LOSE 10.6 POUNDS in FOUR WEEKS with this ONE WEIRD TRICK Discovered by Local Slime Hive Mind! Doctors GRUDGINGLY RESPECT Them, Hope to Become Friends

The first time we mentioned the potato diet, in Part III of our series A Chemical Hunger, we shared the story of Chris Voigt, the Executive Director of the Washington State Potatoes Commission, who lost 21 pounds on a 60-day potato diet. By Part X of the series, we started to wonder if someone should maybe run a study, and see if the potato diet really works as well as all that. 

For those of you who are just joining us, the potato diet is a diet where you try to get most of your calories (>95%) from potatoes. You can have drinks like coffee and tea. You can season the potatoes with salt, spices, and whatever hot sauce you want. You can even cook with oil. The only thing we asked people to entirely avoid was dairy (see original post for details). 

Does this mean you can eat fries for every meal? It does, and some people came pretty close to that ideal. See for example, this post:

I have never heard of a diet that allows you to eat french fries for all three meals, and I did just that on a couple of days. It rocked.

Or:

But we’re getting ahead of ourselves.

1. Background

We announced the first Potato Diet Community Trial on April 29th 2022, in a post titled, “Potato Diet Community Trial: Sign up Now, lol”. We announced the trial on twitter, and on the SSC/ACX subreddit. Signups opened the same day. We asked people to try the diet for four weeks

As people signed up and started sharing their experiences, we made a twitter thread of live-ish updates. In this thread you can read anecdotes shared on twitter that aren’t found in the official study data.

To sign up for the study, participants filled out a google form (PDF available in the repository; see below) of demographic information, then over the next four weeks, recorded their data on a copy of a google sheet that we provided.

Two hundred and twenty people filled out the signup form before we closed the study. As far as we can tell, most signups came from twitter, reddit, and word-of-mouth. We actually didn’t ask about this, probably should have. Whoops.

Signups closed on June 3rd, 2022, four weeks after we announced the diet.

We downloaded people’s data when they sent us an email to formally close the study. Anyone who didn’t send us an email to officially close the study, we grabbed their data (if any) in the last days before closing the study. The dataset we’ll be examining today represents the state of the data as of midnight on Friday, July 1st, 2022, four weeks after we closed signups and eight weeks after we started collecting data.

Raw data, the analysis script, and study materials are available on the OSF. We decided to store our data and materials there, since that repository is well-supported and we expect it to stay available for a long time. The organized data is “SMTM Potato Diet Community Trial Main Form.csv”; the script is called “SMTM Potato Diet Community Trial 1 Analysis.R”; and the raw data is in a folder called “Potato Raw Dato” 

This dataset is very rich — we certainly haven’t found everything there is to find in these data. A number of people measured other variables (like blood pressure, resting heart rate, and sleep) and we haven’t looked at those data in any systematic way.

Also there is a lot of room for new findings in coding the free-response data. You could, for example, go through and try to code what kind of oil(s) people are using, and see if people who use different oils lose different amounts of weight, find the diet easier, etc.

We really look forward to seeing other people do their own analyses. Send them our way, we’ll link them or do a roundup post or a meta-analysis or something.  

Two participants asked that we not share their data publicly. But if you’re following along at home you should still get the same results as we do, because those two participants seem to have entered no data.

If you have advice about what to do differently next time, we are interested in hearing that. But if you don’t like something about the study design and just want to gripe — run your own study!

2. Variables

Let’s start with a recap of the study variables.

Our demographic variables are — age, ethnicity, height in inches, local ZIP or postal code, current country of residence, profession, and reported sex. 

Sex was initially reported as “Male”, “Female”, or a free-response “other” field. A few participants reported being trans or nonbinary, so we created two variables, “Chromosomal Sex (estimated)” and “Hormonal Profile (estimated)” where we estimated their chromosomal sex and hormonal profile, respectively, based off of free report data. As the names suggest, these are just estimates. We don’t actually have access to your chromosomes.

This is in case there end up being major endocrinological effects. It seems like there could be sex differences in the potato diet because there are clear sex differences in obesity and in anorexia, which we think may be related.

On their datasheets, participants were asked to record a slate of variables every day. Our main daily variables are — daily weight in pounds; notes for each day; energy for each day on a scale from 1-7, where higher numbers are more energy; mood for each day on a scale from 1-7, where higher numbers are a better mood; and ease of the diet for each day on a scale from 1-7, where higher numbers are finding the diet easier.

We also had a field where participants could record whether or not they broke the diet (eating something substantial other than potatoes) each day. If they stuck to the diet we asked them to put a 0 in this field, if they broke the diet we asked them to put a 1. This is a bit of a mouthful so we will often colloquially refer to these as “cheat days”.

3. Demographics

A total of 220 people submitted the initial form.

Of those, 11 people filled out the signup form incorrectly in such a way that we couldn’t sign them up (they didn’t enter an email, didn’t indicate critical data such as height, etc.). We enrolled the remaining 209 people in the study.

Let’s take a look at the demographics of the people who enrolled: 

  • Age ranged from 18 to 69, with a mean of 35.2 and a median of 35. 
  • Reported sex was 50 female, 151 male, 7 other entries (e.g. “non-binary”, “AFAB on testosterone so idk how you wanna categorise that”), and one person who didn’t respond.
  • Based on this, we estimated 51 XX participants and 156 XY participants; and we estimated 53 people with a more “female” hormonal profile and 153 people with a more “male” hormonal profile.
  • Reported ethnicity was 185 white, 10 Asian, 2 Indian, and 4 more specific entries (e.g. Latin, Indonesian, etc.). Everyone else who reported ethnicity reported being a mix (e.g. “Brazilian. Mostly white, kinda mixed though.”; “German/Vietnamese/Anglo-Saxon“).
  • Participants mostly came from the Anglosphere and Europe: 133 US, 17 UK, 17 Canada, 7 Germany, 6 Australia, 4 Ireland, 3 Sweden, 2 Poland, 2 India, 2 Hungary, 2 France, and several singletons from places like Finland, Mexico, Serbia, Brazil, and “Magyarorsz√°g” [sic] which we think is also Hungary.
  • Profession is hard to code since it’s so diverse, but it looks like the biggest groups were software engineers/programmers, grad students, various scientists and academics, and game designers.

Out of the 209 people signed up, 5 started the diet late for one reason or another, and were still in the middle of the four weeks when we closed data collection on July 1st. We let them keep going and looked at the 204 people remaining.

Of these 204 participants, 44 never entered any data onto their datasheet. As far as we can tell, they just never got around to starting the diet — we certainly didn’t get any data from them.

This leaves us with a total of 160 people who entered some data. Of those 160:

  • Age ranged from 19 to 61, with a mean of 36.0 and a median of 35.5. 
  • Reported sex was 29 female, 124 male, 6 other entries, and one person who didn’t respond.
  • Based on this, we estimated 30 XX participants and 129 XY participants; and we estimated 32 people with a more “female” hormonal profile and 126 people with a more “male” hormonal profile.
  • Reported ethnicity was 145 white, 5 Asian, and 10 other entries like “Polish” or “Japanese/ Hispanic”.
  • Participants were still largely Americans: 104 US, 13 Canada, 12 UK, 6 Germany, 5 Australia, 3 Sweden, 2 Poland, 2 Ireland, 2 Hungary, and one each to a number of others.
  • Again the most common profession is software engineer / programmer, with various research jobs and IT jobs behind it.

Of this group, 35 people formally closed the diet early by sending us an email. We coded the reason they dropped out based on their comments.

One we coded as dropping out because of boredom (“Overall not a difficult diet, but I decided to end it because I was getting pretty bored of potatoes.”).

Two reported stopping because they got sick, which we coded as illness. This isn’t potato-related illness, to be clear — one had a throat infection and the other got shingles.

Six reported stopping because of a schedule conflict, coded as schedule. Some of them specifically said they could have kept going otherwise, like participant 66959098: 

I am ending my diet at 21 days instead of at 28. This is mostly a scheduling issue, having family visiting next week and would like to go out and eat with them. I believe I could have made the four weeks without too much trouble otherwise, and I may even go back on the diet again sometime later. 

The remaining 27 early closures reported stopping because they found the diet really difficult in one way or another, and we coded this as difficulty. For example, participant 29957259: 

I threw in the towel on the potato diet six days in. The first few days were easy for me, but it eventually grew much more difficult. I found myself thinking about food way more than someone whose next meal was planned should have.

Clearly the potato diet really does not work for some people! More on this later.

Another 57 people made it partway to 4 weeks but didn’t officially close the study, and we don’t know why. We went back and forth on what to call this, since we don’t know why they stopped reporting their data, and we wanted the coding to sound as neutral as possible. In the end we coded them as dropped

These participants don’t seem to have just flaked out. Many of them made it a long way. Several people made it past two weeks, and two people made it all the way to day 27:

We’re going to try to stay agnostic about what happened in these cases, because these participants didn’t give us a clear reason why they dropped out. But we can also make some educated guesses. 

Some people clearly dropped out because the diet was too difficult. For example, participant 31554252’s last comment was: 

Finding it very difficult to keep going—just very sick of potatoes

But other people don’t seem to have found the diet difficult, and probably dropped out for other reasons. For example, participant 71309629 appears to have dropped out because of illness. They said, “Got sick, will update later” on the last day they entered data, and haven’t updated since. We hope you’re ok!

Similarly, participant 97388755 could probably be coded as ending for schedule reasons. She said in the comments:

I renounce potato. I’m moving house and the chocolate cravings and trying to make potatoes for 2 people is a pain in the ass.

It might be interesting to go back and try to re-code all the dropped trials, figure out why they stopped the diet, but not today.

Since we asked everyone how easy the diet was, we can also look at the ease they reported on the last day they gave us a weight measurement (though a few people stopped reporting ease before then). As a reminder, higher numbers / more to the right is more easy:

Some people definitely were finding this difficult when they stopped, and it’s reasonable to think that the people who gave a 1 or 2 on the last day stopped because they couldn’t stand it.

But plenty of people who dropped out without telling us why rated diet ease at a 6 or a 7. The modal value is clearly 5! So while some of these dropped trials are because of difficulty, others presumably dropped out for other reasons: they had to go on a trip, they had a family emergency, they got sick with COVID, etc.

The diet protocol in the original post asked for 29 days of weight measurement. The last measurement would be on the morning of the 29th day, giving us 28 days of complete data.

But we fucked up on the data recording sheet and made it seem like people should record only up to day 28. Most people followed instructions — they gave us 28 days of data, then stopped. This is our fault, we messed up.

whoops

To keep things standard, we used each person’s data at day 28 as their final day of data. For people who went past 28 days (a number of people kept collecting their data and/or kept going with the diet), we treated them as if they did 28 days exactly. We used their weight on day 28 as their final weight, counted their number of cheat days up to day 28, etc. 

At some point it might be interesting to go back and look at the data of people who did 29+ days, but again, not a project for today.

This is technically 27 full days of potato diet, since the measurement for day 28 is the MORNING of day 28. But tiny differences like this are like, eh, who cares. If the effect is substantial at all, it won’t matter anyways. Anyways, henceforth this span will be referred to as “four weeks”.

One participant (40207077) didn’t report his weight for day 28, so we used his day 29 data. Coincidentally this is also the person who lost the least weight over the 4 weeks. If you kicked him out because he often forgot to report his weight, average weight lost on the diet would be even greater.

Anyways, 64 people made it the full four weeks and completed the potato diet. Let’s review their demographics: 

  • Age ranged from 19 to 61, with a mean of 36.7 and a median of 36.5.
  • For sex, 5 reported their sex as female, 54 male, 4 other entries, and one nonresponse.
  • We estimated 6 XX and 57 XY; and we estimated 7 people with a more “female” hormonal profile and 56 people with a more “male” hormonal profile.
  • For ethnicity, 57 were white, 4 Asian, 1 Polish, 1 “several of the above”, and 1 “half-asian, half-white”.
  • Participants reported being in the following countries: 46 US, 4 Canada, 2 each in UK, Germany, and Ireland, and several singletons.

Racial diversity is definitely a major limitation of this study, especially since obesity differs a lot across ethnicities. The diet could easily work half as well, or not at all, for African-Americans. Or for all we know, it could work twice as well. The results we have so far look really promising (as you’ll see in a minute), and we think it’s important to see if they’ll generalize. So if we run another potato diet study, and you’re part of a racial group that isn’t well-represented in this study (i.e. if you are not white), your data could contribute a lot!

Retention

The first question is, what is the retention rate for the potato diet? Well, it depends how you slice it.

If you want to be maximally strict, 64 people made it four weeks out of 209 enrolled, so 30.6%.

Not too bad. This is a kind of extreme diet, and it would be pretty impressive even if only 30% of people made it to the end. Frankly, we’re impressed so many people signed up in the first place. 

But we think this is too low, in fact. Only 209 people were enrolled in the study, and because some trials were ongoing at closing, only 204 had potentially available results. 64 out of 204 would give us a retention rate of 31.4%.

But of those 204 people, 44 never entered any data. There’s a good chance most of these people never started the study, and shouldn’t be considered dropouts. In this case, retention is out of 160, and 64 out of 160 is 40.0%.

If you wanted to be maximally permissive, you could only count the dropouts who sent us an email to formally close the study. This gives us a total of 102 people, and makes the retention rate 64 out of 102 people, which is 62.7%

(Actually if you wanted to be super maximally permissive, you could only count people as dropouts if they explicitly stopped because of finding the diet difficult. Then retention would be 64 out of 91, or 70.3%.)

So we think the retention rate is somewhere between 40.0% and 62.7%, though you could make a case that the retention rate is as low as 30%. In any case, the idea that between one-third and two-thirds of people get to the end of four weeks on basically only potatoes is pretty wild.

Of course, a hard cutoff doesn’t make much sense. Most people made it some number of days between 1 and 28. Heck, five people ended the potato diet on day 27! 

When we look at the number of days people made it to, we do seem to see two (or maybe three?) clear groups: 

Clearly the most common outcome is to make it the full four weeks. The next most common is to drop out in the first week or so. 

But there’s another bump near the end of the third week, and that seems kind of interesting, especially because some people mentioned hitting a wall at around three weeks. For example, participant 23300304 stopped on day 22 and reported: 

Initially I found the diet extremely easy… However, quite suddenly after about three weeks I started feeling unwell, with low level nausea, headaches and general tiredness. Initially I thought I was falling ill. But I didn’t really show any specific symptoms of illness. After a few days I was feeling so bad I decided to end the diet. I felt better by the end of the first day eating my usual diet again.

Similarly, things were going great for participant 63746180. They had already lost about 10 pounds over 18 days and seemed to be enjoying it. But then:

My reason for ending is that I was hungry to the point of headache and dizziness, but could not force myself to eat a potato.  It was a weird experience, my body was screaming for food but I couldn’t swallow a potato.  I went from pretty happy with eating potatoes to completely unwilling to eat a potato in the span of a day. 

So there might be something interesting with people hitting a wall at three weeks or so. However, as you can see from the histogram, it was a minority of participants.

4. Weight Loss

Of the participants who made it four weeks, one lost 0 lbs (participant 40207077). Everyone else lost more than that.

The mean amount lost was 10.6 lbs, and the median was 10.0 lbs. The 99% confidence interval on the mean is 12.1 to 9.1 lbs of weight loss. The greatest amount of weight lost was 24.0 lbs, from participant 74282722.

We thought this might end up being bimodal — some people going into potato mode and other people just struggling through — but it looks pretty normally distributed around 10 lbs. There’s sort of a little spike around 15 lbs maybe.

We can also look at individual time series data:

And here’s the average over time: 

We can also do these plots as percent weight change, but you’re gonna be pretty disappointed, they look almost exactly the same: 

Actually Why Not Just Look at All The Data

Like we mentioned above, a hard cutoff doesn’t make much sense. Let’s just look at all the data.

Here’s weight change by total number of days completed on the potato diet for all participants who entered data: 

Seems like a clear trend. And it makes sense to us; if you make it 22 days on the diet, you get about 3/4 the benefit of making it the full four weeks on the diet.

We can see that only two people reported a net weight gain on their diet, and of only 2.3 and 0.1 lbs. In addition, twelve people did report exactly no weight change — though nine of them only entered data for day 1, so they couldn’t have lost any weight. It doesn’t look like the potato diet can go “wrong” and you can gain a lot of weight. 

We want to point out that the person who lost the MOST weight (24.8 lbs; participant 71319394) actually ended the diet on day 27 — “I am calling it done a day early, but I think it has gone really well for me and was really easy for about 3 weeks.” — so he doesn’t appear in the “completed four weeks” analyses.

Also note the outlier, participant 89861395, who reported losing 41.6 lbs in 18 days. We assume this is an error, in part because he reported being 296.8 lbs on day 17, and then being 267.0 lbs on day 18, after which point he recorded no further data. It seems unlikely that he lost 29.8 overnight just before closing the study. Probably he lost 11.8 lbs total before stopping, the number suggested by his weigh-in on day 17. 

When we plot this over time, it becomes clear that it didn’t really matter if people “finished” or not:

People lost about a half a pound a day on average, though with quite a bit of variation (we did kick out that one measurement claiming to lose 29.8 lbs in a single day, since it’s probably a typo). There appears to be no meaningful difference in the daily weight loss of people who did and didn’t make it the full four weeks. In fact, people who made it the full four weeks had slightly lower average weight loss, a mean of 0.41 lbs a day compared to a mean of 0.55 lbs a day in people who didn’t make it four weeks.

Here’s how the potato diet COULD have worked: some people don’t lose weight, so they quit, and other people do lose weight, so they keep going. If that happened, we would see a really successful group of people who made it to four weeks and lost a bunch of weight, and another group of dropouts who lost little or no weight. But that’s not what happened. Almost everybody who tried the diet seemed to lose about the same amount of weight per day. So something causes the dropouts to drop out, but it’s not that the diet doesn’t work for them. The diet works for pretty much everyone, at least for however long they can stick to it. But then, for unclear reasons, some people hit a wall.

You might want to know, how much weight will I lose if I don’t make it four weeks? How much weight will I lose if I start and keep going until I hit a wall? Well, it depends on how long it takes for you to hit that wall, but we can talk about what you can expect on average.

People who entered at least two weight measurements but didn’t make it four weeks lost an average of 5.5 lbs, with a median of 4.2 lbs and a maximum weight loss of 24.8 lbs.

If we pool everyone who entered at least two weight measurements, they lost an average of 7.7 lbs, with a median of 6.9 lbs and a maximum weight loss of 24.8 lbs.

So strictly speaking, if you start the diet, based on these data you should expect to lose 7.7 lbs on average. If you fully expect to make it four weeks for some reason, then you should expect to lose 10.6 lbs; and if you for some reason are sure you will NOT make it four weeks, you should still expect to lose 5.5 lbs on average.

Finally, it’s worth noting the subjective element. Just look at how happy many participants were with the diet:

I lost almost 25 lbs and have felt great throughout. I have been sleeping fine and having plenty of energy. 

Well I thought that was super fun and I’m happy to have done it. Lost about 16 pounds. … Anyway, I had a blast. I would consider doing potatoes again in the future. This is probably the thinnest I’ve been in at least 15 years or so.

Thank you for doing this. I’ve found it very valuable and think potatoes will continue to play a role in my health.

Thanks for organizing this!

Thanks for the opportunity to do this, it’s been an interesting ride, and I did lose weight. 

Hi! Thanks for doing such a great study!

I felt really good during the diet. This is the best I’ve felt in several years. My clothes fit better, I’m not as tired all the time, my back and knee has felt better than they had for the last 6 months.

I did it. One month, mostly potato. And I am really happy I came across your tweet about this crazy and kinda dumb idea for a study. Over this past month I lost pretty much exactly 10 kg / 22 lbs. It felt easy most of the time, and I feel fantastic. My goal of a BMI < 30 is still 20 kg away, but that feels achievable for the first time I can remember.

Thanks for running this experiment! It was very fun, and I wish there were more things like this going on in the world. 

Thank you so much for including me in your study! It has been a huge boon to me personally and it was nice to be able to contribute to science!

I had a good time overall with the diet, and ultimately I think the viscerally-felt revelation that an adjustment to my diet gives me far greater mental clarity will be long-term life-changing. Thanks for that.

By BMI Bracket

We can also break down these same analyses by starting BMI bracket.

None of our participants were “underweight” (BMI < 18.5) to start. Of the people who entered any data, 27 had starting BMIs between 18.5 and 25, 66 were BMI 25-30, 43 were BMI 30-35, 17 were BMI 35-40, and 7 had starting BMIs above 40. 

Retention by Starting BMI

Overall, it doesn’t seem like retention is much better or worse for people with higher or lower starting BMIs. This is a little surprising — you might expect leaner people to drop out more, since they have less to lose. Or you might expect heavier people to drop out more, because they presumably have a harder time losing weight. But we don’t really see much evidence for either.

We can also plot these variables to get a better look. We’ll adapt the colors from this uh lovely diagram by the CDC:

Again, we see pretty similar retention across groups. This plot shows the days completed, out of 28, by people in each bracket. Vertical lines are medians:

People with a BMI < 25 do seem to be more likely to drop out on the first day, but that might just be noise.  

Weight Loss

And here’s weight loss for people who completed the four weeks by BMI bracket. Again, vertical lines are medians:

As expected, people with higher starting BMIs lost more weight. We can also show this as time series: 

What is not expected, and what we find quite surprising, is that people who started the study with a BMI of less than 25 (what they call “normal weight”) often lost weight as well. And not just a little weight, a decent amount of weight. Median weight loss for BMI < 25 was actually 7.3 lbs! 

This becomes more striking if we break it out as percent body weight lost: 

A really interesting example comes from Nicky Case, who shared her experience as a, uh, a case study

I was already “normal BMI”, but signed up coz fighting science’s ivory tower with potato is funny

(Also the diet may help with anxiety/depression. And it’s  good to see if there’s a “floor”, i.e., it only works for “high” BMIs but not “normal” BMI)

I started 5’8″, 137lb. Already middle-low range of “normal BMI”.

I’m now on Day 19 of “try to eat only potato, but as much as you want” – and I’ve cheated on 8/19 (40%!) of the days – I’m *still* losing roughly 2.2lb/1kg a week(?!) 

(& from SMTM’s early data, “losing roughly 2.2lb/1kg a week” seems to be common for the volunteers so far: https://mobile.twitter.com/mold_time/status/1530527527680327680… )

(It *is* really weird, tho, that I’m getting about the same effect size even when I already started “normal” BMI *and am cheating a lot*)

All of Nicky’s feedback is great, see it in the thread.

Nicky isn’t the only example of someone who started with a low BMI and saw it go even lower. There’s also participant 89852176, who made it the full four weeks: 

I went into it not feeling like I had a lot of weight to lose (starting weight/BMI 143/21.1), but my wife and I started together at the same time, and she had more to lose. In addition, I was hoping for an improvement in my blood pressure (typically 120ish/85ish); I haven’t seen a significant change there. However, I did see significant weight loss; my ending weight/BMI (this morning, day 29) was 132.4/19.5.

Naturally we are wondering why people who are already at the bottom end of the range for “normal weight” are losing weight on this diet. Two possibilities come to mind.

One possibility is that the natural human BMI is really around 19. These days we think of 22 or 23 as pretty normal, but that seems to be the high end for hunter-gatherers. 

For example, this review says:

Walker and colleagues compiled body size and life history data for more than 20 small-scales societies. They report mean ± SD body mass indices (BMI) of 21.7 ± 2.9 for n = 21 adult female cohorts and 22.2 ± 2.7 for n = 20 male cohorts, mid-range within the WHO category for ‘normal weight’ (BMI: 18.5–24.9; WHO). … within the Hadza hunter-gatherer population, we find little evidence of overweight or obesity. BMI for both men (20.0 ± 1.7, n = 84) and women (20.3 ± 2.4, n = 108) 20 to 81 years remains essentially constant throughout adulthood and similar between sexes (Fig. 1). 

And Staffan Lindeberg, in his book Food and Western Disease, says: 

The average BMI at 40 years of age [for hunter-gatherers] has typically been around 20 kg/m2 for men and 19 kg/m2 for women. After the age of 40, the BMI for both sexes drops because muscle mass and water content decrease with age and because fat is not increasingly accumulated.

So if the potato diet is resetting your lipostat (if you’re not familiar, we describe this below) and sending your BMI towards what it would have been if you hadn’t been raised in a modern environment, maybe your BMI is headed towards the hunter-gatherer range of 19-20. 

It doesn’t seem like potatoes would send your BMI any lower, in part because there have been cultures that lived almost entirely on potatoes and they did not all drop to BMI 10 and die. For example, take this account of the Irish, from Adam Smith of all people (h/t Dwarkesh Patel):

Experience would seem to shew, that the food of the common people in Scotland is not so suitable to the human constitution as that of their neighbours of the same rank in England. But it seems to be otherwise with potatoes. The chairmen, porters, and coal-heavers in London, and those unfortunate women who live by prostitution, the strongest men and the most beautiful women perhaps in the British dominions, are said to be, the greater part of them, from the lowest rank of people in Ireland, who are generally fed with this root. No food can afford a more decisive proof of its nourishing quality, or of its being peculiarly suitable to the health of the human constitution.

Another option is that potatoes just have super weight loss properties that work no matter how much you weigh (but more on this later).

Adherence

We say “nothing but potatoes”, but the potato diet is actually a lot more permissive than all that. You get oil, spices, and drinks, and in our version of the diet, we said, “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.” 

People took us at our word, and many people chose to take several cheat meals or cheat days (several people mentioned loving this aspect of the diet). For each day, they reported whether or not they broke the diet, so we have an estimate of how many cheat days each person had, and we can look at that as part of this analysis.

We do want to remind you that this is self-report. Different people had different standards about what counted as breaking the diet, and some people were more rigorous about tracking this variable than others. It might be a good future project to go through all the raw data at some point and get better estimates for adherence based on the comments.

But that said, let’s take a look at them cheat days:

Only five people reported not a single cheat day. Everyone else said they broke the diet at least once. Most people cheated a few times, but a few people (36%) broke the diet for more than a week’s worth of days.

This is important because clearly the potato diet’s effects are robust to a couple’a cheat days.

We can take a better look at this with a nice scatterplot. Here we compare number of cheat days on the x-axis to weight change on the y-axis: 

You can see there’s a bit of a trend between more cheat days and less weight loss. Remember, higher numbers here are less weight loss; zero lbs is at the top. People on the left, who cheated very little, lost a whole range of weights. People on the right, who took more than 14 cheat days, tended to see much less weight loss. 

The basic correlation is only r = 0.176, and not significant. Though we do notice a weird outlier in the bottom right, and without that participant, the correlation is r = 0.303, p = .014.

One interesting thing here is that the five people who reported 0 cheat days are all tightly clustered around losing 10 lbs, so the diet does seem to maybe be the most reliable for people who don’t take cheat days. But some people who took cheat days lost a lot more than that. 

So overall we see that cheat days maybe matter a bit, but not a ton. It’s looking good for the 90% potato diet.

Heck, it’s looking good for the *40%* potato diet! Participant 68030741 broke the diet on 27 out of 28 days. (And actually didn’t mark down if he broke the diet on day 22, so maybe 28 out of 28.) He says:

I couldn’t get enough protein with only potatoes, so I supplemented with other food. Also, eating only potatoes without anything to accompany them quickly became too monotonous for me. So, I ended up getting only 40% of my calories from potatoes, but I still lost 7 lb over 4 weeks. I limited my intake of non-potatoes, but I ate potatoes ad libitum. I didn’t try to limit my daily calories; in fact the opposite, I often just wasn’t hungry enough to eat more.

There are some similar stories from other people, like participant 48507645:

I was really surprised at the results. While I cheated way more often than I wanted or anticipated, I still lost almost 10lbs. That’s with cheating almost every weekend (due to unforeseen social obligations). 

And here’s one from participant 35182564:

I also must confess, that I was not very strict with the “no dairy” rule. I took milk for my coffee (4-5 cups a day) and occasionally a small piece of butter or some spoon of plain yogurt to go with the cooked potatoes. This does not seem to have impacted the successful outcome. But it made the diet so much easier and also improved the “empty stomach” and “hungry” feelings a lot. Everything besides these “tiny” amount of dairy, I noted in the sheet.

The most extreme case study may come from Joey “No Floors” Freshwater, who shared his story on twitter. He wasn’t able to enroll in the study proper but he decided to do his own version consisting of “1-1.5lbs of potatoes a day when I could”, or about a 20% potato diet. Turns out it works just fine, for him at least. Here are some screenshots:  

So it looks like the 20% potato diet can work, at for least some people.

EASY POTATESY

Most people who made it the four weeks report the diet being anywhere between “pretty easy” and “real easy”.

(24235303) It was remarkably easy to stick to the diet.  I generally wasn’t hungry and when I was I just ate a potato.  I only had cravings for other things when I was directly looking at them, such as when I was helping to put away groceries for my family.  This seemed to require a lot less willpower than my previous successful diets.

(41297226) I lost 17 lbs in 28 days, felt very few food cravings or aversive hunger, didn’t get tired of potatoes.

(14122662) I felt mostly normal during this diet. I did often miss going out to restaurants or just having a non-potato meal, but the craving was never so strong as to be unbearable.

(63746180) Most of the time I had a good experience on the diet.  I didn’t feel cravings for other food.  Sometimes I would imagine eating out at a restaurant as a fun thing to do, but it didn’t have the same urgency as typical food cravings.  

(57747642) General Diet Thoughts: It’s really surprisingly easy. I was skeptical that I’d be able to finish the four weeks when I started, but once you get in the groove (and learn some tricks for prepping large quantities of potatoes quickly and easily) it’s extremely simple to stick with it. I basically never felt hungry or low energy.

Even some people who dropped out mentioned that it wasn’t hard for them. For example, take this report from participant 70325385: 

Overall, it was a good experience. I thought getting fewer calories would have a more detrimental effect on my mood and energy, to the point where I wouldn’t be able to function normally at all. What I noticed was mostly a ~2 point penalty to my mood and energy, which isn’t that big in the grand scheme of things but enough to be an annoyance.

On the other hand, we want to note that the potato diet was really, really hard for some people. Here are a few stories from people who stopped before completing four weeks.

(52058043) Not only is it very inconvenient to daily life and travel, it also feels pretty gross.  I feel uncomfortably full, but still wanting anything, anything at all, that isn’t potatoes.

(86547222) In short, my experience was not great. First two days I didn’t peel potatoes and my digestion went crazy. After that I started to peel potatoes, which helped but not by a lot. During those 9 days that I stuck to the diet I mostly felt apathy. The diet removed any joy associated with food from my life, and I missed that.

More speculation on some people loving it and other people hating it later.

Beyond the self-report, we can also look at people’s daily ratings of how easy they found the diet, on a 1-7 scale from 1 “hard to eat only potatoes” to 7 “lol this is so easy, I love potato”.

We averaged each person’s ease ratings over the four weeks for a mean ease rating. The mean of these ratings was 4.6 and the median was median 4.7, both of course on a 7-point scale.

It does seem like people who found the diet easier lost a bit more weight:

The correlation here is small, only r = -0.155, and not significant. This may, however, be the result of one participant who lost almost 25 lbs but seems to have hated every day of it. See him in the far bottom left? Without that guy, the correlation is r = -0.326, p = .008.

This is participant 74282722, who is also the outlier on the previous plot, with 23 cheat days out of 28 days of the diet. Perhaps this guy’s experience was not typical.

Comparison to other Diet Studies

It’s not a contest, but we think the potato diet compares pretty favorably to the rest of the literature.

Meta-analyses like this one do find that many diets cause 10-20 lbs of weight loss on average. But these studies tend to run for much longer than the study we’re reporting on today. The studies in that meta-analysis ran for 16-52 weeks (median 24 weeks) to get that 10-20 lbs of weight loss. If the potato diet went for 16-52 weeks… well that would be something wouldn’t it. At an average weight loss rate of half a pound a day, you do the math.

This meta-analysis compared interventions based on diet, exercise, and diet plus exercise found that people lost about 23.5 lbs on just a diet, 6.4 lbs on an exercise regime, and 24.2 lbs with diet plus exercise. Again this is pretty good, but these diets were all run for what they describe as “short durations”, which is 15.6 +/- 0.6 weeks.

This two-year trial from The New England Journal of Medicine compared low-fat, Mediterranean, and low-carbohydrate diets in a randomized design. All three of these diets saw only about 2 kg (4.4 lbs) weight loss at one month. This is less than the potato diet participants who dropped out before reaching four weeks, who lost an average of 5.5 lbs (median 4.2 lbs).

Maximum weight loss on these diets was at around 5 months in, when participants had lost an average of about 5 kg (11.0 lbs) in the low-fat and Mediterranean diets, and an average of about 6.5 kg (14.3 lbs) in the low-carb diet. This is about comparable to the weight loss on the potato diet, but it took five times as long.

The attrition rate for the potato diet is pretty comparable to other diet studies. That NEJM paper mentions that “common limitations of dietary trials include high attrition rates (15 to 50% within a year)”, and as a sampling from some papers we grabbed at random from Google Scholar, we see attrition rates of 49.3% in this study, 32.3% in this study, and 56.3% in this study.

Admittedly these attrition rates are over very different time scales, so it may be the case that the potato diet is a little harder to stick to than these other diets. But that seems pretty well offset by the much faster and more reliable weight loss.

We also didn’t include any of the intense measures many diet studies implement to keep their participants in line. We didn’t lock people in a metabolic ward. We didn’t control how they prepared their meals. We didn’t do portion estimation. Heck, most of our participants didn’t even stick that closely to the diet. Most of them took several cheat days! 

They still lost an average of 10.6 lbs over four weeks. Of those who made it the full four weeks, one lost zero pounds — the other 63 all lost at least 3 lbs. Of the participants who entered at least two days of weight data, two gained weight, three saw no weight change, and the other 146 lost weight. If you’re statistically inclined, the effect size for those who made it four weeks is d = 2.28. The potato diet is remarkably consistent.

​​It’s hard to estimate how much some of these other diet studies cost, but we’d guess at least tens of thousands of dollars. In comparison, our budget was $0. And we did the whole study in what, 10 weeks?

5. Effects other than Weight Loss

Ok, enough about weight loss. We were promised MORE.

The case studies did all mention weight loss, but they also mentioned other beneficial effects, the kind of thing we would love to see.

Chris Voigt reported major improvements in his bloodwork: “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.”

Andrew Taylor said, “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.” 

This is pretty exciting, so we wanted to look for other effects beyond weight. To keep things simple, we just asked people to track their mood and energy every day, both on a 1-7 scale (7 is better mood and more energy).

We took a look at both variables, and there does seem to be something there. There’s a small trend for mood, from an average of 4.3 on day 1 to an average of 4.7: 

Of the people who made it four weeks, 45.3% reported a higher mood on day 28 than on day 1. An additional 34.0% reported the same mood (on a 7-point scale) on day 1 and day 28. 

And slightly more for energy, from an average of 4.1 on day 1 to an average of 4.7 on day 28:

Of the people who made it four weeks, 50.9% reported higher energy on day 28 than on day 1. An additional 37.7% reported the same level of energy (on a 7-point scale) on day 1 and day 28. 

But there’s definitely some variation — some people reported feeling VERY energetic: 

There were also some reports of more specific forms of feeling energetic, like increased fidgeting: 

(81125989) I also noticed I’m fidgeting a lot, but not sure if I was always fidget-y before, and I’m only noticing now since I’ve read about lipostats & Non-Exercise Activity Thermogenesis

(88218660) Definitely had increased fidgeting at various points.

We also did this extremely scientific poll on twitter: 

So it does look like a substantial minority experienced this, but still, a minority. 

Effects and Variables we Didn’t Ask for

We asked people to track mood and energy; but, perhaps foolishly, we didn’t ask them to track things like blood pressure and sleep. 

But despite our failure, many people chose to track additional variables anyways, and reported all kinds of other effects of the potato diet above and beyond weight loss.

Certainly many people did NOT experience these side effects. Many people just didn’t mention whether or not they experienced them, but for most of these effects, there were some people who specifically said they didn’t feel it. For example, participant 81125989, who didn’t feel anything: 

I didn’t feel any noticeably better or worse. My sleep, anxiety, & ability to focus were trash the last few weeks, but they’ve already been that way for months before anyway.

But it’s hard to tell for most of these effects, since we didn’t track them systematically. A project for next time (or for one of you!).

Anyways, here is a selection of effects other than weight loss that were mentioned at least a couple times, and/or that we found interesting.

Digestion both Good and Bad

Lots of people reported digestive changes. Some of these were good. Others were very bad.

(72706884) Other: Improved digestion. 

(89852176) almost exclusively loose stools alternating with mild constipation from day 12ish onward

(38751343) My only note is that when I ate potatoes for more than 24 hours, I had the best poops. Total no-wipers. 10/10 poops. I have IBS so it’s rare for me to have a solid bowel movement. Next time I decide to have anal sex, I’m definitely going to eat potatoes for 24 hours prior.

Before you go rushing to cram potatoes before your next bout of anal sex, beware: the potato diet gave other people diarrhea:

(68545713) I had trouble getting started with the diet because at first. I was leaving the skins on, and not using any salt or oil. I had quite extreme diarrhea in the beginning, which I attribute to the unusually high fiber. I also just don’t like potatoes, so not using any salt or oil made the actual eating of the potatoes very unpleasant for me.

After only a few days, I allowed myself salt and oil, and at about the same time I started “imperfectly peeling” the potatoes to reduce (but not eliminate) the fiber. This made the diet much easier for me.

Sleep

Several people reported better sleep, and sometimes reported sleeping more.

(72706884) Improved sleep, even with caffeine pills. I never woke up in the middle of the night, which is atypical.

(34196505) I sort of feel like I slept better. This is not consistent with how I usually feel on a calorie deficit–normally, I have a hard time sleeping.

(31664368) Good energy and sleep from a crappy baseline (~4 month old at home, just starting to get “normal” sleep)

(63173784) I needed more than usual sleep on the diet, but once I added chicken I was able to sleep more deeply

My sleep apnea symptoms disappeared, except when I had the one “normal” meal in the middle. I must be reacting to other foods. 

There may be a relationship between the amount of sleep people require on this diet and how much weight they lose — someone should look into this at some point.

Blood Pressure

Several people tracked their blood pressure, and they tended to see improvement, sometimes a lot of improvement. 

If you don’t look at BP measurements very often, here’s a quick refresher on what the different ranges mean, from the FDA:

Normal pressure is 120/80 or lower. Your blood pressure is considered high (stage 1) if it reads 130/80. Stage 2 high blood pressure is 140/90 or higher. If you get a blood pressure reading of 180/110 or higher more than once, seek medical treatment right away. A reading this high is considered “hypertensive crisis.”

Two people saw minor increases. Participant 76703005’s blood pressure went from 123/69 (day 1) to 138/82 (day 29). Similarly, participant 26650045 went from 115/76 (day 1) to 116/80 (day 24, their last day).  

But other people saw their blood pressure decline, sometimes by a lot.

(90638348) Blood pressure down, resting pulse down, pulse/ox up (data in spreadsheet) 

Looking at the spreadsheet, participant 90638348 saw their blood pressure go from 139/98 on day 3 (the first they recorded) to 122/88 on day 29. They actually have BP data up to day 32, when BP was 125/87

Participant 14558563 also tracked their blood pressure, and found it went from 164/100 (day 5) to 153/98 (day 29). They even have data up to day 35, when it was 150/102.

(68482929) I ate a LOT of seasoning and salt, but my blood pressure dropped to 111/73 (before the diet it was 139/something)

(57747642) My blood pressure went down from a pre-diet average of about 135/85 to an average now of about 128/70. So that’s interesting.

(57875769) I also checked my blood pressure a few times, although I wasn’t scientific about it so I’d consider this anecdotal, but on day two of my diet my blood pressure was 149/96 (yikes!) and my last reading on day 27 was 126/81. 

(66959098) I also took a blood pressure measurement before and after the diet, starting at 177/107 and going down to 130/80.

Not asking for blood pressure measurements was an oversight on our part, since the measurement is so standard and it’s so easy to track at home. If we run any future studies, we plan to include it; and if you try the potato diet on your own, we recommend that you track it! 

Pulse / RHR  

A few people measured their resting heart rate, and found that it dropped during their time on the potato diet.

Participant 90638348 reported their pulse (BPM) dropped from 78 (day 1) to 64 (day 29). 

Participant 14558563 reported their pulse dropped from 68 (day 5) to 56 (day 29). 

And participant 05999987 had this to say:

I noticed I often had to pee during the night, which is unusual for me. (Note that my version of potato diet was also very low sodium, mostly because bland potato was just fine with me and I figured if I got way out of Na/K balance my body would let me know, like a deer in search of a salt lick). More interesting is my resting heart rate went down by almost 10 bpm from ~63 to 54. 

Cholesterol

A few people got more comprehensive blood work done, and the changes they saw over the course of the diet were generally positive. 

Participant 95730133 had this to say in his closing remarks: 

As promised, here’s the results of my blood work! Taken on the first day (5/31) and last day (6/27) of my potato diet. Note the second test was also fasted though it isn’t marked.

Summary:

Total cholesterol dropped from a high 242 mg/dL to a healthy 183 mg/dL.

LDL cholesterol improved from a high 148 mg/dL to a still high 124 mg/dL (0-99 is the target range).

All other levels remained healthy and in the target ranges.

Another participant (23300304) sent us his full blood test results. Like the guy above, 23300304 saw his total cholesterol drop, from 4.5 mmol/L to 3.1 mmol/L (about 174 mg/dL to 120 mg/L in the other units). He also saw his LDL cholesterol drop from 3.0 mmol/L to 1.4 mmol/L (116 mg/L to 54 mg/L). However, his triglycerides went up, from 0.65 mmol/L to 1.79 mmol/L.

Hypomania

When we tried this diet, we experienced some pretty hardcore hypomania:

This makes sense for us because we are mad scientists. But would “normal” people experience the super-wiring effects of potatoes too? Apparently yes, though certainly not everyone.

Participant 68545713 reported:

Energetically and mentally, I felt very energetic on the diet in a “hectic” kind of way. Not bad at all for me, that’s my preferred state. I tend to think of my mental clarity as being about a) how many trains of thought I can have going at once and b) how often I lose a train of thought to a blank mind. On potatoes, I had all ~3 trains running, and I rarely lost a thought. (That is quite unusual for me, and strikes me as very unlikely to be a coincidence.) … I’d classify the energy I get from a potatoes-only diet as “frantic”, or “hectic”, or “excited”.

Participant 15106191 gave these notes:

(Day 5) Energy boost kicked in today. Feel half my age

(Day 6) Potato energy going strong. Feel like Irish Superman

(Day 15) Almost too much energy, hard to sit down at a computer and work, took a break to play basketball 

And participant 02142044 described: 

[At] one point, I was feeling a mild euphoria, and then it just stopped … I felt a sort of euphoria/hypomania that lasted from day 17 to day 20, and I’m unsure how to reproduce it

Certainly not everyone saw this effect of the potatoes. Participant 90638348 said:

Never saw the manic energy described by other folks. I was sorta looking forward to that.

Migraines 

Only one person mentioned their migraines, but most participants probably don’t have migraines to begin with, so we found this interesting. This was participant 35182564, who said:

My frequent migraines improved during the diet. I could also go much longer without food than before and the blood sugar ups and downs were less pronounced, which is probably why the migraine is better. I am very happy about that.

Acne

Similarly, one person mentioned a serious improvement in their skin. Participant 36634531: 

One unexpected consequence is that my skin is way clearer.  I usually have a lot of redness in my face and am acne-prone.  My skin has been way less red and acne has been infrequent which makes me wonder if I have a food allergy.  If relevant for genetic reasons:  I am of Jewish and English/Irish descent.

Libido

Two people mentioned libido issues; participant 95730133:

My libido was down a good bit this month, which I’ve seen during weight loss periods before.

…and participant 70325385

The diet had a fairly large effect on my energy and mood most days, and greatly decreased libido starting almost immediately.

Most people didn’t report this effect; but also no one mentioned the potato diet making them extra horny. 

Fear and Grief???

One of the strangest effects that some people reported was an increase in intense feelings of fear and grief. For example, participant 95730133, who said:

I had 2-3 days with bad anxiety, which is super uncommon for me and represents a big chunk of the days I’ve ever felt anxious. May have had something to do with the rapid weight loss / potatoes.

We also saw some clear anecdotes about this on twitter: 

Chairman Birb Bernanke also discussed this a bit more in a retrospective post on her substack:

Like I said above, potato diet is fucking weird. I mention this and the above because towards the end of the third week, I found myself crying every day. I was having actual meltdowns… five days in a row. 

I am not talking “oh I am so sad, let a single tear roll down my cheek while I stare out of a window on a rainy day” levels of gloom and general depression. I am talking “at one point I couldn’t fold some of my laundry in a way that was acceptable to me, and this made me think I should kill myself, so I started crying”. 

Is this a really dark to drop in the middle of a sort of lighthearted post about potato diet? Yes. I am sorry if you are uncomfortable reading it. Personally, I think I have a responsibility to talk about it, because the mentally weird aspect of this diet cannot be stressed enough.

If you experience this kind of side effect, we recommend you dial back or discontinue the diet. As Birb put it:

To anyone who wants to do this diet, or is considering it after the benefits I described above: I encourage you to do it, but please be extra cautious that your mental state might be altered and that you are not necessarily in your right mind.

Muscle / Exercise

Finally, let’s talk about the topic on everyone’s mind: getting swole, and staying that way.

When we opened signups, many people asked if you’d be able to get enough protein on an all-potato diet. Potatoes do have some protein, and more than their reputation would lead you to believe (3-5 g in a medium potato), but it’s true that 20 potatoes a day won’t give you as much protein as many people think you need. 

This is where we reveal that this community trial is not actually the first-ever study of an all-potato diet. There are a few very small, very old studies, and they’re pretty illuminating on the subject of potato fitness. Stephan Guyenet explains:

Starting nearly a century ago, a few researchers decided to feed volunteers potato-only diets to achieve various research objectives. The first such experiment was carried out by a Dr. M. Hindhede and published in 1913 (described in 15). Hindhede’s goal was to explore the lower limit of the human protein requirement and the biological quality of potato protein. He fed three healthy adult men almost nothing but potatoes and margarine for 309 days (margarine was not made from hydrogenated seed oils at the time), all while making them do progressively more demanding physical labor. They apparently remained in good physical condition. Here’s a description of one of his volunteers, a Mr. Madsen, from another book (described in 16; thanks to Matt Metzgar):

“In order to test whether it was possible to perform heavy work on a strict potato diet, Mr. Madsen took a place as a farm laborer… His physical condition was excellent. In his book, Dr. Hindhede shows a photograph of Mr. Madsen taken on December 21st, 1912, after he had lived for almost a year entirely on potatoes. This photograph shows a strong, solid, athletic-looking figure, all of whose muscles are well-developed, and without excess fat. …Hindhede had him examined by five physicians, including a diagnostician, a specialist in gastric and intestinal diseases, an X-ray specialist, and a blood specialist. They all pronounced him to be in a state of perfect health.”

Dr. Hindhede discovered that potato protein is high quality, providing all essential amino acids and high digestibility. Potato protein alone is sufficient to sustain an athletic man (although that doesn’t make it optimal). A subsequent potato feeding study published in 1927 confirmed this finding (17). Two volunteers, a man and a woman, ate almost nothing but potatoes with a bit of lard and butter for 5.5 months. The man was an athlete but the woman was sedentary. Body weight and nitrogen balance (reflecting protein gain/loss from the body) remained constant throughout the experiment, indicating that their muscles were not atrophying at any appreciable rate, and they were probably not putting on fat. The investigators remarked:

“The digestion was excellent throughout the experiment and both subjects felt very well. They did not tire of the uniform potato diet and there was no craving for change.”

So previous all-potato diets didn’t lead to serious atrophy; it seems like people can maintain muscle just fine on a potato diet, and maybe even build muscle. Despite being relatively low in protein, that protein may be exceptionally available or otherwise of unusually high quality.

Empirically, participants in our potato study seemed to lose mostly fat, not muscle. Participant 10157137 used a Fitbit Aria scale to measure fat %, which went from 17.3% (day 1) to 16.5% (day 28). And they were not alone: 

(57875769) I lost nearly 17 pounds, and if the body composition on my scale is to be believed, roughly 75% of that was fat. 

(46804417) In total I lost 12.5lb (5.7kg) and 4.3% (33%->28.7%) body fat. I measured the fat % using a FitBit Aria 2 scale. I found it impressive that almost all the weight I lost was fat, usually when I diet I lose some fat but close to maybe half of the total?

Maybe you don’t trust these home scales, and you know what, fair enough. But these numbers are backed up with athletic performance, which indicates no noticeable muscle loss: 

(41297226) Weightlifting: I’ve been lifting off an on the last couple months. Went from deadlift/squat/bench of 155/165/135 on April 29th (day -5 pre-diet) to 160/145/125 on May 16th (day 13, first time lifting during diet) to 175/150/140 (day 21). I’d say: inconclusive, but doesn’t seem like I was held back from improvement by potatoes (+ taking 4g of BCAAs post workout)

(14122662) In general, I was shocked by the amount of weight I lost, especially since I started out slim and didn’t have much weight to lose in the first place. I had to actively make sure I was eating enough each day so that I wouldn’t lose even more weight. That said, I felt fine throughout the diet and stayed physically active by rock climbing, hiking, and playing kickball and tennis. My health was never a big concern for me.

(01772895) I went on several pretty intense road/mountain bike rides and kept up while feeling good over the course of the diet.

(05999987) I stuck with my usual level of physical activity which is at least 5 miles of walking a day, with some plyometrics. On the few occasions I did do some more intensive activities (a hike with a long, steep uphill portion) or jogging I felt more muscularly tired than usual, though in general I had average for me, or slightly above average energy.

(74872365) I felt unable/unwilling to lift weights during it. I was lifting 3x a week beforehand, and tried near the beginning to workout a couple times but started feeling kinds of joint soreness I wasn’t used to (assuming because of impaired recovery from previous workout). I tried to give it a few more days rest and just suddenly felt very much like not exercising… so I hardly lifted at all for the rest of it. But after the diet was over (a few weeks after it, what with moving and stuff) I got back into gym, got going again at reduced weights, and in two weeks matched or exceeded previous personal bests on most lifts (but haven’t gotten back to previous bench press best). I overall feel very positive about the way in which I was able to resume working out and hitting PRs after it was over, it wasn’t an overall bad thing for my lifting in the grand scheme.

On the other hand, not everyone had sustained athletic performance on the potato diet. For example, participant 57747642 said: 

One difficulty for me was keeping up my running volume on the diet. Pre-diet I ran ~20 miles a week. During the diet I found longer runs to be extremely tiring–I think I was just in too much of a caloric deficit to have much glycogen available. I started cheating by drinking a bottle of gatorade before my longer runs and that seemed to fix the issue. But I still only averaged about 8 miles a week of running which was quite a step down.

(15106191; Day 14) Bench press went down today, likely losing muscle along with the fat, either because of the low protein of potatoes or just the calorie deficit

(34196505) I lift weights at the gym a few times a week, and even on days when I made a point of eating a ton, I felt more fatigued and had a hard time lifting my goal weight. Physical activity seemed harder in general. This is consistent with how I usually feel about a calorie deficit.

If you’re training for a marathon that’s four weeks away, don’t start now. But for most of us, it’s clear that four weeks of the potato diet doesn’t cause serious atrophy or muscle loss.

6. Why do some people find the diet easy and others don’t? 

Some people find the diet comically easy, while other people hit a wall at some point and are suddenly unable to eat another potato. We’d like to know why. 

It’s worth distinguishing between two things; or that is to say, we think there are two ways to lose weight on the potato diet.

First, you can grit your teeth and force yourself to eat nothing but starchy tubers while fighting back your desire to eat literally anything else. A few people who made it the full four weeks seem to have had this experience. For example, participant 83122914:

It was an interesting experience, but it didn’t feel like any kind of magic bullet for long-term weight loss. I initially ate mostly mashed potatoes, but over time I found myself losing the desire to eat them. I craved meat, salad, etc. … I’ve had similar weight loss results in the past with a low-carb diet. 

But most people lost weight the other way: after a day or two of eating potatoes, their appetite waned, they didn’t want anything else, and they began to steadily lose weight.

This is the interesting part. To make this easier to talk about, let’s call it entering “potato mode”, or “potatosis”. Actually, Greek for potato is “patata”, should it be “patataosis”? 

Also worth noting that it’s not like the potato diet was just easy for some people and hard for others. More like, almost everyone found it easy at first. Some people found it easy for days or weeks and then suddenly hit a wall. So the question may be more like, why do some people hit a wall at three days, others at three weeks, and others apparently not at all? 

Demographics

It’s possible that the difference between the people who found the diet easy and the people who hit a wall will be something easy to notice, maybe basic demographic variables like race and sex. Let’s see:

The group of participants who provided us any data were mostly male (any way you slice it), mostly white, and mostly from the US.

But overall, basic demographics don’t seem to track onto who made it four weeks and who ended the study early. People who made it four weeks were slightly older, more likely to be from the US, and less likely to be white, but none of these differences are very big.

The only difference that jumps out is by sex. About 20% of the people who got to the point of recording data were female, compared to only about 10% of the people who made it four weeks.

We’re not sure why, or if this is even a real result. With so few female participants to start with, this could just be random noise. 

Participants who are XY did report the diet being a little easier, with a mean ease rating of 4.4/7, compared to 4.2/7 for XX participants, but this is not significant (p = 0.530). 

We also noticed that XY participants did complete slightly more days overall, but it’s not clear if this is robust. Looking at the plotted data, it doesn’t seem like a huge difference: 

It’s notable that our three big case studies (Chris Voigt, Andrew Taylor, and Penn Jilette) were all XY. We also did look at Brian & Jessica Krock, though, and Jessica Krock is XX. She made it pretty far on an all-potato diet, but she also seems to have found it much, much harder than most people do:

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.

But with such a small number of XX participants, it’s hard to be sure.

That said, 20% (6 out of 30) of XX participants made it four weeks. If the potato diet only works for one out of every five people with two X chromosomes, that’s still pretty good.

We do wonder if this is a real effect, and if so, why it happens. It would be good if future studies had more XX participants. 

Having lots of trans participants would also help us tell if the cause is more hormonal or more chromosomal. In this study, there aren’t enough people whose chromosomes and hormones don’t “match” to actually disentangle any effects.

Oil

Some people seemed to have an easier time, or see better weight loss, when they used less oil.

Not that kind

For our own part, one of us was fine for the first two weeks on a relaxed all-potato diet with olive oil, but didn’t see any weight loss until switching to a no-oil version for the last two weeks, when they lost 10 lbs. 

Participant 68482929 did some analysis of his own on this question: 

The amount of olive oil I consumed had a noticeable effect on how much weight I lost:

image.png

The main thing I craved on the diet was more olive oil. If I ate 10 tbsp / day, that felt about right (and my stool was normal and I gained a bit of weight on those days). The more I cut the oil, the more I had intestinal distress, and the more weight I lost.

Here’s that image: 

Participant 88218660 mentioned something similar: 

third week – started making air fryer fries at home with < 1 Tbsp of oil and eating pretty much only these. Also allowed myself to have ketchup – I’d estimate an upper bound of 200 calories per day of ketchup, but I expect it was less than that. Stopped losing weight. Very unclear if this is a natural plateau or an actual effect of ketchup. Cravings came back in force, as did normal hunger feeling.

Final day – switched back to mashed potatoes with no oil. Hunger was gone again, cravings were dampened, but didn’t immediately lose any more weight.

It’s not clear if this was the oil or the ketchup (or something else) but they definitely seem to have dropped out of potato mode for some reason. We reached out to participant 88218660 for clarification and he told us that he used olive oil at home. 

Despite these stories, many people used lots of oil throughout the diet and still lost weight. This suggests it’s not that all oil is bad and inhibits the potato diet. More likely, it’s that 1) some kinds of oil (e.g. olive oil vs canola oil) inhibit potato mode more than others, 2) certain batches / sources of the same oil (two different brands of canola oil or something) inhibit potato mode for some reason, 3) some people respond to oil differently because of genetics or microbiome or something, or probably 4) some combination of the above. Or it could just be noise, this isn’t strong evidence yet.

Nicky Case also recently did a regression analysis of her own data over 40 days, and found a strong effect of olive oil. But it looks like it was in the opposite direction — for her, more olive oil was associated with more weight loss. Check out the analysis in her twitter thread:

It’s sort of not surprising that all these anecdotes reference olive oil, since we recommended that people should probably use olive oil if they use oil at all. But it’s still kind of interesting. Recommending olive oil might have limited the amount of information we’ll be able to get out of these data! A few people did mention they did very well on Five Guys fries, which are fried in peanut oil… Five Guys, talk to us. 

Some people did keep detailed notes of their oil consumption, so it’s possible that a clear answer to this question is hiding somewhere in the data. But it’s also possible that we’d need to run a controlled experiment to figure it out, and we may do that at some point (unless one of you gets to it first?).

Salt / Sodium

Salt intake might also help explain why some people had trouble with this diet. 

We didn’t ask people to limit salt intake, but some people may have been keeping their intake down anyways, and that may have made the diet harder than necessary. Even if they weren’t trying to limit how much salt they ate, they may still not have been getting enough. Potatoes by themselves are a naturally low-sodium food. 

For example, consider the experience of participant 57875769:

Probably my biggest piece of advice is to use plenty of salt. Depending on the nutrition labels, potatoes have zero sodium or an extremely low amount. It seems hard to get the recommended amount of sodium (and I’ve seen some heterodox sources that say the recommendations should be even twice as high as they are) without adding salt to potatoes. A few days I felt kind of light headed or unfocused and I’d finding adding a little bit of salt to a glass of water (under the threshold where I could taste it) would often improve things pretty quickly.

Or this participant on twitter: 

Some people also mentioned craving pickled things, which could be the manifestation of a salt craving:

(01772895) Interestingly toward the end, my main cravings were actually for pickled vegetables for some reason.

Of course, we don’t know for sure if the people who dropped out early WEREN’T getting enough salt. But if some people were avoiding salt this could explain some of the difference.

Health

Another possibility is that finding the potato diet difficult can be an early sign of health issues.

Potatoes are high in potassium, and the kidneys need to do a certain amount of work to clear all that potassium from your system. They’re also high in certain toxins. A healthy body under no extra stress is equipped to handle these toxins no problem. But if your health is compromised, it might be another story. 

If you eat one potato, your body will be able to deal with the extra potassium and the low levels of plant toxins. If you eat nothing but potatoes and you have reasonably healthy kidneys, again your body will be able to handle it. But if you eat nothing but potatoes and you have poor kidney health, at some point your poor kidneys may not be able to handle all the extra potassium, potato toxins, and other junk. This will make you start to feel terrible, and may explain why some people did fine on the potato diet for a long time and then suddenly started feeling terrible.

Kidney function seems like the simplest case, but other kinds of hidden health issues could also give your body trouble.

The clearest example comes from Alex Beal (who gave us permission to use his case as an example). He was one of our earliest participants in the potato diet, and also one of the first to drop out of the study. He started tweeting about his experience, did ok on the first meal, but soon found himself feeling awful and totally unable to stand potatoes. He published a log of his experiences here, where he says: 

I’ve decided to drop out of the study after less than 48 hours. This diet kicked my ass.  

Beal stopped the diet on May 1st. A few days later, he found out he had prediabetes:

This maybe explains why he had such unusual trouble with the potato diet (remember, 90% of people who entered at least one day of data made it more than two days, and 40% made it all the way to day 28). Beal has a (mild) metabolic disorder he didn’t know about when he started, and it’s pretty reasonable to suspect that this may have limited his ability to deal with all these potatoes.

We discussed this with Beal and he agrees it’s plausible. “In a study population of obese folks,” he says, “I do worry undiagnosed diabetes or prediabetes is a risk. It’s very common for it to go undiagnosed.” This is similar to something JP Callaghan mentioned, where he said, “There are tons of people walking around with their kidneys at like 50% or worse who don’t even know it.”

Beal did mention that his kidney numbers came back ok, so it’s probably not literally potassium clearance in his case (though who knows).

One strike against this explanation is that younger people generally have better kidney function, so if this were why people are dropping out of the study, you’d expect to see many fewer dropouts among younger people, which we don’t see. But for what it’s worth, Alex Beal is pretty young and he had undiagnosed prediabetes before signing up for the study. It’s possible that we recruited a sample that has disproportionately high numbers of young people with undiagnosed renal and/or metabolic disorders.

In any case, finding the potato diet really hard may be an early warning sign for kidney issues and/or diabetes, possibly because the high levels of potassium put a strain on your kidneys that you wouldn’t normally experience, so it might reveal problems you wouldn’t normally notice. So the potato diet may be a useful at-home diagnostic tool.

If you had a hard time with the potato diet, especially if you were only able to make it a few days, talk to your doctor about checking for kidney function and prediabetes.

Whatever you find out, please let us know, that’s important data.

Peels

A related issue comes from potato peels.

A number of people mentioned that peeling the potatoes made the diet noticeably easier:

(02142044) The diet was a bit tough at the beginning, probably because I didn’t peel them. 

(68545713) After only a few days, I allowed myself salt and oil, and at about the same time I started “imperfectly peeling” the potatoes to reduce (but not eliminate) the fiber. This made the diet much easier for me.

(86547222) First two days I didn’t peel potatoes and my digestion went crazy. After that I started to peel potatoes, which helped but not by a lot.

This matches our experience. On the potato diet, there was a point at which the peels started getting disgusting — but without the peel, potatoes continued to be delicious. We were very pro-peels starting out, but by about halfway through, we started peeling them and that made a clear difference.

This is interesting because it certainly goes against common wisdom about the peels — that they’re especially nutritious, that they’re good for you, and so on. It’s true they’re high in fiber, and it may be fine if you are eating only like, four or five potatoes now and then. But as Stephan Guyenet points out:

Peel [potatoes] before eating if you rely on them as a staple food … Potato peels are nutritious but contain toxins.

Again, your body can handle most vegetable toxins in small doses. But if you are eating a lot, at some point they might get to the point where it’s a problem.

So it could certainly be that past a certain point, eating the peels will become difficult for some people. Or it could be that the peels are generally fine if you’re healthy, but they pose a problem for people with undiagnosed poor kidney function. There could easily be a peels * kidney interaction.

It could also just be fiber. Lots of people reported digestive issues, and the peels are especially high in dietary fiber. 

So it’s possible that some people who dropped out early could have made it further if they started peeling their potatoes. If you’re having trouble on the diet, we definitely recommend ditching the peels.

It’s Random

Like we mentioned, potatoes contain toxins, and some potatoes contain more toxins than others. For example, levels of the toxin solanine increase when potatoes are improperly stored, or exposed to too much sunlight, and green potatoes tend to have more solanine.

Most bags of potatoes are fine, but maybe one day you go to the grocery store and just happen to get a bag of greener-than-usual potatoes, which make you feel sick, and since you’re being careful, prompt you to end the diet early. From your perspective you can’t tell why you suddenly got sick, but from a god’s-eye-view, it was the bad batch of potatoes. So maybe random chance is what’s causing some people to hit a wall.

(Just avoiding green potatoes wouldn’t totally fix the problem, because potatoes can be high in toxins without being green. But definitely do avoid green potatoes.)

If this were the case, it would look pretty random who drops out. It does look pretty random who drops out. So maybe the dropouts are from some kind of random factor like this!

7. Why the Heck Does the Potato Diet Work

The human body has a lipostat that regulates body weight, and the lipostat has a setpoint, a weight that it wants to maintain. For the sake of an example, let’s say it wants to maintain a BMI of 23. The lipostat can detect how much fat is stored and takes action to drive body fatness to the set point of BMI = 23. If your body’s BMI is below the setpoint, the lipostat will drive you to eat more, exercise less, sleep more, and store more of what you eat as fat. If your body’s BMI is above the setpoint, the lipostat will drive you to eat less, move and fidget more, and store less of the food you eat as fat.

People become obese because something has gone wrong with the lipostat — for some reason it is defending a set point above BMI 30, and all the regulatory systems of the body are working together to push body weight to that level and keep it there (for more information, see here).

It seems clear to us that something about the potato diet lowers your lipostat set point, and weight loss kicks in because the lipostat starts to defend that new, lower weight.

When you run a normal calorie deficit (don’t eat as many calories as you need), you get sluggish, you lack energy, you get hungry, and you have a hard time exercising. This is because your body wants to defend its weight at the current set point, whatever that point is, and will work really hard to keep you from getting lighter.

But when you are heavier than your current set point, the body pulls out all the stops to help you lose weight and drop to the set point. You feel more energetic, you fidget to burn extra calories, your body temperature goes up, you stop feeling hungry, and so on. In line with this, people in potato mode reported being very energetic, having hypomania, fidgeting all the time, and having no trouble exercising. This is exactly what we’d predict if your lipostat set point suddenly went down.

In addition, there are two special points that strongly support the idea that the potato diet lowers your lipostat set point. 

First, some people keep losing weight after stopping the diet. We think this means that the lipostat set point dropped faster than weight loss was able to follow, and it took a few days after the diet was over for BMI to catch up. If the diet just worked on caloric restriction, then you would expect people to start gaining weight again after stopping. But that’s not the case, or at least, not always the case.

(36634531) My weight is still holding steady after resumption of a typical diet.  Are you guys going to ping the participants in X months to see if we return to baseline? 

(57875769) Since stopping my weight has stayed pretty flat (I was 215.3 lbs this morning and I ended the diet at 215.2, and I was traveling for a few days which usually causes me to gain weight) and I find that I have a much smaller appetite than I used to. I’m having to re-learn how much food I should serve myself or order at each meal because I’m used to eating much more. 

This is just suggestive for now, but we’ll know more in 6 months when we do the first followup. 

But the biggest sign that the potato diet lowers your lipostat set point is the overwhelmingly common experience of how the potato diet makes hunger feel entirely different.

(36634531) My appetite did eventually tank.  I was down to one meal a day.  I don’t know if I was just full all the time or if my stomach shrunk or what.  I was never feeling hungry throughout the diet.

(68545713) [I] felt less desperate than before-potatoes when I did get hungry. It was wonderful.

(29550957) Subjective feeling is definitely that I could get hungry, but it was not an urgent problem. Completely different from my usual modus operandi of gravitating in the direction of food whenever slightly hungry.

(10010108) I simply was not hungry in the mornings. Once I did start eating, I was starving every 1-2 hours. Out of habit, I do not eat after 8 pm. Sometimes we would have dinner at 7 due to scheduling, and I would be stomach growling hungry at bedtime, between 10-12. I was not going to get up and eat, so I drank water and slept. The hunger just wasn’t there in the mornings though. 

(81125989) My sense of hunger was anomalous: some days I’d eat less than 1000 calories and feel totally fine, some days I’d get a sudden sharp pang of hunger right after a hefty meal. And on my cheat days, even when I ate to satiety, I ate a lot less than I did pre-potato diet.

(74872365) I recall feeling like hunger exists in two distinct modes, and potato diet worked helped switch one off while downregulating the other: there’s the “need to feel full and need blood sugar” hunger and the “pleasure reward hunger.” It was like when I finished a mashed potato dinner the first hunger was satiated fully but I still would have eaten a whole pint of ice cream for pleasure if I was allowed to. I still kind of wanted to eat for more pleasure, but the pleasure based eating was “deactivated” from controlling my decision, and the potatoes weren’t hitting that pleasure center. Hence I only ate up to the level of the first hunger metric, the more “physical” one, and that level was downregulated of course. During cheat days (which were all around dinner times I think), the moment I started eating non-potato, I got insanely outlandishly hungry and ate surprising amounts of food the rest of the evening. It was like I would eat a bunch and then suddenly feel empty an hour later.

 

(68030741) I limited my intake of non-potatoes, but I ate potatoes ad libitum.  I didn’t try to limit my daily calories; in fact the opposite, I often just wasn’t hungry enough to eat more.

(1772895) Toward the end of the diet, I found it difficult to eat enough potatoes. I’d be a bit tired and hungry, but the effort of cooking them and eating them seemed too much to bother with. This was an interesting experience, and gave me some empathy for a few of my friends who have a hard time keeping weight on, even with an unrestricted diet. When they’ve described themselves as sometimes being ‘too lazy to eat’ in the past, I basically found that unimaginable, as I don’t think I could ever be too lazy to eat cake, for example. However, if the reward I got from eating cake was similar to the reward I get from eating potatoes, I guess that’s how I’d feel.

What’s interesting though is that I wasn’t feeling tired and hungry and craving some other food — I just didn’t feel like eating. Maybe this is something to do with the stuff Pen Gillette mentioned about eating habits fading. Interestingly toward the end, my main cravings were actually for pickled vegetables for some reason.

(77742719) I did get more tired throughout, and my appetite actually continually decreased. Had to remind myself to eat quite often and actually made a schedule. On this last day, I had only one meal of potatoes, 500 kcal.

(90638348) Was not ever resentful or hungry, always felt “full”

(88218660) First week – no oil, pretty much all mashed, non-organic russets with cajun seasoning and hot sauce. Almost immediately I could tell my cravings were significantly dampened (though not gone, especially if I was looking at tasty food) and that the normal feeling of hunger was entirely gone for me – what was left was a feeling of being almost faint and feeling not great when I went too long without eating. Took a lot of adjusting to.

(57875769) I feel full sooner than I used to, and I feel like there is a much richer variety of sensations that influence whether I want to eat more food. I remember some people advocating that to maintain a healthy weight you just need to learn to listen to my body, which is sort of what this feels like. Perhaps the people giving that advice were always thin and so listening to their body was never hard. I’ve started feeling signals I don’t remember feeling before I started the diet. It’s almost as if the volume from some things (e.g. a hyper-palatable diet) drowned out and deafened me to all the signals I was supposed to listen to. Now I feel like I’m hearing these again.

(76011343) throughout I had a ton more energy, better mood, weird hunger effect that you guys have documented (didn’t feel hungry and had to force self to eat)

As you can probably tell, this experience was extremely common. But we should note that it wasn’t universal, even among people who lost a lot of weight. Participant 99479977 lost 22lbs but specifically mentioned no appetite/hunger effect: 

I’ve seen a lot of people mentioning how the diet changed their perception of hunger. For me at least that didn’t change. What I did notice though is that I become sated much quicker. Today I packed myself four medium size roasted potatoes for lunch during uni, and I felt sated after just three of them.

And see also this report from participant 34196505:

It wasn’t like some hunger switch flipped off in my brain after a day or three of nothing but baked potatoes–I still got hungry, and it felt similar to normal hunger. I saw people on twitter saying they were having a hard time reaching 1,000 calories a day. Can’t relate.

People did eat very few calories on this diet. Most people didn’t track calories very closely (another benefit of the diet — no calorie counting!) but some people chose to record how much they were eating. The people who recorded calories (self-report, so grain of salt here) generally reported eating very little.

For example, participant 68030741 kept super detailed notes on calorie consumption and should be the starting point for anyone who wants to dive deeper into this question. He reports eating as little as 756 calories in a given day, and never more than 1740. 

Participant 71309629 never reported eating more than 1556 kcal, and ate as little as 307 kcal one day.

Participant 07644625 has “been tracking [calories] for 4035 days … hard to stop now” and reported eating as little as 1172 kcal in a day — but also often ate more than 2000.

Participant 05999987 also said:

As for ease of diet, it was quite easy to feel full, without eating very many calories at all. This worried me the first week, even on days when I supplemented the potatoes with salmon I never ate even  1300 calories a day. In fact, I averaged 921 calories per day. 

This is consistent with the reduced appetite. But it is NOT an explanation any more than “the bullet” is a good explanation for “who killed the mayor?” Something about the potato diet lowered people’s lipostat set point, which reduced their appetite, which yes made them eat fewer calories, which was part of what led them to lose weight. Yes, “fewer kcal/day” is somewhere in the causal chain. No, it is not an explanation.

But we’re bored of trying to explain this one, so we’re going to let the cat do it:

Alternately, if you prefer your arguments to come from bipeds:

Theories 

We’ve previously written about how we don’t believe in definitive experiments, so we don’t think that the potato diet will be the silver bullet for or against any particular theory. In general, most theories predict the potato diet should cause weight loss, so the potato diet does not do much to distinguish between them.

But that’s ok, this study was not designed to help distinguish between different theories of the obesity epidemic — it was designed to see if the potato diet works under realistic conditions, and to get a rough sense of what percent of people it works for. Now that we have that, future studies can use the potato diet as a “model diet” to start pitting theories against one another. Won’t that be fun. 

Even so, the data from this first study does tell us a little bit about different theories. Compared to other diet studies, the potato diet has the benefit of being super controlled — it’s a clear baseline of potato, with few interfering factors. So let’s take a look.

Something special about potatoes?

One thing we need to address right off the bat is the possibility that potatoes cure obesity for some reason totally unrelated to the obesity epidemic.

For example: cocaine makes you lose weight. But the obesity epidemic didn’t happen because everyone was on cocaine for all of history, which kept them skinny, and then in the 20th century people started forgetting to take their cocaine, and we all gained 40 lbs. It’s just that cocaine has strong weight loss effects totally unrelated to whatever caused the obesity epidemic. 

Similarly, it’s possible that potatoes are just a potent weight-loss drug for reasons totally unrelated to the increase in obesity since circa 1970. There are a few things that make this seem plausible.

For starters, Staffan Lindeberg, in his book Food and Western Disease, has a whole section on how maybe humans were built to eat roots and tubers: 

Increasing evidence suggests that large starchy underground storage organs (roots, tubers, bulbs and corms), which plants form in dry climates, were staple foods 1–2 million years ago. There are at least three arguments in favour of this notion. Firstly, in contrast to most other animals including non-human primates, humans have an exceptional capacity to produce salivary amylase in order to begin hydrolysis of starch in the mouth. The underlying change in copy number of the gene coding for salivary amylase may have occurred approximately 1 million years ago. … Secondly, roots often need to be prepared under high temperature in order for its starch to be available for digestion and for its bioactive or toxic substances to be neutralised. There are many indications of Palaeolithic humans using fire for cooking, and one of the most common cooking methods for plant foods was probably the so-called earth oven, where food wrapped in large leaves is placed in a covered pit with hot stones or glowing coals. Thirdly, human tooth morphology, including incisal orientation, seems to be well designed for chewing root vegetables. … Our bipedal ancestors were apparently less efficient hunters than many carnivorous animals and less efficient fruit-foragers than the arboreal primates. In order to increase the caloric yield per workload (‘optimal foraging strategy’), root vegetables may often have been an optimal dietary choice. An illustrative example is the Machiguenga tribe of the Amazon, among whom one woman can dig up enough root vegetables in one hour to feed 25 adults for one day. The excellent health status among this and other starch-eating ethnic groups, including our own study population in Papua New Guinea (see Section 4.1), contradicts the popular notion that such foods are a cause of obesity and type 2 diabetes.

If we really are built to eat tubers above and beyond all other foods, this might explain why the potato diet lowers your lipostat set point to hunter-gatherer levels.

There’s also some evidence that potato protease inhibitor II suppresses appetite and reduces food intake, though these studies don’t seem to be especially targeted — it looks like they basically just gave people potato extract. 

We don’t think the evidence is all that strong, but it certainly seems possible that potatoes just suppress appetite and make you lose weight.

We’ll know more when we get the six-month followup results. If potatoes just suppress your appetite during the time you’re eating them, then once you stop eating them, you should gain most of the weight back. But if potatoes are doing something more profound, and resetting your lipostat or whatever (however they do that), then weight loss should be at least somewhat sustained by six months out. For what it’s worth, this is what we see in the case studies, like Penn Jillette and Andrew Taylor, who seem to have had little trouble keeping the weight off.

It’s possible of course that BOTH are true, that potatoes both suppress your appetite in the short term and somehow reset your lipostat in the long term. In fact, the combination of these effects would be a pretty good explanation for why the potato diet is so unusually powerful. But we’ll have to wait and see.

But assuming for a moment that potatoes are NOT a superpotent weight-loss drug for some reason, what would this tell us about other theories? 

Calorie-Counting, Willpower, and other Traditional Diets

No.

(34459757) Pretty easy as far as diets go, basically never felt hungry. Previously I’ve successfully lost 25 lbs via just calorie restriction (mostly by eating box mac and cheese and other prepackaged things with easy calorie counts), and potatoes were definitely easier and I lost weight at the same speed. 

(66959098) It felt pretty easy.  I have tried simple CICO diets before where I simply reduce portion sizes and maintain a calorie deficit, which were incredibly hard to follow through and caused me to think about food all of the time. This had no such effect, no strong hunger, no strong cravings. I am happy with the results from just three weeks.

(99479977) I have tried various diets before, but restricting calories while eating whatever I like left me hungry, which lead to overeating and actually gaining more weight. The potato diet kept me sated, allows for just enough variety (especially through condiments) to keep me engaged

(27316026) I started the study slightly overweight by BMI and mostly interested in helping out along with seeing how it went firsthand. I’m 35 and 5’9 and my weight has been slowly going up on average for a decade, interrupted by harsh diets every few years to try and get back down under 160. I’ve always succeeded at these diets, which normally lasted around 2 months and involved meticulous calorie counting. I hated these diets and was only able to maintain them with the knowledge that they would be over relatively soon. Comparatively the potato diet has been a joy. It only took a few days to settle into, but after working out a few dishes I enjoyed I wasn’t hungry and food cravings were largely absent.

(95730133) I was pleasantly surprised with the amount and consistency of weight loss on this. 2.5 lbs a week is pretty dramatic and this was even easier to stick to than when I’ve done calorie counting previously at a shallower slope (1.25 lbs/week).

(29550957) This is pretty much the best diet I’ve ever been on, including earlier this year when I also ate mostly potatoes- but with tons of dairy (butter, sour cream, cheese) on them. Despite literally messing up an entire week’s worth of days, I seem to be durably down about 10lbs.

(30719090) This has been quite a revelation:

I have been dieting on and off for about 10 years now. The only successful diet was 10 years ago when I got down to 75kg (165lbs). This was based on buying an expensive range of low carb meals. I was less overweight at the time and it was something of a struggle. The diet was eventually derailed by personal circumstances and I have since then gradually increased my weight reaching 200lbs and over recently.

All other diets I have tried have had a small loss initially, but the loss has never continued. The psychological difficulty of maintaining a restricted diet when the losses did not continue was always too much for me. I hate the feeling of being hungry.

The potato diet has been very different. I actually like potatoes so I have not found it difficult to eat them every day and I have found it very easy to resist the temptation of other food.

(35182564) Since I was very successful, losing more than 20 pounds in six weeks, I will probably continue some more relaxed form of the diet for a few more weeks. I have been trying to lose weight for years with absolutely no success. The potato diet did in six weeks, what I could not accomplish in many years. I hope I can keep the lower weight (will send an update in a few months).

(05999987) As a person who has slowly gained weight over the years until I hit the border BMI between overweight and obese and it has become very difficult to lose weight. I’ve often done a couple weeks of limiting to 1500 kCal/day with what a normal person would think healthy–lots of vegetables, some whole grains, some lean proteins, olive oil, legumes. Every time I’d lose a couple pounds, but not much more, and find myself to be quite hungry most of the time. The main difference with potato diet is that I only once experienced the brain-crashing feeling that I need to eat something immediately because my brain is no longer working due to the colloquial usage of “low blood sugar”. The rational part of my brain also didn’t notice any hunger and I could read about/watch people eat/think about delicious foods and not feel like I really wanted to eat them, and I’m the sort of person who thinks about cooking a lot. Plain cold potato was just fine with me, and while I looked forward to the end of the diet and eating normal food again on a theoretical level, I didn’t care about adding condiments, etc. 

(63833277) I occasionally had french fries or tater tots or even a couple of times pringles. My wife used some dairy in preparing the mashed potatoes and had ketchup on my fried potatoes, so probably technically every single day should have a “1” in the “broke diet” field. But if I’d done that I’d never have been able to stick with it as well as I did–I basically tried to bend the diet such that I could successfully stick with it but no further and call that success. I thought about retrospectively changing them all to 1s but there *were* days when I *actually* broke the looser diet I’d set for myself and I didn’t want to elide that distinction. Basically think of my diet as a slightly loose potato diet that’s like 95%-97% potatoes instead of 97%-99% as expected. Sorry for not being ideal about that, I figured that would be better than giving up after 5 days.

DESPITE THE DEVIATIONS, THE DIET WAS AN ASTOUNDING SUCCESS!

I’ve never lost weight before. My life has been a slow drumbeat of “this is my setpoint weight, I can’t lose any but I don’t gain any” punctuated by “Life event, my setpoint weight is now X lbs higher than it used to be”. I was never able to motivate myself to stick with diets because I was constantly half-assing them, thus not losing weight, thus seeing no point in sticking with a diet that wasn’t losing me weight.

I lost half a pound a day on this potato diet. I am astounded, as is everyone who knows me!

The potato diet is not a willpower diet. Some people saw huge effects even while cheating. Some people saw huge effects on this diet even when they had found other diets super hard in the past.

We understand if you don’t really get this. We didn’t get it either, despite reading about all the previous success stories, until one of us tried the potato diet for ourselves. Hunger vanishes in a really weird way that is hard to describe to anyone who hasn’t felt it directly. So listen to all our participants who are like “no it’s not calories, it’s not willpower”. Or try it for yourself, you might be surprised! 

Anyone else who complains about calorie-counting will be thrown directly into the sun.

Carbs make you fat

Some people think that carbs make you fat. But the potato diet seems like bad news for any “carbs make you fat” theory, since potatoes are starchy carbs. More complex versions might still have a leg to stand on, but obviously this finding is a problem for this kind of theory.

Seed Oils

There’s a theory that the obesity epidemic is caused by “seed oils”, an umbrella term for things like canola oil, soybean oil, corn oil, sunflower oil, and peanut oil. We’ve previously reviewed this theory, and found it unconvincing.  

We didn’t track the oil people were eating in any rigorous way, but many people had seed oils like canola and peanut oil on their potatoes. Since their diet was otherwise so limited, this seems like a problem for seed oils theory.

On the other hand, the amount of oil they were eating did seem to make a difference for some people. So maybe this is more evidence for “something that is sometimes in oil and sometimes not”. It fits pretty well with contamination theories (more in a bit), or anything else that might vary in oils, perhaps due to factors like different growing conditions.

Long-Term Theories

There are some theories that suggest that the obesity epidemic is the result of what we’ll call “long-term” factors. For example, evolutionary theories say that natural selection is, for some reason, pushing us towards greater body weights over time. Epigenetic theories suggest that things that happened to your parents or grandparents cause obesity, as the result of gene expression. 

Developmental theories say that people become more obese later in life because of something that happened to them early on in development or childhood. This recent massive review paper specifically argues “that obesity likely has origins in utero,” i.e. you get obese at 25 because of things that happened to you when you were an embryo.

But the potato diet poses a challenge for these theories. If obesity is caused by something that happened to you in utero, or by something that happened to your grandmother, then how come it can be reversed in a couple of weeks of potatoes? There may be ways to resolve this challenge, but it’s a challenge nonetheless. 

Mono Diet

Some people have told us, “oh you can eat any one thing and lose weight like this”. Penn Jillette also says this. He told “Good Morning America” in 2016:

It didn’t have to be potatoes, they aren’t magic. I picked potatoes because it’s the funniest word. I could have chosen beans or just almost anything.

We’re not so sure. In particular, why do people think that other mono diets work? We haven’t seen any. We encourage anyone to find anecdotes, studies, or better yet, run their own Onion Diet study or whatever.

The potato diet isn’t even really a mono diet. We explicitly allow for oil and seasonings, and lots of people lost weight with tons of cheat days. The mono-ness (monotony?) of the potato diet clearly is not the active ingredient. 

Potatoes are also unusual in that they are (almost) nutritionally complete. You couldn’t do the white bread diet and get far. But you could maaaaaaaybe do the whole wheat bread and oil diet, or the wheat bread and cheese diet. Also known as: the basic daily diet in Europe for centuries.

That said, we do think that studies (maybe more internet community trials) of other very simple diets would be interesting — especially since most cultures historically have had very simple diets, which shows there are many simple diets you should be able to live on indefinitely. So we’d love to see, for example, studies on diets composed exclusively of: 

  • Rice & beans
  • Rice & fish 
  • Rice & lentils
  • Buckwheat soba & edamame
  • Bread & olives / olive oil

(Someone should check that these are nutritionally complete first, though.)

This last one is already close to the Mediterranean diet, but it would be interesting to cut the Mediterranean diet down to literally just bread, olives, olive oil, wine, and cheese. Or literally to just bread and olives / olive oil, if you could survive on that. 

So anyways, if you are sure that any mono diet would work, please do run your own study, we want to see it. We’d be happy to discuss study design with you!

Food Reward

Some people put the obesity epidemic down to a factor called “food reward”. They say that people are obese now because food has gotten more delicious, and that the potato diet causes weight loss because potatoes aren’t delicious. An attempt to describe the theory might look something like this:

People are more obese because food is way more fun to eat now. You can even be agnostic about why food is more fun to eat, and maybe it’s a million small reasons. But over time food producers have figured out how to hit that mental g-spot that makes people go YUM, and when you do that, people eat more than they should and they gain weight. The potato diet works because potatoes are boring and so people don’t overeat.

To be frank, we still don’t really get this theory. That is, we don’t think it makes sense. 

First, we’re not convinced modern food is more delicious than old-timey foods. They had butter and ham and sugar and ice cream and even donuts back in 1900. Check out our review of foods of the 1920s and 1930s — lots of the food culture was weird, but they also had like, just tons of lard and pie. 

Second, if the problem is that Doritos and Kraft Singles have been hyper-engineered by food scientists to be irresistible, then how exactly would the potato diet pry people away from them? If they are irresistible, then it should be really really hard to stop eating doritos and start eating potatoes. But people say that it doesn’t take much or even any willpower to stay on the potato diet, and many people report no cravings. If your model is “people eat the most delicious foods available and cannot help themselves”, then the only way the potato diet could hold people’s attention is if straight potatoes are more delicious and addictive than twinkies. 

Frankly we think they are more delicious than twinkies — but if that’s true and food reward is the law of the brain, then fast-food companies should be peddling baked potatoes instead of Snickers bars. 

Finally, the food reward perspective predicts that the potato diet works because potatoes are boring so you don’t want to eat them. We think this is also bunkum. Potatoes are great, and everyone knows it. Lots of participants reported not only enjoying potatoes, but liking them more after completing four weeks of the study:

(24235303) I didn’t mind eating potatoes.  They were still perfectly tasty throughout, and varying form factor and spices kept things fresh enough.

(02142044) I felt a sort of euphoria/hypomania that lasted from day 17 to day 20, and I’m unsure how to reproduce it … It was both a feeling of well-being, but also the potatoes started feeling delicious, like they were extremely savory.

(29550957) The last two days my family forced me to eat a bunch of other stuff for my birthday and honestly I wasn’t super enthusiastic about it! I wish I could have just been eating more potatoes. I notice I definitely felt worse after eating stuff like cake, and actually felt durably very stuffed for hours afterwards.

(31497197) Overall, I’d say the diet “works” in that I ate as much as I wanted, mostly didn’t crave other food too often, never got sick of potato, and lost weight.  On the very relaxed diet, I lost an average of 2lbs/week, and I think that would have been higher with less frying, but commercial food is not conducive to diets at the best of times. … This is really easy, in that I don’t hate potatoes and haven’t gotten sick of them.

(16832193) I was quite surprised that I didn’t get tired of potatoes. I still love them, maybe even more so than usual?!

Participant 57875769, Day 11: 

My wife and I went out to eat with a friend and I expected to use today as a cheat day, but honestly potatoes sounded like the best thing on the menu so I ordered hash browns and french fries. The hash browns were very filling on their own so I didn’t eat many of the fries.

And again Day 29: 

I’m ending today. It’s weird though, I’m thinking of all the foods I could eat today and I might just stick with potatoes for a lot of my meals. It’s going to feel strange going back to a more varied diet.

So, people come out of the diet saying they love potatoes. Many of them choose to keep eating potatoes even though they’re off the diet. Some of them say they MISS eating so many potatoes. If this isn’t what people mean by “food reward” or “palatability”, then we’re not sure what they mean. If people do mean something else specific, we’d be interested in hearing that.

Same thing for satiety. Yes, potatoes are high satiety, in the sense that you don’t want to eat anything else after you eat potatoes. But why are they high in satiety? Why do they make you not want to eat any more? This is borderline circular reasoning. 

Microbiome

Some people think that the obesity epidemic is caused by some kind of problem with the microbiome, the little beasties that live in your digestive system. 

Microbiome theorists have been in contact with us and have shared how they think potato starch is great for the microbiome, pointing us to studies like this one and popular science posts such as this

This is really a proposed mechanism, rather than a theory of the cause(s) of the obesity epidemic. It doesn’t explain why the microbiome gets so messed up in the modern environment, but this also means it is potentially consistent with many different theories. If high levels of sugar, fat, light exposure, iron supplements, PFAS, lithium, processed foods, or whatever mess up the microbiome, and something in potatoes fixes it, the potato diet would work just about like we see here.

This seems reasonably plausible to us. In particular, many participants report digestive or gastrointestinal changes (both good and bad) on the potato diet, which is about what you would expect if the potato diet were seriously changing your microbiome. One possible limitation is that weight loss does seem to be driven by the brain, but there may be a gut-brain connection that renders this point moot.

That said, we’re not sure how to test this hypothesis any further. We could compare the potato diet to a normal diet supplemented with potato starch, but if the potato starch supplement also caused weight loss, that wouldn’t point to the microbiome specifically, it would just show that the potato starch contains the same active ingredient as the potato diet, whatever that is.

We could also test stool samples, but honestly we don’t know what we would be looking for. Yeah some things would probably change in your microbiome after four weeks of potatoes, and we could see if any of them were correlated with weight loss, but that’s a pretty blunt instrument. What should we actually look for? If anyone has opinions on *exactly* what might be going on with the microbiome, we’d be interested in hearing your theory.

Processed Foods 

“Processed food makes us fat” is a line that has been pushed by outlets such as the Washington Post and the NIH. The basic idea is pretty simple: ultra-processed foods make you fat, for some reason. People who support this perspective don’t usually say what it is about these processed foods that make them so fattening, but it’s often mindlessly conflated with the food reward theory:

It also doesn’t mean that all processed food is bad. Whole-grain bread and cereal are excellent, and there are good versions of such things as frozen pizza and jarred pasta sauce. Also wine.

What it does mean is that modern industrial food processing — and only modern industrial food processing — has enabled the manufacture of the cheap, convenient, calorie-dense foods engineered to appeal to us that have become staples of our obesogenic diet.

This perspective does seem to predict that the potato diet should cause weight loss, because potatoes are super unprocessed, about the rawest food most people are likely to eat. Participant 20943794 does a nice job pointing out just how unusual potatoes are in this way:

Potatoes are a lot less processed than most food I eat … even the dishes I “make” “myself” have a big pre-made components. For example, when I “make” spaghetti, I used dried noodles that were made in a factory, a jar of sauce that was made in a factory, and beef that was butchered in ground in (at least) an industrial kitchen, if not another factory. The only stuff that’s really raw is the vegetables I chop and add.

So at first glance, the potato diet looks good for the idea that processed foods make you fat.

But there are some problems. First off, even if processed foods make you gain weight, that doesn’t necessarily mean that unprocessed foods will make you lose weight. Foods high in cyanide will kill you, but foods low in cyanide won’t bring you back to life (as far as we know, maybe someone should check). 

We also want to say, we really think this is a non-theory. Even assuming processed foods do make you fat, this isn’t a theory (in our opinion) because it doesn’t address the question of WHY processed foods make you gain weight. 

For comparison: in this study, we’ve found that eating enough potatoes makes you lose weight. But “the potato theory” isn’t a good explanation for the potato diet; we want to know what about potatoes makes this happen! So we really demand to know what it is about processed food that (potentially) makes people gain weight. Treating “processed foods” as a theory itself is at best circular reasoning (“processed foods make you fat because they are processed foods”). 

Not to say that there aren’t potential versions of this idea that do work as a theory. Processed foods might be uniquely low in nutrients that we need to stay lean (potassium?). Or, since they spend so much time in contact with industrial machinery, they might be especially high in obesogenic contaminants.

Contamination

There are all kinds of contaminants in the environment that didn’t used to be there. We know that some chemicals can cause weight gain in humans and animals. With these two facts in mind, we think it stands to reason that the obesity epidemic could be caused by one or more contaminants that are getting into our brains and messing up our ability to properly regulate our body weight. We presented a version of this theory in our book/series A Chemical Hunger, and while we don’t think it’s a sure thing, we do think that there’s a lot of evidence in favor. 

The potato diet is definitely consistent with the contamination theory. Since potatoes are so incredibly unprocessed, they are presumably unusually low in most contaminants. Whatever contaminant you might be concerned about, there is probably less in a plain baked potato than there is in a steak, candy bar, or box of pasta. 

The main wrinkle here is that weight loss on the potato diet is so fast, which is a little weird if we assume that the obesity epidemic is caused by contaminants. It seems like something about the potatoes would have to either stop the contaminants from messing with your lipostat, or would have to rapidly flush the contaminants from your body. 

Lithium

We think lithium may be one contaminant contributing to the obesity epidemic (we covered this in Part VII and Interludes G, H, and I of A Chemical Hunger, and we published some correspondence with a specialist here).

Briefly, the lithium hypothesis looks plausible because lithium causes weight gain at clinical doses, and we know people are exposed to more lithium now than they were back in the 1960s. The only thing is, how much lithium do you need to get exposed to before you start gaining weight, and are we getting exposed to at least that much? We’re working on answering these questions, but we have found some evidence that people get exposed to quite a bit in their food (though it’s complicated). 

The fact that the potato diet causes weight loss isn’t really strong evidence for or against the lithium hypothesis. But we do want to point out, it’s consistent with the lithium hypothesis.

Potatoes are high in potassium, and there’s evidence that potassium competes with lithium in the brain in interesting ways. If obesity is caused by your brain getting all gummed up with lithium, and potassium makes it stop, then the high levels of potassium in potatoes would be the sort of thing that might cause lots of rapid weight loss.

Participant 02142044 mentioned this hypothesis: 

You probably already know this, but I find it credible a potential reason as to why the diet works, if it does, is that it is helping clear lithium, which would also help explain the mild hypomanias people experience. https://jasn.asnjournals.org/content/10/3/666 seems to indicate that potassium and sodium can help with clearing lithium. That is also why I started salting more.

The fact that the potato diet causes hypomania in some people and fear & grief effects in others is also maybe consistent with lithium, since lithium is both an antimanic and a sedative.

Another mark in favor is that we do have some idea of what foods may be high in lithium, and there are a few hints that these foods can boot people out of potato mode and stop their weight loss. In particular, we have reason to think that tomatoes are often high in lithium, and one of our participants reported this: 

Another food group that we think is often high in lithium is dairy, and there’s again some evidence that eating dairy can limit the potato diet. Consider this story from participant 29550957:

This is pretty much the best diet I’ve ever been on, including earlier this year when I also ate mostly potatoes- but with tons of dairy (butter, sour cream, cheese) on them. Despite literally messing up an entire week’s worth of days, I seem to be durably down about 10lbs.

If this is the case, then cheating on foods that are low in lithium should always be fine, and may explain why people were able to cheat on this diet so much and still see the effects.

Cheating on foods that CAN be high in lithium is a gamble. A crop that concentrates lithium won’t grab much if it’s grown in a lithium-poor environment, but will be totally loaded if it’s grown in a lithium-rich environment. So it’s quite possible that that e.g. some ketchup is loaded with lithium and some isn’t, depending on where it was grown, how it was processed, etc. This would look like ketchup making a huge difference for some people and not at all for others.

Unfortunately we still don’t have a great list of which foods are high and which are low in lithium. The list we do have, we don’t particularly trust, which is why we are gonna do our own survey of the food supply.

However if we had to guess right now, our best bets for foods that are high in lithium (and if this hypothesis is correct, might inhibit the potato diet) are: Eggs, milk, soft cheeses (but maybe not butter or hard cheese?), anything containing whey, tomatoes, goji berries, leafy greens, beef, pork, carrots, and beets. But again, this list ain’t gospel. 

One point against the lithium-potassium hypothesis is that participant 23300304 sent us blood work from both before and after the diet, and his potassium levels only went from 4.0 mmol/L to 4.5 mmol/L, both within the normal range. But blood levels may not be relevant, since this kind of thing tends to be under tight biological control, and of course we know that potatoes are high in potassium.

If the lithium-potassium competition hypothesis is true, other high-potassium, low-lithium diets might also cause weight loss. There’s a little bit of evidence that potassium consumption is related to successful weight loss, which makes this seem plausible. 

But straight potassium supplementation may or may not work. At first we thought you could just give people potassium salt and see what happened, but we talked to a specialist who studies lithium clearance from the brain, and he said that the bioavailability of potassium from different sources complicates this a lot. We’re still trying to figure out what a good design for this study would be, but it’s not necessarily as simple as “consume a lot of potassium, avoid tomatoes and whey, and lose a lot of weight”, though we suppose someone could try it and see. 

Looking at lithium and potassium in the urine of someone doing the potato diet might help with this, and so we’re considering asking for urine samples in future studies. But it might also be inconclusive.

For example, maybe lithium raises your lipostat set point by gumming up the brain somehow, and high levels of potassium lower the set point by increasing lithium clearance and forcing it all out of the brain. Lithium that gets forced out of the brain has to go somewhere, and if this were the case, it would probably end up in the urine, so you would see elevated levels of lithium in people who enter potato mode.

But maybe lithium causes obesity by forcing potassium out of the brain, and high levels of potassium cure obesity by supplementing potassium faster than the lithium can clear it. If something like this were the case, you might not see more lithium in people’s urine when they go on the potato diet. 

Probably neither of these explanations are exactly correct — these are just examples to show that urine tests during the potato diet might be a good idea, but won’t be conclusive. 

Something else about Potassium

But it’s also not like potassium and lithium are married. Potassium could still cause weight loss even if the lithium hypothesis is totally wrong. Potatoes are notorious for being high in potassium, so it’s reasonable to suspect that this might be the active ingredient.

That said, if it’s not lithium, why would potassium cause weight loss? We don’t know. Any ideas? 

Don’t most theories predict weight loss on the potato diet?

Well, yes and no. Many theories do predict weight loss on the potato diet; but most theories don’t predict potato mode, this state where hunger disappears and you (occasionally) feel charged with incredible energy.

Finally, to anyone who thinks they knew it would work in advance… 

Ok wise guy. 

If you predicted (or could have predicted) that the potato diet would cause this kind of weight loss, or if medical / nutritional science could have predicted that this diet was going to be so effective in the short term, and so easy for so many people — then why haven’t doctors and nutritionists been recommending the potato diet to people alongside diet and exercise?

Why did all these popular press articles have doctors and nutritionists throwing a fit about how dangerous and unhealthy the potato diet would be? Look at these comments they got on stories about Andrew Taylor, who lost over 100 lbs on the potato diet:

“I personally would not recommend it,” says Dr. Nadolsky. “It’s very restrictive. A vegan diet is very restrictive and a ketogenic diet is very restrictive, but a potato diet is one of the most restrictive diets you could ever do.” … the diet itself would be very hard to stick with for most people, says Dr. Nadolsky.

Or this, from a story about Penn Jillette

This type of extreme diet can pose serious health risks due to its severe limitations. “While there’s no doubt that potatoes — just like all vegetables — are supremely nutritious, eliminating almost all other food groups in totality is not only dangerous, but can really backfire,” says Jaclyn London, M.S., R.D., Nutrition Director at the Good Housekeeping Institute.

If you knew the potato diet would work, why did you not run this study many years ago? Why are there no clinical trials? Did you think people would not be excited to see this result? 

Guess the NIH is too scared of the tater.

8. How to Potato Diet if you want to Potato Diet

We’re not currently accepting signups, but we know that some of you will want to try the potato diet for yourselves. So here is some current advice, from us and from some participants.

First, our advice:

  • When you start off, try eating mostly (> 95% of your calories) potatoes, with a little oil, and as much hot sauce and salt as you want. You can also have zero-calorie beverages like black coffee and tea. This seems really strict but many people find it to be much easier than they expected, so give this version a try first. 
  • If you feel bad/weird and are like “I can no longer stand potatoes!”, try:
    • Eating a potato. Hunger feels different on this diet and you may not realize that you are hungry. Yes, really. 
    • Drinking water. It’s really easy to get dehydrated on this diet, and again you can’t always tell. 
    • Eating a different kind of potato. There are many varieties, try mixing it up. You will almost certainly want to eat more than one kind of potato.
    • Peeling your potatoes. Eating less peel / no peel seems to help some people with digestive and energy issues, especially after a few days on the diet. 
    • Eating more salt. Potatoes are naturally low in sodium and you may not be getting enough. 
    • Getting sunlight. Potatoes have no vitamin D, you may be craving that.
    • If none of these other things help, do a cheat meal and eat whatever you’re craving. (But maybe still avoid dairy?) If you find you keep taking cheat meals, go ahead and drop down to the 80%, 60%, or even a lower % potato diet. The 40% potato diet works just fine for some people. 
  • If you still feel bad after trying these steps, stop the diet. If you are suffering then the diet isn’t working anyways, and you shouldn’t take risks with your health. Plus life is too short to do things that make you miserable.
  • If the diet is easy but you’re not losing weight (or otherwise not seeing effects), try doing 100% potato, no oil.

And here’s some advice from participants:

(33217580) I found that despite all the warnings, it was really easy to underprepare and end up with not enough food. The days where I either had done enough prep or just had time to go cook were definitely much simpler than the days where I would have been happy to just eat some boiled potatoes, but sadly the tupperware was empty, and I got really hungry, ate chips or fries, was a little lower on energy or moodier etc. If I’m going to continue (and I might, because it worked so well!), I’m going to aim for comically large  proportions in food prep, because then I might actually have something close to enough.

(31664368) Advice: figure out a way to exit the diet gracefully. I have a robust belly, but significant GI issues I am still going through. Perhaps it was 1 thing I ate that set things on a bad track for several days. Trying oatmeal and crackers as easy non-potato food, but would love a playbook of how to get back to feeling solid after eating a burrito.

(14122662) If I were doing this again, I might also invest in a nice knife. I noticed that chopping the potatoes each day was effortful and a strain on my hand. Being able to slice through the potatoes more cleanly would have been a nice convenience.

(63187175) It requires a lot of preparation and staying ahead of your meals. Potatoes aren’t something you can just grab out of the cupboard and eat, there’s always some amount of cooking required and (at least in my limited experience) that cooking is either quite labor or time intensive (and usually both). If I do this again, my main takeaway lesson is that to be successful in sticking to it, I need to very deliberately over-prepare and always make way more than I want at a time. Just-in-time preparation is way too hard to follow. When I get home from a long day at work and discover that there are no potatoes already made, those were always the moments when I absolutely hated this diet. Even worse, I ran out of potatoes many times during these 3 weeks and had to take a trip to the store before I could even start cooking. Another area where I’d be more diligent if I try this again.

(02142044) How I’d do it again

– Ensure that my weighing scale is reliable

– Keep not using oil

– Stick to the diet strictly throughout

– Only eat potatoes boiled in their own water (mostly or only yellow?).

– Buy them in bio market if possible?

– Probably still eat sweet potatoes weekly for vit A?

– No exercises during this period.

– Do it in a period with less changes in my life overall (no medication, no changing location in between, no big relationship changes, etc)

– Keep filtering water throughout

– Change the way I track thing:

  * Note how much kg of potatoes I eat each meals.

  * Change “Mood” to “Lowest low”, “Highest high”, “Irritability”, “Fluctuation” and “Highest calm/plenitude”

  * Keep track of “How tired am I of this diet?”

  * Also note what is happening in my life to see other kinds of corelations.

– Supplement in B12 way more, salt my meals from the beginning

– No garlic. Cayenne pepper and tabasco are okay

(81125989) Advice to others trying the diet:

Feeling lazy? Trader Joe’s olive-oil Kettle-cooked potato chips for the win. Only three ingredients – potato, olive oil, and salt.

Choose cooking methods that are very low-prep-time, yet high-bulk. At first, I sliced potatoes before baking – this took over an hour each time and only made enough for one meal. Eventually, I realized I could just cut slits in whole potatoes, coat ’em in olive oil & salt, and dump ’em in the oven. Easy & makes enough for 2 days.

Variety is the spice of potato life. Get different kinds of potato, or you will get so intensely bored. (Also, get sweet potatoes for Vitamin A. Maybe placebo, but I noticed my evening low-light vision got worse, but improves the day after I eat sweet potato)

Schedule cheat days? I’ll have to wait to see your full analysis on the dose-response of the potato diet (weight loss vs days cheated)… but if the dose-response is good, then I recommend scheduling cheat days to stave off boredom. (Also, for social eating.) In particular, I ate red meats to get my B12. You can also eat liver or clams. Also potato has no Vitamin D, go get lots of sun or eat dairy/fatty fishes. (I don’t trust supplements; every time I’ve looked at a pre-registered RCT of a vitamin supplement, it’s either near-zero or somehow way less than just eating a whole food that’s known to be a source of it.)

(31497197) Howtos:

 – Buy lots of potatoes.  Bake off or boil off five or ten pounds every couple days, then refrigerate to eat, mash, fry as wedges, roast as cakes, etc.  

 – Takiea baked potato that can be microwaved as needed, and or a small tupperware thing of mashed potato with some chilli/garlic/hot sauce in it when going places for long enough that being hungry will come up, but tables/utensils/microwaves etc will be available.

 – Properly flavored mashed can be used as a dip for potato chips or something when going camping, etc.

 – If with a group at a restaurant, order fries, or just have a beer.  The mashed potato might be full of dairy fat.

 – When eating non-potato snacks, make a note and carry on.  Make sure they aren’t dairy.  

 – Make peace with breaking the diet for a meal every so often.  It will happen sooner or later.  Try not to, but eventually (group camping, or a nice restaurant, or something) it will be better to break the diet than not.  Do so, and get back on potato immediately afterwards.

(21112694) While I only did about five whole days of the diet, I would highly recommend a 1-2 day transition off the diet. The day I ended, I went out for an event and had a large dinner which my digestive tract was not ready for. I typically have no issues with my GI tract, so I figured it wouldn’t be an issue given the shorter diet period. It could have just been a one-off random occurrence, but if you see this trend pop up more, it may be beneficial to suggest a slower transition off the diet, especially for those with GI issues like IBS (I don’t have any). 

9. What’s Next

We’re very happy with this study, but there are some major limitations. Almost all of our participants were white, and most of them were Americans. We expect these results will generalize to other groups in other contexts, but frankly it’s not in the data. 

The potato diet definitely causes weight loss, but a few major questions remain. Questions like, why do some people hit a wall immediately, and find the diet impossible after only a few days? Why do a few people suddenly hit a wall after about 3 weeks?

What’s up with cheat days? Does the 80% potato diet work for everyone? Can some people lose weight on the 40% potato diet? What about the 20% potato diet? The SMTM author who tried the potato diet didn’t lose any weight until they cut out all oil, at which point they started losing about a pound a day. So for some people it seems like the 100% potato diet is really necessary? Is that true? Why would that be? 

Is the attrition rate really higher, and is the diet more difficult, for women / people with two X chromosomes? If so, why? What about trans people? If there’s a chromosomal effect, how does it interact with exogenous hormones?

All of these are questions that would be good to answer in future work.

Our current plan is to follow up with our participants in 6 months, 1 year, and 2 years (assuming it’s still interesting/relevant at that point). We’ll make posts with those results, and share the data publicly, as these followups happen, so look for the first followup post about six months from now.

We may also go back into these data and do more analyses, since there are almost certainly more things to find in the data we’ve already collected. 

Also, expect a forthcoming post on reflections about doing this kind of shoestring internet science. Keep your eyes peeled.

weirdly large number of image search results for “winking potato”

We’re not currently taking signups, but if you want to try the potato diet for yourself, why not track your data using a structured spreadsheet, so all resulting data will be standardized. You’re welcome to download a copy of THIS FORM and follow the instructions, and you can send us an email with your copy of the form when you’re done. Just include the words “Potato Diet” in the email title so the emails are easy to sort and track.

If we can secure funding, our next study may be “potato camp”, a project where we send 20 or more overweight & obese volunteers to a summer camp and serve them nothing but potatoes for four weeks. This would allow us to replicate these results in a slightly more controlled fashion, collect things like urine and serum samples, and so on. And it would be a pretty good deal for participants — we’d make sure there’s wifi, so if you have a remote job, you can just drop by for four weeks and keep working as normal. If you’d be interested in attending potato camp, SIGN UP HERE. If you’d be interested in funding this project, contact us

We might also run other studies, but we’re still figuring out what would be the best and most fun use of our time. Maybe we will run something on potassium. Or maybe our next study will be unrelated to obesity, it’s not the only interesting research topic in the world.

If you would like to be notified of future stupid studies like this one, SIGN UP HERE. You can also just subscribe to the blog itself by email (below), or follow us on twitter, if you want to keep up with our work in general.

And if you feel like reading this post has added a couple of dollars’ worth of value to your life, or if you have lost weight on the potato diet and you think it improves the quality of your life by more than one dollar a month, consider donating $1 a month on Patreon

Thanks for going on this journey with us.

Sincerely, 
Your friendly neighborhood mad scientists,
SLIME MOLD TIME MOLD

[PEER REVIEWED BY ADAM MASTROIANNI]


End Note: Academics, you may cite this report as–

Time Mold, S. M. (2022). LOSE 10.6 POUNDS in FOUR WEEKS with this ONE WEIRD TRICK Discovered by Local Slime Hive Mind! Doctors GRUDGINGLY RESPECT Them, Hope to Become Friends. SLIME MOLD TIME MOLD.

Total Diet Studies and the Mystery of ICP-MS

After our recent post on Lithium in Food, several readers pointed us to a literature on “Total Diet Studies”, or TDS for short.

The TDS approach is pretty intuitive: if you want to study contaminants or residues that people are maybe exposed to through their food, one way to do that is to drive around to a bunch of actual grocery stores and supermarkets, buy the kinds of foods people actually buy and eat, prepare the foods like they’re actually prepared in people’s homes, and then test your samples for whatever contaminants or residues you’re concerned about. 

Or in the words of a review paper on the Total Diet Study approach from 2014:

A Total Diet Study (TDS) generally consists of selecting, collecting and analysing commonly consumed food purchased at retail level on the basis of food consumption data to represent a large portion of the typical diet, processing the food as for consumption, pooling the prepared food items into representative food groups, homogenizing the pooled samples, and analysing them for harmful and/or beneficial chemical substances (EFSA, 2011a). From a public health point of view, a TDS can be a valuable and cost effective complementary approach to food surveillance and monitoring programs to assess the presence of chemical substances in the population diet and to provide reliable data in order to perform risk assessments by estimating dietary exposure.

These papers include measurements of trace elements in various foods, and some of them include measurements for lithium. We didn’t find these papers while writing our first review of the levels of lithium in food and drink because these papers aren’t looking for lithium specifically — they’re looking at all sorts of different contaminants and minerals, and lithium just happens to sometimes make the cut.

Some Total Diet Studies, like this one from the US in 1996, this one from Egypt in 1998, this one from Chile in 2005, this one from Cameroon in 2013, and this one from China in 2020, don’t measure lithium. In fact the USDA has been doing a Total Diet Study since 1961, and haven’t ever measured lithium. 

But anyways, several of these papers do include measurements of lithium in various national food supplies, and they’re strange, because unlike every other source we’ve seen, which all routinely find some foods with more than 1 mg/kg lithium, they find less than 0.5 mg/kg lithium in every single food. 

TDS with Li

The oldest TDS study we’ve seen that includes lithium is from 1999 in the United Kingdom, reporting on the UK 1994 Total Diet Study and comparing those results to data from previous UK Total Diet Studies. (The UK TDS has been “carried out on a continuous annual basis since 1966” but it seems like they only started including lithium in their analysis in the 1990s.) They report the mean concentrations of 30 elements (aluminium, antimony, arsenic, barium, bismuth, boron, cadmium, calcium, chromium, cobalt, copper, germanium, gold, iridium, iron, lead, lithium, manganese, mercury, molybdenum, nickel, palladium, platinum, rhodium, ruthenium, selenium, strontium, thallium, tin, and zinc) in 119 categories of foods, combined into 20 groups of similar foods for analysis.

The highest mean concentration of lithium they found in the food categories they examined was an average of 0.06 mg/kg (fresh weight) in fish. They estimated a total exposure of 0.016 mg lithium a day, and an upper limit of 0.029 mg a day, in the British diet at the time. This appears to be substantially less than the amount found in a 1991 sample, which gave an estimate of 0.040 mg lithium a day in the British diet. They explicitly indicate there is no data on lithium in foods (in their datasets) from before 1991.

France conducted a TDS in 2000, and a report all about it was published in 2005. They looked at levels of 18 elements (arsenic, lead, cadmium, aluminium, mercury, antimony, chrome, calcium, manganese, magnesium, nickel, copper, zinc, lithium, sodium, molybdenum, cobalt and selenium) in samples of 338 food items.

The highest mean concentration of lithium they found in the food categories they examined was an average of 0.123 mg/kg in shellfish (fresh matter) and 0.100 mg/L in drinking water. They estimated an average daily exposure of 0.028 mg for adults, with a 97.5th percentile daily exposure of 0.144 mg. They specifically mention, “drinking waters and soups are the vectors contributing most (respectively 25–41% and 14–15%) to the exposure of the populations; other vectors contribute less than 10% of the total food exposure.”

France did another TDS in 2006, with a report published in 2012. This time they looked at Li, Cr, Mn, Co, Ni, Cu, Zn, Se and Mo in 1319 samples of foods typically consumed by the French population.

Similar to the first French TDS, the highest mean concentration of lithium they found in the food categories they examined was an average of 0.066 mg/kg (fresh weight) in shellfish. But the highest individual measurements were found in two samples of sparkling water, with 0.612 mg/kg and 0.320 mg/kg.

New Zealand seems to run a Total Diet Study programme every 4–5 years since 1975, but we’ve only been able to find lithium measurements from this project in a paper from 2019, looking at data from the 2016 New Zealand Total Diet Study. Maybe, like some of the other TDS projects, they only started including lithium testing later on. Anyways, in this paper they looked at 10 elements (antimony, barium, beryllium, boron, bromine, lithium, nickel, strontium, thallium and uranium) in eight composite samples each of 132 food types.

This paper is a little strange, and unlike most of these papers, doesn’t give much detail. They summarize the main findings for lithium as, “the reported concentrations ranged from 0.0007 mg/kg in tap water to 0.54 mg/kg in mussels” and say that the mean overall intake of lithium in New Zealand adults is 0.020–0.029 mg/day.

The most recent TDS that looked at lithium seems to be this 2020 paper, which looks at food collected between October 2016 and February 2017 in the Emilia-Romagna Region in Italy. They looked at levels of fifteen trace elements (antimony, barium, beryllium, boron, cobalt, lithium, molybdenum, nickel, silver, strontium, tellurium, thallium, titanium, uranium, and vanadium) in 908 food and beverage samples from local markets, supermarkets, grocery stores, and community canteens.

The highest concentration of lithium they found in the food categories they examined was in fish and seafood (50th percentile 0.019 mg/kg, IQR 0.010–0.038 mg/kg), and legumes (50th percentile 0.015 mg/kg, IQR 0.006–0.035 mg/kg). They estimate a dietary lithium intake for the region of 0.018 mg/day (IQR 0.007–0.029 mg/day).

So overall, these papers report that lithium levels in foods and beverages never break 0.612 mg/kg, and almost universally keep below 0.1 mg/kg.

How About Those Numbers

We’re skeptical of these numbers for a couple of reasons.

For starters, these five papers disagree with basically every other measurement we’ve ever seen for lithium in food.

The TDS papers say that all foods and beverages contain less than 1 mg/kg lithium, and that people’s lithium intake is well below 1 mg a day. But this is up against sources like the following, which all find much higher levels (not an exhaustive list):

  • Bertrand (1943), “found that the green parts of lettuce contained 7.9 [mg/kg] of lithium”
  • Borovik-Romanova (1965) “reported the Li concentration in many plants from the Soviet Union to range from 0.15 to 5 [mg/kg] in dry material”, in particular listing the levels (mg/kg) in tomato, 0.4; rye, 0.17; oats, 0.55; wheat, 0.85; and rice, 9.8.
  • Hullin, Kapel, and Drinkall (1969) found more than 1 mg/kg in salt and lettuce, and up to 148 mg/kg in tobacco ash.
  • Duke (1970) found more than 1 mg/kg in some foods in the Chocó rain forest, in particular 3 mg/kg in breadfruit and 1.5 mg/kg in cacao. 
  • Sievers & Cannon (1973) found up to 1,120 mg/kg lithium in wolfberries.
  • Magalhães et al. (1990) found up to 6.6 mg/kg in watercress at the local market.
  • Ammari et al. (2011), looked at lithium in plant leaves, including spinach, lettuce, etc. and found concentrations in leaves from 2 to 27 mg/kg DM.
  • Manfred Anke and his collaborators found more than 1 mg/kg in a wide variety of foods, in multiple studies across multiple years, up to 7.3 mg/kg on average for eggs.
  • Schnauzer (2002) reviewed a number of other sources finding average intakes across several locations from 0.348 to 1.560 mg a day.
  • Five Polish sources from 1995 that a reader recently sent us reported finding (as examples) 6.2 mg/kg in chard, 18 mg/kg in dandelions, up to 470.8 mg/kg in pasture plants in the Low Beskids in Poland, up to 25.6 mg/kg in dairy cow skeletal muscle, and more than 40 mg/kg in cabbage under certain conditions. (These papers aren’t available online but we plan to review them soon.)   

It seems like either the measurements from the TDS papers are right, and all foods contain less than 1 mg/kg lithium, or all the rest of the literature is right, and many plants and foods regularly contain more than 1 mg/kg lithium. The alternative, that both of them are right, would mean that the same foods consistently contain less than 1 mg/kg in France and New Zealand while containing more than 1 mg/kg in Germany and Brazil. This seems like the most far-fetched possibility.

There are three strikes against the TDS numbers. First, they’re strictly outnumbered. When five papers from four sources (two of those papers are from France) say one thing and the rest of the literature clearly says another, it’s not a sure thing, but the side with more evidence… well it has more evidence for it.

Second, the TDS studies have a divided focus. They’re not really interested in lithium at all; they’re interested in the local food supply, and lithium just happens to be one of between 9 and 30 different elements they’re testing for. In comparison, pretty much all the other papers are looking at lithium in particular. If we had to guess which kind of team is more likely to mess up this kind of analysis, the team interested in this one particular element, or the team that randomly included the element in the list of several elements they’re testing for, we know which we’d pick. It’s hard to imagine that every team looking for lithium chose the wrong analysis or screwed it up in the same way somehow. It’s easy to imagine that the TDS studies, which measured lithium incidentally, might get some part of the analysis wrong.

It’s kind of like clothing. Ready-made sizes will fit most elements, but if you have an unusual body type (really long arms, really thick neck, etc.) you may have to go to a tailor. And lithium has the most unusual body type of all the solid elements. It wouldn’t be at all surprising if off-the-rack clothes didn’t fit poor little lithium.

uhhhhh spectral analysis

The third thing that’s strange is that there seem to be some internal contradictions within the studies. For example, in the first French TDS study, the lithium levels in water are much higher than lithium levels in things that are made out of water, which seems impossible. The mean lithium level in drinking water is 0.100 mg/kg, but the lithium levels in things that are mostly water are much lower: 0.038 mg/kg in soups, 0.006 mg/kg in coffee, 0.004 in non-alcoholic beverages, 0.003 in alcoholic beverages, and 0.002 in hot beverages. Soup is maybe a little different, but coffee and beverages are mostly water. How can there be fifty times more lithium in plain water than in hot beverages, which are (we assume) mostly water? 

For that matter, how can drinking water be the category with the second-most lithium (after shellfish)? Water is the main ingredient in beverages, but it’s also a major ingredient of pretty much every food. Fruits, salads, milk, vegetables, etc. etc. all contain lots of water. Unless there’s some major, universal filtering going on, there should be more lithium in at least some foods than there is in water. 

And that’s what you see if you look at the other elements in this first French paper — more in foods than in water. For example, the average level of manganese in drinking water in these data is 0.19 mg/kg, and the mean levels in beverages are all 0.30 mg/kg or higher; the mean level in soup is 0.97 mg/kg; the mean level in fruits is 2.05 mg/kg, much higher. Same for zinc. The mean level in drinking water is 0.05 mg/kg, which is the lowest mean level of zinc of any food category. Other elements, at least, tend to have higher concentrations in some foods than in water.

In the second French TDS study, the same thing happens. The highest concentration of lithium they found in any food was in water, 0.612 mg/kg. The mean for water this time around was only 0.035 mg/kg, but that’s still higher than the means for most beverages and the mean for almost every food. 

(The other TDS papers don’t give mean lithium measurements for water, so we can’t do the same comparison with them.)

This doesn’t make much sense. Water is a major component of many foods and it would be shocking if lithium didn’t find its way from water into food (and more obviously into beer and tea). But all of the fruits and vegetables have less lithium than the water that would presumably be used to irrigate them. 

There’s a rich literature of hydroponics experiments that shows that all sorts of plants accumulate lithium. When you grow them in a lithium solution under controlled conditions, or in soil spiked with lithium, the plants end up containing a higher concentration of lithium than the solution/soil they were grown in.

These spikes are much larger than the levels of lithium plants are normally exposed to in the environment, but they’re experimental evidence that lithium accumulates, even to enormous degrees. You should reliably expect to see more lithium in plants than in the water they’re grown with. There might be some plants that don’t accumulate, but water shouldn’t universally contain the highest amounts.

We didn’t really include these sources in our original review because that was a review of lithium in food, and these hydroponically-grown experimental plants aren’t in the actual food supply. But they’re pretty informative, so here’s a selection of the studies: 

  • Magalhães et al. (1990) grew radish, lettuce and watercress in a hydroponic system, with solution containing lithium levels of 0.7, 6.8 and 13.6 mg/L. These are all somewhat high, but exposure to 0.7 mg/L in water isn’t totally unrealistic. Plants were collected thirty days after transplanting. At the lowest and most realistic level of exposure, 0.7 mg/L, lettuce contained 11 mg/kg lithium, radish bulbs contained 11 mg/kg, radish leaves contained 17 mg/kg, and watercress contained 37 mg/kg. At 6.8 mg/L in the solution all plants contained several hundred mg/kg, and at 13.6 mg/L, radish leaves and watercress contained over 1000 mg/kg.
  • Hawrylak-Nowak, Kalinowska, and Szymańska (2012) grew corn and sunflower plants in glass jars containing 0 (control), 5, 25, or 50 mg/L lithium in a nutrient solution. After 14 days, they harvested the shoots, and found that lithium accumulated in the shoots in a dose-dependent manner. Even in the control condition, where no lithium was added to the solution, sunflower shoots contained 0.9 mg/kg and corn shoots contained 4.11 mg/kg lithium. At 5 mg/L solution, sunflower contained 422.5 mg/kg and corn contained 72.9 mg/kg; at 25 mg/L solution, sunflower contained 432.0 mg/kg and corn contained 438.0 mg/kg; at 50 mg/L solution, sunflower contained 3,292.0 mg/kg and corn contained 695.0 mg/kg. These levels are unrealistically high, but the example is still illustrative.
  • Kalinowska, Hawrylak-Nowak, and Szymańska (2013) grew lettuce hydroponically in solution containing 0, 2.5, 20, 50 or 100 mg/L lithium. Lithium concentrations above 2.5 mg/L progressively fucked the plants up more and more, but there was clear accumulation of lithium in the lettuce. There was some concentration in the leaves in a solution of 2.5 mg/L (though they don’t give the numbers), and when the lettuce was grown in a 20 mg/L solution, there was around 1000 mg/kg in the leaves.
  • Antonkiewicz et al. (2017) is an 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 — it actually grows better when exposed to some lithium, and only shows 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.
  • 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.”

Again, these are unrealistic for the amount of lithium you might find in your food, but they’re clear support for the idea that plants consistently accumulate lithium relative to the conditions they’re grown in. It doesn’t make sense that we see water having the highest concentration in the TDS data.

This is your sunflower leaf on 50 mg/L lithium

So for all these reasons, we’re pretty sure that the TDS numbers are wrong and that the lithium-specific literature is right. Specialty research that looks for lithium in particular is more reliable in our opinion than sources that happen to look at lithium as one contaminant along with a dozen others. 

But even so, you’d have to be terminally incurious to look at this and not wonder what was going on. Why do these five papers have measurements that don’t match the rest of the literature? 

What’s Going on in the TDS

Since these papers disagree with every other source, and they all share the same Total Diet Study approach, it seems like there must be something wrong with that approach. 

Sometimes this kind of mistake can come from problems with the equipment, dropping a decimal, or misreading units, like mistaking mg/kg for µg/kg.

But we have a hard time imagining that all of these different teams with (as far as we can tell?) no overlap in authors would be making exactly the same error of using the wrong units or moving a decimal place. It’s possible they all use the same slightly-misleading software or something; we have seen a few other papers that report lithium in one set of units, and every other element they test for in different units. But again, it would be weird for every single TDS study to screw this up in exactly the same way. 

So we went back and took a closer look at their methods. What we noticed is that every one of these TDS studies used the same analysis technique — inductively coupled plasma mass spectrometry, or ICP-MS. 

So we wonder if there might be an issue with ICP-MS. 

Let’s take a closer look at those TDS methods: 

The 1999 TDS paper from the United Kingdom:  

Samples of each food group … were homogenized and digested (0.5 g) in inert plastic pressure vessels with nitric acid (5 ml) using microwave heating (CEM MDS 2000 microwave digestion system). All elements except mercury, selenium and arsenic were analysed by Inductively Coupled Plasma-Mass Spectrometry (ICP-MS) (Perkin Elmer Elan 6000).

The 2005 first TDS paper from France:

The elementary analyses (about 18 000 results in all) were carried out by the Environmental Inorganic Contaminants and Mineral Unit of the AFSSA-LERQAP, which is the national reference laboratory. All the 998 individual food composite samples were homogenized and digested (about 0.6 g taken from each sample) in the quartz vessels with suprapure nitric acid (3 ml) using Multiwave closed microwave system (Anton-Paar, Courtaboeuf, France). The total content of all selected essential and non essential trace elements in the foods was determined by Inductively Coupled Plasma-Mass Spectrometry (ICP-MS) (VG PlasmaQuad ExCell-Thermo Electron, Coutaboeuf, France), a very powerful technique for quantitative multi-elemental analysis.

France again in 2012:

The National Reference Laboratory (NRL) for heavy metals was chosen to analyse 28 trace elements, and among them nine essential elements, Li, Cr, Mn, Co, Ni, Cu, Zn, Se and Mo, by inductively coupled plasma-mass spectrometry (ICP-MS) after microwave-assisted digestion. 

Sample digestion was carried out using the Multiwave 3000 microwave digestion system (Anton-Paar, Courtaboeuf, France), equipped with a rotor for 8 type X sample vessels (80-mL quartz tubes, operating pressure 80 bar). Before use, quartz vessels were decontaminated in a bath of 10% HNO3 (67% v/v), then rinsed with ultra-pure water, and dried in an oven at 40 °C. Dietary samples of 0.2–0.6 g were weighed precisely in quartz digestion vessels and wet-oxidised with 3 mL of ultra-pure water and 3 mL of ultra-pure HNO3 (67% v/v) in a microwave digestion system. One randomly-selected vessel was filled with reagents only and taken through the entire procedure as a blank. The digestion program had been optimised previously (Noël, Leblanc, & Guérin, 2003). After cooling at room temperature, sample solutions were quantitatively transferred into 50-mL polyethylene flasks. One hundred microlitres of internal standard solution (1 mg L−1) were added, to obtain a final concentration of 2 μg L−1, and then the digested samples were made up with ultrapure water to the final volume before analysis by ICP-MS.

ICP-MS measurements were performed using a VG PlasmaQuad ExCell (Thermo, Courtaboeuf, France). The sample solutions were pumped by a peristaltic pump from tubes arranged on a CETAC ASX 500 Model 510 autosampler (CETAC, Omaha, NE). 

The 2019 New Zealand TDS paper doesn’t give much detail at all. They just say: 

Samples were analysed for 10 toxic elements by ICP-MS at Hill Laboratories, Hamilton, New Zealand. 

Ok then.

Finally, the 2020 TDS paper from Italy

We measured content of fifteen trace elements (antimony, barium, beryllium, boron, cobalt, lithium, molybdenum, nickel, silver, strontium, tellurium, thallium, titanium, uranium, and vanadium) in 908 food and beverage samples through inductively coupled plasma mass spectrometry.

Using a clean stainless-steel knife, we cut solid foods by collecting samples from six different points in the plate. Then, we homogenized the samples using a food blender equipped with a stainless-steel blade and we placed a portion of 0.5 g in quartz containers previously washed with MilliQ water (MilliQPlus, Millipore, MA, USA) and HNO3. We liquid-ashed the samples with 10 ml solution (5 ml HNO3 + 5 ml·H2O) in a microwave digestion system (Discover SP-D, CEM Corporation, NC, USA) and we finally stored them in plastic tubes, and diluted to 50 ml with deionized water before analysis. Using an inductively coupled plasma mass spectrometer (Agilent 7500ce, Agilent Technologies, CA, USA), we performed trace element determination.

So, all of these papers use the same analysis technique, ICP-MS. We don’t know the exact technique used by the team in New Zealand, but all the other teams used microwave digestion with nitric acid (HNO3). Three of them (the French and Italian TDS studies) used quartz vessels.

The fact that all these studies use similar analysis techniques makes it much more plausible that something about this technique is screwing up something about the lithium detection.

This also seems likely because most other papers, the ones that find more than 1 mg/kg lithium in food, don’t use ICP-MS. Here’s a small selection.

The most recent paper finding more than 1 mg/kg lithium in plant matter seems to have used inductively coupled plasma optical emission spectrometry (ICP-OES), a related but distinct technique. This is Robinson et al. (2018), which found that plants can contain “several hundred mg/kg Li” in leaves. Here’s their procedure: 

Plant samples were washed in deionized water and dried at 60 °C until a constant weight was obtained. Subsequently, they were milled using a Cyclotech type 1093 cyclone grinder with an aluminium rotor. Plant material (0.5 g) was digested in 5 ml HNO3. The digests were diluted with Milli Q (Barnstead, EASYpure RF, 18.3 MΩ-cm) to a volume of 25 ml and filtered with a Whatman 52 filter paper (pore size 7 μm). … Pseudo-total element concentrations (henceforth referred to as “total”) were determined in the acid digests using ICP-OES (Varian 720 ES).

Ammari et al. (2011), looked at lithium in solids (plant leaves, including spinach, lettuce, etc.) and found concentrations in leaves from 2 to 27 mg/kg DM. They used this procedure: 

Collected leaves were gently washed in distilled water, air-dried, and then oven-dried to a constant weight at *70°C. Dry leaves were finely ground in a Moulinex Mill (Moulinex, Paris, France) to pass through a 40-mesh sieve. As Li is known to be present in cell vacuoles in inorganic soluble form, Li was determined in filtrates of oven-dry ground leaf samples (5 g) suspended in 50 ml of deionized water for 1 h. This procedure was used in the current study because not all the lithium present in natural unprocessed foods is taken up by the human body (pers. comm. with nutritionists; Dr. Denice Moffat, USA). Lithium extracted with deionized water represents the soluble fraction that is directly taken up by the gastrointestinal tract and considered the most bio-available. … The concentration of Li in leaf samples was measured with a flame photometer.

Anke’s 2005 paper doesn’t give a ton of detail, but seems to have used atomic absorption spectroscopy (AAS) for lithium, and reports numbers up to 7.5 mg/kg in foods. 

Magalhães et al. (1990) found up to 1,216 mg/kg in (hydroponically-grown, experimental) watercress and say: 

Thirty days after transplanting, the plants were harvested, shoots and roots separately, and their fresh weight determined. They were oven-dried at 700C for 72 hours, weighted, ground in a Wiley mill and analyzed for N, P, K, Ca, Mg, Fe and Li contents after digestion in H2SO4 and H202. N was determined by Nesslerization, P by an ammonium molybdate-amino naphthol sulfonic acid reduction method (Murphy & Riley 1962), K and Li by flame emission and Ca, Mg and Fe by atomic absorption (Sarruge & Haag 1974).

Drinkall et al. (1969), one of our oldest sources, found up to 148 mg/kg in pipe tobacco and used “the atomic absorption technique”. Specifically they say: 

Methods for determination of lithium in foodstuffs have in the past been limited almost entirely to the use of the spectrograph and the flame photometer. In the present investigation, however, it was decided to apply the technique of atomic absorption for this purpose. The chief reason for this choice was the lack of occurrence of spectral interference occasioned by elements other than lithium, Indeed, the only elements which were thought likely to prove troublesome were calcium and strontium. Even these, however, were found not to interfere. The instrument used throughout this work was the Unicam SP90 Atomic Absorption Spectrophotometer, a propane-air flame being employed.

So this diverse set of methods all found levels of lithium above 1 mg/kg, while the “ICP-MS with microwave digestion in nitric acid (usually in quartz vessels)” technique seems to reliably find way less than 1 mg/kg. This is starting to look like it’s an issue with the analysis.

If this is the case, then if we can find other papers that use ICP-MS with microwave digestion in nitric acid, they should also show low levels of lithium, well below 1 mg/kg. 

That’s exactly what we’ve found. Take a look at Saribal (2019). This paper used ICP-MS and looked at trace element concentrations in cow’s milk samples from supermarkets in Istanbul, Turkey. They found an average of 0.009 mg/L lithium in milk, way lower than the measurements for milk found in sources that don’t use ICP-MS. 

Saribal, like the TDS studies, used ICP-MS to look for lithium alongside a huge number of other elements — 19 in fact. The full list was: lithium, beryllium, chromium, manganese, cobalt, nickel, copper, arsenic, selenium, strontium, molybdenum, cadmium, antimony, barium, lead, bismuth, mercury, thallium, and uranium. Like the TDS studies, they did digestion in nitric acid: 

The quadrupole inductively coupled plasma mass spectrometer (ICP-MS) used in this work was Thermo Scientific X Series II (Thermo Fisher Scientific, Bremen, Germany).

One-milliliter portions of each milk samples were digested in 65% HNO3 and 2 mL 30% H2O2 (Merck, Poole, UK) on a heat block. The temperature was increased gradually, starting from 90 °C and increasing up to 180 °C. The mixture was cooled down and the contents were transferred to polypropyl- ene tubes with seal caps. Each digested sample was diluted to a final volume of 10 mL with double deionized water

Here’s another one. Kalisz et al. (2019) looked at “17 elements, including rare earth elements, in chilled and non-chilled cauliflower cultivars”. They used ICP-MS, they microwave digested with nitric acid, and they found lithium levels of less than 0.060 mg/kg. Here’s the method: 

We investigated the content of Ag, Al, Ba, Co, Li, Sn, Sr, Ti, Sb, and all rare-earth elements. … Curds were cut into pieces and dried at 70 °C in a dryer with forced air circulation. Then, the plant material was ground into a fine and non-fibrous powder using a Pulverisette 14 ball mill (Fritsch GmbH, Germany) with a 0.5-mm sieve. Next, 0.5 g samples were placed in to 55 ml TFM vessels and were mineralized in 10 ml 65% super pure HNO3 (Merck no. 100443.2500) in a Mars 5 Xpress (CEM, USA) microwave digestion system. The following mineralization procedure was applied: 15 min. time needed to achieve a temperature of 200 °C and 20 minutes maintaining this temperature. After cooling, the samples were quantitatively transferred to 25 ml graduated flasks with redistilled water. Contents of mentioned elements were determined using a high-dispersion inductively coupled plasma optical emission spectrometer (ICP-OES; Prodigy Teledyne Leeman Labs, USA).

There are a couple complications, but they’re worth looking at. Seidel et al. (2020) used ICP-MS and found reasonable-seeming numbers in a bunch of beverages. But, as far as we can tell, they didn’t digest the beverages at all. They just say:

Li concentrations in our 160 samples were determined via inductively coupled plasma mass spectrometry (ICP-MS) as summarized in Table 1.

Here’s Table 1 in case you’re curious: 

This seems like evidence that something about the digestion process might be to blame. 

There’s also Voica, Roba, and Iordache (2020), a Romanian paper which used ICP-MS and found up to 3.8 mg/kg in sheep’s milk and up to 4.2 mg/kg in pumpkins. This is pretty surprising — it’s the first ICP-MS paper we’ve seen that finds more than 1 mg/kg lithium in a sample of food. They even use microwave digestion with nitric acid! So at first glance, this looks like a contradiction — but when we looked closer, their method did differ in some interesting ways.

The lithium concentrations were determined by inductively coupled plasma – mass spectrometry (ICP-MS). 

Considering that samples have a very complex composition with large organic matter content, the total digestion of the matrix is mandatory to assure complete metal solubility. The studied samples were subjected to microwave assisted nitric acid digestion by using a closed iPrep vessel speed system MARS6 CEM One Touch. The digestion vessels were cleaned with 10 mL HNO3 using the microwave cleaning program and rinsed with deionized water. Approximately 0.3 g aliquots of the samples were weighed, followed by digestion in 10mL HNO3 60% at high pressure, temperature and in the presence of microwave irradiation. The vessel was closed tightly, placed on the rotor, and the digestion was carried out following the program presented in Table 1.

After complete digestion and cooling, the samples were filtered, transferred to 50 mL graduated polypropylene tubes and diluted to volume with deionized water.

A Perkin Elmer ELAN DRC-e instrument was used with a Meinhard nebulizer and a glass cyclonic spray chamber for pneumatic nebulization. The analysis was performed in the standard mode and using argon gas (purity ≥ 99.999%) for the plasma following the manufacturer’s recommendations.

The operating conditions were a nebulizer gas flow rate of 0.92 L/min; an auxiliary gas flow of 1.2 L/min; a plasma gas flow of 15 L/min; a lens voltage of 7.25 V; a radiofrequency power of 1100 W; a CeO/Ce ratio of 0.025; and a Ba++/Ba+ ratio of 0.020.

We don’t know exactly what the difference might be, but the fact that they mention that “considering that samples have a very complex composition with large organic matter content, the total digestion of the matrix is mandatory to assure complete metal solubility” suggests that they were aware of limitations of normal digestion methods that other teams may have been unaware of. And none of the other papers seem to have used pneumatic nebulization, so maybe that makes the difference and lets you squeeze all the lithium out of a pumpkin.  

yeah that’s one way to do it

Another difference we notice is that while Voica, Roba, and Iordache do use ICP-MS and the same kind of digestion as the TDS studies, they don’t test for anything else — they’re just measuring lithium. So maybe the thing that torpedoes the ICP-MS measurements is something about testing for lots of elements at the same time — a trait shared by all the TDS studies, Saribal (2019), and Kalisz et al. (2019), but not by Seidel et al. (2020) (the beverages paper) and not by Voica, Roba, and Iordache (2020).

A final (we promise) paper that helps triangulate this problem is Nabrzyski & Gajewska (2002), which looked at lithium in food samples from Gdańsk, Poland. They found an average of only 0.07 mg/kg in milk products and of only 0.11 mg/kg in smoked fish. This is not quite as low as the TDS studies but it’s much lower than everything else. And weirdly, they didn’t use ICP-MS, they used AAS. But they did digest their foods in nitric acid. Here’s the method: 

The representative samples were dry ashed in quartz crucibles and the ash was treated with suitable amounts of conc. HCl and a few drops of conc. HNO3. The obtained sample solution was then used for the determination of Sr, Li and Ca by the flame atomic absorption spectrometry (AAS) method. Ca and Li were determined using the air-acetylene flame and Sr with nitrous oxide-acetylene flame, according to the manufacturer’s recommendations.

So maybe this seems like more evidence that it’s something about the digestion process in particular, though this paper could also just be a weird outlier. It’s hard to tell without more tests.

Close Look at ICP-MS

We seem to have pretty clear evidence that ICP-MS, maybe especially in combination with microwave digestion / digestion with nitric acid, gives much lower numbers for lithium in food samples than every other analysis technique we’ve seen. 

So we wanted to know if there was any other reason to suspect that ICP-MS might give bad readings for lithium in particular. We did find a few things of interest.

If you check out the Wikipedia page for ICP-MS, lithium is mentioned as being just on the threshold of what the ICP-MS can detect. This makes sense because lithium is unusual, much smaller than all other other metals. See for example: “The ICP-MS allows determination of elements with atomic mass ranges 7 to 250 (Li to U)” and “electrostatic plates can be used in addition to the magnet to increase the speed, and this, combined with multiple collectors, can allow a scan of every element from Lithium 6 to Uranium Oxide 256 in less than a quarter of a second.” 

While ICP-MS is generally considered the gold standard for spectral analysis, like all methodologies, it has some limitations. Given that lithium is at the bottom of the range to begin with, it seems plausible to us that even small irregularities in the analysis might push it “off the end” of the range, disrupting detection. There’s more likely to be problems with lithium than with the other elements the TDS papers were analyzing.

We noticed that the 1999 UK TDS study had this to say about the upper limits of detection for ICP-MS: “The platinum group elements are notoriously difficult to analyse, as the concentrations, generally being close to the limits of detection, can be prone to some interferences in complex matrices when measured by ICP-MS.” 

Now lithium is on the low end of the range, not the high range. But since the UK TDS study authors were concerned that elements “close to the limits of detection, can be prone to some interferences in complex matrices when measured by ICP-MS”, it seems like interference might be an issue. This shows that “fall of the end of the range” is a real concern with ICP-MS analysis. So ICP-MS may be the gold standard for spectral analysis, but it falls short of being the platinum standard.

There’s also something interesting in Anke’s 2003 paper, where he says:

Lithium may be determined in foods and biological samples with the same techniques employed for sodium and potassium. However, the much lower levels of lithium compared with these other alkali metals, mean that techniques such as flame photometry often do not show adequate sensitivity. Flame (standard addition procedure) or electrothermal atomic absorption spectrophotometry are the most widely used techniques after wet or dry ashing of the sample. Corrections may have to be made for background/matrix interferences. Inductively coupled plasma atomic emission spectrometry is not very sensitive for this very low-atomic-weight element.

As usual with Anke this is very cryptic, and inductively coupled plasma atomic emission spectrometry (ICP-AES) isn’t the same technique as ICP-MS. But even so, Anke’s comment does suggest that there might be some limitations on ICP methods when measuring lithium, that they might not be very sensitive.

We also found an article by environmental testing firm WETLAB which describes several problems you can run into doing lithium analysis, including that “[w]hen Li is in a matrix with a large number of heavier elements, it tends to be pushed around and selectively excluded due to its low mass. This provides challenges when using Mass Spectrometry.” They also indicate that “ICP-MS can be an excellent option for some clients, but some of the limitations for lithium analysis are that lithium is very light and can be excluded by heavier atoms, and analysis is typically limited to <0.2% dissolved solids, which means that it is not great for brines.” We’re not looking at brines, but this may also hold true for digested food samples. WETLAB indicates their preferred methodology is ICP-OES.

Conclusion

Maybe nobody knows what’s going on here! It’s looking more and more like this is just a question that’s sitting out on the limits of human knowledge. It’s a corner case — to know why some papers find high levels and other papers find really low levels, you might have to jointly be an expert on ICP-MS, lithium analysis, and chemical analysis in food. Manfred Anke is the only guy we’ve ever heard of who seemed like he might be all three, and he’s been dead for more than ten years. So maybe there’s no one alive who knows the answer. But that’s why we do science, right?

In any case, we’re very glad to know about this complexity early on in the process of planning our own survey, since we had also been planning to use ICP-MS! We had assumed that ICP-MS was the best technique and that it would certainly give us the most accurate numbers. But measurement is rarely that simple — we should have been more careful, and now we will be.

How do we figure out what’s going on here, and what technique we should use? We could go back and pore over the literature in even more detail. But that would take a long time, and would probably be inconclusive. Much better is to simply test a bunch of foods using different techniques, pit ICP-MS against techniques like AAS and flame photometry, and see if we can figure out what’s going on. So that’s what we’re gonna do.

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: 

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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]