A Series of Unfortunate Omelettes: Lithium in Food Review & Survey Proposal

One thing that makes lithium a plausible explanation for the obesity epidemic is that clinical doses of lithium cause weight gain as a side-effect. A clinical dose of lithium is in the range of 1000 mg (“300 mg to 600 mg … 2 to 3 times a day”), and people pretty reliably gain weight on doses this high. In a 1976 review of case records, about 60% of people gained weight on clinical doses, with an average weight gain of about 10 kg.

But those are clinical doses, and it seems like the doses you’re getting from the environment are generally much smaller. There’s usually some lithium in modern drinking water, and there’s more lithium in drinking water now than there used to be. It seems to get into the water supply from things like drilled water wells, fracking, and fossil fuel prospecting, transport, and disposal. But even with all these sources of contamination, the dose you’re getting from your drinking water is relatively low, probably not much more than 0.2 mg per day. If you live right downstream from a coal plant, or you’re chugging liter bottles of mineral water on the regular, you could maybe get 5 or 10 mg/day. But no one is getting 1000 mg/day or even 300 mg/day from their drinking water. 

So what gives? 

Effects of Trace Doses

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

This is plausible for a few reasons. There’s lots of evidence (or at least, lots of papers) showing psychiatric effects at exposures of less than 1 mg (see for example meta-analysis, meta-analysis, meta-analysis, dystopian op-ed). 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. 

There’s also the case study of the Pima in the 1970s. The Pima are a group of Native Americans who live in the American southwest, particularly around the Gila River Valley, and they’re notable for having high rates of obesity and diabetes much earlier than other groups. They had about 0.1 mg/L in their water by the 1970s (which was 50x the national median at the time), for a dose of only about 0.2-0.3 mg per day, and were already about 40% obese. All this makes the trace lithium hypothesis seem pretty reasonable.

Unfortunately, no one knows where the weight gain effects of lithium kick in. As far as we can tell, there’s no research on this question. It might cause weight gain at doses of 10 mg, or 1 mg, or 0.1 mg. Maybe 0.5 mg a week on average is enough to make some people really obese. We just don’t know.

Some people in the nootropics community take lithium, often in the form of lithium orotate (they use orotate rather than other compounds because it’s available over-the-counter), as part of their stacks. Based on community posts like this, this, and this, the general doses nootropics enthusiasts are taking are in the range of 1-15 mg per day. 

We haven’t done a systematic review of the subreddit (but maybe you should, that would be a good project for someone) but they seem to report no effects or mild positive effects at 1 or 2 mg lithium orotate and brain fog and fatigue at 5 mg lithium orotate and higher. Some of them report weight gain, even on doses this low. The fact that a couple extra mg might be enough to push you over the line suggests that the weight gain tipping point is somewhere under 10 mg, maybe a lot under. And for what it’s worth, all of this is consistent with the only randomized controlled trial examining the effects of trace amounts of lithium which found results at just 0.4 mg a day. 

Clinical and Subclinical Doses

Another possibility is that people really ARE getting unintended clinical doses of lithium. We see two reasons to think that this might be possible.

#1: Doses in the Mirror may be…

The first is that clinical doses are smaller than they appear. 

When a doctor prescribes you lithium, they’re always giving you a compound, usually lithium carbonate (Li2CO3). Lithium is one of the lightest elements, so by mass it will generally be a small fraction of any compound it is part of. A simple molecular-weight calculation shows us that lithium carbonate is only about 18.7% elemental lithium. So if you take 1000 mg a day of lithium carbonate, you’re only getting 187.8 mg/day of the active ingredient.

The little purple orbs are the pharmacologically active lithium ions, everything else is non-therapeutic carbonate

For bipolar and similar disorders, lithium carbonate has become such a medical standard that people usually just refer to the amount of the compound. It’s very unusual for an ion to be a medication, so this nuance is one that some doctors/nurses don’t notice. It’s pretty easy to miss. In fact, we missed it too until we saw this reddit comment from u/PatienceClarence/, which begins, “First off we need to differentiate between the doses of lithium orotate vs elemental lithium. For example, my dosage was 130 mg orotate which would give me 5 mg ‘pure’ lithium…” 

Elemental lithium is what we really care about, and when we look at numbers from the USGS or serum samples or whatever, they’re all talking about elemental lithium. When we say people get 0.1 mg/day from their water, or when we talk about getting 3 mg from your food, that’s milligrams of elemental lithium. When we say that your doctors might give you 600 mg per day, that’s milligrams lithium carbonate — and only 112.2 milligrams a day of elemental lithium. With this in mind, we see that the dose of elemental lithium is always much lower than the dose as prescribed. 

A high clinical dose is 600 mg lithium carbonate three times a day (for a total of 1800 mg lithium carbonate or about 336 mg elemental lithium), but many people get clinical doses that are much smaller than this. Low doses seem to be more like 450 mg lithium carbonate per day (about 84 mg/day elemental lithium) or even as little as 150 mg lithium carbonate per day (about 28 mg/day elemental lithium).

Once we take the fact that lithium is prescribed as a compound into account, we see that the clinical dosage is really closer to something like 300 mg/day for a high dose and 30 mg/day for a low dose. So at this point we just need to ask, is it possible that people might occasionally be getting 30 mg/day or more lithium in the course of their everyday lives? Unfortunately we think the answer is yes.

#2: Concentration in Food

The other reason to think that modern people might be getting clinical or subclinical doses on the regular is that there’s clear evidence that lithium concentrates in some foods. 

Again, consider the Pima. The researchers who tested their water in the 1970s also tested their crops. While most crops were low in lithium, they found that one crop, wolfberries, contained an incredible 1,120 mg/kg.

By our calculations, you could easily get 15 mg of lithium in a tablespoon of wolfberry jelly. If the Pima ate one tablespoon a day, they would be getting around 100 times more lithium from that tablespoon than they were getting from their drinking water.

The wolfberries in question (Lycium californium) are a close relative of goji berries (Lycium barbarum or Lycium chinense). The usual serving size of goji berries is 30 grams, which if you were eating goji berries like the ones the Pima were eating, would provide about 33.6 mg of lithium. This already puts you into clinical territory, a little more than someone taking a 150 mg tablet of lithium carbonate.

If you had a hankering and happened to eat three servings of goji berries in one day, you would get just over 100 mg of lithium from the berries alone. We don’t know how much people usually eat in one go, but it’s easy enough to buy a pound (about 450 g) of goji berries online. We don’t have any measurements of how much lithium are in the goji berries you would eat for a snack, but if they contained as much lithium as the wolfberries in the Gila River Valley, the whole 1 lb package would contain a little more than 500 mg of lithium.

So. Totally plausible that some plants concentrate 0.1 mg/L lithium in water into 1,120 mg/kg in the plant, because Sievers & Cannon have measurements of both. Totally plausible that you could get 10 or even 100 mg if you’re eating a crop like this. So now we want to know, are there other crops that concentrate lithium? And if so, what are they?

In this review, we take a look at the existing literature and try to figure out how much lithium there is in different foods. What crops does it concentrate in? Is there any evidence that foods are further contaminated in processing or transport? There isn’t actually all that much work on these questions, but we’ll take a look at what we can track down.

Let’s not bury the lede: we find evidence of subclinical levels of lithium in several different foods. But most of the sources that report these measurements are decades old, and none of them are doing anything like an exhaustive search. That’s why at the end of this piece, we’re going to talk a little bit about our next project, a survey of lithium concentrations in foods and beverages in the modern American food supply.

Because of this, our goal is not to make this post an exhaustive literature review; instead, our goal is to get a reasonable sense of how much lithium is in the food supply, and where it is. When we do our own survey of modern foods, what should we look at first? This review is a jumping off point for our upcoming empirical work.

Context for the Search

But first, a little additional context. 

There are a few official estimates of lithium consumption we should consider (since these are in food and water, all these numbers should be elemental lithium). This review paper from 2002 says that “the U.S. Environmental Protection Agency (EPA) in 1985 estimated the daily Li intake of a 70 kg adult to range from [0.650 to 3.100 mg].” The source they cite for this is “Saunders, DS: Letter: United States Environmental Protection Agency. Office of Pesticide Programs, 1985”, but we can’t find the original letter. As a result we don’t really know how accurate this estimate is, but it suggests people were getting about 1-3 mg per day in 1985.

These numbers are backed up by some German data which appear originally to be from a paper from 1991, which we will discuss more in a bit: 

In Germany, the individual lithium intake per day on the average of a week varies between [0.128 mg/day] and [1.802 mg/day] in women and [0.139] and [3.424 mg/day] in men. 

The paper also includes histograms of those distributions: 

Both of these say “mg/day” but we’re pretty sure that’s 1000x too high and they should say “µg/day”. If it were mg/day we think many of these people would be dead?

We want to call your attention to the shape of both of these distributions, because the shape is going to be important throughout this review. Both distributions are pretty clearly lognormal, meaning they peak early on but then have a super long tail off to the right. For example, most German men in this study were getting only about 0.2 to 0.4 mg of lithium per day, but twelve of them were getting more than 1 mg a day, and five of them were getting more than 2 mg a day. At least one person got more than 3 mg a day. And this paper is looking at a pretty small group of Germans. If they had taken a larger sample, we would probably see a couple people who were consuming even more. You see a similar pattern for women, just at slightly lower doses.

We expect pretty much every distribution we see around food and food exposure to be lognormal. The amount people consume per day should usually be lognormally distributed, like we see above. The distribution of lithium in any foods and crops will be lognormal. So will the distribution of lithium levels in water sources. For example, lithium levels in that big USGS dataset of groundwater samples we always talk about are distributed like this:

With scatterplot because those outliers are basically invisible on the histogram

Again we see a clear lognormal distribution. Most groundwater samples they looked at had less than 0.2 mg/L lithium. But five had more than 0.5 mg/L and two had more than 1 mg/L.

This is worth paying close attention to, because when a variable is lognormally distributed, means and medians will not be very representative. For example, in the groundwater distribution you see above, the median is .0055 mg/L and the mean is .0197 mg/L. 

These sound like really tiny amounts, and they are! But the mean and the median do not tell anywhere close to the full story. If we keep the long tail of the distribution in mind, we see that about 4% of samples contain more than 0.1 mg/L, about 1% of samples contain more than 0.2 mg/L, and of course the maximum is 1.7 mg/L. 

This means that about 4% of samples contain more than 20x the median, about 1% of samples contain more than 40x the median, and the maximum is more than 300x the median.

Put another way, about 4% of samples contain more than 5x the mean, about 1% of samples contain more than 10x the mean, and the maximum is more than 80x the mean.

We should expect similar distributions everywhere else, and we should expect means and medians to consistently be misleading in the same way. So if we find a crop with 1 mg/kg of lithium on average, that suggests that the maximum in that crop might be as high as 80 mg/kg! If this math is even remotely correct, you can see why crops that appear to have a low average level of lithium might still be worth empirically testing.

Another closely related point: that USGS paper only found those outliers because it’s a big survey, 4700 samples. Small samples will be even more misleading. Let’s imagine the USGS had taken a small number of samples instead. Here are some random sets of 6 observations from that dataset:

0.044, 0.007, 0.005, 0.036, 0.001, 0.002

0.002, 0.028, 0.005, 0.001, 0.009, 0.001

0.003, 0.006, 0.002, 0.001, 0.001, 0.006

We can see that small samples ain’t representative. If we looked at a sample of six US water sources and found that all of them contained less than 0.050 mg/L of lithium, we would miss that some US water sources out there contain more than 0.500 mg/L. In this situation, there’s no substitute for a large sample size (or, the antidote is to be a little paranoid about how long the tail is).

So if we looked at a sample of (for example) six lemons, and found that all of them contained less than 10 mg/kg of lithium, we might easily be missing that there are lemons out there that contain more than 100 mg/kg.

In any case, the obvious lognormal distribution fits really well with the kind of bolus-dose explanation we discussed with JP Callaghan, who said: 

My thought was that bolus-dosed lithium (in food or elsewhere) might serve the function of repeated overfeeding episodes, each one pushing the lipostat up some small amount, leading to overall slow weight gain. … I totally vibe with the prediction that intake would be lognormally distributed. … lognormally distributed doses of lithium with sufficient variability should create transient excursions of serum lithium into the therapeutic range.

In the discussion with JP Callaghan, we also said:

Because of the lognormal distribution, most samples of food … would have low levels of lithium — you would have to do a pretty exhaustive search to have a good chance of finding any of the spikes. So if something like this is what’s happening, it would make sense that no one has noticed. 

What we’re saying is that even 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. If we take that model seriously, the average amount might not not be the real driver, and we should focus on whether there are huge lithium bombs out there, and how often you might encounter them. Or it could be even more complicated! Maybe some foods give you repeated moderate doses, and others give you rare megadoses. 

Two final notes before we start the review: 

First, if two sources disagree — one says strawberries are really high in lithium and the other says that strawberries are really low in lithium, or something — we should keep in mind that disagreement might mean something like “the strawberries were grown in different conditions (i.e. one batch was grown in high-lithium soil and the other batch wasn’t)” or even “apparently identical varieties of strawberries concentrate lithium differently”. There isn’t a simple answer to simple-sounding questions like “how much lithium is in a strawberry” because reality is complicated and words make it easy to hide that complexity without thinking about it.

Second, we want to remind you that whatever dose causes obesity, lithium is also a powerful sedative with well-known psychiatric effects. If you’re getting doses up near the clinical range, it’s gonna zonk you out and probably stress your kidneys. 

Ok. What crops concentrate lithium?

Lithium Concentration

Unfortunately we couldn’t find several of the important primary sources, so in a number of places, we’ve had to rely on review papers and secondary sources. We’re not going to complain “we couldn’t find the primary source” every time, but if you’re ever like “why are they citing a review paper instead of the original paper?” this is probably why.

We should warn you that these sources can be a little sloppy. Important tables are labeled unclearly. Units are often given incorrectly, like those histograms above that say mg/day when they should almost certainly say µg/day. When you double-check their citations, the numbers don’t always match up. For example, one of the review papers said that a food contained 55 mg/kg of lithium. But when we double-checked, their source for that claim said just 0.55 mg/kg in that food. So we wish we were working with all the primary sources but we just ain’t. Take all these numbers with a grain of salt.

Particularly important modern reviews include Lithium toxicity in plants: Reasons, mechanisms and remediation possibilities by Shahzad et al. (2016), Regional differences in plant levels and investigations on the phytotoxicity of lithium by Franzaring et al. (2016), and Lithium as an emerging environmental contaminant: Mobility in the soil-plant system by Robinson et al. (2018). Check those out if you finish this blog post and you want to know more.

It’s worth noting just how concerned some of these literature reviews sound. Shahzad et al. (2016) say in their abstract, “The contamination of soil by Li is becoming a serious problem, which might be a threat for crop production in the near future. … lack of considerable information about the tolerance mechanisms of plants further intensifies the situation. Therefore, future research should emphasize in finding prominent and approachable solutions to minimize the entry of Li from its sources (especially from Li batteries) into the soil and food chain.”

Older reviews include The lithium contents of some consumable items by Hullin, Kapel, and Drinkall — a 1969 paper which includes a surprisingly lengthy review of even older sources, citing papers as far back as 1917. Sadly we weren’t able to track down most of these older sources, and the ones we could track down were pretty vague. Papers from the 1930s just do not give all that much detail. Still, very cool to have anything this old. 

There’s also Shacklette, Erdman, Harms, and Papp (1978), Trace elements in plant foodstuffs, a chapter from (as far as we can tell) a volume called “Toxicity of Heavy Metals in the Environment”, which is part of a series of reference works and textbooks called “HAZARDOUS AND TOXIC SUBSTANCES”. It was sent to us by a very cool reader who refused to accept credit for tracking it down. If you want to see this one, email us.

A bunch of the best and most recent information comes from a German fella named Manfred Anke, who published a bunch of papers on lithium in food in Germany in the 1990s and 2000s. He did a ton of measurements, so you will keep seeing his name throughout. Unfortunately the papers we found from Anke mostly reference measurements from earlier work he did, which we can’t find. Sadly he is dead so we cannot ask him for more detail.

From Anke, in case anyone can track them down, we’d especially like to see a couple papers from the 1990s. Here they are exactly as he cites them:  

Anke’s numbers are very helpful, but we think they are a slight underestimation of what is in our food today. We’re pretty sure lithium levels in modern water are higher than levels in the early 1990s, and we’re pretty sure lithium levels are higher in US water than in water in Germany. In a 2005 paper, Anke says: “In Germany, the lithium content of drinking water varies between 4 and 60 µg/L (average : 10 µg/L).” Drinking water in the modern US varies between undetectable and 1700 µg/L (1.7 mg/L), and even though that 1700 is an outlier, about 8% of US groundwater samples contain more than 60 µg/L, the maximum Anke gives for Germany. The mean for US groundwater is 19.7 µg/L, compared to the 10 µg/L Anke reports.

So the smart money is that Anke’s measurements are probably all lower than the levels in modern food, certainly lower than the levels in food in the US.

Here’s another thing of interest: in one paper Anke estimates that in 1988 Germany, the average daily lithium intake for women was 0.373 mg, and the average daily lithium intake for men was 0.432 mg (or something like that; it REALLY looks like he messed up labeling these columns, luckily the numbers are all pretty similar). By 1992, he estimates that the average daily lithium intake for women was 0.713 mg, and the average daily lithium intake for men was 1.069 mg. He even explicitly comments, saying, “the lithium intake of both sexes doubled after the reunification of Germany and worldwide trade.”

That last bit about trade suggests he is maybe blaming imported foods with higher lithium levels, but it’s not really clear. He does seem to think that many foreigners get more lithium than Germans do, saying, “worldwide, a lithium intake for adults between [0.660 and 3.420 mg/day] is calculated.”

Anyways, on to actual measurements.

Beverages

Beverages are probably not giving you big doses of lithium, with a few exceptions.

Most drinking water doesn’t contain much lithium, rarely poking above 0.1 mg/L. Some beverages contain more, but not a lot more. The big exception, no surprise, is mineral water.

As usual, Anke and co have a lot to say. The Anke paper from 2003 says, “cola and beer deliver considerable amounts of lithium for humans, and this must be taken into consideration when calculating the lithium balance of humans.” The Anke paper from 2005 says that “amounts of [0.002 to 5.240 mg/L] were found in mineral water. Like tea and coffee, beer, wine and juices can also contribute to the lithium supply.” But the same paper reports a range of just 0.018 – 0.329 mg/L in “beverages”. Not clear where any of these numbers come from, or why they mention beer in particular — the citation appears to be the 1995 Anke paper we can’t find. 

In fact, Anke seems to disagree with himself. The 2005 paper mentions tea and coffee contributing to lithium exposure. But the 2003 paper says, “The total amount in tea and coffee, not their water-soluble fraction in the beverage, was registered. Their low lithium content indicates that insignificant amounts of lithium enter the diet via these beverages.”

This 2020 paper, also from Germany, finds a weak relationship for beer and wine and a strong relationship for tea with plasma concentrations for lithium. We think there are a lot of problems with this method (the serum samples are probably taken fasted, and lithium moves through the body pretty quickly) but it’s interesting.

Franzaring et al. (2016), one of those review papers, has a big figure summarizing a bunch of other sources, which has this to say about some beverages: 

For water, 1 ppm is approximately 1 mg/L

So obviously mineral water can contain a lot — if you drank enough, you could probably get a small clinical dose from mineral water alone. On the other hand, who’s drinking a liter of mineral water? Germans, apparently.

We think their sources for wine are Classification of wines according to type and region based on their composition from 1987 and Classification of German White Wines with Certified Brand of Origin by Multielement Quantitation and Pattern Recognition Techniques from 2004. The 1987 paper reports average levels of lithium in Riesling and Müller-Thurgau wines in the range of about 0.010 mg/L, and a maximum of only 0.022 mg/L. The 2004 paper looks at several German white wines, and reports a maximum of 0.150 mg/L. This is pretty unsystematic but does seem to indicate an increase. 

This paper from 2000 similarly finds averages of 0.035 and 0.019 mg/L in red wines from northern Spain. This 1994 paper and this 1997 paper both report similar values. We also found this 1988 paper looking at French red wines which suggests a range from 2.61 to 17.44 mg/L lithium. Possibly this was intended to be in µg/L instead of in mg/L? “All results are in milligrams per liter except Li, which is in micrograms per liter” is a disclaimer we’ve seen in more than one of these wine papers.

So it might be good to check, but overall we don’t think you’ll see much more than 0.150 mg/L in your wine, and most of you are hopefully drinking less than a full liter at a time.

She’s just so happy!

The most recent and most comprehensive source for beverages, however, is a 2020 paper called Lithium Content of 160 Beverages and Its Impact on Lithium Status in Drosophila melanogaster. Forget the Drosophila, let’s talk about all those beverages. This is yet another German paper, and they analyzed “160 different beverages comprising wine and beer, soft and energy drinks and tea and coffee infusions … by inductively coupled plasma mass spectrometry (ICP-MS).” And unlike other sources, they give all the numbers — If you want to know how much lithium they found in Hirschbraeu/Adlerkoenig, “Urtyp, hell” or the cola known as “Schwipp Schwapp”, you can look that up. 

They find that, aside from mineral water, most beverages in Germany contain very little lithium. Concentration in wine, beer, soft drinks, and energy drinks was all around 0.010 mg/L, and levels in tea and coffee barely ever broke 0.001 mg/L.

The big outlier is the energy drink “Acai 28 Black, energy”, which contained 0.105 mg/L. This is not a ton in the grand scheme of things — it’s less than some sources of American drinking water — but it’s a lot compared to the other beverages in this list. They mention, “it has been previously reported that Acai pulp contains substantial concentrations of other trace elements, including iron, zinc, copper and manganese. In addition to acai extract, Acai 28 black contains lemon juice concentrate, guarana and herb extracts, which possibly supply Li to this energy drink.”

BEWARE

We want to note that beverages in America may contain more lithium, just because American drinking water contains more lithium than German drinking water does. But it’s doubtful that people are getting much exposure from beverages beyond what they get from the water it’s made with. 

Basic Foods

We also have a few leads on what might be considered “basic” or “component” foods.

Anke mentions sugars a bit, though doesn’t go into much detail, saying, “honey and sugar are also extremely poor in lithium…. The addition of sugar apparently leads to a further reduction of the lithium content in bread, cake, and pastries.“ At one point he lists the range of “Sugar, honey” as being 0.199 – 0.527 mg/kg, with a mean of 0.363 mg/kg. That’s pretty low.

We also have a little data from the savory side. This paper from 1969 looked at levels in various table salts, finding (in mg/kg):

On the one hand, those are relatively high levels of lithium. On the other hand, who’s eating a kilogram of salt? Even if table salt contains 3 mg/kg, you’re just never gonna get even close to getting 1 mg from your salt.

Plant-Based Foods

It’s clear that plants can concentrate lithium, and some plants concentrate lithium more than others. It’s also clear that some plants concentrate lithium to an incredible degree. This last point is something that is emphasized by many of the reviews, with Shahzad et al. (2016) for example saying, “different plant species can absorb considerable concentration [sic] of Li.” 

Plant foods have always contained some lithium. The best estimate we have for preindustrial foods is probably this paper that looked at foods in the Chocó rain forest around 1970, and found (in dry material): 3 mg/kg in breadfruit; 1.5 mg/kg in cacao, 0.4 mg/kg in coconut, 0.25 mg/kg in taro, 0.4 mg/kg in yam, 0.6 mg/kg in cassava, 0.5 mg/kg in plantain fruits, 0.1 mg/kg in banana, 0.3 mg/kg in rice, 0.01 mg/kg in avocado, 0.5 mg/kg in dry beans, and 0.05 mg/kg in corn grains. Not nothing, but pretty low doses overall.

There are a few other old sources we can look at. Shacklette, Erdman, Harms, and Papp (1978) report a paper by Borovik-Romanova from 1965, in which she “reported the Li concentration in many plants from the Soviet Union to range from 0.15 to 5 [mg/kg] in dry material; she reported Li in food plants as follows ([mg/kg] in dry material): tomato, 0.4; rye, 0.17; oats, 0.55; wheat, 0.85; and rice, 9.8.” That’s a lot in rice, but we don’t know if that’s reliable, and we haven’t seen any other measurements of the levels in rice. We weren’t able to track the Borovik-Romanova paper down, unfortunately.

From here, we can try to narrow things down based on the better and more modern measurements we have access to.

Cereals

We haven’t seen very much about levels in cereals / grains / grass crops, but what we have seen suggests very low levels of accumulation.

Hullin, Kapel, and Drinkall (1969) mention an earlier review which found that the Gramineae (grasses) were especially “poor in lithium”, giving a range of 0.47-1.07 mg/kg. 

Borovik-Romanova reported, in mg/kg, “rye, 0.17; oats, 0.55; wheat, 0.85; and rice, 9.8” in 1965 in the USSR. Most of these concentrations are very low. Again, rice is abnormally high, but this measurement isn’t at all corroborated. And since we haven’t been able to find this primary source, there’s a good chance it should read 0.98 instead.

Anke, Arnhold, Schäfer, & Müller (2005) report levels from 0.538 to 1.391 mg/kg in “cereal products”, and in a 2003 paper, say “the different kinds of cereals grains are extremely lithium-poor as seeds.” Anke reports slightly lower levels in derived products like “bread, cake”. 

There’s also this unusual paper on corn being grown hydroponically in solutions containing various amounts of lithium. They find that corn is quite resistant to lithium in its water, actually growing better when exposed to some lithium, and only seeing a decline at concentrations around 64 mg/L. (“the concentration in solution ranging from 1 to 64 [mg/L] had a stimulating effect, whereas a depression in yielding occurred only at the concentrations of 128 and 256 [mg/L].”) But the plant also concentrates lithium — even when only exposed to 1 mg/L in its solution, the plant ends up with an average of about 11 mg/kg in dry material. Unfortunately they don’t seem to have measured how much ends up in the corn kernels, or maybe they didn’t let the corn develop that far. Seems like an oversight. (Compare also this similar paper from 2012.)

Someone should definitely double-check those numbers on rice to be safe, and corn is maybe a wildcard, but for now we’re not very worried about cereal crops.

Leafy Vegetables

A number of sources say that lithium tends to accumulate in leaves, suggesting lithium levels might be especially high in leafy foods. While most of us are in no danger of eating kilograms of cabbage, it’s worth looking out for. 

In particular, Robinson et al. (2018) observed significant concentration in the leaves of several species as part of a controlled experiment. They planted beetroot, lettuce, black mustard, perennial ryegrass, and sunflower in controlled environments with different levels of lithium exposures. “When Li was added to soil in the pot experiment,” they report, “there was significant plant uptake … with Li concentrations in the leaves of all plant species exceeding 1000 mg/kg (dry weight) at Ca(NO3)2-extractable concentrations of just 5 mg/kg Li in soil, representing a bioaccumulation coefficient of >20.” For sunflowers in particular, “the highest Li concentrations occurred in the bottom leaves of the plant, with the shoots, roots and flowers having lower concentrations.”

Obviously this is reason for concern, but these are plants grown in a lab, not grown under normal conditions. We want to check this against actual measurements in the food supply. 

Hullin, Kapel, and Drinkall (1969) report that an earlier source, Bertrand (1943), “found that the green parts of lettuce contained 7.9 [mg/kg] of lithium.” They wanted to follow up on this surprisingly high concentration, so they tested some lettuce themselves, finding: 

This pretty clearly contradicts the earlier 7.9 mg/kg, though the fact that lettuce can contain up to 2 mg/kg is still a little surprising. This could be the result of lettuce being grown in different conditions, the lognormal distribution, etc., but even so it’s reassuring to see that not all lettuce in 1969 contained several mg per kg.

In this study from 1990, the researchers went and purchased radish, lettuce and watercress at the market in Brazil, and found relatively high levels in all of them:

Let’s also look at this modern table that reviews a couple more recent sources, from Shahzad et al.:

FW = Fresh Weight and DM = Dry Matter, we think? 

None of these are astronomical, but it’s definitely surprising that spinach contains more than 4 mg/kg and celery and chard both contain more than 6 mg/kg, at least in these measurements.

So not to sound too contrarian but, maybe too many leafy greens are bad for your health. 

Fruits & Non-Leafy Veggies

Anke, Arnhold, Schäfer, & Müller (2005) say that “fruits and vegetables supply 1.0 to 7.0 mg Li/kg,” and report levels from 0.383 to 6.707 mg/kg in fruits. 

This is a wide range, and a pretty high ceiling. But as usual, Anke is much vaguer than we might hope. He gives some weird hints, but no specific measurements. In the 2003 paper, Anke says, “as a rule, fruits contain less lithium than vegetative parts of plants (vegetables). Lemons and apples contained significantly more lithium, with about 1.4 mg/kg dry matter, than peas and beans.”

More specific numbers have been hard to come by. We’ve found a pretty random assortment, like how Shahzad et al. report that “in a hydroponic experiment, Li concentration in nutrient solution to 12 [mg/L], increased cucumber fruit yield, fruit sugar, and ascorbic acid levels, but Li did not accumulate in the fruit (Rusin, 1979).” It’s interesting that cucumbers survive just fine in water containing up to 12 mg/L, and that suggests that lithium shouldn’t accumulate in cucumbers under any realistic water levels. But cucumbers are not a huge portion of the food supply.

What we do see all the time is sources commenting on how citrus plants are very sensitive to lithium. Anke says, “citrus trees are the most susceptible to injury by an excess of lithium, which is reported to be toxic at a concentration of 140–220 p.p.m. in the leaves.” Robinson et al. (2018) say, “citing numerous sources, Gough et al. (1979) reported a wide variation in plant tolerance to Li; citrus was found to be particularly sensitive, whilst cotton was more tolerant.” Shahzad et al. say, “Bradford (1963) found reduced and stunted growth of citrus in southern California, U.S.A., with the use of highly Li-contaminated water for irrigation. …  Threshold concentrations of Li in plants are highly variable, and moderate to severe toxic effects at 4–40 mg Li kg−1 was observed in citrus leaves (Kabata-Pendias and Pendias, 1992).” This Australian Water Quality Guidelines for Fresh and Marine Waters document says, “except for citrus trees, most crops can tolerate up to 5 mg/L in nutrient solution (NAS/NAE 1973). Citrus trees begin to show slight toxicity at concentrations of 0.06–0.1 mg/L in water (Bradford 1963). Lithium concentrations of 0.1–0.25 mg/L in irrigation water produced severe toxicity symptoms in grapefruit … (Hilgeman et al. 1970)”.

All tantalizing, but we can’t get access to any of those primary sources. For all we know this is a myth that’s been passed around the agricultural research departments since the 1960s.

The citrus is tantalizing, get it? 

Even if citrus trees really are extra-sensitive to lithium, it’s not clear what that means for their fruits. Maybe it means that citrus fruits are super-low in lithium, since the tree just dies if it’s exposed to even a small amount. Or maybe it means that citrus fruits are super-high in lithium — maybe citrus trees absorb lithium really quickly and that’s why lithium kills them at relatively low levels.

So it’s interesting but at this point, the jury is out on citrus.

Nightshades

Multiple sources mention that the Solanaceae family, better known as nightshades, are serious concentrators of lithium. Hullin, Kapel, and Drinkall mention that even in the 1950s, plant scientists were aware that nightshades are often high in lithium. Anke, Schäfer, & Arnhold (2003) mention, “Solanaceae are known to have the highest tolerance to lithium. Some members of this family accumulate more than 1000 p.p.m. lithium.” Shacklette, Erdman, Harms, and Papp (1978) even mention a “stimulating effect of Li as a fertilizer for certain species, especially those in the Solanaceae family.”

Shahzad et al. (2016) say, “Schrauzer (2002) and Kabata-Pendias and Mukherjee (2007) noted that plants of Asteraceae and Solanaceae families showed tolerance against Li toxicity and exhibited normal plant growth,” and, “some plants of the Solanaceae family, when grown in an acidic climatic zone accumulate more than 1000 mg/kg Li.” We weren’t able to track down most of their sources for these claims, but we did find Schrauzer (2002). He mentions that Cirsium arvense (creeping thistle) and Solanum dulcamara (called things like fellenwort, felonwood, poisonberry, poisonflower, scarlet berry, and snakeberry; probably no one is eating these!) are notorious concentrators of lithium, and he repeats the claim that some Solanaceae accumulate more than 1000 mg/kg lithium, but it’s not clear what his source for this was.

Hullin, Kapel, and Drinkall mention in particular one source from 1952 that found a range of 1.8-7.96 [mg/kg] in members of the Solanaceae. 7.9 mg/kg in some nightshades is enough to be concerned, but they don’t say which species this measurement comes from. 

The finger seems to be pointing squarely at the Solanaceae — but which Solanaceae? This family is huge. If you know anything about plants, you probably know that potatoes and tomatoes are both nightshades, but you may not know that nightshades also include eggplants, the Capsicum (including e.g. chili peppers and bell peppers), tomatillos, some gooseberries, the goji berry, and even tobacco. 

We’ve already seen how wolfberries / goji berries can accumulate crazy amounts under the right circumstances, which does make this Solanaceae thing seem even more plausible. 

Anke, Schäfer, & Arnhold (2003) mention potatoes in particular in one section on vegetable foods, saying: “All vegetables and potatoes contain > 1.0 mg lithium kg−1 dry matter.” There isn’t much detail, but the paper does say, “peeling potatoes decreases their lithium content, as potato peel stores more lithium than the inner part of the potato that is commonly eaten.”

That same paper that tries to link diet to serum lithium levels does claim to find that a diet higher in potatoes leads to more serum lithium, but we still think this paper is not very good. If you look at table 4, you see that there’s not actually a clear association between potatoes and serum levels. Table 5 says that potatoes come out in a regression model, but it’s a bit of an odd model and they don’t give enough detail for us to really evaluate it. And again, these serum concentrations were taken fasted, so they didn’t measure the right thing.

It’s much better to just measure the lithium in potatoes directly. Anke seems to have done this in the 1990s, but he’s not giving any details. We’ll have to go back all the way to 1969, when Hullin, Kapel, and Drinkall included three varieties of potatoes in their study (numbers in mg/kg):

These potatoes, at least, are pretty low in lithium. The authors do specifically say these were peeled potatoes, which may be important in the light of Anke’s comment about the peels. These numbers are pretty old, and modern potatoes probably are exposed to more lithium. But even so, these potatoes do not seem to be mega-concentrators, and Hullin, Kapel, and Drinkall did find some serious concentrators even back in 1969. 

This is especially interesting to us because it provides a little support for the idea that the potato diet might cause weight loss by reducing your lithium intake and forcing out the lithium already in your system with a high dose of potassium, or something. At the very least, it looks like you’d get less lithium in your diet if you lived on only potatoes than if you somehow survived on only lettuce (DO NOT TRY THE LETTUCE DIET).

Apparently the nightshade family’s tendency to accumulate lithium does not include the potatoes (unless the peeling made a huge difference?). This suggests that the high levels might have come from some OTHER nightshade. Obviously we have already seen huge concentrations in the goji berry (or at least, a close relative). But what about other nightshades, like tomatoes, eggplant, or bell peppers? 

Hullin, Kapel, and Drinkall do frustratingly say, “[The lithium content] of the tomato will be reported elsewhere.” But they don’t discuss it beyond that, at least not in this paper. We’ll have to look to other sources.

Shacklette et al. report: “Borovik-Romanova reported the Li concentration in [dry material] … tomato, 0.4 [mg/kg].” This is not much, though these numbers are from 1965, and from the USSR.

A stark contrast can be found in one of Anke’s papers, where they state, “Fruits and vegetables supply 1.0 to 7.0 mg Li/kg food DM. Tomatoes are especially rich in Li (7.0 mg Li/kg DM).” 

This is a lot for a vegetable fruit! It occurs to us that tomatoes are pretty easy to grow hydroponically, and you could just dose distilled water with a known amount of lithium. If any of you are hydroponic gardeners and want to try this experimentally, let us know! 

But tomatoes are obviously beaten out by wolfberries/goji berries, and they also can’t compare to this dark horse nightshade: tobacco.

SURPRISE

That’s right — Hullin, Kapel, and Drinkall (1969) also measured lithium levels in tobacco. They seem to have done this not because it’s another nightshade, but because previous research from the 1940s and 1950s had found that lithium concentrations in tobacco were “extraordinarily high”. For their own part, Hullin and co. found (mg/kg in ash): 

This is a really interesting finding, and in a crop we didn’t expect people to examine, since tobacco isn’t food.

At the same time, measuring ash is kind of cheating. Everything organic will be burned away in the cigarette or pipe, so the level of any salt or mineral will appear higher than it was in the original substance. As a result, we don’t really know the concentration in the raw tobacco. This is also the lithium that’s left over in the remnants of tobacco after it’s been smoked, so these measurements are really the amount that was left unconsumed, which makes it difficult to know how much might have been inhaled. Even so, the authors think that “the inhalation of ash during smoking could provide a further source of this metal”. 

This is also interesting in combination with the fact that people with psychiatric disorders often seem to self-medicate with tobacco. Traditionally schizophrenics are the ones drawn to being heavy smokers, but smoking is disproportionately common in bipolar patients as well. Researchers have generally tried to explain this in terms of nicotine, which we think of as being the active ingredient in tobacco, but given these lithium levels, maybe psychiatric patients smoke so much because they’re self-medicating with the lithium? Or maybe lithium exposure through the lungs causes schizophrenia and bipolar disorder? (For comparison, see Scott Alexander discussing a similar idea.)  

We didn’t find measurements for any other nightshades, but we hope to learn more in our own survey.

Animal-Based Foods

Pretty much everything we see suggests that animal products contain more lithium on average than plant-based foods. This makes a lot of general sense because of biomagnification. It also makes particular sense because many food animals consume huge quantities of plant stalks and leaves, and as we’ve just seen, stalks and leaves tend to accumulate more lithium than other parts of the plants.

toxic waste make bear sad

But the bad news is that, like pretty much everything else, levels in animal products are poorly-documented and we have to rely heavily on Manfred Anke again. He’s a good guy, we just wish — well we wish we had access to his older papers.

It’s like he’s toying with us!!!

Meat

Meat seems to contain a consistently high level of lithium. Apparently based on measurements he took in the 1990s, Anke calculates that meat products contain an average of about 3.2 mg/kg, and he gives a range of 2.4 to 3.8 mg/kg. 

In Anke, Arnhold, Schäfer, & Müller (2005) he elaborates just a little, saying, “Poultry, beef, pork and mutton contain lithium concentrations increasing in that order.”

In place of more detailed measurements, Anke, Schäfer, & Arnhold (2003) give us this somewhat difficult paragraph: 

On average, eggs, meat, sausage, and fish deliver significantly more lithium per kg of dry matter than most cereal foodstuffs. Eggs, liver, and kidneys of cattle had a mean lithium content of 5 mg/kg. Beef and mutton contain more lithium than poultry meat. Green fodder and silage consumed by cattle and sheep are much richer in lithium than the cereals largely fed to poultry. Sausage and fish contain similar amounts of lithium to meat. 

Beyond this, we haven’t found much detail to report. And even Anke can’t keep himself from mentioning how meat plays second fiddle to something else:

… Poultry, beef, pork and mutton contain lithium concentrations increasing in that order. Most lithium is delivered to humans by eggs and milk (> 7000 µg/kg DM). 

This is backed up by Hullin, Kapel, and Drinkall (1969), who said: 

Among foods of animal origin, those which have been found to contain lithium include eggs (Press, 1941) and milk (Wright & Papish, 1929; Drea, 1934).

So let’s leave meat behind for now and look at the real heavy-hitters.

Dairy

The earliest report we could find for milk was this 1929 Science publication mentioned by Hullin, Kapel, and Drinkall. But papers this old are pretty terse. It’s only about three-quarters of a page, and the only information they give about lithium is that it is included in the “elements not previously identified but now found to be present” in milk. 

Anke can do one better, and estimates an average for “Milk, dairy products” of 3.6 mg/kg with a range of 1.1 to 7.5 mg/kg. This suggests that the concentration in dairy products is pretty high across the board, but also that there’s considerable variation.

Anke explains this in a couple ways. First of all, he says that there were, “significant differences between the lithium content of milk”, and he suggests that milk sometimes contained 10 mg/kg in dry matter. This seems to contradict the range he gives above, but whatever. 

He also points out that other dairy products contain less lithium. For example, he says that butter is “lithium-poor”, containing only about 1.2 mg/kg dry matter, which seems to be the bottom of the range for dairy. “In contrast to milk,” he says, “curd cheese and other cheeses only retain 20–55% of lithium in the original material available for human nutrition. The main fraction of lithium certainly leaves cheese and curd cheese via the whey.”

This is encouraging because we love cheese and we are glad to know it is not responsible for poisoning our brains — at least, not primarily. It’s also interesting because 20-55% is a pretty big range; we’d love to know if some cheeses concentrate more than others, or if this is just an indication of the wide variance he mentioned earlier in milk. Not that we really need it, but if you have access to the strategic cheese reserve, we’d love to test historical samples to see if lithium levels have been increasing. 

What he suggests about whey is also pretty intriguing. Whey is the main byproduct of turning milk into cheese, so if cheese is lower in lithium than milk is, then whey must be higher. Does this mean whey protein is super high in lithium?

Whey protein display in The Hague, flanked by boars

Eggs

The oldest paper we could find on lithium in eggs is a Nature publication from 1941 called “Spectrochemical Analysis of Eggs”, and it is half a page of exactly that and nothing else. They do mention lithium in the eggs, but unfortunately the level of detail they give is just: “Potassium and lithium were also present [in the eggs] in fair quantity.”

Anke gives his estimate as always, but this time, it’s a little different: 

Anke gives an average (we think; he doesn’t label this column anywhere) of 7.3 mg/kg in eggs. This is a lot, more than any other food category he considers. And instead of giving a range, like he does for every other food category, he gives the standard deviation, which is 6.5 mg/kg.

This is some crazy variation. Does that mean some eggs in his sample contained more than 13.8 mg/kg lithium? That’s only one standard deviation above the average, two standard deviations would be 20.3 mg/kg. A large egg is about 50 g, so at two standard deviations above average, you could be getting 1 mg per egg. 

That does seem to be what he’s suggesting. But if we assume the distribution of lithium in eggs is normal, we get negative values quickly, and an egg can’t contain a negative amount of lithium.

Because lithium concentrations can’t be negative, and because of the distributions we’ve seen in all the previous examples, we assume the distribution of lithium in eggs must be lognormal instead.

A lognormal distribution with parameters [1.7, .76] has a mean and sd of very close to 7.3 and 6.5, so this is a reasonable guess about the underlying distribution of eggs in Germany in 1991.

Examination of the lognormal distribution with these parameters suggests that the distribution of lithium in eggs (at least in Germany in 1991) looks something like this: The modal egg in this distribution contains about 3 mg/kg lithium. But about 21% of the eggs in this distribution contain more than 10 mg/kg lithium. About 4% contain more than 20 mg/kg. About 1% contain more than 30 mg/kg. About 0.4% contain more than 40 mg/kg. And two out of every thousand contain 50 mg/kg lithium or more. 

That’s a lot of lithium for just one egg. What about the lithium in a three-egg omelette? 

ACHTUNG

To answer this Omelettenproblem, we started by taking samples of three eggs from a lognormal distribution with parameters [1.7, .76]. That gives us the concentration in mg/kg for each egg in the omelette.

Again, a large egg is about 50 grams. In reality a large egg is slightly more, but we’ll use 50 g because some restaurants might use medium eggs, and because it’s a nice round number. 

So we multiply each egg’s mg/kg value by .05 (because 50 g out of 1000 g for a kilogram) to get the lithium it contains in mg, and we add the lithium from all three eggs in that sample together for the total amount in the omelette.

We did this 100,000 times, ending up with a sample of 100,000 hypothetical omelettes, and the estimated lithium dose in each. Here’s the distribution of lithium in these three-egg omelettes in mg as a histogram: 

And here it is as a scatterplot in the style of The Economist

As you can see, most omelettes contained less than 3 mg lithium. In fact, most contained between 0.4 and 1.6 mg.

This doesn’t sound like a lot, but we think it’s pretty crazy. A small clinical dose is something like 30 mg, and it’s nuts to see that you can get easily like 1/10 that dose from a single omelette. Remember that in 1985, the EPA estimated that the daily lithium intake of a 70 kg US adult ranged from 0.650 to 3.1 mg — but by 1991 Germany, you can get that whole dose in a single sitting, from a single dish! 

Even Anke estimated that his German participants were getting no more than 3 mg a day from their food. But this model suggests that you can show up at a cafe and say “Kellner, bringen Sie mir bitte ein Omelette” and easily get that 3 mg estimate blown out of the water before lunchtime.

Even this ignores the long tail of the data. The omelettes start to peter out at around 5 mg, but the highest dose we see in this set of 100,000 hypothetical breakfasts was 11.1 mg of lithium in a single omelette.

The population of Germany in 1990 was just under 80 million people. Let’s say that only 1 out of every 100 people orders a three-egg omelette on a given day. This means that every day in early 1990s Germany, about 800,000 people were rolling the dice on an omelette. Let’s further assume that the distribution of omelettes we generated above is correct. If all these things are true, around 8 unlucky people every day in 1990s Germany were getting smacked with 1/3 a clinical dose of lithium out of nowhere. It’s hard to imagine they wouldn’t feel that. 

Processed 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. 

There are a few interesting things worth mentioning, however — all from Anke, Schäfer, & Arnhold (2003), of course.

Mostly Anke and co find that processed foods are not extreme outliers. “Ready-to-serve soups with meat and eggs were [rich] in lithium,” they say, “whereas various puddings, macaroni, and vermicelli usually contained < 1 mg lithium/kg dry matter. Bread, cake, and pastries are usually poor sources of lithium. On average, they contained less lithium than wheat flour. The addition of sugar apparently leads to a further reduction of the lithium content in bread, cake, and pastries.”

Even in tasty treats, they don’t find much. We don’t know how processed German chocolate was at the time, but they say, “the lithium content of chocolates, chocolate candies, and sweets amounted to about 0.5 mg/kg dry matter. Cocoa is somewhat richer in lithium. The addition of sugar in chocolates reduces their lithium content.”

The only thing that maybe jumps out as evidence of contamination from processing is what they say about mustard. “Owing to the small amounts used in their application,” they begin, “spices do not contribute much lithium to the diet. It is surprising that mustard is relatively lithium-rich, with 3.4 mg/kg dry matter, whereas mustard seed contains extremely little lithium.” Mustard is generally a mixture of mustard seed, water, vinegar, and not much else. We saw in the section on beverages that wine doesn’t contain much lithium, so vinegar probably doesn’t either. Maybe the lithium exposure comes from processing?

Misc

We notice that for many categories of food, we seem to have simply no information. How much lithium is in tree nuts? Peanuts? Melons? Onions? Various kinds of legumes? How much is in major crops like soy? This is part of why we need to do our own survey, to fill these gaps and run a more systematic search.

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.

Meat seems to contain a lot of lithium, but honestly not that much more than things like tomatoes and goji berries. Vegetarians will consume less lithium when they stop eating meat, but if they compensate for not eating meat by eating more fruit, they might actually be worse off. If they compensate by eating more eggs, or picking up whey protein, they’re definitely worse off! 

Vegans have it a little better — just by being vegan, they’ll be cutting out the three most reliable sources of lithium in the general diet. As long as they don’t increase their consumption of goji berries to compensate, their total exposure should go down. Hey, it makes more sense than “not eating dairy products gives you psychic powers because otherwise 90% of your brain is filled with curds and whey.”

But even so, a vegan can get as much lithium as a meat-eater if they consume tons of nightshades, so even a vegan diet is not a sure ticket to lithium removal. Not to mention that we have basically no information on plant-based protein sources (legumes, nuts) so we don’t know how much lithium vegans might get from that part of their diet.

In Conclusion

There’s certainly lithium in our food, sometimes quite a bit of lithium. It seems like most people get at least 1 mg a day from their food, and on many days, there’s a good chance you’ll get more.

That said, most of the studies we’ve looked at are pretty old, and none of them are very systematic. Sources often disagree; sample sizes are small; many common foods haven’t been tested at all. The overall quality is not great. We don’t think any of this data is good enough to draw strong conclusions from. Personally we’re avoiding whey protein and goji berries for right now, but it’s hard to get a sense of what might be a good idea beyond that. So as the next step in this project, we’re gonna do our own survey of the food supply.

The basic plan is pretty simple. We’re going to go out and collect a bunch of foods and beverages from American grocery stores. As best as we can, we will try to get a broad and representative sample of the sorts of foods most people eat on a regular basis, but we’ll also pay extra-close attention to foods that we suspect might contain a lot of lithium. Samples will be artificially digested (if necessary) and their lithium concentration will be measured by ICP-MS. All results will be shared here on the blog.

Luckily, we have already secured funding for the first round of samples, so the survey will proceed apace. If you want to offer additional support, please feel free to contact us — with more funding, we could do a bigger survey and maybe even do it faster. We could also get a greenhouse and run some hydroponic studies maybe.

If you’re interested in getting involved in other ways, here are a few things that would be really helpful:

1. If you would be willing to go out and buy an egg or whatever and mail it in to be tested, so we could get measurements from all over the country / the world, please fill out this form.

2. If you work at the FDA or a major food testing lab or Hood Milk or something, or if you’re a grad student with access to the equipment to test your breakfast for lithium and an inclination to pitch in, contact phil@whylome.org to discuss how you might be able to contribute to this project.

Potato Diet Community Trial: Sign up Now, lol

In French, the word for potato is pomme de terre. This literally translates to apple of the earth. By this logic, potatoes are the lowest-hanging fruit of all.

More seriously: We keep getting more and more interested in the all-potato diet. This is a diet where you eat nothing but potatoes (and sometimes a bit of seasoning) for a few weeks to a few months. It sounds like a dumb gimmick that could never work, but there are a surprising number of people out there saying that they tried it, it worked for them, and they kept the weight off for months or even years after.

Anecdotes are limited in all sorts of ways, but there are a surprising number of very strong anecdotes about the all-potato diet causing huge amounts of easy, sustainable weight loss:

Again, anecdotes by themselves are limited. We don’t know how many people tried this diet and didn’t get such stunning weight loss. We don’t know how long the weight stays off for. And the sample size is really small. Someone should really do a study or something, and figure this thing out.

Well, ok, if you insist. But you all have to help! 

Tl;dr, we’re looking for people to volunteer to eat nothing but potatoes (and a small amount of oil & seasoning) for at least four weeks, and to share their data so we can do an analysis. You can sign up below.

Aren’t there already diets that work? Well, maybe, but we certainly don’t have any that work reliably. Reviews of meta-analyses say things like, “Numerous randomized trials comparing diets differing in macronutrient compositions (eg, low-carbohydrate, low-fat, Mediterranean) have demonstrated differences in weight loss and metabolic risk factors that are small (ie, a mean difference of <1 kg) and inconsistent.” And The Lancet says, “unlike other major causes of preventable death and disability, such as tobacco use, injuries, and infectious diseases, there are no exemplar populations in which the obesity epidemic has been reversed by public health measures.” We could go on like this all day — actually wait, we already did

There are all sorts of crazy fad diets out there that haven’t been formally tested, and many of them have anecdotes that sound at least this good. Some of you may have even tried one. So why are we so interested in this over all the others?

Most diets are unpleasant and require you to use a lot of willpower to eat the right stuff or avoid the wrong stuff. On most diets, people are hungry all the time and feel terrible and gain the weight back as soon as they stop dieting. But the potato diet, at least according to the anecdotes, isn’t unpleasant at all — it’s quite easy. This isn’t a willpower diet. If the diet works, and it’s as easy to stick to as they say, that would be an important finding.

Most diets are hard to follow in that the instructions are precise and/or complicated — you have to eat exactly the right ratio of stuff to other stuff, carefully weigh and measure all your portions, count calories, do a lot of math in your head, check all the ingredients in everything you buy, etc. In contrast, the all-potato diet is really simple. No complex principles. No weighing and measuring your food. No checking ingredients. Just potato.

Some diets claim they won’t work unless you do everything just right. If you don’t lose weight on one of these diets, fans of the diet can always fall back on saying, maybe you did it wrong. In comparison, potato diet is easy. We don’t think it really matters if you accidentally eat a chocolate bar, as long as you are eating mostly potatoes. If you eat mostly potatoes and you don’t lose weight, then the diet doesn’t work, no one will be saying “you did it wrong.”

The potato diet also appears to have a huge effect size — 20 lbs for Chris Voigt, 114 lbs for Andrew Taylor, etc. — which should make it easy to study. We’re not fiddling around with a diet that might make you lose 5 lbs. If most people lose as much weight as Chris and Andrew, that will be really obvious. And if it doesn’t work for most people, well, that’s an important finding too.

Finally, one of the most interesting things about the potato diet is that people seem to keep the weight off afterwards, which is basically unheard of for diets. If we can confirm that in a study, it will be a pretty big deal. 

So that’s why we want to study the potato diet in particular. It should be easy to get a straight answer about this diet. If it works, people will be able to use this diet to lose weight and gain energy, if that’s what they want. And if it works, it probably provides some kind of hint about why the obesity epidemic is happening in the first place. So let’s do a study.

Diet Design

To figure out how to run this study, we needed to figure out what kind of all-potato diet seems to work for weight loss. To do this, we took a close look at the case studies we mentioned above. Some of these accounts are pretty detailed, so we won’t bore you with it up front. If you want more detail, we give an overview of each case study in the appendices.

The overall picture looks pretty clear. The basis of the all-potato diet is, unsurprisingly, eating almost nothing but potatoes.

In the most extreme cases, like Penn Jillette and the Krocks, people appear to eat literally nothing but potatoes, with no seasonings, and drink nothing but water. This seems to work pretty well but sounds like it would be hard to stick to. It’s notable that both of these examples kept it up for only two weeks, though they did lose impressive amounts of weight.

In comparison, Andrew Taylor was able to stick to an all-potato diet for a full year. He let himself use spices and seasonings, drank things other than water, and he still lost more than 100 pounds. He just made sure to take a B12 vitamin and kept away from oil and dairy.

Chris Voigt lost the least weight, but he seems to have had a pretty easy time of it. He was able to lose 21 lbs while using all kinds of salt and seasonings and cooking his potatoes in oil, and he wasn’t even trying to lose weight at all. This suggests, to us at least, that stricter versions of the diet aren’t necessary to see the benefits.

Potatoes are indeed very nutritious (here’s the USDA page for russet potatoes). The official word is that they don’t contain any vitamin A and don’t contain any B12. We’re not sure about the vitamin A — Andrew Taylor went a year without supplementing vitamin A (he did take B12), but maybe he got all the vitamin A he needed from the sauces he used? In any case, a vitamin B12 supplement is appropriate, and a vitamin A supplement seems like a good idea. [EDIT: u/alraban on reddit points out that Andrew ate sweet potatoes, which are high in Vitamin A. This is a good point, so now our recommendation is that you should either include sweet potatoes or take a Vitamin A supplement.] If you take a normal multivitamin you should be totally covered — but again, none of the case studies seem to have needed it.

Based on these examples taken together, our version of the diet is: 

THE POTATO DIET

  • Drink mostly water. You can also have some other beverages. Chris Voigt had coffee, tea, and diet soda. Andrew Taylor sometimes had beer, even. Just don’t take them with cream or sugar and try not to get too many of your daily calories from your drinks. 
  • Eat potatoes. Buy organic if you can, and eat the peels whenever possible. Start with whole potatoes and cook them yourself when you can, but in a pinch you can eat potato chips or fries if you need to. You can calculate how many potatoes to eat (a potato is about 100 calories, so if you need 2000 kcal/day, eat about 20), but we think it’s better to eat the potatoes ad libitum — make a lot of potatoes and just eat as much as you want.
  • Perfect adherence isn’t necessary. If you can’t get potatoes, eat something else rather than go hungry, and pick up the potatoes again when you can. 
  • Seasonings are ok. Chris used seasonings like Tabasco sauce, chives fresh out of his garden, a Thai herb/pepper paste, and bouillon cubes in water for fake gravy. Andrew used seasonings like dried herbs, fat-free sweet chili, barbecue sauce, and soy milk (in mashed potatoes). Do what you can to keep yourself from getting bored.
  • Oil is ok. Chris used it, Andrew and Penn didn’t. You can go either way. In fact, it would be great for us if some of you use oil and others of you don’t, so we can see if there is any difference. If you do use oil, probably use olive oil, which seems to be what Chris used. Maybe consider imported olive oil from Europe, which we suspect contains fewer contaminants, in case the contamination theory is correct.
  • Take a daily B12 supplement, since potatoes don’t contain any. We like this version but use whatever you like. Take vitamin A if you’re not eating sweet potatoes. A multivitamin would also be fine as long as it contains B12. 
  • Everyone seems to agree: No dairy. Maybe this doesn’t matter, but on the off chance this is really important for some reason, please avoid all dairy products. 

If in doubt, pick one of the examples we describe in the appendices and follow their example. You can always ask yourself, what would Chris Voigt do? And then do that.

In the spirit of self-experimentation, and because we were curious, one of us decided to try the all-potato diet for ourselves. That author is currently on day 11 of the all-potato diet. In that author’s own words: 

I was originally going to do just one or two days of the potato diet to see what it was like, but it was so easy that I figured I should try to keep to it for a full week. But it was still easy at a week, and now I’m just curious how long I can keep going for.

I feel fine, totally normal. I don’t feel more energetic than normal, but I’m pretty energetic to begin with. My mood is a little better, and I’m maybe sleeping better. Exercise seems easier, or at least it’s not any harder, kind of surprising when all my protein comes from potatoes. I haven’t lost any weight but I’m not overweight so I didn’t have much to lose in the first place.

It doesn’t require any willpower. I don’t crave anything else, I’m not tempted to buy other food at the grocery store, I’m not jealous when people around me are eating pizza or chocolate. I’m happy to sit down to a pile of potatoes every meal. They still smell delicious. If anything, I like potatoes even more now. The hardest part is the logistics of preparing that many potatoes every single day. 

I’m using European olive oil, salt, spices, vinegar, and a couple of hot sauces to keep the potatoes interesting. I want to say that it would be much harder without them, but honestly, this is so much easier than I expected, I don’t know what to expect anymore. Maybe it would be just as easy without oil and hot sauce.

Here’s my advice based on my personal experience. You should get a wide variety of potatoes. When you’re eating nothing but potatoes, the differences between different varieties become very obvious. At first I was happy with yukon gold but after a few days I began to crave russet potatoes. Make a lot every time you cook, you will eat more than you expect. And make sure to drink lots of water, I keep finding it hard to remember and end up feeling dehydrated.

UPDATE DAY 13: For the last two days I tried nothing but baked potatoes with no oil and barely any spices. It was really easy, I feel super energetic, and I started losing weight. So if the diet isn’t having any effect for you, consider trying it with no oil.

Study Design

That’s the diet we’re thinking of. What about the study design? 

Official-sounding diet studies from like the NIH and stuff don’t always run all their subjects at the same time, so we won’t bother doing that either. We’ve made it so you can sign up and participate in this study at any time. Rolling admissions.

There’s no need for a control group because the spontaneous remission rate for obesity is so low. For example, if someone said they had invented a medicine that could re-grow lost limbs, we wouldn’t need a control group for that trial, because the spontaneous limb regrowth rate is almost exactly zero (in humans anyways). If anyone regrew their arms or legs, that would be pretty convincing evidence that the medicine works as promised. Similarly, people almost never spontaneously drop 20 pounds, so we don’t need a control group.

This is also a trap. We expect that some people will come back with “but there wasn’t a control group!” This is a sign that they didn’t actually read what we’ve written and are boneheads who don’t understand how research works.

We’re not worried about tight experimental control. Maybe this diet would work better in the lab, but what we are actually interested in is how it works when implemented by normal people in the comfort of their home. If it doesn’t work in those circumstances, we want to know that! If the potato diet can’t be used practically, we don’t really care if it works in the lab, we know which side our potato is buttered sprinkled with garlic salt on. If it doesn’t work with this design, it just doesn’t work. And if it does work at home, it would presumably work even better in the lab. 

We’re also interested in the huge effect size described in the anecdotes above. We’re not worried about tiny amounts of noise from things like what you’re wearing or what time of day you weigh yourself. If the experience of Chris Voigt is at all typical — if the average person loses about 20 lbs — these tiny differences won’t matter.

And we’re not all that worried about adherence. If the 100% potato diet works, the 90% potato diet probably works too. So while we prefer that anyone sending us their data tries to refrain from eating any delicious pickles during the diet, if you do eat a pickle, it probably doesn’t matter.

Sign up to Eat Potatoes for the Glory of Science

This looks pretty promising, so let’s try to go past the anecdotes and do this in something like a rigorous fashion. Who wants to eat some ‘taters? 

The only prerequisite for signing up is being willing to eat nothing but potatoes for at least four weeks, and being willing to share your weight data with us.

(And being an adult, having a scale, not being allergic to potatoes, etc. etc.)

One reason to sign up is that you hope this will help you lose weight, lower your blood pressure, make you less depressed, or see one of the other effects reported by people like Chris Voigt and Andrew Taylor. But another reason you might want to sign up is to help advance the state of nutritional science. In a small way, this study will tell us something about nutrition, weight loss, and obesity that we don’t currently know. If the diet works, it will give us a practical intervention that people can use to reduce their weight, which we don’t really have right now.

And beyond that, running a study like this through volunteers on the internet is a small step towards making science faster, smarter, and more democratic. Imagine a future where every time we’re like, “why is no one doing this?”, every time we’re like, “dietary scientists, what the hell?”, we get together and WE do it, and we get an answer. And if we get a half-answer, we iterate on the design and get closer and closer every time. 

That seems like a future worth dreaming of. If you sign up, you get us closer to that future. We hope that this is only the first of what will be a century full of community-run scientific trials on the internet. Maybe by 2030, the redditors will have found a way to triple your lifespan. But for the first study, let’s start with potato.

We understand that eating nothing but potatoes for four weeks sounds pretty daunting. But based on the case studies above, and our own experience, we want to reassure you that it will probably be much easier than you expect. In fact, here’s our suggestion: If you are at all interested in trying it, go ahead and sign up and start collecting your data. Try the first day or two and see how it feels.

If it’s really hard for you to stay on the diet and you just can’t continue, go ahead and stop, just send us an email and close out the diet as normal (see instructions below). We’re interested in the diet as a whole, and if 40% of people can’t stick to the diet for more than two days, that’s important information about how effective the diet is in a practical sense. We’d be happy to have that information. 

But based on our own experience, we suspect that most of you who try it for a couple days will be like, “wow this is so easy! I could do this for a couple weeks no problem.” If that’s how you feel, keep collecting your data and see if you can keep it up for four weeks. 

If you want to go for longer than four weeks, that’s great, we would be happy to have more data.

If at any point you get sick or begin having side-effects, stop the diet immediately. We can still use your data up to that point, and we don’t want anything to happen to you.

If you are taking potassium supplements, often given as blood pressure medications (like Losartan) please take this extra seriously. A diet of 20 potatoes a day will give you about 300% your recommended potassium. While this should be safe by itself, it might be a problem if you are already taking a potassium supplement. Don’t sign up if you have bad kidneys, kidney disease, or diabetes (you can check with your doctor). Be aware of the signs of hyperkalemia.

We are mostly interested in weight loss effects for people who are overweight (BMI 25+) or obese (BMI 30+), but the energy and mental health effects reported in some of the case studies are interesting too. If you are “normal weight” (BMI 20-25) you can also sign up, especially if you want to feel more energetic or you want to tackle depression and anxiety or something. 

And for everyone, please consult with your doctor before trying this or any other weight loss regimen. We are not doctors. We are 20 rats in a trenchcoat. eee! eee! eee!

Anyways, to sign up: 

  1. Fill out this google form, where you give us your basic demographics and contact info. You will assign yourself a subject number, which will keep your data anonymous in the future. [UPDATE: Signups are now closed, but we plan to do more potato diet studies in the future. If you’re interested in participating in a future potato diet study, you can give us your email at this link and we’ll let you know when we run the next study.]
  2. We will clone a version of this google sheet and share the clone with you. This will be your personal spreadsheet for recording your data over the course of the diet.
  3. On the first day, weigh yourself in the morning. If you’re a “morning pooper”, measure yourself “after your first void”; if not, don’t worry about it. We don’t care if you wear pajamas or what, just keep it consistent. Note down your weight and the other measures (mood, energy, etc.) on the google sheet. Then spend day 1 eating nothing but potatoes. On day 2, weigh yourself in the morning, note down data in the sheet, then spend day 2 eating nothing but potatoes. On day 3, etc.
  4. We prefer that you stick closely to the diet for at least four weeks. But if you do break the diet at some point, just note that down in the appropriate column and try to stick to the diet the next day. Again, we’re interested in how the diet works for normal people at home, and so imperfect adherence is ok. If you totally can’t stand the diet, just stop doing it and end the study per the next instructions.
  5. Whenever you are done with the diet (preferably four weeks, or longer if you want, we’re happy to have more data if you are enjoying the diet), weigh yourself and fill out one last morning’s data so we have an endpoint, then stop the diet.
  6. Then, send us an email with the subject line “[SUBJECT ID] Potato Diet Complete”. This will let us know to go grab your data. This is also your opportunity to tell us all about how the diet went for you. Please tell us all the data that doesn’t easily fit into the spreadsheet — how you felt on the diet, what brand of oil you used, what kind of potatoes you bought, where you got them from, what kind of cookware you used, before and after pictures (if you want), advice to other people trying the diet, etc. We think there’s a pretty good chance that this diet will work for some people and not for others, and if that happens, we will dig into these accounts to see if we can figure out why (e.g. maybe this works with olive oil but not with vegetable oil, or something).
  7. If we have our act together, we will send each of you a brief google form following up at 6 months and at 1 year, and maybe at future intervals (5 years?).

Assuming we get 20 or so people, we will write up our results and publish them on the blog. We would really like to get a couple hundred people, though, since at that point it becomes possible to do more complex statistical analyses. So if you think this is an interesting idea, please tell your friends. 

We’ll keep this updated with roughly how many people have signed up and stuff, until we get bored or decide the study is closed:

Signed Up: 220 [CLOSED]

Past the 4-Week Mark: 46

We’re pretty happy with this study design. In particular, we don’t think it’s a weakness that people are doing this at home, since those are the conditions that we actually want to understand the diet under. We want to know how it works when it’s applied like it would actually be applied.

That said, if you are a wealthy donor and you want to fund a more controlled version of this — maybe, send 30 overweight and obese volunteers to a campground in Colorado for a couple weeks and feed them nothing but potatoes while they’re there, and hire a nurse or two to check up on them every day — please contact us. It’d be cheap as far as nutrition research goes, and we’ll make you a mixtape of potato songs.

Appendix A: Super Basic Potato Preparation

Use whatever recipes you want, but here are two very simple ways to prepare them.

Here’s how to roast any kind of potato:

  1. Preheat oven to 425 F.
  2. Spread a thin layer of olive oil on a large cookie sheet.
  3. Wash potatoes and make sure they do not have any dirt or anything gross on them.
  4. Cut off any gross spots on the outside of the potatoes.
  5. Cut the potatoes into any of the following: large fries, slices about a quarter inch thick, or chunks a little bigger than a grape. Do the whole batch with the same method.
  6. If you find any other bad spots while you’re cutting up the potatoes, cut them off and throw them away.
  7. Put the cut potatoes in a large bowl and dress them with olive oil, salt, and whatever seasonings you want (salt, pepper, garlic powder, rosemary, etc.). Mix them so the oil and seasoning is all over the potatoes.
  8. Put the potatoes on the cookie sheet and make sure they are all well seasoned / well oiled.
  9. Put them in the oven for 20 minutes, then take them out and stir them with a wooden spoon or spatula. They will probably stick to the cookie sheet a bit, this is normal.
  10. Put them back in for another 20 minutes and then take them out again. Let one cool and try it, making sure not to burn your mouth. If it seems done and edible, turn off the oven, your potatoes are done. If it still seems a little raw, put them back in for another 10 minutes.
  11. When done, eat with your favorite no-calorie sauces and vinegars.

Here’s how to boil any kind of potato:

  1. Fill a pot with enough water to cover however many potatoes you’re making. Salt the water and set it on the stove on high to boil.
  2. Wash potatoes and make sure they do not have any dirt or anything gross on them.
  3. Cut off any gross spots on the outside of the potatoes.
  4. Cut the potatoes into small chunks. Any size is fine, but smaller chunks will cook faster.
  5. If you find any other bad spots while you’re cutting up the potatoes, cut them off and throw them away.
  6. When the water boils, put the potatoes in and turn the heat to medium.
  7. Every five minutes, pull out a potato chunk, let it cool, and taste it to see if it’s ready. 
  8. When they are done, turn off the heat and pour the potatoes out into a colander. 
  9. Dress the potatoes with spices and olive oil (you probably want to add salt) and eat with your favorite no-calorie sauces and vinegars.

Appendix B: Chris Voigt

The earliest example of an all-potato diet we’re aware of is a guy named Chris Voigt

Chris was the Executive Director of the Washington State Potatoes Commission, and he was tired of hearing all the myths about potatoes being unhealthy. He wanted to remind people about the amazing nutrients contained in this everyday vegetable. So as a demonstration of the power of potato, he decided to eat nothing but 20 potatoes a day, for 60 days straight:

Chris started his diet on October 1, 2010, and didn’t use any milk, butter or cheese toppings for mashing his potatoes. The only way he had them were fried, boiled, mashed, steamed, chipped or baked. His diet continued for 60 straight days and ended on November 29, 2010.

Also here’s an incredibly corny video if you prefer that format.

Chris wasn’t trying to lose weight. In an interview conducted years later, he said, “I was kind of hoping to be alive at the end of the 60 days… I wasn’t trying to lose weight.” He was 197 pounds at the start of his diet and he describes himself as “six foot one and a half”, so his starting BMI was about 26, just slightly overweight. He seems to have been eating a pretty healthy diet beforehand and he wasn’t seriously overweight, which is why he didn’t think he would lose weight. In fact, he based his daily potato consumption off of a calculation of how much he would need to eat to maintain his starting weight. In response to an early comment on his blog, he said, “I’m eating 20 potatoes a day because that’s how many I’ll have to eat to maintain my current weight.”

But despite his best efforts, by the end of the 60 days, he weighed 176 lbs, a loss of 21 lbs to a BMI of 23.2. His cholesterol also went from 214 to 147, and his glucose went from 104 to 94. In fact, seems like almost everything that could be measured improved: “My cholesterol went down 67 points, my blood sugar came down and all the other blood chemistry — the iron, the calcium, the protein — all of those either stayed the same or got better.” (Here’s a page where someone has compiled a bunch of these numbers.)

Chris did all this in consultation with his doctor, and he does suggest that you have to have a baseline level of health for this to be safe: 

Chris Voigt didn’t go on 20 potatoes and a diet blindly. He first carried out thorough consultations with his dietician and doctor to be sure that he could actually live on potatoes for 60 days straight. After all, you need hale and hearty kidneys for processing the excessive potassium provided by 20 potatoes every day. In addition, you should have also stored ample amounts of necessary nutrients that are lacking in potatoes, for instance vitamin A, for avoiding any harmful side effects.

Those were his results. What was the diet like? 

In the abstract, Chris describes his diet like this

Literally, I just ate potatoes and nothing else. There were a few seasonings, but no gravy, no butter, no sour cream, and just a little bit of oil for cooking. That was it.

That isn’t quite enough detail for our purposes. But older archives of Chris’s site have the blog, which gets a lot more specific. Read it for yourself for the full story, but here are some highlights, focusing on what kinds of potatoes he ate and how he prepared them:

Day 1 – So I had 5 baked red potatoes for breakfast, mashed potatoes with a little garlic seasoning for lunch, and while my family had all the fixing at the steakhouse celebrating my wife’s birthday, I had garlic mashed potatoes and an order of steak fries. The all potato diet wasn’t too bad today, but I did cringe a little when everyone had ice cream for dessert.

Day 2 –  I’m really struggling to eat enough calories. I had two baked potatoes this morning with a couple shots of Tabasco sauce, a serving of mashed potatoes sprinkled with a few BBQ potato chips for a change in texture, and another serving of mashed potatoes and 5 roasted small red potatoes. I didn’t hit the 2200 calories I was hoping for today. I didn’t realize how filling the potatoes would make me feel.

Day 4 – My wife made me 3 pounds of roasted red potatoes that were lightly coated in olive oil with some of her special seasonings. While I made two containers of russet mashed potatoes, one with chives fresh out of our garden and one with a Thai herb/pepper paste I’ve never had before. My wife tells me the paste goes a long way and be careful not to use too much.

Day 6 – I was in potato Nirvana tonight. My wife boiled a bouillon cube with potato starch to make me “psuedo gravy”. It was awesome! She smothered Yukon Gold and Purple potato slices in this gravy and baked it in the oven for an hour. Then cooked homemade yellow and purple chips with artifical sweetner and cinnamon for dessert. It was heaven for a flavor deprived husband. I would marry her all over again because of this!

Day 11 – So one thing people keep asking about is, “What about my weight?” I’ve been hesitant to talk about this because I don’t want people to think of this as a weight loss diet. It is not, and it’s not something I want people to replicate. … So let me step down from my nutrition soap box and talk about weight. I started this diet at 197 pounds. I’m six foot one and a half so according to my BMI, I was a little over weight. I should be in the 175-185 range. Right now, I’m at 189 pounds. Most of that weigh loss happened early, only because I was struggling to eat enough potatoes. I seemed full the whole time so it was hard to keep eating. But now, my weight loss has become more stable.

Day 15 – I feel good. Lot’s of energy, I’m dropping a few pounds which I needed to, and no weird side effects. And mentally, I think I’ve found my groove. Weekdays are pretty easy but weekends are a little tougher, still have desires for other foods but I think those a waning a bit as I get further into this diet.

Day 19 – So my family had potstickers last night while I had roasted red potatoes. For the potstickers, my wife made a dipping sauce that I tried on my red potato wedges. It was pretty good. The sauce was soy sauce, ginger, and some off the shelf dry asian seasoning. It was a nice change of pace. It added a flavor I haven’t had in a long time.

Day 22 – I had about a pound of hash browns this morning for breakfast, two pounds of mashed potatoes with black pepper for lunch, which means I have to eat close to 4 more pounds before bed. I’m leaning towards baked potatoes with balsamic vinegar for dinner but I’m not sure I’m ready for 4 pounds of it.

Day 24 – So here is a new one for you that my wife made up. Fake ice cream made from potatoes. She took 1/2 cup cocoa powder, 1/2 cup artificial sweetner, and a little water to make a chocolate sauce. Then mixed it with about 2 cups of “riced” potatoes and ice. Blended it and put in freezer. It was actually really good, ju…st a strange texture though. I love my wife! What a treat!

Day 26 – I brought my food for the day and stuffed it in the office fridge. Two pounds of purple mashed potatoes topped with garlic salt, 6 smalled baked red potatoes that I’ll probably put balsamic vinegar on, and about 10 oz of gnocchi made with riced potatoes and potato flour, then lightly fried. Can’t boil them because they fall apart since they don’t have the egg in them that you would normally use.

…  I drove to Spokane Sunday night and caught an early flight to Boise the next day. Must remember to prepare better! Nearly starved! I broke into a small emergency stash of instant potatoes I had with me for breakfast, had 3 small bags of …chips and 1 baked potato for lunch, and an order of fries at McD’s for dinner.

Day 28 – So here is what I had yesterday to eat. About 2 pounds of roasted red potatoes lightly seasoned and with a little olive oil, 3 pounds of purple mashed potatoes sprinkled with garlic salt, and about a pound and a half of “riced” potatoes that were fried up lightly. It was kind of like light fluffy hash browns. And a few handfuls of potato chips for a change in texture.

… think about how weird and unusual this diet is. Health professionals actually suggested I include some fries and chips prepared in healthy oils as part of my diet to make me more healthy during this diet. Doesn’t that sound so weird out loud or written in this blog? You have to remember that there is absolutely no fat in a potato, no fat in any of the seasonings or herbs I’m eating. But there are 2 fatty acids that are essential to bodily functions and are needed by your body. The healthy oils from the fries and chips are supplying me those fatty acids. Without them, I would not look or feel very good at the end of these 60 days. The take home message, you need those fatty acids to live but the reality for most people is that we eat too many of them. Live in moderation!

Day 33 – Got out of the house this morning without any seasonings for my spuds. So far, I’ve eaten 6 boiled, yellow flesh, plain potatoes. You know…I really think this is getting easier. I’m not having the intense cravings for other foods that I use to have. Maybe I’ve found my groove.

…  I thought I’d take a moment to answer a couple questions I always get from folks about the diet. One is, “Are you taking any supplements?” No. This diet is about nutrition, there are so many nutrients in potatoes that you could literally live off them for an extended period of time without any major impacts to your health. If I could take supplements, I think you could probably do this diet for a really long time! Also, I get asked about beverages. I drink mostly water, but can have things that don’t add calories or any major nutrients. I do drink some black coffee, plain black tea, or an occasional diet soda.

Day 45 – I just ate about a kilo of purple mashed potatoes for dinner tonight. But I think I added too much garlic salt. Probably shouldn’t do any major kissing tonight. 🙂

Day 50 – Just in case I’m subjected to a lie detector test at some point, I have to come clean on 3 incidents. There were 3 separate times in the previous 50 days where I was making my kids lunch, peanut butter and jelly sandwiches, and without thinking, it was more of a reflex move, I licked clean the peanut or jelly that had gotten on my fingers. Its been bugging me so I needed to share.

Day 60 – So here are most of the stats from my latest medical exam and how it compares to where I was prior to the start of the diet. Weight, started at 197, finished at 176. Cholesterol, started at borderline high of 214, finished at 147. Glucose, started at 104, dropped to 94. So improvements in each of those catagories. I don’t have a hard copy yet, will try to get that tomorrow and will post online. Me Happy!!

Day 61 – (Diet officially over) Its funny because I still have yet to eat something else besides potatoes. I’ve been a little busy this morning so I wasn’t able to pack a lunch or breakfast. But the fridge in our office still had a couple of my potato only dishes. So guess what I had for my first meal at the end of the diet. Potatoes! Hopefully that will change later today. And I bet there will still be potatoes tonight, but with something on them or with them!

… One more thing, a few new folks have joined our little community and have sent me questions about the diet. First, I took no other supplements. It literally was just potatoes, seasonings, and oil for cooking. Now there were a few things we did classify as seasonings since they didn’t really add any significant nutrients, such as Tabasco Sauce which is really just dried peppers and vinegar. Had balsalmic vinegar a few times, and an occasional bouillon cube that was used in mashed potatoes or mixed with potato starch to form something like gravy. THe cubes were 5 calories and really only added sodium to the diet, which we consider a seasoning. 

Day 63 – A big thank you to the Washington Beef, Dairy, and Apple producers. They, along with the Washington Potato Commission, hosted a dinner at the Moses Lake Head Start facility for all the kids and their parents. We did crafts and a short nutrition workshop on the importance of eating healthy, well balanced meals. Not just 20 potatoes a day 🙂 And a big thank you to the staff for all of their work on this and the wonderful Mr. Potato Head they gave me. We had lean beef strips for our tortillas, along with roasted onions, peppers, and potatoes, and apple slices and low fat milk. I sampled everything and wanted to chow down but my doctor has advised me to ease back slowly into other foods. So I’m still eating a lot of potatoes!

On the one hand, Chris took the potato diet very seriously. He really did get almost all his calories from potatoes for about 60 days. He stuck to the plan.

On the other hand, he didn’t take it too seriously. He used cooking oil, spices, and a bunch of different seasonings. He still had coffee, tea, and the “occasional diet soda”. But this didn’t ruin the diet — he still lost weight and gained energy.

The results do seem astounding. More energy, better sleep, lower cholesterol, etc. etc. And how was it subjectively? “I’m really struggling to eat enough calories. … I didn’t realize how filling the potatoes would make me feel. … I feel good.” 

The weight loss results aren’t that extreme, but Chris wasn’t very overweight to begin with. He went from a BMI of 26 to an “ideal” BMI of 23. He didn’t really have many more excess pounds to lose. So let’s take a look at a more extreme example. 

Appendix C: Andrew Taylor

Andrew Taylor is an Australian man who did an all-potato diet for a full year. He started at 334 pounds and he lost 117 pounds over the course of what he called his “Spud Fit Challenge.”

Here’s a video of Andrew before the diet, describing what he is about to attempt. Here’s a video of him 11 months in. And here are some descriptions of how it went

The physical benefits of Taylor’s Spud Fit Challenge remain, he says. “I’ve maintained the weight loss and I’m still free of the daily grind of battling with food addiction. I had a check up a few weeks ago and my doctor was very happy with the state of my health.”

Taylor says that he was clinically depressed and anxious before undertaking his all-potato diet, “which is no longer an issue for me,” he says. “My mental health is much better these days.”

During his challenge, Taylor ate all kinds of potatoes, including sweet potatoes. To add flavor to his meals, he used a sprinkle of dried herbs or fat-free sweet chili or barbecue sauce. If he made mashed potatoes, he only added oil-free soy milk.

He drank mostly water, with the occasional beer thrown in (proof that no man can resist a great brew). Because his diet completely lacked meat, he supplemented with a B12 vitamin.

He also didn’t restrict the amount he consumed. Instead, Taylor ate as many potatoes as he needed to satisfy his hunger. For the first month, he didn’t work out at all and still dropped 22 pounds, but then he added 90 minutes of exercise to his routine every day.

 “I feel amazing and incredible! I’m sleeping better, I no longer have joint pain from old football injuries, I’m full of energy, I have better mental clarity and focus,” he writes on his site.

Like Chris Voigt, Andrew made sure to get regular checkups

Taylor said has had medical supervision, including regular blood tests, throughout the year. His cholesterol has improved and his blood-sugar levels, blood pressure and other health indicators are good, he explained. He feels “totally amazing,” noting he no longer has problems with clinical depression and anxiety, sleeps better, feels more energetic and is physically stronger.

Andrew is now running spudfit.com. For the specifics of Andrew’s diet, the FAQ is pretty detailed: 

A combination of all kinds of potatoes, including sweet potatoes. I used minimal dried and fresh herbs, spices and fat-free sauces (such as sweet chilli, tomato sauce or barbecue sauce) for a bit of flavour. I also use some soy milk (no added oil) when I make mashed potatoes.

I drank only water and the occasional beer. I didn’t drink any tea or coffee but I’ve never liked them anyway. If you want to drink tea or coffee I think that would be fine as long as you use a low fat (no added oil) plant based milk.

For the first month I did no exercise and still lost 10kgs. After that I tried to do around 90 minutes of training every day. I DID NOT exercise for weight loss, I did it because for the first time in years I had excess energy to burn, enjoyed it and it made me feel good. I think that whatever the amount of exercise I did, my body adjusted my hunger levels to make sure I take in enough food. If I didn’t let myself go hungry then I was fine.

Rule 1: Do your own research and make educated decisions – don’t just do things because you saw some weird bloke on the internet doing it! Also get medical supervision to make sure everything is going well for you, especially if you are taking any medications.

Rule 2: Eat a combination of all kinds of potatoes, including sweet potatoes. I have minimal herbs, spices and fat-free sauces for a bit of flavour. I also use some soy (or other plant-based with no added oil) milk when I make mashed potatoes. Also take a B12 supplement if you plan on doing this for longer than a few months. Definitely no oil – of any kind – or anything fatty such as meats, cheeses, eggs or dairy products (even lean or low-fat versions).

Rule 3: DO NOT RESTRICT OR COUNT CALORIES. I eat as much as I like, as often as I like, I do not allow myself to go hungry if I can help it.

I used a non-stick granite pan and fry in water or salt reduced vegetable stock. When I used the oven I just put the potatoes straight on the tray. I also liked to cook potatoes in my pressure cooker and my air fryer.

I felt amazing and incredible and I still do! My sleep improved, joint pain from old football injuries went away, I gained energy and improved mental clarity and focus. Also I lost 52.3 kilograms (117 pounds) over the course of the year. By far the best part is that I no longer suffer with clinical depression and anxiety.

I tried to keep it as simple as possible. I didn’t own an air fryer or a pressure cooker or any other special gadgets. Most of what I ate was either boiled, baked or mashed potatoes. I would make a really big batch of one type and then eat it for a day or two until it was gone and then repeat.

(did you eat the skins?) I did but if you don’t want to that’s ok too.

This is the most surprising thing of all, I can’t explain why but I’m not at all bored of my potato meals.

Over the month of January, following the completion of my Spud Fit Challenge, I lost another 2kg (4lbs). This took my total weight loss to 55kg (121lbs) and meant I weighed the same as I did when I was 15 years old – 96kg (211lbs)! Since then I’ve stopped weighing myself so I can’t be sure of what I actually weigh, my new clothes still all fit though and I still feel good so I guess my weight is around the same (nearly 15 months later at the time of writing this).

This diet looks pretty similar to what Chris did. All potatoes but not wildly strict — he would have seasonings and sauces and even an occasional beer. The big difference is that Andrew studiously avoided added oils, and took a B12 supplement. 

The B12 seems like a good addition to us, especially since Andrew was doing this for a full year, because potatoes contain almost no B12. Hard to say if avoiding oil was important but using oil didn’t keep Chris Voigt from seeing a lot of benefits from potatoes. On the other hand, Andrew didn’t seem to miss it. 

Appendix D: Penn Jillette 

Penn Jillette, of the famous magician duo Penn & Teller, lost over 100 lbs, down from “probably over 340”, on a diet that started with a 2-week period of nothing but potatoes.

You can hear him describe his process in this video, but here are a few choice details: 

I didn’t mind not being energetic and stuff. But I started having blood pressure that was stupid high like, you know, like English voltage, like 220 even on blood pressure medicine.

If you take medical advice from a Las Vegas magician you are an idiot who deserves to die. You have to do this for yourself and with your proper medical professionals.

And one of the really good ways to do that that worked tremendously for me is what’s called the mono diet which is just what you think from the root, eating the exact same thing.

And I could have chosen anything. I could have chosen corn or beans or whatever. Not hot fudge but anything. And I chose potatoes because it’s a funny thing and a funny word.

For two weeks I ate potatoes, complete potatoes – skin and everything and nothing added, nothing subtracted. When I say nothing subtracted I mean no skin taken off but also no water. You can’t cut it up and make it chips in a microwave. Don’t take water out of it. 

Leave the potato completely – so that means baked or boiled and not at any mealtime. You don’t get up in the morning, eat a potato. You don’t eat it at lunch or dinner. Mealtimes are obliterated. When you really need to eat, eat a potato. And over that first two weeks I lost I believe 14 pounds. So already I’m a different person.

Then after that two weeks I went to, you know, bean stew and tomatoes and salads. But still no fruit and no nuts. Certainly no animal products. And I lost an average – these words are careful – an average of 0.9 pounds a day.  So I took off pretty much all the weight in three or four months, in a season, in a winter.

And that was 17 months ago. So I’ve kept the weight off for 17 months. Now two years is magic. Very few people keep it off for two years. I’ve got seven more months to go. I think I have a shot at it.

I feel better. I’m happier. I’m off most of my blood pressure meds. Not all of them, it takes a while for the vascular system to catch up with the weight loss. I have more fun. I believe I’m kinder.

All of that having been said now that I’m at target weight I also – this is important – I also didn’t exercise while I was losing the weight. Exercising is body building. It’s a different thing. Wait until you hit the target weight, then you exercise. Then it’s easy. Then it really does good. But while you’re losing weight make it winter. Sleep a little more. Get sluggish. Let your body just eat the fat that you’ve stored up just the way you should. Hibernate a little bit. Let it eat the fat. Be a little bit like a bear.

Again, a pretty impressive story. And, as of 2019, he seems to be keeping it off.  

Appendix E: Brian & Jessica Krock

Penn’s example inspired a similar attempt from the Krocks, a couple who have jointly lost over 220 lbs starting with two weeks of an all-potato diet

He was 35 when we started this journey and tipped the scales at 514 pounds. My own weight was approaching 300 pounds and my health was starting to suffer. High blood pressure, anxiety and acne were just the start of my issues. 

We picked a start date on the calendar (June 22, 2018 – which also happened to be the 11th anniversary of when we first started dating) and started doing research. The first book I read was Penn Jillette’s Presto!: How I Made Over 100 Pounds Disappear and Other Magical Tales. It was exactly what I needed to get into the right frame of mind for starting this journey. It wasn’t a book from a doctor or a nutritionist or someone telling me why eating the way I did was going to kill me. It was a book from someone who KNEW the real struggle we have dealt with for years. Someone who spend years overweight, LOVED food, and didn’t buy into the whole “eat in moderation” philosophy a lot of our past failed diets relied on.

The first day of potatoes sucked. I seriously contemplated quitting during the FIRST day. After eating my first round of potatoes, I literally walked from our apartment to a grocery store to look at the extra cheesy hot-and-ready pizza I thought I needed. I gazed at the pizza and walked around the store looking for something to eat. Luckily, I was able to keep it together and walk out of the store and back home to my pantry full of potatoes.

I’m not trying to be dramatic, but it was seriously one of the hardest things I’ve done in my life. It took more will power than I thought either of us had.

Even when we started the two weeks of potatoes, we still weren’t sure what the heck we were supposed to do after that. We knew it was vegan. We knew we wouldn’t be able to use added salt, sugar, oil, etc. But that was about it. So we did a lot of research during those two weeks of eating nothing but potatoes. From what I could tell, after the two weeks of potatoes, Penn Jillette followed a whole food, plant-based diet for the most part, so we decided to stick with that.

 We will never go back to eating the way we used to eat. As hokey as it might sound: This is not a diet – it is a lifestyle. We know if we go back to our old ways, we’ll gain the weight back again. The best part is… we don’t want to go back to how we ate before! We actually enjoy food more now than we did before. We have a better relationship with food. We feel like we eat MORE variety now. Eating a whole food, plant-based diet has opened our minds and palates to a new world of food that we would not have given a second thought to before.

They seem to have had a harder time than the other examples we looked at. But we also notice they are the heaviest people we’ve looked at so far, so it’s not hard to imagine that it might have been roughest for them. But even so, it seems to have worked. 

As far as we can tell, they are following Penn’s approach over what Chris and Andrew did — no oil or nothin’, just potatoes. Our sense is that this is probably more hardcore than what is necessary but like, more power to them. On the other hand, this may be part of what made it so difficult. Even Andrew used seasonings! Detailed instructions for how they prepare Taters appear in their videos.

The Krocks are still making videos, and if you look at their channel, they seem to have kept a lot of weight off.

Appendix F: Potato Hack

We are also going to talk about potato hack. This is not a case study per se but it is another all-potato approach, and one that has lots of very positive reviews on Amazon, for whatever that’s worth.

Per the website, “The Potato Hack (aka The Potato Diet) is an extremely effective method for losing weight without experiencing hunger.”

The Potato Hack Overview has this to say about the details: 

Red and yellow potatoes work the best, because after they are boiled they keep longer than Russet potatoes, which tend to get mushy quicker. However, Russet potatoes do work. Try all potato types.

Sweet potatoes are not potatoes. They can work for some people, but not nearly as well. If you can not handle nightshades, purple yams with white flesh can be a substitute. Weight loss is likely to be slower when you don’t use regular potatoes.

The only way to make the potato fattening is to process it and cook it in oil. So avoid fries and chips. For the potato hack to work the potatoes need to be cooked only in water. Boil, steam, or pressure cook.

When cooked potatoes are cooled overnight in the refrigerator they develop something called resistant starch. Resistant starch is beneficial to our gut flora, balances blood sugar, and other additional health benefits. These resistant starches are not digested in the same manner as regular calories, so they have the effect of reducing the calories of potatoes.

Refrigerating cooked potatoes overnight will reduce the calories by about 17%. The potatoes can be reheated before eating without losing any of the resistant starch.

The potato hack will still work if you don’t refrigerate the potatoes, so although this step is encouraged, it is optional.

Eat the potatoes plain. Salt if you must. You can add a splash of malt or red wine vinegar if a blood sugar spike is a concern, although cooling the potatoes will reduce the glycemic response.

To get the full benefit of the potato hack, it is strongly advised to eat the potatoes plain. You are teaching your brain how to get full without flavor. This is the opposite approach taken in dieting where one continues to get flavorful food but in a restrictive manner.

With the potato diet, do not walk away from the table hungry. Eat until full.

This is a little more finicky (what potatoes to use, how to store them, etc.) but overall looks a lot like the other examples we’ve considered. 

The hack also links to some testimonies, including this one guy’s particular approach. We’ll include it here because it gives an unusual amount of detail about purchasing and preparation:  

If your time is valuable to purchase organic, because you will not need to peel the potatoes, plus they have more nutrition. If you want to save money, purchase non-organic. I cycle between both options.

The three most common options for potatoes are going to be red, yellow, and russet. 98% of the time I will purchase red or yellow. They hold up much better structurally when you take them in and out of the refrigerator over a day or two.

Russet potatoes get mushy quickly. The only time I get Russet is if I get a really good price and I know I’m doing a strict potato hack, so I’m not using those potatoes two days later.

I’ve boiled so many potatoes in the last two years, my hands have developed muscle memory as if I were driving a manual car. Here is how I’ve optimized my potato preparation.

1. Peel directly into colander if the potatoes are not organic.

2. Place the potato directly into the cleaned and dried storage container.

3. Fill the storage container. When I first started hacking, I would weigh the potatoes. Once I figured out my container could hold 5.5 pounds, then I put my scale away.

4. Remove each potato. If it is small, place it in a stockpot, otherwise chop it into parts. For me, a medium potato is 2 or 3 parts. A large potato will be more. My goal is to have approximately equal size potato parts. I want them to boil at the same rate.

5. Once that is complete, I rinse the potatoes in the stockpot.

6. Refill stockpot with clean water and boil.

7. While the potatoes are boiling, empty peels in a compost bin.

8. Boil until done to your liking. I tend to cook mine a little longer than Tim Steele describes in his book The Potato Hack, but whatever you like is the right answer. Experiment.

9. Drain and let potatoes cool. The reason I want the potatoes to cool is that if I don’t, the steam will collect on the roof of the storage container and drain down onto the potatoes, making them mushy more quickly. If I want the potatoes to cool fast, I will spread them on a cookie sheet and place them outside (provided outside is cooler than inside).

10 Put the cooled potatoes in the storage bin and refrigerate.

That is my optimized path. I’m sure you’ll find your own.

Peer Review: Obesity II – Establishing Causal Links Between Chemical Exposures and Obesity

A new paper, called Obesity II: Establishing Causal Links Between Chemical Exposures and Obesity, was just published in the journal Biochemical Pharmacology (available online as of 5 April 2022). Authors include some obesity bigwigs like Robert H. Lustig, and it’s really long, so we figured it might be important. 

The title isn’t some weird Walden II reference — there’s a Part I and Part III as well. Part I reviews the obesity epidemic (in case you’re not already familiar?) and argues that obesity “likely has origins in utero.”

“The obesity epidemic is Kurt Cobain’s fault” is an unexpected but refreshing hypothesis

Part III basically argues that we should move away from doing obesity research with cells isolated in test tubes (probably a good idea TBH) and move towards “model organisms such as Drosophila, C. elegans, zebrafish, and medaka.” Sounds fishy to us but whatever, you’re the doctor.

This paper, Part II, makes the case that environmental contaminants “play a vital role in” the obesity epidemic, and presents the evidence in favor of a long list of candidate contaminants. We’re going to stick with Part II today because that’s what we’re really interested in.

For some reason the editors of this journal have hidden away the peer reviews instead of publishing them alongside the paper, like any reasonable person would. After all, who could possibly evaluate a piece of research without knowing what three anonymous faculty members said about it? The editors must have just forgotten to add them. But that’s ok — WE are these people’s peers as well, so we would be happy to fill the gap. Consider this our peer review:

This is an ok paper. They cite some good references. And they do cite a lot of references (740 to be exact), which definitely took some poor grad students a long time and should probably count for something. But the only way to express how we really feel is:

Seriously, 43 authors from 33 different institutions coming together to tell you that “ubiquitous environmental chemicals called obesogens play a vital role in the obesity pandemic”? We could have told you that a year ago, on a budget of $0. 

This wasted months, maybe years of their lives, and millions of taxpayer dollars making this paper that is just like, really boring and not very good. Meanwhile we wrote the first draft of A Chemical Hunger in a month (pretty much straight through in October 2020) and the only reason you didn’t see it sooner was because we were sending drafts around to specialists to make sure there wasn’t anything major that we overlooked (there wasn’t).

We don’t want to pick on the actual authors because, frankly, we’re sure this paper must have been a nightmare to work on. Most of the authors are passengers of this trainwreck — involved, but not responsible. We blame the system they work under.

We hope this doesn’t seem like a priority dispute. We don’t claim priority for the contamination hypothesis — here are four papers from 2008, 2009, 2010, and 2014, way before our work on the subject, all arguing in favor of the idea that contaminants cause obesity. If the contamination hypothesis turns out to be right, give David B. Allison the credit, or maybe someone even earlier. We just think we did an exceptionally good job making the case for the hypothesis. Our only original contributions (so far) are arguing that the obesity epidemic is 100% (ok, >90%) caused by contaminants, and suggesting lithium as a likely candidate. 

So we’re not trying to say that these authors are a bunch of johnny-come-latelies (though they kind of are, you see the papers up there from e.g. 2008?). The authors are victims here of a vicious system that has put them in such a bad spot that, for all their gifts, they can now only produce rubbish papers, and we think they know this in their hearts. It’s no wonder grad students are so depressed! 

So to us, this paper looks like a serious condemnation of the current academic system, and of the medical research system in particular. And while we don’t want to criticize the researchers, we do want to criticize the paper for being an indecisive snoozefest.

Long Paper is Long

The best part of this paper is that comes out so strongly against “traditional wisdom” about the obesity epidemic:  

The prevailing view is that obesity results from an imbalance between energy intake and expenditure caused by overeating and insufficient exercise. We describe another environmental element that can alter the balance between energy intake and energy expenditure: obesogens. … Obesogens can determine how much food is needed to maintain homeostasis and thereby increase the susceptibility to obesity. 

In particular we like how they point out how, from the contaminant perspective, measures of how much people eat are just not that interesting. If chemicals in your carpet raise your set point, you may need to eat more just to maintain homeostasis, and you might get fat. This means that more consumption, of calories or anything else you want to measure, is consistent with contaminants causing obesity. We made the same point in Interlude A. Anyways, don’t come at us about CICO unless you’ve done your homework. 

We also think the paper’s heart is in the right place in terms of treatment: 

The focus in the obesity field has been to reduce obesity via medicines, surgery, or diets. These interventions have not been efficacious as most people fail to lose weight, and even those who successfully lose substantial amounts of weight regain it. A better approach would be to prevent obesity from occurring in the first place. … A significant advantage of the obesogen hypothesis is that obesity results from an endocrine disorder and is thus amenable to a focus on prevention. 

So for this we say: preach, brothers and sisters.

The rest of the paper is boring to read and inconclusive. If you think we’re being unfair about how boring it is, we encourage you to go try to read it yourself.

Specific Contaminants

The paper doesn’t even do a good job assessing the evidence for the contaminants it lists. For example, glyphosate. Here is their entire review:

Glyphosate is the most used herbicide globally, focusing on corn, soy and canola [649]. Glyphosate was negative in 3T3-L1 adipogenic assays [650], [651]. Interestingly, three different formulations of commercial glyphosate, in addition to glyphosate itself, inhibited adipocyte proliferation and differentiation from 3T3-L1 cells [651]. There are also no animal studies focusing on developmental exposure and weight gain in the offspring. An intriguing study exposed pregnant rats to 25mg/kg/day during days 8-14 of gestation [652]. The offspring were then bred within the lineage to generate F2 offspring and bread to generate the F3 progeny. About 40% of the males and females of the F2 and F3 had abdominal obesity and increased adipocyte size revealing transgenerational inheritance. Interestingly, the F1 offspring did not show these effects. These results need verification before glyphosate can be designated as an obesogen.

For comparison, here’s our review of glyphosate. We try to, you know, come to a conclusion. We spend more than a paragraph on it. We cite more than four sources.

We cite their [652] as well, but we like, ya know, evaluate it critically and in the context of other exposure to the same compound. We take a close look at our sources, and we tell the reader we don’t think glyphosate is a major contributor to the obesity epidemic because the evidence doesn’t look very strong to us. This is bare-bones due diligence stuff. Take a look: 

The best evidence for glyphosate causing weight gain that we could find was from a 2019 study in rats. In this study, they exposed female rats (the original generation, F0) to 25 mg/kg body weight glyphosate daily, during days 8 to 14 of gestation. There was essentially no effect of glyphosate exposure on these rats, or in their children (F1), but there was a significant increase in the rates of obesity in their grandchildren (F2) and great-grandchildren (F3). There are some multiple comparison issues, but the differences are relatively robust, and are present in both male and female descendants, so we’re inclined to think that there’s something here. 

There are a few problems with extending these results to humans, however, and we don’t just mean that the study subjects are all rats. The dose they give is pretty high, 25 mg/kg/day, in comparison to (again) farmers working directly with the stuff getting a dose closer to 0.004 mg/kg.

The timeline also doesn’t seem to line up. If we take this finding and apply it to humans at face value, glyphosate would only make you obese if your grandmother or great-grandmother was exposed during gestation. But glyphosate wasn’t brought to market until 1974 and didn’t see much use until the 1990s. There are some grandparents today who could have been exposed when they were pregnant, but obesity began rising in the 1980s. If glyphosate had been invented in the 1920s, this would be much more concerning, but it wasn’t.

Frankly, if they aren’t going to put in the work to engage with studies at this level, they shouldn’t have put them in this review. 

If this were a team of three people or something, that would be one thing. But this is 43 specialists working on this problem for what we assume was several months. We wrote our glyphosate post in maybe a week?

Some of the reviews are better than this — their review of BPA goes into more detail and cites a lot more studies. But the average review is pretty cruddy. For example, here’s the whole review for MSG:

Monosodium glutamate (MSG) is a flavor enhancer used worldwide. Multiple animal studies provided causal and mechanistic evidence that parenteral MSG intake caused increased abdominal fat, dyslipidemia, total body weight gain, hyperphagia and T2D by affecting the hypothalamic feeding center [622], [623], [624]. MSG increased glucagon-like peptide-1 (GLP-1) secretion from the pGIP/neo: STC-1 cell line indicating a possible action on the gastrointestinal (GI) tract in addition to its effects on the brain [625]. It is challenging to show similar results in humans because there is no control population due to the ubiquitous presence of MSG in foods. MSG is an obesogen.

Seems kind of extreme to unequivocally declare “MSG is an obesogen” on the basis of just four papers. On the basis of results that seem to be in mice, rats, mice, and cells in a test tube, as far as we can tell (two of the citations are review articles, which makes it hard for us to know what studies they specifically had in mind). Somehow this is enough to declare MSG a “Class I Obesogen” — Animal evidence: Strong. In vitro evidence: Strong. Regulatory action: to be banned. Really? 

Instead, we support the idea of — thinking about it for five minutes. For example, MSG occurs naturally in many foods. If MSG were a serious obesogen, tomatoes and dashi broth would both make you obese. Why are Italy and Japan not more obese? The Japanese first purified MSG and they love it so much, they have a factory tour for the stuff that is practically a theme park — “there is a 360-degree immersive movie experience, a diorama and museum of factory history, a peek inside the fermentation tanks (yum!), and finally, an opportunity to make and taste your own MSG seasoning.” Yet Japan is one of the leanest countries in the world.

As far as we can tell, Asia in general consumes way more MSG than any other part of the world. “Mainland China, Indonesia, Vietnam, Thailand, and Taiwan are the major producing countries in Asia.” Why are these countries not more obese? MSG first went on the market in 1909. Why didn’t the obesity epidemic start then? We just don’t think it adds up. 

(Also kind of weird to put this seasoning invented in Asia, and most popular in Asia, under your section on “Western diet.”)

Adapted from Fig. 3

Let’s also look at their section on DDT. This one, at least, is several paragraphs long, so we won’t quote it in full. But here’s the summary: 

A 2017 systematic review of in vitro, animal and epidemiological data on DDT exposures and obesity concluded the evidence indicated that DDT was “presumed” to be obesogenic for humans [461]. The in vitro and animal data strongly support DDT as an obesogen. Based on the number of positive prospective human studies, DDT is highly likely to be a human obesogen. Animal and human studies showed obesogenic transmission across generations. Thus, a POP banned almost 50 years ago is still playing a role in the current obesity pandemic, which indicates the need for caution with other chemical exposures that can cause multigenerational effects.

We’re open to being convinced otherwise, but again, this doesn’t really seem to add up. DDT was gradually banned across different countries and was eventually banned worldwide. Why do we not see reversals or lags in the growth of obesity in those countries those years? They mention that DDT is still used in India and Africa, sometimes in defiance of the ban. So why are obesity rates in India and Africa so low? We’d love to know what they think of this and see it contextualized more in terms of things like occupation and human exposure timeline.

Review Paper

With a long list of chemicals given only the briefest examination, it’s hard not to see this paper as overly inclusive to the point of being useless. It makes the paper feel like a cheap land grab to stake a claim to being correct in the future if any of the chemicals on the list pan out.

Maybe their goal is just to list and categorize every study that has ever been conducted that might be relevant. We can sort of understand this but — why no critical approach to the material? Which of these studies are ruined by obvious confounders? How many of them have been p-hacked to hell? Seems like the kind of thing you would want to know! 

You can’t just list papers and assume that it will get you closer to understanding. In medicine, the reference for this problem is Ioannidis’s Why Most Published Research Findings Are False. WMPRFAF was published in 2005, you don’t have an excuse for not thinking critically about your sources.

Despite this, they don’t even mention lithium, which seems like an oversight. 

Oh right, Kurt Cobain IS responsible for the obesity epidemic

We wish the paper tried to provide a useful conclusion. It would have been great to read them making their best case for pretty much anything. Contaminants are responsible for 50% of the epidemic. Contaminants are responsible for no more than 10% of the epidemic. Contaminants are responsible for more than 90% of the epidemic. We think phthalates are the biggest cause. We think DDT is the biggest cause. We think it’s air pollution and atrazine. Make a case for something. That would be cool.

What is not cool is showing up being like: Hey we have a big paper! The obesity epidemic is caused by chemicals, perhaps, in what might possibly be your food and water, or at work, though if it’s not, they aren’t. This is a huge deal if this is what caused the epidemic, possibly, unless it didn’t. The epidemic is caused by any of these several dozen compounds, unless it’s just one, or maybe none of them. What percentage of the epidemic is caused by these compounds? It’s impossible to say. But if we had to guess, somewhere between zero and one hundred percent. Unless it isn’t. 

Effect Size

The paper spends almost no time talking about effect size, which we think is 1) a weird choice and 2) the wrong approach for this question. 

We don’t just care about which contaminants make you gain weight. We care about which contaminants make you gain a concerning amount of weight. We want to know which contaminants have led to the ~40 lbs gain in average body weight since 1970, not which of them can cause 0.1 lbs of weight gain if you’re inhaling them every day at work. These differences are more than just important, they’re the question we’re actually interested in!

For comparison: coffee and airplane travel are both carcinogens, but they increase your risk of cancer by such a small degree that it’s not even worth thinking about, unless you’re a pilot with an espresso addiction. When the paper says “Chemical ABC is an obesogen”, it would be great to see some analysis of whether it’s an obesogen like how getting 10 minutes of sunshine is a carcinogen, or whether it’s an obesogen like how spending a day at the Chernobyl plant is a carcinogen. Otherwise we’re on to “bananas are radioactive” levels of science reporting — technically true, but useless and kind of misleading.

The huge number of contaminants they list does seem like a mark in favor of a “the obesity epidemic is massively multi-causal” hypothesis (which we discussed a bit in this interview), but again it’s hard to tell without seeing a better attempt to estimate effect sizes. The closest thing to an estimate that we saw was this line: “Population attributable risk of obesity from maternal smoking was estimated at 5.5% in the US and up to 10% in areas with higher smoking rates”.

Stress Testing

Their conclusion is especially lacking. It’s one thing to point out that what we’re studying is hard, but it’s another thing to deny the possibility of victory. Let’s look at a few quotes:

“A persistent key question is what percent of obesity is due to genetics, stress, overnutrition, lack of exercise, viruses, drugs or obesogens? It is virtually impossible to answer that question for any contributing factors… it is difficult to determine the exact effects of obesogens on obesity because each chemical is different, people are different, and exposures vary regionally and globally.”

Imagine going to an oncology conference and the keynote speaker gets up and says, “it is difficult to determine the exact effects of radiation on cancer because each radiation source is different, people are different, and exposures vary regionally and globally”. While much of this is true, oncologists don’t say this sort of thing (we hope?) because they understand that while the problem is indeed hard, it’s important, and hold out hope that solving that problem is not “virtually impossible”. Indeed, we’re pretty sure it’s not. 

They’re pretty pessimistic about future research options:

“We cannot run actual ‘clinical trials’ where exposure to obesogens and their effects are monitored over time. Thus, we focus on assessing the strength of the data for each obesogen.”

Assessing the strength of the data is a good idea, but this is leaving a lot on the table. Natural experiments are happening all the time, and you don’t need clinical trials to infer causality. We’d like to chastise this paper with the following words:

[Before] we set about instructing our colleagues in other fields, it will be proper to consider a problem fundamental to our own. How in the first place do we detect these relationships between sickness, injury and conditions of work? How do we determine what are physical, chemical and psychological hazards of occupation, and in particular those that are rare and not easily recognized?

There are, of course, instances in which we can reasonably answer these questions from the general body of medical knowledge. A particular, and perhaps extreme, physical environment cannot fail to be harmful; a particular chemical is known to be toxic to man and therefore suspect on the factory floor. Sometimes, alternatively, we may be able to consider what might a particular environment do to man, and then see whether such consequences are indeed to be found. But more often than not we have no such guidance, no such means of proceeding; more often than not we are dependent upon our observation and enumeration of defined events for which we then seek antecedents.

… However, before deducing ‘causation’ and taking action we shall not invariably have to sit around awaiting the results of the research. The whole chain may have to be unraveled or a few links may suffice. It will depend upon circumstances.

Sir Austin Bradford Hill said that, and we’d say he knows a little more about clinical trials than you do, pal, because HE INVENTED THEM. And then he perfected them so that no living physician could best him in the Ring of Honor– 

So we think the “no clinical trials” thing is a non-issue. Sir Austin Bradford Hill and colleagues were able to discover the connection between cigarette smoking and lung cancer without forcing people to smoke more than they were already smoking. You really can do medical research without clinical trials.

They did not do this

But even so, the paper is just wrong. We can run clinical trials. People do occasionally lose weight, sometimes huge amounts of weight. So we can try removing potential obesogens from the environment and seeing if that leads to weight loss. If we do it in a controlled manner, we can get some pretty strong evidence about whether or not specific contaminants are causing obesity.

Defeatism

Our final and biggest problem with this paper is that it is so tragically defeatist. It leaves you totally unsure as to what would be informative additional research. It doesn’t show a clear path forward. It’s pessimistic. And it’s tedious as hell. All of this is bad for morale. 

The paper’s suggestions seem like a list of good ways to spend forever on this problem and win as many grants as possible. This seems “good” for the scientists in the narrow sense that it will help them keep their tedious desk jobs, jobs which we think they all secretly hate. It’s “good” in that it lets you keep playing what Erik Hoel describes as “the Science Game” for as long as possible:

When you have a lab, you need grant money. Not just for yourself, but for the postdoctoral researchers and PhDs who depend on you for their livelihoods. … much of what goes on in academia is really the Science Game™. … varying some variable with infinite degrees of freedom and then throwing statistics at it until you get that reportable p-value and write up a narrative short story around it.

Think of it like grasping a dial, and each time you turn it slightly you produce a unique scientific publication. Such repeatable mechanisms for scientific papers are the dials everyone wants. Playing the Science Game™ means asking a question with a slightly different methodology each time, maybe throwing in a slightly different statistical analysis. When you’re done with all those variations, just go back and vary the original question a little bit. Publications galore.

If this is your MO, then “more research is needed” is the happiest sound in the world. Actually solving a problem, on the other hand, is kind of terrifying. You would need to find a new thing to investigate! It’s much safer to do inconclusive work on the same problem for decades.

This is part of why we find the suggestion to move towards research with “model organisms such as Drosophila, C. elegans, zebrafish, and medaka” so suspicious. Will this solve the obesity epidemic? Probably not, and certainly not any time this decade. Will it allow you to generate a lot of different papers on exposing Drosophila, C. elegans, zebrafish, and medaka to slightly different amounts of every chemical imaginable? Absolutely.

(As Paul Graham describes, “research must be substantial– and awkward systems yield meatier papers, because you can write about the obstacles you have to overcome in order to get things done. Nothing yields meaty problems like starting with the wrong assumptions.’”)

With all due respect to this approach, we do NOT want to work on obesity for the rest of our lives. We want to solve obesity in the next few years and move on to something else. We think that this is what you want to happen too! Wouldn’t it be nice to at least consider that we might make immediate progress on serious problems? What ever happened to that? 

Political Scientist Adolph Reed Jr. once wrote that modern liberalism has no particular place it wants to go. “Its métier,” he said, “is bearing witness, demonstrating solidarity, and the event or the gesture. Its reflex is to ‘send messages’ to those in power, to make statements, and to stand with or for the oppressed. This dilettantish politics is partly the heritage of a generation of defeat and marginalization, of decades without any possibility of challenging power or influencing policy.“

In this paper, we encounter a scientific tradition that no longer has any place it wants to go (“curing obesity? what’s that?”), that makes stands but has a hard time imagining taking action, that is the heir to a generation of defeat and marginalization. All that remains is a reflex of bearing witness to suffering. 

We think research can be better than this. That it can be active and optimistic. That it can dare to dream. That it can make an effort to be interesting. 

Why do we keep complaining about this paper being boring? Why does it matter? It matters because when the paper is boring, it suggests that the idea that obesity is caused by contaminants isn’t important enough to bother spending time on the writing. It suggests people won’t be interested to read the paper, that no one cares, that no care should be taken in the discussion. That nothing can be gained by thinking clearly about these ideas. It suggests that the prospect of curing obesity isn’t exciting. But we think that the prospect of curing obesity is very exciting, and we hope you do too!

Philosophical Transactions: Lithium in Scottish Drinking Water with Al Hatfield

Previous Philosophical Transactions:

Al Hatfield is a wannabe rationalist (his words) from the UK who sent us some data about water sources in Scotland. We had an interesting exchange with him about these data and, with Al’s permission, wanted to share it with all of you! Here it is:


Hi,

I know you’re not that keen on correlations and I actually stopped working on this a few months ago when you mentioned that in the last A Chemical Hunger post, but after reading your post today I wanted to share it anyway, just in case it does help you at all. 

It’s a while since I read all of A Chemical Hunger but I think this data about Scottish water may support a few things you said:

– The amount of Lithium in Scottish water is in the top 4 correlations I found with obesity (out of about 40 substances measured in the water)

– I recall you predicted the top correlation would be about 0.5, the data I have implies it’s 0.55, so about right.

– I recall you said more than one substance in the water may contribute to obesity, my data suggested 4 substances/factors had correlations of more than 0.46 with obesity levels and 6 were more than 0.41.

Method

– Scottish Water test and record how much of up to 43 substances is in each reservoir/water source in Scotland https://www.scottishwater.co.uk/your-home/your-water/water-quality/water-quality

– their data is in pdf format but I converted it to Excel

– Scottish Water don’t publish Lithium levels online but I did a Freedom of Information request and they emailed it to me and I added it to the spreadsheet.

– I used the website to get the water quality data for a reservoir for every city/big town in Scotland and lined it up in the spreadsheet.

– I used Scottish Health Survey – Local Area Level data to find out what percentage of people are obese in each area of Scotland and then matched it as well as I could to a reservoir/water source.

– I then used the Data Analytics add-on in Excel to work out the correlations between the substances in the water and obesity.

Correlations with obesity (also in attachment)

Conductivity 0.55

Chloride 0.52

Boron 0.47

Lithium 0.47

Total Trihalomethanes 0.42

Sodium 0.42

Sulphate 0.38

Fluoride 0.37

Colony Counts After 3 Days At 22øc 0.34

Antimony 0.33

Gross Beta Activity 0.33

Total organic carbon 0.31

Gross Alpha Activity 0.30

Cyanide 0.26

Iron 0.26

Residual Disinfectant – Free 0.23

Arsenic 0.23

Pesticides – Total Substances 0.23

Coliform Bacteria (Total coliforms) 0.23

Copper 0.19

PAH – Sum Of 4 Substances 0.19

Nitrite 0.17

Colony Counts After 48 Hours At 37øc 0.16

Nickel 0.13

Nitrite/Nitrat e formula 0.13

Nitrate 0.12

Cadmium 0.11

Turbidity 0.08

Bromate 0.08

Colour 0.06

Lead -0.10

Manganese -0.12

Hydrogen ion (pH) -0.12

Aluminium -0.15

Chromium -0.15

Ammonium (total) -0.22

2_4-Db -0.25

Residual Disinfectant – Total -0.36

2_4-D -0.42

Dicamba -0.42

MCPB -0.42

MCPP(Mecoprop) -0.42

Scottish Water definition of Conductivity

Conductivity is proportional to the dissolved solids content of the water and is often used as an indication of the presence of dissolved minerals, such as calcium, magnesium and sodium.

Anyway, not sure if that’s any help to you at all but I enjoy your blog and thought I would send it in. Let me know if you have any questions.

Thanks 

Al


Hi Al,

Wow, thanks for this! We’ll take a look and do a little more analysis if that’s all right, and get back to you shortly. 

Do you know the units for the different measurements here, especially for the lithium? We’d be interested in seeing the original PDFs as well if that’s not too much hassle.

Thanks! 

SMTM


Hi,

You’re welcome! That’s great if you can analyse it as I am very much an amateur. 

The units for the Lithium measurements are µgLi/l. I’ve attached the Lithium levels Scottish Water sent me. I think they cover every water source they test in Scotland (though my analysis only covered about 15 water sources).

Sorry I don’t have access to the original pdfs as they’re on my other computer and I’m away at the moment. But I have downloaded a couple of pdfs online. Unfortunately the online versions have been updated since I did my analysis in late November, but hopefully you can get the idea from them and see what measurements Scottish Water use.

Let me know if you’d like anything else.

Thanks,

Al


Hey Al,

So we’ve taken a closer look at the data and while everything is encouraging, we don’t feel that we’re able to draw any strong conclusions.

We also get a correlation of 0.47 between obesity and lithium levels in the water. The problem is, this relationship isn’t significant, p = 0.078. Basically this means that the data are consistent with a correlation anywhere between -0.06 and 0.79, and since that includes zero (no relationship), we say that it’s not significant.

This still looks relatively good for the hypothesis — most of the confidence interval is positive, and these data are in theory consistent with a correlation as high as 0.79. But on the whole it’s weak evidence, and doesn’t meet the accepted standards.

The main reason this isn’t significant is that there are only 15 towns in the dataset. As far as sample sizes go, this is very small. That’s just not much information to work with, which is why the correlation isn’t significant. For similar reasons, we haven’t done any more complicated analyses, because we won’t be able to find much with such a small sample to work with. 

Another problem is that correlation is designed to work with bivariate normal distributions — two variables, both of them approximately normally distributed, like so: 

Usually this doesn’t matter a ton. Even if you’re looking at a correlation where the two variables aren’t really normally distributed, it’s usually ok. And sometimes you can use transformations to make the data more normal before doing your analysis. But in this case, the distribution doesn’t look like a bivariate normal at all:  

Only four towns in the dataset have seriously elevated lithium levels, and those are the four fattest towns in the dataset. So this is definitely consistent with the hypothesis.

But the distribution is very strange and very extreme. In our opinion, you can’t really interpret a correlation you get from data that looks like this, because while you can calculate a correlation coefficient, correlation was never intended to describe data that are distributed like this.

On the other hand, we asked a friend about this and he said that he thinks a correlation is fine as long as the residuals are normal (we won’t get into that here), and they pretty much are normal, so maybe a correlation is fine in this case? 

A possible way around this problem is nonparametric correlation tests, which don’t assume a bivariate normal distribution in the first place. Theoretically these should be kosher to use in this scenario because none of their assumptions are violated, though we admit we don’t use nonparametric methods very often. 

Anyways, both of the nonparametric correlation tests we tried were statistically significant — Kendall rank correlation was significant (tau = 0.53, p = .015), and so was the Spearman rank correlation (rho = 0.64, p = .011). Per these tests, obesity and lithium levels are positively correlated in this dataset. The friend we talked to said that in his opinion, nonparametric tests are the more conservative option, so the fact that these are significant does seem suggestive. 

We’re still hesitant to draw any strong conclusions here. Even if the correlations are significant, we’re working with only 15 observations. The lithium levels only go up to 7 ppb in these data, which is still pretty low, at least compared to lithium levels in many other areas. So overall, our conclusion is that this is certainly in line with the lithium hypothesis, but not terribly strong evidence either way.

A larger dataset of more than 15 towns would give us a bit more flexibility in terms of analysis. But we’re not sure it would be worth your time to put it together. It would be interesting if the correlation were still significant with 30 or 40 towns, and we could account for some of the other variables like Boron and Chloride. But, as we’ve mentioned before, in this case there are several reasons that a correlation might appear to be much smaller than it actually is. And in general, we think it can sometimes be misleading to use correlation outside the limited set of problems it was designed for (for example, in homeostatic systems).

That said, if you do decide to expand the dataset to more towns, we’d be happy to do more analysis. And above all else, thank you for sharing this with us!

SMTM

[Addendum: In case anyone is interested in the distribution in the full lithium dataset, here’s a quick plot of lithium levels by Scottish Unitary Authority: 

]


Thanks so much for looking at it. Sounds like I need to brush up on my statistics! Depending how bored I get I may extend it to 40 towns some time, but for now I’ll stick with experimenting with a water filter.

All the best,

Al

Philosophical Transactions: JP Callaghan on Lithium Pharmacokinetics

In the beginning, scientific articles were just letters. Scholars wrote to each other about whatever they were working on, celebrating their discoveries or arguing over minutiae, and ended up with great stacks of the things. People started bringing interesting letters to meetings of the Royal Society to read aloud, then scientists started addressing their letters to the Royal Society directly, and eventually Henry Oldenburg started pulling some of these letters together and printing them as the Philosophical Transactions of the Royal Society, the first scientific journal.

In continuance of this hallowed tradition, in this blog post we are publishing some philosophical transactions of our own: correspondence with JP Callaghan, an MD/PhD student at a large Northeast research university going into anesthesia. He has expertise in protein statistical mechanics and kinetic modeling, so he reached out to us with several ideas and enlightened criticisms.

With JP Callaghan’s help we have lightly edited the correspondence for clarity, turning the multi-threaded format of the email exchange into something more linear. We found the conversation very informative, and we hope you do as well! So without further ado: 


JP Callaghan:  Hi guys, great work on A Chemical Hunger

I’m sure someone already suggested this but the Fulbright program executes the “move abroad” experiment every year. In fact, they do the reverse experiment as well, paying foreigners to move to the US. The Phillipines Fulbright program seems especially active.

(The Peace Corps is already doing this experiment as well, but that’s probably probably more confounded since people are often living in pretty rustic locations.)

You could pretty easily imagine paying these folks a little extra money to send you their weight once a month or whatever.

SLIME MOLD TIME MOLD:  Thank you! Yeah, we’ve been trying to figure out the best way to pursue this one, using existing data if possible. Fulbright is a good idea, especially US <–––> Philippines, and especially because we suspect young people will show weight changes faster. We’ve also thought about trying to collect a sample of expats, possibly on reddit, since there are a lot of anecdotes of weight loss in those communities.

The tricky thing is finding someone who has an in with one of these groups. We probably can’t just cold call Fulbright and ask how much all their scholars weigh, though we’ll start asking around. 

JPC: Unfortunately my connection with the Fulbright was brief, superficial, and many years ago. I can ask around at my university, though. I’m not filled with unmitigated optimism, but the worst they can do is say no/ignore me.

Also, I wanted to mention that lithium level measurements are extremely common measurements in clinical practice. It’s used to monitor therapeutic lithium (for e.g. bipolar folks). (Although I will concede usually they are measuring .5 – 1.5 mmol/L which would be way higher than serum levels due to contamination.) Also, it’s interesting that the early pharmacokinetic studies also measured urine lithium (see e.g. Barbara Ehrlich’s seminal 1980 paper) so there’s precedent for that as well. I’m led to understand from my lab medicine colleagues that it’s a relatively straightforward (aka cheap) electrochemical assay, at least in common clinical practice.

SMTM:  We’ve looked into measurement a bit. We’re concerned that serum levels aren’t worth measuring, since lithium seems to accumulate in the brain and we suspect that would be the mechanism (a commenter suggested it might also be accumulation in bone). But if we were to do clinical measurements, we’d probably measure lithium in urine or maybe even in saliva, since there’s evidence they’re good proxies for one another and for the levels in serum, and they’re easier to collect. Urine might be especially important if lithium clearance rate ends up being a piece of the puzzle, which it seems like it might. 

JPC: It is definitely true that lithium accumulates inside cells (definitely rat neurons and human RBCs, probably human neurons, but maybe not human muscle; see e.g. that Ehrlich paper I mentioned). The thing is, lithium kinetics seem to be pretty fast. Since it’s an ion, it doesn’t partition into fat the way other long-lasting medications and toxins do, and so it’s eliminated fairly quickly by the kidneys. (THC is a classic example of a hydrophobic “contaminant”; this same physical chemistry explains why a long-time pothead will test positive for THC for months, but you can stop using cocaine and, 72 hours later, screen negative.)

It might be worth your time to look at some of the lithium washout experiments that have been done over the years (e.g. Hunter, 1988 where they see lithium levels rapidly decline after stopping lithium therapy that had been going on for a month).

I suppose, though, that I’m not aware of any data that specifically excludes the possibility that there is a very slow “third compartment” where lithium can deposit (such as, as your commenter suggested, bone; although I don’t know much about whether or not lithium can incorporate into the hydroxyapatite matrix in bone. It’s mostly calcium phosphate and I’m not sure if lithium could “find a place” in that crystalline matrix).

Anyway, though, my understanding is that lithium kinetics in the brain are relatively fast. (For instance, see Ebadi, et al where they measure [Li] in rat brains over time.) So even if you have a highly accumulated slow bone compartment, the levels of lithium you’d get in the brain would still be super low, because it equilibrates with the blood quickly and therefore is subject to rapid elimination by the kidneys.

However, I don’t think you need to posit accumulation for your hypothesis. If you’re exposed to constant, low levels of lithium, you reach an equilibrium. There’s some super low serum concentration, some rather-higher intracellular concentration, and it’s all held in steady state by the constant intake via the GI tract (say, in the water) and constant elimination by the kidneys. Perhaps this is what you’re getting at when you say the rate of elimination might be very important?

Instead, consider some interesting pharmacodynamics: low-level (or maybe widely fluctuating, since lithium is also quickly cleared?) exposure to lithium messes with the lipostat. This process is probably really slow, maybe because weight change is slow or maybe because of some kind of brain adaptation process or whatever. We have good reason to suspect low-level lithium has neurological effects already anyway through some of the population-level suicide data I’m sure you’re aware of.

Urine and serum levels of lithium are only good proxies for one another at steady state. I really strongly suggest you guys look at that Ehrlich paper. She measures serum, intra-RBC, and urine [Li] after a dose of lithium carbonate (the most common delayed-release preparation of pharmaceutical lithium).

Another good one is Gaillot et al which demonstrates how important the form of lithium (lithium carbonate vs LiCl) is to the kinetics. (As an aside, this might be a reason for lithium grease to be so bad; lithium grease is apparently some kind of weird soap complex with fatty acids, maybe it gets trapped in the GI tract or something.)

SMTM: The rat studies are interesting but don’t rats seem like a bad comparison for determining something like rate of clearance? Besides just not being human, their metabolisms are something like 6-8x faster than ours and their lifespans are about 20 times shorter. Also human brains are huge. What do you think?

JPC: Certainly I agree that rats are not people and are bad models in many ways. I think that renal function is the key parameter you’d want to compare. The most basic measure of kidney function is the GFR (glomerular filtration rate), which basically measures how much fluid gets pushed through the “kidney filter” per unit time. Unfortunately in people we measure it in volume/time/body surface area and in rats volume/time/mass which makes a comparison less obvious than I was hoping. To be honest, I am not sure how well rat kidney function and human kidney function is comparable. (Definitely more comparable than live and dead human kidney function, though 😉.)

What do you mean by ”their metabolisms are something like 6-8x faster than ours”? Like, calories/mass/time? Usually when I think about “metabolic rate” I am thinking of energy usage. When we think about drug elimination, the main things that matter are 1) liver function (for drugs that are hepatically metabolized) 2) various tissue enzyme function (e.g. plasma esterases for something like esmolol) and 3) renal function. I don’t generally think about basal metabolic rate as being a pertinent factor, really, except perhaps in cases where it’s a proxy for hepatic metabolism.

Lithium is eliminated (“cleared”) almost exclusively by the kidney and it undergoes no metabolic transformations, so I wouldn’t worry about anything but kidney function for its clearance.

You’re right, though, the 20x lifespan difference could be an issue. If we are worried about accumulation on the timescale of years, then obviously a shorter rat life is a problem. But (if I read your blog posts right) rats as experimental animals are also getting fatter so presumably the effect extends to them on the timescale of their life? (Did you have data in rats? I don’t remember.)

Indeed, if it’s actually just that there a constant low-level “infusion” of lithium via tapwater, grease exposure at work, etc giving rise to a low steady-state lithium (rather than actual bioaccumulation) this would explain why the effect does extend to these short-lived experimental animals.

SMTM: You make good points about laboratory animals. There are data on rats and they do seem to be getting heavier. Let’s stick a pin in this one for a now, you may find this next bit is relevant to the same questions:

In your opinion, are the studies you cite consistent or inconsistent with the findings of Amdisen et al. 1974 and Shoepfer et al. 2021? Also potentially relevant is Amidsen 1977. We describe their findings near the end of this section — basically they seem to suggest that Li accumulates preferentially in the bones, thyroid, and parts of the brain. The total sample size is small but it seems suggestive. We agree accumulation may not be essential to the theory but doesn’t this look like evidence of accumulation? We’ve attached copies of Amdisen et al. 1974 and Amdisen 1977 as PDFs in case you want to take a closer look. [SMTM’s Note: If anyone else wants to see these papers, you can email us.]

Especially interesting that Ebadi et al. say, “it has been shown that sodium intake exerts a significant influence on the renal elimination of lithium (Schou, 1958b)”, somewhat in line with our speculation here. We’ll have to look into that. 

Brains

JPC: Thanks for the papers. As you predicted, I’m finding them super interesting.

Shoepfer et al, 2021 is a lovely, very interesting paper (complete with some adorable Deutsch-English). I was aware of it but had not taken the time to read it yet.

By my read, it is primarily seeking to establish this new, nuclear fission based approach to measuring lithium in pathology tissue. After spending some time with it, I don’t really know how to interpret their findings. The main reason I am not sure what to do with this paper is that the results are in dead peoples’ brains. Indeed, they specifically note in their ‘limitations’ section: “The lithium distribution patterns so far obtained with the NIK method, thus in no way contradicting given literature references, are based on post mortem tissue.” The reason this is pertinent is that there is a lot of active transport of other monovalent cations (K, Na) and so I would worry that this is true for lithium as well and (obviously) this is almost certainly disrupted in dead people.

The second thing is that the tissue was fixed in (presumably) formalin and stained with hematoxylin and eosin before measuring lithium, which then comes out in units of mass/mass. Obviously in living tissue there’s lots of water and whatnot, and the mass-density of water and formalin is going to be pretty different.

So, as the authors say, I would say it’s neither consistent nor inconsistent with other data.

SMTM: It’s true that all the brain samples we have in humans are in dead brain tissue, but this seems like an insurmountable issue, right? Looking at dead tissue is the only way to get even a rough estimate of how much lithium is in the brain, since as far as we know there’s no way to test the levels in a living human brain, or if there is, no one has taken those measurements and it’s outside our current budget. 

In any case, the most relevant findings from these studies, at least in our opinion, are 1) that lithium definitely reaches brain tissue and sticks around for a while, and 2) regardless of absolute levels, there seems to be relatively more lithium in parts of the brain that regulate appetite and weight gain. These conclusions seem likely to hold even given all the reasonable concerns about dead tissue. What do you think?  

JPC: I agree. In my mind, the main question is whether or not lithium persists in the brain after cessation of lithium therapy. Put more rigorously, what is the rate of exchange between the “brain compartment” and (probably) the “serum compartment.” (I guess it could also be eliminated by CSF too maybe? Or “glymphatics”? idk I guess nobody really understands the brain.)

The main issue I have is this: if you’re exposed, say, to 20 ppb lithium and your serum has 20 ppb lithium and so does the cytoplasm in your neurons, this is actually the null hypothesis (that lithium is an inert substance that just flows down its concentration gradient). It’s obviously false (we know lithium concentrates in RBCs of healthy subjects, for instance), but this paper doesn’t help me decide if lithium 1) passively diffuses throughout the body 2) is actively concentrated in neurons, or even 3) is actively cleared from cells, simply because I don’t really know what to do with the number.

The second issue is the preparation. Maybe formalin fixation washes lithium away, or when it fixes cell membranes maybe the lithium is allowed to diffuse out. Maybe it poorly penetrates myelin sheaths, and has a tendency to concentrate the lithium inside cells by making the extracellular environment more hydrophobic (nature abhors an unsolvated ion).

Another reason I am so skeptical of the “slow lithium kinetics” hypothesis is just the physical chemistry of lithium. It’s a tiny, charged particle. Keeping these sorts of ions from moving around and distributing evenly is actually really hard in most cases. There are a few cases of ionic solids in the human body (various types of kidney stones, bones, bile stones] but for the most part these involve much less soluble ions than lithium and everything is dissolved and flows around at its whim except where it’s actively pumped.

SMTM: This is a good point, and in addition, the fact that tourists and expats seem to lose weight quickly does seem to be a point in favor of fast lithium over slow lithium. If those anecdotes bear out in some kind of more systematic study, “slow lithium kinetics” starts looking really unlikely. Another possibility, though, is that young people are the only ones who lose weight quickly on foreign trips, and there’s something like a “weight gain in the brain, reservoir in the bone” system where people remain dosed for a long time once enough has built up in their bones (or some other reservoir).

JPC: Very possible. Also young people generally have better renal function. There are tons of people walking around with their kidneys at like 50% or worse who don’t even know it.

A third and distant issue what I mentioned about the active transport of Na and K that happens in neurons (IIRC something like 1/3 of your calories are spent doing this) ceasing when you’re dead. This is also a fairly big deal, though, since there are various cation leak channels in cell membranes (for electrical excitability reasons, I think; ask an electrical engineer or a different kind of biophysicist) through which Li might also escape. (Since, after all, a reasonable hypothesis for the mechanism of action is that Li uses Na channels.)

Between these three difficulties, I do actually see this as borderline insurmountable for ascertaining how much lithium is in an alive brain based on these data. Basically, it comes down to “I don’t know how much lithium I should expect there to be in these experiments.”

However, “relatively more lithium in parts of the brain that regulate appetite and weight gain” is a good point. I think that this is something you actually can reasonably say: it seems like there is more lithium in these areas than other areas. The within-experiment comparisons definitely seem more sound. It would also be consistent with the onset of hunger/appetite symptoms below traditionally-accepted therapeutic ranges.

I do also want to clarify what I mean by “no accumulation.” There is of course a sort of accumulation for all things at all times. You take a dose of some enteral medication, it leaches into your bloodstream from your gut, accumulating first in the serum. It then is distributed throughout the body and accumulates in other compartments (brain, liver, kidney, bone, whatever). Assuming linear pharmacokinetics, there’s some rate that the drug goes in to and out of each of these compartments. 

If you keep taking the drug and the influx rate (from the serum into a compartment) is higher than the efflux rate (back to the serum from the compartment), the steady state in the compartment will be higher than the serum at steady state. In some sense, this could be called “accumulation.” But in another sense, if both these rates are fast, your accumulation is transient and quickly relaxes to zero if you clear the serum compartment of drug (which we know happens in normal individuals in the case of lithium). Although the concentration in the third compartment is indeed higher than in the serum, if you stop taking the drug, it will wash out (first from the serum then, more slowly, from the accumulating compartment).

SMTM: Thanks, this clarification is helpful. To make sure we understand, “accumulation” to you means that a contaminant goes to a part of the body, stays there, and basically never leaves. But you’re open to “a sort of accumulation” where 50 units go into the brain every day and only 10 units are cleared, leading to a more-or-less perpetual increase in the levels. Is that right? 

JPC: Yes. I would frame this in terms of rates, though. So 5 x brain concentration units go to the brain and 1 x brain concentration units go out of the brain per unit time, such that you get a steady state concentration difference between the serum in the brain of in_rate / out_rate (in this case).

You guys seem mathy so I’ll add: for an arbitrary number of compartments this is just a first-order ODE. You can represent this situation as rate matrix K where element i, j represents the rate (1/time) that material flows from compartment i to j (or maybe j to i, I can never remember). Anyway this usually just boils down to something looking like an eigenvector problem to get the stationary distribution of things. (Obviously things get more complicated when you have pulsatile influx.)

The key question, though, is what effect does this high concentration in the accumulating compartment have on the actual physiology? If we have slowly-resolving, high concentration in the brain, then I think we could call this clinical (ie neuropharmacologically significant) accumulation. However, I think the case in the brain is that you have higher-than-serum concentrations, but that these concentrations quickly resolve after cessation of lithium therapy. My reasoning for this is that lithium pharmacokinetics are classically well-modeled with two- and three-compartment models, which mostly have pretty fast kinetics (rate parameters with half lives in the hours range).

SMTM: This is interesting because our sense is sort of the opposite! Specifically, our understanding is that most people who go off clinical doses of lithium do not lose much weight and tend to keep most of the weight they gained as a side effect (correct us if we’re wrong, we haven’t seen great documentation of this). 

This seems at least suggestive that relatively high levels of lithium persist in the brain for a long time. On the other hand, clinical doses are really, really huge compared to trace doses, so maybe there is just so much in the brain compartment that it sometimes takes decades to clear. Ok we may not actually disagree, but it seemed like an interesting minor point of departure that might be worth considering.

JPC: I don’t know about this! I agree that slower (months to years) kinetics of lithium in the brain could explain this. An alternative (relatively parsimonious) explanation would be that, as Guyenet proposes, there simply is no mechanism for shedding excess adiposity. So if you gain weight as the result of any circumstance, if it stays on long enough for the lipostat to habituate to it, you just have a new, higher adiposity setpoint and have great difficulty eliminating that weight. That is, not being able to get the weight off after lithium-related weight gain might just be normal physiology.

The idea that clinical doses are just huge is sort of interesting. Normally, we think of the movement of ions in these kinetics models as having first-order kinetics (i.e. flux is proportional to concentration), but if you have truly shitboats of lithium in the brain, you could imagine that efflux might saturate (i.e. there are only so many transporters for the lithium to get out, since I imagine the cell membrane itself is impenetrable to Li+). This could be interesting. Not sure how you’d investigate it though. Probably patch-clamp type studies in ex vivo neurons? These are unfortunately expensive and extremely technical.

Amidsen

JPC: I see Amdisen et al. 1974 describes a fatal dose of lithium, which is very different pharmacokinetically from therapeutic doses. Above about 2.0 mmol/L (~2x therapeutic levels), lithium kinetics become nonlinear—that is, the pharmacokinetics are no longer fixed and the drug begins to influence its own clearance. In the case of lithium, high doses of lithium reduce clearance, leading to a vicious cycle of toxicity. This is a big deal clinically, often leading to the need for emergent hemodialysis.

So this is consistent with the papers I mentioned earlier (Ehrlich et al, Galliot et al) in the sense that cannot really conflict because they are reporting on two very different pharmacokinetic regimes.

You can’t directly compare the lithium kinetics in this patient to those in healthy people. You can see in figure 1 that the patient’s “urea” (I assume what we’d call BUN today?) explodes, which is a result of renal failure. It sounds like the patient wasn’t making any urine, i.e. has zero lithium clearance.

Figure 1 from Amdisen et al. 1974

SMTM: True, it’s hard to tell. But FWIW lithium also seems to be cleared through other sources like sweat, so even renal failure doesn’t mean zero lithium clearance, just severely reduced. (Though not sure the percent. 50% through urine? 80%? 99%?)

JPC: Yes this is true, of course. My intuition would be that it’s closer to 99% or even like 99.9%. The kidney’s “function” (I guess you have to be a bit careful not to anthropomorphize/be teleological about the kidney here, but you know what I mean) is to eliminate stuff from the blood via urine, which it does very well, whereas sweat and other excreta have other functions.

Let’s assume for a second that lithium and sodium are the same and that the body doesn’t distinguish (obviously false; all models are wrong but some are useful) and let’s do some math.

In the ICU we routinely track “ins and outs” very carefully. Generally normal urine output is 0.5 – 1.5 mL/kg body weight/hr. In a 70 kg adult call it >800 mL/day. But because we also know how much fluid is going in, we know how much we lose to evaporation (sweat, spitting, coughing up gunk, etc), which we call “insensible losses.” This is usually 40-800 mL/day.

A normal sweat chloride (which we use to check for cystic fibrosis) is <29 mM. Because sweat doesn’t have a static charge, we know there’s some positive counterion. Let’s assume it’s all sodium. So call it 30 mM NaCl, and calculate 800 mL x 30 mM = 24 mmol NaCl and 40 mL x 30 mM = 1.2 mmol. These are collected using (I think) topical pilocarpine to stimulate sweat production, so this would be an upper bound probably. It’s pretty close to what they find here which is in athletes during training (full disclosure I didn’t read the whole thing), which seems like it would be similar to the pilocarpine case (i.e. unlikely to be sustained throughout the day).

We also measure 24-hour sodium elimination when investigating disorders of the kidney. A first-reasonabe-google-hit normal range is 40-220 mmol Na/24 hours. (Of course, this is usually done when fluid-restricting the patient, so this would be on the low end of normal. If you go to Shake Shack and eat a giant salty burger your urine urea and Na are going to skyrocket. If you’re in a desert, your urine will be WAY concentrated, but maybe lower volume. It’s hard to generalize so this is at best a Fermi estimation type of deal.)

Anyhow, we’re looking at somewhere between 2x and 250x more sodium eliminated in the urine. Again my guess is that we’d be closer to the 250x number and not the 2x number for some of the reasons I mention above. Also I worry you can’t just multiply insensible losses * sweat [Na] because as water evaporates it gets drawn out of the body as free water to re-hydrate the Na, or something.

In writing this up, I also found this paper which also does some interesting quantification of sweat electrolytes (again we get a mean sweat [Na] of 37 and [Cl] of 34), but in some of the later plots (Figure 2) we can see that [Na] and [Cl] go way low and that the average seems to be being pulled up by a long tail of high sweat electrolytes.

So not sure what to take away from that but I thought I’d share my work anyway. 🙂

Bone

JPC: In the case of bone, however, there might be something here! You could imagine the bone being a large but slowly-exchanging depot of lithium. I’d be interested to see if anyone has measured bone lithium levels in folks who were, say, on chronic therapeutic lithium. I’m not aware of anything like that.

SMTM: It seems to fit Amdisen et al. 1974. That case study is of a woman who was on clinical levels of lithium for three years, and had relatively high concentrations in her bones. Like you say, a fatal dose of lithium is very different pharmacokinetically from therapeutic doses, but the rate at which lithium deposits in bone is presumably (?) much slower than for other tissues, so this may be a reasonable estimate of how much had made it into her bones from three years of clinical treatment. Sample size of one, etc., but like you say there doesn’t seem to be any other data on lithium in bones. 

JPC: I think it’s hard to say for sure if high concentration in her bones is due to the chronic therapy or the overdose. However, they note higher (0.77 vs 0.59 mmol/kg) in dense bone (iliac crest) than in spongey bone (vertebral body; there’s a better name than spongey… maybe cumulus? I don’t remember.). That’s interesting because it suggests to me (assuming that the error in the measurement is << 0.77-0.59) there is more concentrating effect in mineralized bone than all the cellular components (osteoclasts, osteoblasts, hematopoietic cells etc). 

Anyway it’s suggestive that maybe there is deposition in bone. I wouldn’t hang my hat on it, but it is definitely consistent with it. I also agree that bone mineralization/incorporation seems like it ought to be on a longer timescale than cellular transport, so that is consistent as well. Obviously n=1, etc etc, but it’s kind of cute.

SMTM: Maybe we should see if we could do a study, there must be someone out there with a… skeleton bank? What do you call that? 

JPC: A cadaver lab? I think most medical schools have them (ours does). In an academic medical setting, I would just get an IRB to collect bone samples from all the cadavers or maybe everyone who gets an autopsy that’s sufficiently extensive to make it easy to collect some bone. This would be a convenience sample, of course, but it would be interesting. Correlate age, zip code, renal function if known?

Because the patient is dead, there’s no risk of harm, and because they’re already doing the autopsy/dissection/whatever it should be relatively straightforward to collect in most cases (I mean, they remove organs and stuff to weigh and examine them so grabbing a bit of bone is easy). Unfortunately all these people got sick and died so you have a little bit of a problem there. For example, if someone had cancer and was cachectic, what can you learn from that? Idk.

In vivo bone biopsies are also a relatively common procedure done by interventional radiology under CT guidance (it’s SUPER COOL). You also have the problem that people are getting their biopsies for a reason, and usually the reason boils down to “we think that this bone looks weird,” so your samples would be almost by definition abnormal.

SMTM: Great! Maybe we can find someone with a cadaver lab and see if we can make it happen. This is a very cool idea.

Control Systems

SMTM: Earlier you mentioned the idea that the body’s set point can only be raised, but it seems really unlikely to us that there’s no mechanism for shedding excess adiposity. 

JPC: Hmm. You guys are definitely better read on this subject than I am, but do I fear I have oversimplified the Guyenet hypothesis somewhat. My recollection is that it is more that there’s no driving force for the lipostat setpoint to return to a healthy level if it has habituated to a higher level of adiposity.

I like the analogy to iron. (I don’t think that Guyenet makes this connection, but I read The Hungry Brain years ago so I’m not sure.) It turns out that the body has no way of directly eliminating iron, so when iron levels get high, the body just turns off the “get more iron” system. Eventually, iron slowly makes its way out of the body because bleeding, entropy, etc etc and the iron-absorption system clicks back on. (This is relevant because patients who receive frequent transfusions, such as those with sickle cell, get iron overload due to their inability to eliminate the extra iron.)

I guess, by analogy, it would be that the mechanism for shedding adiposity would be “turn off the big hunger cues.” It’s not no mechanism, it’s just a crappy, passive, poorly-optimized mechanism. (Presumably because, like how nobody got transfusions prior to the 20th century, there was never an unending excess of trivially-accessible and highly palatable food in our evolutionary history.)

SMTM: Well, overfeeding studies raise people’s weights temporarily but they quickly go back to where they were before. Anecdotally, a lot of people who visit lean countries lose decent amounts of weight in just a few weeks. And occasionally people drop a couple hundred pounds for no apparent reason (if the contamination hypothesis is correct, this probably happens in rare cases where a person serendipitously eliminates most of their contamination load all at once). And people do have outlets like fidgeting that seem to be a mechanism beyond just “turn off the big hunger cues.” All this seems to suggest that weight is controlled in both directions.

JPC: Proponents of the above hypothesis would explain this by saying that the lipostat doesn’t have time to habituate to the new setpoint during the timescale of an overfeeding study, and so they lose the weight by having their “acute hunger cues” turned off. Whereas as weight creeps up year after year, the lipostat slowly follows the weight up. You do bring up a good point about fidgeting, though.

My thought was that bolus-dosed lithium (in food or elsewhere) might serve the function of repeated overfeeding episodes, each one pushing the lipostat up some small amount, leading to overall slow weight gain. 

I think combining the idea that the brain concentrates lithium with an “up only” lipostat might give you this effect? If we say 1) lithium probably concentrates first in areas controlling hunger and thirst, leading to an effect on this at lower-than-theraputic serum concentrations, you might see weeks of weight-gain effect from a bolus 2) that we know that weight gain can occur on this timescale and then not revert (see the observation, which I read about in Guyenet, that most weight is gained between thanksgiving and NYE). What do you think?

SMTM: To get a little more into the weeds on this (because you may find it interesting), William Powers says in some of his writing (can’t recall where) that control systems built using neurons will have separate systems for “push up” and “push down” control. If he’s right, then there are separate “up lipostats” and “down lipostats”, and presumably they function or fail largely separately. This suggests that a contaminant that breaks one probably doesn’t break the other, and also suggests that the obesity epidemic would probably be the result of two or more contaminants.

JPC: Yes! Super interesting. There are lots of places in the brain where this kind of push-pull system is used. I remember very clearly a neuroscience professor saying, while aggressively waving his hands, that “engineers love this kind of thing and that’s probably why the brain does it too.” I wonder if he was thinking of Powers’ work when he said that.

SMTM: Let’s say that contaminant A raises the set point of the “down lipostat”, and contaminant B raises the set point of the “up lipostat”. Someone exposed to just A doesn’t necessarily get fatter, but they can drift up to the new set point if they overeat. At the same time, with exercise and calorie restriction, there’s nothing keeping them from pushing their weight down again. 

Someone exposed to both A and B does necessarily get fatter, because they are being pushed up, and they have to fight the up lipostat to lose any weight, which is close to impossible. (This might explain why calorie restriction seems to work as a diet for some people but doesn’t work generally.) 

Someone exposed to just B, or who has a paradoxical reaction to A, sees their up and down lipostats get in a fight, which looks like cycles of binging and purging and intense stress. This might possibly present as bulimia.

There isn’t enough evidence to tell to this level of detail, but a plausible read based on this theoretical perspective is that we might see something like, lithium raises the set point of the down lipostat and PFAS raise the set point of the up lipostat, and you only get really obese if you get exposed to high doses of both. 

JPC: Very interesting! It’s definitely appealing on a theoretical level. (See: your recent post on beauty in science.) I just don’t know anything about the state of the evidence in the systems neuroscience of obesity to say if it’s consistent or inconsistent with the data. (Same is of course true of the lipostat-creep hypothesis above.)

I’m not sure about why you think the two systems would function separately? Certainly, for us to see a change, there would have to be a failure of one or the other population preferentially but I’m not sure why this would be less common than one effect or the other. They’d be likely anatomical neighbors, and perhaps even developmentally related. I guess it would all depend on the actual physiology. I’m thinking, for instance, of how the eye creates center-surround receptive fields using the same photoreceptors in combination with some (I think) inhibitory interneurons (neural NOT gates). The same photoreceptor, hooked up a different way, acts to activate or inhibit different retinal ganglion cells (the cells that make up the optic nerve… I think. It’s been a while.). Another example might be the basal ganglia, which (allegedly) functions to select between different actions, but mostly our drugs act to “do more actions” by being pro-dopaminergic (for instance to treat Parkinsons) or “do fewer actions” by being antidopaminergic (as in antipsychotics like haloperidol).

SMTM: Yeah good points and good question! We have reasons to believe that these systems (and other paired systems) do function more or less separately, but it might be too long to get into here. Long story short we think they are computationally separate but probably share a lot of underlying hardware. 

Dynamics

SMTM: What do you think of a model based on peak lithium exposure? Our concern is that most sources of exposure are going to be lognormally distributed. Most of the time you get small doses, but very rarely you get a really really large dose. Most food contains no lithium grease, but every so often some grease gets on your hamburger during transport and you eat a big glob of it by accident. 

Lognormal Distribution

Or even more concerning: you live downriver from a coal power plant, and you get your drinking water from the river. Most of the time the river contains only 10-20 ppb Li+, nothing all that impressive. But every few months they dump a new load of coal ash in the ash pond, which leaches lithium into the river, and for the next couple of days you’re drinking 10,000 ppb of lithium in every glass. This leads to a huge influx, and your compartments are filled with lithium. 

This will deplete over time as your drinking water goes back to 10 ppb, but if it happens frequently enough, influx will be net greater than efflux over the long term and the general lithium levels in your compartments will go up and up. But anyone who comes to town to test your drinking water or your serum will find that levels in both are pretty low, unless they happen to show up on one of the very rare peak exposure days. So unless you did exhaustive testing or happened to be there on the right day, everything would look normal.

JPC: I totally vibe with the prediction that intake would be lognormally distributed. From a classic pharmacokinetic perspective, I would expect lognormally-distributed lithium boluses to actually be buffered by the fact that renal clearance eliminates lithium in proportion to its serum concentration–that is, it gets faster as lithium concentrations go up.

But I’m a big believer that you should shut up and calculate so I coded up a three compartment model (gut -> serum <-> tissue), made up some parameters* that seemed reasonable and gave the qualitative behavior I expected). Then either gave the model either 300 mg lithium carbonate three times a day (a low-ish dose of the the preparation given clinically), or three-times-a-day doses drawn from a lognormal distribution with two parameter sets (µ=1.5 and σ=1.5 or σ=2.5; this corresponds to a median dose of about 4.4 mg lithium carbonate in both cases, since the long tail doesn’t influence the median very much).

* k_gut->serum = 0.01 per minute

* k_serum->brain = 0.01 per minute

* k_brain->serum = 0.0025 per minute

* k_serum->urine = 0.001 per minute

* V_d,serum = 16 L

In my opinion, this gives us the following hypothesis: lognormally distributed doses of lithium with sufficient variability should create transient excursions of serum lithium into the therapeutic range.

Because this model includes that slow third compartment, we can also ask what the amount of lithium in that compartment is:

My interpretation of this is that the third compartment smooths the very spiky nature of the serum levels and, in that third compartment, you get nearly therapeutic levels of lithium in the third compartment for whole weeks (days ~35-40) after these spikes, especially if you get two spikes back to back. (Which it seems to me would be likely if you have, like, a coal ash spill or it’s wolfberry season or whatever.)

There clearly are a ton of limitations here: the parameters are made up by me, real kinetics are more like two slow compartments (this has one), lithium carbonate is a delayed preparation that almost certainly has different kinetics from food-based lithium, and I have no idea how realistic my lognormal parameters are, to name a few. However, I think the general principle holds: the slow compartment “smooths” the spikes, and so doing seems to be able to sustain highish [Li] even when the kidney is clearing it by feasting when Li is plentiful and retaining it during famine periods.

I’m not sure if this supports your hypothesis or not (do you need sustained brain [Li] above some threshold to get weight gain? I don’t think anyone knows…) but I thought the kinetics were interesting and best discussed with actual numbers and pictures than words. What do you guys think? Is this what you expected?

SMTM: Yes! Obviously the specifics of the dynamics matter a lot, but this seems to be a pretty clear demonstration of what we expected — that it’s theoretically possible to get therapeutic levels in the second compartment (serum) and sometimes in the third compartment (brain?), even if the median dose is much much lower than a therapeutic dose. 

And because of the lognormal distribution, most samples of food or serum would have low levels of lithium — you would have to do a pretty exhaustive search to have a good chance of finding any of the spikes. So if something like this is what’s happening, it would make sense that no one has noticed. 

It would be interesting to make a version of this model that also includes low-level constant exposure from drinking water (closer to 0.1 mg per day) and looks at dynamics over multiple years, getting an impression of what lifetime accumulation might look like, but that sounds like a project for another time.

Thyroid

JPC: Another thought is that thyroid concentrations may also matter. If lithium induces a slightly hypothyroid effect, people will gain weight that way too, since common (even classic) symptoms of hypothyroidism are weight gain and decreased activity. (It also proposes an immediate hypothesis [look at T3 vs TSH] and intervention [give people just a whiff of levothyroxine and see if it helps].) There’s also some thought that lithium maybe impacts thirst (full disclosure have not read this article except the abstract)?

SMTM: Also a good note, and yes, we do see signs of thyroid concentration. Some sort of thyroid sample would also be less invasive than a brain sample, right? 

JPC: Yes. We routinely biopsy thyroid under ultrasound guidance for the evaluation of thyroid nodules (i.e. malignant vs benign). These biopsies might be a source of tissue you could test for lithium, but I’m not sure. The pathologists may need all the tissue they get for the diagnosis, they may not. Doing it on healthy people might be hard because it’s expensive (you need a well-trained operator) and more importantly it’s not a risk free procedure: the thyroid is highly vascular and if you goof you can hit a blood vessel and “brisk bleeding into the neck” is a pretty bad problem (if rare).

That said, it is definitely less invasive than a brain biopsy, and actually safer than the very low bar of “less invasive than a brain biopsy” implies.

Clinical

SMTM: Do you have clinical experience with lithium? 

JPC: Minimal but non-zero. I had a couple of patients on lithium during my psychiatry rotation and I think one case of lithium toxicity on my toxicology rotation. I do know a lot of doctors, though, so I could ask around if they’re simple questions.

SMTM: Great! So, trace doses might be the whole story, but we’re also concerned about possible lithium accumulation in food (like we saw in the wolfberries in the Gila River Valley). We wonder if people are getting subclinical or even clinical doses from their food. We do plan to test for lithium in food, but it also occurred to us that a sign of this might be cases of undiagnosed lithium toxicity. 

Let’s make up some rough numbers for example. Let’s say that a clinical dose is 600,000 µg and lithium toxicity happens at 800,000 µg. Let’s also say that corn is the only major crop that concentrates lithium, and that corn products can contain up to 200,000 µg, though most contain less. Most of the time you eat fewer than four of these products a day and get a subclinical dose of something like 50,000 – 300,000 µg. But one day you eat five corn products that all happen to be high in lithium, and you suddenly get 1,000,000 µg. You’ve just had an overdose. If common foods concentrate lithium to a high enough level, this should happen, at least on occasion. 

If someone presents at the ER with vomiting, dizziness, and confusion, how many docs are going to suspect lithium toxicity, especially if the person isn’t on prescription lithium for bipolar? Same for tremor, ataxia, nystagmus, etc. We assume (?) no one is routinely checking the lithium blood levels of these patients for lithium, that no one would think to order this blood test. Even if they did, there’s a pretty narrow time window for blood levels detecting this spike, as far as we understand. 

So our question is something like, if normal people are occasionally presenting with lithium toxicity, would the medical system even notice? Or would these cases be misdiagnosed as heavy metal exposure / dementia / ischemic stroke / etc.? If so, is there any way we can follow up with this? Ask some ER docs to start ordering lithium tests in any mystery cases they see? Curious to know what you think, if this seems at all plausible or useful.

JPC: I have a close friend who is an ED doc! She and I talked about it and here’s our vibe:

With a presentation as nonspecific as vomiting, dizziness, and confusion, my impression is that most ED docs would be unlikely to check a lithium level, especially if the patient is well enough to say convincingly “no I didn’t take any pills and no I don’t take lithium.” At some point, you might send off a lithium level as a hail-Mary, but there are so many things that cause this that a very plausible story would be: patient comes to ED with nausea/vomiting, dizziness, and altered mental status. The ED gives maybe fluids, checks some basic labs, does an initial workup, and doesn’t find anything. Admits the patient. The next day the admitting team does some more stuff, checks some other things, and comes up empty. The patient gets better after maybe 24-48h, nobody ever thinks to check a lithium level, and since the patient is feeling better they’re discharged without ever knowing why.

Another version would go: patient is super sick, maybe their vomiting and diarrhea get them super dehydrated and give them an AKI (basically temporary kidney failure). People think “wow maybe it’s really bad gastritis or some kind of primary GI problem or something?” The patient is admitted to the ICU with some kind of gross electrolyte imbalance because they’re in kidney failure and they pooped out all their potassium, someone decides they need hemodialysis, and this clears the lithium. Again the patient gets better, and everyone is none the wiser.

Tremor, ataxia, nystagmus, etc. are more focal signs and even if someone doesn’t have a history of lithium use, and in this case our impression is that people would be more likely to check a lithium level. We also think it wouldn’t always happen. Even in classic presentations of lithium toxicity, sometimes people miss the diagnosis. (Emergency medicine is hard; people aren’t like routers where they blink the link light red when the motherboard is fried or power light goes orange if the AC is under voltage. Things are often vague and complicated and mysterious.)

Something you’d have to explain is how this isn’t happening CONSTANTLY to people with really borderline kidney function. Perhaps one explanation might be that acute lithium intoxication (i.e. not against a background of existing lithium therapy) generally presents late with the neuro stuff (or so I hear).

We think that this is plausible if it is relatively uncommon or almost always pretty mild. If we were having an epidemic of this kind of thing (like on the scale of the obesity epidemic) I think it would be weird that nobody has noticed. Unless of course it’s a pretty mild, self-resolving thing. Then, who knows! AFAIK still nobody really knows why sideaches happen—figuring it out just isn’t a priority.

On occasion, the medical-scientific community also has big misses. There’s an old line that “half of what you learn in medical school is false, you just don’t know which half.” We were convinced until 1982 that ulcers were caused by lifestyle and “too much acid”; turns out that’s completely wrong and actually it’s bacteria. I saw a paper recently that argued that pretty much all MS might be due to EBV infection (no idea if it’s any good).

I think you could theoretically “add on” a lithium level to anybody that’s getting a head CT with the indication being “altered mental status.” “Add on” just means that the lab will just take the blood they already have from the patient and run additional testing, if they have enough in the right kind of tube. The logic is that patients with new-onset, dramatic, and unexplained mental status changes often get head CTs to rule out a bleed or other intracranial badness, so a head CT ordered this way could be a sign that the ordering doc may be feeling stumped.

If you wanted to get fancy, you could try to come up with a lab signature of “nausea/vomiting/diarrhea of unclear origin” (maybe certain labs being ordered that look like a fishing expedition) and add on a lithium there as well. 

SMTM: Good point, but, isn’t it possible that it IS happening constantly to people with really borderline kidney function? The symptoms of loss of kidney function have some overlap with the symptoms of lithium intoxication, maybe people with reduced kidney function really do have this happen to one degree or another whenever they draw the short straw on dietary lithium exposure for the day. Lots of people have mysterious ailments that lead to symptoms like nausea and dizziness, seemingly at random.

Or we could look at it from the other angle — lithium can cause kidney damage, kidney disease is (very roughly) correlated with obesity at the state level, and as far as we can tell, rates of kidney disease are going up, right? Is it possible that many cases interpreted as chronic kidney disease are “actually” chronic lithium intoxication?

JPC: I guess it’s definitely possible. The “canonical” explanation to this would be that diabetes (which is obviously linked to obesity) destroys your kidneys. But, if it’s all correlated together as a vicious cycle (lithium → obesity → CKD → lithium) that’s kind of appealing too. I bet a lot is known about the obesity-diabetes-kidney disease link though and my bet without looking into it would be that there’s some problem with that hypothesis.

My thought here was that if people with marginal/no kidney function are getting mild cases, I would expect people with normal kidney function to be basically immune. Or, if people with normal kidney function get mild cases, people with marginal kidneys should get raging cases. This is because serum levels of stuff are related to the inverse of clearance. The classic example is creatinine, which is filtered by the kidney and used as a (rough) proxy for renal function.

SMTM: This is super fascinating/helpful. For a long time now we’ve been looking for a “silver bullet” on the lithium hypothesis — something which, if the hypothesis is correct, should be possible and would bring us from “plausible” to “pretty likely” or even “that’s probably what’s going on”. For a long time we thought the only silver bullet would be actually curing obesity in a sample population by making sure they weren’t consuming any lithium, but that’s a pretty tall order for a variety of reasons, not least because (as we’ve been discussing) the kinetics remain unclear! But recently we’ve realized there might be other silver bullets. One would be finding high levels of lithium in food products, but there are a lot of different kinds of foods out there, and since the levels are probably lognormal distributed you might need an exhaustive search. 

But now we think that finding people admitted to the ER with vague symptoms and high serum lithium, despite not taking it clinically, could be a silver bullet too. Even a single case study would be pretty compelling, and we could use any cases we found to try to narrow down which foods we should look at more closely. Or if we can’t find any of these cases, a study of lithium levels in thyroid or in bone could potentially be another silver bullet, especially if levels were correlated with BMI or something. 

JPC: I’m always hesitant to describe any single experiment as a silver bullet, but I agree that even a single case report, under the right conditions, of high serum lithium in someone not taking lithium would be pretty suspicious. You’d have to rule out foul play and primary/secondary gain (i.e. lying) but it would definitely be interesting. As far as finding lithium in bone or thyroid (of someone not taking lithium), I’d want to see some kind of evidence that it’s doing something, but again it’d definitely be supportive.

SMTM: Absolutely. We also don’t really believe in definitive experiments. The goal at this stage is to look for places where there might be evidence that could promote this idea from “plausible” to “likely”.

A Chemical Hunger – Part X: What to Do About It

[PART I – MYSTERIES]
[PART II – CURRENT THEORIES OF OBESITY ARE INADEQUATE]
[PART III – ENVIRONMENTAL CONTAMINANTS]
[INTERLUDE A – CICO KILLER, QU’EST-CE QUE C’EST?]
[PART IV – CRITERIA]
[PART V – LIVESTOCK ANTIBIOTICS]
[INTERLUDE B – THE NUTRIENT SLUDGE DIET]
[PART VI – PFAS]
[PART VII – LITHIUM]
[INTERLUDE C – HIGHLIGHTS FROM THE REDDIT COMMENTS]
[INTERLUDE D – GLYPHOSATE (AKA THE ACTIVE INGREDIENT IN ROUNDUP)]
[INTERLUDE E – BAD SEEDS]
[PART VIII – PARADOXICAL REACTIONS]
[PART IX – ANOREXIA IN ANIMALS]
[INTERLUDE F – DEMOGRAPHICS]
[INTERLUDE G – Li+]
[INTERLUDE H – WELL WELL WELL]

[INTERLUDE I – THE FATTEST CITIES IN THE LAND]

Assuming you take our main thesis seriously — that obesity is the result of environmental contaminants — what should you do about it?

Our suggestions are very prosaic: Be nice to yourself. Eat mostly what you want. Trust your instincts. 

Diet and exercise won’t cure obesity, but this is actually good news for diet and exercise. You don’t need to put the dream of losing weight on their shoulders, and you can focus on their actual benefits instead. You should focus on your diet — not to get thin, but to make sure that you have enough energy to do everything you want to do in life. This means eating enough and making sure you get what you need. You should exercise — not to slim down, but to gain strength and energy, and you shouldn’t get discouraged when you don’t drop 50 lbs fast.

Don’t be mean to fat people. If you’re fat, don’t be mean to yourself about it. Don’t be a dick.

Pancakes Good

And this doesn’t apply to most of our readers, of course, but just in general — we gotta stop spending money on circular nutrition research. It’s clearly not going anywhere. Other theories of obesity don’t engage with the observations that are out there about the obesity epidemic, and try to explain the wrong thing.

Most theories focus on the dynamics of individual weight loss, under the assumption that obesity is the result of the normal mechanics of eating, exercise, weight loss, and weight gain. But we think that the dynamics of individual weight loss have almost nothing to do with the real question, which is why obesity rates are so much higher now than they were in the 1970s, and the rest of human history. Individuals can gain or lose 15-20 lbs from their set point, but this is messing around within the range of control — we only care about the set point.

Let’s say it’s 50 °F outside. If your thermostat is set to 72 °F and you open the door, your house’s temperature will drop at first and then will go back up to the set point of 72 °F. If your thermostat is set to 110 °F and you open the door, your house’s temperature will drop at first and then will go back up to the set point of 110 °F (assuming your furnace is strong enough).

This is a standard feature of how homeostatic systems respond to major disturbances — the controlled value swings around for a bit until the system can get it back under control, and send it back to the set point. So all the diet and exercise studies we’ve done over the last 50 years have just been an exercise in who can create the biggest, most jarring disturbance — but the lipostat always finds a way to bring your weight back where it wants it.

So all these “punch the control system as hard as we can” studies don’t tell us anything about why the thermostat is set to 110 °F in the first place, which is what we’re really interested in.

Get It Outta Me

Bestselling nutrition books usually have this part where they tell you what you should do differently to lose weight and stay lean. Many of you are probably looking forward to us making a recommendation like this. We hate to buck the trend, but we don’t think there’s much you can do to keep from becoming obese, and not much you can do to drop pounds if you’re already overweight. 

We gotta emphasize just how pervasive the obesity epidemic really is. Some people do lose lots of weight on occasion, it’s true, but in pretty much every group of people everywhere in the world, obesity rates just go up, up, up. We’ll return to our favorite quote from The Lancet:

“Unlike other major causes of preventable death and disability, such as tobacco use, injuries, and infectious diseases, there are no exemplar populations in which the obesity epidemic has been reversed by public health measures.”

The nonprofit ourworldindata.org has data from the WHO covering obesity rates in almost every country in the world from 1975 to 2016. In every country in this dataset, the obesity rate either stayed the same or increased every single year from 1975 to 2016. There is not one example of obesity rates declining for even a single country in a single year. Countries like Japan and Vietnam are some of the leanest countries in the world (about 4% and 2% obese, respectively), but in this dataset at least, even these super-lean countries don’t see even a single year where their obesity rates decline.

We see the same trend even for smaller-scale data. The Institute for Health Metrics and Evaluation (IHME) has a dataset of county-level obesity data from 2001 to 2011, which is publicly available on their website. Using this we can look at obesity rates across the United States, and we can see how much obesity rates have changed in each county between 2001 and 2011. We see that between 2001 and 2011, obesity rates decreased in zero counties, stayed the same in zero counties, and increased in 3,143 out of 3,143 counties and county equivalents in the United States.

The smallest increase between 2001 and 2011 was in Eagle County, Colorado, where obesity rates went from 20.0% in 2001 to 21.5% in 2011, an increase of 1.5%. You’ll notice that this is Colorado once again, and it turns out that the five counties with the smallest increase from 2001 to 2011 are all in Colorado. Of the 25 counties with the smallest increase, 13 are in Colorado. The take-home here is that Colorado really is special. 

If we zoom in a little further on these data, we can find ONE case of obesity rates declining — they went from 22.7% in 2009 to 22.4% in 2011 in Fairfax City, Virginia, a drop of 0.3%. There were also two counties where rates stayed the same 2009-2011. But this is one county with rates going down, two staying the same, and 3,140 going up. If population-level reversals are this tiny and this rare, it’s hard to imagine that there is much an individual can do to change their own weight. 

But that said, here are a few ideas, approximately in order from least extreme to most extreme.

First off, there are a few things that won’t change how many contaminants you’re exposed to, but that may have an impact on your weight anyways.

1. The first is that you can put on more muscle mass. This won’t affect your weight as it appears on the scale, but it does often seem to affect people’s body composition. The lipostat pays attention to how much fat you have, but it also seems to pay some attention to how much you literally weigh (see these studies in mice, and this recent extension in humans). So if you gain muscle mass, you may lose fat mass. For advice on how to gain muscle mass, please see the internet.

2. — The second is that you could consider getting gastric bypass or a similar, related surgery. Our understanding is that these procedures are very effective at causing weight loss in many cases. However, they are pretty dangerous — this is still a surgical procedure, and so inherently comes with a risk of death and other serious complications. If you consider this option please take it very seriously, consult with your doctor, etc.

Many of you, however, are not just interested in weight loss, or are interested in weight loss along with reducing how many mystery chemicals you’re exposed to — “You stupid kids I don’t want to lose weight I want to get these contaminants out of my body!!!” So here’s a list of steps you could take to reduce your exposure and possibly lose weight, again approximately in order from least extreme to most extreme.

1. — The first thing you should consider is eating more whole foods and/or avoiding highly processed foods. This is pretty standard health advice — we think it’s relevant because it seems pretty clear that food products tend to pick up more contaminants with every step of transportation, packaging, and processing, so eating local, unpackaged, and unprocessed foods should reduce your exposure to most contaminants. 

2. — The second thing you can do is try to eat fewer animal products. Vegetarians and vegans do seem to be slightly leaner than average, but the real reason we recommend this is that we expect many contaminants will bioaccumulate, and so it’s likely that whatever the contaminant, animal products will generally contain more than plants will. So this may not help, but it’s a good bet. 

3. — The third thing is you can think about changing careers and switching to a leaner job. Career is a big source of variance in obesity rates, so if you have a job in a high-obesity profession like truck driver or mechanic, consider switching to a job in a low-obesity profession like teacher or surveyor. For a sense of what careers are high- and low-obesity, check out this paper about obesity by occupation in Washington State and this paper about obesity by occupation in US workers. If you are already in a pretty lean career, then ignore this one.

We think this goes double if you’re in a profession where you’re working with lithium grease directly, or even around lithium grease. Do what you can to stay away from the stuff.

4. — The fourth thing you can consider is changing where you live. The simplest is to change where you live locally — stay in the same area, but move to a different house or apartment. This one is tricky, and sort of a shot in the dark. How will you know if you are moving to a more or less-contaminated house? But if you suspect your house is high in contaminants, it might be worth moving. If you find specific contaminants especially concerning, you can try having your local water tested for them.

5. — A better option is to move to a leaner place altogether. If you’re in the United States, we recommend Colorado. Colorado is the leanest state, has exceptionally pure water sources, individual cities and counties in Colorado are extreme lean outliers, etc. Unbelievably, this comic exists: 

By Brian Crain for The Washington Post

If Colorado doesn’t suit you, you can move to some other state — Hawaii and Massachusetts are not far behind. To find your dream location, look at the CDC’s list of states, or one of the datasets of county-level data like this one or this one, and find a location with a lower rate of obesity than where you currently live. Or pick one of the places from the list of leanest communities in the US

6. — This may not be extreme enough. After all, even Colorado is more than 20% obese. So a more radical version of the same idea is moving to a leaner country altogether. 

If you live in the United States, the good news is that most countries are less obese than where you live now, even if you live in Colorado. Especially good choices seem to be Japan, South Korea, and Thailand, but there are many options — for the whole picture, check out the summary from Our World in Data

But don’t just take our word for it, listen to these happy customers. Like this person who lost weight over five months in Vietnam, this person who moved to Vietnam and lost 112 pounds in ten months, this person who lost about 4kg (9lbs) after about two months in Japan (and similar stories in the comments), this person who lost 5lbs on a two-week trip to Japan, or this person who lost 10lbs during a two-week trip to Japan, despite not keeping up with their exercise regimen. Most of these people attribute their weight loss to eating less and walking more, but you’ll also notice that most of them say it was easy to eat less and walk more, and that many of them report being surprised at how much weight they lost and how easily they lost it. 

We’ve also gotten a number of similar stories from commenters on the blog. First up is Julius, who said:

I currently live in Seattle but have moved around a lot. I’ve made 6 separate moves between places where I drank the tap water (mostly USA/UK/Hungary) and places I haven’t (South East Asia, India, Middle East). Whenever I’ve spent significant time in bottled water countries I lost weight (up to 50 lbs), and each time, save one 3 month stretch in Western Europe, I gained it back in tap water countries. I also lost weight for the first time in the States (20 lbs) this year around the time I switched to filtered water.

There’s also a similar story from Ross:

Very thought provoking and well researched piece. How about Japan? Very low rates of obesity. Similar issues with chemical residue. Anecdotally when I moved to Japan from the West I began to lose weight involuntarily, down to a BMI of 22. When I moved back to the West I regained weight. It’s a big rich country with plenty of processed, packaged food.

And a story from Tuck about their daughter:

Yes, my daughter is going to college in Japan. They have the “Freshmen 15 lbs” over there as well, except it’s the 15 lbs the foreigners lose when they go on a Japanese diet. Got a few panicked messages about “not having anything to wear”… LOL

So before you sign up for the gastric bypass, try spending a couple months in a lean country and see how it goes.

Studies

The question “what do we do about it” also includes the question “what research comes next?” Here’s what we’re thinking.

Correlational Studies

A lot of people’s first instincts when reading this work is to propose correlational studies. (We don’t necessarily mean a literal correlation, we just mean something that’s not a controlled experiment.) But we think that correlational studies are the wrong way to go at this point.

The first reason is statistical. We covered this in Part IV but it bears repeating. Because most of the modern variation in obesity is genetic, the apparent effect of any contaminant will be quite small, probably no larger than r = 0.50 and maybe a lot smaller. In any study we could run, the range of the variable would probably be restricted, and when the range of a variable is restricted, the correlation always ends up looking smaller than it really is. Some people have proposed we do animal studies for more control — but this is also a bad choice statistically, since the obesity effects in animals seem to be smaller than the effects for humans.

The combination of these problems means that any correlational study would be searching for a pretty small effect, and that means you would need a huge sample size to even have a good chance of finding a potential relationship. So “run a quick correlational study” starts looking like “find a way to fund and organize a study with 1,000 mice”. While we love mice, this seems like an awful lot of them. And even if we have enough statistical power that we have a 90% chance to detect a relationship, that still means we have a 10% chance of missing the relationship altogether. We don’t love those odds. 

Second, A Chemical Hunger already documents a lot of correlational evidence for contaminants in general, and for a few contaminants in particular, especially lithium. If you already find this evidence compelling, it’s hard to imagine that one more piece of correlational evidence will do anything for you. And if you don’t find our review convincing, it’s hard to imagine that another piece of correlational evidence will change your mind.

The contamination theory of obesity has to be possible, in the sense that we know chemicals can cause weight gain and we know various chemicals are in the environment. We hope we’ve also convinced you that it’s plausible. Now we want to figure out, is it true? More correlational evidence isn’t going to get us there.

So overall we recommend going right for the jugular. If this theory is correct, then we have a good shot at doing what we really want to do — actually curing obesity — and no result could be more convincing than that. 

Experiments

So in general, we approve of the idea of doing experiments to just cure obesity straight up.

Normally in public health it’s hard to do this kind of experiment, because it’s unethical to expose people to dangerous chemicals. Back when they were trying to figure out if cigarettes cause cancer, they didn’t do any studies where they assigned people to smoke 3 packs a day. But there’s nothing unethical about removing a contaminant from the environment, so we like that approach. 

We call these experiments, and they are, but in many cases we can actually cheat a little by not bothering to include a control group. People almost never spontaneously stop being obese, so we can just use the general obesity rate in the population as our control group. 

Generally speaking, there are two approaches. “Broad-spectrum” experiments take the overall contaminant theory seriously, and just try to reduce contaminant exposure generally, without committing to any specific contaminant. “Targeted” experiments go after one contaminant in particular, and see if controlling levels of that contaminant alone can lead to weight loss.

These have clear trade-offs. The broad-spectrum experiments are more likely to work and require less experimental control, but if they cure obesity, they don’t tell us what contaminant is responsible (curing obesity would still be pretty cool tho). The targeted experiments are less likely to work because we might go after the wrong contaminant, or we might fuck up our experimental control and let some contamination through — but if they DO work, then we have strong evidence that we’ve found the contaminant that’s responsible.

For all of these studies, the big hurdle is that we don’t know how quickly obesity can be reversed, even under the best circumstances. It might also vary a lot for different people — we have no idea. So if we try any of these experiments, we need to run them for several months at the very least, just to get a good idea of whether or not it’s working. Maybe if we’re lucky we’ll find out you can cure obesity in 2 weeks; but 3 months, 6 months, or even 1 year seems more plausible. 

Below, we propose a few basic ideas for experiments. These aren’t exhaustive — as we do more research, we may come up with new and better ways to try to cure obesity. But they seem like an ok place to start.

Broad-Spectrum Experiments

Slime Mold Time Mold’s Excellent Adventure

The idea is simple. Some places, like Colorado, are pretty lean relative to everywhere else. We think that’s because those places are less contaminated. So we find some people who are obese, and pay for them all to take a year-long vacation to Boulder, Colorado, and see if they lose any weight. 

For better effect, go a step further and send them to one of the leanest countries in the world instead. Vietnam seems to be the leanest country in the world right now, at only about 2% obese, and rent is pretty cheap there, so that would be a good option. If you want to stay in heavily industrialized nations, Japan is a good alternative; if you want to stay in the English-speaking world, maybe the Philippines. There are lots of good places to choose from.

For full effect, you would want your participants to eat the local food and drink the local water as much as possible. If they’re eating American food and drinking American beer, then you’re right back where you started.

(If you know of any study abroad or similar programs that we could piggyback on, please let us know!)

Throw Water Filters at the Problem and See What Happens

This is a broad-spectrum version of a targeted idea, below. The basic idea is simple. Contaminants might be in the water supply; filters get lots of stuff out of water; people drink water. So in this study, we find a bunch of people who are overweight or obese, send them the strongest/best water filters we can afford, and see if they lose any weight over the next several months. 

For even more effect, send the filters to people who live in the most obese states, or even target some of the most obese communities directly.

This really is not a precision instrument — filters don’t get everything out of water, and water might not even be your main source of contaminants. Maybe your food or your carpets are the bigger problem. But if losing weight were as simple as throwing a water filter at the problem, that would be pretty exciting, and we would want to know.

Targeted Experiments

Right now lithium is our top suspect, so we’re using lithium as our go-to example in all of these experiments. But if it turns out that lithium isn’t a good match, any of these experiments could be retrofitted to target some other contaminant instead. 

To use a targeted approach, we need to be able to figure out how much exposure people are getting, and we need to know what we can do to reduce that exposure. So there are a few pre-experiment projects we need to do first.

To begin with, we need to figure out which water filters (if any!) remove lithium from drinking water. If we can find a filter that works, this will let us make sure any water source is lithium-free.

In addition, we’re worried that lithium might accumulate in food, so we need to do another study where we look at as many different types of food as we can and try to figure out if there are high levels of lithium in any of the stuff we’re all eating. Without this, any study will be hopelessly complicated because we won’t be able to control for the lithium in your food. But if we figure out what crops (if any) are concentrating lithium, maybe we can figure out a way to feed people a low-lithium diet.

Targeted Water Filters

Assuming we can find a water filter that does the job, we could do a pretty straightforward study where we send people a water filter that takes lithium out of their water, and see if they lose weight over a couple months.

For maximum effect, we would also want to make sure they weren’t getting any lithium from their food, which is why we want to do a study on how much lithium is in the food supply. It’s not clear how easy this would be — we might have to curate food sources and provide people with all their meals as well, which would make this study a hundred times more complicated.

There are a couple other things we could do to improve this study. We could focus on sending water filters to people in the most obese parts of the country, or to places where we already know the water is contaminated with lithium.

We could test the amount of lithium in people’s blood, urine, and/or saliva as they use the filter, see if it goes down, and see if the decrease in lithium in their body tracks on to weight loss. Assuming people did lose weight, this would be important because it might help us figure out more about the mechanism of lithium leaving the body. Some people will probably clear lithium faster than others, and if lithium causes obesity, we would want to be able to figure out how to help people clear it from their body as fast as possible. 

We could also do a slightly bigger study, where we go to one of the fattest places in the US and install a bunch of whole-home water filtration systems for a couple randomly selected families who are overweight or obese. This would be more expensive but it would have some perks. If it turns out that showering in lithium-tainted water is really the active ingredient, and not just drinking it, then a whole-home water filtration system would take care of that. 

There’s also a small chance that there’s just no filter on the market that can get lithium out of drinking water. Or maybe distillation works, but the cost is prohibitive for a whole-home system. In that case, we could rent a few water tanker trucks, fill them with water we know is low in lithium (we’ll import it from Colorado if we have to!), and take them to a cul-de-sac in one of the most obese communities in the US. If we can find a neighborhood who’d sign up for this, we could switch their houses’ water supplies over to our tanker trucks for a few months, bringing in new water as needed, and see if that did anything for their health. 

Amish Obesity

This piece from the LA Times is pretty bad, but it tells an interesting story. In part of Ontario, Canada, a group of Old Order Amish have “stunningly low obesity levels, despite a diet high in fat, calories and refined sugar.” The figure they quote is an obesity rate of only 4%. But about 200 miles south, the Amish in Holmes County, Ohio have obesity rates similar to the rest of the population, closer to 30% obese.

These two groups should be genetically similar. Both groups grow most of their own food. Both of them have pretty similar lifestyles — despite what the LA Times piece and this related article say, even if “only” 40% of the Amish in Ohio do hard farm labor, their lives are still more like the Amish in Ontario than the non-Amish in Holmes Country. 

This makes them almost a perfect comparison. Why are the Amish in Ohio so much more obese than the Amish in Ontario? If the contamination hypothesis is correct, then we should be able to look at the local environments of these two communities and find more contamination (of one sort or another) in Ohio than in Ontario. 

Because both groups grow most of their own food (we think?), we don’t need to worry about the influence of food imported from elsewhere — whatever contaminants are in their water will also be in their plants, and they won’t be bringing in contaminated food from outside. This makes this situation a much more controlled environment to study our hypothesis.

If lithium is the contaminant that causes obesity, we might expect to see deeper wells in Ohio than in Ontario. Information about the Amish is hard to find on the internet, for obvious reasons, but we have found some information that suggests that the Amish in America do use drilled wells, some of which may be relatively recent. We can’t find anything about the wells used by the Amish in Ontario — but it would be interesting if they were still using older, shallower wells for their water.

Another thing we might expect to see, if lithium is to blame, is evidence of some kind of fossil fuel activity in Ohio and not in Ontario. Well, in our last post we did review evidence for fossil fuel contamination in a number of places in Ohio. And when we were looking for documentation on water wells in Amish Ohio, we came across articles like Fracking on Amish Land (in Ohio), Energy Companies Take Advantage of the Amish Prohibition on Lawsuits (in Ohio), this excerpt about natural gas wells (in Pennsylvania), and Tradition, temptation as Amish debate fracking (in Pennsylvania, but mostly in Ohio). 

Ontario has its own problems, including thousands of abandoned gas wells, but very few of them appear to be on Amish land. Zoom in on the towns of Milverton, Millbank, Newton, Linwood, and Atwood on that map, and you’ll see that there are almost no petroleum wells around these Amish communities. And unlike in Ohio, we haven’t found any news stories about recent drilling or fracking on Amish land in Ontario. 

Or we could just go test the water. It’s a simple question, how much lithium is in the water in each place, and testing for other contaminants might not be a bad idea either. If we find similar levels of lithium in both places, and there are no complicating factors like imported food, that would be a strike against lithium as an explanation. But if there’s more lithium in the food and water in Ohio than in Ontario, that would be quite a mark in favor of the lithium hypothesis. Assuming they were interested, we could then work with the Amish in Ohio to try to get the lithium (or whatever) out of their water, and see if that reduced their rates of obesity. 

We don’t expect that we have many Amish readers, but if you know of a good way to get in contact with the Amish in either of these locations, we’d be interested in talking to them!  

Research Advising

There are also a few ideas we have that we won’t be pursuing ourselves, but if someone else (or a small team) wants to go after them, we would be happy to advise.

Taking lithium out of the water supply as a whole would be pretty hard, so it’s not usually an option. But it might be an option for countries that get most of their drinking water from desalination. You could run this as an experiment — one desalination plant uses lithium-free brine while another continues with the normal procedure — but you wouldn’t have to. In this case, there’s no need for a control group. If Saudi Arabia or Kuwait changed their desalination process so that no lithium ended up in their water, and saw their obesity rate fall 10% over the next five years, that would be evidence enough. Or you could do a version of this study with some other relevant group, e.g. seafarers drinking desalinated water as suggested by commenter ugoglen. So if anyone is able to do something like this, we would be interested in being involved.

In our post on PFAS, we did a small amount of regression modeling using data from The National Health and Nutrition Examination Survey (NHANES) and found evidence of a relationship between BMI and certain PFAS in the data for 1999-200, 2003-2004, and 2005-2006. This finding is very suggestive, but we only tested some very simple models, and we only looked at three of the datasets that are available. We think that a bigger analysis could be very illuminating, but model fitting isn’t our specialty. We would love to work with a data scientist or statistician with more model fitting experience, however, to conduct a more complete analysis. So if you have those skills and you’re interested, please let us know

We’re still pretty interested in the all-potato diet. So far all we have are anecdotes, but the anecdotes are pretty compelling. Chris Voigt famously vowed to eat nothing but 20 plain potatoes (and a small amount of cooking oil) and lost 21 pounds over 60 days, without feeling very hungry. There’s also Andrew Taylor of Australia, who lost 114 lbs over a year of eating nothing but potatoes and reports feeling “totally amazing”. Last we heard he’s still doing pretty well. Magician Penn Jillette lost over 100 lbs using a strategy that started with two weeks of a potato-only diet (h/t reader pie_flavor), and seems to be keeping it off. This also inspired at least one copycat attempt from a couple who have jointly lost over 220 lbs starting with two weeks of an all-potato diet.

There’s also this comment from u/DovesOfWar on reddit:

To complement the potatoes anecdote, at some point to save money and time I ate almost nothing but potatoes, onions and butter and I lost like 60 pounds. I stopped because everyone thought I was starving (despite not being hungry) and I chugged it off to extreme lazyness/depression (despite not being sad) so I stopped doing that and never connected it to my diet, but what I should have done is write a fad book on the diet and solve the money problem that way. I’m back to a normal healthy 29 BMI now and still relatively poor, so I see I interpreted the experiment completely wrong and now my life sucks.

Based on those examples, you can see why we’re interested. It seems pretty low-cost (potatoes are cheap) and low-risk (if you feel bad, you can stop eating potatoes). If someone wants to organize a potato-centered weight-loss study, or if people just want to get together and try it for themselves, we’d be happy to advise. You can coordinate on the subreddit u/pondgrass set up over at r/spudbud if you like, though so far there doesn’t seem to be much activity.

We’re also interested in the effect of alkali metal ions, especially potassium. Lithium, currently our prime suspect, is an alkali metal ion that appears to affect the brain. Other alkali metal ions like sodium and potassium also play an important role in the brain, and there’s evidence that these ions may compete with each other, or at least interact, in interesting ways (see also here, here, and here). If lithium causes obesity, it may do so by messing with sodium or potassium signaling (or maybe calcium) in the brain, so changing the amount of these ions you consume, or their ratios, might help stop it. 

This is supported by some hints that potassium consumption is related to successful weight loss. Potatoes are high in potassium, so if the all-potato diet really does work, that might be part of the mechanism.

You can easily get sodium from table salt, and you can get potassium from potassium salts like this one or this one. We’ve tried them, and we find them a little gross, but to some people they taste just like regular salt. If that’s no good, there are always dietary sources like potatoes.

So trying various forms of alkali-metal diets — high-K+, high-K+/low-Na+, high-K+/high-Na+, high-K+/low-Ca2+, etc. — seems pretty easy and might prove interesting. As before, if someone wants to organize a community study around this angle, or if people want to try it for themselves, we’d be happy to advise. These salts are pretty safe, and not prescription medications, but they’re not quite as basic as potatoes — before you try seriously changing your sodium or potassium intake, please talk with your doctor.

Also, how about lithium grease? These greases are basically the perfect slow-release form of lithium, which make them kind of concerning. Mechanics work with lithium grease and are relatively obese. But there are alternative kinds of greases that don’t use lithium, and sometimes companies intentionally switch what kind of grease they use. If a company switched out lithium grease for some other grease in one of their factories, we could compare the weights of workers at that factory to workers at other factories, and see if there was any weight loss over the next few years. And what happens when mechanics who use lithium grease every day switch to a new job? What happens if they get promoted to a desk job? What happens when they retire? If you know a group of mechanics or some other group that works with lithium grease and might be interested, please let us know!

We’re also interested in advising original ideas. We love it when you send us ideas we never would have come up with ourselves. So if you have some great idea — a review of a contaminant we didn’t cover, another idea for a related study, relevant anecdotes that might inspire something, etc. — let us know. If we like it, we’ll do what we can to help — advise you, promote it, try to help you get funding, whatever.


This is the end of A Chemical Hunger. We will still write more about obesity, and probably more about contamination, but this is the end of the series. Thank you for reading, commenting, sharing, contributing, questioning, challenging, and yes, even disputing! We’ve learned a lot from your comments and questions — and we hope you’ve learned something from reading!

Even if you still don’t find our hypothesis convincing, thank you for reading the series all the way to the end! We think it’s great that you were willing to give our wacky idea the time of day. This kind of exploration is essential, even if some of the theories turn out to be a little silly. And even if our theory is totally wrong, someday someone will figure out the answer to this thing, and we’ll send the global obesity rate back down to 2%.

As we mentioned, we want to conduct some research to follow up on the book-length literature review you just finished reading. Our near-term goal is to better understand how people get exposed to contaminants, especially lithium, so we can give advice on how to avoid exposure. Our medium-term goal is to figure out what causes obesity, probably by trying to cure it in a sample population. Our long-term goal is to try to cure it everywhere. That would be pretty cool.

If you’re interested in supporting this research, you can become a patron on patreon, or contact us if you want to help fund a larger project.

In conclusion: Be excellent to each other. Party on, dudes.


A Chemical Hunger – Interlude I: The Fattest Cities in the Land

[PART I – MYSTERIES]
[PART II – CURRENT THEORIES OF OBESITY ARE INADEQUATE]
[PART III – ENVIRONMENTAL CONTAMINANTS]
[INTERLUDE A – CICO KILLER, QU’EST-CE QUE C’EST?]
[PART IV – CRITERIA]
[PART V – LIVESTOCK ANTIBIOTICS]
[INTERLUDE B – THE NUTRIENT SLUDGE DIET]
[PART VI – PFAS]
[PART VII – LITHIUM]
[INTERLUDE C – HIGHLIGHTS FROM THE REDDIT COMMENTS]
[INTERLUDE D – GLYPHOSATE (AKA THE ACTIVE INGREDIENT IN ROUNDUP)]
[INTERLUDE E – BAD SEEDS]
[PART VIII – PARADOXICAL REACTIONS]
[PART IX – ANOREXIA IN ANIMALS]
[INTERLUDE F – DEMOGRAPHICS]
[INTERLUDE G – Li+]
[INTERLUDE H – WELL WELL WELL]

It’s surprisingly hard to tell what the fattest and leanest American cities are. 

We can’t find an official source — the closest we can find is this Gallup report from 2014 that lists some of the most and least obese US communities, out of 189 “Metropolitan Statistical Areas”. They offer a top 10 most obese list and a top 10 least obese list both for all US communities, and for “Major US communities”, which are communities with populations above 1 million. This isn’t perfect, but Gallup is pretty reliable, so for now let’s take it seriously. 

We’ve already seen that communities in Colorado get most of their water from pure snowmelt and are exceptionally lean. It would be interesting to see if other communities on the leanest list seem to have exceptionally pure local water, and if there’s any evidence of lithium (or other contaminants) in the drinking water of the communities on the most obese list.

There are 38 communities on Gallup’s lists. We’re going to hit them all, so to keep this from spiraling out of control, we’ll focus on communities where we can find actual measurements of how much lithium is in their water. For everywhere else, we’ll give a decent overview, and let you know if we can make educated guesses, but keep the speculation to a minimum.

Because “major communities” is kind of vague and long-winded, we’ll be calling the communities on that list “cities”.

Lithium isn’t commonly recorded in water quality assessments, so for most of these communities, no direct measurements of lithium in drinking water were available — so we use other local measurements, like levels in nearby groundwater, instead. If you find actual tap water lithium measurements for any communities we missed, please let us know!

Before we start, let’s orient you to the lithium measurements we’ll be looking at: 

  • 2 ng/mL is low, about how much was in the water in 1964 
  • 10 ng/mL starts to seem like a concern, and is the EPA’s threshold for drinking water
  • 40 ng/mL is the EPA’s threshold for groundwater contamination at power plants
  • 100+ ng/mL is a lot, about how much the Pima were exposed to

Least Obese

Gallup offers these lists for the least obese communities in the United States:

Boulder, CO – #1 Leanest Community

In our last post, we discussed how Colorado gets almost all its drinking water from snowmelt, so it’s no surprise that three of the ten leanest communities are from Colorado.

Even for Colorado, Boulder is a crazy outlier, at only 12.4% obese. Boulder is a college town, so age may be having some effect here, but nearby Fort Collins is also a college town, and their obesity rate is 18.2%. So is Boulder’s water source separate? Is it somehow crazy-extra-pure? Strangely enough, the answer on both counts may be “yes”. Boulder gets its water from a different company than Denver does, and its water generally comes from much closer by

Naples-Marco Island, FL  – #2 Leanest Community

Water in Naples “is drawn from the Lower Tamiami Aquifer via 51 wells.” We found this document suggesting that in 2008 the city of Naples was contracting analysis including lithium for the City Utilities Department. But we haven’t been able to find any actual lithium measurements either for the city or the Lower Tamiami Aquifer, and no other indications of lithium contamination in the area.

Fort Collins-Loveland, CO – #3 Leanest Community

Another Colorado town, Fort Collins’ appearance on this list is unsurprising. The water in this town comes from “the Upper Cache la Poudre River and Horsetooth Reservoir.” We can’t find any lithium measurements for these sources, but they appear to be snowmelt sources similar to other surface waters in Colorado. Their water appears to be at least partially provided by a company called Northern Water, which also provides water to Boulder.

Charlottesville, VA – #4 Leanest Community

Charlottesville gets its water from South Fork Rivanna River Reservoir and Ragged Mountain Reservoir. These collect water from the surrounding mountains, and the watershed appears to be about 70% forested. We haven’t been able to find any lithium measurements related to Charlottesville or from either of the reservoirs.

Bellingham, WA – #5 Leanest Community

The City of Bellingham gets its water from Lake Whatcom. According to this report, lithium measurements for Lake Whatcom should be available in a CSV called lakemetalstoc.csv on this page. All the other data files are indeed there, but lakemetalstoc.csv is not, and we can’t find it anywhere else. We fired up the Wayback Machine and found a version of the page from 2011, which helpfully tells us that “metals, TOC … are not posted in electronic format, but are included in the printed copies of the annual reports.” Ok then.

Denver, CO – #6 Leanest Community, #1 Leanest City

In our last post we reviewed how Denver gets its water from pure snowmelt off the Rocky Mountains, but we hadn’t tracked down any actual lithium measurements. Happily, we can now add something to that previous finding. This report from Denver Water in 2010 lists lithium as one of the “Contaminants Not Found In Denver’s Drinking Water” — “either below the reporting limit or the average result was less than the reporting limit.” Same for this report from 2016, this report from 2017, etc. etc.

San Diego-Carlsbad-San Marcos, CA – #7 Leanest Community, #2 Leanest City

In San Diego, 85-90% of city drinking water is “imported from Northern California and the Colorado River”. We haven’t been able to find any measurements of lithium in San Diego tap water, but this report from 2018 says that wastewater at the San Diego North City Water Reclamation Plant ranged from 12 ng/mL to 48 ng/mL in 2018. Similar numbers are found in this report about wastewater at the South Bay Water Reclamation Plant from 2011. In fact it looks like there are a LOT of wastewater reports, but we’ll stop there. 

This doesn’t tell us how much is in San Diego drinking water exactly, but wastewater almost certainly contains no less lithium than the tap water it started as, so this suggests that the lithium concentration in San Diego drinking water is somewhere below 12-48 ng/mL.  

San Jose-Sunnyvale-Santa Clara, CA – #8 Leanest Community, #3 Leanest City

For San Jose-Sunnyvale-Santa Clara, we’ve been able to find some lithium measurements for the tap water itself. This report from 2017 finds a range of “not detected” to 25 ng/mL in the water served to San Jose-Sunnyvale-Santa Clara, with a median level of 5.60 ng/mL. This is pretty low. The numbers in this report from 2018 are even lower — a range of “<5” to 6.2 ng/mL and an average of “<5”. There’s also this other report from 2018 finding a range from “not detected” to 8.1 ng/mL, with a median of 3 ng/mL.

Bridgeport-Stamford-Norwalk, CT – #9 Leanest Community

Bridgeport and surrounding towns appear to get their water from “mostly surface water drawn from a system of eight reservoirs (Aspetuck, Easton Lake, Far Mill, Hemlocks, Means Brook, Saugatuck, Trap Falls and West Pequonnock).” 

We haven’t been able to find any lithium measurements for the city or for any of these reservoirs, but we do want to note that at least some of these reservoirs were in use back in 1964, and back then they all contained less than 0.50 ng/mL lithium, a truly miniscule amount. There isn’t any sign that they’ve been exposed to lithium since then (no nearby coal power plants, no petroleum mining in Connecticut at all), so lithium levels in these reservoirs may still be that low. There is a coal power plant in Bridgeport itself, but while it might be contaminating the harbor, the city isn’t drinking that water.

Barnstable Town, MA – #10 Leanest Community

Barnstable Town is a small town on Cape Cod. Like every part of Cape Cod, Barnstable relies on the Cape Cod Aquifer for its groundwater. We managed to find this report from 1988 where some hydrologists injected bromide and lithium into the Cape Cod Aquifer to test their transport in the aquifer over time. To do this they needed background readings of lithium levels so that they could track their own sample, and they found that the background concentration of lithium in the aquifer was “below the detection limit”, or something less than 10 ng/mL. Unfortunately their analysis wasn’t very sensitive so we don’t know how much less.

San Francisco-Oakland-Fremont, CA – #4 Leanest City

You may remember from above that the water in San Jose-Sunnyvale-Santa Clara contains very little lithium. This water system gets about 20% of its water from Hetch Hetchy Reservoir, a reservoir located in Yosemite National Park, and this is relevant to San Francisco because Hetch Hetchy supplies San Francisco with 85% of its drinking water.

We can’t find any lithium measurements for Hetch Hetchy itself (not even in the 1964 data!), but Hetch Hetchy water largely comes from snowmelt, and if it’s providing San Jose-Sunnyvale-Santa Clara with 20% of its drinking water, Hetch Hetchy can’t be holding much lithium. For this reason, we suspect that the lithium levels in San Francisco drinking water are probably low as well. 

Boston-Cambridge-Quincy, MA – #5 Leanest City

Boston and most of the surrounding towns get their water from the Quabbin Reservoir in western Massachusetts. Again we can’t find any modern measurements, but Boston was drawing from the Quabbin in 1964, and in the 1964 data we see that water sourced from the Quabbin contained only 0.21 ng/mL lithium. Massachusetts hasn’t drilled any new oil wells right next to the Quabbin or anything in the past 60 years, so while we’d love to see some modern tests to confirm this, there’s no reason to expect lithium levels in the Quabbin to be much higher today.

Miami-Fort Lauderdale-Pompano Beach, FL – #6 Leanest City

In Miami, “water supply comes from the Biscayne Aquifer, the County’s primary drinking water source.” In the USGS well water dataset, there are 53 measurements from the Biscayne Aquifer, all from either 2010 or 2016. The average level of lithium in these samples is 1.26 ng/mL, the median is 1.11 ng/mL, the maximum level is a mere 2.60 ng/mL, and in a full 24 of these 53 samples, the levels of lithium were below the detectable threshold. 

This aquifer is such an exceptional case, they mention it by name in the abstract: “no public supply wells in the Biscayne aquifer (southern Florida) exceeded either threshold, and the highest concentration in that aquifer was 2.6 [ng/mL].”

Washington-Arlington-Alexandria, DC-VA-MD-WV – #7 Leanest City

Water for DC comes from the Potomac River. DC Water provides detailed water quality reports online, all the way up through 2021, and in the report for 2021, the average level of lithium in DC water was 2 ng/mL and the range was 1 to 2 ng/mL. Now, the Gallup numbers are from 2014 — well, in the report from 2014, the average level of lithium in DC water was 2.1 ng/mL and the range was 1.2 to 4.0 ng/mL. Case closed.

Minneapolis-St. Paul-Bloomington, MN-WI – #8 Leanest City

Minneapolis and St. Paul both draw much of their water from the Mississippi River. This may not seem like a good idea, but they’re so close to the headwaters that the Mississippi hasn’t really had a chance to pick up all that much stuff on its way to the ocean. Unfortunately we haven’t been able to find any lithium measurements from either city. 

Los Angeles-Long Beach-Santa Ana, CA – #9 Leanest City

Drinking water in LA comes from a couple different sources — the Owens River, Northern California and the Colorado River, and groundwater. Again we haven’t been able to find actual measurements, but we can note that much of this water is piped hundreds of miles from distant mountain ranges (see figure below).

We also found this news report from 2015 about “a massive natural gas leak at Aliso Canyon” that appears to have contaminated tap water in the Los Angeles water system. This includes a picture of lithium measurements from what appears to be a powerpoint slide deck, indicating average lithium levels in LA drinking water of 65.4 ng/mL. This is pretty high, but of course the gas leak occurred in 2015 and the Gallup obesity numbers are from 2014. 

The article also includes a statement from a Los Angeles Department of Water and Power spokesperson saying that “the agency doesn’t test for lithium and is not required to.” This suggests that there are probably no official lithium records to be found for the city, so it’s no surprise we weren’t able to find anything.

Seattle-Tacoma-Bellevue, WA – #10 Leanest City

Seattle gets most of its drinking water from two large watersheds in “mountain forests” to the east. The only lithium coming out of Seattle is a Nirvana byproduct. Ok but seriously, we couldn’t find anything.

Most Obese

Next, let’s look at the most obese communities.

Gallup sez:

Huntington-Ashland, WV-KY-OH – #1 Most Obese Community

Let’s start at the top. Huntington-Ashland WV-KY-OH is the #1 most obese community on Gallup’s list and appears to get all of its drinking water from the Ohio River. We can’t find any measurements for lithium in the actual river water, but we found this report outlining several nearby power plants that show coal-ash contamination in groundwater. 

Coal-ash contamination is relevant because fossil fuels and their byproducts are often extremely rich sources of lithium. This includes coal ash as well as oilfield brines and other “produced water” from petroleum extraction.

The first power plant we’ll look at is the Mountaineer Plant in New Haven, WV, which is about 70 miles directly upstream of Huntington-Ashland and was found to be contaminated with lithium in 2019. These reports are a little tricky to read, but if you flip through the plant’s own groundwater monitoring reports, it looks like the levels in the plant’s groundwater monitoring wells often exceeded 40 ng/mL and sometimes exceeded 100 ng/mL.

The Mountaineer Plant, the locations of the plant’s groundwater monitoring wells, and the Ohio River

Just a few miles downstream on the Ohio River sits the Gavin Power Plant. This plant is split up into three sections on the groundwater testing reports. There isn’t much lithium in the Bottom Ash Pond, but in the Residual Waste Landfill, several wells are heavily contaminated, and the highest level recorded was 249 ng/mL. In the Fly Ash Reservoir, many testing wells contain more than 100 ng/mL lithium, the highest level detected being 702 ng/mL.

Just 1.6 more miles down the Ohio River, in the direction of Huntington-Ashland, sits Kyger Creek Station. Many of the groundwater monitoring wells at this plant also show high concentrations of lithium, including levels as high as 480 ng/mL.

How many other places in America are right downstream from three coal power plants? This seems too crazy to be a coincidence. If lithium causes obesity, then it’s no wonder that Huntington-Ashland is #1 in the nation.

McAllen-Edinburg-Mission, TX – #2 Most Obese Community

McAllen, Texas gets its water from the Rio Grande. This one is almost too easy — the USGS well water report says, “the highest concentrations [of lithium] were in the High Plains, Rio Grande, Stream-valley aquifers and Basin and Range basin fill aquifers of the West.”

We have access to the raw data, and we can confirm that the Rio Grande aquifer had the second-highest levels of lithium of all the principal aquifers in the dataset. In Texas, there were only 9 measurements from this aquifer, but the level of lithium was pretty high in all of them — the median was 59.7 ng/mL, the mean 64.83 ng/mL, and the range was 20.8 ng/mL to 115.0 ng/mL.

Hagerstown-Martinsburg, MD-WV – #3 Most Obese Community

Hagerstown-Martinsburg MD-WV is interesting because Hagerstown is in Washington County, MD. By coincidence, one of the few good sources we have for levels of lithium in the 1970s is a 1976 paper looking at 384 drinking water samples from Washington County. Back in 1976 they found very low levels of lithium in the well water in Washington County, with 90% of samples containing less than 10 ng/mL and the highest level being only 32 ng/mL.

Unfortunately we can’t find good modern data for lithium levels in Hagerstown or Washington County as a whole. As far as we can tell from their water quality reports, Washington County doesn’t test for lithium at all. Numbers from the state as a whole do seem to have increased since 1976, but the state’s trends don’t tell us all that much about this one town.

We can also mention that Martinsburg, the other half of Hagerstown-Martinsburg MD-WV, is notable for being exceptionally contaminated with PFAS, even for West Virginia. According to this source it looks like the USGS is planning to test West Virginia for lithium too, keep an eye on this one! 

Yakima, WA – #4 Most Obese Community

Most of Yakima’s drinking water comes from the Naches River, though this is supplemented by 4 wells that draw from the Ellensburg Aquifer. This USGS report from 2013 suggests that well water in the area is pretty low in lithium, but most of their water doesn’t come from the wells. Unfortunately we haven’t been able to find any measurements at all for tap water in Yakima or for the Naches River in general. There is this 1987 USGS report that includes measurements of lithium in Yakima River Basin streambed sediment, if anyone wants to try to make sense of that.

There’s also a possible mining connection — the Bumping Lake Mineral Spring Calcium Mine is upstream of Yakima and has lithium listed as one commodity of interest. Even so, it’s not clear whether this is relevant.  

Little Rock-N Little Rock-Conway, AR – #5 Most Obese Community

Drinking water in Little Rock comes from two surface water sources, Lake Winona and Lake Maumelle, which supply Jackson Reservoir. Drinking water in Conway comes from nearby Brewer Lake. Unfortunately we have not been able to find any lithium measurements from any of these bodies of water.

Now, Arkansas does sit on a huge amount of lithium in the form of the Smackover Formation, which is being mined by Standard Lithium Ltd., but this is all in southern Arkansas and should be downstream from the Little Rock area, so unless something weird is happening (which is possible) that shouldn’t be reaching Little Rock. 

That said, there are plenty of petroleum jobs in Little Rock. Maybe it’s just more plain old oil-field brine spills — like this spill from 2015, when a pipeline under the Arkansas River near Little Rock ruptured, spilled 4 million cubic feet of natural gas, and blew up a tugboat.

Charleston, WV – #6 Most Obese Community

Charleston is the capital of West Virginia and the state’s most populous city. The city sits at the intersection of the Kanawha and Elk rivers. The city’s water supply appears to come primarily from the Elk River. We can’t find any lithium measurements either in Charleston tap water, or in the water from either river. 

Even so, there are good reasons to suspect lithium contamination in the area. West Virginia has a long history of Coal and Natural Gas production, and Charleston is no exception. In fact, the first natural gas well in the United States was drilled in Charleston in 1815 by Captain James Wilson. Most of the official histories (including naturalgas.org) say that the first natural gas well in the United States was drilled in 1821 by William Hart in Fredonia, New York, but what they mean is that the first intentional natural gas well in the United States was drilled in 1821 by William Hart in Fredonia, New York. This is true, because when Captain James Wilson hit natural gas in Charleston in 1815, he wasn’t drilling for gas — he was drilling for salt brine. 

This is because the Kanawha River has an even longer history with salt brines than it does with natural gas. It was such a big deal that the little community upstream of Charleston now known as Malden, WV, was originally known as Kanawha Salines! In some ways this shouldn’t be a surprise, since we already know that fossil fuels and salt brines tend to pop up in the same areas.

This is a concerning potential source of lithium contamination, but can we confirm this with any measurements? We can’t find any modern measurements, but this 1906 report includes an analysis of a sample of brine from Malden taken in 1905 and finds a level of lithium chloride of 0.101 “parts in 1,000 parts by weight.” Parts-per notation can be a little ambiguous, but this probably works out to around 101,000 ng/mL lithium in the brine. In any case, it was more lithium than was found in the brines in other parts of West Virginia — about 3x that found in Webster Springs and about 10x that found in Hartford City.

Toledo, OH – #7 Most Obese Community

When you Google “toledo ohio lithium”, one of the first links you see is this: 

Ouvrir la photo

This leads to a news story about a chemical fire at the Lithium Innovations plant in central Toledo, Ohio. “The fire is releasing lithium gas, a potentially toxic fume, into the air,” reports WTOL11 News. “The gas could make the air difficult to breathe.” There’s even a police drone video of the fire on Youtube.

The fire was in 2017, so while it probably wasn’t good for the health of the community, it couldn’t have impacted Gallup’s obesity numbers, which are from 2014. But the Lithium Innovations plant came to Toledo in 2009, so it had a couple of years to expose people to the metal. The news report we quoted above also casually mentions, “during a 2010 inspection, fire inspectors found large quantities of lithium.”

We can’t find any direct measurements of lithium in Toledo’s drinking water, but this does look pretty bad. 

Clarksville, TN-KY – #8 Most Obese Community

Water in Clarksville comes from the Cumberland River. Clarksville, and the Cumberland, are practically surrounded by fossil fuel plants. About 20 miles downstream, sitting right on the river, is the Cumberland Fossil Plant. Groundwater testing wells at this plant seem to have pretty high levels of lithium — in 2018, the highest level was 79 ng/mL. 

About 80 miles upstream is a different plant, the Gallatin Fossil Plant, which also sits right on the Cumberland River. In fact it sticks way out in a bend in the river, so it’s surrounded by the Cumberland River on three sides. Several of the groundwater testing wells show an average of more than 60 ng/mL lithium, and the well with the highest level of contamination, right on the river’s edge, has a mean concentration of 1,660 ng/mL and a maximum of 2,300 ng/mL. This is further away, but the level of lithium contamination is almost 30x higher, and it is upstream.   

Jackson, MS – #9 Most Obese Community

Water in Jackson comes from a couple different sources — the Pearl River, the Ross Barnett Reservoir, and six groundwater wells. Unfortunately we can’t find any lithium measurements for any of these sources.

Like some other places on this list, Jackson has a long history of natural gas mining within the city limits, which gives us this great line from Wikipedia: “failure did not stop Ella Render from obtaining a lease from the state’s insane asylum to begin a well on its grounds in 1924”. 

They also tried to mine oil in Jackson, but it didn’t work out. Wikipedia gives us this other very interesting line about why: “The barrels of oil had considerable amounts of salt water, which lessened the quality.” Now is a good time to mention that Jackson sits right on the Smackover Formation, which is notorious for the high level of lithium in its brines. We can’t find any measurements for the levels of lithium in these brines around Jackson specifically, but this report does mention “lithium-rich produced water from Norphlet and Smackover completions in east central Mississippi” in the abstract.

There are also some weird records suggesting that people have been drilling for CO2 deposits from the Norphlet formation right on the banks for the Ross Barnett Reservoir, but these reports are much more vague than we would like.

We also found this report about oilfield brines contaminating groundwater and streams in Lamar and Marion Counties, Mississippi, and this other report about oilfield brines contaminating groundwater in Lincoln County, Mississippi. Neither of these are near Jackson but it does make you wonder. So no smoking gun, but it seems suggestive. 

Green Bay, WI – #10 (tied) Most Obese Community

Lake Michigan is Green Bay’s “main source” of water. Green Bay also has a lot of coal stuff going on. They used to have two coal power plants, both right on the water. Green Bay West Mill (sometimes called Green Bay Broadway?) burned coal for more than 100 years, but as of 2020 they are switching over entirely to natural gas. There was also Pulliam Plant or JP Pulliam Generating Station, a coal and natural gas power plant which operated from 1927 to 2018. Unusually, we can’t find any groundwater monitoring data for either of these plants.

But these are not the end of Green Bay’s coal-based attractions. Arguably more interesting are the coal piles stored by C. Reiss Coal Co. right on beautiful riverfront property, right in the middle of town, and a 10-minute walk from the local elementary school. 

The locals have an interesting relationship with these coal piles. The announcement that the city might be able to move the piles was: 

…embraced by residents of the Astor Neighborhood, across the Fox River from the coal piles, whose properties can be covered by a thin film of coal dust when the wind blows out of the west.

Resident Cheryl Renier-Wigg said the coal dust was “an unpleasant surprise” when she moved into the neighborhood in 1990. 

“It’s that you don’t realize you’ve got this coal dust lingering in the air until you clean your windows or your outside tables and chairs,” Renier-Wigg said. “You wipe it down and it’s black. Plastic things get pitted to the point you can’t clean them anymore.” 

So these are not lithium measurements, but the coal plants and coal dust blowing all over town are certainly the sorts of things that might be getting lithium into the local environment.

Rockford, IL – #10 (tied) Most Obese Community

According to the official report from 2020, “the source of drinking water used by ROCKFORD is Ground Water.” 

Rockford is located on the Rock River. Just upstream of Rockford on the Rock River is Rockton. A company named Chemtool built a new manufacturing facility in Rockton in 2008. What does Chemtool make, you ask? 

The plant grew and soon employed dozens of people. Everything was going well until June 14th, 2021, when the plant exploded.

Memphis, TN-MS-AR – #1 Most Obese City

We found this 2021 story from the Memphis Flyer about the Allen Fossil Plant, which is located adjacent to Memphis on the Mississippi River. The plant ran from 1959 to 2018 — according to the Flyer, it consumed 7,200 tons of coal per day, producing about 85,000 tons of ash every year. The plant is now closed but the ash remains, in “two massive ponds at the old coal-plant site.”

The TVA report from 2019 finds lithium in the monitoring wells at the plant — only one is above the safety threshold of 40 ng/mL, but it’s at concentrations above 20 ng/mL in other wells. There’s also something weird going on here, where many of the measurements are marked as “the result is estimated”, and there are a few much higher values (up to 125 ng/mL) that are marked as “the analyte was not detected above the indicated reporting limit.” It’s also notable that they report background levels, for theoretically uncontaminated groundwater, of up to 34 ng/mL. This isn’t a huge concentration — but it is very high compared to the levels found around Memphis in 1964, which ranged from 0.51 to 3.80 ng/mL.  

Because coal power plants often use inadequate testing mechanisms, the true level of lithium around plants may be higher than reported. For example, in some cases power plants use methods with a reporting limit of 200 ng/mL, which makes any levels below this threshold appear on reports as “not detected”. 

San Antono, TX – #2 Most Obese City

The San Antonio Water System “draws water from the Edwards Aquifer to service its customers in all 8 counties of the Greater San Antonio metropolitan area.” This is kind of complicated because the Edwards Aquifer is divided into different zones, and San Antonio sits right on the line between the freshwater and saline water zones, or “bad water line”. The saline water zone definitely contains a ton of lithium, up to 290,000 ng/mL. 

Some of this also appears to end up in the freshwater zone, and in drinking water. This USGS report from 1987 looked at four “subareas” of the Edwards Aquifer and found 12.9, 13.0, 16.0, and 100.0 ng/mL lithium in each. This other USGS report from 1987 found 22 ng/mL lithium in a well in the freshwater zone. There’s also this 2014 report on the Edwards Aquifer from the Edwards Aquifer Authority, which is confusing and vague, but suggests that about 33 samples from the freshwater zone contained 50 ng/mL or more of lithium. We can also just look at the USGS well water data again, because they pick out the “Edwards-Trinity aquifer system” specifically. In these 100 observations from 2008-2018, the median level of lithium is 6.03 ng/mL, the mean is 20.74 ng/mL, and the maximum is 188.00 ng/mL. 

And all of these measurements are much higher than historical values — in 1964, four wells in San Antonio were tested and found to contain only 1.5 ng/mL lithium.

Richmond, VA – #3 Most Obese City

Richmond gets its water from the James River and has since 1924. 

Chesterfield Power Station sits on the James River downstream. In 2020, several monitoring wells at this site were found to contain more than 100 ng/mL lithium, the highest concentration being 265 ng/mL.

The lower ash pond at Chesterfield Power Station

Bremo Power Station sits on the James River upstream. It was originally commissioned in 1931 and burned coal until 2013, when it converted to natural gas. In 2020, two monitoring wells were found to contain high levels of lithium — 121 ng/mL in one and 330 ng/mL in the other. Coincidentally, these seem to be the two wells closest to the James River, just a couple hundred feet from the banks. There are four monitoring locations in the river, and at the time of testing none of them registered high levels of lithium — but the reporting just says “<7.3” ng/mL for all four of them, suggesting they are not very sensitive.

New Orleans-Metairie-Kenner, LA – #4 Most Obese City

New Orleans gets its water from the Mississippi River. In the 100 cities paper from 1964, they report 4.3 ng/mL lithium in the Mississippi River near New Orleans. A similar amount was found in 1979, with this paper reporting 3.8 ng/mL lithium in New Orleans drinking water. By 1984, this paper reports about 15 ng/mL lithium in the Mississippi River near New Orleans. 

Unfortunately this is where the trail goes cold. We can’t find any more modern sources for lithium in either New Orleans drinking water or in the lowest stretches of the Mississippi River (if you are a chemist in the area, would you mind going down to the river for us? or just turn on your tap). 

Columbus, OH – #5 Most Obese City

Columbus gets its drinking water from — well, it’s complicated. Four wells in Franklin County provide about 15% of the city’s water supply. The other 85% comes from the Griggs and O’Shaugnessy Reservoirs, fed by the Scioto River, and the Hoover Reservoir, fed by Big Walnut Creek.

The only lithium measurements we were able to find come from this USGS report from 1991,  where they found lithium levels in the Scioto River between 10 ng/mL and 45 ng/mL. This is south of the city, however, so these are the levels after it has passed through the city. Even so, it’s interesting that the levels were all above 10 ng/mL even back in 1991. 

North of Columbus in Morrow County, there are a bunch of Class II injection wells, which are used to send oil brines BACK TO HELL back deep beneath the earth. This seems concerning for Columbus because Morrow county is the headwaters of Big Walnut Creek, and some of these injection wells appear to sit right alongside some of the area’s many streams.

The local injection authorities make all the usual claims about how these brines never get into creeks or public water supplies, but there have been spills — like this one in 2016, where a train plowed into a brine truck, spilling 3,200 gallons of brine. See also this senior thesis from 1974 documenting oil-field brines in Morrow County — it begins, “Since the discovery of oil in Morrow County, Ohio in 1961 the area’s ground and surface water has become grossly contaminated by oil-field brines.” And also this paper by Wayne Pettyjohn from 1971 which mentions extensive brine contamination, with several contamination events in Morrow County specifically.

Most of these reports don’t include any actual lithium measurements, but the Supporting Information for this paper does, and they find that oilfield brines in eastern Ohio contain between 202 ng/mL and 108,000 ng/mL lithium.

Oh, and they spread it on the roads as a de-icer, even though it’s definitely radioactive.

Rochester, NY – #6 Most Obese City

Rochester draws its drinking water from nearby lakes. Back in 1964, the local lithium levels were around 1.2 ng/mL. This report finds no lithium at all in Hemlock Lake between 1975 and 1977. 

Today things seem like they are different. We found this USGS report on groundwater quality in western New York from 2006, which reports lithium concentrations in the local aquifers as high as 917 ng/mL. Thankfully the sites with levels this high don’t appear to be close to any population centers, but the two wells closest to Rochester contain 64.2 ng/mL and 78.9 ng/mL lithium. 

We can’t find any actual measurements for either lake or for the local drinking water. The city’s annual water quality reports give a clear list of all the contaminants they test for and lithium isn’t on the list, so there probably aren’t any records out there for us to find. 

Louisville-Jefferson County, KY-IN – #7 Most Obese City

Louisville appears to get most or all of its drinking water from the Ohio River. Like other cities we’ve looked at along the Ohio River, Louisville is downstream from a coal power plant with a lithium problem.

The Ghent Generating Station is about 70 miles upstream from Louisville. This news article from 2021 describes coal ash being moved to ash ponds near the Ohio River, and mentions that “groundwater monitoring wells at the Ghent power plant had lithium levels up to 154 times the amount considered safe … one of the highest lithium levels documented at 265 coal power plant sites.” We also found this news article from 2019 about how “Louisville Gas and Electric power plants are illegally contaminating groundwater flowing into the Ohio River”, which mentions lithium specifically. We tracked down some actual measurements, and found that levels of lithium found in the groundwater at this plant can be as high as 6,167 ng/mL.

Oklahoma City, OK – #8 Most Obese City

The Oklahoma State Capitol has the interesting distinction of being the only state capitol grounds in the United States with active oil rigs. This is because Oklahoma City, Oklahoma sits on top of the Oklahoma City Oil Field. This produces a lot of oil and a lot of brine.

Oklahoma State Capitol Building; note oil derrick on the right

At this point the contamination should not be a surprise. Here’s a USGS report from 1998 on water quality in the confusingly-named Canadian County, Oklahoma, which is just one county over from Oklahoma City. They report one measurement from a test well in the area, which showed a concentration of 32 ng/mL of lithium.

We can’t find any more recent measurements in drinking water, or for the brine itself, but as always there are the news reports of oil and gas wastewater wells overlapping with drinking water wells, and news reports of oil-field brines polluting the water supply “to such a degree that no trees or flowers will grow.”

Detroit-Warren-Livonia, MI – #9 Most Obese City

It probably won’t take any special convincing to get you to believe that the drinking water in Detroit might be contaminated. Unfortunately Detroit is another one of those cities that just doesn’t seem to test for lithium, but it’s still looking pretty bad.

To begin with, at the Trenton Channel Power Plant on the Detroit River, all eight groundwater testing wells are heavily contaminated. Six out of eight had an average level of lithium above 40 ng/mL, and the highest level on record is 370 ng/mL.

And at the end of the day, the city is just generally polluted. Take for example the Samuel B. Jolly Site at 3445 West Warren Avenue, Detroit. This used to be a gas service station, but is currently a vacant lot. The service station structures have been removed, but three 8,000-gallon gasoline storage tanks, “temporarily out of use”, remain underground. The report calls this a leaking underground storage tank (“LUST”; no, really) site, and documents the petroleum contamination. The units are a little unfamiliar because they’re for soil rather than water, but suffice to say, of the 14 samples, 10 contained more lithium than the statewide background levels, and the highest measurement was almost 30x higher than background levels.

Cleveland-Elyria-Mentor, OH – #10 Most Obese City

Cleveland drinking water comes from Lake Erie. Cleveland doesn’t seem to test for lithium, and we can’t find any modern measurements for the lake, though we’ll note that Cleveland is downstream of Detroit. 

Without any measurements, the best we can do is note that the water around Cleveland has a history of being really, really polluted. Cleveland sits where the Cuyahoga River empties into Lake Erie, a river so polluted that it has caught fire at least 13 times. Most of these were in 1969 or before, but another one came around in 2020, when an oil tanker truck crashed and leaked flaming gas into the river. 

The timeline seems a little off for this, since the river was more polluted in the past than it is now. But a lot of these pollutants have stuck around in one way or another, leading to headlines like, “Cleveland’s water supply at risk as toxic blob creeps across Lake Erie, Ohio EPA says”.

But we can also just note that Cleveland was only 28.0% obese in 2014, which seems to be sightly less than the rate for Ohio overall in that year. We may have simply reached the point on the list where the cities are catching up to background levels.   

In Conclusion

Looking at the leanest list, we were able to find explicit measurements of the lithium levels in the drinking water of five communities. In Denver’s drinking water, lithium is consistently tested for but not detected. In San Jose, the median level of lithium in the water was around 3-5 ng/mL, and the maximum observed was only 25 ng/mL, which seems to be an outlier. In Barnstable Town, the aquifer they draw their water from appears to contain less than 10 ng/mL lithium, though the analysis we found wasn’t sensitive enough to say how much less. Miami’s aquifer contains a median of 1.11 ng/mL, and the maximum level observed was only 2.6 ng/mL. Finally, in DC we found an average of 2 ng/mL and a range of only 1-4 ng/mL in drinking water. 

There were also six communities where we weren’t able to find measurements of lithium in drinking water from modern sources, but were able to find evidence that suggests that the lithium levels are probably quite low. In most cases this is suggested by the fact that the community gets its drinking water from a pristine source, like remote mountain snowmelt, and in some cases we were able to support this with historical measurements. If a source wasn’t contaminated in 1964, and nothing has happened to change that, then the source probably still isn’t contaminated now.

Finally, in six of the communities on the leanest list, we weren’t able to find any indication of how much lithium is in their drinking water.

Looking at the most obese list, we were able to find good measurements of the lithium levels in the drinking water of two communities. In McAllen, the median level we found was 59.7 ng/mL, with a range from 20.8-115.0 ng/mL. In San Antonio, the most recent analysis found a median level of lithium of 6.03 ng/mL, a mean of 20.74 ng/mL, and a maximum of 188.00 ng/mL. 

In twelve communities, we found evidence of groundwater and/or drinking water source contamination from fossil fuel sources — usually coal plants nearby or upriver, but also natural gas wells, injection wells, other coal sources, etc. In nine of these communities, we found direct measurements of the contamination, with levels of lithium levels in groundwater often smashing the reporting limit of 40 ng/mL, the highest being 6,167 ng/mL. In the other three, we found evidence of nearby coal plants or other major petroleum contamination, but couldn’t find direct measurements of lithium levels. 

We also found five communities with evidence of lithium exposure or contamination from some other source — like explosions of local lithium-grease factories.

Finally, in two of the communities on the most obese list, we weren’t able to find any indication of how much lithium is in their drinking water and weren’t able to find any evidence of lithium contamination. 

Overall, there is evidence of lithium contamination in most of the most obese communities. In contrast, when going down the list of the leanest communities, we didn’t find any indication of lithium contamination, and in the drinking water measurements we found, we never saw a lithium level above 25 ng/mL. We also didn’t find any evidence of fossil fuel mining or waste disposal near any of the leanest communities. 

Drinking water is important, but this still surprised us — we didn’t expect such a clear association. There’s something kind of weird going on here. When we discovered evidence that wolfberries concentrate 100 ng/mL lithium in water to 1,120,000 ng/mL in the plant, we were pretty excited. Trace doses are really low compared to psychiatric doses, which makes it seem a little weird to expect trace doses to have any noticeable effect at all. But if other crops concentrate lithium like the wolfberry does, then people could be getting sub-therapeutic (i.e. pretty huge) doses from their food alone.

For a while there we thought this was the solution — that if lithium caused obesity, it did so via subtherapeutic doses in your food. But in our last post and in the examples we give above, we found what looks like a pretty strong relationship between how much lithium is in the groundwater and how obese people are, even down to the community level. 

We’re not sure what to make of this. It could be that lithium doesn’t cause obesity, it’s something else that commonly co-occurs with lithium, something else found in coal ash and oilfield brines. 

Maybe trace levels of lithium in your drinking water really are enough to make you obese, all by themselves. Or maybe it’s not “drinking” water per se. Maybe lithium has a different, much stronger effect when it’s absorbed through your skin, or when you inhale lithium-rich steam droplets into your lungs. If this were the case, then tap water levels would matter a lot, at least if you’re showering in the stuff. As far as we know there aren’t any studies where they had people shower in distilled water, but if you find one, let us know.


[Next Time: WHAT DO WE DO ABOUT IT?]


A Chemical Hunger – Interlude H: Well Well Well

[PART I – MYSTERIES]
[PART II – CURRENT THEORIES OF OBESITY ARE INADEQUATE]
[PART III – ENVIRONMENTAL CONTAMINANTS]
[INTERLUDE A – CICO KILLER, QU’EST-CE QUE C’EST?]
[PART IV – CRITERIA]
[PART V – LIVESTOCK ANTIBIOTICS]
[INTERLUDE B – THE NUTRIENT SLUDGE DIET]
[PART VI – PFAS]
[PART VII – LITHIUM]
[INTERLUDE C – HIGHLIGHTS FROM THE REDDIT COMMENTS]
[INTERLUDE D – GLYPHOSATE (AKA THE ACTIVE INGREDIENT IN ROUNDUP)]
[INTERLUDE E – BAD SEEDS]
[PART VIII – PARADOXICAL REACTIONS]
[PART IX – ANOREXIA IN ANIMALS]
[INTERLUDE F – DEMOGRAPHICS]
[INTERLUDE G – Li+]

A while back, one of us was talking to a family member about the improperly sealed abandoned boreholes in the Gila River Valley, and how oilfield brines are really high in lithium. This inspired him to speculate that while most of us don’t live near improperly sealed abandoned boreholes, there is a different kind of hole in the ground that many of us interact with every day — the wells we draw our water from.

There are a couple of things that make water wells seem kind of suspicious. When it comes to obesity, we’re looking for something that’s really universal, something that would reach pretty much everyone, because every part of the world is becoming more obese all the time. Maybe some people have oilfield brines in their water, sure. But not everyone is downriver from a pipeline.

Well, back in the day, nobody got their water from deep, drilled wells. Nowadays, millions of people drink well water every single day. The USGS estimates that 115 million people, more than one-third of the nation’s population, rely on groundwater for drinking water, and that 43 million of those people are drinking from private wells. And just because you aren’t drinking well water doesn’t mean you’re not affected — when all those wells bring up water from the depths, it ends up mixing with the surface water. 

This could represent a pretty big change in the ecosystem. You might think of groundwater as just normal water — maybe more pure, but still just water. But often it’s not like surface water at all. Some of the water flowing underground has been there only for a few weeks, but some of that water has been down there for hundreds, thousands, or even millions of years. 

Generally speaking, the deeper the well, the older the water you’re drawing. But sometimes even relatively shallow wells draw from very old waters. For example, this analysis from Alberta suggests that in the Paskapoo Formation aquifers, “a very important source of water for irrigation and drinking in southwestern Alberta,” some water samples drawn from relatively shallow depths (less than 60 meters) are more than 1,000,000 years old.

Who knows what might be down there. The USGS helpfully notes, “old groundwater is more likely than young groundwater to have contaminants from natural sources, such as metals and radionuclides, because old groundwater can spend thousands of years in contact with and reacting with aquifer rocks and minerals that might contain these elements.” If water from drilled wells tends to have more lithium in it than water from shallow wells or surface water does, that would explain why people are exposed to more lithium now than they used to be, and could explain why the exposure is so universal. 

Artist’s rendition of Paskapoo Formation wells in Alberta, Canada

Basic well-drilling technology first arose in the early 1800s. We can take as an example Levi Disbrow, who according to some sources drilled the first artesian well in the United States in 1824. Things took a leap forward in 1909 when a patent for the first roller cone drill bit was issued to Howard Hughes Sr. — but even then, drilling tools were all still platform-based, and impractical for homeowners. It wasn’t until the 1940s that portable drills became effective, and it took until the 1970s for drilled wells to become common for individual homes. 

Most states keep pretty good records for drilled wells, so we’re able to confirm this with publicly available data. Rather than trying to hunt down data for every state, we did some spot checks. For example, Massachusetts keeps a database of wells dating back to 1962. Looking just at new, domestic wells, we see that about 96% were drilled in 1970 or later, and about 91% were drilled in 1980 or later. The two biggest decades for domestic drilling in Massachusetts were the 1990s and the 2000s, when about 37,000 wells were drilled each decade.

In Vermont, well drillers have been required to submit reports to the state on each well they drill since 1966, but there are some records dating as far back as 1924. We found that of the wells in the database, 96% had been drilled since 1970, and 83% had been drilled since 1980. Again, the two decades with the most well drilling were the 1990s and 2000s.

Since we mentioned bioaccumulation in plants last time, we also want to mention that a lot of crops these days are irrigated with water from drilled wells. Without getting too much into the details, it looks like most irrigation wells were also drilled pretty recently. In Kansas for example, it looks like only five of the irrigation wells on record were drilled before 1970, compared to about 22,000 wells drilled afterwards! 

The timeline for drilled wells lines up pretty well with the timeline for the spread of obesity. These days lots of people get their water from drilled wells, but that’s historically weird. If well water contains more lithium than surface water does, and lithium causes obesity, that would explain why obesity is so widespread.

The second reason this seems plausible is that similar things have happened with well-drilling and other contaminants. Let’s look at one well-documented example (h/t Phil Wagner):

It was the best intentions of governments and world bodies in the 1970s to improve health that led to the crisis in Bangladesh. Until the 1980s, most villagers drew water from shallow wells, or collected it from ponds and rivers – and regularly suffered cholera, dysentery and other water-borne diseases. 

In response to these preventable illnesses, the UN and many western donors advised Bangladesh to bore deeper “tube wells” into the underground water aquifers to draw clean, pathogen-free water. But the scientists and donors advised drilling to about 150ft (46m) – almost precisely the depth of arsenic-rich rock. 

The first cases of arsenic poisoning were discovered in the early 1990s, and, in 1995, an international conference in Kolkata drew the world’s attention to the problem.

Efforts have been made to do something about this, but it still seems to be a huge problem. This report from the Human Rights Watch in 2016 says that “an estimated 43,000 people die each year from arsenic-related illness in Bangladesh”.

Similar contamination can be found elsewhere. In parts of India, wells are contaminated with uranium.

Third and finally, we want to point to a few examples that indicate that lithium specifically might be a problem in deep, drilled wells. The first is a passage from Sievers & Cannon (1973), the Gila River Valley paper, about where the Pima got their home drinking water:

Wells, the main source of domestic water, have needed deepening because the ground-water table has dropped at least 20 feet in the last few years. The lower aquifers now in use produce water of higher salt content than previously.

They don’t quite say it outright, but this suggests that the Pima wouldn’t have been exposed to as much lithium if they hadn’t deepened their wells. The lower aquifers have a higher salt content, and this likely includes dissolved lithium salts.

An even clearer example can be found in this paper about lithium levels in part of Maryland in 1976, where they found that deep wells had abnormally high levels of lithium compared to other sources: 

Lithium levels varied by type of water source. The highest lithium levels were found in deep wells. Two thirds of the samples with concentrations greater than or equal to 10 [ng/mL] were found in deep wells, and 24% of the deep wells had concentrations greater than or equal to 10 [ng/mL]. City waters had no levels greater than 12 [ng/mL], and less than 2% had levels over 10 [ng/mL].

This all just makes the idea seem plausible. What we really want to know is, is there an appreciable amount of lithium in well water today? 

Lithium in Modern America

The answer is yes!

The first time we wrote about lithium, we said we didn’t know if there was lithium in the groundwater, we didn’t know if groundwater concentrations of lithium had increased over time, and the USGS wasn’t interested. Well, we are happy to report that all of that has changed.

On February 11, 2021, the USGS released a report titled Lithium in U.S. Groundwater. The first conclusion they share is that “45% of public-supply wells and about 37% of U.S. domestic supply wells have concentrations of lithium that could present a potential human-health risk.” It doesn’t get any better from there. The header for the report looks like this:

The report is backed by a paper released on May 1, 2021. The raw data is available here (see the two urls near the bottom).

There’s a lot of interesting stuff in this paper, but mostly we want to know if there are serious levels of lithium in well water, and if most Americans are getting lithium in their drinking water. The answer in both cases seems to be a pretty clear “yes”:

Concentrations nationwide ranged from <1 to 396 [ng/mL] (median of 8.1 [ng/mL]) for public supply wells and <1 to 1700 [ng/mL] (median of 6 [ng/mL]) for domestic supply wells. For context, lithium concentrations were compared to a Health Based Screening Level (HBSL, 10 [ng/mL]) and a drinking-water only threshold (60 [ng/mL]). These thresholds were exceeded in 45% and 9% of samples from public-supply wells and in 37% and 6% from domestic-supply wells, respectively

This dataset includes a few samples from as far back as 1991, but almost all the samples were collected after 2000, and the biggest chunk are all from 2010 or later, so this is a pretty modern dataset. As we can see, the median concentration in well water is about 6-8 ng/mL, though this kind of obscures the fact that about 40% of all wells contain more than 10 ng/mL of lithium. Since we have the raw data, we can clarify and state that the median for all samples was 6.9 ng/mL. 

There are two comparisons we want to make. The first is to historical sources — are we being exposed to more lithium now than we were back in the day? Our best source for this is that 1964 paper, Public water supplies of the 100 largest cities in the United States by Durfor & Becker, which as you may remember is available on Google Books. They report a median level lithium concentration of only 2.0 ng/mL in the water supplies they analyzed. Based on this, the median level in US drinking water seems to have increased 3-4x since 1964. But this obscures the long tail of these data. Back in 1964, the maximum level they recorded was 170 ng/mL. In the modern data, the highest level is 1700 ng/mL, 10x higher.

We can also compare this to the Pima, who in the early 1970s were being exposed to about 100 ng/mL of lithium in their drinking water. This was very unusual back then but it is only somewhat unusual now — about 5% of the modern well water samples were in this range or higher, and about 1% contained more than 200 ng/mL. 

The median level of contamination has increased somewhat, but the maximum level of exposure has increased by an order of magnitude. There’s definitely more lithium in the groundwater today than there was in the 1960s and 1970s.

(We also noticed that in this paper, they mention: “As the stream flows toward its mouth, many sources contribute dissolved and suspended matter to the stream. … It is not surprising that the raw water obtained by Minneapolis, Minn., from the upper reaches of the Mississippi River contains about one-half the amount of dissolved solids as the raw water used by New Orleans, La., near the mouth of the river.”)

The other comparison we want to make is to other countries. The United States is pretty obese, much more obese than most other parts of the world. So the next step is to track down some data and see if other parts of the world have more or less lithium in their groundwater and/or drinking water than we do. 

We’ve found sources for a couple other countries, and we’re prepared to make some comparisons. These distributions are generally skewed, so the median is really the most appropriate metric here — but unfortunately some of these sources don’t report it and just report the mean instead. So to keep us comparing apples to apples as much as possible, remember — the US is about 36% obese, the median of lithium in the well water dataset is 6.9 ng/mL, and the mean is 19.7 ng/mL.

Greece is about 25% obese. In 2013, a team published this paper looking at lithium levels in 149 samples of drinking water from 34 prefectures of Greece. They found that the average level of lithium in the samples was 11.10 ng/mL, with a range from 0.1 to 121 ng/mL. (They also looked at 21 samples of different kinds of bottled waters and found mean lithium levels of 6.21 ng/mL) We can see that the average is lower than the average level in American well water, and that while there is quite a range of values, the range is also much more limited than the range in modern American water samples. We can also point out that the highest level for lithium in this sample (121 ng/mL) was on Samos Island, and in our first post on lithium, we found hints that people on Samos Island are about as obese as Americans.  

Denmark is about 20% obese. In 2017, a team published this paper looking at lithium levels in 158 drinking water samples from 151 public waterworks supplying approximately 42% of the Danish population. Of these, 139 measurements came from “a drinking water sampling campaign, executed from April to June 2013, spatially covering the entire country”. They found an average level of lithium in their sample of 11.6 ng/mL (SD 6.8 ng/mL), with a range from 0.6 ng/mL in Western Denmark to 30.7 ng/mL in Eastern Denmark. This average is pretty high, though lower than the average in our American samples, but it’s also notable that the range and maximum levels are quite low. Even though the Greek and Danish averages are very similar, the Danish maximum value is about one-fourth the Greek maximum value. They also happily report the median value, 10.5 ng/mL.

Austria is about 20% obese. In 2018, a team published this paper looking at 6460 lithium measurements in drinking water samples from all 99 Austrian districts. The average level of lithium was 11.3 ng/mL (SD 27 ng/mL), with a range from “not detected” to 1300 ng/mL.The authors mention that the measurements are extremely skewed — between this and that extreme maximum value, we expect the median is much lower than 11.3 ng/mL.

Italy is about 20% obese. In 2015, a team published this paper looking at lithium concentrations in drinking water at 145 sites in Italy. The average level of lithium in the samples was 5.28 ng/mL, with a range from 0.110 to 60.8 ng/mL. The mean and the maximum level are markedly lower than the levels found in American water. 

Japan is about 4% obese, making it the leanest industrialized nation in the world. In 2020, a team published this paper (h/t commenter Patrick Halstead) looking at lithium levels in 434 drinking water samples in the 274 municipalities of Kyushu Island, the third largest island of Japan’s five main islands, which is home to about 10% of the population. They found that the average level of lithium in the samples was 4.2 ng/mL (SD 9.3 ng/mL), with a range of 0 ng/mL to 130 ng/mL. 

This average is lower than any of the other modern averages we’ve seen. If you look at the map below, you’ll see that only three municipalities had more than 40 ng/mL lithium in their water. Combined with the high maximum value of 130 ng/mL, this suggests an extreme skew, and suggests that the median value is lower than 4.2 ng/mL, maybe much lower. Unfortunately the authors haven’t publicly shared the raw data, so it’s hard to know what the median value really is.

There’s also this paper from 2020 (h/t commenter AJ), by some of the same authors, which looked at lithium levels in tap water samples across the 26 municipalities of Miyazaki Prefecture. Miyazaki Prefecture is part of Kyushu Island, so this is sort of zooming in on the result above. The average lithium levels in the tap water samples was 2.8 ng/mL, with a range from 0.2 ng/mL to 12.3 ng/mL. This time they also report the median, which is 1.7 ng/mL. Note that this median level is lower even than the median in the US in 1964.  

There’s also this paper from 2009, again by some of the same authors, again looking at a prefecture on Kyushu Island. This time they looked at Oita Prefecture, which borders Miyazaki Prefecture to the south. The only difference is that the data are somewhat older, being collected in 2006. Unfortunately they don’t seem to report a mean or a median, but the range was from 0.7 ng/mL to 59 ng/mL, and the authors note that “the distribution of lithium levels was considerably skewed.” Reporting on this paper, the BBC said, “The researchers speculated that while these levels were low, there may be a cumulative protective effect on the brain from years of drinking this tap water.”

Taken together, these three papers strongly suggest that Japanese people have much lower levels of lithium in their drinking water than Americans, or indeed any industrialized population.

We’re comparing a lot of unlike things here. We’re comparing means to medians; comparing sources from different countries and across different years; comparing samples from “groundwater”, “well water”, and “drinking water” without knowing if these are meaningfully different. But even with these limitations, we see that drinking water in America clearly has higher levels of lithium than the drinking water in other countries. This is apparent in the average levels found in large samples, but even more impressive is the differences in extreme values. Most other countries see maximum values of not much more than 100 ng/mL, while the American maximum value recorded was 1700 ng/mL, and a full 1% of samples in our best dataset contained more than 200 ng/mL lithium.

There’s more lithium in American well water than there is in the drinking water of these countries. But there’s also more lithium in the drinking water of these countries than there was in America in the 1960s. Greece, Denmark, Austria, and Italy all have more lithium in their water today than America did in 1964. The median in the dataset for America in 1964 was 2.0 ng/mL — we only have averages for most of these countries, but they all are much higher than 2.0 ng/mL. Denmark, where they do report the median, has a median value of 10.5 ng/mL. The only exception is Japan, where the median (if we could calculate it) might be around 2.0 ng/mL. But modern-day Japan is leaner than America was in 1964 — they’re about as lean as America was in 1890! 

Lithium and Depth

We can also look at the data from this new USGS report to see if there’s anything to our suspicion that drilling deeper and deeper wells is leading to more background lithium exposure. 

The most basic thing to look for is just to see if deeper wells have higher concentrations of lithium, and the answer is a clear “yes”. The paper itself comments, “Lithium concentrations … are positively correlated with well depth”, and naturally we see the same thing in the raw data.

The relationship varies slightly depending on how you do the analysis, but however you slice it, well depth and lithium levels are correlated at about r = 0.2. Because the sample size is several thousand, these are always statistically significant. The relationship also remains significant, and about the same strength, when we control for other variables we expect to be relevant.

In the case of the arsenic contamination in Bangladesh, arsenic was concentrated at a depth of around 50 meters. Wells at around this depth tended to be heavily contaminated, but wells that were either shallower or deeper were generally fine. We thought there might be a similar “sweet spot” for lithium, but so far we haven’t found much evidence for this. Overall there is a weak but pretty constant relationship, where the deeper the well is, the more lithium it contains. There are some indications of a sweet spot for certain types of aquifers, but we’d need to do a more detailed analysis.

There’s even some evidence that wells have been getting deeper over the years. This dataset doesn’t contain information about when wells were drilled, but when they were tested is a proxy for when they were drilled — a well tested in 2003 couldn’t have been drilled in 2008. When we look at the data, we see that the depth of the wells being tested shows a consistent increase over time. In the 1990s they tested 39 wells, and the deepest was only 260 feet deep. In the 2000s, they tested 1,288 wells, and 313 were deeper than 260 feet. Only two of the wells tested in the 2000s were more than 2,000 feet deep. In the 2010s and on, 33 of the wells they tested were more than 2,000 feet deep.

This is supported by the publicly-available well data we pulled from Vermont and Massachusetts earlier, where we see moderate correlations (about r = 0.3) between the year a well was completed and the overall depth. This is omitting the wells in the MA dataset that were listed as being 4,132,004 and 10,112,002 feet deep — we think these may be typos.

What about the maps? 

If there’s one thing we’ve learned from this project, it’s that people love maps. This paper contains a few, and they’re pretty interesting. This one is the most relevant: 

​​

One thing that you’ll notice is that the distribution of lithium in well water doesn’t match up all that well with the distribution of obesity. Colorado is the leanest state but has pretty high levels of lithium in its well water. Alabama is quite obese but levels of lithium in the well water there are relatively low. What gives? 

We think there are a couple of reasons not to be concerned about this. The first is that the sample is nowhere near representative. If you look at the map, you’ll see that the domestic-supply networks are thick around the coasts but thin in the interior of the country — except in Nebraska, where they are massively overrepresented for some reason. Only six wells were recorded in West Virginia and only three in Kentucky, which is too bad because those states seem pretty important. No effort seems to have been made to target population centers — this is a study by the USGS, so they are more interested in figuring out the features of major aquifers than of major cities. If a major city happens to be drawing from an especially contaminated source, they might have missed it.

The second is that there are big seasonal and weather effects, which they don’t adjust for. There’s almost no lithium in rain and snow — it’s essentially distilled water — so when it rains, lithium levels in groundwater drop as it becomes diluted with this influx of pure water. Similarly, there are seasonal effects — in part due to precipitation and snowmelt cycles — where lithium in the groundwater rises and falls over the course of the year.

But the third and most important thing is that all of these measurements are of well water, but many areas get their drinking water from surface sources rather than from wells. 

Let’s start with Colorado, since it’s the clearest example. As you can see from the map above, the average level of lithium in Colorado well water is higher than the national average. We have the raw data, so again we can tell you that the median level in Colorado wells is 17.8 ng/mL, the mean is 28.0 ng/mL, and the max is a rather high 217.0 ng/mL.

But this doesn’t matter, because almost none of the drinking water in Colorado comes from wells. Instead, most of the drinking water in Colorado comes from surface water, and most of that water comes directly from pure snowmelt.

Denver is the largest city in Colorado and also the capital. A company called Denver Water, which is Colorado’s oldest and largest water utility, serves the city of Denver and surrounding areas. They have this to say about where they get their water

Denver Water … relies on a system that collects rain and snow from across 4,000 square miles of mountains and foothills west of Denver. … On an average year, the utility captures 290,000 acre-feet of rain and snowmelt in its collection system. That’s roughly 94 billion gallons of water — or enough to fill up nearly 157 Empower Fields at Mile High. The water flows down rivers and streams, then through a network of tunnels, pipelines and canals to treatment facilities in the Front Range to be cleaned for delivery to homes and businesses. Because most of the water comes from mountain snowmelt in the spring, water is stored in mountain reservoirs until it is needed.

On another page, they say:

Denver Water is responsible for the collection, storage, quality control and distribution of drinking water to 1.5 million people, which is nearly one-fourth of all Coloradans. Almost all of its water comes from mountain snowmelt, and Denver is the first major user in line to use that water. Denver Water’s primary water sources are the South Platte River, Blue River, Williams Fork River and Fraser River watersheds, but it also uses water from the South Boulder Creek, Ralston Creek and Bear Creek watersheds.

Colorado Springs is the second-largest city in Colorado. Despite the name, they also get most of their drinking water from snowmelt. Per coloradosprings.gov

Colorado Springs is a community that lacks a natural water source. 80% of our community’s water comes via pipelines from the western slope, 200 miles away.

And per waterworld.com

Most of Colorado Springs’ current water comes from snowmelt, either on Pikes Peak or on the Western Slope. If snowfall is inadequate and precipitation falls as rain, the water is not easily captured in the high mountains where the Homestake pipeline begins. However, the Southern Delivery System (SDS) project would capture water as the flow emerged from the mountains as the Arkansas River and into Pueblo Reservoir.

Also enjoy this video from Colorado Springs Utilities called What it Takes to Drink Snowmelt.

Aurora is the third-largest city in Colorado (and right next to Denver). We bet you can guess where we’re going with this! From auroragov.org:

One of the benefits of living in a state that relies primarily on this surface water is that unlike groundwater, surface water is a renewable water source. 

Aurora receives 95 percent of our water from surface water sources, with the remaining five percent coming from deep aquifer groundwater wells. Replenished each year through snowmelt, Aurora’s water supply is transported from 180 miles away through a complex and extensive system.

As we mentioned above, precipitation has extremely low levels of lithium because it’s basically been distilled. In one study of rainwater in Montréal, they found a mean level of only 0.48 ng/mL. This means that if you are drinking rainwater or snowmelt, you are getting less lithium in your drinking water than any other group we’ve seen — less than in Italy, less than the Japanese, and less than Americans back in 1964. 

People in Colorado more or less are drinking nothing but snowmelt. It runs through rivers and reservoirs first, so it probably picks up some trace minerals and other contaminants from the slopes and riverbeds. But it doesn’t matter if the well water in Colorado is high in lithium — people aren’t drinking that, they’re drinking snowmelt.

Lithium aside, this is pretty interesting just from the perspective of Colorado being the leanest state. Snowmelt will be extremely low in pretty much every contaminant, so this seems to be additional evidence that obesity is caused by a contaminant that is carried in drinking water. We think you can still get exposure from other sources as well, probably your food — which is why Colorado is 20% obese, rather than 2% obese like premodern populations — but this seems like some evidence that drinking water alone makes some difference.

Other states also use surface water, but we’re pretty sure no one else is getting 95-100% of their drinking water directly from snowmelt. Utah is just on the other side of the ridge, but their Department of Environmental Quality says

Utah’s drinking water comes from either surface water (lakes, reservoirs, rivers) or ground water (wells or springs), altogether 1,850 sources. Utah’s larger cities generally use surface water and wells while its small towns depend on springs that serve the system all year long, supplemented by wells during the summer months.

Nearby Nebraska seems to get most of their drinking water from wells. According to one source, about 80 percent of the population consumes drinking water that is pumped from groundwater sources; according to another source, 85% of the population does. So unlike Colorado, Nebraska should be concerned about the levels of lithium in their groundwater — a median level of 17.6 ng/mL and a mean of 21.7 ng/mL — because they’re actually drinking it. And the rest of us should be concerned as well, because Nebraska is #3 in the nation for agricultural production.


[Next Time: THE FATTEST CITIES]


A Chemical Hunger – Interlude G: Li+

[PART I – MYSTERIES]
[PART II – CURRENT THEORIES OF OBESITY ARE INADEQUATE]
[PART III – ENVIRONMENTAL CONTAMINANTS]
[INTERLUDE A – CICO KILLER, QU’EST-CE QUE C’EST?]
[PART IV – CRITERIA]
[PART V – LIVESTOCK ANTIBIOTICS]
[INTERLUDE B – THE NUTRIENT SLUDGE DIET]
[PART VI – PFAS]
[PART VII – LITHIUM]
[INTERLUDE C – HIGHLIGHTS FROM THE REDDIT COMMENTS]
[INTERLUDE D – GLYPHOSATE (AKA THE ACTIVE INGREDIENT IN ROUNDUP)]
[INTERLUDE E – BAD SEEDS]
[PART VIII – PARADOXICAL REACTIONS]
[PART IX – ANOREXIA IN ANIMALS]
[INTERLUDE F – DEMOGRAPHICS]

Let’s talk about some of the new stuff we’ve learned about lithium.

Lithium Grease

Our first post on lithium mentioned lithium grease, which is used on all kinds of heavy machinery. We found this interesting because professions that work closely with cars, trucks, planes, and trains tend to be more obese than average, and if lithium causes weight gain, lithium grease might be able to explain this pattern.

We knew that lithium grease was a modern invention, but we recently found out that the timeline for lithium greases matches the timeline of the obesity epidemic even better than we realized — it was introduced in the 1940s, but only started seeing serious use in the 1980s. Here’s the story per The Society of Tribologists and Lubrication Engineers:

Greases made with simple lithium soap thickeners first appeared in the 1940s, starting with Clarence Earle’s 1942 patent (U.S. 2,274,675). Users found that these greases resisted water better than greases made with sodium soaps, and they performed better at high temperatures than calcium soap greases did. Lithium soap greases resist shearing, and they exhibit good pumpability properties, although they require the addition of antioxidants. This combination of advantages outweighed the extra manufacturing expense compared with calcium and sodium thickeners, and lithium soap greases (notably lithium 12-hydroxystearate formulations) quickly claimed a large share of the market (9). 

Lester McClennan patented the first lithium complex grease in 1947 (U.S. 2,417,428), but lithium complex greases did not become popular commercially until the early 1980s (9). For the past 20-30 years, manufacturers have been shifting away from thickeners based on simple lithium soaps to lithium complex thickeners because of the latter’s better performance at high temperatures, Waynick says. 

With this in mind, you can imagine our reaction when we saw an email drop into our inbox with the subject line, “Repeatedly eating lithium grease”. This email turned out to be from reader Emily Conn, sharing the following anecdote about a guy she used to work with: 

I used to work in HVAC repair with a guy named A—, and he was sort of famous in our company for eating lithium grease. The reason he did this was so that he could identify the sort of grease that had been used somewhere and then apply the same type. He could even taste differences between brands. We all touched the stuff, which I thought at the time was safe, but he was the only one who ever ate it.

Well, all the other health problems the guys in the company had, he had 10 times over. Not only was he extremely fat, he was also frequently out for medical issues, although I never knew what they were.

Another note for the story – I’ve never seen anyone else care about matching brands of lithium grease, not sure why A— thought it was important. Also, I never validated his claim that he could taste the difference between brands – that was what he said he could do but none of us ever checked.

This is just an anecdote and only a sample size of one, and may not be representative of all cases. Nevertheless, we strongly recommend that you avoid eating lithium grease.

What about the Middle East?

In our first post about lithium, we speculated that many Middle Eastern countries have high rates of obesity because they get a lot of their drinking water from desalination. Desalination removes all trace elements from seawater, but because distilled water is bad for pipes and trace elements are important for your health, the desalinated water is remineralized by blending it with some of the original sea water. 

Seawater has more than a bit of lithium in it, and lithium levels in the Persian Gulf are on the high end for seawater. Based on measurements of seawater in the gulf, we calculated that desalinated seawater in the Middle East could end up carrying a pretty big dose of lithium, somewhere in the range of 10-100 ng/mL.

(Also notable is that desalination produces lots of toxic brine, which is itself a problem.)

It’s true that 100 ng/mL is a pretty high level of lithium to find in your drinking water, but it’s not a total outlier — we see lithium levels this high or higher in places like Texas, some Greek Islands, and some parts of Austria. So 100 ng/mL is concerning, but it’s still surprising that Middle Eastern countries ended up so obese when there are other places that get similar doses.

Some Reddit comments recently introduced us to the Pima people of the Gila River Valley, who had very high levels of obesity way before the obesity epidemic started for the rest of the world, as high as 40% obese in 1970. In the course of looking into this, we learned that the Pima were exposed to very high levels of lithium in their food and water quite early on, because “in the Gila River Valley, deep petroleum exploration boreholes were drilled during the early 1900’s through the thick layers of gypsum and salty clay found throughout the valley. Although oil was not found, salt brines are now discharging to the land surface through improperly sealed abandoned boreholes, and the local water quality has been degraded.” Fun!

This led us to the literature on oil-field brines, which tend to contain huge amounts of lithium. How huge? Well first we need some comparisons. In drinking water, a low level of lithium is about 0.5 ng/mL, and high levels are 100 or 200 ng/mL. In some parts of Chile, however, drinking water can have up to 700 ng/mL, and in Argentina, up to 1000 ng/mL. In seawater, lithium concentrations are usually in the range of 100 to 1000 ng/mL. The highest concentrations of all are found in extreme locations like the Dead Sea, with 14,000 ng/mL of lithium, and 24,880 ng/mL in the headwaters of one river in Chile. 

All of these are dwarfed by the levels possible in oil-field brines. Here’s a quick review from a USGS paper released in May 2021:

Produced water from oil and gas wells can have extremely high concentrations of lithium (Dresel and Rose, 2010; Blondes et al., 2018). For example, waters from shale gas wells in the U.S. had reported lithium concentrations ranging from 10 to 634,000 [ng/mL] (median 25,000 [ng/mL]) and those from conventional oil and gas wells had concentrations ranging from <10 to 1,730,000 [ng/mL] (median 5000 [ng/mL]) (Blondes et al., 2018). Lithium and associated components of such brines may be accidentally or intentionally released to the surface or groundwater in certain locations (Tasker et al., 2018; McDevitt et al., 2019).

Another point of comparison is this report from 2019 on recovering lithium from “oil and gas produced water”. This includes a number of interesting observations, including that Smackover brines from the Smackover Formation, which extends from Texas to Florida, contain between 50,000 ng/mL and 572,000 ng/mL of lithium. This source is currently being considered for exploration by the Arkansas Smackover Lithium Project.

Some of these levels are very very extremely high indeed. The highest number we reported in our original post was 24,880 ng/mL in parts of Chile. In comparison, the MEDIAN concentration in waters from shale gas wells is 25,000 ng/mL. Many of these brines have lithium concentrations in the range of 100,000 ng/mL, and some contain more than 1,000,000 ng/mL!

The USGS report also mentions that lithium concentrations are higher in arid regions. All together, this seems pretty interesting because the Middle East is especially famous for 1) being very arid and 2) having lots and lots of oil wells.

In theory, these wells should all be sealed and/or the brines should be injected deep underground where they can never contaminate anything humans come into contact with. This is important because these brines are not only as salty as hell, but also radioactive. Fortunately, the oil and natural gas industry doesn’t make mistakes.

It seems quite clear that the Pima were exposed to lithium from brines leaking out of improperly sealed boreholes, so there is at least one example of accidental exposure. And the USGS report we quoted above acknowledges that “such brines may be accidentally or intentionally released to the surface or groundwater”. Is it possible that the Middle East is especially obese because of lithium leaking in from petroleum mining, rather than (or in addition to) lithium exposure from desalination? 

If this were true, one thing we might see would be especially high rates of obesity in oil field workers. There are some indications that this is the case. One paper looked at Kuwait Oil Company employees in 1999-2000, and found that 28.8% of field workers were obese, compared to only 25.1% of office workers. Still, both of these groups were less obese than Kuwait in general at the time (about 29% obese). There are also reports like this one, this one, and this one, that suggest that obesity is a particular issue for oil and gas workers, though the reports are frustratingly short on details.

We’ll also note that some of these reports focus on offshore oil workers in particular, and it seems that offshore oil rigs get much of their water from desalination (e.g. see here, here). 

“The mining industry,” says a paper from 2017 suggested by a reader, “has the highest proportion (76%) of overweight and obese employees in Australia.” This is in comparison to 62.8% of Australian adults in general. Tsai et al. (2008) looked at “4153 Shell Oil Company employees from three refineries, one each in Texas, Louisiana, California” in the years between 1994 and 2003. “For study subjects actively employed in 1994,” they report, “the most current examination data before 1994 were used. For employees hired after 1994, data were derived from the preemployment exams.” They found that 44.6% of employees were overweight, and an additional 29.0% were obese. For comparison, the general rate of obesity in the US was about 21% in 1994 and about 28% in 2003. (Though note that all these samples are majority male, often about 80% male, which increases the mean somewhat.)

It’s easy to see how this could be a problem in the Middle East, where there’s so much oil drilling. But is it a problem elsewhere? Is it a problem in the US? And could these brines really be getting into the average person’s groundwater?

The first thing to keep in mind is that the United States is one of the top three oil producing countries in the world, and as of this writing holds the #1 spot for most oil produced per day. We produce a lot of oil, and that means we also produce a lot of brine. 

The second thing to keep in mind is that we seem to be pretty bad at not spilling our brine everywhere. You’ll recall that the USGS report we quoted above said, “lithium and associated components of such brines may be accidentally or intentionally released to the surface or groundwater in certain locations.” This sounds bad enough, but the bird’s-eye view really obscures some of the horrible details. So let’s look at some sources for these horrible details. In no particular order: 

This report from North Dakota State University, which mentions that “the average well in North Dakota produces 18 barrels of brine per barrel of oil and three barrels of brine per barrel of gas,” and goes into some detail about “commonly used methods” for responding to brine spills. 

This report “characteriz[ing] the major and trace element chemistry and isotopic ratios … of surface waters (n = 29) in areas impacted by oil and gas wastewater spills in the Bakken region of North Dakota”, which is full of interesting tidbits. For example, we can see that there appear to be more leaks pretty much every year, and we can see that in this sample 46.7% of the brine leakage by volume came from pipeline leaks. We even have lithium measurements — we can see that in “Type A Spills” (whatever those are), the first sample contained 3,244 ng/mL lithium, the second sample contained 3,490 ng/mL, the third sample contained 478 ng/mL… you get the idea.

This report of an ACME Environmental response to an event where “500 barrels of produced water and 50 barrels of oil spilled into a drainage gully which directly flowed into a creek” in Central Oklahoma. The spill was vacuumed up and then the area was flushed with freshwater until “the salinity levels reached an acceptable level.”

This article from certifiedcropadviser.org, that tries to sound optimistic, but includes a number of concerning statistics. “North Dakota’s oil boom can have a salty side-effect,” it begins. “Wastewater from oil drilling and hydraulic fracturing – or fracking – is often laden with salts and can spill, contaminating soils. In 2014, for example, 42 such brine spills per week, on average, were recorded in North Dakota.” They discuss a new method for cleaning up such spills, but the method appears to remove less than half of the salts. “Other methods,” they tell us, “attempt to push the salts below the level plant roots can reach.”

This article from Rolling Stone, which documents some cases of brine trucks crashing and spilling thousands of gallons of brine into drinking water, discusses a case where a hauling company had been dumping brine into abandoned mine shafts for six years, and mentions that “brine has even been used in commercial products sold at hardware stores and is spread on local roads as a de-icer.” If they’re spreading it on the roads, that would uh, that would be a clear reason why it’s ended up everywhere:

Radioactive oil-and-gas waste is purposely spread on roadways around the country. The industry pawns off brine — offering it for free — on rural townships that use the salty solution as a winter de-icer and, in the summertime, as a dust tamper on unpaved roads. … In 2016 alone, 11 million gallons of oil-field brine were spread on roads in Pennsylvania … Much of the brine is spread for dust control in summer, when contractors pick up the waste directly at the wellhead, says Lawson, then head to Farmington to douse roads. On a single day in August 2017, 15,300 gallons of brine were reportedly spread.

This article from the Dallas Morning News, which documents some seriously concerning spills. Really this one is just worth quoting directly. Here are some choice excerpts: 

Five years ago, a broken pipe soaked the land with as much as 420,000 gallons of wastewater, a salty drilling byproduct that killed the shrubs and grass. It was among dozens of spills that have damaged the Johnsons’ grazing lands and made them worry about their groundwater.

An Associated Press analysis of data from leading oil- and gas-producing states found more than 180 million gallons of wastewater spilled from 2009 to 2014 in incidents involving ruptured pipes, overflowing storage tanks and even deliberate dumping. There were at least 21,651 individual spills. The numbers are incomplete because many releases go unreported.

Though oil spills get more attention, wastewater spills can be more damaging. Microbes in soil eventually degrade spilled oil. Not so with wastewater — also known as brine, produced water or saltwater. Unless thoroughly cleansed, salt-saturated land dries up. Trees die. Crops cannot take root.

“Oil spills may look bad, but we know how to clean them up,” said Kerry Sublette, a University of Tulsa environmental engineer. “Brine spills are much more difficult.”

The AP obtained data from Texas, North Dakota, California, Alaska, Colorado, New Mexico, Oklahoma, Wyoming, Kansas, Utah and Montana — states that account for more than 90 percent of U.S. onshore oil production. In 2009, there were 2,470 reported spills in the 11 states; by 2014, the total was 4,643. The amount spilled doubled from 21.1 million gallons in 2009 to 43 million in 2013.

The spills usually occur as oil and gas are channeled to metal tanks for separation from the wastewater, and the water is delivered to a disposal site — usually an injection well that pumps it back underground. Pipelines, tank trucks and pits are involved.

Equipment malfunctions or human error cause most spills, according to state reports reviewed by the AP. Though no full accounting of damage exists, the scope is sketched out in a sampling of incidents:

•In North Dakota, a spill of nearly 1 million gallons in 2006 caused a massive die-off of fish and plants in the Yellowstone River and a tributary. Cleanup costs approached $2 million. Two larger spills since then scoured vegetation along an almost 2-mile stretch.

•Wastewater from pits seeped beneath a 6,000-acre cotton and nut farm near Bakersfield, Calif., and contaminated groundwater. Oil giant Aera Energy was ordered in 2009 to pay $9 million to grower Fred Starrh, who had to remove 2,000 acres from production.

•Brine leaks exceeding 40 million gallons on the Fort Peck Indian Reservation in Montana polluted a river, private wells and the municipal water system in Poplar. “It was undrinkable,” said resident Donna Whitmer. “If you shook it up, it’d look all orange.” Under a 2012 settlement, oil companies agreed to monitor the town’s water supply and pay $320,000 for improvements, including new wells.

•In Fort Stockton in West Texas, officials in February accused Bugington Energy of illegally dumping 3 million gallons of wastewater in pastures. The Middle Pecos Groundwater Conservation District levied a $130,000 fine, alleging a threat to groundwater, but the company hasn’t paid, contending the district overstepped its authority.

•A pipeline joint failure caused flooding on Don Stoker’s ranch near Snyder in West Texas in November 2012, turning his hackberry shade trees into skeletons. Vacuum trucks sucked up some saltwater and the oil company paid damages, but Stoker said his operation was in turmoil. “I had to stay out there three days and watch them while they were getting the saltwater out, to make sure they didn’t totally destroy the whole area.”

So yeah, maybe these brines are sometimes ending up in the groundwater.

No one is drinking these brines directly. For one thing, doing so would almost certainly kill you. But the lithium concentrations in these brines are so high that even a small amount leaching into your drinking water could have big consequences. 

Let’s imagine that a groundwater source containing no lithium mixes with a brine that contains 100,000 ng/mL lithium. If the brine mixes at 1%, the water source ends up containing 1,000 ng/mL lithium, higher than pretty much any lithium levels we’ve seen in drinking water. If the brine mixes at 0.1%, the water source still ends up containing about 100 ng/mL lithium, which is pretty high. But we see about 100 ng/mL in the data for the Pima (coming up below), and that’s probably from a leak from an old well, so 100 ng/mL looks pretty plausible for a brine leak. Even if it were only mixing at 0.05%, that would still be 50 ng/mL in your drinking water, which is quite a bit.

Return to Gila River Valley

A while ago, we looked at the case of the Pima people of the Gila River Valley. During our investigation, we became interested in a paper by Sievers & Cannon (1973). Sources suggested that this paper contained a lot of detail about lithium contamination in the Gila River Valley in the early ‘70s, but we weren’t able to track it down.

But in recent developments, commenter Ralph Waldo Porcupine found the original paper and sent us a copy. Thanks Ralph!

This paper is short, but contains a number of interesting details, so let’s jump right in. To begin with, the obvious pull quote is:

It is tempting to postulate that the lithium intake of Pimas may relate 1) to apparent tranquility and rarity of duodenal ulcer and 2) to relative physical inactivity and high rates of obesity and diabetes mellitus.

Native Americans have higher rates of obesity and diabetes than Caucasians, so we should expect relatively high rates among the Pima either way. However, the paper makes it clear that the rates of both diseases among the Pima are “extraordinary”, even for Native American populations at the time, “the highest ever reported”. For full context:

Most southwestern tribes greatly exceed whites in prevalence of diabetes mellitus. Observations at the PIMC reveal that the Pima tribe has the highest diabetic rate—45% of adults (12). Population studies by Bennett confirm an extraordinary frequency of diabetes mellitus in Pima Indians—the highest ever reported and 10 to 15 times that for the general population (2).

Most American Indian tribes have a very high prevalence of obesity. … The Pima tribe has an especially high rate of marked obesity.

The obvious question is, how much lithium was in their water back in the 1970s? The paper doesn’t name a specific number, but judging from Figure 1, the median lithium level in their drinking water was around 100 ng/mL. You’ll recall that this is pretty high even compared to the modern water sources we reviewed in our first post on lithium.

This figure is a little hard to read, so let’s orient you. Each “chemical constituent” is a vertical bar showing the range of concentrations in 77 samples, and a small triangle indicates the median value. We can see that the triangle for lithium is hovering around 10-1 ppm, which works out to 100 ng/mL.

The diagonal line cutting through the figure indicates the median for each constituent in municipal waters, and the horizontal location of each of the bars tells you how much of each constituent is normally in “municipal waters”. This may actually be the most important aspect of the figure, because it answers a longstanding question: back in the day, how much lithium was in the average water supply? We know that in the early 1970s the Pima were getting about 100 ng/mL, but how much was everyone else getting? 

Figure 1 suggests that back in the early 1970s, the average concentration of lithium in “municipal waters” was just slightly more than 1 ng/mL. This seems like a pretty big deal — the Pima were not just being exposed to a pretty high dose in their water, their dose was 50-100x higher than the median dose in American municipal water sources at the time! 

But we can actually do one better, because Sievers & Cannon cite their source for this diagonal line, a 1964 paper called Public water supplies of the 100 largest cities in the United States by Durfor & Becker. This whole paper is available on Google Books where you can also download a copy for yourself as a PDF.

Just like the title says, this paper looks at the public water supplies of the 100 largest cities in the United States in 1964, and looks at what was in their water. Unlike most modern sources, lithium was on their list — so amazingly, we have pretty good records of how much lithium was in American drinking water all the way back in 1964. 

The records are quite clear. The median level of lithium in their samples was only 2.0 ng/mL, 50 times less than the median for the Pima and quite low compared to modern sources.

The minimum level detected was “not detected at all”, and perusing the numbers from individual cities, this makes a lot of sense. As you flip through the 100 cities, you see that lithium levels are generally quite low — often around 1 ng/mL, but sometimes no lithium at all. 

Occasionally lithium levels are higher, especially for cities in arid locations like Arizona and Texas. The maximum level detected was 170 ng/mL (in Texas), which is a lot — but this makes sense given what we see with the Pima. We already knew that some water supplies were contaminated with lithium that far back, and it’s no surprise that these water supplies are in Arizona and Texas! In fact, while it’s hard to read from Figure 1, it looks like the maximum value recorded in the Gila River Valley was more than 170 ng/mL, probably closer to 250 ng/mL. But notably, not all water supplies from arid locations had high concentrations of lithium, not even in Texas.

This also matches the other historical sources we’ve been able to find, though most of them have a much more limited scope. 

Municipal Drinking Water and Cardiovascular Death Rates from 1966 looked at water from 88 cities. They don’t give much detail, but suggest that the lithium levels in city drinking water were somewhere in the range of 16.8 ng/mL to 5.3 ng/mL. This may seem maddeningly vague to you — it also seems vague to us, so we’re more inclined to trust the 100-cities paper from above, since it is much clearer and provides more detail.

This paper from 1970 looks at lithium levels in the drinking water of 27 Texas communities in summer and fall 1968. They found that lithium was present in measurable amounts in the drinking water of 22 of the 27 communities, and found levels above 11 ng/mL in 15 of the 27. Matching what we saw in the 100-cities paper, some sources were found to contain as much as 160 ng/mL. Texas wasn’t universally contaminated back then, but like Arizona, it had some extreme cases.

Mood and Lithium in Drinking Water from 1976 looked at 384 drinking water samples from Washington County, Maryland. They found that 37.5% of the samples had lithium levels below 1.9 ng/mL and 75.2% had lithium levels below 5.9 ng/mL. About 90% of samples contained less than 10 ng/mL, and the highest recorded level was a mere 32 ng/mL.

Wolfberries

Sievers & Cannon also found that trace elements in the groundwater accumulate in some plants but not in others. Lithium in particular seems to concentrate in specific plants to an incredible degree:

Vegetation is low in most trace elements but some food plants concentrate particular ones. Mesquite beans accumulate strontium; cabbage accumulates sulfate; beans concentrate molybdenum and wolfberry contains an extraordinary 1120 ppm lithium in the dry weight.

Figure 2 shows the chemical content of produce and plants that grow on the sandy alluvium of the Gila River. This vegetation has low concentrations of most trace metals but has high levels of lithium. The median level of lithium for Pima Reservation plants is 1.4 ppm (general average elsewhere, 1.0 ppm) but the mean is much higher due to abnormal accumulation by the wolfberry (or squawberry; Lycium californium).

High concentrations of particular elements in certain vegetations become important to human health if the plants are consumed in quantity. Some unusual accumulations in edible plants are shown in Table I. The wolfberry, with an extraordinary lithium content of 1120 ppm, is used occasionally for jelly. 

They’re not kidding when they say “extraordinary” — 1,120 ppm is equivalent to 1,120,000 ng/mL! 

Let’s unpack this a little. Elsewhere in the paper they say, “Pima Indians drink about 1.6 liters per day (9) of hard water.” Since the level of lithium in the water seems to have been around 100 ng/mL, which is the same as 100 µg/L, this suggests that they got about 160 µg of lithium per day from their drinking water.

Lycium californium

In comparison, they say that the wolfberry is “occasionally” used for jelly. Let’s say that this means an average of one tablespoon of wolfberry jelly per day, and let’s assume that the dose is the same in the jelly as it is in the wolfberry itself. A tablespoon is about 14 milliliters, so with a lithium concentration of 1,120,000 ng/mL, they would be getting 15,680,000 ng or 15,680 µg of lithium from the jelly. If these numbers are anywhere near correct, then the Pima were getting around 100 times more lithium from wolfberry jelly than directly from their drinking water. 

This might help us square the fact that lithium seems to be associated with weight gain, but the trace amounts in water are so much smaller than the therapeutic doses given by psychiatrists. By the calculations we did in our first post on lithium, the “minimum efficacious” therapeutic dose is about 600,000 µg per day, which would take about 40 tablespoons of wolfberry jelly (2 ½ cups, or slightly more than one jar of jelly). Alternatively, 3,750 liters of Gila River Valley water. It would be hard to drink that much water, but you could definitely get a therapeutic dose if you ate enough jelly. We don’t know what dose of lithium you need before the weight gain starts kicking in, but whatever it is, you can get there a lot faster if lithium is concentrating in the plants you eat.

Let’s imagine that corn accumulates lithium similarly to the wolfberry. (Just to be clear, this is purely a hypothetical — we have no reason to suspect corn in particular.) If your corn is irrigated with pure water containing no lithium, then the corn also contains no lithium. But if the corn is irrigated with water containing 100 ng/mL lithium, like the water in the Gila River Valley, then the corn accumulates a lot of lithium, maybe as much as 1,120 ppm / 1,120,000 ng/mL like the wolfberry does. Certain corn products might contain even more, if they concentrate the lithium further. If the corn is irrigated with water somewhere in between those two doses, then the corn ends up containing some lithium, but probably not as much.

This is complicated even further by the fact that (again just picking on corn as an example, this is true of most crops) there are many different varieties of corn. We treat them all as simply “corn”, but there can be important differences between different varieties, and some varieties might end up concentrating more lithium than others. This means that it’s impossible or sort of even meaningless to ask a question like, “how much lithium is in corn?” Well, what kind of corn? Where is it from? How much lithium was the irrigation water when it was being grown? 

So in the future, we need to keep an eye out for plants that might be concentrating lithium. Even if they are only exposed to trace amounts in their water, they could end up concentrating levels around 10,000 times higher! We grow a lot of crops — corn, soybeans, wheat, grapes, rice, almonds, peanuts, apples, etc. — which of these concentrate lithium from their water? Which are commonly exposed? 

This complicates things somewhat, but the good news is that if this is the case, we wouldn’t have to worry too much about lithium in our actual drinking water. Instead, we would want to make sure that the water we use to irrigate crops is as low in lithium as possible, which seems much more manageable.


[Next Time: WELL WELL WELL]


A Chemical Hunger – Interlude F: Demographics

[PART I – MYSTERIES]
[PART II – CURRENT THEORIES OF OBESITY ARE INADEQUATE]
[PART III – ENVIRONMENTAL CONTAMINANTS]
[INTERLUDE A – CICO KILLER, QU’EST-CE QUE C’EST?]
[PART IV – CRITERIA]
[PART V – LIVESTOCK ANTIBIOTICS]
[INTERLUDE B – THE NUTRIENT SLUDGE DIET]
[PART VI – PFAS]
[PART VII – LITHIUM]
[INTERLUDE C – HIGHLIGHTS FROM THE REDDIT COMMENTS]
[INTERLUDE D – GLYPHOSATE (AKA THE ACTIVE INGREDIENT IN ROUNDUP)]
[INTERLUDE E – BAD SEEDS]
[PART VIII – PARADOXICAL REACTIONS]
[PART IX – ANOREXIA IN ANIMALS]

Income

The stereotype is that poor people are more obese than rich people, but rich countries are definitely more obese on average than poor countries:

This same trend of wealth being related to obesity is also mirrored within many countries. In poor countries, upper-class people are generally more likely to be obese than lower-class people. For example, in India rich people are fatter than poor people.

We see that the general pattern between countries is that wealth is associated with obesity, and we see the pattern within most poor countries is also that wealth is associated with obesity. Given this, it would be kind of surprising if the relationship ran the other way around in wealthy countries. 

Still, common-sense beliefs say that — in America at least — poor people are more obese than rich people, maybe a lot more obese. But evidence for this idea is pretty elusive. 

The National Health and Nutrition Examination Survey (NHANES) is an ongoing project by the CDC where every year they take a nationally representative sample of about 5,000 Americans and collect a bunch of information about their health and lifestyle and so on. In 2010 a NCHS team led by Cynthia Ogden examined the NHANES data from 2005-2008. They wanted to find out if there was any relationship between socioeconomic status and obesity, the exact same question we have in this post.

The results of their analysis were mixed, but there certainly wasn’t a strong relationship between socioeconomic status and obesity. Their key findings were: 

Among men, obesity prevalence is generally similar at all income levels, however, among non-Hispanic black and Mexican-American men those with higher income are more likely to be obese than those with low income.

Higher income women are less likely to be obese than low income women, but most obese women are not low income.

There is no significant trend between obesity and education among men. Among women, however, there is a trend, those with college degrees are less likely to be obese compared with less educated women.

Between 1988–1994 and 2007–2008 the prevalence of obesity increased in adults at all income and education levels.

Cynthia Ogden got to do it again in 2017, this time looking at the NHANES data from 2011-2014, trying to figure out the same thing. Again the picture was complicated — in some groups there is a relationship between socioeconomic status and obesity, but it sure ain’t universal. This time her team concluded:

Obesity prevalence patterns by income vary between women and men and by race/Hispanic origin. The prevalence of obesity decreased with increasing income in women (from 45.2% to 29.7%), but there was no difference in obesity prevalence between the lowest (31.5%) and highest (32.6%) income groups among men. Moreover, obesity prevalence was lower among college graduates than among persons with less education for non-Hispanic white women and men, non-Hispanic black women, and Hispanic women, but not for non-Hispanic Asian women and men or non-Hispanic black or Hispanic men. The association between obesity and income or educational level is complex and differs by sex, and race/non-Hispanic origin.

If you don’t trust us but do trust the Washington Post, here’s their 2018 article on Ogden’s work.

The studies that do find a relationship between income and obesity tend to qualify it pretty heavily. For example, this paper from 2018 finds a relationship between obesity and income in data from 2015, but not in data from 1990. This suggests that any income-obesity connection, if it exists, is pretty new, and this matches the NHANES analysis above, which found some evidence for a connection 2011-2014 but almost no evidence 2005-2008. Here’s a pull quote and relevant figure:

Whereas by 2015 these inverse correlations were strong, these correlations were non-existent as recently as 1990. The inverse correlations have evolved steadily over recent decades, and we present equations for their time evolution since 1990.

Another qualifier can be found in this meta-analysis from 2018. This paper argues that while there seems to be a relationship between income and obesity, it’s not that being poor makes you obese, it’s that being obese makes you poor. “Obesity is considered a cause for lower income,” they say, “when obese people drift into lower-income jobs due to labour–market discrimination and public stigmatisation.” 

Anyone who is familiar with how we treat obese people should find this theory plausible. But we don’t even have to bring discrimination into it — being obese can lead to fatigue and health complications, both of which might hurt your ability to find or keep a good job. 

This may explain why Cynthia Ogden found a relationship between income and obesity for women but not for men. It’s not that rich women tend to stay thin; it’s that thin women tend to become rich. A thin woman will get better job offers, is more likely to find a wealthy partner, is more likely to find a partner quickly, etc. Meanwhile, there’s a double standard for how men are expected to look, and so being overweight or even obese hurts a man’s financial success much less. This kind of discrimination could easily lead to the differences we see.

But the biggest qualifier is the relationship between race and income. If you’re at all familiar with race in America, you’ll know that white people make more money, have more opportunities, etc. than black people do. Black Americans also have slightly higher rates of obesity. The NHANES data we mentioned earlier contain race data and are publicly available, so we decided to take a look. In particular, we now have complete data up to 2017-2018, so we decided to update the analysis.

Sure enough, when we look at the correlation between BMI and household income, we see a small negative relationship, where people with more income weigh less. But we have to emphasize, this relationship is MEGA WEAK, only r = -.037. Another way to put this is that household income explains only one-tenth of a percent of the variance in BMI! Because the sample size is so huge, this is statistically significant — but not by much, p = .011. And as soon as we control for race, the effect of income disappears entirely.

We see the same thing with the relationship between BMI and family income. A super weak relationship of only r = -.031, explaining only 0.07% of the variance in BMI, p = .032. As soon as we control for race, the effect of income disappears.

We see the same thing with the relationship between BMI and education. Weak-ass correlation, r = -032, p = .022, totally vanishes as soon as we control for race. 

Any income effect needs to take into account the fact that African-Americans have higher BMIs and make less than whites do, and the fact that Asian-Americans have lower BMIs and make slightly more than whites do.

We don’t see much of a connection between income and obesity. If there is a link, it’s super weak and/or super idiosyncratic. Even if the connection exists, it could easily be that being obese makes you poorer, not that being poor makes you obese. 

Race

Race actually doesn’t explain all that much about BMI either. A simple model shows that in the 2017-2018 data at least, race/ethnicity explains only 4.5% of the variance in BMI. The biggest effect isn’t that African-Americans are heavier than average, it’s that Asian-Americans are MUCH leaner than everyone else. In this sample, 42% of whites are obese (BMI > 30), 49% of African-Americans are obese, but only 16% of Asian-Americans are obese! 

On the topic of race, some readers have tried to argue that race can explain the altitude and/or watershed effects we see in the Continental United States. But we don’t think that’s the case, so let’s take a closer look. Here’s the updated map based on data from 2019:

US Adults

This map is for all adults, and things have not changed much in 2019. Colorado is still the leanest state; the states along the Mississippi river are still among the most obese. Now, it’s true that a lot of African-Americans do live in the south. But race can’t explain this because the effect is pretty similar for all races. 

For non-hispanic white Americans, Colorado is still one of the leanest states (second-leanest after Hawaii) and states like Mississippi are still the most obese:

Non-Hispanic White Adults

For non-hispanic black Americans, Colorado is still one of the leanest states, and while you can’t see it on this map because the CDC goofed with the ranges, states like Mississippi and Alabama are still the most obese: 

Non-Hispanic Black Adults

In fact, here’s a hasty photoshop with extended percentile categories: 

Non-Hispanic Black Adults

If the overall altitude pattern were the result of race, we wouldn’t see the same pattern for both white and black and Americans — but we do, so it isn’t.


[Next Time: Li+]