Half-Tato Diet Community Trial: Sign up Now

In the original potato diet study, we asked people to try to eat nothing but potatoes. This worked pretty well — people lost 10.6 lbs on average over just four weeks.

But we also told them, “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 this to heart. We asked people to track how often they broke the diet, and almost everyone took at least one cheat day.

Five people said they stuck to the diet 100%, but everyone else said they broke the diet at least once. Most people cheated only a few times, but as you can see from this histogram, a substantial minority cheated more than half the time:

Taking these cheat days didn’t seem to matter much. Almost everyone lost weight, even if they cheated a lot:

In general, the more often people cheated, the less weight they lost. But even the people who cheated the most still lost around 5 lbs. 

Realistically, our original potato diet study was really more like a 90% potato diet. People took quite a few cheat days, and it mostly didn’t seem to matter. Makes you wonder how low we can push that percent and still have it work — after all, the original weight loss effect was ginormous.

This is one reason why today we are announcing a 50% potato diet study. We’re looking for people to volunteer to get about 50% of their calories per day from potatoes for at least four weeks, and to share their data so we can do an analysis. You can sign up below.

Case Studies

The other reason we’re doing this study is a number of extremely interesting case studies.

Case Study: Joey No Floors Freshwater

The earliest case study comes from Joey “No Floors” Freshwater, who shared his story on twitter. He did a version of the potato diet consisting of “1-1.5lbs of potatoes a day when I could”. This comes out to about a 20% potato diet, and it turns out the 20% potato diet works quite well, at least for Joey. 

Sadly Joey is no longer on twitter, but we do still have the screenshots:  

Nicky Case Study: Nicky Case

The second case study comes from Nicky Case. Nicky participated in the original potato diet study and lost more than 10 lbs over four weeks, without much difficulty. This is kind of striking because Nicky was pretty lean to begin with.

After the potato diet ended, her weight slowly climbed back up. So 50 days after the end of the potato diet, she started a half-tato diet (“at least ONE meal per day is potato”). On the half-tato diet, she lost weight at about half the rate she did on the potato diet, and described it as “TRIVIALLY EASY to do”. Here’s the figure: 

This is very encouraging. Nicky tried both the potato diet and the half-tato diet for more than 40 days each, and the direct comparison makes it pretty clear that the half-tato diet caused about half as much weight loss, at least for her. 

Case Study: M’s Potatoes-by-Default

Our third case study comes from M, a reader whose email we published in December as a Philosophical Transactions post

M tried a version of the potato diet he calls “potatoes by default”. He describes this approach like so:

If I didn’t have anything better to eat, I’d eat potatoes. This meant that if I had plans for lunch or dinner, I would eat whatever it was I would’ve normally eaten ad libitum, and I tried actively to prevent the diet from materially interfering with my lifestyle (I drank alcohol socially as I normally would’ve, I participated in all the meals I normally would’ve participated in with friends, I tried arbitrary new dishes at restaurants, etc.). … In practice, “potatoes by default” meant I was eating potatoes for roughly 1/3 of my meals, mostly for lunch when I was working from home during the week or on weekends, since I usually had dinner plans of some kind. 

This relatively potato-light approach caused surprisingly rapid weight loss. M describes it like so: “I think my main reaction to the data was that it was kind of insane? I was eating potatoes a third of the time and literally whatever else I wanted the rest of the time, and losing weight almost as quickly as the full potato diet.” 

Here’s the figure. The chart on the right is just a zoomed-in version of the chart on the left, the vertical red line is when he began the potato diet, and the gray bars are when he was traveling and ate no potatoes:

The orange dots in this plot follow the daily averages for the full-tato diet we did. You can see that they are very similar to the blue dots, which are M’s data. When M says that he was losing weight almost as quickly as the full potato diet, he wasn’t joking. While the half-tato diet worked about 50% as well for Nicky, “potatoes by default” seemed to work much better than 50% for M. 

You’ll also notice that M kept on “potatoes by default” for much longer than 30 days, and while the weight loss seems to slow a bit near the end, he keeps losing weight for basically the whole period covered in the plot. He loses more than 10% of his body weight over about three months! And he wasn’t even getting that many calories from potatoes — only like 30%!


That’s why we are running a half-tato diet community trial. Let’s take a look at the design!

Half-Tato Diet Protocol

The half-tato diet is very flexible. As long as you are getting around 50% of your calories each day from potatoes, you’re on target. 

Here are three ways of doing half-tato:

True Half-Tato: Try to get 50% of your calories from potatoes each day, however you want.

Potatoes-by-Default: This is M’s plan, and it worked well for him. Basically, if you don’t have any other plans for a meal, eat only potatoes (a little cooking oil and spices/hot sauce are ok, but nothing substantial). Otherwise, if you are seeing friends or going on a date or anything else, eat as you normally would. If you choose this plan, consider taking a close look at M’s email to us where he describes his protocol in more detail.

Potato Meal: Have one meal a day be nothing but potatoes (with basic spices, etc.). For other meals, eat as normal. This is basically what Nicky Case tried for her half-tato diet. She describes it as “½ the weight-loss effect, but it was *much* easier than Full-Tato. Trivially easy, even.”

On the signup sheet (linked below), we will ask you to indicate which approach you are planning to follow. You don’t have to stick with the approach you choose, but it will be good to know which approaches are most popular, and if there happens to be a big difference between these approaches for some reason, maybe we’ll be able to pick up on it.

When you’re not eating potatoes, please eat as you normally would. The goal is to see how the diet works when you otherwise eat, exercise, and live as normal, so try not to change too much. 

We do, however, have two small suggestions.

In the original potato diet study, we asked people to try to avoid dairy. But now we are not so worried about it. For the half-tato diet, please feel free to continue eating dairy if you want. We will just ask you to track the number of servings of dairy you eat each day on your data sheet. That way, on the off chance that dairy does make a huge difference, we may be able to detect it.  

The second has to do with tomato products, especially ketchup. We reached out to the case studies we mentioned above, and most of them told us that they didn’t have ketchup with their potatoes, or didn’t have it very often, so “no ketchup” may be important for the half-tato diet to work. You may want to avoid tomato products and not have ketchup with your potatoes, but it’s really up to you.

Like with dairy, we will just ask you to track the number of servings of tomato products you eat each day on your data sheet. That way, if tomatoes stop the potato effect for some reason, we may be able to detect it.  

To sum this up:

  • Get around 50% of your calories from potatoes each day, using whatever method (one potato-only meal a day, potatoes-by-default, etc.) you like.
  • Start with whole, raw potatoes when you can, consider cooking them in a way that keeps them as whole as possible.
  • Otherwise, eat as you normally would. Don’t consciously eat better, but also don’t consciously eat worse.
  • On the spreadsheet we share with you (below), track your weight, approximate percent potato for each day, your energy, mood, and the ease of the study, as described on the sheet.
  • Track servings of dairy just in case, don’t bother avoiding it if you don’t want to.
  • Track servings of tomato products, just so we can see if there’s a difference. Maybe consider avoiding them, especially if you’re not losing weight.
  • Track any bonus variables you’re willing/interested to track.

On the first day of half-tato, start eating potatoes as per the approach you chose above (e.g. potatoes-by-default). As long as you are feeling ok, keep trying to stick with it. The effect sometimes takes a couple days to become clear; there’s lots of variation between different people; you may lose a little weight one day and gain weight the next; don’t worry if the effect takes a little while to show up.

If you start feeling bad or weird, try one of these helpful hints:

  • Eating a potato (or something else). Hunger feels different on the potato diet and you may not realize that you are hungry. Yes, really. 
  • Drinking water.
  • Eating a different kind of potato. Different varieties of potatoes may seem like they’re all pretty much the same, but they can really be quite different, and if you’re eating a lot of potatoes, these differences become much easier to notice. 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. They’re also high in potassium, which can throw off your electrolyte balance if you don’t get enough sodium to match it. 

If you try these things and still feel bad or weird, take a day or two off the half-tato diet and just mark down on your sheet that 0% of your food (or whatever) for those days was from potatoes. 

If you start feeling really bad, or you otherwise can’t make the half-tato work for you, just stop the trial early. We don’t want anything bad to happen to you. Just send us an email to close out the trial as normal (see below).

Two-Week Baseline

In our previous community trials, we didn’t include a control group. This is because we expected the effect sizes to be ginormous. People don’t, generally speaking, spontaneously drop 10 lbs in four weeks, so it’s clear the weight loss on the potato diet is “real” without the need for a control group.

This worked less well for the potassium trial, but we wanted to get the biggest sample size we could for that study, and we weren’t sure how many signups we would get beforehand. We stand behind the idea that when you’re trying to estimate an effect size, it’s good to get as many people in the experimental condition as possible.

We’re still not going to include a control group, because we don’t think it would be very interesting to recruit half of you to sit around and do nothing for several weeks, and it wouldn’t teach us very much. 

But we will do the next-best thing, and that’s to ask you to take a baseline of your weight change without the half-tato diet. For the first two weeks of the study, eat as you normally would, and track your weight over time. Then on the fifteenth day, start the half-tato protocol and get on to eating lots of potatoes. It’s simple.

This lets us use everyone as a control group for themselves, sort of like a crossover design. While this design wouldn’t work for everything, we think it works pretty well for the half-tato diet. 

Variable-Span Signup

We’d like you to try the half-tato diet for at least four weeks. With the two-week baseline, this is a total commitment of six weeks.

But if you’re willing to go further, we would be really interested to have that data. So for the half-tato diet community trial, we are opening things up and letting people enroll for however long they want.

Credit where credit is due, this part of the design was Nicky Case’s idea. She describes it as a “hey this trial runs for however long you want, and we’ll just report data every month for whoever hasn’t dropped out yet” design, and we think it makes a lot of sense.

This is a bit like what we did with the potassium trial — we asked people to keep going to 60 days if they were willing, some did, and we reported on their data in a second analysis post. We want to do the same thing in this study, except that we’d like to ask you to sign up for longer spans up front, if you’re willing.

We won’t hold you to this. It’s not a commitment. We’d just like to know up front how long you’re planning to sign up for. If you can’t make it that long, that’s fine. Just tell us how long you’re thinking you might try. 

(Obviously you can also keep going for longer if you want, don’t let us stop you.)

For example, you can sign up for:

  • 2-week baseline + 4-week half-tato
  • 2-week baseline + 8-week half-tato
  • 2-week baseline + 12-week half-tato

And so on and so forth, all the way up to 2-week baseline + 68-week half-tato. We will take snapshots of the data at relevant intervals and analyze the data up to that point. 

Sure, “report every month on whoever hasn’t dropped out yet” has a selection bias. The people who sign up for 52 weeks will not be your average ordinary citizens. In fact, they will be paragons, heroes. But that doesn’t concern us. We still want to see those data.

And if you sign up for 52 weeks but it turns out no one can actually be bothered to do half-tato that long, that’s still useful data. Just think about it. 😉 

Sign Up

Ok researchers, time to sign up.

The only prerequisites for signing up are: 

  • You must be 18 or older;
  • In generally good health, and specifically with no kidney problems;
  • Willing to do a two-week period of baseline measurements; 
  • Willing to get about 50% of your calories every day from potatoes, as described above, for at least four weeks, and;
  • Willing to share your data with us.

As usual, you can sign up to lose weight, lower your blood pressure, get more energy, or see one of the other potential effects. But you can also sign up to help advance the state of medical science. This study will tell us something about nutrition, weight loss, and obesity. If the half-tato diet works for most people, it will give us a practical weight-loss intervention that’s much easier than the 100% potato diet.

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 beginning 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 now we are doing potato.

Eating this much potato may sound a little daunting, but people who have tried it say that it is much easier than they expected, and delicious to boot. Here’s our suggestion: If you are at all interested in trying the half-tato diet, go ahead and sign up and start collecting your data. Collect your baseline measurements for two weeks, then try the first day or two of half-tato and see how it feels. If you hate it and have to stop, we would still love to have that 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.

We are mostly interested in weight loss effects for people who are overweight (BMI 25+) or obese (BMI 30+), but if you are “normal weight” (BMI 20-25) you can also sign up. The original full-tato diet caused weight loss in people of normal weight, and it would be interesting to see if the same thing happens for the half-tato. 

And for everyone, please consult with your doctor before trying this or any other weight loss regimen. 

If you were part of the original SMTM Potato Diet Community Trial, or the SMTM Low-Dose Potassium Community Trial, please feel free to sign up for this study as well! We know that most people who were part of the Potato Diet Community Trial have returned to their baseline weight in the last 6 months, so the original results shouldn’t interfere. And it will be very interesting to compare your weight loss on the half-tato diet to your weight loss on the full-tato diet. Since we can make direct within-person comparisons, this will give us a much better sense of if the half-tato diet works half as well (or better; or worse) as the full-tato diet.

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.
  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 whatever, just keep it consistent. Note down your weight and the other measures (mood, energy, etc.) on the google sheet.
  4. For the first two weeks, eat as normal and continue to track your weight and other variables to provide the baseline. Then when the two weeks of baseline are complete (clearly marked on the data sheet), start eating about 50% potatoes, and continue with the half-tato diet for however long you signed up for (4 weeks or longer).
  5. We prefer that you try to get around 50% of your calories from potatoes for at least four weeks. But imperfect adherence is ok. If you only get 30% of your calories from potatoes one day, or you have to skip a day entirely, that’s all right. Just note it down on your sheet. We’re interested in how the diet works for normal people at home, with all the complications that entails.
  6. When you reach the end of the diet (whether you’re ending the diet early, reaching the span you signed up for, or going beyond it), send us an email with the subject line “[SUBJECT ID] Half-Tato Diet Complete”. This will give us a sense of how the study is proceeding in general and is your opportunity to tell us all about how the study went for you. Please tell us any information that doesn’t easily fit into the spreadsheet — how you felt, what kind of potatoes you used, how you prepared them, before and after pictures (if you want), advice to other people trying this, etc. There’s a chance that the half-tato approach will work for some people and not for others, and if that happens, we’ll dig into these accounts to see if we can figure out why.
  7. Remember that it is ok to end the study early if you need to, for example if you get sick, or if you decide that 12 weeks or whatever is too long of a commitment. It’s also fine to reach 12 weeks and keep going if you’re having a good time. Just make your intentions clear in the comments on your data sheet and send us an email whenever you decide to finish, we’d love to hear from you.

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!

Interview: Exfatloss on Ex150

This post is an interview with some guy, writing under the name Exfatloss, who has been conducting a weight loss self-experiment and recently put out a blog post about the results so far

Exfatloss has tried a lot of different weight loss techniques, including the potato diet, but nothing seemed to work over the long term. Until now, that is. He has invented a diet he calls “ex150” that has caused a surprising amount of weight loss, and which seems to be quite reliable — at least for him.

This interview is lightly edited for clarity, and to make Exfatloss “sound smart and funny” per his request.

Exfatloss: Hey SMTM, I finally wrote up a summary on my crazy diet experiment, now that I’ve lost just over 43lbs in 5 months. It has a weight graph that I hope you find enlightening.

Feedback from an experimental/author/publication/science/whatever perspective highly appreciated!

SMTM: This is very exciting, and it makes us want to drink some heavy cream right away, yum. Several questions: 


SMTM: For starters let us make sure we understand the ex150 diet as you describe it. It involves:

  • Eating just one meal per day, of:
    • ~150 g meat, usually as
      • ground beef chuck (80% lean / 20% fat) or 
      • ribeye steak
    • ~60 g green vegetables, usually as
      • microwaved frozen vegetables “(okra, spinach, green beans, fajita mix)”
    • ~80 g pasta sauce, usually as
      • “the sauce is low-everything and mostly water (e.g. most store brand tomato/alfredo pasta sauce)”
      • I.e. either red or white sauce
    • As much butter as you want to cook these things in. (“usually about 15g”)
    • None of these things measured or weighed precisely, i.e. the diet seems quite flexible. “I don’t think the exact number matters much.”

Exfatloss: Initially I just cut a 1lb thing of ground beef into thirds. It’s pretty much exactly 150g that way. I’d say it doesn’t matter much if you do 130g or 170g. That’s what I mean by “exact numbers don’t matter much.” If lack of a kitchen scale is holding you back, don’t worry about it, eyeballing it worked fine for me. Now if you were to eyeball double the amount of meat… I dunno. I’d consider that more “ex300” than “inexact numbers.”

tl;dr, just buy 1lb of meat and cut it into thirds.


  • Otherwise eating no meals but:
  • butter and whipped cream, as much as you want, as snacks/desserts
    • Sometimes with instant coffee powder for flavor or tomato sauce to cut the fat taste
    • Quite a lot of it, “I go through a lot of cartons of heavy cream, maybe one every 2-4 days.” How big of a carton? 16 oz?
  • As a result, most calories come from cream.
  • No-calorie foods like coffee are also ok, including coffee with arbitrary amounts of cream, and including going to Starbucks.

Exfatloss: The heavy cream comes in 32oz. I have 3 of those in my fridge right now. I think it’s about one 32oz carton every other day I go through. I put instant coffee powder in the whipped cream most days for flavor.

SMTM: Also you are currently in the USA right? 

Exfatloss: Yes, and have been for this entire weight loss period so far.

SMTM: As we understand the intent behind the design, the butter and whipped cream are there to make it high-fat, the 150 g meat is there to make it a low-but-nonzero protein diet, and the vegetables are there to give some minimum amount of fiber. Does that seem right? 

Exfatloss: Vegetables for flavor/texture and minimal fiber, yes.

Pure ground beef tastes like shit. Trust me, I’ve tried it.

Butter/cream are there to provide calories that are not protein/lithium/whatever the factor is. They’re a known-not-fattening source of calories that also happens to cause no bloating and that I deal with super well. 

SMTM: Butter and cream are “a known-not-fattening source of calories that also happens to cause no bloating”? Our sense is that most people would assume that butter and cream are fattening and might cause bloating, so the fact that you seem so confident is surprising. Known to whom, how? It’s news to us! 

Exfatloss: Well, known to me, at this point 😉 Through trial and error. There are a bunch of people with theories why (low protein, low PUFA, low UFA).. but honestly I have no clue if any of them are right. I just know I lost a bunch of weight eating mostly heavy cream.

I think it’s an important factor of any sustainable diet that you are NOT in a caloric deficit, or it won’t work (Caloric deficit symptoms -> “willpower breakdown” -> quit diet).

SMTM: This also really stands out! It does seem to fit with what we saw on the potato diet. How did you come to this conclusion?  

Exfatloss: Decades of experience? Pretty much any time you restrict your intake or increase your expenditure, you can expect to keep it up for 1-3 weeks or maaaybe if you’re really hardcore a bit longer, and then it stops working and you lose “willpower.” That seems like THE ultimate diet experience of everybody who’s ever tried to lose weight. I write about this in my latest post.

Also when people say “deficit” they are super vague and conflate things and that’s why it’s both necessary and impossible to run a deficit to lose weight. Planning on writing about this at one point.

SMTM: What is the pasta sauce there for? You say, “mostly water”, is that also part of the design? 

Exfatloss: Flavor and to soak up the fat 🙂 It tastes significantly better with the sauce. Maybe that’s just me. This whole meal is my previous go-to meal for over 3 years, just scaled down. I used to eat 1lb of that stuff per day, now it’s ~170g and I added the cream to make up for the calories.

SMTM: It may not matter, but we’re curious, what method do you use to test whether you’re in ketosis? If you tracked your ketones data it might be interesting to graph or publish it as well.

Exfatloss: Currently using a ketone blood meter (finger prick style). I will say a lot of carnivore peeps are calling my “zero fiber != ketosis” statement BS and I’ve updated that section of the blog post to clarify.

Since ketone blood strips are expensive and annoying I haven’t tracked those in years, since first starting keto 7 years ago. So unfortunately no data to show 😦

Would be cool if CGMs could track more than just blood glucose! I would love to have years worth of ketone levels. Good news is that the next-gen Libre Freestyle CGM will have this! Very excited.

Palatability and Variability

SMTM: In your post you talk a bit about hypotheses, including this one:

Palatability/brain hack: there is a lot of science out there around the brain’s ways of dealing with food, food reward, and metabolism. Stephan Guyenet’s The Hungry Brain is maybe the best summary, I think. I’ll admit I haven’t read the book, but I listened to a few podcasts where he talks about the ideas, and I think the ex150 diet fits his hypothesis. The idea is that hyper-palatable food that is very energy-rich causes us to overeat in terms of energy. The ex150 diet has 1 hyper-palatable meal every day, but it is very small. The remaining calories come from a bland mono-food that’s hard to overeat (heavy cream). Maybe this tricks the brain into not overeating the cream, yet never feeling more than 24h away from a hyper-palatable meal to release lots of dopamine or other happy food reward signals? I think that even if this might not be the main causal factor, it sure helps make the diet sustainable. I’m never more than 24h away from the most delicious meal I could imagine, and I can eat unrestricted amounts of “dessert” (=whipped cream w/ instant coffee powder).

This mostly seems like evidence against the palatability hypothesis to us, though it might be interesting to ask Guyenet what he thinks. But to us it seems like you are eating delicious foods and getting a lot of food reward. If as much heavy cream and butter as you want plus “the most delicious meal I could imagine” counts as “low palatability”, then the term is so meaningless that it should be tossed out.

Exfatloss: I do personally think that “palatability” (and “satiety”) are meaningless the way they’re often used, even by Guyenet. I heard him on a podcast where he basically said (paraphrasing) “Science has found that humans tend to be caused by their brain to overeat foods that have high palatability.” Wait, isn’t that the definition of palatability? Very roundabout way of saying “Food that tastes good tastes good.” 😀

SMTM: Yeah that has always seemed kind of circular to us. 

Exfatloss: I’ve @mentioned Guyenet on Twitter, but he didn’t reply (maybe cause I’m a nobody lol). Maybe I’ll ask him again when I have street cred lol. I do think he’s a good representative/explainer of “The Science” on this because he’s got a good grasp of various ideas out there and has been in full-contact debates with Taubes etc. and was able to hold his own. I respect him. I sometimes feel like citizen-scientism is bordering on anti-science and someone knee-deep in science like him is able to check that tendency. That said, in a fight, my money is on Taubes.

SMTM: We like Guyenet and he’s interacted with us a tiny bit, maybe we can help get his attention. We understand that he’s reluctant to engage with weird randos on the internet but we’d be curious to see what he thinks of this.

Exfatloss: Regarding the dichotomy here: I think the meat/vegetables/sauce meal has near infinite palatability, I’ve literally eaten a pound of this before scaling it down for ex150. So if this diet was “eat as many of these tiny meals a day as you want” I’d eat 15 of them. But I can only have 1. The cream/butter on the other hand has extremely low “palatability” in the sense that it’s very hard to overeat.

How do you know you’ve had too much cream? You’ll fricking know. It comes from one second to the next, where the thought of another sip almost makes you gag. Total on-off switch for me, whereas I can literally eat carbs until I puke and not be satiated (ask me how I know. College, man!)

So if “palatability” means something like “able to overeat” then cream is not it, because it’s very self-limiting. Potatoes and dry chicken breast are also very self-limiting, but they’re in fact so limiting that I got into a massive deficit, got caloric deficit symptoms, and had to quit the diet (plus all the fiber made me feel bloated and gross).

SMTM: Your results look a little more like the variability hypothesis, though. We interpret this as a version of (or closely related to) the palatability hypothesis, where the problem is not tasty foods per se, but eating a variety of foods that are tasty in different ways. We think this theory is poorly-supported but ex150 is definitely a low-variety diet, mostly consisting of the same 5 or so foods eaten every day, however delicious they might be.

It’s clear that ex150 is a low-variety diet, close to a mono diet. But it also seems like variety or mono-ness aren’t the active ingredients here because you did other low-variety and/or mono diets and they didn’t work for you at all. If low-variety or mono diets worked for you, then you would have lost weight on the other low-variety/mono diets you tried — on the carnivore diet, on the “eating only at In’n’out burger” diet, and on the potato diet. 

Exfatloss: Yea I do think there’s something to “variety -> overeating.” I do think mono-foods “work” in being self-limiting. My hypothesis here is basically that ex150 manages to hit the goldilocks zone – 1 hyper-palatable meal per day and the rest is a self-limiting mono-food, but it’s not so mono that you get into a massive deficit that makes the diet unsustainable (like potatoes did for me).

On my first week of Potato I was doing only boiled potatoes sans everything, and I couldn’t get down more than 600kcal per day. I’d force myself to go to the fridge, grab a boiled potato, take a bite. It’s not even that the bit tasted bad – but after 1 bite, I was almost gagging. I just couldn’t take a second bite.

So clearly too self-limiting to be sustainable. 200ml of heavy cream has almost 700kcal just on its own and you don’t have to boil it, doesn’t come with all the bloating fiber, digests super easily. Plus you can put instant coffee in it 🙂

SMTM: This isn’t our sense of how the potato diet works in general, since it seems like the tato makes you LESS INTERESTED in other foods.

This seems especially clear in people who have tried half-tato diets. They let themselves eat other foods, but eating a big chunk of potatoes on a regular basis seems to lower your appetite for everything else. For example see M’s experience on the half-tato diet. He says, “maybe two or three weeks in, for the first time in a really long time, I did not have the urge to finish off leftover food at dinner.” Or Joey No Floors Freshwater, who said, “The difference is now I get full and stop eating. I leave food on the plate, which is new for me. I leave texmex on the plate y’all. Its wild.” So the potato diet doesn’t seem to work on just the self-limiting aspects of potatoes because people are less interested in eating other foods too. 

That might be one more reason to do a larger half-tato diet study, to see if this generalizes.

Exfatloss: Hm, that sure wasn’t my experience. For me, it was just an inefficient fast plus the worst bloat in years.

I only did full-tater, maybe half-tater would’ve worked better for me? Not sure why it would work so awesome for some and so badly for me.

One theory I have for that is the goldilocks satiety idea. If you eat a mono food and it’s not satiating enough, you’ll overeat and gain weight. If it’s too satiating, you won’t be able to eat enough to meet energy expenditure and you’ll begin getting caloric deprivation symptoms and will eventually land in caloric bankruptcy (see my post).

Not sure why exactly potatoes don’t hit goldilocks zone for me but do for others. Maybe I have a higher energy expenditure or do worse on potatoes?

Re-reading the section of those people who had potato-success, I do think there’s something to “fix satiety.” Maybe the common thread is that these diets somehow fix satiety in people whose satiety signals are broken.

Of course that just moves the question to “how did the satiety signals break and what fixes them?”

SMTM: To us this looks like evidence against both palatability and variability in your case, and some evidence against them in general, especially if it turns out that ex150 works for other people.

Exfatloss: As those hypotheses are commonly understood, yea. But maybe the Goldilocks Palatability thing? 🤷

I.e. it’s not that “lowest palatability/variety” is optimal, but “modest palatability/variety?”

SMTM: Some other theoretical explanations do come to mind. You’re probably eating close to zero calories from seed oils, so while we don’t find seed oils to be a very plausible theory of obesity, we want to at least note that this result is very consistent with that theory.

Exfatloss: Yea, I’ve actually kind of added that as a new hypothesis. I found this insane s/saturatedfat subreddit after posting my article. People there were like “Duh, of COURSE you would lose tons of fat by eating saturated fat!” There’s this guy Fire in a Bottle (twitter/youtube) who has this whole theory how modern meat (even beef) is full of TCCD (I forget what it stands for but it’s BAD cause CHEMICALS) and PUFAs etc. and that’s what’s making us fat.

I will say I did Paleo for 3+ years before Keto, and Keto for 7 years before this, so it’s not like I was chugging seed oils. But I was eating TONS of US commercial grown beef. So if it’s in that..

It would be cool to design experiments to kind of disentangle the various hypotheses, although I’m not sure exactly how. I suppose a month of 2lbs/day of grass-fed beef? 🤷 Maybe ask the gurus who recommend those theories to design an experiment? They’d know.

SMTM: We also notice that “lots of pure fat” does sound kind of like the Shangri-La Diet, so there might be some connection there. A chemical engineer we work with has repeatedly emphasized that while lithium probably accumulates in many foods, it shouldn’t end up in oils because it’s not fat-soluble. Maybe this is connected to why high-fat diets sometimes work? This isn’t limited to lithium, it’s just generally a note that if obesity is caused by a contaminant, there’s some reason to think that the contaminant doesn’t accumulate in fats.

Exfatloss: Interesting, yea. I remember reading about Shangri La years ago. It does seem very similar. Question is why, I guess: is it “appetite suppression” and what does that even mean – ensuring energy balance is met or some psychological thing?

Have you sent a bunch of meat/milk/cream/potatoes to the lithium lab yet? That would shine some light on it, I imagine.

SMTM: We’re working on it! 😉 

Potato Diet

SMTM: The fact that you didn’t lose any weight on the potato diet and “HATED how bland it was” seems really interesting, especially given that most people on the potato diet said they loved it and many talked about how delicious they found the potatoes, even after 30 days. And for the most part, obese participants had the most success on the potato diet, so it’s interesting that you found it boring.

It kind of suggests there might be at least two kinds of obesity, one that responds to the potato diet and one that responds to ex150. If something like that were the case, it would be pretty easy to demonstrate experimentally.

Exfatloss: I’ve long suspected that obesity is a “slightly complicated problem.” My analogy is a broken down car.

You drive by a car broken down by the side of the road.

You say: “Have you tried putting gas in the tank?”

“Yes, still doesn’t drive.” says the guy

“I’m pretty sure putting gas in cars works, my friend broke down once and he put gas in the tank and then it worked again.”

“Doesn’t work for me,” says the guy in the car.

“I think you’re just not putting enough gas in the tank,” say you.

That’s basically the state of our discourse on obesity, when even much simpler things like cars can break down for a handful of reasons. Maybe spark plugs. Flat tire. Crankshaft. Hell, I’ve had a cylinder blow up on me because the timing belt skipped a beat and one of the cylinders fired out of order.

If there were 4 causes of obesity and 4 different diets to fix them, we would currently conclude that there is no solution and we don’t know and nothing works better than anything else, because we insist on averaging everything out.

On average, putting gas in broken down cars’ tanks doesn’t work. But sometimes it does. When lack of gas is the problem.

SMTM: Yes! We’ve been working on a post about this. People spend a lot of time saying obesity is a disease when clearly it is a symptom that can be caused by all kinds of things. So while there could be just one epidemic, there could equally be several.

There could even be several epidemics for just one reason. If you roll a bunch of cars over a cliff, many of them will break when they hit the bottom and won’t be able to start. But they might all end up broken in different ways, even if the ultimate cause is “was rolled off of a cliff”. 

Exfatloss: Yea “disease” has always seemed wrong to me. I get that people want to take the moral stigma out of it, but “disease” sounds like your immune system will clear it out after 2 weeks or it’s a viral infection or something.

If anything, I’d call it a “condition.”

SMTM: Your experience actually seems like some evidence against the contamination hypothesis and in favor of some kind of deficiency hypothesis. Let’s say that obesity is caused by a deficiency in either X or Y. Potatoes contain X and heavy cream contains Y. If you are X-deficient but have good Y levels, then the potato diet will cure your obesity but cream will taste gross because your body is trying to avoid overloading on Y. If you are Y-deficient but have good X levels, then ex150 will cure your obesity but potatoes will taste gross because your body is trying to avoid overloading on X. 

Exfatloss: I don’t know if I agree, it could easily be consistent with contamination. Maybe potatoes and fats are both very low in contaminants, but some people do super well on fiber and starch whereas others do better on fat. I’m sure people with dairy intolerance will hate my diet, but I used to chug a quart of milk for breakfast as a kid and I can dairy all day. Others apparently love potatoes all day. Personally I do best on “close to zero but not quite zero” fiber.

I think the “feels good on X/Y diet” and “contamination” theories can exist side by side and explain this.

SMTM: Would you be at all interested in running an ex150 community trial, maybe recruiting specifically from people who also found the potato diet bland/difficult? You could start by just getting a couple of other people to try it as case studies, since there’s a rather blurry line between “2-3 case studies” and “community trial of 10-20 people”. If the effect is as strong for other people as it is for you, you wouldn’t need a very big sample size to produce convincing results.

Exfatloss: Yea, definitely. In fact I’m trying to recruit some of my friends 🙂 One insisted on switching to the diet at the same time as doing CrossFit for the first time, because apparently isolating variables is for losers…

If you pointed a couple people my way I’d be happy to set up some kind of study. People can contact me on twitter or the blog, or can email me at hello@exfatloss.com

SMTM: Absolutely! People will see it in the blog post and we’ll share about it on twitter, we’ll encourage people to email you there.

Exfatloss: Sounds good!

If it’s just a handful of people I think I’d be more comfortable managing it. I’m not sure I’d be up for hundreds of people like you had on Potato because I’ve never done that type of thing before. That seems to require infrastructure.

SMTM: Yes, and it’s good to start with more case studies before scaling it up to dozens of people. Better to make sure it generalizes and we can re-create it so we don’t waste everyone’s time. 

Exfatloss: Yea for sure. Maybe I’m just somehow a crazy sat fat outlier who can’t deal with potatoes 🙂

Boundary Conditions

SMTM: You mention,

For example, could you make the diet work eating only at common fast food restaurants? Using only prepared deli meats? What about cheese? Is it really just about the amount of protein, or does it matter what kind of protein? Eggs?

Does the diet even need to be ketogenic? What happens when you reach a healthy weight, can you back off the diet? Do you cycle it? Is there a maintenance version?

These seem like the most important questions to us. If you switched to 150g eggs + different vegetables + as much olive oil as you want, would it persist? What about other formulations?

What if you stick with the original formulation but slowly add rice until you are no longer in ketosis? You wouldn’t necessarily need to go out of ketosis if you could show a correlation between the rate of weight loss and your ketone levels (though obviously dropping out of ketosis without it affecting the weight loss would be most convincing). 

Exfatloss: I’m actually currently on day 5 of ex150deli, which substitutes supermarket deli meat cuts (salami, turkey breast, roast beef..) for the ground beef. I kept the vegetables/sauce the same for science’s sake and let me tell you, they do NOT go well together with sliced deli meats lol. [SMTM note: since finished with success, see here]

Agreed that this would be awesome. It seems there’s gotta be a whole lot of alpha out there in fat loss, and we’re probably nowhere near the efficient frontier. So we should explore the boundaries. What do we actually have to give up to be successful? Why give up more.

SMTM: We also noticed that you say,

What piqued my interest though was that the super-low-protein carnivore diet, while it still kicked me out of ketosis, made me rapidly lose weight, about 10lbs in the 12 days until I ended the experiment early (because I was out of ketosis already, proving the hypothesis).

This story suggests that such a thing is possible. 

Exfatloss: See my 2/17/2023 update on the post on the fiber/ketosis issue, several carnivore people claim I’m wrong on this and I concede it’s possible.

SMTM: It also seems like this could just be a cream-maximalist diet, right? Do you know about how many calories you’re getting per day, and how many of them are from cream? Seems like it’s over 50% right? 

Exfatloss: 50%? Ha. It’s 85% before I add the cream in the coffee 🙂 I have a macro estimation in this blog post.

SMTM: There would be a darkly comic element if obesity was cured by high doses of cream, but it would also make some sense. What is the one treatment for obesity that no one would ever think to try? “Drink as much heavy cream as you can stand, every day.” We’re confident that most people would never try this (ok maybe some people would on keto), so it would make sense if everyone missed it… 

Exfatloss: Ha you should see the r/saturatedfat people.. as I understand it, the claim is literally that eating saturated fat will increase your metabolic rate by insane levels and thus create a massive bottom-up deficit.

SMTM: In general, is there a principle of “if you’ve been looking for a long time and tried everything you can think of and nothing works, the real answer must be something that seems really stupid”? Reminds us of Sherlock Holmes’ “when you have eliminated the impossible, whatever remains, however improbable, must be the truth.”

Exfatloss: I will confess to having read a lot of Sherlock Holmes.

SMTM: Us too! 

Superstition and ABA

SMTM: Generally we are concerned about the “superstition” element of self-experiments. If spontaneous remission is a possibility, and you try a long enough list of things, you might randomly spontaneously remiss and it would look like the thing you were trying at the time is the cause: 

Let’s say that Mary develops chronic fatigue syndrome (CFS). She is proactive and wants to solve the problem, so she comes up with a plan of 26 different treatments, which we’ll call A, B, C, D, and so on. Maybe A is “cut out dairy”, B is “walk 20 minutes every day”, etc. but the specific plans don’t really matter. She starts implementing each plan for two weeks, first plan A, then plan B, etc. 

But Mary is working from the wrong assumption. She thinks her chronic fatigue comes from something she’s doing or not doing. … But what really happened is that last month she bought a bag of rice that was grown in a field that was contaminated with cadmium, and developed low-level cadmium poisoning, which is entirely responsible for her chronic fatigue. …None of the interventions she has planned will help. 

But the cadmium is slowly being cleared from her system by natural means at the same time as she works her way through the 26 treatments. What happens is this: Mary reaches treatment L (“take omega-3 supplements”) just as the cadmium in her system drops below critical levels, and Mary is immediately “cured”. 

Since her symptoms stop almost immediately after starting treatment L, Mary assumes that the omega-3 supplements are what cured her, and continues taking them indefinitely.

This is basically what happened when you moved back to the US from China. 

So we REALLY like how you took a 14-day break from ex150 right in the middle of your self-experiment. If you were randomly losing weight for some other reason, then you should have kept on losing weight during this break. The fact that you gained weight back, and that it closely corresponds to the break (modulo pemmican), seems like strong evidence that, as you say, “it wasn’t some other random factor in the environment causing the fat loss.” 

We see the same thing in a smaller way in two other short breaks you take.

This looks a lot like an ABA design, or since you have four experimental periods, an ABABABAB design. 

Usually we would say that ABA-type designs don’t really provide enough evidence to draw clear conclusions. Even with an ABABABAB, that’s still only a sample size of 8 intervals. But in this case, the effect seems so distinct and so the effect size so huge we’re not sure. What do you think? 

Exfatloss: Definitely agreed that it doesn’t prove “what did it” or even anything.

But it disproved a bunch of really likely environmental factors like a) city (walkability? air quality?) b) weather/temperature c) drinking water d) cancer haha.

I think it’s a really easy and pretty good thing to do. If you really know why the light turns on and off, you shouldn’t be afraid to hit the switch a couple of times and see if it works as you thought. That’s kind of the least you can do. If you never turn the light off because you’re afraid it won’t come on again, does that really sound like you understand why it’s on in the first place?

Set Point 

SMTM: In your Q&A section you give this exchange: 

Q: You’re just going for walks now.

A: No, fat loss started 2 months before that and the rate hasn’t changed. But yes, I feel so energetic many days on this diet that I started spontaneously wanting to go outside and take long walks. One time I even fell into a light jog! In my experience this is a result of effective fat loss, having “unlocked” the key to utilizing my body fat, not the cause of fat loss. 1,150kcal/day (0.3lb of body fat) would be a long walk to take every day.

This is interesting to us because it suggests your set point is falling faster than your weight is. Compare this experience to how you mentioned that running as exercise just makes you hungrier to compensate for the extra calories you burn. So that suggests that something about this diet changes your set point very quickly, which seems interesting. 

Exfatloss: I kind of believe that we’re thinking about “set points” slightly wrong. This is inspired by my understanding of circadian rhythms.

All humans have a “genetically predetermined circadian rhythm.” But it’s not that somewhere in your genes it says “8am EST” or anything. The best analogy I’ve read is that what’s basically encoded is a spring weight. Imagine your circadian clock is powered by a spring, and sunshine pushes down on the spring. Different people have different spring weights. Most people’s weight is such that if they get even a little bit of sunlight during a normal day, their spring is fully compressed and ready to go again. Some people have a very stiff spring, and they need enormous amounts of sun exposure to get it compressed during one day.

If you move even normal people to the north pole or something, even their springs will never compress (in the constant dark) or always be overcompressed (in the constant sunlight). If you put people in a cave, the spring mechanism just completely stops working.

My point being, what if it’s not that we have a “set point” that says “He shall be 210lbs” but instead, the rate of how “calories in” is split up? Similar to the P ratio. This ratio could be influenced by various factors like macro composition, chemicals in the food, sunlight, sleep quality.. some people have a ratio in such a way that pretty much no matter what they do, the calories they eat will be sent to the furnace. Other people will have ratios that require them to take super extreme measures to prevent gaining fat. If you put healthy people on a PUFA-sugar-juice diet and sleep deprive them and feed them tons of lithium, even they will probably gain fat.

For example, maybe I’m just an insulin hyper-responder, and what normal people consider “normal” amounts of carbs or protein makes me obese. And suddenly my ratio has swung from one end of the scale (->90% of calories in go to fat) to the other (->90% calories are sent to the furnace and you will fricking go for a walk every day even in freezing rain just cause you can’t stand sitting still).

Maybe it’s not that this ratio per se is encoded. Point is it could easily be encoded as a flow rate, not as an absolute “set point == 210lbs” value. And you just reach a different equilibrium with your current environment depending on the flow rate/spring rate. Just as you’ll reach a certain “waking set point” in the winter, and a different one in the summer, depending on factors like sun exposure.

SMTM: This is a good argument, but the difference between circadian rhythm and metabolic set point is that while the body doesn’t have access to a direct measure of time (it uses external cues like sunlight), it does have access to internal metrics about obesity. This seems to involve signals like leptin, literal compressive weight on your bones, blood sugar, stomach fullness, etc. 

Exfatloss: But those metrics aren’t an objective, comprehensive obesity score like body fat %. It’s different chemical signals. Those signaling pathways can be disrupted or conflated or confused.

In a computer analogy, there isn’t one program in your body that can read the total fat storage value and set the heater/AC accordingly. It’s a bunch of distributed systems sending each other messages in various ways. If something goes wrong with some of the packages, unspecified behavior can set in. The TCP port could be blocked. The pipe could be broken. Your packages might get misrouted by a rogue/broken system in the middle. There might be backpressure in the signaling system that changes the frequency/density of the packages arriving.

Might also be personal. For example, my sensitivity to physical stomach fullness is practically zero. I always assumed that people meant this figuratively. I have literally eaten until I was painfully full and felt zero satiation. I wanted to continue, I just couldn’t, from the pain.

Pro-tip: never go to an all-you-can eat pizza place.

The potato diet wasn’t quite that bad, but it was also really bad.

On the other hand, the whipped cream satiety hits me like a cement truck. One bite fine, second bite good, third bite NO WAY I’M FULL. (These are the last 3 bites, not the first 3 bites, of a whipped heavy cream meal.)

SMTM: How about the hairpin turns when you try going off the diet and back on again? Whatever this diet is doing, your weight seems really responsive! That’s weird, but it kind of matches the results on the potato diet, which also seems to cause abrupt changes in most people’s weight. 

Exfatloss: A lot of the hairpin is water retention. I’ve seen as much as +6lbs the day (!) after ending my second ex150 month, and -4lbs after the first day of pemmican.

One confounder with potato for me is actually that I was pretty low-fiber before it, because I hate fiber. So I went from a low-fiber to an all-fiber diet, which would jack up my water retention. So given the above numbers, even if I lost 6lbs on potato, the very first day of increased water retention could negate it.

Btw these water retention effects are plateau effects, which was my criticism of your recent potassium study. But if you do switchbacks, it creates these insane hairpin turns.

I basically disregard the first, really steep weight loss when I go on the diet. Usually it takes at most 5 days to finish the plateau effect and for the “real” fat loss rate to show.


SMTM: We agree that the real point is the meta-framework of experiments, so we’re really interested to hear more about these other things you tried that you list near the beginning of your post (cold showers, no online news, carnivore diet), what can you tell us about those? 

To emphasize: the real point is the meta-framework of experiments. Formulate a hypothesis, design a 30-day experiment, test it. I’ve probably done dozens of these over the years.

Here are some examples from the last few years:

30 days of cold showers

90 days of no online news (I thought stress might contribute)

90 days of the carnivore diet

30 days of eating only at In’n’out burger

Doing Starting Strength, a beginner’s powerlifting program

Doing Simple & Sinister, a kettlebell training program

30 days of a low-fiber diet

30 days of a low-protein diet

30 days of a potato diet

30 days of drinking only distilled water (including for coffee)

Eating only pemmican, a raw meat paste invented by Native Americans

Exfatloss: Ha I’m planning to eventually write a longer post where I detail some of these experiences. [SMTM note: this post has since been written, see here]

Some highlights: cold showers did nothing. No online news (suggested by a friend) showed me that I consume news as entertainment, but that I just replace it with movies/video games when I stop consuming the news. Carnivore diet was super bland and boring (YES steak gets boring!) and I didn’t lose any weight. In’n’out was the best, I love that place! My first low-protein trial was entirely done at In’n’out, as was the low-fiber one. Starting Strength made me fatter. Pemmican was even more unpalatable than potatoes lol, I chewed every bite for 2 minutes. It just tastes like I imagine cow manure tastes like. Ugh. Sad because I really wanted to like it.

SMTM: A lot of science criticism seems really facile. In particular, it seems like lots of people don’t understand measurement, they think that measuring things is both objective and easy. It makes us wonder if these people have just never tried to measure anything for themselves so they don’t realize what is involved (compare: Reality has a surprising amount of detail). So our sense is that trying a lot of failed diets is part of what has made you a careful experimenter. What was your experience of this? Does this have practical implications for training, or for people who want to get into research / self-experimentation? You seem very virtuous to us. What advice would you give to other people who wanted to do self-experiments like this?

Exfatloss: Hm, not sure. I just like experimenting and trying new stuff, I’d probably keep doing it even if I reach my goal weight. Just for fun.

Most experiments have no effect or almost no effect. “It makes no difference” seems the default result.

SMTM: Good insight.

Exfatloss: All diet experiments that somehow rely on you eating less or burning more energy seem to fail very quickly because caloric deficit symptoms set in. I call these diets “inefficient fasts” because you could’ve saved yourself 15 days and gotten too hungry to continue by water fasting, instead of getting too hungry to continue on day 18 of your diet.

Even when you’re really, absolutely, positively sure you identified The Thing, you can be completely wrong. This was my experience after “knowing” through experiment that keto is what made me lose 100lbs. I had literally already written the book 🙂

Lesson in humility. One of the reasons why I’m couching my terms more this time and mostly going off of my experience so far. One of my broader claims this time was the zero-fiber/ketosis thing, and apparently I’ve already been proven wrong. Zing!

I am very critical of Science(tm) as an institution, especially in fat loss and nutrition. It seems that a lot of scientists hide behind mouse models and sophisticated studies so they don’t have to face the fact that nobody actually fricking knows how to lose weight.

Saw a meta-analysis recently that concluded “all diets work well to reduce weight.” Really? Must’ve not heard about this obesity epidemic.

That’s why I love the citizen scientist stuff so much. I think modern ethics boards literally make it illegal to do meaningful diet research.

SMTM: Preach!

Exfatloss: Try getting a 85% calories from heavy cream study approved.

Final Thoughts

SMTM: Finally, can we publish your responses to these questions (and responses to any followup questions) as an interview on our blog? If that sounds good, we’ll produce a version of this email thread, edited for clarity and flow, and go over it with you before publishing. 

Exfatloss: Yea, that sounds great! Please edit it to make me sound smart and funny lol. Exfatloss is good as a name. You can mention that I’m a guy just for clarity, as that can make a big difference in fat loss/metabolism I think.

SMTM: How should our readers reach you if they have questions? Comments on your Substack? Email? 

Exfatloss: Substack is best. Also on Twitter @exfatloss


And thank you for inspiring me to try this shit again, I had given up until I read the Lithium series.

4 jeans sizes is already so worth it. You wouldn’t believe the quality of life difference 40lbs makes. Literally wouldn’t believe it. If I never lost another pound, this would still be a huge success.

SMTM: ❤ ! 


SMTM Potato Diet Community Trial: 6 Month Followup

Most diets help people lose a little weight. But once you go off the diet, the weight usually comes right back.

But what about the potato diet? In our recent community trial, people lost an average of 10.6 pounds over only four weeks on the potato diet, and the weight loss was very reliable. Of the people who finished four weeks on the diet, all but one of them lost weight, and a few people lost more than 20 pounds.

Most diets are not nearly this effective. The potato diet seems unusually good at causing weight loss. Could it also be unusually good at maintaining weight loss after people stop eating potatoes? 

There are some signs that it might. The potato diet was partially inspired by several case studies, and the case studies suggest that the weight you lose on the potato diet stays off, at least for a while. We focus on three case studies in particular:

Chris Voigt lost 21 lbs on a 60-day potato diet back in 2010. It’s not clear if he gained that back or not — this article from 2018 doesn’t mention it either way. He looks pretty lean in photos, but then again, he was pretty lean to begin with.

Andrew Taylor did an all-potato diet for a full year and lost 117 pounds. This was 7 years ago and he seems to have kept most of the weight off since then. Of course, Andrew did the potato diet for a full year, and was pretty strict about it, so his experience might not generalize to people who did the potato diet for only four weeks. 

And of course, Penn Jillette, of Penn & Teller fame, lost over 100 lbs on a diet that started with a two-week period of nothing but potatoes. This was way back in 2014, and despite only doing potatoes for two weeks, he seems to have kept most of the weight off as well.

In these cases, especially the last two, it seems like the potatoes have somehow reset these people’s lipostats, the system in the brain that keeps you at a particular weight. Their lipostats used to be really high for some reason; then they did a potato diet; now their lipostat seems to be defending a set point about 100 pounds lower. 

The good news is that we now have a larger sample to work with, so maybe we can finally get at some of these questions. It has been about 6 months since the close of the SMTM Potato Diet Community Trial, and this is the 6-month followup analysis.


We sent an email on January 1st, 2023 to everyone who had participated in the Potato Diet Community Trial, asking people to fill out a short 6-month followup survey.

In this survey, we asked them for:

  • Their potato diet participant ID, so we could connect their responses to the original results
  • Their current weight
  • How much potato they continued to eat post-study
  • If they participated in the SMTM potassium trial
  • And any general comments

We gave people approximately two weeks to fill out this survey. Then on January 14th, we downloaded the data.

There were a total of 53 responses by this point.

The majority (51 of them) were people who we analyzed in the original trial.

Of these, 32 were people who made it the full 4 weeks in the original trial. This happens to be exactly half of the 64 who originally made it to 4 weeks.

When we did the original analysis of the potato diet, there were still a few people who were in the middle of their four weeks of the diet, so we didn’t analyze their data at the time. Two of those people responded to this followup survey. They were not in the original analysis, but they did both complete four weeks, so we are going to include them in this analysis. 

So in total we have 34 people who completed 4 weeks on the potato diet and then reported back at the 6-month check-in. This is our main group of interest.

One person (participant 24235303) reported being 136.4 lbs at the 6-month followup, but he was 222.2 lbs at the end of the potato diet, so this would mean he had lost 85.8 more pounds over the intervening 6 months. Because this seems unlikely, and because his comment was, “my weight drifted back up over a few months”, we assumed this was a typo. We followed up by email and he confirmed that he meant to type 236.4 lbs, so we corrected this number for the analysis. 

Participant 63746180 reported being pregnant (congratulations!) so we are excluding her data from this analysis as her weight may not be representative. 

Participant 65402765 mentioned that they “started semaglutide around the same time as potato diet”. Semaglutide (sold under brand names like Ozempic and Wegovy) is an anti-obesity medication, so while this participant did lose 13.4 lbs in this 6-month period, we also excluded their data from the analysis. 

Because of these exclusions, the final sample size for the rest of the post is 32 people.

All new data and materials are available on the OSF.


On average, people gained back most of the weight they lost. This subset of people lost an average of 11.1 pounds from Day 1 to Day 28, and from Day 28 to the 6-month followup there was on average 10.3 lbs of weight re-gain.

People are on average down 0.71 lbs from their starting weight on Day 1 of the original study, but this is not significantly different from zero. On average, people are pretty much back to baseline.

In aggregate, it looks like a pretty strict reversion to the mean — people lost a little more than 10 lbs over 4 weeks on the potato diet, and gained back almost all of that weight over the next 6 months. 

This is still a relatively successful weight loss intervention — you do a diet for just one month and it takes about 6 months to gain back the weight you lost. This suggests that if you were willing to do a week or two of potato diet every 3 months, you could probably keep your weight down indefinitely.

But just looking at the averages conceals a pretty drastic spread. When we plot the results, we can see that 6 months later, most people are back near baseline, maybe slightly under baseline on average. But some people are down almost 20 or 30 lbs, some people are up more than 10 lbs, and one person is up almost 30 lbs! 

That central cluster is what gives us the average. Most people gained weight in the 6 months after the end of the potato diet, and ended up on average slightly under baseline. 

Four people kept losing weight (one of them isn’t obvious in the plot, they were near the top of the pack at Day 28 and are near the bottom of the pack at the 6-month check-in), and three of those people ended up down more than 15 lbs over 6 months. Those three are the clear outliers below the main group at 6 months.

Five people gained back way more (10+ lbs) than they lost. These are the five dots way above the main group at 6 months, including that one dot that is up at nearly 30+ lbs. 

It may be hopeless to try to figure out what is different about these eight or so people, given the small sample size, but let’s try.


Since there are so few outliers, let’s start by looking at them one-by-one.

Participants ​​99065049, 82575860, 66459072, 10157137, and 77742719 all ended up more than 10 lbs heavier than their baseline on Day 1 of the potato diet. 

Participant ​​99065049 is the outlier, having lost 6.3 lbs in the trial and gained back 34.5 lbs since then, for a total gain of 28.2 lbs since Day 1. We wanted to double-check this result, so we reached out to this participant over email and he confirmed that it was not a typo.

This group didn’t say much about themselves in the comments. Only two of them left responses at all. Participant 10157137 said: 

After the potato diet my cholesterol had improved, but post diet it shot back up again 😔

Participant 82575860 said:

Would appreciate a follow up post on the best potato-based recipes that were sent in 

Participants 20943794, 19289471, and 35182564 lost the most weight. All of them lost more than 5 lbs on the potato diet, and kept losing weight after that. Their total weight loss by 6 months was 19.3 lbs, 23.2 lbs, and 28.7 lbs, respectively. 

Participant 35182564, who lost the most weight, said:

Weight is incredibly stable, although I eat normal, just like before the potato diet. This was a great success.

Participant 20943794 offered the most detail, saying: 

After the potato diet ended, I started a pretty traditional CICO diet using the Noom app. Roughly speaking, I lost 10 lbs on the potato diet, and another 10 on the CICO diet. 

Before the potato diet, I tried calorie counting and various high-protein, low carbohydrate diets, and have never had this kind of sustained success. (E.g., I’ve lost 20 – 30 lbs before, but I didn’t maintain that weight for more than a month or so). 

In addition to the potato diet, there are some other confounding factors: 

1. Whey protein has figured heavily in all my previous diet regimens, but I obviously didn’t take any during the potato diet, and even after it ended, I drastically cut back how much protein powder I consumed (because of the lithium hypothesis) 

2. Because of covid and it’s after-effects, I eat out far less frequently than I ever did before. Since January 2020, I’ve eaten restaurant food (whether dine-in or take-out) only about a dozen times (most of that was on a business trip in October 2022). Before that, I’d say I ate restaurant food on average once per week

Moving on from the comments, we can see if any of the other variables offer us insight.

The potato diet included people from all weight brackets, and maybe that’s what is causing this confusing pattern. For example, maybe all the outliers who gained weight over baseline are people who were slightly underweight when they started the potato diet, and who have gone up to a healthy weight 6 months later. Maybe all the outliers who lost extra weight were very heavy people whose lipostats were easier to reset. 

But when we plot the results by BMI bracket, we see basically no pattern: 

Another possibility is that this reflects whether or not people kept eating potatoes after the trial was over. After all, you can eat potatoes without being on the potato diet, and many people do. Perhaps the people who kept losing weight are the people who stuck with the potato diet, even if only casually, for the long-term. And maybe the people who gained extra weight grew disgusted with potatoes and stopped eating them entirely. 

The good news is that we collected this very variable. But again, when we plot it, we see no such thing: 

The person who lost the most weight ate “way less potatoes than [they] used to”. The people who gained the most weight are all in the middle. No clear pattern here.

That said, if you plot this variable WITHOUT the outliers, you see basically what we would expect — people who kept eating more potatoes are mostly still below their original weight, people who didn’t change their potato intake are back to baseline, and people who are eating way less potato than they used to are slightly above baseline. 

Finally, here’s a breakdown by country. Most participants are Americans but take a look: 

American Holidays

Most of our participants are Americans, and in the span between the start of July and the end of December there’s a major American holiday period that famously involves a lot of eating: the period from Thanksgiving to New Year’s.  

Obligatory Rockwell

As a result, at the 6-month followup our participants were asked to weigh themselves just after a period of especially serious and far-ranging eating. Quite possibly they were being asked to weigh themselves at the heaviest they would be all year.

So in some ways, the particular timing of how this all worked out is a rather conservative test of the potato diet. The weight loss from the potato diet does not seem to survive the holiday period, but it might last somewhat better across any other 6-month span.

A number of our participants commented on this as well. Let’s take a look: 

(57875769) For about the first month after doing the trial my weight continued to trend downward although much more slowly. Then it slowly started creeping back up. Most of the weight came back during the holidays (it’s a little unfortunate that the six month follow up landed right after Thanksgiving, Christmas, and New Years!).

(89852176) After ending the full potato diet about 10 pounds below my typical weight, I returned rather quickly to my baseline (spurred on by eating at family vacation) and stayed there for several months. I ended the year roughly 5 pounds higher than baseline, all of which were gained in the second half of December with “typical” USA holiday (over-)eating.

(63187175) Gained about 5 pounds over the holidays, I was closer to 235 at the beginning of December

(50913144) I stayed at the lower weight for a few months, it only started creeping back up at pre-potato-trial rates in the last 6 weeks or so.  I am probably going to do another round of potato intervention, i don’t like the potassium and it doesn’t seem to help me much. 

(15106191) This measurement is being taken just after the holidays. This is higher than my pre-potato weight but I don’t blame the potatoes, its normal for me to weigh about this much more in January than I did in June

This is also somewhat supported by Nicky Case’s followup survey, which she conducted separately (with our peer review) and ran before the holidays. On October 30th, 2022, she put out a survey on the potato diet, asking people about their current status. She only got 9 responses, but found that most people were still below baseline and had kept most of the weight off.

If we expand our plot using her data, we can see that some people were down quite a bit more in late October / early November than they were at our 6-month check in.  

Some people, however, mentioned gaining the weight back more quickly: 

(25547207) It took about a two months to gain all my weight back. My strength training had to cease 2 weeks in for the remainder of the study, and my large lifts dropped about 10%. It took about 1 month to recover my original strength and I was making gains before fully recovering my weight.

(72706884) I gained back all the weight within 3 months


The potato diet causes very consistent weight loss. But whatever makes the potato diet work doesn’t permanently change your set point. The first thing we see is that most people gain back the weight they lost over time, and on average, it looks like they are back close to their original weight about six months later. 

Unless it did permanently change the lipostat for those three people for some reason. Because the second thing we see is striking individual differences. A small number of people ended up weighing 10+ pounds more or less than they did when they signed up for the trial, and it’s not clear why. 

Maybe they had unusual life circumstances that happened to make them lose or gain more weight over those six months. Maybe they are just random outliers. Or maybe they are more/less sensitive to potatoes for some reason, more sensitive to whatever the active ingredients are. Something something cybernetic attractor states.

There’s a chance that the outliers who kept losing weight are just noise, or that they would have lost weight anyways for some other reason and just happened to sign up for the potato diet at the right time. But there’s also the chance that there is something different about these four participants. If we could figure out what that difference is, maybe we could create lasting weight loss for everyone. For example, are these four people the only four vegans in this sample? We didn’t think to ask this question, but if they were, that would be very interesting. A potential extension then would be to do a much larger potato diet study (1000+ participants) and keep special track of the people who kept losing weight after the trial ended. 

Still, the potato diet is a relatively successful weight loss intervention, since one month of dieting gives consistent results that tend to stick around for about six months. And given the significant individual differences we see, it seems that for some people the effects are more lasting. While we don’t know why this happens for some people and not for others, there’s a small chance that you’ll end up being one of these outliers, and you’ll keep losing weight after the potato diet is over.

We will probably still do the 1-year followup to keep up with these outlier participants, and to see if overall average weight remains below the original baseline or not. But in general, it seems like the conclusion is that 4 weeks of potato diet will make you lose weight, and six months later most people will be back around baseline.

Low-Dose Potassium at 60 Days

In the SMTM Low-Dose Potassium Community Trial, people took some potassium and lost some weight. Specifically, they took an average of about 1900 mg of potassium per day and lost an average of 0.85 lbs over 29 days

That’s not much weight loss, but it’s also not a very big supplemental dose of potassium, and the weight loss is significantly different from zero. People who took higher doses of potassium lost more weight, as did people who weighed more to begin with.

But what about past that first span of 29 days? Some people kept going with the protocol, taking potassium up to 60 days. Today we report their data.

30+ Days Results

We took a snapshot of all participants’ data on January 5, 2023. This was more than a month after we collected the data from the first 29 days, so everyone had the opportunity to reach 60 days by this point if they wanted to. This new snapshot is available on the OSF.

All the sample sizes in this case are too small to be statistically significant with the potential effect sizes involved, so we don’t report any statistical tests in this post. 

We cleaned these raw data and are going to look at the data from Day 1 on the protocol to Day 60. Some people may have kept going past Day 60, but we aren’t going to look at that right now. 

Here are the overall trajectories for the people who reported at least one day’s weight beyond day 29. The vertical red line indicates day 29, so all data points beyond that are past the span of the original trial. 

Overall the trend seems to continue. One person ended up down more than 15 lbs, but that’s not at all representative. 

People lost weight on average, but we already knew that. In this case we are most interested in whether they kept losing weight past the official end of the trial, so here are those same data zeroed from their weight on Day 29:

We see that in this span, people also lost weight on average, though the average weight loss was not very large. The average weight change past day 29 is negative, -0.37 lbs with all data.

See that spike up to more than 10 lbs? As you may have guessed, those are the days immediately following Thanksgiving. The participant reported that this was their “heaviest weight in 9 years”, but as you can see they lost all that excess weight very quickly. 

These plots can make it hard to see what has happened for each individual, so let’s now break things down and just show their last reported weights, again relative to their weight on Day 29. 

Here’s a plot of each person’s last reported day, and their reported weight change as of that day.

You can see that there are roughly two groups — most people either made it just a few days past Day 29, or made it up to very close to day 60.

We can take a special look at that second group, people who made it to Day 60 or nearly did so. Here’s everyone who made it past 50 days, broken out by just the landmark measurements — their weight on Day 1, on Day 29 at the official end of the trial, and on the last day they reported.

And here are those same data as a table:

On average, these people lost a decent bit (2.7 lbs) in the first span of the trial, and less in the second span (1.0 lbs). But this obscures a lot of individual stories that are more extreme in one way or another, like participant 42293886, who gained 3 lbs in the first leg but lost 4.6 lbs going to day 60, for a total change of 1.6 lbs. (This participant told us, “Not going to go off potassium any time soon I suspect.  Making a little effort to lose weight, and it’s showing a small amount of success.”)

Also notable is that the only two people who had net weight gain by 50+ days are people who had already gained weight by day 29.


Probably the people who kept going past Day 29 were the ones who were most motivated, or who had seen the best results up to that point, so there may be some selection bias.

While none of this is super compelling, people who kept going did on average keep losing weight. They didn’t stick right where they were on Day 29 and they didn’t regress back to the mean. It’s a small amount more evidence in favor of the idea that supplemental potassium might cause weight loss, another tiny pebble on the scale.

In a practical sense, we still recommend that anyone who wants to lose weight should go on the potato or half-tato diet. It’s much more reliable, and more delicious.  


Companions the creator seeks, not corpses, not herds and believers. Fellow creators the creator seeks—those who grave new values on new tablets. Companions the creator seeks, and fellow harvesters; for everything about him is ripe for the harvest.

— Friedrich Nietzsche, “Thus Spoke Zarathustra”

There’s a long tradition in the history of medicine where people figured out the cause of an industrial disease by noticing that one profession had a much higher rate of the disease than everyone else. For example, in Victorian and Edwardian England, chimney sweeps had a rate of scrotal cancer more than 200 times higher than workers who weren’t exposed to tar on the job. No, we are not making this up.

Now it’s your turn to do something similar. Your mission, should you choose to accept it, is to write a review of the mysteries on a topic and send it to us at slimemoldtimemold[at]gmail[dot]com by July 1st 2023.

Pick a topic, and write about the mysterious aspects of that topic, like we did for the mysteries of obesity in Part I of A Chemical Hunger. We mostly expect you to review topics from “hard science” areas like medicine, biology, chemistry, and neuroscience, but we are open to reviews of mysteries from social science, economics, political science, or the humanities. If you feel you can make a strong case for some mysteries and why they are mysterious, that’s good by us.

You can include Normal Mysteries, things that are unexplained but that most people know about and don’t seem all that confusing. For example, IBS and migraines are about 2-3x more common in women than in men. Everyone kind of knows this, so it’s not all that weird, but no one can really explain it, so it is still a mystery. The first three mysteries we reviewed about the obesity epidemic were all pretty normal. 

You should also review Weird Mysteries, things that most people aren’t aware of and/or that seem like they totally don’t make sense, things that fly in the face of our understanding. The rest of the mysteries we reviewed about the obesity epidemic were pretty weird, like how lab animals and wild animals are also getting more obese. What’s up with that? 

Our hot tip is that the simplest form of mystery is just unexplained or unexpected variation. A good example is how obesity rates vary by altitude — low-altitude counties in the United States have much higher obesity rates than high-altitude countries do. This is not predicted by most theories of obesity, and many people found this very surprising.

An unexpected LACK of variation can also be a mystery. For obesity, it feels intuitive that people who eat different kinds of diets should weigh different amounts, but diet consistently seems to make very little difference. From the perspective of the mainstream understanding of obesity, this is pretty mysterious.

How do you know that you’ve found a good mystery? It’s an emotion, a feeling that starts in your gut, not unlike IBS (which, hey now that we think about it, is pretty mysterious). Start with something that you just can’t wrap your stomach around. We’re looking for a confusion that started rumbling in your tummy when you were a student who kept asking the same basic questions and couldn’t get a straight answer, a confusion that has just kept grumbling away right there next to your esophagus ever since — now that’s a mystery. The best mysteries will be assumptions where everyone else thinks everything is fine, but you have a nagging suspicion that something is wrong.

Please focus on the mysteries of your chosen subject — DO NOT include a theory. If you feel you need to provide context, you can discuss popular theories and how your mysteries support or undermine them (like we did in Part II). But no arguing for a theory or introducing a theory of your own. 

This is a mystery contest, not a theory contest. Your mystery review is the hook; if you do a great job reviewing some mysteries and win the contest, everyone will be excited to hear about your theory. Then you can put it on your own blog and get a lot of readers. If people think you have a promising direction, maybe you can get funding to study it further. 

Software engineers who have just lost their jobs; grad students on strike; academics who are fed up with the paywall curtain; couples who have just retired at 35; founders whose last venture was recently acquired; billionaire playboys with too much time on their hands; anyone who is looking to make a pivot to research — this is the contest for you. You don’t need a lot of research chops to look at something and tell that it’s weird; anyone can pick out mysteries by noticing when things don’t add up, when things are unexplained, or when experts all disagree on the best explanation. 

If anything, outsiders and newbies have an advantage. If your career doesn’t rely on pretending to understand, it’s easier to spot things that don’t make any sense.

Don’t do this though

Contest Format

We have recruited some judges to help us evaluate the mysteries: Adam Mastroianni, Lars Doucet, Applied Divinity Studies, Tony Kulesa, and possibly some other judges TBA. We will consult with these judges and will choose around 5-10 finalists, which will be published on the blog. Then readers will vote for the best. First place will get at least $2000, second place $1000, third place $500, though we might increase those numbers later on.

Use your expertise. The best entries will probably be about things YOU are already familiar with, things where you know about the mysteries the rest of us haven’t noticed yet. 

All forms of media are welcome! We like to write really long stuff, and sometimes we just post our correspondence. But if you like to boil ‘em instead of mash ‘em (or stick them in a stew!), that’s cool too. Podcasts, videos, slideshows, semaphore code, etc. are all welcome. All written finalists will be published on the blog. Finalists in other formats (e.g. videos, podcasts) will be linked to. The language shared by the judges is English, so we prefer materials that suit the conventions of English speakers.

You must submit your entry under a pseudonym. This helps people discuss you and your work without having to say, “the guy or lady perhaps or person or team who wrote the SMTM mystery contest entry on pancreatic cancer”. Instead they can say, “blorpShark’s wonderful mysteries of pancreatic cancer review”, which is much nicer. 

Pseudonyms also keep famous people from having an advantage. For this reason, if you already go by a well-known pseudonym on the internet, please choose a new pseudonym for this contest. 

Team submissions are strongly encouraged (friendship is the most powerful force in the universe), and we encourage you to pick a band name. Go to your nearest band name generator and pick the stupidest name it generates. For solo entries, we recommend a rap name generator, like Post Malone did

After the contest is over, if you want to connect your pseudonym to your other name(s), please feel free to do so. If you do not provide a pseudonym, one will be provided for you. 

If you submit a non-written entry, please send it to us in a form that is as anonymous as possible. For example, you might send a podcast entry as an audio file, or a video essay as a video file. Don’t mention your name in the recording, etc.

Please submit written entries by putting them in a Google doc and sharing that doc with us. We will try to preserve your formatting as best we can if we publish your entry as a finalist, but no promises. If you want to make sure your formatting appears as intended, use simple formatting (e.g. bold, italics, and images). The more complicated your formatting is, the more likely we are to make an error in copying it over. 

Please don’t put your name or any hints about your identity in the Google doc itself. If you do, we may remove that information or disqualify your entry.

Please make sure that the Google doc is unlocked and that we can read it and share it with the other judges. Go to the “Share” button in the upper right, and on the bottom of the popup click on where it says “restricted” and change to “anyone with the link”. If you send us a document we can’t read, we will probably disqualify you.

Frankly we reserve the right to disqualify entries for any reason, or no reason at all. 

If you win, we will send you your prize money in the form of an envelope stuffed with cash, or something else if we agree that it’s more convenient. 

Your due date is July 1st, 2023. If you have any questions, ask in the comments so other people who have the same questions can see. You can also email us or ask us questions on twitter. Good luck!

People Took Some Potassium and Lost Some Weight

In November 2021, we finished our series A Chemical Hunger, where we argue that the obesity epidemic is the result of environmental contaminants, and that one of those contaminants might be lithium. We hadn’t really expected anyone to read it. But we were wrong — tens of thousands of people have now read the series, and to date the twitter thread giving an overview of the series has more than 2 million views. 

In April 2022, we announced the Potato Diet Community Trial. We expected that the potato diet would be really hard to stick to and people would only lose a little weight, if any. But we were wrong — people said the potato diet was easy, enjoyable, and on average, people lost 10.6 lbs over 4 weeks.

Potatoes are really high in potassium, so we wondered if potassium could be the active ingredient causing the weight loss in the potato diet. We decided to try a self-experiment where we took small amounts of potassium salt every day, but it seemed unlikely that such tiny doses could have any effect. But we were wrong — we each lost about 5 pounds over four weeks. One of us kept going and lost 12 lbs over 60 days. 

In October 2022, we announced the low-dose potassium community trial (twitter thread here). Even with the results of our self-experiment, it still seemed unlikely that such tiny doses of potassium would do anything for people on average. 

Now, you are reading the post with analysis and results from that study.


  1. Motivation
  2. Variables
  3. Protocol
  4. Participants
  5. Weight Loss
  6. Effects Other than Weight Loss
  7. Interpretation
  8. Future Studies
  9. Conclusion

1. Motivation

The goal of this study is to see if the large doses of potassium found in potatoes could plausibly be the reason why people lose weight on the potato diet. 

The doses of potassium in this study are small in comparison to the potato diet, only a few thousand milligrams per day. This is much less potassium than people got on the potato diet, so we don’t expect the effect to be large in any practical sense. In fact, we expect that if there is an effect at these doses, it will be quite small, probably a loss of only a few pounds on average. We are just looking to try to see if there is any effect at all.

Potato diet estimate per the USDA’s estimate for potassium in 2000 calories of potatoes

We are studying potassium because it is a major variable from the potato diet that we can easily look at in isolation, not because we think potassium will be a great or a practical treatment for obesity on its own. 

We don’t expect everyone to lose weight on this protocol, or for it to be sustainable in the long term. We just want to know if potassium could be the reason why people lose weight on the potato diet, something that we currently have almost no information about. If it looks plausible, that tells us something about why the potato diet works; and then we can consider, ok wait a minute, why would potassium cause weight loss at all? But more speculation on these points after we look at the results.

Raw data, the analysis script, and study materials are available on the OSF. The dataset is very rich and there’s a good chance that we haven’t found everything there is to find. So if you are statistically inclined, after you’ve finished reading this post we encourage you to download the data and have a look for yourself. If you find anything interesting, or even if you’re just able to confirm our findings, you should write up your analysis on your own blog and let us know about it! Science is a game, please play!

If you recreate these analyses at home, your results may be slightly different than ours because three participants asked that their data not be shared publicly.

Whether or not you like what we’ve done here, we encourage you not to take our word for it. Download the data and materials, perform your own analysis, share your criticisms, run your own study. If you think you can do a better job, maybe you are right! Show us how it’s done.

2. Variables

We collected variables at three points.

First, we collected demographic variables at signup. The variables we collected at this point were:

  • chromosomal sex 
  • reported hormone profile (so we can distinguish trans participants with less ambiguity) 
  • age in years
  • profession
  • race/ethnicity (from a limited number of options)
  • local postal code
  • current country of residence
  • whether they had done any sort of potato diet in the last year

In response to this last question, the majority told us they had not done any potato diet in the last year, but 40 told us they had done some kind of potato diet on their own, and 7 said they took part in our Potato Diet Community Trial.

After signup, we had people track a number of variables about their health and their diet (and how much potassium they were taking) over the course of the study, on a spreadsheet we provided. You can view a version of that spreadsheet here.

The main variables collected on this sheet were: 

  • weight (in the morning)
  • potassium doses (up to four doses a day)
  • variables for whether or not participants consumed meat, eggs, dairy, leafy greens, and tomato products each day (just a 1 for “ate it today” and a 0 for “didn’t eat it today”), because we suspect these foods may be high in lithium (though we’re not sure)

We also included fields for several bonus variables, which were optional but encouraged. These variables were:

  • calorie intake
  • waist circumference (which a couple people asked for after the potato diet)
  • sodium intake
  • energy, mood, and ease of study (all on 7-point scales)
  • systolic and diastolic blood pressure
  • total Cholesterol, as well as LDL and HDL cholesterol
  • triglycerides
  • resting heart rate
  • fasting blood glucose
  • body temperature
  • estimated hours of sleep the night prior
  • sleep quality the night prior 
  • fidgeting (on a 1-7 scale)
  • estimated minutes of exercise
  • (and several fields for notes) 

After we took a look at the data, we realized we had a few questions about aspects of the study that we hadn’t really measured. For example, some people mentioned that they hated the potassium while other people mentioned finding it delicious. But most people didn’t mention this aspect at all, so it would be hard to conduct any analysis related to how much people enjoyed the potassium.

So finally, on December 3rd, we sent a followup survey asking about some of these remaining questions. Five days later, there were 105 responses. We downloaded these responses and added them to the dataset.

The variables we collected at this point were:

  • what potassium compound they had primarily consumed
  • what form they had taken it in (e.g. salt vs. capsule vs. tablet)
  • what brand of potassium they had primarily consumed
  • what delivery methods they had used (e.g. in food vs. in a drink)
  • change in their appetite
  • how much they enjoyed the potassium at the beginning of the trial
  • how much they enjoyed the potassium at the end of the trial
  • whether they felt leaner or chubbier subjectively
  • whether they were intentionally exercising or eating more or less during the trial
  • whether they were on some other diet or routine when they started the potassium trial
  • and a free-response question asking if there was anything else we should know

For more detail, see the copies of the materials available on the OSF

3. Protocol

As a reminder, the main study protocol was: 

  • Start with two doses of 330 mg potassium (1/8 tsp Nu-Salt) on the first day.
  • If you feel fine, try three or four doses of 330 mg potassium (1/8 tsp Nu-Salt) on subsequent days.
  • If you’re feeling fine after 4-7 days, try one dose of 660 mg potassium (1/4 tsp Nu-Salt).
  • If you still feel good, keep increasing your dose by small increments. For example, if you are on two doses of 660 mg (1/4 tsp Nu-Salt) a day, you might increase that to three doses of 660 mg, or one dose of 660 mg and one dose of 1300 mg (1/2 tsp Nu-Salt). If a higher dose makes you feel bad, try returning to the dose you were on before and maintain that.
  • Try slowly increasing to two doses of 1300 mg (1/2 tsp Nu-Salt) a day. Only go beyond that if you are feeling totally fine. 
  • You should calibrate based on your own experience — different people will have different needs and different limits. For example, we’d expect someone who weighs 300 pounds would be able to tolerate higher doses than someone who weighs 150 pounds.
  • If you feel weird / bad / tired / brainfog and you can’t tell why, try:
    • eating something;
    • drinking some water; 
    • getting some sodium; 
    • and see if any of those help. It may be easy to end up needing food / water / salt and not notice.
    • If you still feel weird, try dropping to a lower dose or taking 1-2 days off.
  • If at any point you feel sick or have symptoms of hyperkalemia, stop immediately and seek medical attention.

Participants were asked to record their weight every morning, and they were asked to record data up to the weight measurement on the morning of day 29 regardless of whether they stuck to the protocol. That way even if someone found the potassium intolerable, we could still use their data.

4. Participants

A total of 305 people submitted the initial form.

Of those, 15 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 enter critical data such as height, etc.). We enrolled the remaining 290 people in the study.

Of the 290 people who were enrolled, 57 never entered any data on their spreadsheet, leaving 233 people who entered at least one day of weight data.

The most common outcome in this group was to make it the full 29 days, but the majority of the 233 people who entered data on day 1 stopped entering weight data before day 29. Here’s the distribution of days completed (as measured by last weight entry) from that group:

As shown above, 104 people entered weights on both the first day and on day 29. This was the criteria we specified in advance for the group we would focus on for the main analysis. Specifically, we said: 

Anyone who records data for 29 days is clearly taking the study seriously, even if they weren’t able to stick to the potassium supplements the whole time. … Based on this, our main analysis will focus on participants who provide 4 weeks of data. If you provide a weight measurement for the morning of day 1 and the morning of day 29, so we can calculate your weight before and after, and you took at least one dose of potassium, we will do our best to include you in the analysis.

5. Weight Loss

The main outcome of interest is weight change by the morning of day 29. Here’s the histogram of that variable, with a black vertical line at 0 lbs (i.e. no weight change over 29 days) and a red dashed vertical line at the mean weight change:

On average, people lost weight. The mean is -0.89 lbs, or an average loss of 0.89 pounds over 29 days. With a sample size of 104, this is significantly different from zero in a one-sample t-test, p = .014, and the 95% confidence interval for average weight change is [-1.59, -0.19] pounds. 

However, this obscures the data of several people who made it to the end of the study, but who mistakenly didn’t report a measurement on day 29. If we look at the data of everyone who reported a weight on day 28, this is the histogram: 

This has a mean of -0.85 lbs and a larger sample size, and is also significant, p = .016.

The same thing is true if we look at everyone’s weight at day 27 — the average weight loss is 0.86 lbs and this is significant, p = .016. The exact cutoff doesn’t matter, which indicates that the result is robust

People who dropped out before reaching the end of the four weeks also seem to have lost weight on average. You can see that the majority of people who stopped before day 21 are below zero (the horizontal line), indicating they lost some weight over the time they spent on the trial:

In fact, if you look at the weight change from EVERYONE who reported at least two weight measurements (i.e. not including those people who only reported weight for day 1, who literally could not have seen weight change), people still lost 0.79 lbs on average. Here’s the histogram:

Because of the much larger sample size, this is still significant. In fact the p-value is quite a bit lower (p = .0002) and the 95% CI is noticeably narrower, [-1.20, -0.38] pounds.

The average weight loss here is smaller, but remember that about half of these people did not make it the full four weeks! In fact, this analysis includes 26 people who didn’t even make it 7 days. 

Looking over the course of the study as a whole, it appears that people slowly lose weight over time, with no apparent changes in the trend: 

Of interest here is that the 95% CI excludes zero for the first time on day 7, and that day 25 is the point of greatest average weight change.

Looking at individual trajectories is a right mess, but here’s the plot anyways:


On average it looks like people lose about 0.8 lbs over four weeks on this protocol. This isn’t much weight loss, but it’s statistically distinguishable from nothing.

But obviously some people do lose more weight, sometimes a lot more. Three people lost more than 10 lbs. It’s clear that there is a lot of variation around the small average weight loss. Can we figure out what caused any of this variation?

Well for one thing, some people did not have much weight to lose to begin with. Here’s weight change on day 29 compared to starting BMI:

As you can see, people who started with higher BMIs lost more weight. This correlation is significant, r = -0.269, p = .006, and is exactly what we would expect. People who have a BMI of 22 don’t have much weight to lose, so we should expect to see very little weight loss from them, perhaps no weight loss at all. Meanwhile people with higher starting BMIs have more to lose. It’s interesting to see that the person with the highest starting BMI also lost the most weight. 

Many lean people participated in this study, and most seem to have signed up because they wanted to contribute to the research even if they were unlikely to lose weight. This isn’t an experiment, but some of them do provide a sort of baseline response. “I am happy with both weights,” said one participant, “and wasn’t expecting or hoping for a big weight loss number. I thought of myself as somewhat of a ‘control group.’”

If this were a “normal” study, and we were “normal” researchers, we probably would have restricted signups so that only people with a starting BMI of 30 or higher (technically obese) could sign up for the study. 

If we had done that, here’s what the analysis would look like. Unsurprisingly, this group lost more weight on average: 

The average weight loss for participants who started the trial with a BMI of 30 or above was 1.83 lbs, and again this is significant, p = .031.

Another thing that might matter is what country people are from. This is especially interesting from the perspective of the contamination hypothesis, because we suspect some countries have more contaminants than others. We tried doing a “USA vs. all other countries” analysis, but that was not significant, p = .341. There also doesn’t seem to be a clear effect of what continent people are on, but we can still plot these data:

Nothing groundbreaking here, but we do want to note that we see much less variation in Europe than in North America.

But of course, the main thing we should expect to make a difference in the results of the potassium trial is the amount of potassium! 

In this study, everyone was on the same protocol, but some people took much more potassium than others. People were asked to start with two doses of 330 mg on the first day and slowly work up to two doses of 1300 mg a day, but they were asked to drop to a lower dose if a higher dose made them feel bad, and to only go beyond two doses of 1300 mg per day if they were feeling totally fine. We also asked people never to go above 1300 mg in a single dose or 5200 mg in a day.

Given this protocol, it’s natural that some people ended up on higher doses than others. Here’s the distribution of average daily doses for people who made it the full four weeks:

As you can see, there is considerable variation. 

With this information, we can compare the amount of potassium people were taking to the amount of weight they lost. When we do, we see a clear relationship, where people who took more potassium lost more weight on average: 

This relationship is statistically significant, r = -0.276, p = .005. This is not an experimental result, since we didn’t assign people to different doses, so we shouldn’t assume it’s causal. There are certainly alternative explanations. For example, there may be weird selection issues. People who chose to take more potassium could have been the people who were like “I feel fine, I’ll take more” or people who were like “It’s not working, I’ll take more” or people who were like “I’m losing a little bit of weight, so I’ll take more and lose more”. But this result is also consistent with what we would expect if potassium supplementation was causing the weight loss.

Let’s stop a minute and take a closer look. The regression line here is y = -0.0011x + 1.3110. Essentially what this means is that the model says that on average you would gain 1.3110 lbs if you supplemented no potassium at all for 29 days, but you lose 0.0011 lbs for every mg per day you supplement above that baseline. 

For example, someone consuming 2000 mg per day would lose 2.2 lbs more than baseline; since baseline is 1.3 lbs gained, we would expect them to lose about 0.9 lbs on average over 29 days. 

The potato diet gives exceptionally high doses of potassium. Sources differ on exact numbers, but the USDA says that a medium potato has about 900 mg of potassium and about 160 calories, so 2000 calories of potatoes a day would give a daily dose of about 11,000 mg potassium.

Plugging that dose into the linear equation above, the predicted weight loss on the potato diet (i.e. on a dose of 11,000 mg/day) would be:

> (-0.0011 * 11000) + 1.3110

> -10.789

It’s hard to get any closer than that — the observed weight loss on the potato diet was 10.6 lbs on average. That’s why we titled the report, 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

Realistically, the fact that the linear equation in this case lines up with the potato diet so well is just an amusing coincidence. The 95% confidence interval on the slope is [-0.0019 to -0.0003], so model fits for 11,000 mg/day include anything from 19.6 lbs to 2.0 lbs lost.

But you have to agree, it is amusing.

This is in fact moderate support for the idea that potassium is the only active ingredient in the potato diet. We say moderate because it’s certainly not conclusive, but it would be hard for the data to be any more consistent with that interpretation.

Another interesting comparison can be found in the relationship between weight loss and total potassium taken over the course of 29 days:

This relationship is also significant (r = -0.209, p = .033), though it’s somewhat smaller than the relationship between weight loss and daily average potassium. This may mean that taking a consistent dose is more important than the amount of potassium you take overall, though the confidence intervals of the two correlations clearly overlap, so don’t conclude too much from this difference.

Other than starting BMI and potassium dosage, we can’t really tell why some people lost more weight than others. Sex, reported hormone profile, age, ethnicity, previous experience with the potato diet — none of them seem to matter.

We asked people to report how often they ate meat, eggs, dairy, leafy greens, and tomato products, and while there are sometimes vague trends, none of these variables are ever significantly associated with weight loss. On the other hand, we should note that these were measured in a very rough fashion (just “did you eat it or didn’t you” for each day), so the variables aren’t sensitive enough to detect anything less than a very strong effect.

We also tried looking at all these variables while controlling for starting BMI and daily average dose, but there still don’t seem to be any associations with these variables and weight loss (though it’s possible we’re missing something.)

Similarly, we looked at the variables from the followup survey, but with the exception of one appetite result we will report below, we didn’t find any associations with these variables and weight loss. Even if there were relationships, we probably wouldn’t find them in these data, because there wasn’t much variation in these variables — most participants took potassium in about the same ways and (per our request) didn’t change their diet or exercise during the trial.

Ease of Weight Loss

So much for absolute weight loss. But what about relative weight loss? Were there signs that the potassium made it easier to lose weight? 

Indeed there were, at least in the self-report data. Some people mentioned being surprised at how easy it was to lose weight, and some people mentioned that they were surprised they didn’t gain weight given how poorly they were eating:

(77174810) First of all – holy shit! It’s amazing how well this worked and it’s also surprising that it’s never really been studied before! Thank you for the analysis and thought that you put into this. For this trial, I basically just ate whatever I felt like, went to a football tailgate party nearly every weekend with lots of beer and foods you would not associate with dieting… and still lost nearly 10 lbs! I plan to continue on for at least another couple months so feel free to follow up later if you want to.

I have tried every diet/exercise and variation of CICO, atkins, keto, IF, etc., etc., etc. to try and lose weight. To no one’s surprise, nothing really worked for long and the weight always came back. At the end of 2020 I was over 275. It took me three months of busting my ass to lose 20 pounds and as soon as I started eating “normally” again, I slowly started putting weight back on.

(23881640) I started a quick calorie-restricted diet before the holidays (got to fit into those festive pants!), and I’m combining counting macros, counting calories, AND adding 1 tsp of potassium chloride a day to my water, and the weight is coming off. It’s making the calorie restriction much more bearable. I can tell I’m technically hungry, but adherence is so much easier doing it this way. (I lost 20 pounds before by counting macros, and that was hard.) 

(60114890) Trial was very easy. Lost 5.5 lbs.

I definitely attempted to run a calorie deficit. So, this was a deliberate weight loss attempt. I’ve lost the same 5-15 lbs. maybe six times over the last 30 years. This was the first time it wasn’t really painful and didn’t require a lot of discipline. It’s also the fastest rate of weight loss I’ve experienced (1.5-2 lbs/week as opposed to 0.75-1.0 lbs/week). Very very easy. Why? Mostly appetite suppression. Historically I have been able to run 500 kcal deficits with a lot of effort. I was able to run 750-1000 kcal deficits with almost no effort. Real appetite suppression kicked in after second week, at levels of about 1800mg additional potassium. It was ridiculous—yesterday I ate 1300 kcal and burned 2600 kcal and wasn’t really hungry.

…for my purposes,  I don’t really care if its placebo. My appetite was substantially suppressed. It was easy to run a 750kcal deficit. I’m going to stay on the diet until I’m at target weight of 185lbs, which would be total loss of 13.6 lbs. Feels very doable.

This wasn’t a universal experience, but we think these reports were interesting. 

It seems possible that for most people, small doses of potassium aren’t enough to cause weight loss by themselves, even if they affect your appetite (see below). But they might still be helpful because they enhance other weight-loss approaches.

At this point we would like to draw your attention to the beverages known as “ketoade” and “snake juice”. 

Ketoade is a term for home-made electrolyte drinks people sometimes take as part of the ketogenic diet. These almost always include potassium, usually in the form of Morton® Lite Salt™, a half-and-half mixture of potassium chloride and table salt. Since it’s all homebrew, recipes differ widely, but some people are clearly getting several thousand milligrams of potassium a day from their ketoade.

It’s possible that the keto diet works but is hard to stick to, and that ketoade has become popular because it makes weight loss on a restrictive diet much faster and easier. It’s also possible that the keto diet doesn’t cause weight loss at all, and that most successes on the keto diet actually come from people who are taking large amounts of potassium “on the side” as ketoade. 

Snake juice is a term for (you guessed it) home-made electrolyte drinks people sometimes take as part of various weight loss strategies, including intermittent fasting, keto, and something called the… snake diet. As far as we can tell, no snakes were harmed in the making of this diet — it appears to refer to how snakes go a long time between meals, since it’s a weight loss strategy about going a long time between meals. 

Anyways, snake juice involves drinking a concoction that gives you several thousand milligrams of potassium every day. See this helpful instructional video to learn more. It opens with a man yelling “hey FATTY, behold!” at you, so you just know it is a trustworthy and authoritative source. 

In any case, most participants in the potassium trial were essentially drinking ketoade / snake juice / whatever you want to call it: potassium salt and sodium salt mixed in some beverage, often with a little bit of flavoring. And while the effect size was small, on average it seemed to cause weight loss, even without keto or fasting or anything else.

The results of this study suggest that the ketogenic diet community, and this community of “snake people”, have correctly developed a folk wisdom tradition of taking large doses of potassium to amplify their weight loss routines. If so, that is pretty wild, and it speaks well of the value of folk wisdom in solving people’s real problems.

It’s especially interesting that their theories of obesity don’t seem to point at potassium at all. These people don’t think that potassium is the active ingredient here, and they don’t have any idea why potassium might help them lose weight, but they have figured out that they should take it. That’s pretty impressive.

The inverse is true as well. The fact that internet people have settled on potassium salt as part of their folk weight loss routines supports our finding that straight potassium causes weight loss.

6. Effects Other Than Weight Loss

People mentioned a wide variety of effects, but most effects were only mentioned once or twice. One person said that the potassium made their tinnitus worse, but there doesn’t seem to be any sign of this generalizing to other participants.

We did let people report some bonus variables, but most of these variables didn’t get many responses, so we often didn’t end up with a big enough sample size to analyze. For example, only one person reported their total cholesterol on day 29, and no one reported HDL cholesterol, LDL cholesterol, or triglycerides on day 29. So we won’t be taking a closer look at any of those.

Even so, a few things did come through. Here are the effects that people mentioned more than a couple times in the self-report data, or where there were enough measurements to make taking a look worthwhile: 


The most commonly mentioned effect of potassium was reduced appetite.

(36100230) I found that my appetite was dulled a bit — My mind focused on food a bit less, I snacked less between meals, and ate slightly smaller servings. I found this started to wane a little bit towards the end of the month — not entirely, but I found myself more likely to feel hungry between meals.

(58007117) Taking the potassium was very easy (with the exception of the few times I put nu-salt into pill casings and took it that way – this caused stomach pain, which I did not experience when just taking it dissolved in liquid). My overall impression is that potassium acts as a mild appetite suppressant.

(11538897) I didn’t think of food while doing the trial. At the lower doses, my hunger was affected but my appetite was not. At the higher doses, both were affected. … There was a huge difference in my general desire for food if I took the supplement in the morning before eating. If I took my first dose with food, I would be thinking about food sooner (though I wouldn’t say it was even hunger, just craving). When I took only the supplement and then went to work, it was almost always that I wouldn’t think of food until after work.

(77174810) I settled on 3 doses of ~990mg (3/8 teaspoon) a day at 0730, 1130, 1600. I felt like this kept hunger at the lowest level overall and was easy to stick with. I found that if I took the supplement when I was already hungry, I’d eat more overall. So I take the dose an hour or so before I’d normally eat a meal. 

(19620767) Finished the trial. It was weird, I lost a pound the first day, then nothing for a week, then 4 more pounds, then nothing. My appetite was pretty suppressed the whole time, but due to injury and illness I wasn’t really able to exercise beyond going on walks and doing my PT, I also ate an unusually large amount of junk food for life reasons (depression, birthday cake, etc) without gaining any weight.

(18556224) The potassium didn’t magically decrease the calories I took in — I had to consciously restrict them, or have circumstances dictate that — but it did suppress my hunger, i.e. four weeks I was as hungry during the day (mostly not at all) no matter how much food I had eaten.

I haven’t decided whether the weird feeling that potassium gives me is better or worse than the hunger I’d otherwise experience, since I’ve gotten fairly good at handling that.

I haven’t noticed any cravings during the trial, which is good because that is often a problem for me — not craving things carby things, but craving certain foods I eat anyway (butter, cheese) so that I eat more calories than needed, even though I’m not really hungry for anything, just seeking pleasure.

(49045265) I did notice an reduced appetite. There was only one day during the study I was hungry.

(60114890) I definitely attempted to run a calorie deficit. So, this was a deliberate weight loss attempt. I’ve lost the same 5-15 lbs. maybe six times over the last 30 years. This was the first time it wasn’t really painful and didn’t require a lot of discipline. It’s also the fastest rate of weight loss I’ve experienced (1.5-2 lbs/week as opposed to 0.75-1.0 lbs/week). Very very easy. Why? Mostly appetite suppression. Historically I have been able to run 500 kcal deficits with a lot of effort. I was able to run 750-1000 kcal deficits with almost no effort. Real appetite suppression kicked in after second week, at levels of about 1800mg additional potassium. It was ridiculous—yesterday I ate 1300 kcal and burned 2600 kcal and wasn’t really hungry. …for my purposes, I don’t really care if its placebo. My appetite was substantially suppressed. It was easy to run a 750kcal deficit.

(06769604) My appetite was clearly suppressed, especially in the morning. The issue seemed to be that it would come roaring back in the afternoon and I’d be quite hungry.

This was true even for many people who didn’t lose weight, or who lost only negligible amounts. But it wasn’t universal, and some people explicitly mentioned that there was no change in their appetite. 

We found this interesting, so we included a question about appetite changes in the followup survey. In these data, the majority of people reported no change to their appetite, but about a third reported decreased appetite, and six people reported greatly decreased appetite. Only one person reported any amount of increased appetite.

And you probably won’t be surprised to see that reduction in appetite was associated with weight loss: 

When we treated this self-report measure as a continuous variable on a 1-5 scale, the relationship was significant, r = 0.295, p = .011. But you’ll also notice that many people who did not lose any weight still reported a reduced appetite, suggesting the potassium had some effect for them, just not enough to cause weight loss. 

You might think that potassium caused weight loss because it reduced appetite, which caused people to eat less, which caused weight loss. That may be the case, and several people did mention that they were running a calorie deficit. But we also included a field for people to track their calories if they wanted to, and while only 22 people provided complete data, the correlation in that data is nonsignificant and pretty flat, r = -0.100, p = .659. 

You’ll also notice that it’s trending in the “wrong direction”, where people who reported eating more also lost more weight.

We don’t think it’s helpful to conclude that potassium is “just an appetite suppressant”. Clearly it is an appetite suppressant, but like, um, why? Why would it do this? Everything has a mechanism. What is the mechanism for this?

We think potassium reduces appetite because it turns down your lipostat. As we said with the potato diet,

[Reduced appetite] 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.

Also not shown: increased body temperature, reduced fat storage, etc.

But even if we accept that potassium turns down your lipostat, you still have to ask, why does it do THAT? What is the mechanism that makes potassium turn down your lipostat’s set point? Well, more discussion in a minute.


Some people mentioned noticeable improvements to their sleep.

(24646801) Regarding sleep, in the month or two prior to the study, I had started to wake semi-regularly (5-6 nights/week & 1-2 times per night) to use the toilet. This tapered off rather quickly during the trial and with few exceptions has not returned. I don’t know enough medically to explain why this would be, but it’s definitely an improvement to my sleep, and I would continue the trial indefinitely to retain this result.

(81847724) Sleep is highly subjective but overall I think my sleep quality improved during the experiment, generally sleeping longer without waking up in the middle of the night.

(87352273) Sleep was the most pleasant surprise. I have issues with insomnia, so I tend to stay awake until 2-3 am when I get really sleepy so I don’t end up just lying awake in bed getting frustrated. With ~2000 mg of potassium as well as magnesium before bed, I found myself naturally getting sleepy and falling asleep around midnight every night without much effort or thinking about it.

We included some bonus variables about sleep in the spreadsheet, but the results are inconclusive. 

Sleep quality did go up by 0.2 points, but that was not significant (p = .480). 

Hours slept went down somewhat, which is interesting, but that change also was not significant (p = .296). 

We should note that most people did not report either sleep variable, so the sample size in both of these cases is less than 40. It looks like potassium may improve your sleep a little and/or may help you sleep less, but this isn’t well-supported and even if there is an effect, the effect is probably small.

This is interesting given that Gwern, who is notorious for his attention to detail, did a self-experiment with potassium citrate and “confirmed large neg⁣a⁣tive effects on my sleep”, with a large apparent effect (d = 1.1). Possible differences may come from the fact that Gwern was originally taking potassium in the evening rather than in the morning, and when he tested this he found a difference; was taking about 4000 mg a day, much higher than most people in this trial; and that he was taking potassium citrate, while most people on this trial were taking potassium chloride. (Also Gwern may just be built different.)


We didn’t find any effect of fidgeting (if anything, people fidgeted less over time), but there were a few self-reports of intense or manic energy. 

(87352273) I had really noticeably elevated energy at first, and pretty regularly had the urge to walk or exercise just to burn off some of the nervous energy. The intensity leveled off after the first week or so, but energy overall stayed higher than usual.

(84130320) I had a huge rush of energy, like borderline hypomanic, and I ended up pulling a chest muscle doing pushups because I felt like I was 10 years younger (note to others: you are not actually 10 years younger, do not suddenly do a bunch of pushups). So that sucked.

(93059017) I had so much energy after work that I just needed to walk and I walked an extra mile home.

The participant who lost the most weight (81847724) was also notable for this report:

My mood and energy have been nothing short of fantastic. On a normal day pre-trial, I’d rate my average mood and energy levels in the 4/5 area on the 1-7 scale. Somewhere during week 2 of the trial, I really noticed how elevated I felt in my mood all day long and generally my energy levels were high regardless of the amount of sleep.

However, this increased energy did not seem to be widespread, and some people specifically mentioned not feeling any more energetic. 

Looking at the self-report question we included about energy (though FWIW, a sample size of only 29), people’s energy improved by 0.54 points on a 7-point scale, but this was not significant (p = .126).

Surprisingly, Stimulants

A couple people noted stimulant-like effects, and strangely, some also mentioned a kind of stimulant reduction or substitution effect.

(36100230) I felt a little more focused after taking the potassium. A few times I wanted to get some caffeine, and took potassium instead, and no longer needed the caffeine.

(72706884) My caffeine intake decreased substantially during the early part of the diet. I typically intake 100-250mg of caffeine daily. This was reduced to 30-60mg every other day during the first 2 weeks. I found supplementing with a 200mg caffeine pill helpful and used one daily during weeks 3 and 4.

(64983306) While taking potassium, I also experienced heightened concentration abilities, as if I was taking ritalin/adderall. This feeling would last for 2-3 hours after taking a dose of potassium.

We can corroborate this with our own experience. Caffeine seemed to have less of an effect for us while on the potassium, and weirdly, seems to have less of an effect still! Not sure what’s up with that.

Blood Pressure

Only seven people reported their blood pressure readings on day 29, so there wasn’t enough data to do a proper analysis. 

However, most of them saw their blood pressure go down, so we figured we should go into some detail anyways.

In the seven cases that reported their BP on both day 1 and day 29, people saw their blood pressure go from: 

  • 120/81 to 113/77
  • 114/64 to 116/63
  • 121/91 to 114/78.5
  • 123/90 to 123/80
  • 131/78 to 130/85
  • 111/75 to 99/82
  • 121/78 to 126/81

On average, systolic BP went down by 2.9 points, with a maximum of 12 points down; and diastolic BP went down by 1.5 points, with a maximum of 12.5 points down.

Again, these differences are not significant. But with the very small number of people reporting BP, the sample size isn’t large enough to reach statistical significance. Most of these people also had relatively low blood pressure to begin with, so it’s not clear what kind of change you might see if you had hypertension.


People were split on the potassium. Many people found it distasteful, and some people hated it.

(50612600) this is way too disgusting to drink

unbelievable it’s sold as a food product

(79606462) it truly does taste horrible, even dissolved in 12 oz water

Unsurprisingly, many of these people chose to end the trial early, and we can’t blame them.

On the other hand…

(02689028) does liking kcl salt too much count as anything important

(84130320) My experience overall was actually very pleasant. I didn’t think the taste of the KCl was nearly as bad as advertised. To me, it tasted like salt, if salt were perishable and had spent a little bit too long in the refrigerator. Putting it in sparkling water was fairly good, I could tell it was weirdly salty (especially once I got up to 1300mg/dose) but if I just chugged a little, like half a glass, and then topped it back up it was legitimately delicious. If I did a schorle (fruit juice mixed with sparkling water) instead I could barely taste it. … when I felt really bad and backed off of the potassium per the instructions, I craved potassium. Like I really wanted to eat bananas and was like “boy I could really go for some sparkling water with KCl in it.” It was super strange.

(23578149) I went from finding Nu-Sal revolting (even mixed 2:1 with salt) to finding it pleasant.

But one thing is for sure: it really makes you pee.

(7619655) Have you ever eaten a really salty meal, like pizza or Chinese food, and then felt really thirsty afterwards? That’s how the potassium made me feel a lot of the time. It was drink, pee, drink, pee, drink, pee all day. If I didn’t keep up on the drinking, I would get parched lips and a headache. It was hard to keep this up, so I skipped a bunch of days towards the end.

(74537321) I found I had to pee a lot more often depending on how much water I was drinking. I tried to drink a lot of water throughout the day so I could get the most out of my bowel movements, but one issue was I just had to go pee a lot more. It felt like I would drink a cup of water, and then 20 mins later have to pee like I hadn’t gone all day. 🙂 I would say I had 1 to 2 liters of water per day in addition to meal time drinks (milk, juice, diet soda).

We found these self-reports interesting (also hilarious) so in the followup survey, we explicitly asked people how much they enjoyed the potassium. Because some people mentioned that their opinion of the potassium changed over time, we asked them how they felt about it at both the beginning and at the end of the trial: 

In the beginning, most people found it unpleasant or disgusting (though you will notice there is still one “very delicious” rating!), but:

By the end, a majority found it either neutral or pleasant, though many people still found it super gross.

You might expect that potassium enjoyment would be related to weight loss, but we didn’t find much evidence for that. We didn’t notice any statistically significant relationships with weight loss, though looking at the plots does seem suggestive:

So it’s possible that people who enjoy potassium salts are more likely to lose weight by eating them, but if so, the effect is probably too small to detect in this study. 

7. Interpretation

The lithium hypothesis is the only theory of obesity that predicts that straight potassium might help people lose weight. It’s not a very strong prediction,​​ we simply noticed that lithium and potassium are both monovalent cations, and that they appear to have some interaction in the brain, where the lipostat is located. But other theories wouldn’t predict a relationship between potassium and weight loss at all.

We first introduced the lithium hypothesis in Part VII of our series A Chemical Hunger, expanding on the idea in Interlude G, Interlude H, and Interlude I. In Part X, the conclusion to the series, we speculated that if obesity is caused by lithium exposure, potassium might be an effective treatment: 

Lithium … 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. 

However, the results of this study are not conclusive evidence in favor of the lithium hypothesis, and it benefits us to explore some alternative explanations. 

Prosaic explanations like “potassium caused people to lose water weight” would seem to be ruled out by the fact that many people’s appetites got noticeably weaker, and the fact that some people mentioned that they had never lost weight so quickly or easily before. Same thing for placebo.

So the two classes of likely alternatives are that either it’s something confounded with the potassium dose (i.e. when you take more potassium, you also do more X), or that potassium causes weight loss for some other reason than its relationship to lithium.


A natural starting point is to consider whether obesity could be just another disease of deficiency, one you develop if you don’t get enough potassium. Scurvy is the disease that happens when you don’t get enough vitamin C, beriberi is the disease that happens when you don’t get enough vitamin B1, could obesity be as simple as a potassium deficiency? 

Unfortunately we think that is not the case. Diseases of deficiency are easy to identify because they regularly crop up in situations where people eat a limited diet for a long time. Both beriberi and scurvy, for example, were common among sailors on long voyages. 

Obesity does not really fit this profile. People today may not be getting enough potassium, but if obesity were a disease of deficiency, you would expect to see it showing up in historical records of cities under long sieges, sailors on long voyages, explorers in the Antarctic, and so on.

We see two distant ways to reconcile this idea, however. The first would be if potassium deficiency causes obesity, but only over the very long term. For example, maybe you only develop obesity if you eat a low-potassium diet for 10 years. This would be unusual and we think it is unlikely, but it’s consistent with the data.

The other is if obesity occurs in the rare cases when people both have a potassium deficiency AND have lots of access to calories. Sailors, explorers, and other people who tend to get diseases of deficiency usually are not eating that well in general. Maybe obesity is only triggered when you’re not getting enough potassium, but you can otherwise eat as much as you want. We think this also seems unlikely, but again, we can’t rule it out. 

Hydration / Clearance

People drank a lot more water on the potassium trial because the potassium salt made them thirsty, and they had to pee a lot. People also drank a lot of water on the potato diet, for similar reasons. Is it possible that both diets cause weight loss because they encourage you to drink huge amounts of water, and that water flushes your system (or something)?

This seems pretty unlikely to us, though it is consistent with all the evidence. If someone wants to try the super-hydration community trial, where you try to drink 5 liters a day or something (don’t use that number we made it up, figure out what is actually safe), that would be fairly interesting. We don’t expect it would cause comparable weight loss, in part because we think someone would have noticed by now if staying hydrated was enough to cure obesity. But it sure would be interesting if it did! 


Potassium and sodium balance each other in biological functions. To regulate the increased amount of potassium they were consuming, we encouraged people to consume more sodium as well, and they may also have naturally craved more sodium as they ate more potassium.

As a result, people on the potassium trial may have been getting more sodium than normal. For similar reasons, people on the potato diet may have been getting more sodium than normal. So one kind of weird possibility is that sodium is what’s causing the weight loss here, not potassium.

We did have this in mind from the start, so one of the bonus variables for the study was estimated daily sodium intake.

Unfortunately, out of the 233 people who entered data, only 20 people tracked their sodium, so we don’t have much evidence. But what evidence we do have doesn’t support this interpretation. People who consumed more sodium actually ended up with higher weights at the end (r = 0.101), though the relationship is not significant (p = .670).

In general we do not expect that sodium is responsible for the weight loss observed in this study, nor would we encourage anyone to try a high-sodium diet. But again, we can’t really rule it out. 

Other Biology

Is it possible that potassium increases the clearance of something other than lithium? Just making more urine will increase the clearance of some things! Or could it treat obesity in some other way? 

It seems likely, but we can’t really be much more specific than that. Potassium has approximately one zillion roles in biology, so for example if obesity is caused by anything to do with “hormone secretion and action”, which seems like a pretty broad category, potassium could potentially be a treatment. This seems like a question for someone who knows more about biochemistry than we do.

8. Future Studies

There are a number of studies that could be run to get more information. We might run some of them ourselves in the future. For now, here they are as brief sketches. 

Experimental Extensions 

We know that one of the biggest criticisms we’re going to get on this study is about the lack of blinding and lack of a control group. Everyone in this study took potassium, and everyone knew exactly what they were taking. 

Let’s imagine what a control group might look like. It’s well-established that people get heavier as they get older, so over the course of 29 days, people who do nothing should on average end up weighing slightly more by the end. We’re pretty sure that a straight control group would have lost about 0 lbs and maybe would have gained some small fraction of a pound over the course of the study — if you gain 2 lbs a year, that’s about 0.17 lbs a month.

But it’s true that people in this study were paying more attention to their weight and to their diet, and it’s possible if they were taking packets of some other white powder that wasn’t potassium, they would lose weight for some other reason. It’s possible that there’s some level of placebo. 

That’s fine, because this study was never intended to be the final word. It’s the first study, not the last. 

While the hierarchy of evidence is very important, a meta-analysis of multiple randomized controlled trials doesn’t just happen overnight. With this study, we’ve shown that it’s plausible that potassium by itself could lead to weight loss. There wasn’t evidence for that before.

For example, this comment from the extremely measured thread by Agaricus 

But now that we have this evidence, it might be worth investing more time and energy in a more controlled or more complex study. 

We wouldn’t want to do a straight control group where people do nothing, because that would reduce our effective sample size and it would be boring for participants. Fortunately, there are designs that can help with both problems. Here are two ideas:

First of all, we could run a crossover trial. In this case, the study would run for two months. One half of the participants would be assigned to take potassium for the first month and then take no potassium for the second month. The other half of the participants would be assigned to take no potassium for the first month, and yes potassium for the second month. This allows both groups to serve as controls without reducing our sample size.

Another idea would be to run a dose-dependent experiment. The design might look something like this: one half of the participants would be assigned to a protocol that involves them working up to a dose of 2000 mg of potassium a day. The other half of the participants would be assigned to a protocol that involves them working up to a dose of 4000 mg of potassium a day. (You could also do a dose-dependent experiment with more conditions — some people assigned to 1000 mg a day, some to 2000 mg/day, some to 3000 mg/day, etc.) If potassium is the active ingredient, you should see more weight loss in the group(s) assigned to the higher dose(s). 

Comparing different doses allows us to have a control group without having to have a “no treatment” group that spends the month doing nothing. Both groups are providing valuable data, and we still control for the effect of the intervention. It isn’t blinded, but this design guards against placebo effects because it would be hard for the people in the 4000 mg/day group to arrange to lose more weight than the 2000 mg/day group. 

The main issue in both cases is statistical power. You might need very large sample sizes to detect these differences, and no one should run one of these studies without conducting a very careful power analysis. But, the designs are theoretically sound.

Other Diet(s) High in Potassium

Potatoes are very high in potassium, but they are not the only food that is very high in potassium. Other foods that are very high in potassium include lima beans, swiss chard, spinach, bamboo shoots, butternut squash, kohlrabi, portabella mushrooms, white beans, bok choy, and many others (though avocado and banana are maybe overrated as sources of potassium!). 

If the potato diet causes weight loss because it’s high in potassium, a non-potato diet that is high in potassium might also cause weight loss. So one thing you could do is arrange a trial of some other high-potassium diet and see if that also caused weight loss.

This isn’t a sure thing, however. Other foods do contain potassium, but it’s possible that the potassium is different in these other foods — less bioavailable, released more slowly, part of a different compound, etc. So we don’t think this would be a very strong test of the theory, because it introduces so many new variables. 

In addition, we want to note that many of the items on the list of high-potassium foods are foods that we suspect might be high in lithium. In particular, there’s evidence that lithium accumulates in leafy greens, sprouts, and maybe in gourds, which matches most of the foods on the list above. If the potato diet works because it’s high in potassium AND low in lithium, these other high-potassium foods might not have any effect at all.

If we had to pick just one high-K food to test, we would probably pick coconut water. It’s a liquid, so the potassium is probably more available than average. It’s relatively high in potassium, with about 600 mg per cup. It’s easy to find and requires no preparation. And (as far as we know at least) coconut water isn’t swimming with lithium. So if people wanted to try getting 2000+ mg per day of potassium from coconut water, that would be pretty interesting.

Low-Potassium Potato Diet

In the course of designing this study, we came across a set of practices used to remove potassium from potatoes. Some people with serious kidney disease have to avoid consuming too much potassium, and these techniques were developed so they could enjoy potatoes safely. Potassium removal is usually accomplished by slicing or dicing the potatoes in small pieces to increase surface area, and then soaking (before and/or after cooking) or boiling them in water to leach out the potassium (e.g.: link, link). Some sources claim that this can remove more than 50% or even up to 70% of the potassium in potatoes.

We could test these techniques by preparing some potatoes with these methods and sending the potatoes (and the water they were soaked/boiled in, which should contain the removed potassium) to a lab for analysis. If the sliced/boiled/soaked potatoes had much less potassium than potatoes that were baked or roasted or something, that would suggest that these techniques remove potassium as advertised.

We could then use this information to do another test of the weight-loss powers of potassium, by running an experiment with a modified form of the potato diet.

One group would be assigned to eat a potato diet with potatoes prepared in a way that preserves as much potassium as possible (probably baked), and the other group would be assigned to eat a potato diet with potatoes prepared in a way that removes as much potassium as possible (probably boiled and then soaked and then fried). If the preserves-potassium group lost a lot more weight on their potato diet than the removes-potassium group, that would be further strong evidence that potassium is the main active ingredient in the potato diet. 

This prediction matches the following tidbit from M’s experience with the potatoes-by-default diet, which makes it seem somewhat more more plausible: “I seemed to be able to eat much more when the potatoes were sliced/grated (e.g. Swiss rosti, Chinese tudousi) than when they were closer to whole potatoes (i.e. diced, potato wedges, etc.). I’m not sure why.”

Some people think that the potato diet works because it is a mono diet. It cuts out most other foods, so there’s very little variety, and some people (e.g. here) think that food variety is part of what makes people gain weight. But if soaking all the potassium out of potatoes made for a much smaller effect, that would mean there was a big difference in weight loss between two otherwise-identical mono diets, which would be hard for food variety to explain.

Potato Diet with Urine Test

One plausible hypothesis is that potassium helps clear lithium from your brain, and this is why it causes weight loss. 

If this were the case, most of the lithium that is cleared from the brain should end up in your urine (urinary lithium seems to be a good proxy for levels in the body in general). It should be possible to test people’s urine for a while to establish a baseline, and then start them on the potato diet and see what happens. The level of potassium in their urine should increase dramatically, since there is so much potassium in potatoes. It would be interesting to see if the level of lithium in their urine increased as well. 

If urinary potassium levels were correlated with weight loss, that would be more evidence that potassium is the active ingredient (though they might not be correlated, since urinary potassium levels are part of a control system). If urinary potassium levels were correlated with urinary lithium levels, that would be more evidence that potassium is forcing lithium out of your brain (or some other reservoir). And if urinary lithium levels were correlated with weight loss (or frankly, even if they just went up when you started the potato diet), that would be strong evidence in favor of the idea that lithium is the cause of the obesity epidemic.

This could be the smoking gun for the lithium hypothesis, which makes it a pretty attractive idea. The problem is that we don’t have any experience running studies with urine samples, so we’re not sure how to design this study or how to run it. We’re also not sure whether it’s possible to run it over the internet, or if we would have to get a bunch of people together in person. If you do have experience in running studies with urine samples, and you’re interested in helping, please contact us.

However, even this study might not be conclusive. It’s possible that potassium counteracts the effects of lithium but doesn’t increase the rate of clearance. For example, potassium might compete with lithium in the brain without forcing it out. It might reduce lithium absorption in the small intestine. It might keep lithium from leaching out of your bones. It might do something else. (Lithium pharmacodynamics remain poorly understood.) So while it’s plausible that potassium increases lithium clearance, we aren’t confident that’s how things work. 

9. Conclusion

We ran this study because we suspected that potassium might be the active ingredient in the potato diet, that the high levels of potassium found in potatoes might be why a diet high in potatoes causes weight loss. These results support that interpretation. 

The weight loss observed in this trial was small on average, but the doses of potassium were intentionally very low. There’s evidence that the relationship between weight loss and potassium consumption is dose-dependent, such that people who took larger doses lost more weight on average. Regression modeling suggests that someone who was consuming a dose of potassium equal to the amount provided by the potato diet would lose a similar amount of weight as people lost on the potato diet. 

These results are not decisive. Indeed, no results ever are. However, given the small doses involved, the results could not be more strongly consistent with the potassium hypothesis. 

Potassium supplementation is scientifically valuable because it’s relatively controlled. But it’s not very practical, because it’s not clear if large doses of straight potassium salt are safe for most people, and because many people find potassium salt really gross. We strongly recommend that anyone who wants to lose weight should do the potato diet instead. The potato diet gives a much higher effective dose of potassium while probably being a lot safer, and may have other benefits. 

The all-potato diet is a relatively big commitment (though much easier than most people expect), so you may prefer to try the half-tato diet instead. This involves getting about 50% of your calories from potatoes and, based on the available case studies, seems to be more than 50% as effective and much less annoying. We plan to study it more soon.

If for some reason the potato diet doesn’t work, we would recommend you try to find some other way to eat a diet that’s exceptionally high in potassium. 

If none of these things work for you, then you can try direct potassium supplementation, though you should consult with your doctor, definitely not do it if you have diabetes or kidney disease of any kind, and limit yourself to no more than 5000 mg a day.

We probably will not follow up on this study at 6 months and 1 year, since the average weight loss was so small. It seems unlikely that 0.89 lbs of weight loss will be statistically detectable several months later.

However, several people reported that they are planning to stay on the potassium longer-term, so we may have more results soon from the people who reach 60 days on low-dose potassium. 

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

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 as the result of our research 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.

Your friendly neighborhood mad scientists,

APPENDIX A: Delivery 

People overwhelmingly took potassium chloride (93.3%), overwhelmingly as a salt (92.3%), and mostly as the brand Nu-Salt (62.9%). The most popular method of delivery was to take it dissolved in water, juice, a sports drink, or some other beverage.

We didn’t detect any differences in weight loss for any of these variables, but given that almost everyone took the same kind of potassium in roughly the same way, we wouldn’t have the statistical power to detect any differences unless they were really huge. So there may be differences, but we wouldn’t expect to see any evidence for them in this data, and indeed we do not. 

However, the delivery method does seem to make a difference in terms of enjoyment. Here is a sample of people’s recommendations: 

(45454797) The metallic taste went away after just a few days and I found the salt to actually taste good with a little apple cider vinegar and water. Gatorade without the sugar! (and easier than pressing lemons all the time)

(40941749) I highly recommend orange fanta if you’re gonna drink your magic potion, and hash browns if you wanna eat it. 

(77174810) Yes, KCl tastes gross/weird/bad. I tried a few different concentrations and mixtures with food (don’t mix with a bite of guacamole – yuck!). What I discovered was that mixing it with Simply Strawberry Lemonade makes it very palatable! I dissolved the KCl and a little sea-salt in about 1 oz of water. Then added about 4-6 oz strawberry lemonade. You could damn near sip it this way! Apple cider was the second best mixer.

(94352426) Higher concentrations were only drinkable to me in carbonated drinks made it okay to drink. For me this was the biggest limiting factor, always having to have carbonated water in home, buying it every time I went grocery shopping those bottles are a lot of extra weight. 

Though there was considerable variation: 

(52533228) By far, the easiest way for me to integrate it into my routine was to add it as a salt substitute in my cooking or meal prep. I could not stand adding it to drinks – the taste was usually awful and harsh. When it was added to food, the flavors mixed well in general and it was much much less noticeable.

(79332762) In terms of taking the potassium, I really disliked it. I would happily take a pill 1-2x per day, but I really dislike the taste of KCL. I tried two approaches to taking it, mustard & lemonade. With mustard it worked ok for low doses (1/8 tsp) but for larger doses it felt like too much salt hitting my stomach at once. With lemonade I don’t want to routinely drink enough lemonade that fully masks the flavor. I also really like lemonade as a treat so making it a daily routine (& making it taste bad) felt weird. I don’t really want to chug powerade/gatorade either.

APPENDIX B: Regulated Success

The body puts in a lot of effort to make sure you don’t get too much potassium. So one thing you might expect to see on this trial is that people start losing weight at first, but as their body acclimates to the extra potassium and their kidneys start filtering it out more aggressively, they stop losing weight and they maybe even gain back the weight that they lost. 

Some people did mention something along these lines. For example, participant 98856740 (who submitted after Dec 1 and whose comments are therefore not in the main dataset): 

I lost 6 pounds in the first week and then didn’t lose any more. In fact I bounced between that low number and about three pounds higher. During that weight loss period, I felt hot, enough to wake me up at night. I’ve heard people describe hot flashes during menopause that way. Once I got to the plateau stage, I no longer felt hot, just normal. I speculate that my metabolism was using heat to lose weight. I have no idea why it stopped. I don’t think there was anything materially different about the early days.

From the data, we’re not sure what to think. On the one hand, there are very few clear reversals. For example, the number of people who dropped 5 lbs at some point but ended up losing no more than one pound by day 29 is two, specifically these two participants: 

But on the other hand, most people hit their minimum weight well before the last week of the study, suggesting that many people hit a plateau early on. Here’s the plot where we highlight each person’s day of minimum weight: 

You can see that some people did hit a relatively low minimum weight early on and then never go down further from there. This may be evidence that some people hit a plateau. 

APPENDIX C: Accounts of Greatest Weight Loss


Well, my time in the experiment has been shocking, to say the least of it. So obviously I’m morbidly obese so I should probably address that right away considering I’ve lost over 12 lbs during this experiment.

In January 2022, I started working with a doctor that specializes in weight loss. I was put on a low-carb, ketogenic diet 6 days per week with 1 day of free eating anything I wanted, and an exercise routine of moderate walking every other day. My starting weight was ~485 lbs. My compliance with the diet and exercise routine was 100% from January until the start of the potassium trial. My starting weight at the beginning of the trial was 476.2 lbs, so I lost approximately 9 lbs during that 9-month time frame.

I DID NOT change my diet or exercise habits during the trial to any appreciable measure. There were a couple of times I mixed up my exercise routine but mostly I stuck to the same 60 minutes on a treadmill every other day. Any changes to the exercise were noted in the sheet.

Overall I think it’s incredible that the simple change of adding potassium seems to be responsible for a sudden change in the rate at which I was able to lose weight. I will be continuing supplementing potassium going forward, this is the single most amount of progress I’ve made in weight loss in a month.

I’m going to try to think of anything I can disclose here to give context to the data.

Potassium was consumed from Nu-salt and mixed with a Gatorade zero powder that also had some potassium (both details recorded on the sheet). I didn’t have any set schedule for the potassium, I simply added it whenever I felt thirsty and acquired water (up to the dose limit for the day)

My diet was a strict ketogenic diet (under 20 grams total carbohydrates per day, gross carbs, not net) for 6 days per week and one day a week of eating anything I wanted. I do not track calories. I don’t track macros other than the number of carbohydrates consumed to stay under 20. The 20-carb limit includes the 2g carb per serving of the Gatorade zero powder I used to mix the nu-salt.

I weighed myself completely naked on an “Ideaworks JB5824 Extra Wide Talking Scale” between 8:30 and 9:00 AM every day, preferably after having a morning bowel movement. If I didn’t have one, I would still record my weight. I made a note on the sheet whether or not I had a bowel movement for that particular day.

My heart rate was tracked using an AmazFit band with the pulse check feature, typically immediately before or immediately after weighing myself in the mornings.

Sleep is highly subjective but overall I think my sleep quality improved during the experiment, generally sleeping longer without waking up in the middle of the night.

My mood and energy have been nothing short of fantastic. On a normal day pre-trial, I’d rate my average mood and energy levels in the 4/5 area on the 1-7 scale. Somewhere during week 2 of the trial, I really noticed how elevated I felt in my mood all day long and generally my energy levels were high regardless of the amount of sleep.

During the first week of the experiment I remembered to measure my waist circumference as per the CDC method but frankly, I forgot to do that, but I have included a final measurement.

A final note about compounding factors: lithium reduction

I first discovered Slime Mold Time Mold through the “A Chemical Hunger” series of blog posts, but in particular, the section covering lithium is what caught my attention for potential causes of obesity. The reason it caught my attention is I was put on lithium to treat a neurological condition that I was diagnosed with (tourette’s syndrome) when I was 7 years old, and I can positively say that was the time when I began to put on weight steadily over years and decades regardless of my diet and exercise habits. I am 36 years old and have been off lithium for over 10 years now, but the lithium article really resonated with me as a potential cause. So I’ve installed activated carbon and reverse osmosis water filtration systems on all of the water taps in my house since the first lithium post in 2021. The filters I’m using the claim to remove “over 90%” of lithium from water. (City of Cincinnati water, Cincinnati, OH)

So I don’t know how entirely relevant all that could be to the data, but all of the water that I was mixing the potassium in was also water being treated for the removal of lithium specifically (although its been approximately a year of running filtered taps and only the addition of the potassium has resulted in dramatic weight loss)

I did not participate in the potato diet trial.

Anyone that wants to supplement potassium with Nu-salt should try mixing it with the Gatorade zero powder, it almost completely covers the taste and made the trial a breeze.

One last thing, I chose to limit the amount of Nu-salt I was consuming at the 1300mg per serving mark just because I didn’t want to go through my supply of Nu-salt and Gatorade zero powder too quickly. I felt entirely fine with the amount I was consuming and believe I could have easily continued in either increasing to higher doses or adding more 1300mg doses throughout the day.

Well, I feel like I’m rambling at this point but if there are any questions please feel free to ask, in the meantime I’m going to continue supplementing with potassium.


First I just wanted to clarify that I have been following a Time Restricted Eating, or Intermittent Fasting plan since Sep 30th, prior to learning about this study. I was excited to join the study since I found your posts on Twitter talking about the potato diet that people have raved about. I’ve been eating my meals between 12pm and 6pm every day and I’m sure it has contributed significantly to my weight loss. I hope this doesn’t skew the study results too much as a result of my eating schedule.

I did focus on keeping my calories under 3000 per day with a target of 2500. I also made an effort to exercise 2 to 3 times per week of 30 mins or more. That being said, I do think the potassium helped me manage my hunger, and specifically I felt like I didn’t need to eat that much during the day to feel full.

I found the study relatively easy to do. I set reminders for each dose through out the day, as well as a reminder for recording my weight and waist measurements and used an app to track those using my smart scale and smart measuring tape, both from Renpho. I discovered that drinking each dose with straight water was the easiest and fastest way to get it down. I tried with other drinks and things, but I just knew going in that it would taste funny, and got it over with quickly each time.

Starting out I didn’t have an 1/8th teaspoon measure, so I just started with 1/4 teaspoon. Being 6’4″ and 300 lbs, I figured I could handle a larger dose to begin with. Then as a result of not paying attention to the instructions very well, I ended up going up pretty quickly in dosage the first two weeks. For side effects, it was noticeable the first few days where I felt some stomach discomfort, and general unease, but it went away after the first week. The only other side effect that I think was related to the potassium, is that I found I had to pee a lot more often depending on how much water I was drinking. I tried to drink a lot of water throughout the day so I could get the most out of my bowel movements, but one issue was I just had to go pee a lot more. It felt like I would drink a cup of water, and then 20 mins later have to pee like I hadn’t gone all day. 🙂 I would say I had 1 to 2 liters of water per day in addition to meal time drinks (milk, juice, diet soda). I’m going to continue my eating and exercise schedule, but will stop taking potassium and just record my stats each day for the next month. I’d like to really see how the weight loss was impacted by the potassium. I’ll keep updating the spreadsheet and see how things go. I’m happy to talk more about my experience or answer any questions as part of any follow-up.


My 4 weeks are done, although I intend to keep taking potassium given the moderate success I experienced. Taking the potassium was very easy (with the exception of the few times I put nu-salt into pill casings and took it that way – this caused stomach pain, which I did not experience when just taking it dissolved in liquid). My overall impression is that potassium acts as a mild appetite suppressant. Thanks for running this trial, I’m looking forward to reading about the compiled results.


Sorry for the delay- I couldn’t load the sheets properly on my phone, but I was keeping track and am just now getting the chance to fill out the last week. Please excuse the order of the train-of-thought below.

I took my last weight the morning of Thanksgiving and proceeded to eat my weight in food. I haven’t been eating fast food lately but the cravings hit me hard (probably from a combination of eating way too much, alcohol, and not supplementing for a couple of days). My plan for now is to finish up leftovers today, grab some fast food over the next couple of days, and probably restart a 30 day period on Wednesday having gained about 5 pounds in a week.

All of my supplementary data (heart rate, sleep, exercise) was from my fitbit.

It was very true that I didn’t think of food while doing the trial. At the lower doses, my hunger was affected but my appetite was not. At the higher doses, both were affected. 

The biggest struggle for me was trying to keep track of my calories. I feel like it negatively impacted my trial because it did affect what I ate, even though I was supposed to eat whatever I wanted. I would eat what I wanted and feel shame/guilt for eating over X amount of calories (arbitrary number from back in my restriction days). The perhaps more interesting way it affected the trial was, once my appetite started being affected by supplementing, I would finish meals that I wouldn’t have because “I had already tracked the calories for it, I should get it,” “how can I track 1/3 of a meal,” etc. For my second attempt at the trial I will not be tracking calories, and hopefully not have the pressure of numbers to affect my eating habits. I understand that it was an optional variable anyways, but hypothetically the change in weight would reflect the appx input anyways.

I did not look into the lithium correlation at all, but if it is important- for meat markers, I only eat white meat. For egg markers, I only eat egg whites. The only thing I noticed that seemed to give me actual hunger pangs was if I drank a significant (about or more than 24 oz in a sitting) diet soda. Of course you can see in my data that alcohol also ruined a couple of days, but that didn’t actually make me feel any more hungry, just more crave-y and less likely to resist eating an entire pizza (apparently).

My work schedule is Fri/Sat nights, Sun-Tues mornings, and a random overtime on either Wed or Thur. Although my Fri shift is the same every week, there is a huge difference between that 3pm-11pm shift and my Tues 530-130 shift in terms of when and what I typically eat (and my sleep schedule). 

There was a huge difference in my general desire for food if I took the supplement in the morning before eating. If I took my first dose with food, I would be thinking about food sooner (though I wouldn’t say it was every hunger, just craving). When I took only the supplement and then went to work, it was almost always that I wouldn’t think of food until after work. If I took a dose without food and then went on my walk, even if I had already eaten that day, I would feel very light-headed.

I’m happy I found out about this trial. I am generally pleased with the outcome, if not the methods I specifically used, and am more excited about starting next week with a little less restriction. I’ll still track in case the data is useful for you, but probably only the weight and doses.


[SMTM’s note: despite the comment below, this participant reported losing 8.6 lbs.]

Thanks for running this trial, it was interesting. My subjective feeling is that the potassium supplementation had no discernable effect on my brain function, hunger/diet, or weight. I’m planning to continue supplementing potassium though because my food diary shows my intake of it was very low and I’m curious whether it might have any longer term effects past just the first 4 weeks.


First of all – holy shit! It’s amazing how well this worked and it’s also surprising that it’s never really been studied before! Thank you for the analysis and thought that you put into this. For this trial, I basically just ate whatever I felt like, went to a football tailgate party nearly every weekend with lots of beer and foods you would not associate with dieting… and still lost nearly 10 lbs! I plan to continue on for at least another couple months so feel free to follow up later if you want to.

Interestingly, I was born and raised in Colorado. I lived there for my first 30 years until 2003 when we moved to the East coast and although I am a bigger person (6’5″/225 in 2003), I was never really “heavy” until maybe 2010 or so. I kept putting on weight as I aged into and past my 30s and I just followed conventional “wisdom” that it was due to getting older. Each year I would have a few extra pounds. 

I have tried every diet/exercise and variation of CICO, atkins, keto, IF, etc., etc., etc. to try and lose weight. To no one’s surprise, nothing really worked for long and the weight always came back. At the end of 2020 I was over 275. It took me three months of busting my ass to lose 20 pounds and as soon as I started eating “normally” again, I slowly started putting weight back on.

Anyway, you may have just solved obesity. I hope you enjoy being billionaires. Don’t forget us little guys that did nothing but participate in your study when you are trying to decide on the color for your private jet (I think dark blue would be nice).

Notes and observations:

Yes, KCl tastes gross/weird/bad. I tried a few different concentrations and mixtures with food (don’t mix with a bite of guacamole – yuck!). What I discovered was that mixing it with Simply Strawberry Lemonade makes it very palatable! I dissolved the KCl and a little sea-salt in about 1 oz of water. Then added about 4-6 oz strawberry lemonade. You could damn near sip it this way! Apple cider was the second best mixer.

I felt thirsty a LOT of the time, especially in the first week or so. I increased my water consumption by over a quart/day for the duration of the study (still ongoing)

On the weekends, I ate poorly (nutrition wise) but still overall was eating way less than I usually did.

I only tried a 1320mg dose once. I didn’t feel great but cannot say for sure that it was that higher dose. I plan to try two higher doses/day for the second month

I settled on 3 doses of ~990mg (3/8 teaspoon) a day at 0730, 1130, 1600. I felt like this kept hunger at the lowest level overall and was easy to stick with.

I found that if I took the supplement when I was already hungry, I’d eat more overall. So I take the dose an hour or so before I’d normally eat a meal. 

I’m very curious about this mechanism for weight loss. Does K+ just act as an appetite suppressant? Or is it more that the lipostat is turned down and that makes you less hungry? If lithium passes through the body fairly rapidly, how long does the effect last on the brain (if that is what is happening)? When I have cut calories in the past, it was an uphill battle to fight hunger. Presumably my lipostat was set too high so I’d be hungry and also not lose weight effectively because my body was not trying to lose weight. Hmm, might make sense… I plan to do this for at least another month if not two. It will be interesting to find out:

Could there be any detrimental long-term effects of taking this much extra K?

If I stopped the supplemental K, will I start to trend back up in weight? How hard will it be to keep the weight off?

How long does the effect last? Will I be (normal) hungry tomorrow if I stop supplements today? 

I intend to experiment with the following after I hit my target: 

Could I take the supplement every other day or once a week as a “maintenance” dose and keep the weight off? Or maybe just a smaller daily dose?
Looking forward to your further analysis and trial results.

Study: Subclinical Doses of Lithium Have Plenty of Effects

Drugs have effects. Take more of a drug, and you’ll get more and bigger effects. They call this a dose-response relationship — take some dose, get some response. Benadryl makes you drowsy, mercury gives you hallucinations, cyanide kills you. 

But these effects only kick in above certain doses. At very low doses, the drug has no effects. This always has to be true, because at zero dose, the drug can’t have any effects. 

Then at some dose, the effect starts kicking in. Sometimes this means you start feeling it a little and it gets stronger over time. Other times, it means the response rate increases, and more people start feeling the effect as they take bigger doses.

At some point, the effect is as strong as it can possibly get and it doesn’t get any stronger. Everyone who is going to have a reaction is getting the strongest effect they can get.

Dose-response relationships can be described with dose-response curves, like this one: 

Often these curves make the most sense on a log scale (probably because this is bounded exponential growth; it’s exponential but eventually everyone who is going to have the effect already has it), so for this exercise, we’ll be portraying the x-axis on a log scale. This may not be true for all drugs, but it’s a reasonable starting place.

Lithium is a metal that is also a drug that sometimes causes weight gain. But no one really knows what the dose-response curve for weight gain on lithium looks like. Weight gain is clearly a side effect of clinical doses of lithium (about 50-300 mg of elemental lithium a day), at least for some people. But almost no one has studied lithium doses below 50 mg a day, so we don’t know at what point this weight gain effect starts kicking in.

The dose-response curve could look like this, where weight gain doesn’t show up until you hit therapeutic doses of 100 mg/day and more:

The y-axis is 0 to 40 lbs, this is arbitrary, graphs are for illustration purposes, not real data, etc.

Or it could look like this, where effects kick in starting at subclinical doses of as low as 1 mg/day:

Or it could even look like this, where weight gain starts at trace doses of less than 1 mg/day, and once you’re getting 10 mg/day, you’re maxed out:

The curve could be spread out, with gradual effects increasing across all plausible doses:

Or it could be incredibly abrupt, where weight gain happens suddenly once you’ve passed a certain threshold: 

There’s also good reason to believe the dose-response curve will be different for different people. The response may be different in terms of the shape of the curve, when the effects kick in, and when they max out. 

By ancient tradition, we will call our example patients “Alice” and “Bob”. In this hypothetical, Bob starts seeing weight gain as he approaches 1 mg/day and has already gained almost 40 lbs at 10 mg/day, but Alice doesn’t get the same effects until noticeably higher doses: 

It might also be different in terms of the maximum effect. In this next example, not only does Alice not start gaining weight until 10 mg/kg, she caps out her weight gain at just over 20 lbs, while Bob gains 40 lbs on a similar dose:

Psychiatric doses of lithium are in the 50-300 mg range (elemental), and some people think this means that weight gain must happen in this range. But this may not be the case. 

First of all, there’s plenty of evidence suggesting that the psychiatric effects of lithium kick in at trace doses of less than 1 mg/day. The effects may not be very strong at trace doses, but you can still pick them out in a population-level analysis. In fact, there’s a whole dang literature finding that rates of dementia, suicide, homicide, and other “behavioral outcomes” are associated with trace lithium levels in drinking water. This suggests that some effects kick in at very small doses.

But regardless of whether or not trace amounts of lithium lower the suicide rate, the fact is that lithium has several different effects, and there’s no reason those effects can’t kick in at different doses. It might look something like this:

In this case the y-axis is in percent, not lbs, since you can’t have pounds brain fog.

(To be clear, all these curves are completely made up for the purposes of illustration.)

This should probably be our default assumption. Most drugs have multiple effects, and different effects often kick in at different doses. For example, alcohol is a drug that makes you talkative at low doses and makes you puke your guts out at high doses.

(Your mileage may vary. Adam Mastroianni, who reviewed this piece, says, “Not me, I puke a tiny amount at tiny doses, increasing to a massive amount of puke at large doses.”) 

dose-response figure showing different effects

In fact, we know that lithium has effects that kick in at different doses, because therapeutic effects tend to kick in well before patients die from lithium toxicity, and death is also an effect.

It’s true that some people don’t gain weight at all, even on clinical doses of more than 1000 mg/day. But this might just mean that in their case, the dose-response curve for weight gain is above the dose-response curve for toxicity/death. You can’t get there without dying, so we never see it. (And for some people, the mechanism by which lithium causes weight gain probably just doesn’t work at all.)

In any case, we have almost no information about what the curves might look like for lithium, because there’s very little research on doses below the low end of the clinical range (around 50 mg/day). There’s that literature on trace doses in drinking water which we mentioned above, and there’s one RCT from the ‘90s finding that trace doses of lithium made violent offenders friendlier and happier — but as far as we know, there’s never been any formal study on doses in the range of 1-50 mg/day. If anyone has studied weight gain on lithium doses below 50 mg/day, we’ve certainly never seen it.

So let’s see what we can do to figure out anything at all about the dose-response curve for the weight gain effects of lithium — and, maybe more interesting, the effects of lithium in general. Do any of these curves start showing up at subclinical doses?

Nootropics Survey

One thing that’s interesting, in terms of our bigger “is lithium exposure causing the obesity epidemic?” question, is that most of the side effects of lithium are non-specific — if you feel nauseous and tired, it could be lithium exposure, but it could equally be a million other things. That makes it hard to tell if symptoms of lithium exposure have increased over the past 50 years, since no one has been tracking brain fog rates since 1970. If the rate of increased thirst has dectupled, we might not even know (unless…).  

But one thing people do track is hypothyroidism. Clinical doses of lithium, at least, can lead to hypothyroidism, and even mild thyroid dysfunction is linked to changes in body weight. And while the evidence isn’t anywhere near conclusive, some studies suggest that the rate of hypothyroidism has increased — see for example this popular press article, this analysis of hypothyroidism in the UK, and this study of a population in Scotland. Since clinical doses can cause thyroid problems, increasing rates of hypothyroidism make it slightly more plausible that trace lithium exposure (which has clearly increased) has subclinical effects.

Some of the effects we’re going to study — like fatigue, depression, and muscle weakness — are also symptoms of hypothyroidism. These are also nonspecific, but if they were to increase, they might be diagnosed as hypothyroidism. We’re curious to see if they increase on low, subclinical doses. 

We worked with Troof (a science blogger who has recently been studying nootropics) to put together a survey (a PDF version is available on the OSF) asking nootropics enthusiasts about the doses of lithium they have tried, if any, and the effects they experienced on each dose. (In case you’re not familiar, here’s the Wikipedia page for nootropics.)

The survey was pretty straightforward. First, we asked people for their basic demographic information. Then, we asked them to describe their previous experience with lithium. 

We allowed people to record information for up to five different doses of lithium — different in either being different amounts (e.g. 1 mg/day vs 5 mg/day), different compounds (e.g. lithium as lithium orotate vs. as lithium carbonate), or both. 

For each dose, we asked people to tell us what compound they took, how much they took per day, and approximately how many days they tried the dose for. 

We also asked them what effects they experienced on each dose. Our list of effects was based on this page from Mayo Clinic, though our list did not include all the effects mentioned on this page.  

We make no claims that our list is any sort of principled selection — it’s just a subset of effects we decided to include. There were too many to include all of them, so we made some calls. 

In particular, we focused on “milder” side effects, since we knew that the nootropics folks would be on lower doses than a clinical population and would probably not experience the more severe effects. We also combined some effects to avoid redundancy — for example, we combined multiple effects related to passing gas into the single effect “flatulence” on our list. 

We do regret cutting “fruit-like breath odor” and “eyeballs bulge out of the eye sockets”. Now those are side effects.

In any case, the final list was: 

  • Increased clarity / focus  
  • Increased calm  
  • Improved mood  
  • Improved sleep  
  • Trouble sleeping  
  • Weight gain
  • Weight loss
  • Confusion, poor memory, or lack of awareness
  • Fainting
  • Fast, pounding, or irregular heartbeat or pulse
  • Frequent urination  
  • Increased thirst  
  • Slow heartbeat
  • Stiffness of the arms or legs  
  • Troubled breathing (especially during hard work or exercise) 
  • Unusual tiredness or weakness  
  • Brain fog  
  • Dizziness  
  • Eye pain  
  • Headache  
  • Vision problems  
  • Depression  
  • Diarrhea  
  • Drowsiness  
  • Lack of coordination  
  • Loss of appetite  
  • Muscle weakness  
  • Fatigue  
  • Nausea  
  • Ringing in the ears  
  • Slurred speech  
  • Trembling (severe)  
  • Bloating or indigestion  
  • Flatulence  
  • Decreased libido  
  • Loss in sexual ability, desire, drive, or performance  
  • Tooth pain

We also included an option for “other”.

Finally, because we are especially interested in weight changes, we also asked for each dose, “If you lost / gained weight, what was approximately the magnitude of the loss / gain”, with answers in kilograms. 


Nootropics enthusiasts often take small amounts of lithium, usually because they believe it has a variety of beneficial effects at low doses, effects including balanced mood and reduced stress. So recruiting from the nootropics subreddit seemed like a good way to find people who already have experience with subclinical doses.

We put out the survey on r/Nootropics, in a post titled, “We’re Collecting People’s Experiences with Lithium. All Results and Data Will Be Posted Publicly. If You Have Experience with Lithium, Please Contribute!” This was our only recruitment strategy and, as far as we know, all responses came from people on r/Nootropics. 

A total of 40 people filled out the survey, providing data on at least one regimented dose (an amount taken daily for a period of time) of lithium. Of these, 20 people also reported on a second dose, 5 reported on a third dose, 2 reported on a fourth dose, and one person reported on a fifth dose. From this we can see that of the respondents, 50% have tried at least two different doses of lithium at some point.

For now, we will ignore that some of these doses are the same people, and just treat these as 68 different individual doses. Going back and doing more complex modeling at some point would be a good idea, we encourage that, but it’s not the focus of the post today. To keep it clear, we will call these “cases”. There are 40 people who gave us 68 cases.

Two people don’t report how much they were taking for their second dose, however, so we will be ignoring these cases. In the end we have 66 cases.

This is all self-report, and we haven’t been at all strict about kicking people out. In fact, we didn’t kick anyone out. Some of the data do look a little strange. One person reported taking 5 mg/day of lithium carbonate, which seems unlikely. But we’re taking the data at face value for now. 


First of all, we want to see how much elemental lithium everyone is taking. 

Many people reported a single number for their daily lithium dose, but some people reported a range, e.g. “5mg-20mg”. To convert this into a single number for analysis, whenever a person gave a range of values, we went with the average of the range endpoints. In this example, a report of “5mg-20mg” would be converted to 12.5 mg.

Different lithium compounds contain different amounts of elemental lithium. This is the “active ingredient”, so to speak. We did our best to estimate elemental lithium from the numbers people reported. In most cases, this was pretty straightforward. Lithium carbonate is prescribed by the weight of the compound, and the elemental dose is 18.8% of the weight of the listed dose. Lithium orotate usually lists elemental lithium on the packaging, and so most of the time, no conversion is needed.

However, we did have to guess on a few. For example, one person said that they were taking lithium orotate, but said they were taking 130 mg per day. Based on what we know about lithium orotate doses available on the market (see e.g. here), we think 130 mg elemental is very unlikely — this is probably 5 mg elemental, so we coded it as 5 mg. For all these conversions, you should be able to double-check our numbers in the raw data (available on the OSF). 

Having made these conversions, we find that people were taking doses between 0.25 and 282 mg per day elemental lithium, over spans ranging from 1 day to 4 years. We use dose per day because it’s easy to track. Here’s the distribution: 

As you can see, most people were taking less than 50 mg/day. In fact, most were taking less than 25 mg/day. The median daily dose in this sample is 10 mg/day, the mean is 39.6 mg/day, and the mode (15 people) is 5 mg/day. The next most popular dose after the mode is actually 1 mg/day — 6 people were trying that amount.

In comparison, the average therapeutic dose is 50-300 mg/day elemental lithium, usually delivered as lithium carbonate. So overall, these nootropics folks are taking rather small doses.

Lithium orotate was by far the most popular compound in our sample. This makes a lot of sense — lithium orotate can be purchased over the counter, or over the internet, without a prescription, and comes in relatively low elemental doses, all of which makes it an ideal nootropic. Of the 66 cases, 42 people were taking lithium orotate, 22 were taking lithium carbonate, and one each were taking lithium aspartate and “Lithium Chloride / Ionic Lithium”. 

We keep saying “doses”, but it’s important to keep in mind that from a biological point of view, these are not really doses — these are deltas, a change in the daily dose. People are already getting some small daily dose of lithium every day from their food and water, so whatever they are taking as a nootropic is a dose in addition to the dose they were already getting. We don’t currently know what kinds of doses people are getting from food and water — the literature is a little confused at points — but we’re confident that it’s more than zero.

So while we don’t know if the average American is getting 5 mg/day from their food or just 0.05 mg/day, we know they’re getting some amount — for now, let’s call the average everyday dose X. If someone is taking 5 mg/day as a nootropic, they’re not getting a total dose of 5 mg/day, they’re getting X + 5 mg/day.

Weight Change

Let’s start by looking at weight change on these low doses.

Like the doses themselves, weight change was also reported as a range in a few cases. Like the doses, whenever someone gave a range, we took the mean of that range as our point estimate value. 

Here are the weight changes people reported compared to the daily elemental dose they were taking. Note that the weight changes here are in kilograms:

That plot is a little hard to read because most people are taking low doses (< 50 mg/day) so most of the points are crammed in over on the left side. To make it easier to read, here’s the same plot with the x-axis log10 transformed (with some jitter in the x-axis to keep points from overlapping):

One caveat is that these plots include many people who didn’t actually mention any weight change at all. Since they didn’t mention it, we assumed the weight change on their dose was effectively zero. This seems like a pretty safe assumption, but just in case, here’s the same plot with only the people who explicitly said something about their weight change: 

Most people didn’t see any weight change, or at least, they didn’t report any. But 8 of the 66 cases did report some weight change. 

The first weight change reported is a loss of 3 kg, at a dose of 5 mg/day. This is a low dose, and it’s weight lost, not weight gained, which makes it something of an outlier. 

The first weight gain reported is an increase of 5 kg on 20 mg/day, which this participant reported taking for approximately 365 days. The next weight gain is 8 kg on 50 mg/day, which the person reported taking for only 60 days.

After 50 mg, weight gain seems to be more common, though certainly not universal. Of people who took more than 50 mg/day elemental, 6 of 18 reported weight gain, which is 33%. The highest weight gain reported was 35 kg (not pounds, he was quite clear) on 56.4 mg/day elemental taken as 300 mg/day lithium carbonate, over 4 years.

So, keeping the limitations of the small sample in mind, this suggests that the weight gain effects kick in around the range of 20–50 mg/day of elemental lithium, for somewhere in the ballpark of one third of people. 

The sample size is quite small, but if you squint, it does kind of look like weight gain kicks in a bit earlier for Lithium Orotate than for Lithium Carbonate. We didn’t expect this, but while we were working on this project, a reader pointed us to a small literature finding that lithium orotate is sometimes effective at a lower dose than lithium carbonate. 

This is a literature that currently seems to be driven by Anthony Pacholko and Lane Bekar, two Canadian researchers from Saskatchewan, building off of the work of Hans Nieper in the 1970s. In the interest of full disclosure, we should tell you that Wikipedia describes Nieper as “​a controversial German alternative medicine practitioner” whose therapies have “been discredited as ineffective and unsafe.” The “see also” links at the bottom of his page are “List of unproven and disproven cancer treatments” and “Quackery”. Caveat lector

In any case, there is a review by Pacholko and Bekar from 2021, which does cite many sources outside Nieper, and says in the abstract, “[lithium orotate] is proposed to cross the blood–brain barrier and enter cells more readily than [lithium carbonate], which will theoretically allow for reduced dosage requirements and ameliorated toxicity concerns”. They also have an empirical study published in 2022, which reports benefits of lithium orotate over lithium carbonate in mice.  

We’re not going to review the whole literature here, but it’s worth noting. Let’s mark it down for now as suggestive. 

Other Effects

Weight gain is not the only effect of lithium. It might not even be the most interesting effect.

The nootropics people on reddit dragged us for mostly including negative effects — which, you know what, totally fair. We should have included more positive effects. We’re interested in seeing when the bad stuff kicks in, but while we were at it, we should have looked at when everything kicked in. If we study this again, we’ll include more positive effects.

We also now realize that we should have asked for the effects on a scale (1-7, 0-3, something like that). Asking just “did you experience increased thirst or not” gives us very little information for most of these symptoms. If we study this again, we’ll use more detailed measures. 

But for now, let’s look at the data we have. And the data we have are already pretty interesting. People reported experiencing all sorts of effects:

And, to our surprise, they reported lots of these effects even on pretty low doses: 

As before, this is a little hard to read because of the squashing. Here’s the same thing with the x-axis log10 transformed:

Even below 10 mg/day elemental (a 1 on the x-axis above, since this is log10), most people are reporting a few of these effects, and some of them are reporting several. Above 10 mg/day elemental, almost everyone reports multiple effects! It’s clear that stuff starts kicking in at pretty small doses. 

Moving beyond the aggregated effects, we can ask, what effects popped up specifically? Here’s the list, with the number of cases that mentioned each effect:

  • Increased clarity / focus: 14  
  • Increased calm: 38  
  • Improved mood: 35  
  • Improved sleep: 23  
  • Trouble sleeping: 7  
  • Confusion, poor memory, or lack of awareness: 12  
  • Fainting: 0
  • Fast, pounding, or irregular heartbeat or pulse: 1
  • Frequent urination: 10  
  • Increased thirst: 11  
  • Slow heartbeat: 0
  • Stiffness of the arms or legs: 1  
  • Troubled breathing: 2  
  • Unusual tiredness: 5  
  • Brain fog: 13  
  • Dizziness: 5  
  • Eye pain: 2  
  • Headache: 3  
  • Vision problems: 1  
  • Depression: 5  
  • Diarrhea: 4  
  • Drowsiness: 5  
  • Lack of coordination: 4  
  • Loss of appetite: 5  
  • Muscle weakness: 2  
  • Fatigue: 8  
  • Nausea: 2  
  • Ringing in the ears: 3  
  • Slurred speech: 2  
  • Trembling (severe): 3  
  • Bloating or indigestion: 4  
  • Flatulence: 2  
  • Decreased libido: 10  
  • Loss in sexual ability, desire, drive, or performance: 4  
  • Tooth pain: 0

And here are the top 10:

  • Increased calm: 38  
  • Improved mood: 35  
  • Improved sleep: 23  
  • Increased clarity / focus: 14  
  • Brain fog: 13  
  • Confusion, poor memory, or lack of awareness: 12  
  • Increased thirst: 11  
  • Frequent urination: 10  
  • Decreased libido: 10  
  • Fatigue: 8  

We see that the four positive effects are the most commonly reported, which is what we would expect from a population of nootropics users who are taking lithium in search of positive effects. More than half of the cases reported “increased calm” and “improved mood”, and around a third reported “improved sleep”. On top of this, 14 reported “increased clarity / focus”. Of the 66 cases, 50 (about 75%) reported at least one of these four positive effects. 

But this also makes it especially striking that so many people reported negative effects. If anything, this population is inclined to downplay the negative effects of lithium, but negative effects were reported quite frequently.

The most commonly reported negative effect was brain fog (13), followed by “confusion, poor memory, or lack of awareness” (12). These sound like the same thing, but there wasn’t perfect overlap. We see that 7 people reported brain fog without reporting confusion, and 6 reported confusion without reporting brain fog. 

It’s pretty weird that “increased clarity / focus” is the fourth most common effect and “brain fog” and “confusion, poor memory, or lack of awareness” are effects #5 and #6. Aren’t these polar opposites? Why are they right next to each other in the rankings? Sounds like a possible paradoxical reaction.

The next most common effects were increased thirst (11) and frequent urination (10), which also seem related. 

After that, the next most common is decreased libido (10), which is supported by a less common but related effect, “loss in sexual ability, desire, drive, or performance” (4). These are both reported at rather low doses, as low as 1 mg/day.

The next most common are fatigue (8), and trouble sleeping (7), and then we get into numbers too small to go over individually. But even so, almost every symptom we put on our list was reported by at least one person — we certainly did not expect that. The only three symptoms that no one reported were fainting, slow heartbeat, and tooth pain. 

Some of these symptoms, like ringing in the ears (3), are only reported by people who were taking more than 50+ mg/day. But lots of effects start appearing at very low doses. 

C5H3LiN2O4 , his name is my name too

Like with the weight gain, there might be more effects for orotate than for carbonate at the same elemental dose. Don’t take this as conclusive — there’s not all that much evidence. But it is intriguing.

We can even do a regression looking at just the data from cases where people were taking carbonate or orotate. This brings us to a somewhat unusual finding. 

When the dose of elemental lithium is used to predict the total number of lithium effects, the regression model finds significant main effects of both dose (p = .0008) and compound (p = .021), and a significant dose-by-compound interaction (p = .0019). The total R-squared is 0.257, which is pretty good. This model suggests that lithium orotate does bring on more effects at a lower dose than lithium carbonate.

But, there is only a main effect of dose (p = .005) when dose of elemental lithium is log10 transformed. In this case, the compound (p = .899) and the interaction (p = .718) are not significant, though the R-squared is pretty similar (0.245).

This difference is pretty clear when we plot both models with their regression lines. Here’s the situation if you don’t log-transform the daily lithium dose. You can clearly see that the slopes of the two lines are very different:

But here’s the situation if you do log-transform the daily lithium dose. You can clearly see that the slopes of the two lines are nearly identical:

This is a little weird. On the one hand, that’s a pretty clear interaction in the non-transformed data. On the other hand, we would expect log transformation to be the appropriate transformation for this analysis. Make of that what you will.

Troof points out that a lot of this interaction seems to be driven by a single participant, who looks kind of unusual and is taking an unusually high dose of lithium orotate. If you look at the plots, you can see them as a somewhat clear outlier (taking the most orotate and having the most effects of anyone on that compound). So probably don’t put too much trust in this data point, and without it, the case for an interaction basically disappears.


These results suggest that many effects of lithium kick in at subclinical levels. In this sample, the majority of people who took at least 1 mg of elemental lithium a day reported at least one effect, and people on doses above 5 mg/day tended to report experiencing several effects. 

The most common effects people reported were the four positive effects we asked about, but several negative effects of lithium were commonly reported as well, especially brain fog, “confusion, poor memory, and lack of awareness”, increased thirst, frequent urination, decreased libido, “loss in sexual ability, desire, drive, or performance”, fatigue, and trouble sleeping. A slight majority of cases (53%) reported at least one negative effect.

Weight gain was not a common effect, but it was reported at relatively low doses. The lowest dose for reported weight gain was on a dose of 20 mg/day, and the next lowest was on 50 mg/day. The greatest reported weight gain was on a dose of only 56.4 mg/day. Taken together, this suggests that in the current environment, lithium can cause noticeable weight gain on elemental doses below 50 mg/day, and possibly as low as 20 mg/day.

Unfortunately, this does not tell us all that much about the dose-response curve. There are just too many degrees of freedom, and we don’t know that X value, the amount that people are getting from their food and water. It could be that X is well below the dose-response curve, and +50 mg/day is needed to push you onto the curve:

But it could equally be the case that X is well onto the curve — past the point of greatest sensitivity! — and a big delta like +50 mg/day is needed just to see any weight change at all. 

This evidence doesn’t rule anything in, but it does rule some things out. Given these findings, we can mostly rule out the idea that doses below 10 mg/day have no effects. We can also rule out the idea that weight gain starts kicking in at just 0.1 mg/day — it seems pretty clear that you need a bigger delta than that. But we can also mostly rule out the idea that weight gain only occurs above 600 mg/day.

So while it’s good that some things are ruled out, we still don’t know enough to pin down the dose-response curve.

At least, not for weight gain. We do see what looks like evidence of the dose-response curves for other effects.

Troof also played around with the data a bit, and sent us the following graph. The pattern is clear for some effects and rather messy for others, but we see what looks very clearly like the start of a dose-response curve for increased thirst. We also see what look like dose-response curves for improved mood, improved sleep, increased calm, and increased clarity, where rates of the effects increase and then level off. But there isn’t a clear curve for brain fog or confusion, at least not in these data. 

One weird thing we noticed is that most of these dose-response curves come down at the highest dose level, suggesting that some of these effects actually get less likely past a certain point. Not sure what’s going on there, we’re interested to hear what people think.

Human Challenge

At this point you might be wondering: should someone do a human challenge trial for low-dose lithium? You know, round up some brave souls on the internet, get them all to take 10 mg’s worth of lithium orotate every day for a month, and see what happens to them by the end. Is that a good idea?

We don’t think this is a good idea, for a couple reasons. First of all, we don’t know what X is, which means that increasing the dose by a fixed amount isn’t actually all that informative. 

Second, we’re pretty sure that X is different in different places and for different people. Combine this with the fact that different people probably have different dose-response curves for strictly genetic reasons, and the results begin seeming hopelessly complicated. 

Finally, while low-dose lithium does seem to have positive effects for many people, some of its effects are quite nasty. We wouldn’t want to subject volunteers to unnecessary brain fog and fatigue. If we were sure that the study would teach us a lot, then maybe it would be worth it, maybe we would be open to convincing people to give it a go. Maybe we would try it ourselves. But since we don’t think it would really answer any of our biggest questions, we don’t think a lithium supplementation study would be worth anyone’s while. 

However, Troof has convinced us that there are more than 40 people out there who have already tried subclinical doses of lithium, and that at least some of them will be reading this post. So we’ve put together an updated version of our survey that fixes some of the problems we mentioned above — it asks about the magnitude of each effect, includes more positive effects, and includes more effects in general. If you’ve taken lithium before, you can fill out the survey here, and if we get enough responses, we will post another analysis. If you filled out the first survey, you can fill this one out too, because this one is a little more detailed — just check the box that indicates that you took the first survey, so we can make sure not to double-count you.

Low-Dose Potassium Community Trial: Sign up Now

The potato diet is a diet where you get most or even all of your calories from potatoes. Surprisingly, this is easy for many people to stick to, and participants who stayed on the diet for a full 28 days lost an average of 10.6 lbs, despite the fact that nearly all of them took multiple cheat days. This seems like a pretty strong weight loss effect, but the question remains: why does it work?

Potatoes are special for many many reasons, but by far the most obvious thing that makes them special is that they’re really high in potassium. If potassium is the reason the potato diet makes people lose weight, then there’s a good chance that taking potassium directly would also make people lose weight. Someone should really do a study. Who, us? Ok, fine.

Tl;dr, we’re looking for people to volunteer to supplement small doses of potassium chloride (KCl) for at least four weeks, and to share their data so we can do an analysis. You can sign up below.


Potassium (K) is a slivery-white alkali metal, and element number 19 on the periodic table. In its pure form, it is highly explosive on contact with water. But most of the time, we encounter potassium in forms where it is much more stable. 

In these non-explosive forms, potassium is an essential mineral for human life. Because it plays many important roles in your biology, you have to consume a small amount of potassium every day to remain healthy.


There are a couple reasons to suspect that potassium might be the active ingredient driving the weight loss we see on the potato diet. The first is that the potato diet provides stunningly high doses of potassium, amounts that most people would never otherwise consume. 

For a long time, the recommended daily value for adults (technically, the “Adequate Intake”) was 4,700 mg of potassium per day. But most people don’t get anywhere near this amount. 

In every CDC NHANES dataset from 1999 to 2018, median potassium intake hovers around 2,400 mg/day, and mean intake around 2,600 mg/day. In this report from 2004, the National Academy of Medicine found that “most American women … consume no more than half of the recommended amount of potassium, and men’s intake is only moderately higher.” Per this paper, only 0.3% of American women were getting the recommended amount. Similarly low levels of intake are also observed in Europe, Mexico, China, etc.   

But in 2019, the National Academies of Sciences, Engineering, and Medicine changed the recommended / adequate intake to 2,600 mg/day for women and 3,400 mg/day for men. They say that the change is “due, in part, to the expansion of the DRI model in which consideration of chronic disease risk reduction was separate from consideration of adequacy,” but we can’t help but wonder if they changed it because it was embarrassing to have less than 5% of the population getting the recommended amount.

In any case, recommended potassium intake is something like 2,500 to 5,000 mg per day for adults, and many people don’t get enough.

Potatoes are exceptionally high in potassium. A single potato contains somewhere between 600 and 1000 mg of potassium, depending on which source you look at. They are the 6th highest in potassium on this list of high-potassium foods from the NIH, and 9th on this old list from the USDA. If you do the math, this means that someone on the potato diet, eating 2,000 kcal of potatoes a day, gets at least 11,000 mg of potassium per day, more than twice the old recommended intake. 

Some people on the potato diet found their appetite decreased so much that they were only eating about 1,000 calories per day — but even then, they would still be getting around 5,500 mg of potassium. 

Only 2.8% of Americans in the NHANES data got 5,500 mg per day or more. Only 0.06% were recorded as getting 11,000 mg/day or more. Clearly, the potato diet provides way more potassium than most people would ever get in their day-to-day lives. 

Correlational Evidence

One study, published in 2019, looks at the relationship between potassium intake and weight loss. As far as we know, it’s the only study of its kind (if you know of any others, send ‘em our way). In this study, sixty-eight people were enrolled in a “moderate low calorie/high protein Mediterranean diet” for a year. People generally lost weight, and “the strongest correlate of the decline in BMI was the increase in dietary potassium intake.” 

In the aggregated publicly-available NHANES data from 1999 to 2018, potassium intake is negatively correlated with BMI (r = -0.055, p < .001) and log BMI (r = -0.051, p < .001). Because of complications around body size (taller people consume more food anyways, and therefore more potassium), we actually think that potassium per calorie, or potassium density, is the more appropriate measure. The relationship here is weaker (r = -0.031 with BMI, r = -0.022 if BMI is log-transformed), but still significant because of the large sample size.

But the really interesting thing is that the relationship gets stronger year-to-year across the span of the NHANES data. Here it is with both BMI and potassium density log-transformed. The relationship holds regardless of transformation, but log-transformation makes for the clearest visualization:  

The relationship between potassium density and BMI is not significant in the early years of the NHANES data. From 1999 to 2010, the correlation is always consistent with zero, and p-values are always .20 or greater, even with these very large sample sizes. The sign of the nonsignificant relationship flips back and forth between positive and negative. 

But in the 2011-2012 dataset, the relationship is negative, and the p-value drops below 0.10 for the first time. In the 2013-2014 dataset, the relationship is negative and significant (p < .001). In the remaining two datasets, 2015-2016 and 2017-2018, the correlation gets stronger and stronger. By 2017-2018, the correlation is r = -0.095. Aggregated across all years, the relationship is “only” r = -0.024, but that obscures the fact that the correlation has been increasing since around 2011.

There are certainly alternative explanations for this finding. For example, people who eat a diet that is higher in vegetables might both have lower BMIs and get more potassium on average. But it’s hard to come up with an explanation for why the relationship has been increasing, especially since potassium consumption / dietary potassium density haven’t changed at all over the same timespan: 

This analysis doesn’t tell us much by itself. It isn’t strong evidence that potassium can cause weight loss, and doesn’t convince us of anything in particular. But it’s genuinely pretty weird, and since we don’t have much other correlational evidence, we thought it was good to mention.


The final reason to suspect that potassium might cause weight loss is that we tried taking small doses of potassium for a couple of weeks and we lost weight right away.

Two of the SMTM authors did a self-experiment where we took small doses of Nu-Salt and tracked our weight over time. Nu-Salt is just potassium chloride (KCl) in a salt shaker, marketed as a sodium-free alternative to table salt. You can buy Nu-Salt shakers online, at many local grocery stores, or even at Wal-Mart

We started with two doses of 1/8 teaspoon Nu-Salt (about 330 mg potassium) twice a day and worked up from there. Straight potassium chloride is kind of gross (at least to us, your mileage may vary), so most of the time we mixed the KCl with a drink like Vitamin Water or Gatorade and just chugged it, though occasionally we mixed the potassium into food. Eventually we worked up to doses of 1/2 teaspoon a few (usually 2) times a day.

The first SMTM author to try this lost 5 lbs over the first 10 days, and then hovered around 5 lbs down for the remainder of the four weeks. At the lowest point, they were down 8.4 lbs.

The second author to try potassium supplementation lost 6 lbs over four weeks. They found this so easy that they kept going, and ended up losing a total of 12 lbs over 60 days. Some say they’re still taking potassium to this day (they are).

Here’s the graph for that second author. Note the two gaps when they weren’t able to weigh themselves because they had social commitments — a concert (the first gap) and a fishing tournament (the second gap). 

This weight loss is modest, but surprising given that neither of these authors were very heavy to begin with. We also didn’t do anything else to try to lose weight — we weren’t sleeping more or eating better or doing more cardio. All we did was start taking some extra potassium. Honestly we are shocked. This is kind of unbelievable and we need other people to try it because we are so shocked.

Supplementing potassium, even at these low doses, felt a lot like being on the potato diet. From the start, we felt fidgety and sometimes hypomanic. 

As on the potato diet, we noticed we needed more salt (i.e. more sodium) and more water, but we didn’t always crave salt or feel thirsty, and we had to consciously eat more sodium and drink more water to avoid feeling bad. A related side-effect is that salty foods like potato chips no longer taste salty — we suspect this is because the body needs so much sodium to balance out the potassium that it has “taken the brakes off” the mechanisms that normally make you stop cramming pickles into your mouth. Even straight table salt didn’t taste overwhelmingly salty.

We eventually figured out that you can put table salt into the same glass of water as potassium salt and drink them at the same time. This helps make sure you’re getting more sodium to balance out the potassium, and it also seems to make the potassium taste less weird.

We mostly did half as much sodium salt as potassium salt, a 1:2 ratio — for example, if we were taking a dose of 1/4 tsp potassium salt in water, we would add 1/8 tsp sodium salt to the same glass. But we’re not sure what the best ratio is, and we notice that some electrolyte powders have much higher ratios. For example, LMNT contains 1000 mg sodium for every 200 mg potassium. This seems like a lot but maybe a 5:1 ratio is better, people seem to like the taste of this stuff. 

Like on the potato diet, we found our appetites diminished — what had been regular-sized meals made us feel stuffed like we had just finished Thanksgiving dinner. And just like on the potato diet, what little hunger remained was “weird” and easy to miss. 

When we did feel hungry, it didn’t feel like a “problem”, and we sometimes went too long without eating and ended up feeling like crap. Hunger usually manifested as headaches, fatigue, and mood changes, rather than the physical signs we’re used to. Again, this sounds like the potato diet. For reference, this is how some people described the experience of hunger on the potato diet: 

(And if it does work like the potato diet, then maybe be on the lookout for other weird side effects, like the intense anxiety reported by a few people.)

All this sounds a lot like the potato diet. But that in itself is kind of mysterious. People on the potato diet were getting about 10,000 mg of potassium a day. In comparison, we never supplemented more than 4,000 mg a day, and started the first day with only 660 mg. So it’s worth musing over why we lost weight on such small small doses.

One possibility is that small amounts of straight potassium salt act as a bolus dose. Potassium in food is essentially a slow-release formulation, but straight KCl in solution might be absorbed much more quickly and directly. This means that relatively small doses of potassium salts may lead to bigger spikes in blood potassium. If potassium causes weight loss by reaching a certain serum level, or by reaching the brain, a bolus may be much more effective than an extended-release formulation, which is what you would get in food. 

We were also taking a different form of potassium than is found in food. The potassium compounds found in fruits and vegetables “include potassium phosphate, sulfate, citrate, and others, but not potassium chloride.” Not to mention the fact that we were dissolving the salt into drinks, so really we were getting straight potassium ions, not compounds that needed to be digested.

And in our case, we not only took our KCl in a drink, we tended to chug it all at once. It takes like 5-10 minutes to finish a plate of potatoes; compare that to chugging 330 mg K+ in a Vitamin Water in 10 seconds flat. Even if the potatoes contain more potassium, the pure ions hitting your stomach in such a small window might make a big difference. This might also contribute to a bolus effect. 

We also tended to take our first dose early in the day, often before we had eaten our first meal. If potassium suppresses your appetite, you might get more of an effect if you take it before food. If you’re getting your potassium from food, you literally can’t take it before food. 

A final explanation is that we were somehow primed for weight loss and weird side-effects from doing potato diet self-experiments. Both authors had been self-experimenting with potato diets before trying potassium supplementation, and it’s possible that after several months of high potato intake, pure potassium has more of an effect. We don’t know enough to say anything with confidence yet. But you know, that’s why we want to do a bigger study.

Theory Viability

An important consideration when thinking about new theories is, if this were true, could we have missed it? For example, we can be pretty confident that cheese doesn’t cure cancer, because if it did, someone probably would have noticed by now (compare XKCD’s The Economic Argument). So in this case we should ask ourselves, if dietary potassium leads to weight loss, could that have really flown under the radar? What are the chances that (almost) everyone would have missed it? 

We think it’s possible. The potato diet gives an exceptionally high dose of potassium, much higher than the recommended amount and more than almost anyone is getting in their normal everyday diet. If doses in this range reduce obesity, we probably wouldn’t have noticed because people almost never consume such large amounts on a daily basis.

While there seems to be a relationship with BMI in the normal dietary range, that relationship is hard to detect. The relationship in the NHANES data isn’t even statistically significant until 2013-2014, so people have had less than ten years to notice it. The correlation in the dietary range is also quite small, only about r = 0.05. You need a sample size of 783 observations to have just 80% power to detect a correlation of 0.10, and the correlation between BMI and potassium has never been that high, at least not in the NHANES data. If you want 90% power to detect a correlation of r = 0.05, you need 4,200 observations. So aside from in the NHANES, there haven’t been many chances to notice this either.

Even when people do supplement potassium, they tend to take really tiny amounts. Potassium supplements and multivitamins pretty much always contain 99 mg potassium or less. This appears to be the result of a ruling by the FDA, which says that oral potassium chloride supplements that provide more than 99 mg potassium are unsafe because they have been associated with small-bowel lesions. (This ruling only applies to non-prescription pills; prescription potassium tablets often contain more than 100 mg.)

We can’t quite tell if the FDA has regulated that you can’t put more than 99 mg in a supplement, or if they just require you to add a warning about small-bowel lesions and all the manufacturers have decided not to risk it. The relevant ruling appears to be 21 CFR 201.306, which does not seem to be a regulatory action, but there’s also something in the Federal Register from 1992 (57 FR 18157) which we haven’t been able to find. In any case, this appears to be the origin of the practice.

We are pretty sure that limiting potassium to 99 mg does not make sense and is wrong, for several reasons. First of all, we know that people can handle doses of potassium above 99 mg in some form or another, because people get several thousand mg from their diets every day. And potassium chloride is not the only way to consume potassium. Even if potassium chloride did somehow cause small-bowel lesions, people could take potassium citrate or potassium phosphate instead.

It’s not even clear what the original ruling was based on. This page from the NIH points to this document as a reference for the ruling, but that document just lists “all solid oral dosage form drug products containing potassium chloride that supply 100 milligrams of potassium per dosage unit” under the heading “216.24 Drug products withdrawn or removed from the market for reasons of safety or effectiveness”, and doesn’t give any reason why they were withdrawn. 

The original ruling from 1975, 21 CFR 201.306, doesn’t cite any sources, and it is pretty noncommittal about the state of the evidence:

There have been several reports, published and unpublished, concerning nonspecific small-bowel lesions consisting of stenosis, with or without ulceration, associated with the administration of enteric-coated thiazides with potassium salts. These lesions may occur with enteric-coated potassium tablets alone or when they are used with nonenteric-coated thiazides, or certain other oral diuretics. … Based on a large survey of physicians and hospitals, both United States and foreign, the incidence of these lesions is low, and a causal relationship in man has not been definitely established. Available information tends to implicate enteric-coated potassium salts, although lesions of this type also occur spontaneously.

As far as we can tell, this was all prompted by a small number of articles from the 1960s. This article from 1965 reports six cases of “non-specific ulceration of the small intestine presenting as intestinal obstruction, perforation or haemorrhage” in patients taking “Hydrosaluric-K (enteric-coated hydrochlorothiazide with potassium chloride)”. 

You’ll notice that both of these sources are saying something much more specific than just “potassium bad”. This article, also from 1965, makes it pretty clear that it thinks that enteric-coated potassium supplements, specifically, are to blame:

In 1957 the first of the group of thiazide diuretics was introduced. Because increased potassium excretion is one of the pharmacological effects of these thiazides, from the beginning of their use the supplementary administration of potassium has been a common procedure for protection against the potentially serious hazard of hypokalemia. In 1959, the first of several combinations of a thiazide diuretic with potassium chloride in a single tablet was introduced; some of these combinations are enteric coated while others are not.

Since 1957 there has been a striking increase in incidence of small-bowel ulcerative lesions. Recognition that these are related to the ingestion of enteric-coated potassium chloride is due primarily to the observations of Lindholmer et al in Sweden and Baker et al in this country.

Enteric coating refers to a polymer barrier applied to a pill or supplement that keeps it from dissolving in the stomach. Pills are coated this way for various reasons, but the end result is that the drug or substance is delivered to the intestines, rather than to the stomach. The second paper here is pretty confident that delivery to the intestine, rather than the potassium salt per se, is the problem. “A new preparation is necessary,” they say, “which will not … release potassium suddenly in the small intestine permitting absorption of a high concentration of the potassium chloride.”

Even with enteric coating, these lesions appear to be pretty rare. In that first set of six case studies, the authors note that, “in view of the widespread use of enteric-coated diuretic and potassium chloride tablets, constricting ulcers of the small intestine must be a very rare complication.” They cite only 53 cases from 1963 to 1965, “in which 48 patients had been taking enteric-coated thiazide and potassium chloride tablets, three patients may have been, and two had not.”

All the original sources seem to make it clear that enteric-coated potassium tablets are the thing to watch out for, not potassium itself. This was preserved in the 1975 ruling (“nonspecific small-bowel lesions … associated with the administration of enteric-coated thiazides with potassium salts”), but somewhere along the way the message was muddled and people got confused, and started thinking any potassium pills were potentially dangerous. 

This appears to be a misconception. Though it’s not easy to find in a supplement, people regularly take prescription tablets of more than 100 mg potassium chloride and are just fine. Plain old potassium chloride seems pretty safe, and we can say that with some confidence because it’s something that has been the subject of many studies.

(Sadly none of these studies seem to have tracked body weight.)

In this hypertension study from 1985, participants were given about 2,500 mg potassium a day as “Slow-K (Ciba) eight tablets a day” for a month. They don’t report any negative events. 

In this hypertension study from 2005, participants in one arm of the study were given about 3,700 mg potassium a day as “12 Slow-K tablets”. This lasted for a week and as far as we can tell, everyone was ok — they certainly don’t mention any bowel lesions in the paper. [Edit: We missed it the first time around, but this study did track body weight. People in the trial lost an average of 0.1 kg (0.22 lbs) over 7 days on potassium citrate, and an average of 0.3 kg (0.66 lbs) over 7 days on potassium chloride. They don’t seem to report a test against baseline but it probably would not be significant because the sample size was only 14.]

These Slow-K tablets themselves are just over 300 mg potassium in a “sugar-coated (not enteric-coated) tablet”. Taking 12 of them a day for a week seems to work out just fine.

In this chronic kidney disease study from 2022, participants were given a daily dose of about 1,500 mg potassium in “two capsules, three times per day during meals”. This presumably works out to a total of six capsules a day, or about 250 mg potassium per capsule. In this group with chronic kidney disease, 11% (mostly the older participants) did develop hyperkalemia. But no one developed small-bowel lesions.  

We could keep going like this for a while — many studies give people several thousand milligrams of KCl per day, in forms that contain well over 100 mg of potassium per tablet. As long as tablets aren’t enteric-coated, and people don’t have chronic kidney disease, this turns out just fine. KCl by itself at reasonable doses is quite safe. You can literally buy sacks or jugs of potassium chloride on Amazon, mostly for use in electrolyte solutions (i.e. make your own Gatorade).

Study Design

The design of the study is simple: supplement low doses of potassium directly, and see if people lose weight. Super easy, low cost. And you’re probably not getting enough potassium to begin with. 

This design is similar to the design we used for the potato diet. The main difference is that you will be chugging potassium salt solution instead of eating potatoes, and you can keep eating normal food like usual. 

This study will run the same length as the potato diet so that the two can be compared directly — 28 days, with the final weight measurement on the morning of day 29. But we encourage people who are having a good time with the potassium to keep going and report back again at 60 days.

Supplemental Potassium

We recommend that you use Nu-Salt as the source of your potassium chloride, because that is what we tried and it worked for us. All terms and measurements below will be in Nu-Salt terms; if you use something else, make sure to convert all units to whatever form of potassium you are eating.

You can buy 3 oz shakers of Nu-Salt in various places, including on Amazon. A 3-pak should be enough to cover 28 days of potassium supplementation for most people, but if you want to share with your friends and family, or you’re confident you want to supplement potassium for longer, you can also buy a 12-pak

There are many other potassium chloride brands you could try if you want, like this Morton salt substitute (though we tried this one and found it to be *extra* gross). You could also try another potassium compound, like potassium citrate. We would prefer that most of you stick to KCl, but if a few of you tried other compounds that might be interesting, in case they end up being clearly much more or much less effective.

We’re asking participants to buy their own potassium, and we feel ok about this because potassium salt is pretty cheap, only about 80 cents per ounce. As of this writing, the 3-pak of Nu-Salt Shakers (totaling 9 oz of KCl) is only $7.48 on Amazon. But if you want to participate in this study and you really can’t afford it, contact us and we’ll send you some.

How to Consume

Potassium chloride by itself tastes pretty gross to most people, bitter and metallic all at the same time. This gang of Australian teens tasted all the alkali metal salts, and if you can get past their literally nauseating camerawork, you’ll see that they describe potassium chloride as “really bad” and “weird” and “cold on my tongue” and “it tastes like how bleach smells” and “oh god, what is it?” They still gave it a 3/10 though, which is a higher rating than they gave cesium chloride.

YouTube comments say, “The best way I can honestly describe potassium chloride is the taste of a 9v battery.”

The good news is that it doesn’t take much to mask this unpleasant taste. If you mix the potassium salt into food or beverage, it becomes much easier to handle.

We fooled around with a few approaches, but ultimately we found that it’s easiest to just dissolve the KCl in a glass of water, or Gatorade / Powerade / Vitamin Water. Often we did potassium in a mixture of half water and half one of these drinks. The flavor of 1/8 tsp KCl in a 20 oz drink is pretty understated — the water just feels “smoother”, almost like a fancy mineral water. Which it kind of is.

You can improve the taste a little more if you also add a bit of table salt (NaCl). We found that a mix of 2:1 KCl to NaCl tastes pretty ok — not too salty and not too metallic. For example, if you were putting 1/4 tsp KCl in a Gatorade, adding 1/8 tsp NaCl is a good idea to keep the potassium taste from being overwhelming. But some electrolyte powders contain higher ratios and may be more effective/taste better, so feel free to experiment with adding more (or less) NaCl. 

Adding lemon juice or sugar can also help offset the taste. As you can imagine, if you take this line of thinking to its natural conclusion you’ll end up drinking slightly salty lemonade. It’s not too bad.

We also sometimes tried putting the KCl in food. You can hide small doses in flavorful foods like beans, or in sauces, but if you overshoot at all, the food ends up tasting pretty weird.

Our most successful food discovery is that KCl goes really well with mustard. You can mix 1/4 teaspoon into a generous helping of mustard and barely taste it at all. If anything, KCl gives the mustard a tingly, almost effervescent feel.

If we were normal influencers, this is where we would start promoting DR MOLD-TIME’s KALIATED WEIGHT LOSS MUSTARD. Sadly we don’t know how to sell condiments, but hit us up if you want to do a partnership.


How to Supplement:

  • Take at least one dose per day.
  • But no more than 4 doses per day.
  • Always take doses at least an hour apart.
  • Take doses with plenty of water. It’s also recommended you take them with some table salt, or eat something salty right after. 
  • We recommend that each dose be at least 330 mg potassium (1/8 tsp Nu-Salt).
  • However, never take more than 1300 mg potassium (1/2 tsp Nu-Salt) in a single dose.
  • This means the maximum daily dose from KCl supplementation is 5200 mg, which is high but still less than you would get on the potato diet.
  • If you have to miss a few days that’s fine, just pick it back up when you can.

In the grand scheme of things, these are pretty low doses. A few hundred milligrams of potassium isn’t much, and this dosing scheme will never give you anywhere near the amounts of potassium people were getting on the potato diet. 

If this setup doesn’t cause weight loss, it’s still possible that potassium could be the active ingredient in the potato diet, and the dose on this protocol is simply too low to budge your lipostat. But, safety first, and we hold out hope that small doses may have clear effects, even if the effect of this study is smaller than the potato diet.


Now that we’ve established these basics, here’s the study protocol:

  • Start with two doses of 330 mg potassium (1/8 tsp Nu-Salt) on the first day.
  • If you feel fine, try three or four doses of 330 mg potassium (1/8 tsp Nu-Salt) on subsequent days.
  • If you’re feeling fine after 4-7 days, try one dose of 660 mg potassium (1/4 tsp Nu-Salt).
  • If you still feel good, keep increasing your dose by small increments. For example, if you are on two doses of 660 mg (1/4 tsp Nu-Salt) a day, you might increase that to three doses of 660 mg, or one dose of 660 mg and one dose of 1300 mg (1/2 tsp Nu-Salt). If a higher dose makes you feel bad, try returning to the dose you were on before and maintain that.
  • Try slowly increasing to two doses of 1300 mg (1/2 tsp Nu-Salt) a day. Only go beyond that if you are feeling totally fine. 
  • You should calibrate based on your own experience — different people will have different needs and different limits. For example, we’d expect someone who weighs 300 pounds would be able to tolerate higher doses than someone who weighs 150 pounds.
  • If you feel weird / bad / tired / brainfog and you can’t tell why, try:
    • eating something;
    • drinking some water; 
    • getting some sodium; 
    • and see if any of those help. It may be easy to end up needing food / water / salt and not notice.
    • If you still feel weird, try dropping to a lower dose or taking 1-2 days off.
  • If at any point you feel sick or have symptoms of hyperkalemia (see below), stop immediately and seek medical attention.

This is not a diet. You should continue eating as normal, and food should mostly be consumed ad libitum (eat as much as you want). But there’s one important guideline we want to note. Because potassium supplementation seems like it strongly reduces appetite in some people, you may actually need to eat more than you feel like. We strongly encourage you to make sure you get at least 1000 calories a day, preferably more.

It’s fine to take breaks in the middle or even stop the trial early. But if you sign up, please record 4 weeks of data even if you stop taking potassium at some point, have to end early, have to take a break in the middle, or can’t stand taking KCl for the full 4 weeks. If you do it for two days and hate it, please keep recording your weight and potassium consumption (which would just be zero from then on) for the full 29 days and submit your data as normal. We can still use it!

Our hope is that this will keep us from running into the dropout issues we had in the potato diet. Anyone who records data for 29 days is clearly taking the study seriously, even if they weren’t able to stick to the potassium supplements the whole time.

Based on this, our main analysis will focus on participants who provide 4 weeks of data. If you provide a weight measurement for the morning of day 1 and the morning of day 29, so we can calculate your weight before and after, and you took at least one dose of potassium, we will do our best to include you in the analysis.


Speaking of which, here are the variables we want you to track. 

The main outcome of interest is your weight, taken every morning, after your first “void”, assuming you void in the morning. 

We also want you to track your potassium supplementation. We’ve provided four fields per day for potassium doses and notes, since we ask that you take no more than four doses per day.

There’s a possibility that potassium causes weight loss by protecting you from lithium, and there’s a chance that certain foods are especially high in lithium. We aren’t confident enough about this to ask you to avoid these foods, but we do want to ask you to track how much you’re eating them. We’ve provided fields for meat, eggs, dairy, leafy greens, and tomato products, all of which are currently top lithium candidates. If you eat more than a smidge (by your own judgment) of any of these foods, please put a “1” in that field for that day. If not, put a “0”. 

This way, we can see if any of these foods seem to inhibit potassium weight loss. Relatedly, if you’re supplementing potassium and not seeing any weight loss, you could always try cutting back on the cream and ketchup.

We’ve also included fields for several BONUS VARIABLES. You don’t have to track these, but if you do, the standardized fields will let us analyze these results across participants. In particular, we’d be interested in having data for your blood pressure, sodium intake, and energy/mood, but we’ve included several more fields for variables people might want to track. There’s also a field for tracking waist circumference, which a couple people asked for after the potato diet. 

We also included fields for up to 10 extra variables of your choosing. If you want to record anything else, please put it here. This way you can add more variables without changing the format of the data sheet, which would make it harder to analyze your data. So please don’t touch the formatting, but feel free to add variables in the extra variables area.

And speaking of other variables — Michael Dubrovsky of SiPhox reached out to us to offer a discount to participants who want to test their blood biomarkers with SiPhox’s at-home Quantify kits. We haven’t had a chance to try these kits, but if you’re interested check it out. You can get a two-kit bundle (so you can do one test before the trial and one after) for 40% off at this link.

That’s the gist. Before you sign up, however, we insist you read this section on safety: 


Do not participate if you have diabetes or any kind of impaired kidney function. 

For everyone else, this level of potassium supplementation should be very safe.

Until recently, it was recommended that adults get 4,700 mg of potassium per day in their diet. Most people seem to get less than this, so supplementing is probably a good idea anyways. 

Going over 4,700 mg of potassium a day is also very safe. Most people in the NHANES data got less than the recommended amount, but a small number were estimated to get over 10,000 mg in their diet. The potato diet also seems to indicate that you can take a lot of potassium and not get sick. As a reminder, 2000 calories of potatoes gives you more than 10,000 mg of potassium.  

In addition to recommended allowances, the National Academy of Medicine also sets tolerable upper intake levels (ULs) for vitamins and minerals. But normal doses of dietary potassium are so safe that no upper level has been set, for lack of information. This chapter from the National Academy says, “Although dietary potassium intake can be increased through behavioral change, there is a self-limiting aspect to such changes that makes toxic adverse effects from increases in dietary potassium intake unlikely.”

This study focuses on potassium chloride specifically, which is quite safe. It’s sold as a salt substitute and electrolyte powder — you can buy it in bulk on Amazon. Studies of hypertension sometimes prescribe as much as 3,700 mg potassium a day as potassium chloride, without any apparent ill effects. 

The toxicity of potassium chloride is low. The LD50 for potassium chloride taken orally is around 2,500 mg per kilogram of bodyweight. If you weigh 165 lbs, you would start to be in danger at doses of around 190,000 mg.

Like any substance, very large doses can be dangerous. The main danger is unsurprising — hyperkalemia, which is the condition of having too much potassium in your blood. But to get there, you have to A) take a lot of potassium, B) have kidney problems, or C) both.

The National Academy summarizes the few case studies that are known. The first is from 1978, a 32-year-old woman who died after ingesting an estimated 47 extended-release potassium chloride tablets. 

The second is from 2014, a report of a 26-year-old man who died after consuming an estimated 12,500 mg of potassium, in the form of extended-release potassium chloride tablets. However, “there was also co-ingestion of dextropropoxyphene-acetaminophen in this case, which complicates the interpretation.”

These are the only deaths they report (“death is a particularly severe endpoint to use to establish a UL”), but they review two other case studies as well. One is a case report of a 17-year-old man who developed nausea, vomiting, and diarrhea after consuming around 10,000 mg of potassium as sustained-release potassium chloride tablets.

Another describes a 67-year-old man with kidney injury who had a heart attack after consuming around 2,730 mg per day of potassium from a salt substitute for one week. He also “reportedly consumed a high-potassium diet, in addition to the salt substitute.” They note that, “the amount reportedly consumed from the salt substitute is a level of intake that has been repeatedly studied in potassium supplement trials, wherein the risk of adverse events appears to be low among generally healthy populations.” We agree — 2,730 mg per day seems very safe if you are not a 67-year-old man with a kidney injury. 

The worst-case scenario in this study is that you develop hyperkalemia. If you have healthy kidneys, this shouldn’t happen. But just in case, here are the signs and symptoms.

Symptoms of mild hyperkalemia include muscle weakness, numbness, tingling, and nausea. These could also indicate that you’re not getting enough food, water, or sodium. If you start feeling these symptoms, try eating, drinking some water, or having some table salt or salty food. If the symptoms persist or get worse, consider ending the study or at least taking a break. 

Symptoms of severe hyperkalemia include abnormal heart rhythm, heart palpitations, shortness of breath, chest pain, sudden nausea, and vomiting. If you have any of these symptoms, end the study immediately and seek medical attention. If you have an existing reason you might experience one of these symptoms (you already sometimes have heart palpitations or get nauseous suddenly), do not sign up for this study, since if you had symptoms of hyperkalemia, you wouldn’t be able to tell. 

Sign Up

Ok, now you can sign up.

The only prerequisites for signing up are: 

  • You must be 18 or older;
  • In generally good health and specifically with no kidney problems;
  • Willing to supplement potassium, as described above, for at least four weeks, and;
  • Willing to share your data with us.

Also, we’d prefer that you don’t sign up for this study if you were already a participant in the potato diet study. We’d love to have your help again, it’s just that if you lose even more weight on potassium, that will mess up the 6-month weight-loss followup numbers for the potato diet. Those of you who have tried the potato diet but weren’t officially part of our study can still sign up.

As usual, you can sign up to lose weight, lower your blood pressure, get more energy, or see one of the other potential effects. But you can also sign up to help advance the state of nutritional science. This study will tell us something about nutrition, by either supporting the idea that potassium is the reason the potato diet causes weight loss, or providing evidence against it. 

Beyond that, running a study like this through volunteers on the internet is a small step towards making science faster, smarter, and more democratic. As always, that seems like a future worth dreaming of, and if you sign up, you get us closer to that future.

Potassium salt is a little gross, so you might be wondering if you really want to commit to this for several weeks. But 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 you hate it and have to stop, we would still love to have that data.

If you want to go for longer than four weeks, that’s great, we would be happy to have more data. Report your data at four weeks like normal and then just keep going, and if you make it to 60 days, send us an update.

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.

We are mostly interested in weight loss effects for people who are overweight (BMI 25+) or obese (BMI 30+), but if you are “normal weight” (BMI 20-25) you can also sign up. The potato diet caused weight loss in people of normal weight, and it would be interesting to see if the same thing happens here. 

And for everyone, please consult with your doctor before trying this or any other weight loss regimen. 

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 studies in the future. If you’re interested in participating in a future 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. Start with two doses of 330 mg potassium (1/8 tsp Nu-Salt) on the first day. On day 2, weigh yourself in the morning, note down data in the sheet, then take at least two doses of 330 mg potassium (1/8 tsp Nu-Salt). On day 3, etc. See the dosing protocol above for details.
  4. We prefer that you keep taking at least one dose of potassium a day for at least four weeks. But if you do have to miss some days, or need to take a break, just note that down and keep recording other variables. If you totally can’t stand the potassium, just stop taking it, keep recording other variables until day 29, and submit your data as normal, we can still use it.
  5. When you reach four weeks, and take your weight measurement on the morning of day 29, send us an email with the subject line “[SUBJECT ID] Potassium Trial Complete”. This will let us know to go grab your data. This is also your opportunity to tell us all about how the study went for you. Please tell us any data that doesn’t easily fit into the spreadsheet — how you felt, what kind of potassium you used, before and after pictures (if you want), advice to other people trying this, etc. 
  6. You may reach day 29 and decide to keep going longer. That’s fine. Send us an email on day 29, and if you reach 60 days, send us another email and we will grab your data again. If we get enough data we might do an analysis of this longer span as well. If you go past 60 days and want to share it with us at some point, that’s cool too.
  7. If we have our act together, we will send each of you a brief google form following up at future points.

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!

Special thanks to Austin Vernon for helping us automate parts of the signup process.

Behind the Scenes: Lithium Removal with Household Water Purification Devices

Lithium is an element, atomic number 3. It is a soft, light, highly reactive metal with a variety of uses. Among other things, it’s often found as a trace mineral in drinking water. Small amounts of lithium are naturally present in many water sources, but levels of lithium in American drinking water have been increasing for the past 60 years.

In 1964, the US Department of the Interior published a report called Public water supplies of the 100 largest cities in the United States, which found a median lithium concentration of only 2.0 µg/L in US drinking water. The highest level they recorded was 170 µg/L. 

In 2021, the USGS released a report that found a median level in US groundwater of 6.9 µg/L. This is almost four times the median level in the 1960s, but looking at nothing but the average obscures the fact that many people are getting exposed to even more. For comparison, the maximum level they found in groundwater was 1700 µg/L, ten times the maximum recorded in 1964. 

The USGS also found that about 45% of public-supply wells and about 37% of domestic-supply wells contain concentrations of lithium “that could present a potential human-health risk per the current EPA guidelines”. Here’s how they describe it in the paper:

Lithium concentrations in untreated groundwater from 1464 public-supply wells and 1676 domestic-supply wells distributed across 33 principal aquifers in the United States were evaluated for spatial variations and possible explanatory factors. Concentrations nationwide ranged from <1 to 396 μg/L (median of 8.1) for public supply wells and <1 to 1700 μg/L (median of 6 μg/L) for domestic supply wells. For context, lithium concentrations were compared to a Health Based Screening Level (HBSL, 10 μg/L) and a drinking-water only threshold (60 μg/L). These thresholds were exceeded in 45% and 9% of samples from public-supply wells and in 37% and 6% from domestic-supply wells, respectively.

Levels in drinking water seem to have increased due to a number of related factors, including the use of drilled wells to tap deeper aquifers, higher levels of fossil fuel prospecting and pollution, and the fact that worldwide lithium extraction and use in industrial applications has increased in general, multiplying the opportunities for accidental exposure and pollution. 

Lithium is not currently regulated in drinking water, and water quality reports don’t regularly include it. Most water treatment plants do not track lithium or attempt to reduce it. But the EPA and other government agencies are becoming more concerned about lithium exposure, even at the trace levels found in drinking water: 

Just this January, lithium was added to the EPA’s proposed Unregulated Contaminant Monitoring Rule. The Rule is used by the EPA to collect data for contaminants that are suspected to be present in drinking water and that do not have health-based standards set under the Safe Drinking Water Act.

Although useful for treating mental health disorders, pharmaceutical use of lithium at all therapeutic dosages can cause adverse health effects—primarily impaired thyroid and kidney function. Presently lithium is not regulated in drinking water in the U.S. The USGS, in collaboration with the EPA, calculated a nonregulatory Health-Based Screening Level (HBSL) for drinking water of 10 micrograms per liter (µg/L) or parts per billion to provide context for evaluating lithium concentrations in groundwater. A second “drinking-water-only” lithium benchmark of 60 µg/L can be used when it is assumed that the only source of lithium exposure is from drinking water (other sources of lithium include eggs, dairy products, and beverages such as soft drinks and beer); this higher benchmark was exceeded in 9% of samples from public-supply wells and in 6% of samples from domestic-supply wells.

Lithium is well-known to have psychoactive effects, which is why lithium salts are often prescribed as a psychiatric medication. In particular, lithium tends to make people less manic and less suicidal. Less charitably, it is sometimes described as a sedative. 

But these effects may not always require psychiatric doses. A long-running literature of epidemiological research (meta-analysis, meta-analysis, meta-analysis) suggests that long-term exposure to trace levels of lithium commonly found in drinking water can also have psychiatric effects. Specifically, trace levels in drinking water are often found to be associated with decreased crime, reduced suicide rates, and/or decreased mental hospital admissions. 

Finally, here at Slime Mold Time Mold we suspect that lithium exposure may contribute to the obesity epidemic. Lithium often causes weight gain at psychiatric doses, and while there’s no smoking gun yet, there’s some evidence that there might be a connection between long-term trace lithium exposure and obesity. People who are exposed to more lithium, especially at their jobs, tend to be more overweight. Cities with higher rates of obesity tend to have more exposure to lithium. And a group of Native Americans (the Pima) who had unusually high levels of lithium in their water also had unusually high levels of obesity, all the way back in the 1970s. Food levels may also be a possible vector (though it’s complicated).

So people often ask us, how can I get lithium out of my tap water? 

For a long time, we weren’t able to answer this question. Until very recently, no one was concerned about lithium levels in drinking water, so there isn’t much research on how to get it out. Heck, back in 2014 the NYT ran an opinion piece arguing that maybe we should start putting lithium in our drinking water. How times have changed.

This is further complicated by the fact that lithium is pretty weird. At an atomic number of only 3, it is the third-lightest and third-smallest element. In some ways it is more like the gasses hydrogen and helium than it is like the metals iron, lead, or mercury, which are much larger and much heavier. This makes it hard to predict whether techniques that can remove other metals would also remove lithium, which is present in solution as an especially tiny ion. 

(A favorite “Whoaahhh” fact about Li+ is that it is so small, a bit of electrical energy can make it can creep into the crystal lattices of other compounds and basically just hang out there indefinitely, usually with a bit of swelling of the “host” crystal. It’s kind of like pouring sand into a jar of marbles — lithium is so tiny it can sneak into very small spaces, which is virtually impossible with any other metal ion. The technical term is that it “intercalates” into these materials. Lithium intercalating back and forth between cobalt oxide and graphite, for instance, is the basis of the lithium ion batteries that power virtually every phone and laptop and electric vehicle. There’s an entire field of research focused on making lithium creep into and out of various materials to store energy. People have been trying for a long time to make Na+ do this, since Na+ is so much cheaper and more abundant than Li+, but it’s still way too hard to make any kind of useful battery with an ion as big as Na+.)

To answer the question of how to get lithium out of your drinking water, we set up a project with research nonprofit Whylome to test several commercially-available water filters, the kinds of things you might actually buy for your home, and see how good they are at removing lithium. It’s taken a couple of months of planning, testing, and analysis, but those results are finally ready to share with the world.

This project was funded by generous donations to Whylome from individuals who have asked to remain anonymous. Further support for the research was provided by The Tiny Foundation, which allowed us to expedite several aspects of the research. Special thanks to our funders, Sarah C. Jantzi at the Plasma Chemistry Laboratory at the Center for Applied Isotope Studies UGA for analytical support, and to Whylome for providing general support. 

The full report is here, the raw data are here, and the analysis script is here. Those documents give all the technical details. For a more narrative look, read on. 


  1. Methods
  2. Results
  3. Complications
  4. Conclusions

1. Methods

The basic idea of the study is pretty simple.

You buy a bunch of normal water filtration devices (henceforth “filters”, even though they’re technically not all filters) from a store, like Home Depot, or online, from places like Amazon. Or online from Home Depot.

You spike large quantities of water with specific amounts of lithium, to get water containing known levels of lithium.

Then, you run the lithium-spiked water through the filters and take samples of the water that comes out the other end. 

Finally, you submit that water to chemical analysis and find out how much lithium was removed by each of the filters. 

This is basically the perfect garage experiment — except that in this case, filters were tested in the laundry room, not in a garage.

1.1 Water Filtration Devices

To get a sense of the different options available on the market, we elected to test three different types of devices: carbon filters (which are what most people think of when they think of at-home filters); reverse osmosis devices; and electric water distillation stills. 

We chose devices from brands that most people have heard of, and models that people tend to buy. If you click through the links below, you’ll see that many of these devices are best-sellers.

We settled on the following mix of carbon filters: two pitchers, the Brita UltraMax Filtered Water 18-Cup Pitcher and the PUR Ultimate Filtration Water Filter Pitcher, 7 Cup; three on-tap systems, the Brita 7540545 On Tap Faucet Water Filter, the PUR PLUS Faucet Mount PFM350V, and the Culligan Faucet Mount FM-15A; and two under-sink systems, the Waterdrop 15UA and the Brondell Coral UC300.

We settled on two reverse osmosis devices, the GE GXRQ18NBN Reverse Osmosis Filtration System and the APEC ROES-50 5-stage Reverse Osmosis System.

We also tested two distillation machines, the Megahome 580W Countertop Water Distiller and the Vevor 750W Water Distiller

Devices were purchased off of Amazon, from the Home Depot, or from their manufacturer, depending on availability. For each device, we also purchased as many extra filters as needed, so that each test could start with clean filters (see the report for more detail).

Carbon Filters — We came into this pretty confident that carbon filters would perform very poorly for lithium removal, despite some nonsense to the contrary floating around the internet (for example, here and here). Carbon has a low affinity for Li+, so we didn’t expect it would pull very much out of the water. Carbon can remove some metals, like lead, by ion exchange — the same principle used in water softeners. But the metals it is good at removing are multivalent (having a charge of +2 or +3 or +4), not +1 like Li+.

Carbon is also known for having noticeable variation between individual filters, because the carbon in question is made from plant material (often coconut). There will be minor variations in the carbon properties between batches, depending on how fast the coconuts were growing that month and minutiae like that. So we went into this expecting that there might be some differences between different filters, even within the same brand and/or model. 

Since we expected that carbon filters would probably all suck based on the mechanism of action, and because we expected that there might be noticeable variation, we decided to test several different brands of carbon filters, in multiple configurations (pitcher, on-tap, and under-sink). This is why we tested so many devices and why we got a relatively wide mix of brands and configurations.

This way, if carbon filters are all equally ineffective, it should be very obvious. But if we’re wrong and they’re great, or some are much better than others, we have a good chance of noticing. Carbon filters are also the cheapest and most commonly used filters, another reason to test more of them.

We expected less variation in the other two kinds of devices, so we decided to test two models of each. 

Distillation — We expected that distillation machines would work well, but we didn’t know if that was 80% well, 90% well, or 99.9% well. Lithium salts have zero volatility, so when water evaporates and condenses, the lithium should be left behind. The main risk is that droplets of liquid could get caught in the condenser, which could result in some of the original liquid getting into the clean distillate. So a well-designed distillation machine should perform well, but we didn’t know how reliable or well-designed small at-home countertop models would be.

Reverse Osmosis — We were the most uncertain about reverse osmosis. Reverse osmosis is very good at removing divalent metal ions (like Ca2+ and Mg2+), and pretty effective at removing monovalent metal ions from tap water (like Na+ and K+), but it wasn’t clear if this pattern would extend to lithium. In some ways Na and K are very similar to lithium — all three are present in water as single-charge positive ions, and all three are the same chemical group, the alkali metals. But lithium is much smaller and lighter than other elements. Na has an atomic number of 11, and K has an atomic number of 19, while Li has an atomic number of only 3. 

As a result, we weren’t sure if reverse osmosis would be anywhere near as effective at removing lithium as it is at removing these other contaminants. Maybe reverse osmosis would pull lithium out of the water just like any other ion. Maybe it would miss lithium entirely, because the ion is so small. Or maybe something in between. So we went into this expecting that reverse osmosis might be anywhere from 0% to 100% effective. 

1.2 Lithium Spiked Water

For realism, we worked with actual American tap water. In this case, we used tap water from the town of Golden, Colorado. Despite the fact that it was indeed part of the Colorado Gold Rush, Golden, CO is not named after the gold rush or even after gold itself; it is named after some guy named Tom Golden.

Samples of the tap water were spiked with known quantities of “ultra dry” lithium chloride salt to create spiked water samples of known lithium concentration.

We ended up testing four concentrations of lithium: 40, 110, 170, and 1500 µg/L Li+. This covers a range from “starts to be concerning” to “around the highest levels reported in US drinking water”. There’s also a bit more history to these numbers, but we’ll talk about that below. 

1.3 Testing 

Each filter was tested at each concentration, and at two timepoints (realistically these are “volumepoints”, but that’s not really a word). The carbon filters and the RO devices were each tested after 10 liters and after 20 liters. The distillation machines were tested at 2 liters and again at 4 liters, since they take a really long time to run. 

The testing setup looked roughly like this: 

1.4 Analysis

At the start of the project, we sent the same samples to a couple different testing labs, so we could shop around and compare. All the labs we tried were pretty reliable, but the Plasma Chemistry Laboratory at the Center for Applied Isotope Studies, University of Georgia stood out as the best, so we sent all subsequent samples to them. 

Analysis was performed by ICP-OES. The instrument used was a Perkin Elmer 8300 ICP-OES, and the limit of detection was 1 µg/L. All analyses were done in triplicate and were submitted in a random order.


2. Results

The following figure gives an overview of the results. This figure only includes performance at a concentration of 110 µg/L after the first timepoint (2L for distillation, 10L for the others) but the same general pattern holds across pretty much everything: 

2.1 Carbon Filters

Carbon filters are lousy at removing lithium, but probably not 0% effective. Most of the time, water contained slightly less lithium coming out of the filter than it did going in. But the carbon filters didn’t do much, and there wasn’t a huge amount of variation between them.

2.2 Reverse Osmosis

Reverse osmosis was shockingly good at removing lithium. Removal was reliably high for all systems, more than 80% for the GE system and consistently above 95% for the APEC system. The result is unequivocal: reverse osmosis works. Reverse osmosis does not, however, drive these concentrations close to zero. RO is good, but if you start with 100 µg/L in your tap water, you might still end up drinking 10 µg/L even after filtration. 

In many cases you do end up with less than 10 µg/L after filtration, but if you start with a high concentration, you are still generally getting more lithium than was in the median American water source in 1964 (2 µg/L). The lower your starting lithium, the lower the lithium concentration you are getting out of your RO filter.

2.3 Distillation

Finally, distillation machines are nearly perfect at removing lithium. Lithium levels after distillation were undetectable (<1 µg/L) in most cases, and removal was still >99.5% for the highest concentration (1500 µg/L). Distillation reliably drives any levels you would expect to see in American tap water below the level of detection. 

2.4 Long-Term Reverse Osmosis Test

We also decided to do one long-term test of a single system, to check if it kept performing well over a longer period of time, and to see if anything weird happened. We expected that systems would get slightly worse over time, but there might also be a discontinuity, where a system keeps doing well for a while and then suddenly craps out and does much worse. We wanted to see how much decline happened with more use, and check if there was any discontinuity or sudden point of failure. 

Carbon filters don’t work very well even straight out of the box, so obviously we didn’t test one of those. RO doesn’t remove lithium from water quite as well as distillation, but it’s faster, cheaper, and much easier to install. Because RO sits at this sweet spot, we decided to test the GE RO device up to 100 liters. 

We tested the GE RO device against a concentration of 170 µg/L, and the device continued to do a good job removing lithium even up to 100 L. Performance went down slightly over time, but not enormously. At 10 L, the device removed about 98% of the lithium in the water, and by 100 L, it removed about 89%. We don’t know how well it would perform beyond 100 L, but this finding suggests it would keep doing pretty well but progressively worse over time. 

This would be a good topic for further study — run a few RO devices to 1000 L and see what happens. Alternately, you could install a RO device in the home of someone whose tap water is already high in lithium, test its effectiveness once a month, and get a sense of how these devices would perform in a real-world scenario. 

3. Complications

The conclusions from this study are, fortunately, pretty straightforward. But on the way to those conclusions, there were a few complications.

3.1 PUR Pitcher

In addition to the six carbon filters mentioned above, we also tested the “PUR Ultimate Filtration 7-Cup Pitcher”. When we ran it through the same procedure as the other filters, we found there was more lithium in the filtered water than in the original water, at all concentrations. Basically it seemed like the PUR pitcher was adding lithium to the water instead of taking it away. 

This was confusing and seemed like it might be wrong, so we tried the same pitcher again with a different set of filters. This time we didn’t get the weird result — lithium levels went down when we ran water through the filter, just like normal. 

We’re not totally sure why this happened. One possibility is that some of the water evaporated during testing, but letting the water sit for a few days didn’t make a substantial difference compared to filtering rapidly, so this appears unlikely. Another possibility is that there’s meaningful batch-to-batch variation in the lithium content of the filter cartridges. Activated carbon comes from plants (usually coconuts), so conceivably there could be more lithium in some coconuts than in others. If you got unlucky, the carbon might contain a lot of lithium and you would end up adding lithium to the water instead of taking it away. 

In any case, this was strange and inconclusive enough that we ended up removing it from the main analysis, but we’re reporting it here just in case. Good cautionary tale about how even a simple measurement is never simple. 

3.2 Concentration Complication

We originally planned to test lithium concentrations of 10, 60, 100, and 1000 µg/L.

The reasoning was that 10 and 60 µg/L were the EPA thresholds of interest, and that testing 100 and 1000 µg/L covered two further orders of magnitude while still being realistic — according to the USGS, 4% of groundwater wells in the US contain more than 100 µg/L lithium, and the maximum recorded contained 1700 µg/L.

But two things happened to screw that up. 

First, the tap water in Golden gave us a bit of a surprise. Golden is a city in Colorado, and most tap water in Colorado comes from dazzlingly clean snowmelt. Snowmelt should contain almost no lithium (it’s basically been distilled), so we expected that the tap water in Golden would also contain almost no lithium. This assumption was backed up by water quality reports from nearby Denver, CO, which find no lithium in Denver’s water. 

But to our surprise, when we started testing samples, we found that they contained more lithium than we spiked them with. We circled back and tested the unspiked tap water, and found that it contained around 20-25 µg/L, an amount that was reliable across several months. If there are seasonal changes, our January-March sampling window wasn’t big enough to detect them.

The local water treatment plant is fed by Clear Creek, so we collected and tested a sample from the creek about 2 miles upstream from the water treatment plant. The creek there has a concentration of 27 µg/L, very similar to the tap water. It appears that water enters the Golden, CO treatment plant at around 25 µg/L, and the treatment process has very little impact on lithium concentration.

At this point we were questioning our assumptions about water sources, so we collected some local snow and tested that too. The snowmelt had barely detectable lithium, less than or equal to 1 µg/L. This confirms our earlier belief that precipitation is generally very low in lithium (at least in Golden, CO).

If it’s not in the snowmelt, the lithium must be coming from somewhere else. This is speculation, but the Clear Creek watershed does include many abandoned mines, some dating way back to the early gold and silver rushes from the 1800s, and there is at least one Superfund site, so old mine tailings are one possibility (see in particular here). One of the towns upstream (Idaho Springs) has natural hot springs with some geothermal activity, so another possibility is that these springs add lithium to Clear Creek along the way. We didn’t find an obvious link for Idaho Springs, but other hot springs in Colorado definitely brag about the lithium content of their water (Denver Post on Orvis Hot Springs: “The resort’s seven pools are laden with lithium…”), so this seems quite plausible.

This suggests that our original assumptions were mostly correct — snowmelt contains little to no lithium, so most drinking water in Colorado should be quite pure. But in this specific case, looking at water drawn from Clear Creek, we ended up with more than we expected. Water coming from one of Colorado’s snowmelt reservoirs, rather from a well or stream, would probably contain a lot less.

In the end, the lithium levels in Golden’s tap water raised the lithium level of all of our samples by about 25 µg/L. We were already halfway through testing when we discovered this, so we decided to continue with these slightly higher concentrations. If anything, it’s a stricter test of the filters.

Clear Creek, circa 1868

Second, the lithium salt we used was substantially more potent than the stated strength (i.e. much stronger than expected), which also increased the concentrations we tested. 

We used lithium chloride from Fisher Scientific as the lithium spike for all our samples. According to the certificate of analysis, the salt contained a lot of water. But apparently this was not the case. As far as we can tell, the salt appears to have very little water content, so it contains a lot more lithium per weight than expected (about 30% stronger than expected). This caused us to underestimate the amount of lithium in the salt, and as a result, we added more than we meant to. This is why we ended up testing up to 1500 µg/L.

Again, we were already halfway through testing when we discovered this, and decided to forge ahead. Because this error was propagated across all the samples we had submitted, the analysis was still internally consistent. Even though these weren’t the numbers we had set out to study, it doesn’t really matter. Those numbers were arbitrary to begin with; we chose them because we live in a base-10 world. We were still able to compare between filters at realistic concentrations.  

Together, these two factors inflated the concentrations we tested, from 10, 60, 100, and 1000 µg/L to 40, 110, 170, and 1500 µg/L. First, the tap water from Golden added 25 µg/L to all the samples. Then, the unusually dry lithium salt inflated the amount added to each sample by around 30%.

Fortunately, this does not seriously impact our results. Filters were consistent across all concentrations, and in the end we covered a very similar range, 60-1500 µg/L instead of 10-1000 µg/L. We’re only really missing an analysis of how well the filters would work at low levels, around 10 µg/L. But RO devices that drive 40 µg/L to around 1 µg/L can also be expected to drive 10 µg/L way down low.

The only thing we would want to revisit in future studies is to test carbon filters at levels close to 10 µg/L; but our best bet is that they don’t do much at those levels either.

3.3 Doubles

We also caught one other problem. During analysis, we found that we made a mistake when mixing four of the concentrations. Twice as much lithium chloride as intended was added to the solutions for the PUR faucet mount at concentrations of 110 and 170 µg/L, and also for the Culligan faucet mount at 110 and 170 µg/L. As a result, these two filters were actually tested against ~210 µg/L and ~325 µg/L instead of the intended 110 and 170 µg/L. You can easily see this error if you look at the tables in the report. 

This is unfortunate and does complicate the data, but again it doesn’t seriously change the conclusions. Carbon filters don’t get much lithium out of tap water at any concentration, whether it’s 110, 170, 210, or 325 µg/L. There’s no reason to expect that the PUR and Cullighan faucet mounts would perform differently at these concentrations than at the intended ones — these results fit the overall result, which is that carbon filters aren’t good at removing lithium. 

3.4 Why’d You Have To Go And Make Things So Complicated? 

You may not be used to seeing scientific papers talk about mistakes the research team made, or the incorrect assumptions that showed up halfway through the project, or the weird random anomaly that doesn’t have an easy explanation. But the truth is that this is just what research looks like.

Academic researchers are expected to pretend like everything went perfectly and nothing weird happened, but this is not how actual research projects work. In real projects, especially where you’re trying to advance the frontiers of knowledge, you have to take chances, make mistakes, and yes, even get messy.

There are always going to be some accidents in any research project, and instead of sweeping them under the rug and pretending we never make mistakes, we’re going to talk about them. This not only is virtuous, it also puts you (readers) in a better position to form your own opinion about our results. It gives you a better sense of what to expect if you want to replicate or extend our results. And if we didn’t tell you about all the SNAFUs, we’d be giving you the wrong idea about what research is really like. 

And of course, it’s possible there are other mistakes we haven’t caught yet! We know that the best way to troubleshoot is to get as many eyes on the project as possible, which is why we put all our data and code online for you to see.

Obviously we want to avoid mistakes when we can, which is why we use techniques like randomizing sample order and including control samples to help prevent and diagnose mistakes. But this sort of thing happens, and it’s in everyone’s best interest to just publicly say “whoops, our bad”.

4. Conclusions

If you have the time and money, distillation is the best way to get lithium out of your water. The catch is that distillation is slow: distillation machines usually run at less than 1 liter per hour, a small fraction of the speed of other devices, and consume a lot of energy to get there. Distilling all of your cooking and drinking water with one of these machines would be very slow or very expensive or both.

For the average consumer, reverse osmosis is a much better choice. It’s cheaper and faster, and it works nearly as well as distillation does. For the average American, a RO system will ensure that you end up with less than 10 µg/L in your water, probably much less. 

Both of the RO systems we tested were under-sink units, meaning they go under your sink (duh) and create a stream of purified water that is separate from the actual tap. That way you wash your dishes with the high flow rate you’re accustomed to from a faucet, but fill your glass or make pasta with the separate stream of RO-filtered water.

You could also spring for a professional-grade household system that filters all the water that comes into your house, but there are a few complications. First off, while it should work basically the same as these under-sink units, we didn’t actually test a household system. Second, it’s got a much higher upfront cost and it would be more of a pain to install and maintain. Also keep in mind that typically only 20-50% of the water entering the RO unit actually leaves as clean, filtered water; the rest never makes it through the filter membrane and goes down the drain. Throwing away that much water for things like showering or washing your car would mean a lot of wasted water.

Finally, a whole-house RO system typically needs to be accompanied by a water softener, and we’re not sure if water softeners contain lithium or not. Water softeners operate by ion exchange, exchanging one Ca2+ or Mg2+ ion for two Na+ ions. You “regenerate” the system every so often by dumping a big bag of rock salt (NaCl or occasionally KCl) into the “brine tank”, which displaces the Ca/Mg off of the ion exchanger. If the salt being used for regeneration contains lithium, it would make its way into the drinking water just as readily as Na+. We haven’t tested any water-softening salt yet (though we might at some point), but we did test table salt as part of another project, and that definitely contains some lithium. 

Because of this, it’s not clear whether you’d end up drinking more or less lithium if you install a household RO system with a water softener. If you’re using a water softener without a RO system, you’re probably adding some lithium to your water, though we’re not sure how much. 

If you purchase water that was treated by RO or distillation (as many bottled waters are), it’s probably very low in lithium. But the catch here is that many companies put minerals back in, because pure water actually tastes kind of flat and metallic. Aquafina, for example, is first purified through RO before putting a pinch of salt back in for taste. If the pinch of salt contains lithium, you’re back to square one.

Thanks again to our anonymous donors, the Tiny Foundation, Sarah Jantzi, and Whylome for supporting this research. Finally, thank you for reading!

On the Hunt for Ginormous Effect Sizes

A few people have asked us why we didn’t preregister the analysis for our potato diet study. We think this shows a certain kind of confusion about what preregistration is for, what science is all about, and why we ran the potato diet in the first place. 

The early ancestor of preregistration was registration in medical trials, which was introduced to account for publication bias. People worried that if a medical study on a new treatment found that the treatment didn’t work, the results would get memory-holed (and they were probably right). Their fix was to make a registry of medical studies so people could tell which studies got finished as planned and which ones were MIA. In this sense, our original post announcing the potato diet was a registration, because it would have been obvious if we never posted a followup. 

Pre-registration as we know it today was invented in response to the replication crisis. Starting around 2011, psychologists started noticing that big papers in their field didn’t replicate, and these uncomfortable observations slowly snowballed into a full-blown crisis (hence “replication crisis”). 

Researchers began to rally around a number of ideas for reform, and one of the most popular proposals was preregistration. At the time, many people saw preregistration as a way to save the foundering ship that was psychological science (and all the other ships that looked like they were about to spring a leak). 

Calls for preregistration can be found as early as 2013, in places like this open letter to The Guardian, and on the OSF, where people were already talking about encouraging the use of preregistration with snazzy badges like this one: 

But despite the early enthusiasm, preregistration is not a universal fix. It has a small number of use cases and those cases are specific. Part of being a good statistician is knowing how to preregister a study and knowing when preregistration applies, and it doesn’t apply all that broadly. We think preregistration has two specific benefits — one to the research team, and one to the audience. 

We’ve preregistered studies before, and in our experience, the biggest benefit for researchers is that preregistration encourages you to plan out your analysis in advance. When you do a study without thinking far enough ahead, you sometimes get the data back and you’re like oh shit how do I do this, I wish I had designed the study differently. But by then it’s too late. Preregistration helps with this problem because you have to lay out your whole plan beforehand, which helps you make sure you aren’t missing something obvious. This is pretty handy for the research team because it helps them avoid embarrassing themselves, but it doesn’t mean much for the reader.

The main benefit the audience gets from preregistration is that preregistration makes it clear which analyses were “confirmatory” and which were “exploratory”. Some analyses you plan to do all along (“confirmatory”; no it doesn’t make any sense to us either), and some you only do when you see the data and you’re like, what is this thing here (“exploratory”; you are Vasco da Gama). 

exploratory analyses

This is ok by itself because it does sort of help against p-hacking, which is one of the big causes of the replication crisis. When you do a project, you can analyze the data many different ways, and some of these analyses will look better than others. If you do enough analyses, you’re pretty much guaranteed to find some that look pretty good. This is the logic behind p-hacking, and preregistration makes it harder to p-hack because you theoretically have to tell people what analyses you planned to do from the get-go.

(This only works against p-hacking that comes about as the result of an honest mistake, which is possible. But there’s nothing keeping real fraudsters from collecting data, analyzing it, picking the analysis that looks best, THEN “pre”-registering it, and making it look like they planned those analyses all along. And of course the worst fraudsters of all can just fabricate data.)

But here’s something they don’t always tell you: p-hacking is only an issue if you’re doing research in the narrow range where inferential statistics are actually called for. No p-values, no p-hacking. And while inferential statistics can be handy, you want to avoid doing research in that range whenever possible. If you keep finding yourself reaching for those p-values, something is wrong. 

Statistics is useful when a finding looks like it could be the result of noise, but you’re not sure. Let’s say we’re testing a new treatment for a disease. We have a group of 100 patients who get the treatment and a control group of 100 people who don’t get the treatment. If 52/100 people recover when they get the treatment, compared to 42/100 recovering in the control group, it’s hard to tell if the treatment helped, or if the difference is just noise. You can’t tell with just a glance, but a chi-squared test can tell you that p = .013, meaning there’s only a 1.3% chance that we would see something like this from noise alone. In this case, statistics is helpful.

But it would be pointless to run a statistical test if we saw 43/100 people recover with the treatment, compared to 42/100 in the control group. You can tell that this is very consistent with noise (p > .50) just by looking at it. And it would be equally pointless to run a statistical test if we saw 98/100 people recover with the treatment, compared to 42/100 in the control group. You can tell that this is very inconsistent with noise (p < .00000000000001) just by looking at it. If something passes the interocular trauma test (the conclusion hits you between the eyes), you don’t need to pull out the statistics.

If you’re looking at someone else’s data, you may have to pull out the statistics to figure out if something is a real finding or if it’s consistent with just noise. If you’re working with large datasets collected for unrelated reasons, you may need techniques like multiple regression to try to disentangle complex relationships. Or if you specialize in certain methods where collecting data is expensive and/or time-consuming, like fMRI, you may be obliged to use statistics because of your small sample sizes.

But for the average experimentalist, you can get a sense of the effect size from pilot studies, and then you can pick whatever sample size you need to be able to clearly detect that effect. Most experimentalists don’t need p-values, period.

Better yet, you can try to avoid tiny effects, to study effects that are more than medium-sized, bigger than large even. You can choose to study effects that are, in a word, ginormous. 

I like my women like I like my coffee

And it’s not like we really care about a simple distinction between working and not-working. The Manhattan Project was an effort to build a ginormous bomb. If the bomb had gone off, but only produced the equivalent of 0.1 kilotons of TNT, it would have “worked”, but it would also have been a major disappointment. When we talk about something being ginormous, we mean it not just working, but REALLY working. On the day of the Trinity test, the assembled scientists took bets on the ultimate yield of the bomb:

Edward Teller was the most optimistic, predicting 45 kilotons of TNT (190 TJ). He wore gloves to protect his hands, and sunglasses underneath the welding goggles that the government had supplied everyone with. Teller was also one of the few scientists to actually watch the test (with eye protection), instead of following orders to lie on the ground with his back turned. He also brought suntan lotion, which he shared with the others.

Others were less optimistic. Ramsey chose zero (a complete dud), Robert Oppenheimer chose 0.3 kilotons of TNT (1.3 TJ), Kistiakowsky 1.4 kilotons of TNT (5.9 TJ), and Bethe chose 8 kilotons of TNT (33 TJ). Rabi, the last to arrive, took 18 kilotons of TNT (75 TJ) by default, which would win him the pool. In a video interview, Bethe stated that his choice of 8 kt was exactly the value calculated by Segrè, and he was swayed by Segrè’s authority over that of a more junior [but unnamed] member of Segrè’s group who had calculated 20 kt. Enrico Fermi offered to take wagers among the top physicists and military present on whether the atmosphere would ignite, and if so whether it would destroy just the state, or incinerate the entire planet.

The ultimate yield was around 25 kilotons. Again, ginormous.

Studying an effect that is truly ginormous makes p-hacking a non-issue. You either see it or you don’t. So does having a sufficiently large sample size. If you have both, fuggedaboudit. Studies like these don’t need pre-registration, because they don’t need inferential statistics. If the suspected effect is really strong, and the study is well-powered, then any finding will be clearly visible in the plots.

This is why we didn’t bother to preregister the potato diet. The case studies we started with suggested the effect size was, to use the current terminology, truly ginormous. Andrew Taylor lost more than 100 lbs over the course of a year. Chris Voigt lost 21 lbs over 60 days. That’s a lot.

If people don’t reliably lose several kilos on the potato diet, then in our minds, the diet doesn’t work. We are not interested in having a fight over a couple of pounds. We are not interested in arguing about if the p-value is .03 or .07 or whatever. If the potato diet doesn’t work huge, we don’t want it. Fortunately it does work huge

(We didn’t report a test of significance for the potato diet because we don’t think inferential statistics were needed, but if we had, the relevant p-value would be 0.00000000000000022)

What ever happened to looking for things that… work really well. No one has academic debates over whether or not sunscreen works. No one argues about penicillin or the polio vaccine. There was no question that cocaine was a great, exciting, very wonderful local anesthetic. When someone injects cocaine into your cerebrospinal fluid, you fucking know it. 

We pine for a time when spirits were brave, men were men, women were men, children were men, various species of moths were men, dogs were geese, and scientists tried to make discoveries that were ginormously effective. Somehow people seem to have forgotten. Why are we looking for things that don’t barely work?

Maybe statistics is to blame. After all, stats is only useful when you’re just on the edge of being able to see an effect or not. Maybe all this statistics training encourages people to go looking for literally the smallest effects that can be detected, since that’s all stats is really good for. But this was a mistake. Pre-statistics scientists had it right. Smoking and lung cancer, top work there, huge effect sizes.

We know not everything worth studying will have a big effect size. Some things that are important are fiddly and hard to detect. We should be on the lookout for drugs that will increase cancer survival rates by 0.5%, or relationships that only come out in datasets with 10,000 observations. We’re not against this; we’ve done this kind of work before and we’ll do it again if we have to. 

There’s no shame in tracking down a small effect when there’s nothing else to hunt. But your ancestors hunted big game whenever possible. You should too. 

Good hunting.