buy that some contaminants even if not lithium are causing people to be hungrier or less physically active, etc etc—but I find it implausible it’s not an important one, and even better, it’s one that you can calculate very easily for most of what you eat and then control with less effort than you’d have to expend for almost any other type of “diet”.

This is consistent with e.g. the potato diet being anecdotally weirdly effective at causing weight loss (~1 cal/​gram which is pretty low), and also consistent with most of the generic conventional wisdom around diet like “eat more fruits and veggies and lean meats and less dessert and fast food”, and IMO makes lots of intuitive sense—satiety is complicated, but having a lot of stuff in your stomach is clearly pretty important, so, just put a lot of stuff in your stomach that doesn’t actually have many calories, lol.

• having a lot of stuff in your stomach is clearly pretty important

A question I have here is, why not try for low calories per litre instead of (or as well as) low calories per gram?

Some thoughts on that:

• The relevant thing would be density after chewing, not density on the plate. Maybe there’s not much variance in that. (If so, maybe “swallow your food without chewing” is an unrealized life hack for losing weight, with the caveat that it increases your risk of choking and dying.)

• Maybe your stomach will break down less-dense contents faster? A very naive model says that if you compress something, its surface area decreases so there’s less for acid to react with but the same mass. So it’ll take longer to fully dissolve in an acid bath, but take up less volume initially. I don’t know which will take up more litre-seconds in total, or if that’s the right question to think about. Plus at some point things leave the stomach and I don’t know what triggers that.

• How does this whole thing work with fluids? Presumably they leave your stomach quite fast, so per-calorie they should contribute less to satiety than solids?

• > A question I have here is, why not try for low calories per litre instead of (or as well as) low calories per gram?

I think calories per gram is usually what people study due to some combination of:
- this is the way somebody chose to measure “energy density” early on and it stuck for whatever reasons things stick
- in cooking and/​or conducting experiments, mass is pretty much always easier to measure than volume (even with liquids, in my opinion...)
- we see this metric work pretty well—better than basically any other known single factor, is my impression—to predict satiety response, ad libitum caloric itake, diet adherence, and long-term weight changes in various experiments

I do know of a single-meal study that looked at how volumetric energy density (comparing potato chips vs. popcorn, which have similar energy per mass) predicted ad libitum caloric intake, and found that it does seem to independently matter. I don’t know of any other similar studies, though I won’t claim to be up to date on the literature.

>Plus at some point things leave the stomach and I don’t know what triggers that.

”gastric emptying” is the key term used in studies of this question (I haven’t really studied this myself)

>How does this whole thing work with fluids? Presumably they leave your stomach quite fast, so per-calorie they should contribute less to satiety than solids?

Right, that’s the usual finding. Drinking lots of water before or with meals does seem to promote satiety and lower ad libitum caloric intake, so water itself certainly counts for something, but liquids are generally nowhere near as filling per mass as solid foods, which agrees with the conventional wisdom around not drinking calories.

• Huh – I wonder if this has helped me since I made a concerted effort to eat leafy greens regularly (basically every day).

I always liked the ‘fact’ that celery has net-negative calories :)

I do also lean towards eating fruit raw versus, e.g. blended in a smoothy. Make-work for my gastrointestinal system!

• In German, the tap water is known to be very hard, so essentially no one drinks tap water. Instead, it’s common to drink alcoholic beverages (brewed, so they don’t have the same mineral level) or bottled mineral water. The mineral water does contain some lithium (and some mineral waters contain very high levels), but most bottled water in Germany does not have very high levels of lithium. In this study, the “medium” sample was 171 µg/​L while the “high lithium” sample was 1724 µg/​L. So people who generally drink the high lithium bottled water would be at the lower end of SMTM’s guesses, and everyone else would be safely outside of it.

• In German, the tap water is known to be very hard, so essentially no one drinks tap water.

Our local tap water (in a town close to Munich) is roughly as soft as tap water can be, and I drink nothing else.

But if you’ve found statistics on how countries differ in how much tap water their citizens drink, I’d be interested to see them. Unfortunately, searching for “tap water consumption” includes all the other uses like showering etc.

• Hm, this was mostly anecdotal from speaking to German friends (including people in Munich!), so I guess I was speaking too generally. Certainly more people drink bottled water in Germany at restaurants compared to many other countries, but I see that I was overstating the case for at home.

• Restaurants in Germany don’t tend to offer free tap water, so you need to buy bottled water. I think that Germans just like the taste of sparkling mineral water, hence why they drink it so much.

• Drinking tap water in restaurants is unusual but most consumed beverages are not drunk in restaurants in Germany.

As far as there is a preference for sparkling water, people who like sparkling water often have the equipment to add sparkle to tap water.

I live in Berlin and both myself and other people I know drink a good amount of tap water. Coffee and tea are also usually made from tap water.

• I would interpret your findings about the links between lithium, weight gain, hypothyroidism, and DI differently.

Subclinical hypothyroidism affects an estimated 5% of the population, and causes both weight gain and fatigue. So we can point out that we do see an appreciable amount of both subclinical hypothyroidism and obesity in the general population, and they were found to be associated in 1104 subjects ages 10-19 years old.

Lithium may also cause weight gain by other mechanisms, as yet unknown.

The numbers you found show that going on a clinical dose of lithium causes an average of 0-6 kg weight gain above whatever weight gain they may have experienced from a dietary dose. We can imagine that going from a very low dietary dose of lithium (say < 10 ug/​day) to a small but higher daily dietary dose (say > 40 ug/​day) is responsible for more marginal weight gain than going from 20 ug/​day to 200 mg/​day. So it may be that an increase over time in dietary lithium doses is responsible for most of whatever weight gain lithium is causing in the population, with a much smaller amount of additional weight is caused by putting people on a clinical dose.

Lithium may cause DI only starting at clinical doses. It may then show a dose-dependent association. We would therefore expect to see a dose-dependent relationship between DI and lithium, but no DI epidemic.

The fact that lithium shows a dose-dependent response at therapeutic doses allows for dietary doses in the neighborhood of 20 ug/​day to cause weight gain. What we’d need is evidence that the weight gain caused by lithium disappears at dietary doses.

We don’t have that here. The closest is the Rinker study, which found 1328 MS patients reported weight gain and 1028 reported weight loss. More patients gained than lost weight, so if anything it supports the conclusion that low-dose lithium can lead to weight gain. MS can cause both weight loss and gain generally on its own, so we probably shouldn’t update too much on this one small study.

After learning that 5% of the population has subclinical hypothyroidism, I’m actually more inclined to believe that normal doses of dietary lithium may be causing the obesity epidemic than I was before reading this post. However, my credence is still well below 50%, so I also still agree with your post’s title.

Note: This was originally part of a different comment, but I split it off for clarity.

• After learning that 5% of the population has subclinical hypothyroidism, I’m actually more inclined to believe that normal doses of dietary lithium may be causing the obesity epidemic than I was before reading this post. However, my credence is still well below 50%, so I also still agree with your post’s title.

I’m a bit confused about this update. A lot of chronic diseases are very common. And as I showed, hypothyroidism has not been increasing over time. It might be decreasing. And, again, the geographical pattern of hypothyroidism does not match the geographical pattern of obesity.

• A lot of chronic diseases are very common.

And as I showed, hypothyroidism has not been increasing over time. It might be decreasing.

I’m specifically considering subclinical hypothyroidism. From the paper you link:

A significant limitation to this report is that the incidence rates of thyroid disorders were based on diagnoses recorded on standardized medical records. Because of this, the findings reflect the rates of thyroid functional abnormalities that were clinically detected and exclude subclinical dysfunction since not all service members are tested for thyroid disorders.

And, again, the geographical pattern of hypothyroidism does not match the geographical pattern of obesity.

If we’re working with the “lithium causes a desire to overeat and be sedentary (via hypothyroidism and possibly other mechanisms) in young people, which leads to lifelong obesity-promoting eating and activity habits” version of the hypothesis, then it may just be that Brazil and China are only now gaining the wealth and food supply to permit this to occur in a large enough swathe of the population. We see obesity growing exponentially in China and India (I couldn’t find a graph for Brazil), while it’s looking like it’s on the concave part of the sigmoid curve in the USA.

I’m inclined to think that if lithium is causing obesity in this manner, that subclinical hypothyroidism is one of its important mechanisms of action. If treating subclinical hypothyroidism in young people did not lead to long-term lower rates of obesity, I would lower my credence in an important dietary lithium-obesity link significantly.

• I’m specifically considering subclinical hypothyroidism.

The other paper I linked, which uses nationally representative data from the 2007-2012 NHANES, estimated the prevalence of subclinical hypothyroidism to be 3.5% (lower than the prevalence in the 1988-1994 NHANES, which was 4.3%), and noted that the prevalence of at-risk TSH levels seems to have decreased or remained stable with time. (Although mean TSH levels have increased.)

(I apologize for not having replied earlier — I was curious and wanted to check the raw NHANES data on TSH levels myself before replying to you, so I tried to, but found that parsing one of the datasets was too hard and ended up not doing it.)

[ETA: actually, the 4.3% number is based on a different definition of hypothyroidism. With regards to the definition used in the newer study (TSH > 4.5 mIU/​L in the absence of clinical hypothyroidism), it says the following:

Percent reference population with TSH > 4.5 mIU/​L for this study was found to be 1.88% which is similar to what was found by Hollowell et al. [Hollowell et al. is the group that analyzed ’88-’94 data]. It would indicate that at risk TSH levels in the reference U.S. population may have decreased a bit or remained at the same level for reference US population.

]

• (I apologize for not having replied earlier — I was curious and wanted to check the raw NHANES data on TSH levels myself before replying to you, so I tried to, but found that parsing one of the datasets was too hard and ended up not doing it.)

No worries, thank you for all the great research you’re doing.

The analysis of ’88-’94 data says:

Hypothyroidism was found in 4.6% of the U.S. population (0.3% clinical and 4.3% subclinical)

The analysis of ’07-’12 data says:

The prevalence rate of clinical hypothyroidism in general U.S. population was 2.4%… The percent population with subclinical hypothyroidism was 3.5% (Table 3).

So we see a 20% decrease in subclinical hypothyroidism (4.3% → 3.5%), but an 800% increase in clinical hypothyroidism (0.3% → 2.4%).

My original argument was based on prevalence in the population, not rate of change across time. If anything, given that (as these papers state), clinical hypothyroidism most definitely is associated with BMI, I think they lend support to the hypothyroidism/​obesity explanation. Perhaps what we are seeing is a more rapid move in individual patients from subclinical to clinical hypothyroidism, as a result of the hypothesized lithium contamination. In affected patients, by the time the medical system catches it, it’s usually already clinical, whereas in the (postulated) less lithium-contaminated 80s, there was a longer period of time in the subclinical phase per patient when contact with the medical system could catch and diagnose subclinical hypothyroidism.

I will however make a couple meta notes:

a) I’m not putting as much time into this as you, so I’m worried I’m losing track of the details of the argument.

b) I’m trying to salvage the lithium theory because I don’t think it’s utterly destroyed by this data, not because I think it’s extremely likely.

So I generally just have to apologize if, on reflection, my overall argument here is full of incoherencies and inconsistencies. I’m forming my thoughts as I write these comments, and I expect to change my mind in the future—I’m just not sure in which direction.

• So we see a 20% decrease in subclinical hypothyroidism (4.3% → 3.5%), but an 800% increase in clinical hypothyroidism (0.3% → 2.4%).

The abstract of the paper analyzing ’88-’94 data says that they used a different definition of “subclinical hypothyroidism” than the definition that is commonly used today (I had edited my comment to reflect that a few seconds before you replied. I am so sorry for the error!!). Quoting from the paper:

(Subclinical hypothyroidism is used in this paper to mean mild hypothyroidism, the term now preferred by the American Thyroid Association for the laboratory findings described.)

So it seems that the prevalence of hypothyroidism was 4.6% in this survey, not 0.3%. So the prevalence of clinical hypothyroidism has decreased.

With regards to what we nowadays call subclinical hypothyroidism (TSH > 4.5 mIU/​L in the absence of clinical hypothyroidism), the paper that analyses ’07-’12 data does say:

Percent reference population with TSH > 4.5 mIU/​L for this study was found to be 1.88% which is similar to what was found by Hollowell et al. [Hollowell et al. is the group that analyzed ’88-’94 data]. It would indicate that at risk TSH levels in the reference U.S. population may have decreased a bit or remained at the same level for reference US population.

• Note: I’m a little bit sick today, and it’s possible I made a mistake in my stoichiometry or in converting from math to reasoning. If so, I will happily stand corrected if anybody points out my error.

The change in terminology is just verbiage. In fact, it appears they have narrowed the definition of both subclinical and clinical hypothyroidism in the newer paper. In light of how they changed the definitions, we should think that a definition-neutral rate of both subclinical and clinical hypothyroidism has gone up even more than I’d described in my previous comment.

Hypothyroidism is defined in part by lower-than-normal thyroxine (T4). In the earlier paper, T4 levels are defined as “clinical” that would be defined as “normal” or “subclinical” in the later paper. According to the definitions of the later paper, all “subclinical” patients in the earlier paper would have been considered “normal.”

They switched from measuring bound + unbound thyroxine (T4) to free thyroxine (FT4) in the second paper. So the numbers aren’t directly comparable because they’re measuring the molecule in two different states the body. I don’t know whether we can do more than rely on the researchers’ implied claim that the definitions of normal vs. subclinical vs. clinical hypothyroidism remain comparable under the new definition.

Extracts and calculations for legibility:

’88-’94 paper:

… high T4 is a concentration 169.9 nmol/​liter and low T4, a concentration 57.9 nmol/​liter...

Hypothyroidism was defined as clinically significant if TSH > 4.5 mIU/​liter and T4 < 57.9 nmol/​liter and as subclinical or mild when TSH > 4.5 mIU/​liter and T4 >= 57.9 nmol/​liter...

Subclinical hypothyroidism: TSH > 4.5 mlU/​L and T4 >= 57.9 nM

Clinical hypothyroidism: TSH > 4.5 mlU/​L and T4 < 57.9 nM

’07-’12 paper:

Subclinical hypothyroidism was defined as having TSH levels ≥ 4.5 mIU/​L and FT4 within the normal reference range [of 0.6-1.6 ng/​dL]. Those who had TSH levels ≥ 4.5 mIU/​L and FT4 below 0.6 ng/​dL were defined as having clinical hypothyroidism.

Thyroxine (T4) has molecular weight 776.87 g/​mol.

(.6 ng/​dL) * (10 dL/​L) * (1E-9g/​ng) * (1 mol/​776.87 g) *(1E9 nmol /​ mol) = 7.7 nmol/​L = 7.7 nM.

Subclinical hypothyroidism: TSH >= 4.5 mlU/​L and 7.7 nM ⇐ T4 ⇐ 20.5 nM

Clinical hypothyroidism: TSH >= 4.5 mlU/​L and T4 < 7.7 nM

• FT4 is not the same thing as T4. From Medical News Today:

In adults, normal levels of total T4 range from 5–12 micrograms per deciliter (mcg/​dl) of blood. Normal levels of free T4 range from 0.8–1.8 nanograms per deciliter (ng/​dl) of blood.

I haven’t converted these densities to molarities, so I haven’t compared these ranges with those provided by the ’88-’94 paper, but this distinction seems relevant.

• Good catch, I will edit the previous comment tomorrow when I’m on my computer. Given that the sub vs clinical distinction turns on T4/​FT4 and these papers test for different values, I’d need to give more thought about how comparable they are.

• Update: I have now looked into the raw TSH data from NHANES III (1988-1994) and compared it with data from the 2011-2012 NHANES. It seems that, although median TSH levels have increased a bit, the distribution of serum TSH levels in the general population aged 18-80 (including people with thyroid disorders) has gotten more concentrated around the middle; both very high levels (characteristic of clinical or subclinical hypothyroidism) and very low levels (characteristic of clinical or subclinical hyperthyroidism) are less common in the 2011-2012 NHANES compared to NHANES III. You can see the relevant table here. There might be bugs in my code affecting the conclusion of the analysis.

This paper, which pretty much used the same NHANES surveys, looked at a somewhat different thing (thyroid levels in a reference population without thyroid disorders or other exclusion criteria) but it seems to report the same finding w.r.t. high TSH levels: a lower proportion of the population in the latest survey meets the TSH criteria for clinical or subclinical hypothyroidism.

• The fact that lithium shows a dose-dependent response at therapeutic doses allows for dietary doses in the neighborhood of 20 ug/​day to cause weight gain. What we’d need is evidence that the weight gain caused by lithium disappears at dietary doses.

We don’t have that here. The closest is the Rinker study, which found 1328 MS patients reported weight gain and 1028 reported weight loss. More patients gained than lost weight, so if anything it supports the conclusion that low-dose lithium can lead to weight gain.

Let us not conflate different meanings of “low-dose lithium” here. In the Rinker study, the dose that patients took was still more than 1000x greater than what people in e.g. New Zealand get from their food. That is not a small difference.

Relevantly, this study found no association between serum lithium concentration in the general population in Germany and BMI. Also, as I mentioned in the post, the correlation between log(water lithium levels) and log(obesity %) across Texas counties is negative.

• Relevantly, this study found no association between serum lithium concentration in the general population in Germany and BMI. Also, as I mentioned in the post, the correlation between log(water lithium levels) and log(obesity %) across Texas counties is negative.

I was primarily trying to address your local argument about interpreting obesity, DI, and hypothyroidism in this comment. These other pieces of evidence seem important, but just aren’t what I’m focused on.

• I’m aware of that. By “low-dose lithium,” I specifically meant in the 30mg/​day range, as opposed to the 1000x lower levels in a typical diet. My point is that none of the studies you list can help very well to understand what lithium’s effects are at a normal dietary level. We should not extrapolate our certainty too far out of the range they’ve studied, and as you point out, dietary lithium is very far out of that range. We can and should make that same argument about the link between lithium and weight gain outside of the clinical dose. Just because it causes weight gain at a low or normal clinical dose does not mean it causes weight gain at a dietary dose.

Overall, we should be uncertain about this hypothesis, not certain that it is right or wrong. To me, uncertainty means “worthy of more study.” Of course, it also means “accurately reporting information,” and SMTM has really managed to set themselves up for a takedown by omitting and distorting so much of the information they use to build their case. That said, I retain let’s say 40% credence for a fairly strong version of their “environmental contamination” hypothesis, with perhaps 40% credence that that low ug levels of lithium in a typical diet are perhaps a 30% contributor to contamination-linked obesity.

• I’d very much like to understand how your credences can be so high with nothing else to back them up than “it’s possible and we lack some data”. Like, sure, but to have credences so high you need to have at least some data or reason to back that up.

• When I wrote the comment, it was mainly because of the prevalence of subacute hypothyroidism in the general population. However, one of Natalia’s studies that I hadn’t been focusing on persuaded me that variations in dietary lithium intake is unlikely to be responsible for so much weight gain. Serum lithium isn’t associated with BMI.

• none of the studies you list can help very well to understand what lithium’s effects are at a normal dietary level.

This study found no association between serum lithium concentration in the general population in Germany and BMI. Also, as I mentioned in the post, the correlation between log(water lithium levels) and log(obesity %) across Texas counties is negative.

• Sorry, I specifically meant the studies you list under the “Lithium weight gain seems to (perhaps) be dose-dependent even at therapeutic doses” section, which is what I was focused on when I wrote my comment. My bad for not being clear.

I’m skeptical of how much we can learn from the Texas study. If harder tap water causes people to drink more bottled water, that could explain the negative correlation.

However, I do think the study showing a lack of correlation between lithium and BMI is important, and cuts strongly against the argument I was making. I would expect to see a striking correlation there if large relative variations at low absolute levels of dietary lithium were an important mechanism contributing to obesity. That’s just not the case.

My only reservation is that we’re trying to answer SMTM’s hypothesis using studies that weren’t specifically designed to test it. I don’t feel confident enough to completely dismiss the idea based on this alone. However, I do think it’s substantially more fragile than I thought before I took this into account. Epistemic status: blowin’ in the wind.

• Update: I found a few papers from villages in Argentina with very high lithium exposure, one of which (whose subjects had urinary lithium concentrations ranging from 0.1-14 mg/​L) found a positive association between lithium excretion and BMI (r=0.11), and did find that at such levels lithium increased plasma TSH levels. But only 17% of participants were obese,[1] even though the average urinary concentration was > 4 mg/​L.

In the other one (which I think I’d seen before, actually) serum lithium concentration (which strongly correlated (0.84) with urinary excretion) was not found to be associated with BMI. The range of urinary concentration was 0.105–4.600 mg/​L. Interestingly, higher exposure seemed to have been associated with smaller body size (both height and weight) for the adults in the study as well as the newborn children. The obesity rate among adults in this sample is only 7%.

1. ^

their average age was 37, median 34, and at that age people are pretty close to the highest BMI they’ll ever have, according to NHANES data.

• Very interesting, thanks for finding them.

Those kind of mixed results don’t seem to paint a compelling picture of dietary lithium-induced obesity. So I’m roughly where I was last we exchanged, when you highlighted the lack of serum lithium and BMI correlation in the other study.

In this case, the thing that jumps out at me is that these are studies in Argentinian villages, with people of Indigenous backgrounds eating relatively traditional and likely constrained diets, perhaps with a higher level of compulsion to work than in wealthier areas.

all women almost exclusively drank tap water, their diets (mainly corn, beans, chicken, and pork) were very similar, and only 3 of 202 women reported ongoing use of any medication

The mechanism that seemed most likely to me was that lithium increases both thirst and fatigue (perhaps mediated via subclinical hypothyroidism), leading to increased consumption of sugary beverages in areas with a lot of soda pop around, and decreased activity levels when a sedentary lifestyle is tractable. Since in these areas, the soda pop and sedentary lifestyles are perhaps less available, this might prevent lithium from showing up more strongly as a driver of obesity. If lithium is driving obesity through thirst and sedentary behavior, the women of SAC may just be satisfying their thirst with water and being stuck working even when they’re very tired.

I’d need more data on how obesity rates vary from village to village in this region to know if 17% is low or high. This study in the same village (San Antonio de los Cobres) found an 11% obesity rate among schoolchildren, as compared to 35% in the USA. That’s just to say that we may be looking at a different overall diet/​lifestyle/​genetic/​contaminant reference class than we see in the USA as a whole.

All that said, I don’t see lithium and obesity leaping out of the data. It’s possible that an abundance of diverse low-level environmental contaminants is responsible, with lithium just one of many. Hence, harvesting data from studies looking at specific individual contaminants won’t ever solve the whole puzzle. “It’s probably not the lithium,” but maybe it’s the lithium + 999 other chemicals? Perhaps having a bunch of weird industrial chemicals floating around in the air, water, soil, and food affects people’s metabolism and energy by hammering at all sorts of different bodily systems—inflammation, hunger, mood, who knows what else?

If the explanation is just “a thousand weird chemicals, each with a small and possibly interacting effect across diverse bodily systems making you tired, hungry and thirst” we’d have to ask why, on average, exposure to random chemicals makes you fat and hungry rather than thin and satiated. Perhaps the brain sends hunger and thirst signals when it’s out of whack, on the off chance that the reason it’s having problems is lack of energy? Certainly it makes sense to me that overall, bodily contamination causes fatigue rather than an increase in energy and drive. And I would also expect that the body’s ability to continue extracting nutrients from whatever food you put into it is pretty robust, since that’s mission-critical. So “body gets a chemical shock, guesses hunger/​thirst is the cause, can’t maintain focused energy due to chemical interference, still absorbs nutrients and turns them into fat” as explanation?

And what sort of study would we run or look for to investigate this extremely messy hypothesis?

But I have to admit that “people have more junk food and time on their hands, so people sit around, pig out, and get fat” is also a pretty compelling explanation for the obesity epidemic. The only issue is that McDonald’s has been around since 1940, the country’s been wealthy and working desk jobs for a long time, but obese adults were < 15% of the population in most US states in 1990, but 36 states have obesity rates at 25%+. It could be generational decay in how people spend their time and how they eat. But that is getting handwavey in the same way that the contaminant hypothesis is handwavey.

Thanks for finding those studies!

• As a followup, the portrait I painted of “chemically-induced tired brain misfiring syndrome”-induced obesity (CITBMS-obesity) seems to suggest a link between obesity and depression would be associated. There does appear to be a link or a U-shaped association between BMI and depression (I’ve only scanned the abstracts).

And as I understand it, we can totally have a CITMBS-obesity epidemic and also a CITMBS-underweight problem at the same time. “Chemically induced weight dysregulation” might be what we’d be looking at.

In such a case, actually, that might make it hard to use the studies we’ve looked at so far to gain information. If the curve is U-shaped, the two ends of the curve may cancel out when averaged together and disguise the effect.

I hadn’t thought of that before. Now my credences for lithium and contamination are back up. It doesn’t completely jive with the story I was telling earlier—now we have a piece where, perhaps, the chemically stressed brain gets hungry/​thirsty in some people and loses appetite in others. Both seem plausible. I guess we’d want to look for a relationship between lithium (or other contaminants) and extremes of weight, rather than a correlation between BMI and lithium concentration.

• In such a case, actually, that might make it hard to use the studies we’ve looked at so far to gain information. If the curve is U-shaped, the two ends of the curve may cancel out when averaged together and disguise the effect.

Note that this does not seem to be what has happened at a population level in the US. BMI seems to have increased pretty much at all levels — even the 0.5th percentile has increased from NHANES I (in the early 70′s) to the 2017-March 2020 NHANES, as has the minimum adult BMI. And the difference is not subtle.

For instance, here are the thinnest people in the last NHANES versus the first one:

The relevant Google Colab cells start here.

• And then there’s this study: Chronic environmental contamination: A systematic review of psychological health consequences (again, I’m just skimming abstracts).

Psychological health impact of chronic environmental contamination is understudied… The meta-analyses observed small-to-medium effects of experiencing CEC on anxiety, general stress, depression, and PTSD. However, there was also evident risk of bias in the data.

So not impossible? And perhaps there are methodologies here that could be useful for looking more broadly at a CEC theory of obesity?

• If you want to know why people get obese, it seems to me that one avenue would be to also look at people who neither diet, nor live in scarcity, nor get obese. What is happening differently in their bodies? Has anyone studied this?

• people have tried. Almost everything you find thin population X does, you have another thin population that does exactly the opposite. IIRC “Speaking English makes you fat” was a joke but also more empirically supported than the leading candiates.

EDIT: found it

• I am not aware of a low BMI population in which consumption of processed western food is just as common as it is in high-obesity regions. This seems to be an important counterexample.

• Does the timing work out with that? Highly processed food became dominant well before the great obesity-ing started, right?

• Highly processed food became dominant well before the great obesity-ing started, right?

Do we have evidence of that? As far as I can tell, the SMTM authors merely argue that some specific brands of processed food were available starting from the late 19th century, not that “highly processed food became dominant before the great obesity-ing started,” which is a much stronger claim.

Also, as I argued in this post, the obesity epidemic arguably started way before the SMTM authors often seem to imply it did. Quoting myself:

And it’s not as if Americans were that thin in the early 1970s! 47% of adults were overweight and 14.5% obese (a). In contrast, obesity rates are under 3% in traditional societies that engage in foraging or subsistence farming. Moreover, there is substantial (a) evidence (a) that Americans gained a lot of weight before 1970. It’s hard to know the overweight and obesity rates of the general population back in the 19th century, because there was no NHANES back then, but we do know that men at elite colleges (a) (source), Citadel cadets (a) (source) and veterans all started getting substantially fatter in the early 20th century.

I feel the need to stress this, because the SMTM authors claim (a) that there was an abrupt shift in obesity rates in the late 20th century, a claim that is probably based to some extent on an artifact of the definition of BMI (a), and so some people reading this might have the impression that 1970s Americans were really thin or something, when they really weren’t.

Here are a few charts from the sources I linked to. From this VoxEU article:

A chart by Random Critical Analysis, using data from this book:

A chart made with fancy statistical modeling, from this paper (note that the x-axis is each cohort’s birth year):

This is also relevant (from Random Critical Analysis as well):

We can see that BMI increases superlinearly with body fat %, so if body fat % is linearly growing in a population, BMIs will accelerate.

• Man I’d love to get this data with BF% rather than BMI (I realize this is not your fault and BMI is usually all that’s available, this is a complaint about the field). BF% increase obviously increases BMI, but so does muscle and height-while-keeping-BF%-the-same (because BMI doesn’t scale quite right with height).

Overall I find the second and third graphs especially convincing but would need to think more before updating, thanks for highlighting those.

• The answer might be genetics, so while that would be potentially interesting from a gene therapy point of view, if we find a food contaminant or environmental pollutant is causing the obesity epidemic, that might be much easier to fix—by banning it. After all, there might be many genes of individually small effect involved in resistance to this hypothetical contaminant or pollutant, and those genes might have all sorts of side-effects.

But you are right that by studying these people, and comparing them to obese people, we might in principle discover some (altered) biochemical pathway that is enlightening to know about.

• I emailed this to SMTM this morning:

Hypothesis: overeating is self-medication for emotional pain

Hi,

I admit I haven’t read your entire Chemical Hunger series. I did read the mysteries and the conclusion. And I did a “find on page” for the terms “adverse childhood”, “roseto”, and “blue zones”, and found zero hits.

I recommend watching this 7 minute video by the director of the original ACEs (Adverse Childhood Experiences) study. He was originally working on a weight-loss program at Kaiser (HMO). Of note: 55% of the women who were overweight had been sexually abused as a kid: https://​​www.youtube.com/​​watch?v=y3cCAcGeG8E

And check out the CDC site: https://​​www.cdc.gov/​​violenceprevention/​​aces/​​fastfact.html

A more in-depth talk Dr. Felitti gave: https://​​www.youtube.com/​​watch?v=-ns8ko9-ljU

And this tribute to him is informative too https://​​www.youtube.com/​​watch?v=q22Zt6aGwsA&t=514s

As well as the Blue Zones: https://​​www.bluezones.com/​​2016/​​11/​​power-9/​​

As you’ve found, obesity is viral, and the weight of the people around you influence your own weight.

It could be argued that high-altitude locations make it harder for people to come and go, and that increases community connectedness which keeps weights in check.

I think you’ve stumbled on a lot of correlations, but I believe the cause is emotional pain caused by a reduced feeling of love and belonging in society.

Thanks for listening. ·Dave

• New user here. I’m just wondering if anyone here has seen an analysis of snacking trends in relation to obesity? I have read through a lot of discussions, especially those related to A Chemical Hunger, but I have not seen snacking discussed as a contributor. Frequent snacking is, as far as I know, a fairly recent phenomenon. I would expect it keep insulin levels persistently elevated and to have some of the opposite effects of intermittent fasting. I think the case for acutely elevated insulin as a causal mechanism for obesity is a little overstated, since our body would have many post-prandial hours to achieve fat balance in adipose cells. However, the balance would be hard to achieve if that post-prandial window were shorter (or non-existent).

• 8 Jul 2022 6:56 UTC
1 point
0 ∶ 0

Has the hypothesis

excess sugar/​carbs → metabolic syndrome → constant hunger and overeating → weight gain

been disproved?

• I think the standard answer is that some traditional cultures rely quite heavily on carbs with very low incidence of obesity. Some even eat substantial amounts of sugar (e.g. as honey).

• The key here would be an exact quantification: how much carbs do these cultures consume in relation to the amount of physical activity.

• Herman Pontzer did such a study for the Hadza who eat a lot of honey.

He came to conclusions like “To Pontzer, this means that the human body seems to adjust to physical activity by saving calories on other physiological processes to keep total energy expenditure in check.”

• 2 Jul 2022 15:28 UTC
1 point
0 ∶ 1

Thanks!

I’ve definitely downgraded the (lithium) contamination theory. I’ll still take a (very modest) 100:1 bet on it tho :)

In regard to your (implied) criticism that SMTM’s blog post(s) haven’t been edited, it occurred to me that they may not be a ‘edit blog posts’ person. That seems related to their offered reasons for refusing bet challenge, i.e. ‘we’re in hypothesis exploration mode’. They might similarly be intending to write a follow-up blog post instead of editing the existing one.

(I actually prefer ‘new post’ versus ‘edit existing post’ as a blogging/​writing policy – if there isn’t a very nice (e.g. ‘GitHub like’) history diff visualization available of the edit history.)

• I think your response to SMTM is great. It points out all kinds of shortcomings in their representation of the underlying data. I don’t think lithium is anything like the comprehensive explanation they make it out to be. However, it’s also important to note that your analysis is (and claims to be) nothing more or less than a case for healthy skepticism. “It’s probably not the lithium” doesn’t mean “it’s not worth it to check.”

Note that Matthew Barnett, in his bet, claims to have credence of ~1% that the SMTM hypothesis is “true...”

… but didn’t even suggest what sort of evidence they could use as resolution criteria. Note: Matthew did later write a post (linked in his response to me below) doing exactly this. He just didn’t do it in the Twitter thread, partly because it’s a short format.

I doubt even SMTM thinks lithium explains literally 100% of the obesity epidemic. Matthew must not think they think that either. It’s very hard to interpret what these credences mean in the absence of a specific operationalization. I think it’s less than 1% likely that lithium has a perfect correlation with BMI (and thus that it completely explains obesity), but more than 1% likely that normal dietary doses of lithium are an important causal contributor to the obesity epidemic, via pathways that may be complex and not easy to parse from a single study or metric.

I’m skeptical that refusal to take a bet/​call-out on Twitter amounts to a failure to stand by your beliefs. People are loss averse and have a variety of feelings about both bets and the kinds of people who offer them. This bet offer in particular seems to give off more heat than light. It doesn’t feel fun or collaborative when I read through the Twitter thread, and it should feel that way.

Edit: I am splitting off my thoughts on the hypothesis itself into a separate comment, because the social element and epistemic element feel like they distract from each other.

• Note that Matthew Barnett, in his bet, claims to have credence of ~1% that the SMTM hypothesis is “true...” but didn’t even suggest what sort of evidence they could use as resolution criteria.

This feels unfair to me. I stated in the original tweet,

If [SMTM] takes me up on this offer, I will try to work with them to generate reasonable, unambiguous resolution criteria, and fair odds. I will risk up to \$1000.

The reason why I didn’t suggest any evidence that might be relevant is because I wanted to see what they would come up with (that, and also Twitter encourages you to be brief). However, I later wrote a post engaging with cruxes that I think are important, and in particular, what I think would need to be false for the (alternative) palatability theory of obesity to be falsified.

Other people have also accused me of being unfair to SMTM here, mostly because of the perverse incentives involved with betting them, but I don’t really buy this accusation. Letting someone choose the criteria to a proposed bet maximizes the chances that they can come up with something fair. And nowhere did I continue to harass them about not betting me. I also don’t think their failure to bet me played a significant role in anyone’s argument for why SMTM’s theory is false, anywhere (either in my comments, tweets, or in Natalia’s).

I doubt even SMTM thinks lithium explains literally 100% of the obesity epidemic.

Maybe not, but SMTM did literally summarize their theory as, “These contaminants are the only cause of the obesity epidemic, and the worldwide increase in obesity rates since 1980 is entirely attributable to their effects.” (Note that my bet was not about lithium but was instead about their general theory, which just proposes some small set of contaminants).

• However, I later wrote a post engaging with cruxes that I think are important, and in particular, what I think would need to be false for the (alternative) palatability theory of obesity to be falsified.

That does address the epistemic issue in the present moment. I hadn’t seen it. I will note that in my original comment.

Socially, I think it would have been preferable to first write your crux post, and then to approach them on Twitter. It doesn’t take persistent “harassment” (I didn’t see your post as harassment, and this seems like playful hyperbole to me) to create persistent social tension. A strident Twitter challenge to make a fairly large bet will do that all by itself. I have no idea whether the author(s?) at SMTM actually feel tense. It’s just how it resonated with me, on an emotional level.

I also agree that their failure to bet you is not relevant to most people’s credences for the lithium hypothesis, but their general approach to epistemics was a persistent theme in Natalia’s post, and this was the part that bugged me.

I doubt even SMTM thinks lithium explains literally 100% of the obesity epidemic.

Maybe not, but SMTM did literally summarize their theory as, “These contaminants are the only cause of the obesity epidemic, and the worldwide increase in obesity rates since 1980 is entirely attributable to their effects.” (Note that my bet was not about Lithium but was instead about their general theory, which just proposes some small set of contaminants).

Good catch, I wasn’t precise enough with my language. What I meant was, “I doubt even SMTM thinks lithium explains literally 100% of the prevalence of obesity,” and of course we should replace “lithium” with “environmental contaminants.”

I read them as giving the strongest possible version of their hypothesis. It would also be possible to give their statement about what they view as the most likely version of their hypothesis, in which environmental contaminants explain some range of percentages of the worldwide increase in obesity rates since 1980. These are two distinct and useful statements to make, but the strong statement is easier to make than the credence-based statement, and makes it easier for a new reader to integrate the subsequent argument.

• Letting someone choose the criteria to a proposed bet maximizes the chances that they can come up with something fair.

True, but it’s unclear to me how this relates to the parent. Is your implicit argument that because of this, refusing to take the bet does amount to a failure to stand by their beliefs? Because giving someone the fairest possible framework for a bet doesn’t mean there can be no other objection to taking it, nor imply anything about their argument if they choose not to.

STMT’s reason for doing so was very reasonable. We don’t want them to want it to be true (any more than is inevitable). In fact, I would go so far as to argue that bets on predictions about the world should never involve any party actively investigating those claims, and you should be suspicious of any research from someone who is conflicted in this way.

And while you claim that their “failure” to bet you didn’t play much of a role in anyone’s argument, you sure do seem to be making a lot of fairly combative noise about it. Betting on predictions is can be a useful collaborative tool, but in this case it feels more like a weapon-and a deterrent to speculative investigation.

• Is your implicit argument that because of this, refusing to take the bet does amount to a failure to stand by their beliefs?

No

And while you claim that their “failure” to bet you didn’t play much of a role in anyone’s argument, you sure do seem to be making a lot of fairly combative noise about it.

You are misrepresenting what happened here in a way I find fairly annoying. I am not, nor have I anywhere, independently brought up the bet to make any claim about SMTM’s standards of rigor, so far as I can recall. So, whatever “noise” you think I’m making about this bet must merely be referring to the replies I’m making to people, who are saying I’m being unfair. This includes,

1. Replying on Twitter to SMTM several months ago explaining why I think the perverse incentives are not so bad.

2. Replying to people in this thread, and more recently on Twitter, who are accusing me of being unfair to SMTM, and claiming that this bet somehow plays a critical role in the discussion (despite being from January).

This is totally distinct from making loud noises, trying to draw attention to the bet (which was, in any case, mentioned only as a side-note in the original post).

• No.

Well this isn’t helpful! I was genuinely trying to understand what the point of the quoted statement is. In the context, it seemed like that was the most reasonable interpretation. If it isn’t, then it’d be more productive to explain what you did mean.

I’m sorry that you feel misrepresented. For me, continuing to argue (in response to criticism or otherwise) that there is something wrong with STMT not taking the bet, and that their stated reason is insufficient, and making what read to me like implicit accusations of dishonesty, seems a lot like ‘making combative noise’. It’s quite an imprecise charge, though, and perhaps unhelpful of me to make.

Anyway, I certainly don’t want to be making combative noise, and policing your tone isn’t really adding anything to the (important) object-level discussion, so I’ll beat a retreat.

• For me, continuing to argue (in response to criticism or otherwise) that there is something wrong with STMT not taking the bet, and that their stated reason is insufficient, and making what read to me like implicit accusations of dishonesty, seems a lot like ‘making combative noise’.

For the record, I don’t think there’s anything wrong with what SMTM did in the thread.

But you can see what you’re doing right? If you criticize me, and I reply to the criticism, and then you say, “Ahah! You are making combative noises by replying to criticism!” it’s not a damning statement about my intent. Of course it makes sense that I’m going to reply to criticism, if I think the criticism is not justified.

As for whether I made an implicit accusation of dishonestly, let me just clarify: I did not. I do not currently think SMTM is being actively dishonest about anything related to this discussion, as far as I can tell. And in general, I think few researchers practice explicit dishonesty about their primary research.

Strong disagreement is not the same thing as accusing someone of dishonesty. I don’t know what claim you’re referring to when you said you read me as implicitly making an accusation of dishonesty, but I don’t see it anywhere.

ETA: Edited this comment to be less easily misinterpretable.