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 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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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 Goldengave 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.
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.
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.
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.
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”.
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!
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).
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.
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.
The first time we mentioned the potato diet, in Part III of our seriesA Chemical Hunger, we shared the story of Chris Voigt, the Executive Director of the Washington State Potatoes Commission, who lost 21 pounds on a 60-day potato diet. By Part X of the series, we started to wonder if someone should maybe run a study, and see if the potato diet really works as well as all that.
For those of you who are just joining us, the potato diet is a diet where you try to get most of your calories (>95%) from potatoes. You can have drinks like coffee and tea. You can season the potatoes with salt, spices, and whatever hot sauce you want. You can even cook with oil. The only thing we asked people to entirely avoid was dairy (see original post for details).
Does this mean you can eat fries for every meal? It does, and some people came pretty close to that ideal. See for example, this post:
I have never heard of a diet that allows you to eat french fries for all three meals, and I did just that on a couple of days. It rocked.
As people signed up and started sharing their experiences, we made a twitter thread of live-ish updates. In this thread you can read anecdotes shared on twitter that aren’t found in the official study data.
To sign up for the study, participants filled out a google form (PDF available in the repository; see below) of demographic information, then over the next four weeks, recorded their data on a copy of a google sheet that we provided.
Two hundred and twenty people filled out the signup form before we closed the study. As far as we can tell, most signups came from twitter, reddit, and word-of-mouth. We actually didn’t ask about this, probably should have. Whoops.
We downloaded people’s data when they sent us an email to formally close the study. Anyone who didn’t send us an email to officially close the study, we grabbed their data (if any) in the last days before closing the study. The dataset we’ll be examining today represents the state of the data as of midnight on Friday, July 1st, 2022, four weeks after we closed signups and eight weeks after we started collecting data.
Raw data, the analysis script, and study materials are available on the OSF. We decided to store our data and materials there, since that repository is well-supported and we expect it to stay available for a long time. The organized data is “SMTM Potato Diet Community Trial Main Form.csv”; the script is called “SMTM Potato Diet Community Trial 1 Analysis.R”; and the raw data is in a folder called “Potato Raw Dato”
This dataset is very rich — we certainly haven’t found everything there is to find in these data. A number of people measured other variables (like blood pressure, resting heart rate, and sleep) and we haven’t looked at those data in any systematic way.
Also there is a lot of room for new findings in coding the free-response data. You could, for example, go through and try to code what kind of oil(s) people are using, and see if people who use different oils lose different amounts of weight, find the diet easier, etc.
We really look forward to seeing other people do their own analyses. Send them our way, we’ll link them or do a roundup post or a meta-analysis or something.
Two participants asked that we not share their data publicly. But if you’re following along at home you should still get the same results as we do, because those two participants seem to have entered no data.
If you have advice about what to do differently next time, we are interested in hearing that. But if you don’t like something about the study design and just want to gripe — run your own study!
Let’s start with a recap of the study variables.
Our demographic variables are — age, ethnicity, height in inches, local ZIP or postal code, current country of residence, profession, and reported sex.
Sex was initially reported as “Male”, “Female”, or a free-response “other” field. A few participants reported being trans or nonbinary, so we created two variables, “Chromosomal Sex (estimated)” and “Hormonal Profile (estimated)” where we estimated their chromosomal sex and hormonal profile, respectively, based off of free report data. As the names suggest, these are just estimates. We don’t actually have access to your chromosomes.
This is in case there end up being major endocrinological effects. It seems like there could be sex differences in the potato diet because there are clear sex differences in obesity and in anorexia, which we think may be related.
On their datasheets, participants were asked to record a slate of variables every day. Our main daily variables are — daily weight in pounds; notes for each day; energy for each day on a scale from 1-7, where higher numbers are more energy; mood for each day on a scale from 1-7, where higher numbers are a better mood; and ease of the diet for each day on a scale from 1-7, where higher numbers are finding the diet easier.
We also had a field where participants could record whether or not they broke the diet (eating something substantial other than potatoes) each day. If they stuck to the diet we asked them to put a 0 in this field, if they broke the diet we asked them to put a 1. This is a bit of a mouthful so we will often colloquially refer to these as “cheat days”.
A total of 220 people submitted the initial form.
Of those, 11 people filled out the signup form incorrectly in such a way that we couldn’t sign them up (they didn’t enter an email, didn’t indicate critical data such as height, etc.). We enrolled the remaining 209 people in the study.
Let’s take a look at the demographics of the people who enrolled:
Age ranged from 18 to 69, with a mean of 35.2 and a median of 35.
Reported sex was 50 female, 151 male, 7 other entries (e.g. “non-binary”, “AFAB on testosterone so idk how you wanna categorise that”), and one person who didn’t respond.
Based on this, we estimated 51 XX participants and 156 XY participants; and we estimated 53 people with a more “female” hormonal profile and 153 people with a more “male” hormonal profile.
Reported ethnicity was 185 white, 10 Asian, 2 Indian, and 4 more specific entries (e.g. Latin, Indonesian, etc.). Everyone else who reported ethnicity reported being a mix (e.g. “Brazilian. Mostly white, kinda mixed though.”; “German/Vietnamese/Anglo-Saxon“).
Participants mostly came from the Anglosphere and Europe: 133 US, 17 UK, 17 Canada, 7 Germany, 6 Australia, 4 Ireland, 3 Sweden, 2 Poland, 2 India, 2 Hungary, 2 France, and several singletons from places like Finland, Mexico, Serbia, Brazil, and “Magyarorsz√°g” [sic] which we think is also Hungary.
Profession is hard to code since it’s so diverse, but it looks like the biggest groups were software engineers/programmers, grad students, various scientists and academics, and game designers.
Out of the 209 people signed up, 5 started the diet late for one reason or another, and were still in the middle of the four weeks when we closed data collection on July 1st. We let them keep going and looked at the 204 people remaining.
Of these 204 participants, 44 never entered any data onto their datasheet. As far as we can tell, they just never got around to starting the diet — we certainly didn’t get any data from them.
This leaves us with a total of 160 people who entered some data. Of those 160:
Age ranged from 19 to 61, with a mean of 36.0 and a median of 35.5.
Reported sex was 29 female, 124 male, 6 other entries, and one person who didn’t respond.
Based on this, we estimated 30 XX participants and 129 XY participants; and we estimated 32 people with a more “female” hormonal profile and 126 people with a more “male” hormonal profile.
Reported ethnicity was 145 white, 5 Asian, and 10 other entries like “Polish” or “Japanese/ Hispanic”.
Participants were still largely Americans: 104 US, 13 Canada, 12 UK, 6 Germany, 5 Australia, 3 Sweden, 2 Poland, 2 Ireland, 2 Hungary, and one each to a number of others.
Again the most common profession is software engineer / programmer, with various research jobs and IT jobs behind it.
Of this group, 35 people formally closed the diet early by sending us an email. We coded the reason they dropped out based on their comments.
One we coded as dropping out because of boredom (“Overall not a difficult diet, but I decided to end it because I was getting pretty bored of potatoes.”).
Two reported stopping because they got sick, which we coded as illness. This isn’t potato-related illness, to be clear — one had a throat infection and the other got shingles.
Six reported stopping because of a schedule conflict, coded as schedule. Some of them specifically said they could have kept going otherwise, like participant 66959098:
I am ending my diet at 21 days instead of at 28. This is mostly a scheduling issue, having family visiting next week and would like to go out and eat with them. I believe I could have made the four weeks without too much trouble otherwise, and I may even go back on the diet again sometime later.
The remaining 27 early closures reported stopping because they found the diet really difficult in one way or another, and we coded this as difficulty. For example, participant 29957259:
I threw in the towel on the potato diet six days in. The first few days were easy for me, but it eventually grew much more difficult. I found myself thinking about food way more than someone whose next meal was planned should have.
Clearly the potato diet really does not work for some people! More on this later.
Another 57 people made it partway to 4 weeks but didn’t officially close the study, and we don’t know why. We went back and forth on what to call this, since we don’t know why they stopped reporting their data, and we wanted the coding to sound as neutral as possible. In the end we coded them as dropped.
These participants don’t seem to have just flaked out. Many of them made it a long way. Several people made it past two weeks, and two people made it all the way to day 27:
We’re going to try to stay agnostic about what happened in these cases, because these participants didn’t give us a clear reason why they dropped out. But we can also make some educated guesses.
Some people clearly dropped out because the diet was too difficult. For example, participant 31554252’s last comment was:
Finding it very difficult to keep going—just very sick of potatoes
But other people don’t seem to have found the diet difficult, and probably dropped out for other reasons. For example, participant 71309629 appears to have dropped out because of illness. They said, “Got sick, will update later” on the last day they entered data, and haven’t updated since. We hope you’re ok!
Similarly, participant 97388755 could probably be coded as ending for schedule reasons. She said in the comments:
I renounce potato. I’m moving house and the chocolate cravings and trying to make potatoes for 2 people is a pain in the ass.
It might be interesting to go back and try to re-code all the dropped trials, figure out why they stopped the diet, but not today.
Since we asked everyone how easy the diet was, we can also look at the ease they reported on the last day they gave us a weight measurement (though a few people stopped reporting ease before then). As a reminder, higher numbers / more to the right is more easy:
Some people definitely were finding this difficult when they stopped, and it’s reasonable to think that the people who gave a 1 or 2 on the last day stopped because they couldn’t stand it.
But plenty of people who dropped out without telling us why rated diet ease at a 6 or a 7. The modal value is clearly 5! So while some of these dropped trials are because of difficulty, others presumably dropped out for other reasons: they had to go on a trip, they had a family emergency, they got sick with COVID, etc.
The diet protocol in the original post asked for 29 days of weight measurement. The last measurement would be on the morning of the 29th day, giving us 28 days of complete data.
But we fucked up on the data recording sheet and made it seem like people should record only up to day 28. Most people followed instructions — they gave us 28 days of data, then stopped. This is our fault, we messed up.
To keep things standard, we used each person’s data at day 28 as their final day of data. For people who went past 28 days (a number of people kept collecting their data and/or kept going with the diet), we treated them as if they did 28 days exactly. We used their weight on day 28 as their final weight, counted their number of cheat days up to day 28, etc.
At some point it might be interesting to go back and look at the data of people who did 29+ days, but again, not a project for today.
This is technically 27 full days of potato diet, since the measurement for day 28 is the MORNING of day 28. But tiny differences like this are like, eh, who cares. If the effect is substantial at all, it won’t matter anyways. Anyways, henceforth this span will be referred to as “four weeks”.
One participant (40207077) didn’t report his weight for day 28, so we used his day 29 data. Coincidentally this is also the person who lost the least weight over the 4 weeks. If you kicked him out because he often forgot to report his weight, average weight lost on the diet would be even greater.
Anyways, 64 people made it the full four weeks and completed the potato diet. Let’s review their demographics:
Age ranged from 19 to 61, with a mean of 36.7 and a median of 36.5.
For sex, 5 reported their sex as female, 54 male, 4 other entries, and one nonresponse.
We estimated 6 XX and 57 XY; and we estimated 7 people with a more “female” hormonal profile and 56 people with a more “male” hormonal profile.
For ethnicity, 57 were white, 4 Asian, 1 Polish, 1 “several of the above”, and 1 “half-asian, half-white”.
Participants reported being in the following countries: 46 US, 4 Canada, 2 each in UK, Germany, and Ireland, and several singletons.
Racial diversity is definitely a major limitation of this study, especially since obesity differs a lot across ethnicities. The diet could easily work half as well, or not at all, for African-Americans. Or for all we know, it could work twice as well. The results we have so far look really promising (as you’ll see in a minute), and we think it’s important to see if they’ll generalize. So if we run another potato diet study, and you’re part of a racial group that isn’t well-represented in this study (i.e. if you are not white), your data could contribute a lot!
The first question is, what is the retention rate for the potato diet? Well, it depends how you slice it.
If you want to be maximally strict, 64 people made it four weeks out of 209 enrolled, so 30.6%.
Not too bad. This is a kind of extreme diet, and it would be pretty impressive even if only 30% of people made it to the end. Frankly, we’re impressed so many people signed up in the first place.
But we think this is too low, in fact. Only 209 people were enrolled in the study, and because some trials were ongoing at closing, only 204 had potentially available results. 64 out of 204 would give us a retention rate of 31.4%.
But of those 204 people, 44 never entered any data. There’s a good chance most of these people never started the study, and shouldn’t be considered dropouts. In this case, retention is out of 160, and 64 out of 160 is 40.0%.
If you wanted to be maximally permissive, you could only count the dropouts who sent us an email to formally close the study. This gives us a total of 102 people, and makes the retention rate 64 out of 102 people, which is 62.7%
(Actually if you wanted to be super maximally permissive, you could only count people as dropouts if they explicitly stopped because of finding the diet difficult. Then retention would be 64 out of 91, or 70.3%.)
So we think the retention rate is somewhere between 40.0% and 62.7%, though you could make a case that the retention rate is as low as 30%. In any case, the idea that between one-third and two-thirds of people get to the end of four weeks on basically only potatoes is pretty wild.
Of course, a hard cutoff doesn’t make much sense. Most people made it some number of days between 1 and 28. Heck, five people ended the potato diet on day 27!
When we look at the number of days people made it to, we do seem to see two (or maybe three?) clear groups:
Clearly the most common outcome is to make it the full four weeks. The next most common is to drop out in the first week or so.
But there’s another bump near the end of the third week, and that seems kind of interesting, especially because some people mentioned hitting a wall at around three weeks. For example, participant 23300304 stopped on day 22 and reported:
Initially I found the diet extremely easy… However, quite suddenly after about three weeks I started feeling unwell, with low level nausea, headaches and general tiredness. Initially I thought I was falling ill. But I didn’t really show any specific symptoms of illness. After a few days I was feeling so bad I decided to end the diet. I felt better by the end of the first day eating my usual diet again.
Similarly, things were going great for participant 63746180. They had already lost about 10 pounds over 18 days and seemed to be enjoying it. But then:
My reason for ending is that I was hungry to the point of headache and dizziness, but could not force myself to eat a potato. It was a weird experience, my body was screaming for food but I couldn’t swallow a potato. I went from pretty happy with eating potatoes to completely unwilling to eat a potato in the span of a day.
So there might be something interesting with people hitting a wall at three weeks or so. However, as you can see from the histogram, it was a minority of participants.
4. Weight Loss
Of the participants who made it four weeks, one lost 0 lbs (participant 40207077). Everyone else lost more than that.
The mean amount lost was 10.6 lbs, and the median was 10.0 lbs. The 99% confidence interval on the mean is 12.1 to 9.1 lbs of weight loss. The greatest amount of weight lost was 24.0 lbs, from participant 74282722.
We thought this might end up being bimodal — some people going into potato mode and other people just struggling through — but it looks pretty normally distributed around 10 lbs. There’s sort of a little spike around 15 lbs maybe.
We can also look at individual time series data:
And here’s the average over time:
We can also do these plots as percent weight change, but you’re gonna be pretty disappointed, they look almost exactly the same:
Actually Why Not Just Look at All The Data
Like we mentioned above, a hard cutoff doesn’t make much sense. Let’s just look at all the data.
Here’s weight change by total number of days completed on the potato diet for all participants who entered data:
Seems like a clear trend. And it makes sense to us; if you make it 22 days on the diet, you get about 3/4 the benefit of making it the full four weeks on the diet.
We can see that only two people reported a net weight gain on their diet, and of only 2.3 and 0.1 lbs. In addition, twelve people did report exactly no weight change — though nine of them only entered data for day 1, so they couldn’t have lost any weight. It doesn’t look like the potato diet can go “wrong” and you can gain a lot of weight.
We want to point out that the person who lost the MOST weight (24.8 lbs; participant 71319394) actually ended the diet on day 27 — “I am calling it done a day early, but I think it has gone really well for me and was really easy for about 3 weeks.” — so he doesn’t appear in the “completed four weeks” analyses.
Also note the outlier, participant 89861395, who reported losing 41.6 lbs in 18 days. We assume this is an error, in part because he reported being 296.8 lbs on day 17, and then being 267.0 lbs on day 18, after which point he recorded no further data. It seems unlikely that he lost 29.8 overnight just before closing the study. Probably he lost 11.8 lbs total before stopping, the number suggested by his weigh-in on day 17.
When we plot this over time, it becomes clear that it didn’t really matter if people “finished” or not:
People lost about a half a pound a day on average, though with quite a bit of variation (we did kick out that one measurement claiming to lose 29.8 lbs in a single day, since it’s probably a typo). There appears to be no meaningful difference in the daily weight loss of people who did and didn’t make it the full four weeks. In fact, people who made it the full four weeks had slightly lower average weight loss, a mean of 0.41 lbs a day compared to a mean of 0.55 lbs a day in people who didn’t make it four weeks.
Here’s how the potato diet COULD have worked: some people don’t lose weight, so they quit, and other people do lose weight, so they keep going. If that happened, we would see a really successful group of people who made it to four weeks and lost a bunch of weight, and another group of dropouts who lost little or no weight. But that’s not what happened. Almost everybody who tried the diet seemed to lose about the same amount of weight per day. So something causes the dropouts to drop out, but it’s not that the diet doesn’t work for them. The diet works for pretty much everyone, at least for however long they can stick to it. But then, for unclear reasons, some people hit a wall.
You might want to know, how much weight will I lose if I don’t make it four weeks? How much weight will I lose if I start and keep going until I hit a wall? Well, it depends on how long it takes for you to hit that wall, but we can talk about what you can expect on average.
People who entered at least two weight measurements but didn’t make it four weeks lost an average of 5.5 lbs, with a median of 4.2 lbs and a maximum weight loss of 24.8 lbs.
If we pool everyone who entered at least two weight measurements, they lost an average of 7.7 lbs, with a median of 6.9 lbs and a maximum weight loss of 24.8 lbs.
So strictly speaking, if you start the diet, based on these data you should expect to lose 7.7 lbs on average. If you fully expect to make it four weeks for some reason, then you should expect to lose 10.6 lbs; and if you for some reason are sure you will NOT make it four weeks, you should still expect to lose 5.5 lbs on average.
Finally, it’s worth noting the subjective element. Just look at how happy many participants were with the diet:
I lost almost 25 lbs and have felt great throughout. I have been sleeping fine and having plenty of energy.
Well I thought that was super fun and I’m happy to have done it. Lost about 16 pounds. … Anyway, I had a blast. I would consider doing potatoes again in the future. This is probably the thinnest I’ve been in at least 15 years or so.
Thank you for doing this. I’ve found it very valuable and think potatoes will continue to play a role in my health.
Thanks for organizing this!
Thanks for the opportunity to do this, it’s been an interesting ride, and I did lose weight.
Hi! Thanks for doing such a great study!
I felt really good during the diet. This is the best I’ve felt in several years. My clothes fit better, I’m not as tired all the time, my back and knee has felt better than they had for the last 6 months.
I did it. One month, mostly potato. And I am really happy I came across your tweet about this crazy and kinda dumb idea for a study. Over this past month I lost pretty much exactly 10 kg / 22 lbs. It felt easy most of the time, and I feel fantastic. My goal of a BMI < 30 is still 20 kg away, but that feels achievable for the first time I can remember.
Thanks for running this experiment! It was very fun, and I wish there were more things like this going on in the world.
Thank you so much for including me in your study! It has been a huge boon to me personally and it was nice to be able to contribute to science!
I had a good time overall with the diet, and ultimately I think the viscerally-felt revelation that an adjustment to my diet gives me far greater mental clarity will be long-term life-changing. Thanks for that.
By BMI Bracket
We can also break down these same analyses by starting BMI bracket.
None of our participants were “underweight” (BMI < 18.5) to start. Of the people who entered any data, 27 had starting BMIs between 18.5 and 25, 66 were BMI 25-30, 43 were BMI 30-35, 17 were BMI 35-40, and 7 had starting BMIs above 40.
Retention by Starting BMI
Overall, it doesn’t seem like retention is much better or worse for people with higher or lower starting BMIs. This is a little surprising — you might expect leaner people to drop out more, since they have less to lose. Or you might expect heavier people to drop out more, because they presumably have a harder time losing weight. But we don’t really see much evidence for either.
We can also plot these variables to get a better look. We’ll adapt the colors from this uh lovely diagram by the CDC:
Again, we see pretty similar retention across groups. This plot shows the days completed, out of 28, by people in each bracket. Vertical lines are medians:
People with a BMI < 25 do seem to be more likely to drop out on the first day, but that might just be noise.
And here’s weight loss for people who completed the four weeks by BMI bracket. Again, vertical lines are medians:
As expected, people with higher starting BMIs lost more weight. We can also show this as time series:
What is not expected, and what we find quite surprising, is that people who started the study with a BMI of less than 25 (what they call “normal weight”) often lost weight as well. And not just a little weight, a decent amount of weight. Median weight loss for BMI < 25 was actually 7.3 lbs!
This becomes more striking if we break it out as percent body weight lost:
Nicky isn’t the only example of someone who started with a low BMI and saw it go even lower. There’s also participant 89852176, who made it the full four weeks:
I went into it not feeling like I had a lot of weight to lose (starting weight/BMI 143/21.1), but my wife and I started together at the same time, and she had more to lose. In addition, I was hoping for an improvement in my blood pressure (typically 120ish/85ish); I haven’t seen a significant change there. However, I did see significant weight loss; my ending weight/BMI (this morning, day 29) was 132.4/19.5.
Naturally we are wondering why people who are already at the bottom end of the range for “normal weight” are losing weight on this diet. Two possibilities come to mind.
One possibility is that the natural human BMI is really around 19. These days we think of 22 or 23 as pretty normal, but that seems to be the high end for hunter-gatherers.
Walker and colleagues compiled body size and life history data for more than 20 small-scales societies. They report mean ± SD body mass indices (BMI) of 21.7 ± 2.9 for n = 21 adult female cohorts and 22.2 ± 2.7 for n = 20 male cohorts, mid-range within the WHO category for ‘normal weight’ (BMI: 18.5–24.9; WHO). … within the Hadza hunter-gatherer population, we find little evidence of overweight or obesity. BMI for both men (20.0 ± 1.7, n = 84) and women (20.3 ± 2.4, n = 108) 20 to 81 years remains essentially constant throughout adulthood and similar between sexes (Fig. 1).
The average BMI at 40 years of age [for hunter-gatherers] has typically been around 20 kg/m2 for men and 19 kg/m2 for women. After the age of 40, the BMI for both sexes drops because muscle mass and water content decrease with age and because fat is not increasingly accumulated.
So if the potato diet is resetting your lipostat (if you’re not familiar, we describe this below) and sending your BMI towards what it would have been if you hadn’t been raised in a modern environment, maybe your BMI is headed towards the hunter-gatherer range of 19-20.
It doesn’t seem like potatoes would send your BMI any lower, in part because there have been cultures that lived almost entirely on potatoes and they did not all drop to BMI 10 and die. For example, take this account of the Irish, from Adam Smith of all people (h/t Dwarkesh Patel):
Experience would seem to shew, that the food of the common people in Scotland is not so suitable to the human constitution as that of their neighbours of the same rank in England. But it seems to be otherwise with potatoes. The chairmen, porters, and coal-heavers in London, and those unfortunate women who live by prostitution, the strongest men and the most beautiful women perhaps in the British dominions, are said to be, the greater part of them, from the lowest rank of people in Ireland, who are generally fed with this root. No food can afford a more decisive proof of its nourishing quality, or of its being peculiarly suitable to the health of the human constitution.
Another option is that potatoes just have super weight loss properties that work no matter how much you weigh (but more on this later).
We say “nothing but potatoes”, but the potato diet is actually a lot more permissive than all that. You get oil, spices, and drinks, and in our version of the diet, we said, “Perfect adherence isn’t necessary. If you can’t get potatoes, eat something else rather than go hungry, and pick up the potatoes again when you can.”
People took us at our word, and many people chose to take several cheat meals or cheat days (several people mentioned loving this aspect of the diet). For each day, they reported whether or not they broke the diet, so we have an estimate of how many cheat days each person had, and we can look at that as part of this analysis.
We do want to remind you that this is self-report. Different people had different standards about what counted as breaking the diet, and some people were more rigorous about tracking this variable than others. It might be a good future project to go through all the raw data at some point and get better estimates for adherence based on the comments.
But that said, let’s take a look at them cheat days:
Only five people reported not a single cheat day. Everyone else said they broke the diet at least once. Most people cheated a few times, but a few people (36%) broke the diet for more than a week’s worth of days.
This is important because clearly the potato diet’s effects are robust to a couple’a cheat days.
We can take a better look at this with a nice scatterplot. Here we compare number of cheat days on the x-axis to weight change on the y-axis:
You can see there’s a bit of a trend between more cheat days and less weight loss. Remember, higher numbers here are less weight loss; zero lbs is at the top. People on the left, who cheated very little, lost a whole range of weights. People on the right, who took more than 14 cheat days, tended to see much less weight loss.
The basic correlation is only r = 0.176, and not significant. Though we do notice a weird outlier in the bottom right, and without that participant, the correlation is r = 0.303, p = .014.
One interesting thing here is that the five people who reported 0 cheat days are all tightly clustered around losing 10 lbs, so the diet does seem to maybe be the most reliable for people who don’t take cheat days. But some people who took cheat days lost a lot more than that.
So overall we see that cheat days maybe matter a bit, but not a ton. It’s looking good for the 90% potato diet.
Heck, it’s looking good for the *40%* potato diet! Participant 68030741 broke the diet on 27 out of 28 days. (And actually didn’t mark down if he broke the diet on day 22, so maybe 28 out of 28.) He says:
I couldn’t get enough protein with only potatoes, so I supplemented with other food. Also, eating only potatoes without anything to accompany them quickly became too monotonous for me. So, I ended up getting only 40% of my calories from potatoes, but I still lost 7 lb over 4 weeks. I limited my intake of non-potatoes, but I ate potatoes ad libitum. I didn’t try to limit my daily calories; in fact the opposite, I often just wasn’t hungry enough to eat more.
There are some similar stories from other people, like participant 48507645:
I was really surprised at the results. While I cheated way more often than I wanted or anticipated, I still lost almost 10lbs. That’s with cheating almost every weekend (due to unforeseen social obligations).
And here’s one from participant 35182564:
I also must confess, that I was not very strict with the “no dairy” rule. I took milk for my coffee (4-5 cups a day) and occasionally a small piece of butter or some spoon of plain yogurt to go with the cooked potatoes. This does not seem to have impacted the successful outcome. But it made the diet so much easier and also improved the “empty stomach” and “hungry” feelings a lot. Everything besides these “tiny” amount of dairy, I noted in the sheet.
The most extreme case study may come from Joey “No Floors” Freshwater, who shared his story on twitter. He wasn’t able to enroll in the study proper but he decided to do his own version consisting of “1-1.5lbs of potatoes a day when I could”, or about a 20% potato diet. Turns out it works just fine, for him at least. Here are some screenshots:
So it looks like the 20% potato diet can work, at for least some people.
Most people who made it the four weeks report the diet being anywhere between “pretty easy” and “real easy”.
(24235303) It was remarkably easy to stick to the diet. I generally wasn’t hungry and when I was I just ate a potato. I only had cravings for other things when I was directly looking at them, such as when I was helping to put away groceries for my family. This seemed to require a lot less willpower than my previous successful diets.
(41297226) I lost 17 lbs in 28 days, felt very few food cravings or aversive hunger, didn’t get tired of potatoes.
(14122662) I felt mostly normal during this diet. I did often miss going out to restaurants or just having a non-potato meal, but the craving was never so strong as to be unbearable.
(63746180) Most of the time I had a good experience on the diet. I didn’t feel cravings for other food. Sometimes I would imagine eating out at a restaurant as a fun thing to do, but it didn’t have the same urgency as typical food cravings.
(57747642) General Diet Thoughts: It’s really surprisingly easy. I was skeptical that I’d be able to finish the four weeks when I started, but once you get in the groove (and learn some tricks for prepping large quantities of potatoes quickly and easily) it’s extremely simple to stick with it. I basically never felt hungry or low energy.
Even some people who dropped out mentioned that it wasn’t hard for them. For example, take this report from participant 70325385:
Overall, it was a good experience. I thought getting fewer calories would have a more detrimental effect on my mood and energy, to the point where I wouldn’t be able to function normally at all. What I noticed was mostly a ~2 point penalty to my mood and energy, which isn’t that big in the grand scheme of things but enough to be an annoyance.
On the other hand, we want to note that the potato diet was really, really hard for some people. Here are a few stories from people who stopped before completing four weeks.
(52058043) Not only is it very inconvenient to daily life and travel, it also feels pretty gross. I feel uncomfortably full, but still wanting anything, anything at all, that isn’t potatoes.
(86547222) In short, my experience was not great. First two days I didn’t peel potatoes and my digestion went crazy. After that I started to peel potatoes, which helped but not by a lot. During those 9 days that I stuck to the diet I mostly felt apathy. The diet removed any joy associated with food from my life, and I missed that.
More speculation on some people loving it and other people hating it later.
Beyond the self-report, we can also look at people’s daily ratings of how easy they found the diet, on a 1-7 scale from 1 “hard to eat only potatoes” to 7 “lol this is so easy, I love potato”.
We averaged each person’s ease ratings over the four weeks for a mean ease rating. The mean of these ratings was 4.6 and the median was median 4.7, both of course on a 7-point scale.
It does seem like people who found the diet easier lost a bit more weight:
The correlation here is small, only r = -0.155, and not significant. This may, however, be the result of one participant who lost almost 25 lbs but seems to have hated every day of it. See him in the far bottom left? Without that guy, the correlation is r = -0.326, p = .008.
This is participant 74282722, who is also the outlier on the previous plot, with 23 cheat days out of 28 days of the diet. Perhaps this guy’s experience was not typical.
Comparison to other Diet Studies
It’s not a contest, but we think the potato diet compares pretty favorably to the rest of the literature.
Meta-analyses like this one do find that many diets cause 10-20 lbs of weight loss on average. But these studies tend to run for much longer than the study we’re reporting on today. The studies in that meta-analysis ran for 16-52 weeks (median 24 weeks) to get that 10-20 lbs of weight loss. If the potato diet went for 16-52 weeks… well that would be something wouldn’t it. At an average weight loss rate of half a pound a day, you do the math.
This meta-analysis compared interventions based on diet, exercise, and diet plus exercise found that people lost about 23.5 lbs on just a diet, 6.4 lbs on an exercise regime, and 24.2 lbs with diet plus exercise. Again this is pretty good, but these diets were all run for what they describe as “short durations”, which is 15.6 +/- 0.6 weeks.
This two-year trial from The New England Journal of Medicine compared low-fat, Mediterranean, and low-carbohydrate diets in a randomized design. All three of these diets saw only about 2 kg (4.4 lbs) weight loss at one month. This is less than the potato diet participants who dropped out before reaching four weeks, who lost an average of 5.5 lbs (median 4.2 lbs).
Maximum weight loss on these diets was at around 5 months in, when participants had lost an average of about 5 kg (11.0 lbs) in the low-fat and Mediterranean diets, and an average of about 6.5 kg (14.3 lbs) in the low-carb diet. This is about comparable to the weight loss on the potato diet, but it took five times as long.
The attrition rate for the potato diet is pretty comparable to other diet studies. That NEJM paper mentions that “common limitations of dietary trials include high attrition rates (15 to 50% within a year)”, and as a sampling from some papers we grabbed at random from Google Scholar, we see attrition rates of 49.3% in this study, 32.3% in this study, and 56.3% in this study.
Admittedly these attrition rates are over very different time scales, so it may be the case that the potato diet is a little harder to stick to than these other diets. But that seems pretty well offset by the much faster and more reliable weight loss.
We also didn’t include any of the intense measures many diet studies implement to keep their participants in line. We didn’t lock people in a metabolic ward. We didn’t control how they prepared their meals. We didn’t do portion estimation. Heck, most of our participants didn’t even stick that closely to the diet. Most of them took several cheat days!
They still lost an average of 10.6 lbs over four weeks. Of those who made it the full four weeks, one lost zero pounds — the other 63 all lost at least 3 lbs. Of the participants who entered at least two days of weight data, two gained weight, three saw no weight change, and the other 146 lost weight. If you’re statistically inclined, the effect size for those who made it four weeks is d = 2.28. The potato diet is remarkably consistent.
It’s hard to estimate how much some of these other diet studies cost, but we’d guess at least tens of thousands of dollars. In comparison, our budget was $0. And we did the whole study in what, 10 weeks?
5. Effects other than Weight Loss
Ok, enough about weight loss. We were promised MORE.
The case studies did all mention weight loss, but they also mentioned other beneficial effects, the kind of thing we would love to see.
Chris Voigt reported major improvements in his bloodwork: “My cholesterol went down 67 points, my blood sugar came down and all the other blood chemistry — the iron, the calcium, the protein — all of those either stayed the same or got better.”
Andrew Taylor said, “I’m sleeping better, I no longer have joint pain from old football injuries, I’m full of energy, I have better mental clarity and focus.”
This is pretty exciting, so we wanted to look for other effects beyond weight. To keep things simple, we just asked people to track their mood and energy every day, both on a 1-7 scale (7 is better mood and more energy).
We took a look at both variables, and there does seem to be something there. There’s a small trend for mood, from an average of 4.3 on day 1 to an average of 4.7:
Of the people who made it four weeks, 45.3% reported a higher mood on day 28 than on day 1. An additional 34.0% reported the same mood (on a 7-point scale) on day 1 and day 28.
And slightly more for energy, from an average of 4.1 on day 1 to an average of 4.7 on day 28:
Of the people who made it four weeks, 50.9% reported higher energy on day 28 than on day 1. An additional 37.7% reported the same level of energy (on a 7-point scale) on day 1 and day 28.
But there’s definitely some variation — some people reported feeling VERY energetic:
There were also some reports of more specific forms of feeling energetic, like increased fidgeting:
(81125989) I also noticed I’m fidgeting a lot, but not sure if I was always fidget-y before, and I’m only noticing now since I’ve read about lipostats & Non-Exercise Activity Thermogenesis
(88218660) Definitely had increased fidgeting at various points.
We also did this extremely scientific poll on twitter:
So it does look like a substantial minority experienced this, but still, a minority.
Effects and Variables we Didn’t Ask for
We asked people to track mood and energy; but, perhaps foolishly, we didn’t ask them to track things like blood pressure and sleep.
But despite our failure, many people chose to track additional variables anyways, and reported all kinds of other effects of the potato diet above and beyond weight loss.
Certainly many people did NOT experience these side effects. Many people just didn’t mention whether or not they experienced them, but for most of these effects, there were some people who specifically said they didn’t feel it. For example, participant 81125989, who didn’t feel anything:
I didn’t feel any noticeably better or worse. My sleep, anxiety, & ability to focus were trash the last few weeks, but they’ve already been that way for months before anyway.
But it’s hard to tell for most of these effects, since we didn’t track them systematically. A project for next time (or for one of you!).
Anyways, here is a selection of effects other than weight loss that were mentioned at least a couple times, and/or that we found interesting.
Digestion both Good and Bad
Lots of people reported digestive changes. Some of these were good. Others were very bad.
(72706884) Other: Improved digestion.
(89852176) almost exclusively loose stools alternating with mild constipation from day 12ish onward
(38751343) My only note is that when I ate potatoes for more than 24 hours, I had the best poops. Total no-wipers. 10/10 poops. I have IBS so it’s rare for me to have a solid bowel movement. Next time I decide to have anal sex, I’m definitely going to eat potatoes for 24 hours prior.
Before you go rushing to cram potatoes before your next bout of anal sex, beware: the potato diet gave other people diarrhea:
(68545713) I had trouble getting started with the diet because at first. I was leaving the skins on, and not using any salt or oil. I had quite extreme diarrhea in the beginning, which I attribute to the unusually high fiber. I also just don’t like potatoes, so not using any salt or oil made the actual eating of the potatoes very unpleasant for me.
After only a few days, I allowed myself salt and oil, and at about the same time I started “imperfectly peeling” the potatoes to reduce (but not eliminate) the fiber. This made the diet much easier for me.
Several people reported better sleep, and sometimes reported sleeping more.
(72706884) Improved sleep, even with caffeine pills. I never woke up in the middle of the night, which is atypical.
(34196505) I sort of feel like I slept better. This is not consistent with how I usually feel on a calorie deficit–normally, I have a hard time sleeping.
(31664368) Good energy and sleep from a crappy baseline (~4 month old at home, just starting to get “normal” sleep)
(63173784) I needed more than usual sleep on the diet, but once I added chicken I was able to sleep more deeply
My sleep apnea symptoms disappeared, except when I had the one “normal” meal in the middle. I must be reacting to other foods.
There may be a relationship between the amount of sleep people require on this diet and how much weight they lose — someone should look into this at some point.
Several people tracked their blood pressure, and they tended to see improvement, sometimes a lot of improvement.
If you don’t look at BP measurements very often, here’s a quick refresher on what the different ranges mean, from the FDA:
Normal pressure is 120/80 or lower. Your blood pressure is considered high (stage 1) if it reads 130/80. Stage 2 high blood pressure is 140/90 or higher. If you get a blood pressure reading of 180/110 or higher more than once, seek medical treatment right away. A reading this high is considered “hypertensive crisis.”
Two people saw minor increases. Participant 76703005’s blood pressure went from 123/69 (day 1) to 138/82 (day 29). Similarly, participant 26650045 went from 115/76 (day 1) to 116/80 (day 24, their last day).
But other people saw their blood pressure decline, sometimes by a lot.
(90638348) Blood pressure down, resting pulse down, pulse/ox up (data in spreadsheet)
Looking at the spreadsheet, participant 90638348 saw their blood pressure go from 139/98 on day 3 (the first they recorded) to 122/88 on day 29. They actually have BP data up to day 32, when BP was 125/87
Participant 14558563 also tracked their blood pressure, and found it went from 164/100 (day 5) to 153/98 (day 29). They even have data up to day 35, when it was 150/102.
(68482929) I ate a LOT of seasoning and salt, but my blood pressure dropped to 111/73 (before the diet it was 139/something)
(57747642) My blood pressure went down from a pre-diet average of about 135/85 to an average now of about 128/70. So that’s interesting.
(57875769) I also checked my blood pressure a few times, although I wasn’t scientific about it so I’d consider this anecdotal, but on day two of my diet my blood pressure was 149/96 (yikes!) and my last reading on day 27 was 126/81.
(66959098) I also took a blood pressure measurement before and after the diet, starting at 177/107 and going down to 130/80.
Not asking for blood pressure measurements was an oversight on our part, since the measurement is so standard and it’s so easy to track at home. If we run any future studies, we plan to include it; and if you try the potato diet on your own, we recommend that you track it!
Pulse / RHR
A few people measured their resting heart rate, and found that it dropped during their time on the potato diet.
Participant 90638348 reported their pulse (BPM) dropped from 78 (day 1) to 64 (day 29).
Participant 14558563 reported their pulse dropped from 68 (day 5) to 56 (day 29).
And participant 05999987 had this to say:
I noticed I often had to pee during the night, which is unusual for me. (Note that my version of potato diet was also very low sodium, mostly because bland potato was just fine with me and I figured if I got way out of Na/K balance my body would let me know, like a deer in search of a salt lick). More interesting is my resting heart rate went down by almost 10 bpm from ~63 to 54.
A few people got more comprehensive blood work done, and the changes they saw over the course of the diet were generally positive.
Participant 95730133 had this to say in his closing remarks:
As promised, here’s the results of my blood work! Taken on the first day (5/31) and last day (6/27) of my potato diet. Note the second test was also fasted though it isn’t marked.
Total cholesterol dropped from a high 242 mg/dL to a healthy 183 mg/dL.
LDL cholesterol improved from a high 148 mg/dL to a still high 124 mg/dL (0-99 is the target range).
All other levels remained healthy and in the target ranges.
Another participant (23300304) sent us his full blood test results. Like the guy above, 23300304 saw his total cholesterol drop, from 4.5 mmol/L to 3.1 mmol/L (about 174 mg/dL to 120 mg/L in the other units). He also saw his LDL cholesterol drop from 3.0 mmol/L to 1.4 mmol/L (116 mg/L to 54 mg/L). However, his triglycerides went up, from 0.65 mmol/L to 1.79 mmol/L.
When we tried this diet, we experienced some pretty hardcore hypomania:
This makes sense for us because we are mad scientists. But would “normal” people experience the super-wiring effects of potatoes too? Apparently yes, though certainly not everyone.
Participant 68545713 reported:
Energetically and mentally, I felt very energetic on the diet in a “hectic” kind of way. Not bad at all for me, that’s my preferred state. I tend to think of my mental clarity as being about a) how many trains of thought I can have going at once and b) how often I lose a train of thought to a blank mind. On potatoes, I had all ~3 trains running, and I rarely lost a thought. (That is quite unusual for me, and strikes me as very unlikely to be a coincidence.) … I’d classify the energy I get from a potatoes-only diet as “frantic”, or “hectic”, or “excited”.
Participant 15106191 gave these notes:
(Day 5) Energy boost kicked in today. Feel half my age
(Day 6) Potato energy going strong. Feel like Irish Superman
(Day 15) Almost too much energy, hard to sit down at a computer and work, took a break to play basketball
And participant 02142044 described:
[At] one point, I was feeling a mild euphoria, and then it just stopped … I felt a sort of euphoria/hypomania that lasted from day 17 to day 20, and I’m unsure how to reproduce it
Certainly not everyone saw this effect of the potatoes. Participant 90638348 said:
Never saw the manic energy described by other folks. I was sorta looking forward to that.
Only one person mentioned their migraines, but most participants probably don’t have migraines to begin with, so we found this interesting. This was participant 35182564, who said:
My frequent migraines improved during the diet. I could also go much longer without food than before and the blood sugar ups and downs were less pronounced, which is probably why the migraine is better. I am very happy about that.
Similarly, one person mentioned a serious improvement in their skin. Participant 36634531:
One unexpected consequence is that my skin is way clearer. I usually have a lot of redness in my face and am acne-prone. My skin has been way less red and acne has been infrequent which makes me wonder if I have a food allergy. If relevant for genetic reasons: I am of Jewish and English/Irish descent.
Two people mentioned libido issues; participant 95730133:
My libido was down a good bit this month, which I’ve seen during weight loss periods before.
…and participant 70325385
The diet had a fairly large effect on my energy and mood most days, and greatly decreased libido starting almost immediately.
Most people didn’t report this effect; but also no one mentioned the potato diet making them extra horny.
Fear and Grief???
One of the strangest effects that some people reported was an increase in intense feelings of fear and grief. For example, participant 95730133, who said:
I had 2-3 days with bad anxiety, which is super uncommon for me and represents a big chunk of the days I’ve ever felt anxious. May have had something to do with the rapid weight loss / potatoes.
We also saw some clear anecdotes about this on twitter:
Like I said above, potato diet is fucking weird. I mention this and the above because towards the end of the third week, I found myself crying every day. I was having actual meltdowns… five days in a row.
I am not talking “oh I am so sad, let a single tear roll down my cheek while I stare out of a window on a rainy day” levels of gloom and general depression. I am talking “at one point I couldn’t fold some of my laundry in a way that was acceptable to me, and this made me think I should kill myself, so I started crying”.
Is this a really dark to drop in the middle of a sort of lighthearted post about potato diet? Yes. I am sorry if you are uncomfortable reading it. Personally, I think I have a responsibility to talk about it, because the mentally weird aspect of this diet cannot be stressed enough.
If you experience this kind of side effect, we recommend you dial back or discontinue the diet. As Birb put it:
To anyone who wants to do this diet, or is considering it after the benefits I described above: I encourage you to do it, but please be extra cautious that your mental state might be altered and that you are not necessarily in your right mind.
Muscle / Exercise
Finally, let’s talk about the topic on everyone’s mind: getting swole, and staying that way.
When we opened signups, many people asked if you’d be able to get enough protein on an all-potato diet. Potatoes do have some protein, and more than their reputation would lead you to believe (3-5 g in a medium potato), but it’s true that 20 potatoes a day won’t give you as much protein as many people think you need.
This is where we reveal that this community trial is not actually the first-ever study of an all-potato diet. There are a few very small, very old studies, and they’re pretty illuminating on the subject of potato fitness. Stephan Guyenet explains:
Starting nearly a century ago, a few researchers decided to feed volunteers potato-only diets to achieve various research objectives. The first such experiment was carried out by a Dr. M. Hindhede and published in 1913 (described in 15). Hindhede’s goal was to explore the lower limit of the human protein requirement and the biological quality of potato protein. He fed three healthy adult men almost nothing but potatoes and margarine for 309 days (margarine was not made from hydrogenated seed oils at the time), all while making them do progressively more demanding physical labor. They apparently remained in good physical condition. Here’s a description of one of his volunteers, a Mr. Madsen, from another book (described in 16; thanks to Matt Metzgar):
“In order to test whether it was possible to perform heavy work on a strict potato diet, Mr. Madsen took a place as a farm laborer… His physical condition was excellent. In his book, Dr. Hindhede shows a photograph of Mr. Madsen taken on December 21st, 1912, after he had lived for almost a year entirely on potatoes. This photograph shows a strong, solid, athletic-looking figure, all of whose muscles are well-developed, and without excess fat. …Hindhede had him examined by five physicians, including a diagnostician, a specialist in gastric and intestinal diseases, an X-ray specialist, and a blood specialist. They all pronounced him to be in a state of perfect health.”
Dr. Hindhede discovered that potato protein is high quality, providing all essential amino acids and high digestibility. Potato protein alone is sufficient to sustain an athletic man (although that doesn’t make it optimal). A subsequent potato feeding study published in 1927 confirmed this finding (17). Two volunteers, a man and a woman, ate almost nothing but potatoes with a bit of lard and butter for 5.5 months. The man was an athlete but the woman was sedentary. Body weight and nitrogen balance (reflecting protein gain/loss from the body) remained constant throughout the experiment, indicating that their muscles were not atrophying at any appreciable rate, and they were probably not putting on fat. The investigators remarked:
“The digestion was excellent throughout the experiment and both subjects felt very well. They did not tire of the uniform potato diet and there was no craving for change.”
So previous all-potato diets didn’t lead to serious atrophy; it seems like people can maintain muscle just fine on a potato diet, and maybe even build muscle. Despite being relatively low in protein, that protein may be exceptionally available or otherwise of unusually high quality.
Empirically, participants in our potato study seemed to lose mostly fat, not muscle. Participant 10157137 used a Fitbit Aria scale to measure fat %, which went from 17.3% (day 1) to 16.5% (day 28). And they were not alone:
(57875769) I lost nearly 17 pounds, and if the body composition on my scale is to be believed, roughly 75% of that was fat.
(46804417) In total I lost 12.5lb (5.7kg) and 4.3% (33%->28.7%) body fat. I measured the fat % using a FitBit Aria 2 scale. I found it impressive that almost all the weight I lost was fat, usually when I diet I lose some fat but close to maybe half of the total?
Maybe you don’t trust these home scales, and you know what, fair enough. But these numbers are backed up with athletic performance, which indicates no noticeable muscle loss:
(41297226) Weightlifting: I’ve been lifting off an on the last couple months. Went from deadlift/squat/bench of 155/165/135 on April 29th (day -5 pre-diet) to 160/145/125 on May 16th (day 13, first time lifting during diet) to 175/150/140 (day 21). I’d say: inconclusive, but doesn’t seem like I was held back from improvement by potatoes (+ taking 4g of BCAAs post workout)
(14122662) In general, I was shocked by the amount of weight I lost, especially since I started out slim and didn’t have much weight to lose in the first place. I had to actively make sure I was eating enough each day so that I wouldn’t lose even more weight. That said, I felt fine throughout the diet and stayed physically active by rock climbing, hiking, and playing kickball and tennis. My health was never a big concern for me.
(01772895) I went on several pretty intense road/mountain bike rides and kept up while feeling good over the course of the diet.
(05999987) I stuck with my usual level of physical activity which is at least 5 miles of walking a day, with some plyometrics. On the few occasions I did do some more intensive activities (a hike with a long, steep uphill portion) or jogging I felt more muscularly tired than usual, though in general I had average for me, or slightly above average energy.
(74872365) I felt unable/unwilling to lift weights during it. I was lifting 3x a week beforehand, and tried near the beginning to workout a couple times but started feeling kinds of joint soreness I wasn’t used to (assuming because of impaired recovery from previous workout). I tried to give it a few more days rest and just suddenly felt very much like not exercising… so I hardly lifted at all for the rest of it. But after the diet was over (a few weeks after it, what with moving and stuff) I got back into gym, got going again at reduced weights, and in two weeks matched or exceeded previous personal bests on most lifts (but haven’t gotten back to previous bench press best). I overall feel very positive about the way in which I was able to resume working out and hitting PRs after it was over, it wasn’t an overall bad thing for my lifting in the grand scheme.
On the other hand, not everyone had sustained athletic performance on the potato diet. For example, participant 57747642 said:
One difficulty for me was keeping up my running volume on the diet. Pre-diet I ran ~20 miles a week. During the diet I found longer runs to be extremely tiring–I think I was just in too much of a caloric deficit to have much glycogen available. I started cheating by drinking a bottle of gatorade before my longer runs and that seemed to fix the issue. But I still only averaged about 8 miles a week of running which was quite a step down.
(15106191; Day 14) Bench press went down today, likely losing muscle along with the fat, either because of the low protein of potatoes or just the calorie deficit
(34196505) I lift weights at the gym a few times a week, and even on days when I made a point of eating a ton, I felt more fatigued and had a hard time lifting my goal weight. Physical activity seemed harder in general. This is consistent with how I usually feel about a calorie deficit.
If you’re training for a marathon that’s four weeks away, don’t start now. But for most of us, it’s clear that four weeks of the potato diet doesn’t cause serious atrophy or muscle loss.
6. Why do some people find the diet easy and others don’t?
Some people find the diet comically easy, while other people hit a wall at some point and are suddenly unable to eat another potato. We’d like to know why.
It’s worth distinguishing between two things; or that is to say, we think there are two ways to lose weight on the potato diet.
First, you can grit your teeth and force yourself to eat nothing but starchy tubers while fighting back your desire to eat literally anything else. A few people who made it the full four weeks seem to have had this experience. For example, participant 83122914:
It was an interesting experience, but it didn’t feel like any kind of magic bullet for long-term weight loss. I initially ate mostly mashed potatoes, but over time I found myself losing the desire to eat them. I craved meat, salad, etc. … I’ve had similar weight loss results in the past with a low-carb diet.
But most people lost weight the other way: after a day or two of eating potatoes, their appetite waned, they didn’t want anything else, and they began to steadily lose weight.
This is the interesting part. To make this easier to talk about, let’s call it entering “potato mode”, or “potatosis”. Actually, Greek for potato is “patata”, should it be “patataosis”?
Also worth noting that it’s not like the potato diet was just easy for some people and hard for others. More like, almost everyone found it easy at first. Some people found it easy for days or weeks and then suddenly hit a wall. So the question may be more like, why do some people hit a wall at three days, others at three weeks, and others apparently not at all?
It’s possible that the difference between the people who found the diet easy and the people who hit a wall will be something easy to notice, maybe basic demographic variables like race and sex. Let’s see:
The group of participants who provided us any data were mostly male (any way you slice it), mostly white, and mostly from the US.
But overall, basic demographics don’t seem to track onto who made it four weeks and who ended the study early. People who made it four weeks were slightly older, more likely to be from the US, and less likely to be white, but none of these differences are very big.
The only difference that jumps out is by sex. About 20% of the people who got to the point of recording data were female, compared to only about 10% of the people who made it four weeks.
We’re not sure why, or if this is even a real result. With so few female participants to start with, this could just be random noise.
Participants who are XY did report the diet being a little easier, with a mean ease rating of 4.4/7, compared to 4.2/7 for XX participants, but this is not significant (p = 0.530).
We also noticed that XY participants did complete slightly more days overall, but it’s not clear if this is robust. Looking at the plotted data, it doesn’t seem like a huge difference:
The first day of potatoes sucked. I seriously contemplated quitting during the FIRST day. After eating my first round of potatoes, I literally walked from our apartment to a grocery store to look at the extra cheesy hot-and-ready pizza I thought I needed. I gazed at the pizza and walked around the store looking for something to eat. Luckily, I was able to keep it together and walk out of the store and back home to my pantry full of potatoes.
I’m not trying to be dramatic, but it was seriously one of the hardest things I’ve done in my life. It took more will power than I thought either of us had.
But with such a small number of XX participants, it’s hard to be sure.
That said, 20% (6 out of 30) of XX participants made it four weeks. If the potato diet only works for one out of every five people with two X chromosomes, that’s still pretty good.
We do wonder if this is a real effect, and if so, why it happens. It would be good if future studies had more XX participants.
Having lots of trans participants would also help us tell if the cause is more hormonal or more chromosomal. In this study, there aren’t enough people whose chromosomes and hormones don’t “match” to actually disentangle any effects.
Some people seemed to have an easier time, or see better weight loss, when they used less oil.
For our own part, one of us was fine for the first two weeks on a relaxed all-potato diet with olive oil, but didn’t see any weight loss until switching to a no-oil version for the last two weeks, when they lost 10 lbs.
Participant 68482929 did some analysis of his own on this question:
The amount of olive oil I consumed had a noticeable effect on how much weight I lost:
The main thing I craved on the diet was more olive oil. If I ate 10 tbsp / day, that felt about right (and my stool was normal and I gained a bit of weight on those days). The more I cut the oil, the more I had intestinal distress, and the more weight I lost.
Here’s that image:
Participant 88218660 mentioned something similar:
third week – started making air fryer fries at home with < 1 Tbsp of oil and eating pretty much only these. Also allowed myself to have ketchup – I’d estimate an upper bound of 200 calories per day of ketchup, but I expect it was less than that. Stopped losing weight. Very unclear if this is a natural plateau or an actual effect of ketchup. Cravings came back in force, as did normal hunger feeling.
Final day – switched back to mashed potatoes with no oil. Hunger was gone again, cravings were dampened, but didn’t immediately lose any more weight.
It’s not clear if this was the oil or the ketchup (or something else) but they definitely seem to have dropped out of potato mode for some reason. We reached out to participant 88218660 for clarification and he told us that he used olive oil at home.
Despite these stories, many people used lots of oil throughout the diet and still lost weight. This suggests it’s not that all oil is bad and inhibits the potato diet. More likely, it’s that 1) some kinds of oil (e.g. olive oil vs canola oil) inhibit potato mode more than others, 2) certain batches / sources of the same oil (two different brands of canola oil or something) inhibit potato mode for some reason, 3) some people respond to oil differently because of genetics or microbiome or something, or probably 4) some combination of the above. Or it could just be noise, this isn’t strong evidence yet.
Nicky Case also recently did a regression analysis of her own data over 40 days, and found a strong effect of olive oil. But it looks like it was in the opposite direction — for her, more olive oil was associated with more weight loss. Check out the analysis in her twitter thread:
It’s sort of not surprising that all these anecdotes reference olive oil, since we recommended that people should probably use olive oil if they use oil at all. But it’s still kind of interesting. Recommending olive oil might have limited the amount of information we’ll be able to get out of these data! A few people did mention they did very well on Five Guys fries, which are fried in peanut oil… Five Guys, talk to us.
Some people did keep detailed notes of their oil consumption, so it’s possible that a clear answer to this question is hiding somewhere in the data. But it’s also possible that we’d need to run a controlled experiment to figure it out, and we may do that at some point (unless one of you gets to it first?).
Salt / Sodium
Salt intake might also help explain why some people had trouble with this diet.
We didn’t ask people to limit salt intake, but some people may have been keeping their intake down anyways, and that may have made the diet harder than necessary. Even if they weren’t trying to limit how much salt they ate, they may still not have been getting enough. Potatoes by themselves are a naturally low-sodium food.
For example, consider the experience of participant 57875769:
Probably my biggest piece of advice is to use plenty of salt. Depending on the nutrition labels, potatoes have zero sodium or an extremely low amount. It seems hard to get the recommended amount of sodium (and I’ve seen some heterodox sources that say the recommendations should be even twice as high as they are) without adding salt to potatoes. A few days I felt kind of light headed or unfocused and I’d finding adding a little bit of salt to a glass of water (under the threshold where I could taste it) would often improve things pretty quickly.
Or this participant on twitter:
Some people also mentioned craving pickled things, which could be the manifestation of a salt craving:
(01772895) Interestingly toward the end, my main cravings were actually for pickled vegetables for some reason.
Of course, we don’t know for sure if the people who dropped out early WEREN’T getting enough salt. But if some people were avoiding salt this could explain some of the difference.
Another possibility is that finding the potato diet difficult can be an early sign of health issues.
Potatoes are high in potassium, and the kidneys need to do a certain amount of work to clear all that potassium from your system. They’re also high in certain toxins. A healthy body under no extra stress is equipped to handle these toxins no problem. But if your health is compromised, it might be another story.
If you eat one potato, your body will be able to deal with the extra potassium and the low levels of plant toxins. If you eat nothing but potatoes and you have reasonably healthy kidneys, again your body will be able to handle it. But if you eat nothing but potatoes and you have poor kidney health, at some point your poor kidneys may not be able to handle all the extra potassium, potato toxins, and other junk. This will make you start to feel terrible, and may explain why some people did fine on the potato diet for a long time and then suddenly started feeling terrible.
Kidney function seems like the simplest case, but other kinds of hidden health issues could also give your body trouble.
The clearest example comes from Alex Beal (who gave us permission to use his case as an example). He was one of our earliest participants in the potato diet, and also one of the first to drop out of the study. He started tweeting about his experience, did ok on the first meal, but soon found himself feeling awful and totally unable to stand potatoes. He published a log of his experiences here, where he says:
I’ve decided to drop out of the study after less than 48 hours. This diet kicked my ass.
Beal stopped the diet on May 1st. A few days later, he found out he had prediabetes:
This maybe explains why he had such unusual trouble with the potato diet (remember, 90% of people who entered at least one day of data made it more than two days, and 40% made it all the way to day 28). Beal has a (mild) metabolic disorder he didn’t know about when he started, and it’s pretty reasonable to suspect that this may have limited his ability to deal with all these potatoes.
We discussed this with Beal and he agrees it’s plausible. “In a study population of obese folks,” he says, “I do worry undiagnosed diabetes or prediabetes is a risk. It’s very common for it to go undiagnosed.” This is similar to something JP Callaghan mentioned, where he said, “There are tons of people walking around with their kidneys at like 50% or worse who don’t even know it.”
One strike against this explanation is that younger people generally have better kidney function, so if this were why people are dropping out of the study, you’d expect to see many fewer dropouts among younger people, which we don’t see. But for what it’s worth, Alex Beal is pretty young and he had undiagnosed prediabetes before signing up for the study. It’s possible that we recruited a sample that has disproportionately high numbers of young people with undiagnosed renal and/or metabolic disorders.
In any case, finding the potato diet really hard may be an early warning sign for kidney issues and/or diabetes, possibly because the high levels of potassium put a strain on your kidneys that you wouldn’t normally experience, so it might reveal problems you wouldn’t normally notice. So the potato diet may be a useful at-home diagnostic tool.
If you had a hard time with the potato diet, especially if you were only able to make it a few days, talk to your doctor about checking for kidney function and prediabetes.
A number of people mentioned that peeling the potatoes made the diet noticeably easier:
(02142044) The diet was a bit tough at the beginning, probably because I didn’t peel them.
(68545713) After only a few days, I allowed myself salt and oil, and at about the same time I started “imperfectly peeling” the potatoes to reduce (but not eliminate) the fiber. This made the diet much easier for me.
(86547222) First two days I didn’t peel potatoes and my digestion went crazy. After that I started to peel potatoes, which helped but not by a lot.
This matches our experience. On the potato diet, there was a point at which the peels started getting disgusting — but without the peel, potatoes continued to be delicious. We were very pro-peels starting out, but by about halfway through, we started peeling them and that made a clear difference.
This is interesting because it certainly goes against common wisdom about the peels — that they’re especially nutritious, that they’re good for you, and so on. It’s true they’re high in fiber, and it may be fine if you are eating only like, four or five potatoes now and then. But as Stephan Guyenet points out:
Peel [potatoes] before eating if you rely on them as a staple food … Potato peels are nutritious but contain toxins.
Again, your body can handle most vegetable toxins in small doses. But if you are eating a lot, at some point they might get to the point where it’s a problem.
So it could certainly be that past a certain point, eating the peels will become difficult for some people. Or it could be that the peels are generally fine if you’re healthy, but they pose a problem for people with undiagnosed poor kidney function. There could easily be a peels * kidney interaction.
It could also just be fiber. Lots of people reported digestive issues, and the peels are especially high in dietary fiber.
So it’s possible that some people who dropped out early could have made it further if they started peeling their potatoes. If you’re having trouble on the diet, we definitely recommend ditching the peels.
Like we mentioned, potatoes contain toxins, and some potatoes contain more toxins than others. For example, levels of the toxin solanine increase when potatoes are improperly stored, or exposed to too much sunlight, and green potatoes tend to have more solanine.
Most bags of potatoes are fine, but maybe one day you go to the grocery store and just happen to get a bag of greener-than-usual potatoes, which make you feel sick, and since you’re being careful, prompt you to end the diet early. From your perspective you can’t tell why you suddenly got sick, but from a god’s-eye-view, it was the bad batch of potatoes. So maybe random chance is what’s causing some people to hit a wall.
(Just avoiding green potatoes wouldn’t totally fix the problem, because potatoes can be high in toxins without being green. But definitely do avoid green potatoes.)
If this were the case, it would look pretty random who drops out. It does look pretty random who drops out. So maybe the dropouts are from some kind of random factor like this!
7. Why the Heck Does the Potato Diet Work
The human body has a lipostat that regulates body weight, and the lipostat has a setpoint, a weight that it wants to maintain. For the sake of an example, let’s say it wants to maintain a BMI of 23. The lipostat can detect how much fat is stored and takes action to drive body fatness to the set point of BMI = 23. If your body’s BMI is below the setpoint, the lipostat will drive you to eat more, exercise less, sleep more, and store more of what you eat as fat. If your body’s BMI is above the setpoint, the lipostat will drive you to eat less, move and fidget more, and store less of the food you eat as fat.
People become obese because something has gone wrong with the lipostat — for some reason it is defending a set point above BMI 30, and all the regulatory systems of the body are working together to push body weight to that level and keep it there (for more information, see here).
It seems clear to us that something about the potato diet lowers your lipostat set point, and weight loss kicks in because the lipostat starts to defend that new, lower weight.
When you run a normal calorie deficit (don’t eat as many calories as you need), you get sluggish, you lack energy, you get hungry, and you have a hard time exercising. This is because your body wants to defend its weight at the current set point, whatever that point is, and will work really hard to keep you from getting lighter.
But when you are heavier than your current set point, the body pulls out all the stops to help you lose weight and drop to the set point. You feel more energetic, you fidget to burn extra calories, your body temperature goes up, you stop feeling hungry, and so on. In line with this, people in potato mode reported being very energetic, having hypomania, fidgeting all the time, and having no trouble exercising. This is exactly what we’d predict if your lipostat set point suddenly went down.
In addition, there are two special points that strongly support the idea that the potato diet lowers your lipostat set point.
First, some people keep losing weight after stopping the diet. We think this means that the lipostat set point dropped faster than weight loss was able to follow, and it took a few days after the diet was over for BMI to catch up. If the diet just worked on caloric restriction, then you would expect people to start gaining weight again after stopping. But that’s not the case, or at least, not always the case.
(36634531) My weight is still holding steady after resumption of a typical diet. Are you guys going to ping the participants in X months to see if we return to baseline?
(57875769) Since stopping my weight has stayed pretty flat (I was 215.3 lbs this morning and I ended the diet at 215.2, and I was traveling for a few days which usually causes me to gain weight) and I find that I have a much smaller appetite than I used to. I’m having to re-learn how much food I should serve myself or order at each meal because I’m used to eating much more.
This is just suggestive for now, but we’ll know more in 6 months when we do the first followup.
But the biggest sign that the potato diet lowers your lipostat set point is the overwhelmingly common experience of how the potato diet makes hunger feel entirely different.
(36634531) My appetite did eventually tank. I was down to one meal a day. I don’t know if I was just full all the time or if my stomach shrunk or what. I was never feeling hungry throughout the diet.
(68545713) [I] felt less desperate than before-potatoes when I did get hungry. It was wonderful.
(29550957) Subjective feeling is definitely that I could get hungry, but it was not an urgent problem. Completely different from my usual modus operandi of gravitating in the direction of food whenever slightly hungry.
(10010108) I simply was not hungry in the mornings. Once I did start eating, I was starving every 1-2 hours. Out of habit, I do not eat after 8 pm. Sometimes we would have dinner at 7 due to scheduling, and I would be stomach growling hungry at bedtime, between 10-12. I was not going to get up and eat, so I drank water and slept. The hunger just wasn’t there in the mornings though.
(81125989) My sense of hunger was anomalous: some days I’d eat less than 1000 calories and feel totally fine, some days I’d get a sudden sharp pang of hunger right after a hefty meal. And on my cheat days, even when I ate to satiety, I ate a lot less than I did pre-potato diet.
(74872365) I recall feeling like hunger exists in two distinct modes, and potato diet worked helped switch one off while downregulating the other: there’s the “need to feel full and need blood sugar” hunger and the “pleasure reward hunger.” It was like when I finished a mashed potato dinner the first hunger was satiated fully but I still would have eaten a whole pint of ice cream for pleasure if I was allowed to. I still kind of wanted to eat for more pleasure, but the pleasure based eating was “deactivated” from controlling my decision, and the potatoes weren’t hitting that pleasure center. Hence I only ate up to the level of the first hunger metric, the more “physical” one, and that level was downregulated of course. During cheat days (which were all around dinner times I think), the moment I started eating non-potato, I got insanely outlandishly hungry and ate surprising amounts of food the rest of the evening. It was like I would eat a bunch and then suddenly feel empty an hour later.
(68030741) I limited my intake of non-potatoes, but I ate potatoes ad libitum. I didn’t try to limit my daily calories; in fact the opposite, I often just wasn’t hungry enough to eat more.
(1772895) Toward the end of the diet, I found it difficult to eat enough potatoes. I’d be a bit tired and hungry, but the effort of cooking them and eating them seemed too much to bother with. This was an interesting experience, and gave me some empathy for a few of my friends who have a hard time keeping weight on, even with an unrestricted diet. When they’ve described themselves as sometimes being ‘too lazy to eat’ in the past, I basically found that unimaginable, as I don’t think I could ever be too lazy to eat cake, for example. However, if the reward I got from eating cake was similar to the reward I get from eating potatoes, I guess that’s how I’d feel.
What’s interesting though is that I wasn’t feeling tired and hungry and craving some other food — I just didn’t feel like eating. Maybe this is something to do with the stuff Pen Gillette mentioned about eating habits fading. Interestingly toward the end, my main cravings were actually for pickled vegetables for some reason.
(77742719) I did get more tired throughout, and my appetite actually continually decreased. Had to remind myself to eat quite often and actually made a schedule. On this last day, I had only one meal of potatoes, 500 kcal.
(90638348) Was not ever resentful or hungry, always felt “full”
(88218660) First week – no oil, pretty much all mashed, non-organic russets with cajun seasoning and hot sauce. Almost immediately I could tell my cravings were significantly dampened (though not gone, especially if I was looking at tasty food) and that the normal feeling of hunger was entirely gone for me – what was left was a feeling of being almost faint and feeling not great when I went too long without eating. Took a lot of adjusting to.
(57875769) I feel full sooner than I used to, and I feel like there is a much richer variety of sensations that influence whether I want to eat more food. I remember some people advocating that to maintain a healthy weight you just need to learn to listen to my body, which is sort of what this feels like. Perhaps the people giving that advice were always thin and so listening to their body was never hard. I’ve started feeling signals I don’t remember feeling before I started the diet. It’s almost as if the volume from some things (e.g. a hyper-palatable diet) drowned out and deafened me to all the signals I was supposed to listen to. Now I feel like I’m hearing these again.
(76011343) throughout I had a ton more energy, better mood, weird hunger effect that you guys have documented (didn’t feel hungry and had to force self to eat)
As you can probably tell, this experience was extremely common. But we should note that it wasn’t universal, even among people who lost a lot of weight. Participant 99479977 lost 22lbs but specifically mentioned no appetite/hunger effect:
I’ve seen a lot of people mentioning how the diet changed their perception of hunger. For me at least that didn’t change. What I did notice though is that I become sated much quicker. Today I packed myself four medium size roasted potatoes for lunch during uni, and I felt sated after just three of them.
And see also this report from participant 34196505:
It wasn’t like some hunger switch flipped off in my brain after a day or three of nothing but baked potatoes–I still got hungry, and it felt similar to normal hunger. I saw people on twitter saying they were having a hard time reaching 1,000 calories a day. Can’t relate.
People did eat very few calories on this diet. Most people didn’t track calories very closely (another benefit of the diet — no calorie counting!) but some people chose to record how much they were eating. The people who recorded calories (self-report, so grain of salt here) generally reported eating very little.
For example, participant 68030741 kept super detailed notes on calorie consumption and should be the starting point for anyone who wants to dive deeper into this question. He reports eating as little as 756 calories in a given day, and never more than 1740.
Participant 71309629 never reported eating more than 1556 kcal, and ate as little as 307 kcal one day.
Participant 07644625 has “been tracking [calories] for 4035 days … hard to stop now” and reported eating as little as 1172 kcal in a day — but also often ate more than 2000.
Participant 05999987 also said:
As for ease of diet, it was quite easy to feel full, without eating very many calories at all. This worried me the first week, even on days when I supplemented the potatoes with salmon I never ate even 1300 calories a day. In fact, I averaged 921 calories per day.
This is consistent with the reduced appetite. But it is NOT an explanation any more than “the bullet” is a good explanation for “who killed the mayor?” Something about the potato diet lowered people’s lipostat set point, which reduced their appetite, which yes made them eat fewer calories, which was part of what led them to lose weight. Yes, “fewer kcal/day” is somewhere in the causal chain. No, it is not an explanation.
But we’re bored of trying to explain this one, so we’re going to let the cat do it:
Alternately, if you prefer your arguments to come from bipeds:
But that’s ok, this study was not designed to help distinguish between different theories of the obesity epidemic — it was designed to see if the potato diet works under realistic conditions, and to get a rough sense of what percent of people it works for. Now that we have that, future studies can use the potato diet as a “model diet” to start pitting theories against one another. Won’t that be fun.
Even so, the data from this first study does tell us a little bit about different theories. Compared to other diet studies, the potato diet has the benefit of being super controlled — it’s a clear baseline of potato, with few interfering factors. So let’s take a look.
Something special about potatoes?
One thing we need to address right off the bat is the possibility that potatoes cure obesity for some reason totally unrelated to the obesity epidemic.
For example: cocaine makes you lose weight. But the obesity epidemic didn’t happen because everyone was on cocaine for all of history, which kept them skinny, and then in the 20th century people started forgetting to take their cocaine, and we all gained 40 lbs. It’s just that cocaine has strong weight loss effects totally unrelated to whatever caused the obesity epidemic.
Similarly, it’s possible that potatoes are just a potent weight-loss drug for reasons totally unrelated to the increase in obesity since circa 1970. There are a few things that make this seem plausible.
For starters, Staffan Lindeberg, in his book Food and Western Disease, has a whole section on how maybe humans were built to eat roots and tubers:
Increasing evidence suggests that large starchy underground storage organs (roots, tubers, bulbs and corms), which plants form in dry climates, were staple foods 1–2 million years ago. There are at least three arguments in favour of this notion. Firstly, in contrast to most other animals including non-human primates, humans have an exceptional capacity to produce salivary amylase in order to begin hydrolysis of starch in the mouth. The underlying change in copy number of the gene coding for salivary amylase may have occurred approximately 1 million years ago. … Secondly, roots often need to be prepared under high temperature in order for its starch to be available for digestion and for its bioactive or toxic substances to be neutralised. There are many indications of Palaeolithic humans using fire for cooking, and one of the most common cooking methods for plant foods was probably the so-called earth oven, where food wrapped in large leaves is placed in a covered pit with hot stones or glowing coals. Thirdly, human tooth morphology, including incisal orientation, seems to be well designed for chewing root vegetables. … Our bipedal ancestors were apparently less efficient hunters than many carnivorous animals and less efficient fruit-foragers than the arboreal primates. In order to increase the caloric yield per workload (‘optimal foraging strategy’), root vegetables may often have been an optimal dietary choice. An illustrative example is the Machiguenga tribe of the Amazon, among whom one woman can dig up enough root vegetables in one hour to feed 25 adults for one day. The excellent health status among this and other starch-eating ethnic groups, including our own study population in Papua New Guinea (see Section 4.1), contradicts the popular notion that such foods are a cause of obesity and type 2 diabetes.
If we really are built to eat tubers above and beyond all other foods, this might explain why the potato diet lowers your lipostat set point to hunter-gatherer levels.
There’s also some evidence that potato protease inhibitor II suppresses appetite and reduces food intake, though these studies don’t seem to be especially targeted — it looks like they basically just gave people potato extract.
We don’t think the evidence is all that strong, but it certainly seems possible that potatoes just suppress appetite and make you lose weight.
We’ll know more when we get the six-month followup results. If potatoes just suppress your appetite during the time you’re eating them, then once you stop eating them, you should gain most of the weight back. But if potatoes are doing something more profound, and resetting your lipostat or whatever (however they do that), then weight loss should be at least somewhat sustained by six months out. For what it’s worth, this is what we see in the case studies, like Penn Jillette and Andrew Taylor, who seem to have had little trouble keeping the weight off.
It’s possible of course that BOTH are true, that potatoes both suppress your appetite in the short term and somehow reset your lipostat in the long term. In fact, the combination of these effects would be a pretty good explanation for why the potato diet is so unusually powerful. But we’ll have to wait and see.
But assuming for a moment that potatoes are NOT a superpotent weight-loss drug for some reason, what would this tell us about other theories?
Calorie-Counting, Willpower, and other Traditional Diets
(34459757) Pretty easy as far as diets go, basically never felt hungry. Previously I’ve successfully lost 25 lbs via just calorie restriction (mostly by eating box mac and cheese and other prepackaged things with easy calorie counts), and potatoes were definitely easier and I lost weight at the same speed.
(66959098) It felt pretty easy. I have tried simple CICO diets before where I simply reduce portion sizes and maintain a calorie deficit, which were incredibly hard to follow through and caused me to think about food all of the time. This had no such effect, no strong hunger, no strong cravings. I am happy with the results from just three weeks.
(99479977) I have tried various diets before, but restricting calories while eating whatever I like left me hungry, which lead to overeating and actually gaining more weight. The potato diet kept me sated, allows for just enough variety (especially through condiments) to keep me engaged
(27316026) I started the study slightly overweight by BMI and mostly interested in helping out along with seeing how it went firsthand. I’m 35 and 5’9 and my weight has been slowly going up on average for a decade, interrupted by harsh diets every few years to try and get back down under 160. I’ve always succeeded at these diets, which normally lasted around 2 months and involved meticulous calorie counting. I hated these diets and was only able to maintain them with the knowledge that they would be over relatively soon. Comparatively the potato diet has been a joy. It only took a few days to settle into, but after working out a few dishes I enjoyed I wasn’t hungry and food cravings were largely absent.
(95730133) I was pleasantly surprised with the amount and consistency of weight loss on this. 2.5 lbs a week is pretty dramatic and this was even easier to stick to than when I’ve done calorie counting previously at a shallower slope (1.25 lbs/week).
(29550957) This is pretty much the best diet I’ve ever been on, including earlier this year when I also ate mostly potatoes- but with tons of dairy (butter, sour cream, cheese) on them. Despite literally messing up an entire week’s worth of days, I seem to be durably down about 10lbs.
(30719090) This has been quite a revelation:
I have been dieting on and off for about 10 years now. The only successful diet was 10 years ago when I got down to 75kg (165lbs). This was based on buying an expensive range of low carb meals. I was less overweight at the time and it was something of a struggle. The diet was eventually derailed by personal circumstances and I have since then gradually increased my weight reaching 200lbs and over recently.
All other diets I have tried have had a small loss initially, but the loss has never continued. The psychological difficulty of maintaining a restricted diet when the losses did not continue was always too much for me. I hate the feeling of being hungry.
The potato diet has been very different. I actually like potatoes so I have not found it difficult to eat them every day and I have found it very easy to resist the temptation of other food.
(35182564) Since I was very successful, losing more than 20 pounds in six weeks, I will probably continue some more relaxed form of the diet for a few more weeks. I have been trying to lose weight for years with absolutely no success. The potato diet did in six weeks, what I could not accomplish in many years. I hope I can keep the lower weight (will send an update in a few months).
(05999987) As a person who has slowly gained weight over the years until I hit the border BMI between overweight and obese and it has become very difficult to lose weight. I’ve often done a couple weeks of limiting to 1500 kCal/day with what a normal person would think healthy–lots of vegetables, some whole grains, some lean proteins, olive oil, legumes. Every time I’d lose a couple pounds, but not much more, and find myself to be quite hungry most of the time. The main difference with potato diet is that I only once experienced the brain-crashing feeling that I need to eat something immediately because my brain is no longer working due to the colloquial usage of “low blood sugar”. The rational part of my brain also didn’t notice any hunger and I could read about/watch people eat/think about delicious foods and not feel like I really wanted to eat them, and I’m the sort of person who thinks about cooking a lot. Plain cold potato was just fine with me, and while I looked forward to the end of the diet and eating normal food again on a theoretical level, I didn’t care about adding condiments, etc.
(63833277) I occasionally had french fries or tater tots or even a couple of times pringles. My wife used some dairy in preparing the mashed potatoes and had ketchup on my fried potatoes, so probably technically every single day should have a “1” in the “broke diet” field. But if I’d done that I’d never have been able to stick with it as well as I did–I basically tried to bend the diet such that I could successfully stick with it but no further and call that success. I thought about retrospectively changing them all to 1s but there *were* days when I *actually* broke the looser diet I’d set for myself and I didn’t want to elide that distinction. Basically think of my diet as a slightly loose potato diet that’s like 95%-97% potatoes instead of 97%-99% as expected. Sorry for not being ideal about that, I figured that would be better than giving up after 5 days.
DESPITE THE DEVIATIONS, THE DIET WAS AN ASTOUNDING SUCCESS!
I’ve never lost weight before. My life has been a slow drumbeat of “this is my setpoint weight, I can’t lose any but I don’t gain any” punctuated by “Life event, my setpoint weight is now X lbs higher than it used to be”. I was never able to motivate myself to stick with diets because I was constantly half-assing them, thus not losing weight, thus seeing no point in sticking with a diet that wasn’t losing me weight.
I lost half a pound a day on this potato diet. I am astounded, as is everyone who knows me!
The potato diet is not a willpower diet. Some people saw huge effects even while cheating. Some people saw huge effects on this diet even when they had found other diets super hard in the past.
We understand if you don’t really get this. We didn’t get it either, despite reading about all the previous success stories, until one of us tried the potato diet for ourselves. Hunger vanishes in a really weird way that is hard to describe to anyone who hasn’t felt it directly. So listen to all our participants who are like “no it’s not calories, it’s not willpower”. Or try it for yourself, you might be surprised!
Anyone else who complains about calorie-counting will be thrown directly into the sun.
Carbs make you fat
Some people think that carbs make you fat. But the potato diet seems like bad news for any “carbs make you fat” theory, since potatoes are starchy carbs. More complex versions might still have a leg to stand on, but obviously this finding is a problem for this kind of theory.
We didn’t track the oil people were eating in any rigorous way, but many people had seed oils like canola and peanut oil on their potatoes. Since their diet was otherwise so limited, this seems like a problem for seed oils theory.
On the other hand, the amount of oil they were eating did seem to make a difference for some people. So maybe this is more evidence for “something that is sometimes in oil and sometimes not”. It fits pretty well with contamination theories (more in a bit), or anything else that might vary in oils, perhaps due to factors like different growing conditions.
There are some theories that suggest that the obesity epidemic is the result of what we’ll call “long-term” factors. For example, evolutionary theories say that natural selection is, for some reason, pushing us towards greater body weights over time. Epigenetic theories suggest that things that happened to your parents or grandparents cause obesity, as the result of gene expression.
Developmental theories say that people become more obese later in life because of something that happened to them early on in development or childhood. This recent massive review paper specifically argues “that obesity likely has origins in utero,” i.e. you get obese at 25 because of things that happened to you when you were an embryo.
But the potato diet poses a challenge for these theories. If obesity is caused by something that happened to you in utero, or by something that happened to your grandmother, then how come it can be reversed in a couple of weeks of potatoes? There may be ways to resolve this challenge, but it’s a challenge nonetheless.
Some people have told us, “oh you can eat any one thing and lose weight like this”. Penn Jillette also says this. He told “Good Morning America” in 2016:
It didn’t have to be potatoes, they aren’t magic. I picked potatoes because it’s the funniest word. I could have chosen beans or just almost anything.
We’re not so sure. In particular, why do people think that other mono diets work? We haven’t seen any. We encourage anyone to find anecdotes, studies, or better yet, run their own Onion Diet study or whatever.
The potato diet isn’t even really a mono diet. We explicitly allow for oil and seasonings, and lots of people lost weight with tons of cheat days. The mono-ness (monotony?) of the potato diet clearly is not the active ingredient.
Potatoes are also unusual in that they are (almost) nutritionally complete. You couldn’t do the white bread diet and get far. But you could maaaaaaaybe do the whole wheat bread and oil diet, or the wheat bread and cheese diet. Also known as: the basic daily diet in Europe for centuries.
That said, we do think that studies (maybe more internet community trials) of other very simple diets would be interesting — especially since most cultures historically have had very simple diets, which shows there are many simple diets you should be able to live on indefinitely. So we’d love to see, for example, studies on diets composed exclusively of:
Rice & beans
Rice & fish
Rice & lentils
Buckwheat soba & edamame
Bread & olives / olive oil
(Someone should check that these are nutritionally complete first, though.)
This last one is already close to the Mediterranean diet, but it would be interesting to cut the Mediterranean diet down to literally just bread, olives, olive oil, wine, and cheese. Or literally to just bread and olives / olive oil, if you could survive on that.
So anyways, if you are sure that any mono diet would work, please do run your own study, we want to see it. We’d be happy to discuss study design with you!
Some people put the obesity epidemic down to a factor called “food reward”. They say that people are obese now because food has gotten more delicious, and that the potato diet causes weight loss because potatoes aren’t delicious. An attempt to describe the theory might look something like this:
People are more obese because food is way more fun to eat now. You can even be agnostic about why food is more fun to eat, and maybe it’s a million small reasons. But over time food producers have figured out how to hit that mental g-spot that makes people go YUM, and when you do that, people eat more than they should and they gain weight. The potato diet works because potatoes are boring and so people don’t overeat.
To be frank, we still don’t really get this theory. That is, we don’t think it makes sense.
First, we’re not convinced modern food is more delicious than old-timey foods. They had butter and ham and sugar and ice cream and even donuts back in 1900. Check out our review of foods of the 1920s and 1930s — lots of the food culture was weird, but they also had like, just tons of lard and pie.
Second, if the problem is that Doritos and Kraft Singles have been hyper-engineered by food scientists to be irresistible, then how exactly would the potato diet pry people away from them? If they are irresistible, then it should be really really hard to stop eating doritos and start eating potatoes. But people say that it doesn’t take much or even any willpower to stay on the potato diet, and many people report no cravings. If your model is “people eat the most delicious foods available and cannot help themselves”, then the only way the potato diet could hold people’s attention is if straight potatoes are more delicious and addictive than twinkies.
Frankly we think they are more delicious than twinkies — but if that’s true and food reward is the law of the brain, then fast-food companies should be peddling baked potatoes instead of Snickers bars.
Finally, the food reward perspective predicts that the potato diet works because potatoes are boring so you don’t want to eat them. We think this is also bunkum. Potatoes are great, and everyone knows it. Lots of participants reported not only enjoying potatoes, but liking them more after completing four weeks of the study:
(24235303) I didn’t mind eating potatoes. They were still perfectly tasty throughout, and varying form factor and spices kept things fresh enough.
(02142044) I felt a sort of euphoria/hypomania that lasted from day 17 to day 20, and I’m unsure how to reproduce it … It was both a feeling of well-being, but also the potatoes started feeling delicious, like they were extremely savory.
(29550957) The last two days my family forced me to eat a bunch of other stuff for my birthday and honestly I wasn’t super enthusiastic about it! I wish I could have just been eating more potatoes. I notice I definitely felt worse after eating stuff like cake, and actually felt durably very stuffed for hours afterwards.
(31497197) Overall, I’d say the diet “works” in that I ate as much as I wanted, mostly didn’t crave other food too often, never got sick of potato, and lost weight. On the very relaxed diet, I lost an average of 2lbs/week, and I think that would have been higher with less frying, but commercial food is not conducive to diets at the best of times. … This is really easy, in that I don’t hate potatoes and haven’t gotten sick of them.
(16832193) I was quite surprised that I didn’t get tired of potatoes. I still love them, maybe even more so than usual?!
Participant 57875769, Day 11:
My wife and I went out to eat with a friend and I expected to use today as a cheat day, but honestly potatoes sounded like the best thing on the menu so I ordered hash browns and french fries. The hash browns were very filling on their own so I didn’t eat many of the fries.
And again Day 29:
I’m ending today. It’s weird though, I’m thinking of all the foods I could eat today and I might just stick with potatoes for a lot of my meals. It’s going to feel strange going back to a more varied diet.
So, people come out of the diet saying they love potatoes. Many of them choose to keep eating potatoes even though they’re off the diet. Some of them say they MISS eating so many potatoes. If this isn’t what people mean by “food reward” or “palatability”, then we’re not sure what they mean. If people do mean something else specific, we’d be interested in hearing that.
Same thing for satiety. Yes, potatoes are high satiety, in the sense that you don’t want to eat anything else after you eat potatoes. But why are they high in satiety? Why do they make you not want to eat any more? This is borderline circular reasoning.
Some people think that the obesity epidemic is caused by some kind of problem with the microbiome, the little beasties that live in your digestive system.
This is really a proposed mechanism, rather than a theory of the cause(s) of the obesity epidemic. It doesn’t explain why the microbiome gets so messed up in the modern environment, but this also means it is potentially consistent with many different theories. If high levels of sugar, fat, light exposure, iron supplements, PFAS, lithium, processed foods, or whatever mess up the microbiome, and something in potatoes fixes it, the potato diet would work just about like we see here.
This seems reasonably plausible to us. In particular, many participants report digestive or gastrointestinal changes (both good and bad) on the potato diet, which is about what you would expect if the potato diet were seriously changing your microbiome. One possible limitation is that weight loss does seem to be driven by the brain, but there may be a gut-brain connection that renders this point moot.
That said, we’re not sure how to test this hypothesis any further. We could compare the potato diet to a normal diet supplemented with potato starch, but if the potato starch supplement also caused weight loss, that wouldn’t point to the microbiome specifically, it would just show that the potato starch contains the same active ingredient as the potato diet, whatever that is.
We could also test stool samples, but honestly we don’t know what we would be looking for. Yeah some things would probably change in your microbiome after four weeks of potatoes, and we could see if any of them were correlated with weight loss, but that’s a pretty blunt instrument. What should we actually look for? If anyone has opinions on *exactly* what might be going on with the microbiome, we’d be interested in hearing your theory.
“Processed food makes us fat” is a line that has been pushed by outlets such as the Washington Post and the NIH. The basic idea is pretty simple: ultra-processed foods make you fat, for some reason. People who support this perspective don’t usually say what it is about these processed foods that make them so fattening, but it’s often mindlessly conflated with the food reward theory:
It also doesn’t mean that all processed food is bad. Whole-grain bread and cereal are excellent, and there are good versions of such things as frozen pizza and jarred pasta sauce. Also wine.
What it does mean is that modern industrial food processing — and only modern industrial food processing — has enabled the manufacture of the cheap, convenient, calorie-dense foods engineered to appeal to us that have become staples of our obesogenic diet.
This perspective does seem to predict that the potato diet should cause weight loss, because potatoes are super unprocessed, about the rawest food most people are likely to eat. Participant 20943794 does a nice job pointing out just how unusual potatoes are in this way:
Potatoes are a lot less processed than most food I eat … even the dishes I “make” “myself” have a big pre-made components. For example, when I “make” spaghetti, I used dried noodles that were made in a factory, a jar of sauce that was made in a factory, and beef that was butchered in ground in (at least) an industrial kitchen, if not another factory. The only stuff that’s really raw is the vegetables I chop and add.
So at first glance, the potato diet looks good for the idea that processed foods make you fat.
But there are some problems. First off, even if processed foods make you gain weight, that doesn’t necessarily mean that unprocessed foods will make you lose weight. Foods high in cyanide will kill you, but foods low in cyanide won’t bring you back to life (as far as we know, maybe someone should check).
We also want to say, we really think this is a non-theory. Even assuming processed foods do make you fat, this isn’t a theory (in our opinion) because it doesn’t address the question of WHY processed foods make you gain weight.
For comparison: in this study, we’ve found that eating enough potatoes makes you lose weight. But “the potato theory” isn’t a good explanation for the potato diet; we want to know what about potatoes makes this happen! So we really demand to know what it is about processed food that (potentially) makes people gain weight. Treating “processed foods” as a theory itself is at best circular reasoning (“processed foods make you fat because they are processed foods”).
Not to say that there aren’t potential versions of this idea that do work as a theory. Processed foods might be uniquely low in nutrients that we need to stay lean (potassium?). Or, since they spend so much time in contact with industrial machinery, they might be especially high in obesogenic contaminants.
There are all kinds of contaminants in the environment that didn’t used to be there. We know that some chemicals can cause weight gain in humans and animals. With these two facts in mind, we think it stands to reason that the obesity epidemic could be caused by one or more contaminants that are getting into our brains and messing up our ability to properly regulate our body weight. We presented a version of this theory in our book/series A Chemical Hunger, and while we don’t think it’s a sure thing, we do think that there’s a lot of evidence in favor.
The potato diet is definitely consistent with the contamination theory. Since potatoes are so incredibly unprocessed, they are presumably unusually low in most contaminants. Whatever contaminant you might be concerned about, there is probably less in a plain baked potato than there is in a steak, candy bar, or box of pasta.
The main wrinkle here is that weight loss on the potato diet is so fast, which is a little weird if we assume that the obesity epidemic is caused by contaminants. It seems like something about the potatoes would have to either stop the contaminants from messing with your lipostat, or would have to rapidly flush the contaminants from your body.
Briefly, the lithium hypothesis looks plausible because lithium causes weight gain at clinical doses, and we know people are exposed to more lithium now than they were back in the 1960s. The only thing is, how much lithium do you need to get exposed to before you start gaining weight, and are we getting exposed to at least that much? We’re working on answering these questions, but we have found some evidence that people get exposed to quite a bit in their food (though it’s complicated).
The fact that the potato diet causes weight loss isn’t really strong evidence for or against the lithium hypothesis. But we do want to point out, it’s consistent with the lithium hypothesis.
Potatoes are high in potassium, and there’s evidence that potassium competes with lithium in the brain in interesting ways. If obesity is caused by your brain getting all gummed up with lithium, and potassium makes it stop, then the high levels of potassium in potatoes would be the sort of thing that might cause lots of rapid weight loss.
Participant 02142044 mentioned this hypothesis:
You probably already know this, but I find it credible a potential reason as to why the diet works, if it does, is that it is helping clear lithium, which would also help explain the mild hypomanias people experience. https://jasn.asnjournals.org/content/10/3/666 seems to indicate that potassium and sodium can help with clearing lithium. That is also why I started salting more.
The fact that the potato diet causes hypomania in some people and fear & grief effects in others is also maybe consistent with lithium, since lithium is both an antimanic and a sedative.
Another mark in favor is that we do have some idea of what foods may be high in lithium, and there are a few hints that these foods can boot people out of potato mode and stop their weight loss. In particular, we have reason to think that tomatoes are often high in lithium, and one of our participants reported this:
Another food group that we think is often high in lithium is dairy, and there’s again some evidence that eating dairy can limit the potato diet. Consider this story from participant 29550957:
This is pretty much the best diet I’ve ever been on, including earlier this year when I also ate mostly potatoes- but with tons of dairy (butter, sour cream, cheese) on them. Despite literally messing up an entire week’s worth of days, I seem to be durably down about 10lbs.
If this is the case, then cheating on foods that are low in lithium should always be fine, and may explain why people were able to cheat on this diet so much and still see the effects.
Cheating on foods that CAN be high in lithium is a gamble. A crop that concentrates lithium won’t grab much if it’s grown in a lithium-poor environment, but will be totally loaded if it’s grown in a lithium-rich environment. So it’s quite possible that that e.g. some ketchup is loaded with lithium and some isn’t, depending on where it was grown, how it was processed, etc. This would look like ketchup making a huge difference for some people and not at all for others.
Unfortunately we still don’t have a great list of which foods are high and which are low in lithium. The list we do have, we don’t particularly trust, which is why we are gonna do our own survey of the food supply.
However if we had to guess right now, our best bets for foods that are high in lithium (and if this hypothesis is correct, might inhibit the potato diet) are: Eggs, milk, soft cheeses (but maybe not butter or hard cheese?), anything containing whey, tomatoes, goji berries, leafy greens, beef, pork, carrots, and beets. But again, this list ain’t gospel.
If the lithium-potassium competition hypothesis is true, other high-potassium, low-lithium diets might also cause weight loss. There’s a little bit of evidence that potassium consumption is related to successful weight loss, which makes this seem plausible.
But straight potassium supplementation may or may not work. At first we thought you could just give people potassium salt and see what happened, but we talked to a specialist who studies lithium clearance from the brain, and he said that the bioavailability of potassium from different sources complicates this a lot. We’re still trying to figure out what a good design for this study would be, but it’s not necessarily as simple as “consume a lot of potassium, avoid tomatoes and whey, and lose a lot of weight”, though we suppose someone could try it and see.
Looking at lithium and potassium in the urine of someone doing the potato diet might help with this, and so we’re considering asking for urine samples in future studies. But it might also be inconclusive.
For example, maybe lithium raises your lipostat set point by gumming up the brain somehow, and high levels of potassium lower the set point by increasing lithium clearance and forcing it all out of the brain. Lithium that gets forced out of the brain has to go somewhere, and if this were the case, it would probably end up in the urine, so you would see elevated levels of lithium in people who enter potato mode.
But maybe lithium causes obesity by forcing potassium out of the brain, and high levels of potassium cure obesity by supplementing potassium faster than the lithium can clear it. If something like this were the case, you might not see more lithium in people’s urine when they go on the potato diet.
Probably neither of these explanations are exactly correct — these are just examples to show that urine tests during the potato diet might be a good idea, but won’t be conclusive.
Something else about Potassium
But it’s also not like potassium and lithium are married. Potassium could still cause weight loss even if the lithium hypothesis is totally wrong. Potatoes are notorious for being high in potassium, so it’s reasonable to suspect that this might be the active ingredient.
That said, if it’s not lithium, why would potassium cause weight loss? We don’t know. Any ideas?
Don’t most theories predict weight loss on the potato diet?
Well, yes and no. Many theories do predict weight loss on the potato diet; but most theories don’t predict potato mode, this state where hunger disappears and you (occasionally) feel charged with incredible energy.
Finally, to anyone who thinks they knew it would work in advance…
Ok wise guy.
If you predicted (or could have predicted) that the potato diet would cause this kind of weight loss, or if medical / nutritional science could have predicted that this diet was going to be so effective in the short term, and so easy for so many people — then why haven’t doctors and nutritionists been recommending the potato diet to people alongside diet and exercise?
“I personally would not recommend it,” says Dr. Nadolsky. “It’s very restrictive. A vegan diet is very restrictive and a ketogenic diet is very restrictive, but a potato diet is one of the most restrictive diets you could ever do.” … the diet itself would be very hard to stick with for most people, says Dr. Nadolsky.
This type of extreme diet can pose serious health risks due to its severe limitations. “While there’s no doubt that potatoes — just like all vegetables — are supremely nutritious, eliminating almost all other food groups in totality is not only dangerous, but can really backfire,” says Jaclyn London, M.S., R.D., Nutrition Director at the Good Housekeeping Institute.
If you knew the potato diet would work, why did you not run this study many years ago? Why are there no clinical trials? Did you think people would not be excited to see this result?
Guess the NIH is too scared of the tater.
8. How to Potato Diet if you want to Potato Diet
We’re not currently accepting signups, but we know that some of you will want to try the potato diet for yourselves. So here is some current advice, from us and from some participants.
First, our advice:
When you start off, try eating mostly (> 95% of your calories) potatoes, with a little oil, and as much hot sauce and salt as you want. You can also have zero-calorie beverages like black coffee and tea. This seems really strict but many people find it to be much easier than they expected, so give this version a try first.
If you feel bad/weird and are like “I can no longer stand potatoes!”, try:
Eating a potato. Hunger feels different on this diet and you may not realize that you are hungry. Yes, really.
Drinking water. It’s really easy to get dehydrated on this diet, and again you can’t always tell.
Eating a different kind of potato. There are many varieties, try mixing it up. You will almost certainly want to eat more than one kind of potato.
Peeling your potatoes. Eating less peel / no peel seems to help some people with digestive and energy issues, especially after a few days on the diet.
Eating more salt. Potatoes are naturally low in sodium and you may not be getting enough.
Getting sunlight. Potatoes have no vitamin D, you may be craving that.
If none of these other things help, do a cheat meal and eat whatever you’re craving. (But maybe still avoid dairy?) If you find you keep taking cheat meals, go ahead and drop down to the 80%, 60%, or even a lower % potato diet. The 40% potato diet works just fine for some people.
If you still feel bad after trying these steps, stop the diet. If you are suffering then the diet isn’t working anyways, and you shouldn’t take risks with your health. Plus life is too short to do things that make you miserable.
If the diet is easy but you’re not losing weight (or otherwise not seeing effects), try doing 100% potato, no oil.
And here’s some advice from participants:
(33217580) I found that despite all the warnings, it was really easy to underprepare and end up with not enough food. The days where I either had done enough prep or just had time to go cook were definitely much simpler than the days where I would have been happy to just eat some boiled potatoes, but sadly the tupperware was empty, and I got really hungry, ate chips or fries, was a little lower on energy or moodier etc. If I’m going to continue (and I might, because it worked so well!), I’m going to aim for comically large proportions in food prep, because then I might actually have something close to enough.
(31664368) Advice: figure out a way to exit the diet gracefully. I have a robust belly, but significant GI issues I am still going through. Perhaps it was 1 thing I ate that set things on a bad track for several days. Trying oatmeal and crackers as easy non-potato food, but would love a playbook of how to get back to feeling solid after eating a burrito.
(14122662) If I were doing this again, I might also invest in a nice knife. I noticed that chopping the potatoes each day was effortful and a strain on my hand. Being able to slice through the potatoes more cleanly would have been a nice convenience.
(63187175) It requires a lot of preparation and staying ahead of your meals. Potatoes aren’t something you can just grab out of the cupboard and eat, there’s always some amount of cooking required and (at least in my limited experience) that cooking is either quite labor or time intensive (and usually both). If I do this again, my main takeaway lesson is that to be successful in sticking to it, I need to very deliberately over-prepare and always make way more than I want at a time. Just-in-time preparation is way too hard to follow. When I get home from a long day at work and discover that there are no potatoes already made, those were always the moments when I absolutely hated this diet. Even worse, I ran out of potatoes many times during these 3 weeks and had to take a trip to the store before I could even start cooking. Another area where I’d be more diligent if I try this again.
(02142044) How I’d do it again
– Ensure that my weighing scale is reliable
– Keep not using oil
– Stick to the diet strictly throughout
– Only eat potatoes boiled in their own water (mostly or only yellow?).
– Buy them in bio market if possible?
– Probably still eat sweet potatoes weekly for vit A?
– No exercises during this period.
– Do it in a period with less changes in my life overall (no medication, no changing location in between, no big relationship changes, etc)
– Keep filtering water throughout
– Change the way I track thing:
* Note how much kg of potatoes I eat each meals.
* Change “Mood” to “Lowest low”, “Highest high”, “Irritability”, “Fluctuation” and “Highest calm/plenitude”
* Keep track of “How tired am I of this diet?”
* Also note what is happening in my life to see other kinds of corelations.
– Supplement in B12 way more, salt my meals from the beginning
– No garlic. Cayenne pepper and tabasco are okay
(81125989) Advice to others trying the diet:
Feeling lazy? Trader Joe’s olive-oil Kettle-cooked potato chips for the win. Only three ingredients – potato, olive oil, and salt.
Choose cooking methods that are very low-prep-time, yet high-bulk. At first, I sliced potatoes before baking – this took over an hour each time and only made enough for one meal. Eventually, I realized I could just cut slits in whole potatoes, coat ’em in olive oil & salt, and dump ’em in the oven. Easy & makes enough for 2 days.
Variety is the spice of potato life. Get different kinds of potato, or you will get so intensely bored. (Also, get sweet potatoes for Vitamin A. Maybe placebo, but I noticed my evening low-light vision got worse, but improves the day after I eat sweet potato)
Schedule cheat days? I’ll have to wait to see your full analysis on the dose-response of the potato diet (weight loss vs days cheated)… but if the dose-response is good, then I recommend scheduling cheat days to stave off boredom. (Also, for social eating.) In particular, I ate red meats to get my B12. You can also eat liver or clams. Also potato has no Vitamin D, go get lots of sun or eat dairy/fatty fishes. (I don’t trust supplements; every time I’ve looked at a pre-registered RCT of a vitamin supplement, it’s either near-zero or somehow way less than just eating a whole food that’s known to be a source of it.)
– Buy lots of potatoes. Bake off or boil off five or ten pounds every couple days, then refrigerate to eat, mash, fry as wedges, roast as cakes, etc.
– Takiea baked potato that can be microwaved as needed, and or a small tupperware thing of mashed potato with some chilli/garlic/hot sauce in it when going places for long enough that being hungry will come up, but tables/utensils/microwaves etc will be available.
– Properly flavored mashed can be used as a dip for potato chips or something when going camping, etc.
– If with a group at a restaurant, order fries, or just have a beer. The mashed potato might be full of dairy fat.
– When eating non-potato snacks, make a note and carry on. Make sure they aren’t dairy.
– Make peace with breaking the diet for a meal every so often. It will happen sooner or later. Try not to, but eventually (group camping, or a nice restaurant, or something) it will be better to break the diet than not. Do so, and get back on potato immediately afterwards.
(21112694) While I only did about five whole days of the diet, I would highly recommend a 1-2 day transition off the diet. The day I ended, I went out for an event and had a large dinner which my digestive tract was not ready for. I typically have no issues with my GI tract, so I figured it wouldn’t be an issue given the shorter diet period. It could have just been a one-off random occurrence, but if you see this trend pop up more, it may be beneficial to suggest a slower transition off the diet, especially for those with GI issues like IBS (I don’t have any).
9. What’s Next
We’re very happy with this study, but there are some major limitations. Almost all of our participants were white, and most of them were Americans. We expect these results will generalize to other groups in other contexts, but frankly it’s not in the data.
The potato diet definitely causes weight loss, but a few major questions remain. Questions like, why do some people hit a wall immediately, and find the diet impossible after only a few days? Why do a few people suddenly hit a wall after about 3 weeks?
What’s up with cheat days? Does the 80% potato diet work for everyone? Can some people lose weight on the 40% potato diet? What about the 20% potato diet? The SMTM author who tried the potato diet didn’t lose any weight until they cut out all oil, at which point they started losing about a pound a day. So for some people it seems like the 100% potato diet is really necessary? Is that true? Why would that be?
Is the attrition rate really higher, and is the diet more difficult, for women / people with two X chromosomes? If so, why? What about trans people? If there’s a chromosomal effect, how does it interact with exogenous hormones?
All of these are questions that would be good to answer in future work.
Our current plan is to follow up with our participants in 6 months, 1 year, and 2 years (assuming it’s still interesting/relevant at that point). We’ll make posts with those results, and share the data publicly, as these followups happen, so look for the first followup post about six months from now.
We may also go back into these data and do more analyses, since there are almost certainly more things to find in the data we’ve already collected.
Also, expect a forthcoming post on reflections about doing this kind of shoestring internet science. Keep your eyes peeled.
We’re not currently taking signups, but if you want to try the potato diet for yourself, why not track your data using a structured spreadsheet, so all resulting data will be standardized. You’re welcome to download a copy of THIS FORM and follow the instructions, and you can send us an email with your copy of the form when you’re done. Just include the words “Potato Diet” in the email title so the emails are easy to sort and track.
If we can secure funding, our next study may be “potato camp”, a project where we send 20 or more overweight & obese volunteers to a summer camp and serve them nothing but potatoes for four weeks. This would allow us to replicate these results in a slightly more controlled fashion, collect things like urine and serum samples, and so on. And it would be a pretty good deal for participants — we’d make sure there’s wifi, so if you have a remote job, you can just drop by for four weeks and keep working as normal. If you’d be interested in attending potato camp, SIGN UP HERE. If you’d be interested in funding this project, contact us.
We might also run other studies, but we’re still figuring out what would be the best and most fun use of our time. Maybe we will run something on potassium. Or maybe our next study will be unrelated to obesity, it’s not the only interesting research topic in the world.
If you would like to be notified of future stupid studies like this one, SIGN UP HERE. You can also just subscribe to the blog itself by email (below), or follow us on twitter, if you want to keep up with our work in general.
And if you feel like reading this post has added a couple of dollars’ worth of value to your life, or if you have lost weight on the potato diet and you think it improves the quality of your life by more than one dollar a month, consider donating $1 a month on Patreon.
Thanks for going on this journey with us.
Sincerely, Your friendly neighborhood mad scientists, SLIME MOLD TIME MOLD
The TDS approach is pretty intuitive: if you want to study contaminants or residues that people are maybe exposed to through their food, one way to do that is to drive around to a bunch of actual grocery stores and supermarkets, buy the kinds of foods people actually buy and eat, prepare the foods like they’re actually prepared in people’s homes, and then test your samples for whatever contaminants or residues you’re concerned about.
A Total Diet Study (TDS) generally consists of selecting, collecting and analysing commonly consumed food purchased at retail level on the basis of food consumption data to represent a large portion of the typical diet, processing the food as for consumption, pooling the prepared food items into representative food groups, homogenizing the pooled samples, and analysing them for harmful and/or beneficial chemical substances (EFSA, 2011a). From a public health point of view, a TDS can be a valuable and cost effective complementary approach to food surveillance and monitoring programs to assess the presence of chemical substances in the population diet and to provide reliable data in order to perform risk assessments by estimating dietary exposure.
These papers include measurements of trace elements in various foods, and some of them include measurements for lithium. We didn’t find these papers while writing our first review of the levels of lithium in food and drink because these papers aren’t looking for lithium specifically — they’re looking at all sorts of different contaminants and minerals, and lithium just happens to sometimes make the cut.
But anyways, several of these papers do include measurements of lithium in various national food supplies, and they’re strange, because unlike every other source we’ve seen, which all routinely find some foods with more than 1 mg/kg lithium, they find less than 0.5 mg/kg lithium in every single food.
TDS with Li
The oldest TDS study we’ve seen that includes lithium is from 1999 in the United Kingdom, reporting on the UK 1994 Total Diet Study and comparing those results to data from previous UK Total Diet Studies. (The UK TDS has been “carried out on a continuous annual basis since 1966” but it seems like they only started including lithium in their analysis in the 1990s.) They report the mean concentrations of 30 elements (aluminium, antimony, arsenic, barium, bismuth, boron, cadmium, calcium, chromium, cobalt, copper, germanium, gold, iridium, iron, lead, lithium, manganese, mercury, molybdenum, nickel, palladium, platinum, rhodium, ruthenium, selenium, strontium, thallium, tin, and zinc) in 119 categories of foods, combined into 20 groups of similar foods for analysis.
The highest mean concentration of lithium they found in the food categories they examined was an average of 0.06 mg/kg (fresh weight) in fish. They estimated a total exposure of 0.016 mg lithium a day, and an upper limit of 0.029 mg a day, in the British diet at the time. This appears to be substantially less than the amount found in a 1991 sample, which gave an estimate of 0.040 mg lithium a day in the British diet. They explicitly indicate there is no data on lithium in foods (in their datasets) from before 1991.
France conducted a TDS in 2000, and a report all about it was published in 2005. They looked at levels of 18 elements (arsenic, lead, cadmium, aluminium, mercury, antimony, chrome, calcium, manganese, magnesium, nickel, copper, zinc, lithium, sodium, molybdenum, cobalt and selenium) in samples of 338 food items.
The highest mean concentration of lithium they found in the food categories they examined was an average of 0.123 mg/kg in shellfish (fresh matter) and 0.100 mg/L in drinking water. They estimated an average daily exposure of 0.028 mg for adults, with a 97.5th percentile daily exposure of 0.144 mg. They specifically mention, “drinking waters and soups are the vectors contributing most (respectively 25–41% and 14–15%) to the exposure of the populations; other vectors contribute less than 10% of the total food exposure.”
France did another TDS in 2006, with a report published in 2012. This time they looked at Li, Cr, Mn, Co, Ni, Cu, Zn, Se and Mo in 1319 samples of foods typically consumed by the French population.
Similar to the first French TDS, the highest mean concentration of lithium they found in the food categories they examined was an average of 0.066 mg/kg (fresh weight) in shellfish. But the highest individual measurements were found in two samples of sparkling water, with 0.612 mg/kg and 0.320 mg/kg.
New Zealand seems to run a Total Diet Study programme every 4–5 years since 1975, but we’ve only been able to find lithium measurements from this project in a paper from 2019, looking at data from the 2016 New Zealand Total Diet Study. Maybe, like some of the other TDS projects, they only started including lithium testing later on. Anyways, in this paper they looked at 10 elements (antimony, barium, beryllium, boron, bromine, lithium, nickel, strontium, thallium and uranium) in eight composite samples each of 132 food types.
This paper is a little strange, and unlike most of these papers, doesn’t give much detail. They summarize the main findings for lithium as, “the reported concentrations ranged from 0.0007 mg/kg in tap water to 0.54 mg/kg in mussels” and say that the mean overall intake of lithium in New Zealand adults is 0.020–0.029 mg/day.
The most recent TDS that looked at lithium seems to be this 2020 paper, which looks at food collected between October 2016 and February 2017 in the Emilia-Romagna Region in Italy. They looked at levels of fifteen trace elements (antimony, barium, beryllium, boron, cobalt, lithium, molybdenum, nickel, silver, strontium, tellurium, thallium, titanium, uranium, and vanadium) in 908 food and beverage samples from local markets, supermarkets, grocery stores, and community canteens.
The highest concentration of lithium they found in the food categories they examined was in fish and seafood (50th percentile 0.019 mg/kg, IQR 0.010–0.038 mg/kg), and legumes (50th percentile 0.015 mg/kg, IQR 0.006–0.035 mg/kg). They estimate a dietary lithium intake for the region of 0.018 mg/day (IQR 0.007–0.029 mg/day).
So overall, these papers report that lithium levels in foods and beverages never break 0.612 mg/kg, and almost universally keep below 0.1 mg/kg.
How About Those Numbers
We’re skeptical of these numbers for a couple of reasons.
The TDS papers say that all foods and beverages contain less than 1 mg/kg lithium, and that people’s lithium intake is well below 1 mg a day. But this is up against sources like the following, which all find much higher levels (not an exhaustive list):
Bertrand (1943), “found that the green parts of lettuce contained 7.9 [mg/kg] of lithium”
Borovik-Romanova (1965) “reported the Li concentration in many plants from the Soviet Union to range from 0.15 to 5 [mg/kg] in dry material”, in particular listing the levels (mg/kg) in tomato, 0.4; rye, 0.17; oats, 0.55; wheat, 0.85; and rice, 9.8.
Ammari et al. (2011), looked at lithium in plant leaves, including spinach, lettuce, etc. and found concentrations in leaves from 2 to 27 mg/kg DM.
Manfred Anke and his collaborators found more than 1 mg/kg in a wide variety of foods, in multiple studies across multipleyears, up to 7.3 mg/kg on average for eggs.
Schnauzer (2002) reviewed a number of other sources finding average intakes across several locations from 0.348 to 1.560 mg a day.
Five Polish sources from 1995 that a reader recently sent us reported finding (as examples) 6.2 mg/kg in chard, 18 mg/kg in dandelions, up to 470.8 mg/kg in pasture plants in the Low Beskids in Poland, up to 25.6 mg/kg in dairy cow skeletal muscle, and more than 40 mg/kg in cabbage under certain conditions. (These papers aren’t available online but we plan to review them soon.)
It seems like either the measurements from the TDS papers are right, and all foods contain less than 1 mg/kg lithium, or all the rest of the literature is right, and many plants and foods regularly contain more than 1 mg/kg lithium. The alternative, that both of them are right, would mean that the same foods consistently contain less than 1 mg/kg in France and New Zealand while containing more than 1 mg/kg in Germany and Brazil. This seems like the most far-fetched possibility.
There are three strikes against the TDS numbers. First, they’re strictly outnumbered. When five papers from four sources (two of those papers are from France) say one thing and the rest of the literature clearly says another, it’s not a sure thing, but the side with more evidence… well it has more evidence for it.
Second, the TDS studies have a divided focus. They’re not really interested in lithium at all; they’re interested in the local food supply, and lithium just happens to be one of between 9 and 30 different elements they’re testing for. In comparison, pretty much all the other papers are looking at lithium in particular. If we had to guess which kind of team is more likely to mess up this kind of analysis, the team interested in this one particular element, or the team that randomly included the element in the list of several elements they’re testing for, we know which we’d pick. It’s hard to imagine that every team looking for lithium chose the wrong analysis or screwed it up in the same way somehow. It’s easy to imagine that the TDS studies, which measured lithium incidentally, might get some part of the analysis wrong.
It’s kind of like clothing. Ready-made sizes will fit most elements, but if you have an unusual body type (really long arms, really thick neck, etc.) you may have to go to a tailor. And lithium has the most unusual body type of all the solid elements. It wouldn’t be at all surprising if off-the-rack clothes didn’t fit poor little lithium.
The third thing that’s strange is that there seem to be some internal contradictions within the studies. For example, in the first French TDS study, the lithium levels in water are much higher than lithium levels in things that are made out of water, which seems impossible. The mean lithium level in drinking water is 0.100 mg/kg, but the lithium levels in things that are mostly water are much lower: 0.038 mg/kg in soups, 0.006 mg/kg in coffee, 0.004 in non-alcoholic beverages, 0.003 in alcoholic beverages, and 0.002 in hot beverages. Soup is maybe a little different, but coffee and beverages are mostly water. How can there be fifty times more lithium in plain water than in hot beverages, which are (we assume) mostly water?
For that matter, how can drinking water be the category with the second-most lithium (after shellfish)? Water is the main ingredient in beverages, but it’s also a major ingredient of pretty much every food. Fruits, salads, milk, vegetables, etc. etc. all contain lots of water. Unless there’s some major, universal filtering going on, there should be more lithium in at least some foods than there is in water.
And that’s what you see if you look at the other elements in this first French paper — more in foods than in water. For example, the average level of manganese in drinking water in these data is 0.19 mg/kg, and the mean levels in beverages are all 0.30 mg/kg or higher; the mean level in soup is 0.97 mg/kg; the mean level in fruits is 2.05 mg/kg, much higher. Same for zinc. The mean level in drinking water is 0.05 mg/kg, which is the lowest mean level of zinc of any food category. Other elements, at least, tend to have higher concentrations in some foods than in water.
In the second French TDS study, the same thing happens. The highest concentration of lithium they found in any food was in water, 0.612 mg/kg. The mean for water this time around was only 0.035 mg/kg, but that’s still higher than the means for most beverages and the mean for almost every food.
(The other TDS papers don’t give mean lithium measurements for water, so we can’t do the same comparison with them.)
This doesn’t make much sense. Water is a major component of many foods and it would be shocking if lithium didn’t find its way from water into food (and more obviously into beer and tea). But all of the fruits and vegetables have less lithium than the water that would presumably be used to irrigate them.
There’s a rich literature of hydroponics experiments that shows that all sorts of plants accumulate lithium. When you grow them in a lithium solution under controlled conditions, or in soil spiked with lithium, the plants end up containing a higher concentration of lithium than the solution/soil they were grown in.
These spikes are much larger than the levels of lithium plants are normally exposed to in the environment, but they’re experimental evidence that lithium accumulates, even to enormous degrees. You should reliably expect to see more lithium in plants than in the water they’re grown with. There might be some plants that don’t accumulate, but water shouldn’t universally contain the highest amounts.
We didn’t really include these sources in our original review because that was a review of lithium in food, and these hydroponically-grown experimental plants aren’t in the actual food supply. But they’re pretty informative, so here’s a selection of the studies:
Magalhães et al. (1990) grew radish, lettuce and watercress in a hydroponic system, with solution containing lithium levels of 0.7, 6.8 and 13.6 mg/L. These are all somewhat high, but exposure to 0.7 mg/L in water isn’t totally unrealistic. Plants were collected thirty days after transplanting. At the lowest and most realistic level of exposure, 0.7 mg/L, lettuce contained 11 mg/kg lithium, radish bulbs contained 11 mg/kg, radish leaves contained 17 mg/kg, and watercress contained 37 mg/kg. At 6.8 mg/L in the solution all plants contained several hundred mg/kg, and at 13.6 mg/L, radish leaves and watercress contained over 1000 mg/kg.
Hawrylak-Nowak, Kalinowska, and Szymańska (2012) grew corn and sunflower plants in glass jars containing 0 (control), 5, 25, or 50 mg/L lithium in a nutrient solution. After 14 days, they harvested the shoots, and found that lithium accumulated in the shoots in a dose-dependent manner. Even in the control condition, where no lithium was added to the solution, sunflower shoots contained 0.9 mg/kg and corn shoots contained 4.11 mg/kg lithium. At 5 mg/L solution, sunflower contained 422.5 mg/kg and corn contained 72.9 mg/kg; at 25 mg/L solution, sunflower contained 432.0 mg/kg and corn contained 438.0 mg/kg; at 50 mg/L solution, sunflower contained 3,292.0 mg/kg and corn contained 695.0 mg/kg. These levels are unrealistically high, but the example is still illustrative.
Kalinowska, Hawrylak-Nowak, and Szymańska (2013) grew lettuce hydroponically in solution containing 0, 2.5, 20, 50 or 100 mg/L lithium. Lithium concentrations above 2.5 mg/L progressively fucked the plants up more and more, but there was clear accumulation of lithium in the lettuce. There was some concentration in the leaves in a solution of 2.5 mg/L (though they don’t give the numbers), and when the lettuce was grown in a 20 mg/L solution, there was around 1000 mg/kg in the leaves.
Antonkiewicz et al. (2017) is an unusual paper on corn being grown hydroponically in solutions containing various amounts of lithium. They find that corn is quite resistant to lithium in its water — it actually grows better when exposed to some lithium, and only shows a decline at concentrations around 64 mg/L. (“The concentration in solution ranging from 1 to 64 [mg/L] had a stimulating effect, whereas a depression in yielding occurred only at the concentrations of 128 and 256 [mg/L].”) But the plant also concentrates lithium — even when only exposed to 1 mg/L in its solution, the plant ends up with an average of about 11 mg/kg in dry material.
Robinson et al. (2018) observed significant concentration in the leaves of several species as part of a controlled experiment. They planted beetroot, lettuce, black mustard, perennial ryegrass, and sunflower in controlled environments with different levels of lithium exposures. “When Li was added to soil in the pot experiment,” they report, “there was significant plant uptake … with Li concentrations in the leaves of all plant species exceeding 1000 mg/kg (dry weight) at Ca(NO3)2-extractable concentrations of just 5 mg/kg Li in soil, representing a bioaccumulation coefficient of >20.” For sunflowers in particular, “the highest Li concentrations occurred in the bottom leaves of the plant, with the shoots, roots and flowers having lower concentrations.”
Again, these are unrealistic for the amount of lithium you might find in your food, but they’re clear support for the idea that plants consistently accumulate lithium relative to the conditions they’re grown in. It doesn’t make sense that we see water having the highest concentration in the TDS data.
So for all these reasons, we’re pretty sure that the TDS numbers are wrong and that the lithium-specific literature is right. Specialty research that looks for lithium in particular is more reliable in our opinion than sources that happen to look at lithium as one contaminant along with a dozen others.
But even so, you’d have to be terminally incurious to look at this and not wonder what was going on. Why do these five papers have measurements that don’t match the rest of the literature?
What’s Going on in the TDS
Since these papers disagree with every other source, and they all share the same Total Diet Study approach, it seems like there must be something wrong with that approach.
Sometimes this kind of mistake can come from problems with the equipment, dropping a decimal, or misreading units, like mistaking mg/kg for µg/kg.
But we have a hard time imagining that all of these different teams with (as far as we can tell?) no overlap in authors would be making exactly the same error of using the wrong units or moving a decimal place. It’s possible they all use the same slightly-misleading software or something; we have seen a few other papers that report lithium in one set of units, and every other element they test for in different units. But again, it would be weird for every single TDS study to screw this up in exactly the same way.
Samples of each food group … were homogenized and digested (0.5 g) in inert plastic pressure vessels with nitric acid (5 ml) using microwave heating (CEM MDS 2000 microwave digestion system). All elements except mercury, selenium and arsenic were analysed by Inductively Coupled Plasma-Mass Spectrometry (ICP-MS) (Perkin Elmer Elan 6000).
The elementary analyses (about 18 000 results in all) were carried out by the Environmental Inorganic Contaminants and Mineral Unit of the AFSSA-LERQAP, which is the national reference laboratory. All the 998 individual food composite samples were homogenized and digested (about 0.6 g taken from each sample) in the quartz vessels with suprapure nitric acid (3 ml) using Multiwave closed microwave system (Anton-Paar, Courtaboeuf, France). The total content of all selected essential and non essential trace elements in the foods was determined by Inductively Coupled Plasma-Mass Spectrometry (ICP-MS) (VG PlasmaQuad ExCell-Thermo Electron, Coutaboeuf, France), a very powerful technique for quantitative multi-elemental analysis.
The National Reference Laboratory (NRL) for heavy metals was chosen to analyse 28 trace elements, and among them nine essential elements, Li, Cr, Mn, Co, Ni, Cu, Zn, Se and Mo, by inductively coupled plasma-mass spectrometry (ICP-MS) after microwave-assisted digestion.
Sample digestion was carried out using the Multiwave 3000 microwave digestion system (Anton-Paar, Courtaboeuf, France), equipped with a rotor for 8 type X sample vessels (80-mL quartz tubes, operating pressure 80 bar). Before use, quartz vessels were decontaminated in a bath of 10% HNO3 (67% v/v), then rinsed with ultra-pure water, and dried in an oven at 40 °C. Dietary samples of 0.2–0.6 g were weighed precisely in quartz digestion vessels and wet-oxidised with 3 mL of ultra-pure water and 3 mL of ultra-pure HNO3 (67% v/v) in a microwave digestion system. One randomly-selected vessel was filled with reagents only and taken through the entire procedure as a blank. The digestion program had been optimised previously (Noël, Leblanc, & Guérin, 2003). After cooling at room temperature, sample solutions were quantitatively transferred into 50-mL polyethylene flasks. One hundred microlitres of internal standard solution (1 mg L−1) were added, to obtain a final concentration of 2 μg L−1, and then the digested samples were made up with ultrapure water to the final volume before analysis by ICP-MS.
ICP-MS measurements were performed using a VG PlasmaQuad ExCell (Thermo, Courtaboeuf, France). The sample solutions were pumped by a peristaltic pump from tubes arranged on a CETAC ASX 500 Model 510 autosampler (CETAC, Omaha, NE).
We measured content of fifteen trace elements (antimony, barium, beryllium, boron, cobalt, lithium, molybdenum, nickel, silver, strontium, tellurium, thallium, titanium, uranium, and vanadium) in 908 food and beverage samples through inductively coupled plasma mass spectrometry.
Using a clean stainless-steel knife, we cut solid foods by collecting samples from six different points in the plate. Then, we homogenized the samples using a food blender equipped with a stainless-steel blade and we placed a portion of 0.5 g in quartz containers previously washed with MilliQ water (MilliQPlus, Millipore, MA, USA) and HNO3. We liquid-ashed the samples with 10 ml solution (5 ml HNO3 + 5 ml·H2O) in a microwave digestion system (Discover SP-D, CEM Corporation, NC, USA) and we finally stored them in plastic tubes, and diluted to 50 ml with deionized water before analysis. Using an inductively coupled plasma mass spectrometer (Agilent 7500ce, Agilent Technologies, CA, USA), we performed trace element determination.
So, all of these papers use the same analysis technique, ICP-MS. We don’t know the exact technique used by the team in New Zealand, but all the other teams used microwave digestion with nitric acid (HNO3). Three of them (the French and Italian TDS studies) used quartz vessels.
The fact that all these studies use similar analysis techniques makes it much more plausible that something about this technique is screwing up something about the lithium detection.
This also seems likely because most other papers, the ones that find more than 1 mg/kg lithium in food, don’t use ICP-MS. Here’s a small selection.
The most recent paper finding more than 1 mg/kg lithium in plant matter seems to have used inductively coupled plasma optical emission spectrometry (ICP-OES), a related but distinct technique. This is Robinson et al. (2018), which found that plants can contain “several hundred mg/kg Li” in leaves. Here’s their procedure:
Plant samples were washed in deionized water and dried at 60 °C until a constant weight was obtained. Subsequently, they were milled using a Cyclotech type 1093 cyclone grinder with an aluminium rotor. Plant material (0.5 g) was digested in 5 ml HNO3. The digests were diluted with Milli Q (Barnstead, EASYpure RF, 18.3 MΩ-cm) to a volume of 25 ml and filtered with a Whatman 52 filter paper (pore size 7 μm). … Pseudo-total element concentrations (henceforth referred to as “total”) were determined in the acid digests using ICP-OES (Varian 720 ES).
Ammari et al. (2011), looked at lithium in solids (plant leaves, including spinach, lettuce, etc.) and found concentrations in leaves from 2 to 27 mg/kg DM. They used this procedure:
Collected leaves were gently washed in distilled water, air-dried, and then oven-dried to a constant weight at *70°C. Dry leaves were finely ground in a Moulinex Mill (Moulinex, Paris, France) to pass through a 40-mesh sieve. As Li is known to be present in cell vacuoles in inorganic soluble form, Li was determined in filtrates of oven-dry ground leaf samples (5 g) suspended in 50 ml of deionized water for 1 h. This procedure was used in the current study because not all the lithium present in natural unprocessed foods is taken up by the human body (pers. comm. with nutritionists; Dr. Denice Moffat, USA). Lithium extracted with deionized water represents the soluble fraction that is directly taken up by the gastrointestinal tract and considered the most bio-available. … The concentration of Li in leaf samples was measured with a flame photometer.
Anke’s 2005 paper doesn’t give a ton of detail, but seems to have used atomic absorption spectroscopy (AAS) for lithium, and reports numbers up to 7.5 mg/kg in foods.
Thirty days after transplanting, the plants were harvested, shoots and roots separately, and their fresh weight determined. They were oven-dried at 700C for 72 hours, weighted, ground in a Wiley mill and analyzed for N, P, K, Ca, Mg, Fe and Li contents after digestion in H2SO4 and H202. N was determined by Nesslerization, P by an ammonium molybdate-amino naphthol sulfonic acid reduction method (Murphy & Riley 1962), K and Li by flame emission and Ca, Mg and Fe by atomic absorption (Sarruge & Haag 1974).
Drinkall et al. (1969), one of our oldest sources, found up to 148 mg/kg in pipe tobacco and used “the atomic absorption technique”. Specifically they say:
Methods for determination of lithium in foodstuffs have in the past been limited almost entirely to the use of the spectrograph and the flame photometer. In the present investigation, however, it was decided to apply the technique of atomic absorption for this purpose. The chief reason for this choice was the lack of occurrence of spectral interference occasioned by elements other than lithium, Indeed, the only elements which were thought likely to prove troublesome were calcium and strontium. Even these, however, were found not to interfere. The instrument used throughout this work was the Unicam SP90 Atomic Absorption Spectrophotometer, a propane-air flame being employed.
So this diverse set of methods all found levels of lithium above 1 mg/kg, while the “ICP-MS with microwave digestion in nitric acid (usually in quartz vessels)” technique seems to reliably find way less than 1 mg/kg. This is starting to look like it’s an issue with the analysis.
If this is the case, then if we can find other papers that use ICP-MS with microwave digestion in nitric acid, they should also show low levels of lithium, well below 1 mg/kg.
That’s exactly what we’ve found. Take a look at Saribal (2019). This paper used ICP-MS and looked at trace element concentrations in cow’s milk samples from supermarkets in Istanbul, Turkey. They found an average of 0.009 mg/L lithium in milk, way lower than the measurements for milk found in sources that don’t use ICP-MS.
Saribal, like the TDS studies, used ICP-MS to look for lithium alongside a huge number of other elements — 19 in fact. The full list was: lithium, beryllium, chromium, manganese, cobalt, nickel, copper, arsenic, selenium, strontium, molybdenum, cadmium, antimony, barium, lead, bismuth, mercury, thallium, and uranium. Like the TDS studies, they did digestion in nitric acid:
The quadrupole inductively coupled plasma mass spectrometer (ICP-MS) used in this work was Thermo Scientific X Series II (Thermo Fisher Scientific, Bremen, Germany).
One-milliliter portions of each milk samples were digested in 65% HNO3 and 2 mL 30% H2O2 (Merck, Poole, UK) on a heat block. The temperature was increased gradually, starting from 90 °C and increasing up to 180 °C. The mixture was cooled down and the contents were transferred to polypropyl- ene tubes with seal caps. Each digested sample was diluted to a final volume of 10 mL with double deionized water
Here’s another one. Kalisz et al. (2019) looked at “17 elements, including rare earth elements, in chilled and non-chilled cauliflower cultivars”. They used ICP-MS, they microwave digested with nitric acid, and they found lithium levels of less than 0.060 mg/kg. Here’s the method:
We investigated the content of Ag, Al, Ba, Co, Li, Sn, Sr, Ti, Sb, and all rare-earth elements. … Curds were cut into pieces and dried at 70 °C in a dryer with forced air circulation. Then, the plant material was ground into a fine and non-fibrous powder using a Pulverisette 14 ball mill (Fritsch GmbH, Germany) with a 0.5-mm sieve. Next, 0.5 g samples were placed in to 55 ml TFM vessels and were mineralized in 10 ml 65% super pure HNO3 (Merck no. 100443.2500) in a Mars 5 Xpress (CEM, USA) microwave digestion system. The following mineralization procedure was applied: 15 min. time needed to achieve a temperature of 200 °C and 20 minutes maintaining this temperature. After cooling, the samples were quantitatively transferred to 25 ml graduated flasks with redistilled water. Contents of mentioned elements were determined using a high-dispersion inductively coupled plasma optical emission spectrometer (ICP-OES; Prodigy Teledyne Leeman Labs, USA).
There are a couple complications, but they’re worth looking at. Seidel et al. (2020) used ICP-MS and found reasonable-seeming numbers in a bunch of beverages. But, as far as we can tell, they didn’t digest the beverages at all. They just say:
Li concentrations in our 160 samples were determined via inductively coupled plasma mass spectrometry (ICP-MS) as summarized in Table 1.
Here’s Table 1 in case you’re curious:
This seems like evidence that something about the digestion process might be to blame.
There’s also Voica, Roba, and Iordache (2020), a Romanian paper which used ICP-MS and found up to 3.8 mg/kg in sheep’s milk and up to 4.2 mg/kg in pumpkins. This is pretty surprising — it’s the first ICP-MS paper we’ve seen that finds more than 1 mg/kg lithium in a sample of food. They even use microwave digestion with nitric acid! So at first glance, this looks like a contradiction — but when we looked closer, their method did differ in some interesting ways.
The lithium concentrations were determined by inductively coupled plasma – mass spectrometry (ICP-MS).
Considering that samples have a very complex composition with large organic matter content, the total digestion of the matrix is mandatory to assure complete metal solubility. The studied samples were subjected to microwave assisted nitric acid digestion by using a closed iPrep vessel speed system MARS6 CEM One Touch. The digestion vessels were cleaned with 10 mL HNO3 using the microwave cleaning program and rinsed with deionized water. Approximately 0.3 g aliquots of the samples were weighed, followed by digestion in 10mL HNO3 60% at high pressure, temperature and in the presence of microwave irradiation. The vessel was closed tightly, placed on the rotor, and the digestion was carried out following the program presented in Table 1.
After complete digestion and cooling, the samples were filtered, transferred to 50 mL graduated polypropylene tubes and diluted to volume with deionized water.
A Perkin Elmer ELAN DRC-e instrument was used with a Meinhard nebulizer and a glass cyclonic spray chamber for pneumatic nebulization. The analysis was performed in the standard mode and using argon gas (purity ≥ 99.999%) for the plasma following the manufacturer’s recommendations.
The operating conditions were a nebulizer gas flow rate of 0.92 L/min; an auxiliary gas flow of 1.2 L/min; a plasma gas flow of 15 L/min; a lens voltage of 7.25 V; a radiofrequency power of 1100 W; a CeO/Ce ratio of 0.025; and a Ba++/Ba+ ratio of 0.020.
We don’t know exactly what the difference might be, but the fact that they mention that “considering that samples have a very complex composition with large organic matter content, the total digestion of the matrix is mandatory to assure complete metal solubility” suggests that they were aware of limitations of normal digestion methods that other teams may have been unaware of. And none of the other papers seem to have used pneumatic nebulization, so maybe that makes the difference and lets you squeeze all the lithium out of a pumpkin.
Another difference we notice is that while Voica, Roba, and Iordache do use ICP-MS and the same kind of digestion as the TDS studies, they don’t test for anything else — they’re just measuring lithium. So maybe the thing that torpedoes the ICP-MS measurements is something about testing for lots of elements at the same time — a trait shared by all the TDS studies, Saribal (2019), and Kalisz et al. (2019), but not by Seidel et al. (2020) (the beverages paper) and not by Voica, Roba, and Iordache (2020).
A final (we promise) paper that helps triangulate this problem is Nabrzyski & Gajewska (2002), which looked at lithium in food samples from Gdańsk, Poland. They found an average of only 0.07 mg/kg in milk products and of only 0.11 mg/kg in smoked fish. This is not quite as low as the TDS studies but it’s much lower than everything else. And weirdly, they didn’t use ICP-MS, they used AAS. But they did digest their foods in nitric acid. Here’s the method:
The representative samples were dry ashed in quartz crucibles and the ash was treated with suitable amounts of conc. HCl and a few drops of conc. HNO3. The obtained sample solution was then used for the determination of Sr, Li and Ca by the flame atomic absorption spectrometry (AAS) method. Ca and Li were determined using the air-acetylene flame and Sr with nitrous oxide-acetylene flame, according to the manufacturer’s recommendations.
So maybe this seems like more evidence that it’s something about the digestion process in particular, though this paper could also just be a weird outlier. It’s hard to tell without more tests.
Close Look at ICP-MS
We seem to have pretty clear evidence that ICP-MS, maybe especially in combination with microwave digestion / digestion with nitric acid, gives much lower numbers for lithium in food samples than every other analysis technique we’ve seen.
So we wanted to know if there was any other reason to suspect that ICP-MS might give bad readings for lithium in particular. We did find a few things of interest.
If you check out the Wikipedia page for ICP-MS, lithium is mentioned as being just on the threshold of what the ICP-MS can detect. This makes sense because lithium is unusual, much smaller than all other other metals. See for example: “The ICP-MS allows determination of elements with atomic mass ranges 7 to 250 (Li to U)” and “electrostatic plates can be used in addition to the magnet to increase the speed, and this, combined with multiple collectors, can allow a scan of every element from Lithium 6 to Uranium Oxide 256 in less than a quarter of a second.”
While ICP-MS is generally considered the gold standard for spectral analysis, like all methodologies, it has some limitations. Given that lithium is at the bottom of the range to begin with, it seems plausible to us that even small irregularities in the analysis might push it “off the end” of the range, disrupting detection. There’s more likely to be problems with lithium than with the other elements the TDS papers were analyzing.
We noticed that the 1999 UK TDS study had this to say about the upper limits of detection for ICP-MS: “The platinum group elements are notoriously difficult to analyse, as the concentrations, generally being close to the limits of detection, can be prone to some interferences in complex matrices when measured by ICP-MS.”
Now lithium is on the low end of the range, not the high range. But since the UK TDS study authors were concerned that elements “close to the limits of detection, can be prone to some interferences in complex matrices when measured by ICP-MS”, it seems like interference might be an issue. This shows that “fall of the end of the range” is a real concern with ICP-MS analysis. So ICP-MS may be the gold standard for spectral analysis, but it falls short of being the platinum standard.
Lithium may be determined in foods and biological samples with the same techniques employed for sodium and potassium. However, the much lower levels of lithium compared with these other alkali metals, mean that techniques such as flame photometry often do not show adequate sensitivity. Flame (standard addition procedure) or electrothermal atomic absorption spectrophotometry are the most widely used techniques after wet or dry ashing of the sample. Corrections may have to be made for background/matrix interferences. Inductively coupled plasma atomic emission spectrometry is not very sensitive for this very low-atomic-weight element.
As usual with Anke this is very cryptic, and inductively coupled plasma atomic emission spectrometry (ICP-AES) isn’t the same technique as ICP-MS. But even so, Anke’s comment does suggest that there might be some limitations on ICP methods when measuring lithium, that they might not be very sensitive.
We also found an article by environmental testing firm WETLAB which describes several problems you can run into doing lithium analysis, including that “[w]hen Li is in a matrix with a large number of heavier elements, it tends to be pushed around and selectively excluded due to its low mass. This provides challenges when using Mass Spectrometry.” They also indicate that “ICP-MS can be an excellent option for some clients, but some of the limitations for lithium analysis are that lithium is very light and can be excluded by heavier atoms, and analysis is typically limited to <0.2% dissolved solids, which means that it is not great for brines.” We’re not looking at brines, but this may also hold true for digested food samples. WETLAB indicates their preferred methodology is ICP-OES.
Maybe nobody knows what’s going on here! It’s looking more and more like this is just a question that’s sitting out on the limits of human knowledge. It’s a corner case — to know why some papers find high levels and other papers find really low levels, you might have to jointly be an expert on ICP-MS, lithium analysis, and chemical analysis in food. Manfred Anke is the only guy we’ve ever heard of who seemed like he might be all three, and he’s been dead for more than ten years. So maybe there’s no one alive who knows the answer. But that’s why we do science, right?
In any case, we’re very glad to know about this complexity early on in the process of planning our own survey, since we had also been planning to use ICP-MS! We had assumed that ICP-MS was the best technique and that it would certainly give us the most accurate numbers. But measurement is rarely that simple — we should have been more careful, and now we will be.
How do we figure out what’s going on here, and what technique we should use? We could go back and pore over the literature in even more detail. But that would take a long time, and would probably be inconclusive. Much better is to simply test a bunch of foods using different techniques, pit ICP-MS against techniques like AAS and flame photometry, and see if we can figure out what’s going on. So that’s what we’re gonna do.
One possibility is that small amounts of lithium are enough to cause obesity, at least with daily exposure.
This is plausible for a few reasons. There’s lots of evidence (or at least, lots of papers) showing psychiatric effects at exposures of less than 1 mg (see for example meta-analysis, meta-analysis, meta-analysis, dystopian op-ed). If psychiatric effects kick in at less than 1 mg per day, then it seems possible that the weight gain effect would also kick in at less than 1 mg.
There’s also the case study of the Pima in the 1970s. The Pima are a group of Native Americans who live in the American southwest, particularly around the Gila River Valley, and they’re notable for having high rates of obesity and diabetes much earlier than other groups. They had about 0.1 mg/L in their water by the 1970s (which was 50x the national median at the time), for a dose of only about 0.2-0.3 mg per day, and were already about 40% obese. All this makes the trace lithium hypothesis seem pretty reasonable.
Unfortunately, no one knows where the weight gain effects of lithium kick in. As far as we can tell, there’s no research on this question. It might cause weight gain at doses of 10 mg, or 1 mg, or 0.1 mg. Maybe 0.5 mg a week on average is enough to make some people really obese. We just don’t know.
Some people in the nootropics community take lithium, often in the form of lithium orotate (they use orotate rather than other compounds because it’s available over-the-counter), as part of their stacks. Based on community posts like this, this, and this, the general doses nootropics enthusiasts are taking are in the range of 1-15 mg per day.
Another possibility is that people really ARE getting unintended clinical doses of lithium. We see two reasons to think that this might be possible.
#1: Doses in the Mirror may be…
The first is that clinical doses are smaller than they appear.
When a doctor prescribes you lithium, they’re always giving you a compound, usually lithium carbonate (Li2CO3). Lithium is one of the lightest elements, so by mass it will generally be a small fraction of any compound it is part of. A simple molecular-weight calculation shows us that lithium carbonate is only about 18.7% elemental lithium. So if you take 1000 mg a day of lithium carbonate, you’re only getting 187.8 mg/day of the active ingredient.
For bipolar and similar disorders, lithium carbonate has become such a medical standard that people usually just refer to the amount of the compound. It’s very unusual for an ion to be a medication, so this nuance is one that some doctors/nurses don’t notice. It’s pretty easy to miss. In fact, we missed it too until we saw this reddit comment from u/PatienceClarence/, which begins, “First off we need to differentiate between the doses of lithium orotate vs elemental lithium. For example, my dosage was 130 mg orotate which would give me 5 mg ‘pure’ lithium…”
Elemental lithium is what we really care about, and when we look at numbers from the USGS or serum samples or whatever, they’re all talking about elemental lithium. When we say people get 0.1 mg/day from their water, or when we talk about getting 3 mg from your food, that’s milligrams of elemental lithium. When we say that your doctors might give you 600 mg per day, that’s milligrams lithium carbonate — and only 112.2 milligrams a day of elemental lithium. With this in mind, we see that the dose of elemental lithium is always much lower than the dose as prescribed.
A high clinical dose is 600 mg lithium carbonate three times a day (for a total of 1800 mg lithium carbonate or about 336 mg elemental lithium), but many people get clinical doses that are much smaller than this. Low doses seem to be more like 450 mg lithium carbonate per day (about 84 mg/day elemental lithium) or even as little as 150 mg lithium carbonate per day (about 28 mg/day elemental lithium).
Once we take the fact that lithium is prescribed as a compound into account, we see that the clinical dosage is really closer to something like 300 mg/day for a high dose and 30 mg/day for a low dose. So at this point we just need to ask, is it possible that people might occasionally be getting 30 mg/day or more lithium in the course of their everyday lives? Unfortunately we think the answer is yes.
#2: Concentration in Food
The other reason to think that modern people might be getting clinical or subclinical doses on the regular is that there’s clear evidence that lithium concentrates in some foods.
Again, consider the Pima. The researchers who tested their water in the 1970s also tested their crops. While most crops were low in lithium, they found that one crop, wolfberries, contained an incredible 1,120 mg/kg.
By our calculations, you could easily get 15 mg of lithium in a tablespoon of wolfberry jelly. If the Pima ate one tablespoon a day, they would be getting around 100 times more lithium from that tablespoon than they were getting from their drinking water.
The wolfberries in question (Lycium californium) are a close relative of goji berries (Lycium barbarum or Lycium chinense). The usual serving size of goji berries is 30 grams, which if you were eating goji berries like the ones the Pima were eating, would provide about 33.6 mg of lithium. This already puts you into clinical territory, a little more than someone taking a 150 mg tablet of lithium carbonate.
If you had a hankering and happened to eat three servings of goji berries in one day, you would get just over 100 mg of lithium from the berries alone. We don’t know how much people usually eat in one go, but it’s easy enough to buy a pound (about 450 g) of goji berries online. We don’t have any measurements of how much lithium are in the goji berries you would eat for a snack, but if they contained as much lithium as the wolfberries in the Gila River Valley, the whole 1 lb package would contain a little more than 500 mg of lithium.
So. Totally plausible that some plants concentrate 0.1 mg/L lithium in water into 1,120 mg/kg in the plant, because Sievers & Cannon have measurements of both. Totally plausible that you could get 10 or even 100 mg if you’re eating a crop like this. So now we want to know, are there other crops that concentrate lithium? And if so, what are they?
In this review, we take a look at the existing literature and try to figure out how much lithium there is in different foods. What crops does it concentrate in? Is there any evidence that foods are further contaminated in processing or transport? There isn’t actually all that much work on these questions, but we’ll take a look at what we can track down.
Let’s not bury the lede: we find evidence of subclinical levels of lithium in several different foods. But most of the sources that report these measurements are decades old, and none of them are doing anything like an exhaustive search. That’s why at the end of this piece, we’re going to talk a little bit about our next project, a survey of lithium concentrations in foods and beverages in the modern American food supply.
Because of this, our goal is not to make this post an exhaustive literature review; instead, our goal is to get a reasonable sense of how much lithium is in the food supply, and where it is. When we do our own survey of modern foods, what should we look at first? This review is a jumping off point for our upcoming empirical work.
Context for the Search
But first, a little additional context.
There are a few official estimates of lithium consumption we should consider (since these are in food and water, all these numbers should be elemental lithium). This review paper from 2002 says that “the U.S. Environmental Protection Agency (EPA) in 1985 estimated the daily Li intake of a 70 kg adult to range from [0.650 to 3.100 mg].” The source they cite for this is “Saunders, DS: Letter: United States Environmental Protection Agency. Office of Pesticide Programs, 1985”, but we can’t find the original letter. As a result we don’t really know how accurate this estimate is, but it suggests people were getting about 1-3 mg per day in 1985.
These numbers are backed up by some German data which appear originally to be from a paper from 1991, which we will discuss more in a bit:
In Germany, the individual lithium intake per day on the average of a week varies between [0.128 mg/day] and [1.802 mg/day] in women and [0.139] and [3.424 mg/day] in men.
The paper also includes histograms of those distributions:
We want to call your attention to the shape of both of these distributions, because the shape is going to be important throughout this review. Both distributions are pretty clearly lognormal, meaning they peak early on but then have a super long tail off to the right. For example, most German men in this study were getting only about 0.2 to 0.4 mg of lithium per day, but twelve of them were getting more than 1 mg a day, and five of them were getting more than 2 mg a day. At least one person got more than 3 mg a day. And this paper is looking at a pretty small group of Germans. If they had taken a larger sample, we would probably see a couple people who were consuming even more. You see a similar pattern for women, just at slightly lower doses.
We expect pretty much every distribution we see around food and food exposure to be lognormal. The amount people consume per day should usually be lognormally distributed, like we see above. The distribution of lithium in any foods and crops will be lognormal. So will the distribution of lithium levels in water sources. For example, lithium levels in that big USGS dataset of groundwater samples we always talk about are distributed like this:
Again we see a clear lognormal distribution. Most groundwater samples they looked at had less than 0.2 mg/L lithium. But five had more than 0.5 mg/L and two had more than 1 mg/L.
This is worth paying close attention to, because when a variable is lognormally distributed, means and medians will not be very representative. For example, in the groundwater distribution you see above, the median is .0055 mg/L and the mean is .0197 mg/L.
These sound like really tiny amounts, and they are! But the mean and the median do not tell anywhere close to the full story. If we keep the long tail of the distribution in mind, we see that about 4% of samples contain more than 0.1 mg/L, about 1% of samples contain more than 0.2 mg/L, and of course the maximum is 1.7 mg/L.
This means that about 4% of samples contain more than 20x the median, about 1% of samples contain more than 40x the median, and the maximum is more than 300x the median.
Put another way, about 4% of samples contain more than 5x the mean, about 1% of samples contain more than 10x the mean, and the maximum is more than 80x the mean.
We should expect similar distributions everywhere else, and we should expect means and medians to consistently be misleading in the same way. So if we find a crop with 1 mg/kg of lithium on average, that suggests that the maximum in that crop might be as high as 80 mg/kg! If this math is even remotely correct, you can see why crops that appear to have a low average level of lithium might still be worth empirically testing.
Another closely related point: that USGS paper only found those outliers because it’s a big survey, 4700 samples. Small samples will be even more misleading. Let’s imagine the USGS had taken a small number of samples instead. Here are some random sets of 6 observations from that dataset:
0.044, 0.007, 0.005, 0.036, 0.001, 0.002
0.002, 0.028, 0.005, 0.001, 0.009, 0.001
0.003, 0.006, 0.002, 0.001, 0.001, 0.006
We can see that small samples ain’t representative. If we looked at a sample of six US water sources and found that all of them contained less than 0.050 mg/L of lithium, we would miss that some US water sources out there contain more than 0.500 mg/L. In this situation, there’s no substitute for a large sample size (or, the antidote is to be a little paranoid about how long the tail is).
So if we looked at a sample of (for example) six lemons, and found that all of them contained less than 10 mg/kg of lithium, we might easily be missing that there are lemons out there that contain more than 100 mg/kg.
In any case, the obvious lognormal distribution fits really well with the kind of bolus-dose explanation we discussed with JP Callaghan, who said:
My thought was that bolus-dosed lithium (in food or elsewhere) might serve the function of repeated overfeeding episodes, each one pushing the lipostat up some small amount, leading to overall slow weight gain. … I totally vibe with the prediction that intake would be lognormally distributed. … lognormally distributed doses of lithium with sufficient variability should create transient excursions of serum lithium into the therapeutic range.
In the discussion with JP Callaghan, we also said:
Because of the lognormal distribution, most samples of food … would have low levels of lithium — you would have to do a pretty exhaustive search to have a good chance of finding any of the spikes. So if something like this is what’s happening, it would make sense that no one has noticed.
What we’re saying is that even if people aren’t getting that much lithium on average, if they sometimes get huge doses, that could be enough to drive their lipostat upward. If we take that model seriously, the average amount might not not be the real driver, and we should focus on whether there are huge lithium bombs out there, and how often you might encounter them. Or it could be even more complicated! Maybe some foods give you repeated moderate doses, and others give you rare megadoses.
Second, we want to remind you that whatever dose causes obesity, lithium is also a powerful sedative with well-known psychiatric effects. If you’re getting doses up near the clinical range, it’s gonna zonk you out and probably stress your kidneys.
Ok. What crops concentrate lithium?
Unfortunately we couldn’t find several of the important primary sources, so in a number of places, we’ve had to rely on review papers and secondary sources. We’re not going to complain “we couldn’t find the primary source” every time, but if you’re ever like “why are they citing a review paper instead of the original paper?” this is probably why.
We should warn you that these sources can be a little sloppy. Important tables are labeled unclearly. Units are often given incorrectly, like those histograms above that say mg/day when they should almost certainly say µg/day. When you double-check their citations, the numbers don’t always match up. For example, one of the review papers said that a food contained 55 mg/kg of lithium. But when we double-checked, their source for that claim said just 0.55 mg/kg in that food. So we wish we were working with all the primary sources but we just ain’t. Take all these numbers with a grain of salt.
It’s worth noting just how concerned some of these literature reviews sound. Shahzad et al. (2016) say in their abstract, “The contamination of soil by Li is becoming a serious problem, which might be a threat for crop production in the near future. … lack of considerable information about the tolerance mechanisms of plants further intensifies the situation. Therefore, future research should emphasize in finding prominent and approachable solutions to minimize the entry of Li from its sources (especially from Li batteries) into the soil and food chain.”
Older reviews include The lithium contents of some consumable items by Hullin, Kapel, and Drinkall — a 1969 paper which includes a surprisingly lengthy review of even older sources, citing papers as far back as 1917. Sadly we weren’t able to track down most of these older sources, and the ones we could track down were pretty vague. Papers from the 1930s just do not give all that much detail. Still, very cool to have anything this old.
There’s also Shacklette, Erdman, Harms, and Papp (1978), Trace elements in plant foodstuffs, a chapter from (as far as we can tell) a volume called “Toxicity of Heavy Metals in the Environment”, which is part of a series of reference works and textbooks called “HAZARDOUS AND TOXIC SUBSTANCES”. It was sent to us by a very cool reader who refused to accept credit for tracking it down. If you want to see this one, email us.
A bunch of the best and most recent information comes from a German fella named Manfred Anke, who published a bunch of papers on lithium in food in Germany in the 1990s and 2000s. He did a ton of measurements, so you will keep seeing his name throughout. Unfortunately the papers we found from Anke mostly reference measurements from earlier work he did, which we can’t find. Sadly he is dead so we cannot ask him for more detail.
From Anke, in case anyone can track them down, we’d especially like to see a couple papers from the 1990s. Here they are exactly as he cites them:
Anke’s numbers are very helpful, but we think they are a slight underestimation of what is in our food today. We’re pretty sure lithium levels in modern water are higher than levels in the early 1990s, and we’re pretty sure lithium levels are higher in US water than in water in Germany. In a 2005 paper, Anke says: “In Germany, the lithium content of drinking water varies between 4 and 60 µg/L (average : 10 µg/L).” Drinking water in the modern US varies between undetectable and 1700 µg/L (1.7 mg/L), and even though that 1700 is an outlier, about 8% of US groundwater samples contain more than 60 µg/L, the maximum Anke gives for Germany. The mean for US groundwater is 19.7 µg/L, compared to the 10 µg/L Anke reports.
So the smart money is that Anke’s measurements are probably all lower than the levels in modern food, certainly lower than the levels in food in the US.
Here’s another thing of interest: in one paper Anke estimates that in 1988 Germany, the average daily lithium intake for women was 0.373 mg, and the average daily lithium intake for men was 0.432 mg (or something like that; it REALLY looks like he messed up labeling these columns, luckily the numbers are all pretty similar). By 1992, he estimates that the average daily lithium intake for women was 0.713 mg, and the average daily lithium intake for men was 1.069 mg. He even explicitly comments, saying, “the lithium intake of both sexes doubled after the reunification of Germany and worldwide trade.”
That last bit about trade suggests he is maybe blaming imported foods with higher lithium levels, but it’s not really clear. He does seem to think that many foreigners get more lithium than Germans do, saying, “worldwide, a lithium intake for adults between [0.660 and 3.420 mg/day] is calculated.”
Anyways, on to actual measurements.
Beverages are probably not giving you big doses of lithium, with a few exceptions.
Most drinking water doesn’t contain much lithium, rarely poking above 0.1 mg/L. Some beverages contain more, but not a lot more. The big exception, no surprise, is mineral water.
As usual, Anke and co have a lot to say. The Anke paper from 2003 says, “cola and beer deliver considerable amounts of lithium for humans, and this must be taken into consideration when calculating the lithium balance of humans.”The Anke paper from 2005 says that “amounts of [0.002 to 5.240 mg/L] were found in mineral water. Like tea and coffee, beer, wine and juices can also contribute to the lithium supply.” But the same paper reports a range of just 0.018 – 0.329 mg/L in “beverages”. Not clear where any of these numbers come from, or why they mention beer in particular — the citation appears to be the 1995 Anke paper we can’t find.
In fact, Anke seems to disagree with himself. The 2005 paper mentions tea and coffee contributing to lithium exposure. But the 2003 paper says, “The total amount in tea and coffee, not their water-soluble fraction in the beverage, was registered. Their low lithium content indicates that insignificant amounts of lithium enter the diet via these beverages.”
This 2020 paper, also from Germany, finds a weak relationship for beer and wine and a strong relationship for tea with plasma concentrations for lithium. We think there are a lot of problems with this method (the serum samples are probably taken fasted, and lithium moves through the body pretty quickly) but it’s interesting.
Franzaring et al. (2016), one of those review papers, has a big figure summarizing a bunch of other sources, which has this to say about some beverages:
So obviously mineral water can contain a lot — if you drank enough, you could probably get a small clinical dose from mineral water alone. On the other hand, who’s drinking a liter of mineral water? Germans, apparently.
This paper from 2000 similarly finds averages of 0.035 and 0.019 mg/L in red wines from northern Spain. This 1994 paper and this 1997 paper both report similar values. We also found this 1988 paper looking at French red wines which suggests a range from 2.61 to 17.44 mg/L lithium. Possibly this was intended to be in µg/L instead of in mg/L? “All results are in milligrams per liter except Li, which is in micrograms per liter” is a disclaimer we’ve seen in more than one of these wine papers.
So it might be good to check, but overall we don’t think you’ll see much more than 0.150 mg/L in your wine, and most of you are hopefully drinking less than a full liter at a time.
The most recent and most comprehensive source for beverages, however, is a 2020 paper called Lithium Content of 160 Beverages and Its Impact on Lithium Status in Drosophila melanogaster. Forget the Drosophila, let’s talk about all those beverages. This is yet another German paper, and they analyzed “160 different beverages comprising wine and beer, soft and energy drinks and tea and coffee infusions … by inductively coupled plasma mass spectrometry (ICP-MS).” And unlike other sources, they give all the numbers — If you want to know how much lithium they found in Hirschbraeu/Adlerkoenig, “Urtyp, hell” or the cola known as “Schwipp Schwapp”, you can look that up.
They find that, aside from mineral water, most beverages in Germany contain very little lithium. Concentration in wine, beer, soft drinks, and energy drinks was all around 0.010 mg/L, and levels in tea and coffee barely ever broke 0.001 mg/L.
The big outlier is the energy drink “Acai 28 Black, energy”, which contained 0.105 mg/L. This is not a ton in the grand scheme of things — it’s less than some sources of American drinking water — but it’s a lot compared to the other beverages in this list. They mention, “it has been previously reported that Acai pulp contains substantial concentrations of other trace elements, including iron, zinc, copper and manganese. In addition to acai extract, Acai 28 black contains lemon juice concentrate, guarana and herb extracts, which possibly supply Li to this energy drink.”
We want to note that beverages in America may contain more lithium, just because American drinking water contains more lithium than German drinking water does. But it’s doubtful that people are getting much exposure from beverages beyond what they get from the water it’s made with.
We also have a few leads on what might be considered “basic” or “component” foods.
Anke mentions sugars a bit, though doesn’t go into much detail, saying, “honey and sugar are also extremely poor in lithium…. The addition of sugar apparently leads to a further reduction of the lithium content in bread, cake, and pastries.“ At one point he lists the range of “Sugar, honey” as being 0.199 – 0.527 mg/kg, with a mean of 0.363 mg/kg. That’s pretty low.
We also have a little data from the savory side. This paper from 1969 looked at levels in various table salts, finding (in mg/kg):
On the one hand, those are relatively high levels of lithium. On the other hand, who’s eating a kilogram of salt? Even if table salt contains 3 mg/kg, you’re just never gonna get even close to getting 1 mg from your salt.
It’s clear that plants can concentrate lithium, and some plants concentrate lithium more than others. It’s also clear that some plants concentrate lithium to an incredible degree. This last point is something that is emphasized by many of the reviews, with Shahzad et al. (2016) for example saying, “different plant species can absorb considerable concentration [sic] of Li.”
Plant foods have always contained some lithium. The best estimate we have for preindustrial foods is probably this paper that looked at foods in the Chocó rain forest around 1970, and found (in dry material): 3 mg/kg in breadfruit; 1.5 mg/kg in cacao, 0.4 mg/kg in coconut, 0.25 mg/kg in taro, 0.4 mg/kg in yam, 0.6 mg/kg in cassava, 0.5 mg/kg in plantain fruits, 0.1 mg/kg in banana, 0.3 mg/kg in rice, 0.01 mg/kg in avocado, 0.5 mg/kg in dry beans, and 0.05 mg/kg in corn grains. Not nothing, but pretty low doses overall.
There are a few other old sources we can look at. Shacklette, Erdman, Harms, and Papp (1978) report a paper by Borovik-Romanova from 1965, in which she “reported the Li concentration in many plants from the Soviet Union to range from 0.15 to 5 [mg/kg] in dry material; she reported Li in food plants as follows ([mg/kg] in dry material): tomato, 0.4; rye, 0.17; oats, 0.55; wheat, 0.85; and rice, 9.8.” That’s a lot in rice, but we don’t know if that’s reliable, and we haven’t seen any other measurements of the levels in rice. We weren’t able to track the Borovik-Romanova paper down, unfortunately.
From here, we can try to narrow things down based on the better and more modern measurements we have access to.
We haven’t seen very much about levels in cereals / grains / grass crops, but what we have seen suggests very low levels of accumulation.
Borovik-Romanova reported, in mg/kg, “rye, 0.17; oats, 0.55; wheat, 0.85; and rice, 9.8” in 1965 in the USSR. Most of these concentrations are very low. Again, rice is abnormally high, but this measurement isn’t at all corroborated. And since we haven’t been able to find this primary source, there’s a good chance it should read 0.98 instead.
Anke, Arnhold, Schäfer, & Müller (2005) report levels from 0.538 to 1.391 mg/kg in “cereal products”, and in a 2003 paper, say “the different kinds of cereals grains are extremely lithium-poor as seeds.” Anke reports slightly lower levels in derived products like “bread, cake”.
There’s also this unusual paper on corn being grown hydroponically in solutions containing various amounts of lithium. They find that corn is quite resistant to lithium in its water, actually growing better when exposed to some lithium, and only seeing a decline at concentrations around 64 mg/L. (“the concentration in solution ranging from 1 to 64 [mg/L] had a stimulating effect, whereas a depression in yielding occurred only at the concentrations of 128 and 256 [mg/L].”) But the plant also concentrates lithium — even when only exposed to 1 mg/L in its solution, the plant ends up with an average of about 11 mg/kg in dry material. Unfortunately they don’t seem to have measured how much ends up in the corn kernels, or maybe they didn’t let the corn develop that far. Seems like an oversight. (Compare also this similar paper from 2012.)
Someone should definitely double-check those numbers on rice to be safe, and corn is maybe a wildcard, but for now we’re not very worried about cereal crops.
A number of sources say that lithium tends to accumulate in leaves, suggesting lithium levels might be especially high in leafy foods. While most of us are in no danger of eating kilograms of cabbage, it’s worth looking out for.
In particular, Robinson et al. (2018) observed significant concentration in the leaves of several species as part of a controlled experiment. They planted beetroot, lettuce, black mustard, perennial ryegrass, and sunflower in controlled environments with different levels of lithium exposures. “When Li was added to soil in the pot experiment,” they report, “there was significant plant uptake … with Li concentrations in the leaves of all plant species exceeding 1000 mg/kg (dry weight) at Ca(NO3)2-extractable concentrations of just 5 mg/kg Li in soil, representing a bioaccumulation coefficient of >20.” For sunflowers in particular, “the highest Li concentrations occurred in the bottom leaves of the plant, with the shoots, roots and flowers having lower concentrations.”
Obviously this is reason for concern, but these are plants grown in a lab, not grown under normal conditions. We want to check this against actual measurements in the food supply.
Hullin, Kapel, and Drinkall (1969) report that an earlier source, Bertrand (1943), “found that the green parts of lettuce contained 7.9 [mg/kg] of lithium.” They wanted to follow up on this surprisingly high concentration, so they tested some lettuce themselves, finding:
This pretty clearly contradicts the earlier 7.9 mg/kg, though the fact that lettuce can contain up to 2 mg/kg is still a little surprising. This could be the result of lettuce being grown in different conditions, the lognormal distribution, etc., but even so it’s reassuring to see that not all lettuce in 1969 contained several mg per kg.
In this study from 1990, the researchers went and purchased radish, lettuce and watercress at the market in Brazil, and found relatively high levels in all of them:
Let’s also look at this modern table that reviews a couple more recent sources, from Shahzad et al.:
None of these are astronomical, but it’s definitely surprising that spinach contains more than 4 mg/kg and celery and chard both contain more than 6 mg/kg, at least in these measurements.
So not to sound too contrarian but, maybe too many leafy greens are bad for your health.
This is a wide range, and a pretty high ceiling. But as usual, Anke is much vaguer than we might hope. He gives some weird hints, but no specific measurements. In the 2003 paper, Anke says, “as a rule, fruits contain less lithium than vegetative parts of plants (vegetables). Lemons and apples contained significantly more lithium, with about 1.4 mg/kg dry matter, than peas and beans.”
More specific numbers have been hard to come by. We’ve found a pretty random assortment, like how Shahzad et al. report that “in a hydroponic experiment, Li concentration in nutrient solution to 12 [mg/L], increased cucumber fruit yield, fruit sugar, and ascorbic acid levels, but Li did not accumulate in the fruit (Rusin, 1979).” It’s interesting that cucumbers survive just fine in water containing up to 12 mg/L, and that suggests that lithium shouldn’t accumulate in cucumbers under any realistic water levels. But cucumbers are not a huge portion of the food supply.
What we do see all the time is sources commenting on how citrus plants are very sensitive to lithium. Anke says, “citrus trees are the most susceptible to injury by an excess of lithium, which is reported to be toxic at a concentration of 140–220 p.p.m. in the leaves.” Robinson et al. (2018) say, “citing numerous sources, Gough et al. (1979) reported a wide variation in plant tolerance to Li; citrus was found to be particularly sensitive, whilst cotton was more tolerant.” Shahzad et al. say, “Bradford (1963) found reduced and stunted growth of citrus in southern California, U.S.A., with the use of highly Li-contaminated water for irrigation. … Threshold concentrations of Li in plants are highly variable, and moderate to severe toxic effects at 4–40 mg Li kg−1 was observed in citrus leaves (Kabata-Pendias and Pendias, 1992).” This Australian Water Quality Guidelines for Fresh and Marine Waters document says, “except for citrus trees, most crops can tolerate up to 5 mg/L in nutrient solution (NAS/NAE 1973). Citrus trees begin to show slight toxicity at concentrations of 0.06–0.1 mg/L in water (Bradford 1963). Lithium concentrations of 0.1–0.25 mg/L in irrigation water produced severe toxicity symptoms in grapefruit … (Hilgeman et al. 1970)”.
All tantalizing, but we can’t get access to any of those primary sources. For all we know this is a myth that’s been passed around the agricultural research departments since the 1960s.
Even if citrus trees really are extra-sensitive to lithium, it’s not clear what that means for their fruits. Maybe it means that citrus fruits are super-low in lithium, since the tree just dies if it’s exposed to even a small amount. Or maybe it means that citrus fruits are super-high in lithium — maybe citrus trees absorb lithium really quickly and that’s why lithium kills them at relatively low levels.
So it’s interesting but at this point, the jury is out on citrus.
Multiple sources mention that the Solanaceae family, better known as nightshades, are serious concentrators of lithium. Hullin, Kapel, and Drinkall mention that even in the 1950s, plant scientists were aware that nightshades are often high in lithium. Anke, Schäfer, & Arnhold (2003) mention, “Solanaceae are known to have the highest tolerance to lithium. Some members of this family accumulate more than 1000 p.p.m. lithium.” Shacklette, Erdman, Harms, and Papp (1978) even mention a “stimulating effect of Li as a fertilizer for certain species, especially those in the Solanaceae family.”
Shahzad et al. (2016) say, “Schrauzer (2002) and Kabata-Pendias and Mukherjee (2007) noted that plants of Asteraceae and Solanaceae families showed tolerance against Li toxicity and exhibited normal plant growth,” and, “some plants of the Solanaceae family, when grown in an acidic climatic zone accumulate more than 1000 mg/kg Li.” We weren’t able to track down most of their sources for these claims, but we did find Schrauzer (2002). He mentions that Cirsium arvense (creeping thistle) and Solanum dulcamara (called things like fellenwort, felonwood, poisonberry, poisonflower, scarlet berry, and snakeberry; probably no one is eating these!) are notorious concentrators of lithium, and he repeats the claim that some Solanaceae accumulate more than 1000 mg/kg lithium, but it’s not clear what his source for this was.
Hullin, Kapel, and Drinkall mention in particular one source from 1952 that found a range of 1.8-7.96 [mg/kg] in members of the Solanaceae. 7.9 mg/kg in some nightshades is enough to be concerned, but they don’t say which species this measurement comes from.
The finger seems to be pointing squarely at the Solanaceae — but which Solanaceae? This family is huge. If you know anything about plants, you probably know that potatoes and tomatoes are both nightshades, but you may not know that nightshades also include eggplants, the Capsicum (including e.g. chili peppers and bell peppers), tomatillos, some gooseberries, the goji berry, and even tobacco.
We’ve already seen how wolfberries / goji berries can accumulate crazy amounts under the right circumstances, which does make this Solanaceae thing seem even more plausible.
Anke, Schäfer, & Arnhold (2003) mention potatoes in particular in one section on vegetable foods, saying: “All vegetables and potatoes contain > 1.0 mg lithium kg−1 dry matter.” There isn’t much detail, but the paper does say, “peeling potatoes decreases their lithium content, as potato peel stores more lithium than the inner part of the potato that is commonly eaten.”
That same paper that tries to link diet to serum lithium levels does claim to find that a diet higher in potatoes leads to more serum lithium, but we still think this paper is not very good. If you look at table 4, you see that there’s not actually a clear association between potatoes and serum levels. Table 5 says that potatoes come out in a regression model, but it’s a bit of an odd model and they don’t give enough detail for us to really evaluate it. And again, these serum concentrations were taken fasted, so they didn’t measure the right thing.
It’s much better to just measure the lithium in potatoes directly. Anke seems to have done this in the 1990s, but he’s not giving any details. We’ll have to go back all the way to 1969, when Hullin, Kapel, and Drinkall included three varieties of potatoes in their study (numbers in mg/kg):
These potatoes, at least, are pretty low in lithium. The authors do specifically say these were peeled potatoes, which may be important in the light of Anke’s comment about the peels. These numbers are pretty old, and modern potatoes probably are exposed to more lithium. But even so, these potatoes do not seem to be mega-concentrators, and Hullin, Kapel, and Drinkall did find some serious concentrators even back in 1969.
This is especially interesting to us because it provides a little support for the idea that the potato diet might cause weight loss by reducing your lithium intake and forcing out the lithium already in your system with a high dose of potassium, or something. At the very least, it looks like you’d get less lithium in your diet if you lived on only potatoes than if you somehow survived on only lettuce (DO NOT TRY THE LETTUCE DIET).
Apparently the nightshade family’s tendency to accumulate lithium does not include the potatoes (unless the peeling made a huge difference?). This suggests that the high levels might have come from some OTHER nightshade. Obviously we have already seen huge concentrations in the goji berry (or at least, a close relative). But what about other nightshades, like tomatoes, eggplant, or bell peppers?
Hullin, Kapel, and Drinkall do frustratingly say, “[The lithium content] of the tomato will be reported elsewhere.” But they don’t discuss it beyond that, at least not in this paper. We’ll have to look to other sources.
Shacklette et al. report: “Borovik-Romanova reported the Li concentration in [dry material] … tomato, 0.4 [mg/kg].” This is not much, though these numbers are from 1965, and from the USSR.
A stark contrast can be found in one of Anke’s papers, where they state, “Fruits and vegetables supply 1.0 to 7.0 mg Li/kg food DM. Tomatoes are especially rich in Li (7.0 mg Li/kg DM).”
This is a lot for a vegetable fruit! It occurs to us that tomatoes are pretty easy to grow hydroponically, and you could just dose distilled water with a known amount of lithium. If any of you are hydroponic gardeners and want to try this experimentally, let us know!
But tomatoes are obviously beaten out by wolfberries/goji berries, and they also can’t compare to this dark horse nightshade: tobacco.
That’s right — Hullin, Kapel, and Drinkall (1969) also measured lithium levels in tobacco. They seem to have done this not because it’s another nightshade, but because previous research from the 1940s and 1950s had found that lithium concentrations in tobacco were “extraordinarily high”. For their own part, Hullin and co. found (mg/kg in ash):
This is a really interesting finding, and in a crop we didn’t expect people to examine, since tobacco isn’t food.
At the same time, measuring ash is kind of cheating. Everything organic will be burned away in the cigarette or pipe, so the level of any salt or mineral will appear higher than it was in the original substance. As a result, we don’t really know the concentration in the raw tobacco. This is also the lithium that’s left over in the remnants of tobacco after it’s been smoked, so these measurements are really the amount that was left unconsumed, which makes it difficult to know how much might have been inhaled. Even so, the authors think that “the inhalation of ash during smoking could provide a further source of this metal”.
We didn’t find measurements for any other nightshades, but we hope to learn more in our own survey.
Pretty much everything we see suggests that animal products contain more lithium on average than plant-based foods. This makes a lot of general sense because of biomagnification. It also makes particular sense because many food animals consume huge quantities of plant stalks and leaves, and as we’ve just seen, stalks and leaves tend to accumulate more lithium than other parts of the plants.
But the bad news is that, like pretty much everything else, levels in animal products are poorly-documented and we have to rely heavily on Manfred Anke again. He’s a good guy, we just wish — well we wish we had access to his older papers.
Meat seems to contain a consistently high level of lithium. Apparently based on measurements he took in the 1990s, Anke calculates that meat products contain an average of about 3.2 mg/kg, and he gives a range of 2.4 to 3.8 mg/kg.
On average, eggs, meat, sausage, and fish deliver significantly more lithium per kg of dry matter than most cereal foodstuffs. Eggs, liver, and kidneys of cattle had a mean lithium content of 5 mg/kg. Beef and mutton contain more lithium than poultry meat. Green fodder and silage consumed by cattle and sheep are much richer in lithium than the cereals largely fed to poultry. Sausage and fish contain similar amounts of lithium to meat.
Beyond this, we haven’t found much detail to report. And even Anke can’t keep himself from mentioning how meat plays second fiddle to something else:
… Poultry, beef, pork and mutton contain lithium concentrations increasing in that order. Most lithium is delivered to humans by eggs and milk (> 7000 µg/kg DM).
Among foods of animal origin, those which have been found to contain lithium include eggs (Press, 1941) and milk (Wright & Papish, 1929; Drea, 1934).
So let’s leave meat behind for now and look at the real heavy-hitters.
The earliest report we could find for milk was this 1929 Science publication mentioned by Hullin, Kapel, and Drinkall. But papers this old are pretty terse. It’s only about three-quarters of a page, and the only information they give about lithium is that it is included in the “elements not previously identified but now found to be present” in milk.
Anke can do one better, and estimates an average for “Milk, dairy products” of 3.6 mg/kg with a range of 1.1 to 7.5 mg/kg. This suggests that the concentration in dairy products is pretty high across the board, but also that there’s considerable variation.
Anke explains this in a couple ways. First of all, he says that there were, “significant differences between the lithium content of milk”, and he suggests that milk sometimes contained 10 mg/kg in dry matter. This seems to contradict the range he gives above, but whatever.
He also points out that other dairy products contain less lithium. For example, he says that butter is “lithium-poor”, containing only about 1.2 mg/kg dry matter, which seems to be the bottom of the range for dairy. “In contrast to milk,” he says, “curd cheese and other cheeses only retain 20–55% of lithium in the original material available for human nutrition. The main fraction of lithium certainly leaves cheese and curd cheese via the whey.”
This is encouraging because we love cheese and we are glad to know it is not responsible for poisoning our brains — at least, not primarily. It’s also interesting because 20-55% is a pretty big range; we’d love to know if some cheeses concentrate more than others, or if this is just an indication of the wide variance he mentioned earlier in milk. Not that we really need it, but if you have access to the strategic cheese reserve, we’d love to test historical samples to see if lithium levels have been increasing.
What he suggests about whey is also pretty intriguing. Whey is the main byproduct of turning milk into cheese, so if cheese is lower in lithium than milk is, then whey must be higher. Does this mean whey protein is super high in lithium?
The oldest paper we could find on lithium in eggs is a Nature publication from 1941 called “Spectrochemical Analysis of Eggs”, and it is half a page of exactly that and nothing else. They do mention lithium in the eggs, but unfortunately the level of detail they give is just: “Potassium and lithium were also present [in the eggs] in fair quantity.”
Anke gives his estimate as always, but this time, it’s a little different:
Anke gives an average (we think; he doesn’t label this column anywhere) of 7.3 mg/kg in eggs. This is a lot, more than any other food category he considers. And instead of giving a range, like he does for every other food category, he gives the standard deviation, which is 6.5 mg/kg.
This is some crazy variation. Does that mean some eggs in his sample contained more than 13.8 mg/kg lithium? That’s only one standard deviation above the average, two standard deviations would be 20.3 mg/kg. A large egg is about 50 g, so at two standard deviations above average, you could be getting 1 mg per egg.
That does seem to be what he’s suggesting. But if we assume the distribution of lithium in eggs is normal, we get negative values quickly, and an egg can’t contain a negative amount of lithium.
Because lithium concentrations can’t be negative, and because of the distributions we’ve seen in all the previous examples, we assume the distribution of lithium in eggs must be lognormal instead.
A lognormal distribution with parameters [1.7, .76] has a mean and sd of very close to 7.3 and 6.5, so this is a reasonable guess about the underlying distribution of eggs in Germany in 1991.
Examination of the lognormal distribution with these parameters suggests that the distribution of lithium in eggs (at least in Germany in 1991) looks something like this: The modal egg in this distribution contains about 3 mg/kg lithium. But about 21% of the eggs in this distribution contain more than 10 mg/kg lithium. About 4% contain more than 20 mg/kg. About 1% contain more than 30 mg/kg. About 0.4% contain more than 40 mg/kg. And two out of every thousand contain 50 mg/kg lithium or more.
That’s a lot of lithium for just one egg. What about the lithium in a three-egg omelette?
To answer this Omelettenproblem, we started by taking samples of three eggs from a lognormal distribution with parameters [1.7, .76]. That gives us the concentration in mg/kg for each egg in the omelette.
Again, a large egg is about 50 grams. In reality a large egg is slightly more, but we’ll use 50 g because some restaurants might use medium eggs, and because it’s a nice round number.
So we multiply each egg’s mg/kg value by .05 (because 50 g out of 1000 g for a kilogram) to get the lithium it contains in mg, and we add the lithium from all three eggs in that sample together for the total amount in the omelette.
We did this 100,000 times, ending up with a sample of 100,000 hypothetical omelettes, and the estimated lithium dose in each. Here’s the distribution of lithium in these three-egg omelettes in mg as a histogram:
As you can see, most omelettes contained less than 3 mg lithium. In fact, most contained between 0.4 and 1.6 mg.
This doesn’t sound like a lot, but we think it’s pretty crazy. A small clinical dose is something like 30 mg, and it’s nuts to see that you can get easily like 1/10 that dose from a single omelette. Remember that in 1985, the EPA estimated that the daily lithium intake of a 70 kg US adult ranged from 0.650 to 3.1 mg — but by 1991 Germany, you can get that whole dose in a single sitting, from a single dish!
Even Anke estimated that his German participants were getting no more than 3 mg a day from their food. But this model suggests that you can show up at a cafe and say “Kellner, bringen Sie mir bitte ein Omelette” and easily get that 3 mg estimate blown out of the water before lunchtime.
Even this ignores the long tail of the data. The omelettes start to peter out at around 5 mg, but the highest dose we see in this set of 100,000 hypothetical breakfasts was 11.1 mg of lithium in a single omelette.
The population of Germany in 1990 was just under 80 million people. Let’s say that only 1 out of every 100 people orders a three-egg omelette on a given day. This means that every day in early 1990s Germany, about 800,000 people were rolling the dice on an omelette. Let’s further assume that the distribution of omelettes we generated above is correct. If all these things are true, around 8 unlucky people every day in 1990s Germany were getting smacked with 1/3 a clinical dose of lithium out of nowhere. It’s hard to imagine they wouldn’t feel that.
One thing we didn’t see much of in this literature review was measurements of the lithium in processed food.
We’re very interested in seeing if processing increases lithium. But no one seems to have measured the lithium in a hamburger, let alone a twinkie.
Mostly Anke and co find that processed foods are not extreme outliers. “Ready-to-serve soups with meat and eggs were [rich] in lithium,” they say, “whereas various puddings, macaroni, and vermicelli usually contained < 1 mg lithium/kg dry matter. Bread, cake, and pastries are usually poor sources of lithium. On average, they contained less lithium than wheat flour. The addition of sugar apparently leads to a further reduction of the lithium content in bread, cake, and pastries.”
Even in tasty treats, they don’t find much. We don’t know how processed German chocolate was at the time, but they say, “the lithium content of chocolates, chocolate candies, and sweets amounted to about 0.5 mg/kg dry matter. Cocoa is somewhat richer in lithium. The addition of sugar in chocolates reduces their lithium content.”
The only thing that maybe jumps out as evidence of contamination from processing is what they say about mustard. “Owing to the small amounts used in their application,” they begin, “spices do not contribute much lithium to the diet. It is surprising that mustard is relatively lithium-rich, with 3.4 mg/kg dry matter, whereas mustard seed contains extremely little lithium.” Mustard is generally a mixture of mustard seed, water, vinegar, and not much else. We saw in the section on beverages that wine doesn’t contain much lithium, so vinegar probably doesn’t either. Maybe the lithium exposure comes from processing?
We notice that for many categories of food, we seem to have simply no information. How much lithium is in tree nuts? Peanuts? Melons? Onions? Various kinds of legumes? How much is in major crops like soy? This is part of why we need to do our own survey, to fill these gaps and run a more systematic search.
Meat seems to contain a lot of lithium, but honestly not that much more than things like tomatoes and goji berries. Vegetarians will consume less lithium when they stop eating meat, but if they compensate for not eating meat by eating more fruit, they might actually be worse off. If they compensate by eating more eggs, or picking up whey protein, they’re definitely worse off!
Vegans have it a little better — just by being vegan, they’ll be cutting out the three most reliable sources of lithium in the general diet. As long as they don’t increase their consumption of goji berries to compensate, their total exposure should go down. Hey, it makes more sense than “not eating dairy products gives you psychic powers because otherwise 90% of your brain is filled with curds and whey.”
But even so, a vegan can get as much lithium as a meat-eater if they consume tons of nightshades, so even a vegan diet is not a sure ticket to lithium removal. Not to mention that we have basically no information on plant-based protein sources (legumes, nuts) so we don’t know how much lithium vegans might get from that part of their diet.
There’s certainly lithium in our food, sometimes quite a bit of lithium. It seems like most people get at least 1 mg a day from their food, and on many days, there’s a good chance you’ll get more.
That said, most of the studies we’ve looked at are pretty old, and none of them are very systematic. Sources often disagree; sample sizes are small; many common foods haven’t been tested at all. The overall quality is not great. We don’t think any of this data is good enough to draw strong conclusions from. Personally we’re avoiding whey protein and goji berries for right now, but it’s hard to get a sense of what might be a good idea beyond that. So as the next step in this project, we’re gonna do our own survey of the food supply.
The basic plan is pretty simple. We’re going to go out and collect a bunch of foods and beverages from American grocery stores. As best as we can, we will try to get a broad and representative sample of the sorts of foods most people eat on a regular basis, but we’ll also pay extra-close attention to foods that we suspect might contain a lot of lithium. Samples will be artificially digested (if necessary) and their lithium concentration will be measured by ICP-MS. All results will be shared here on the blog.
Luckily, we have already secured funding for the first round of samples, so the survey will proceed apace. If you want to offer additional support, please feel free to contact us — with more funding, we could do a bigger survey and maybe even do it faster. We could also get a greenhouse and run some hydroponic studies maybe.
If you’re interested in getting involved in other ways, here are a few things that would be really helpful:
1. If you would be willing to go out and buy an egg or whatever and mail it in to be tested, so we could get measurements from all over the country / the world, please fill out this form.
2. If you work at the FDA or a major food testing lab or Hood Milk or something, or if you’re a grad student with access to the equipment to test your breakfast for lithium and an inclination to pitch in, contact email@example.com to discuss how you might be able to contribute to this project.
Back in the day, people “knew” that the way to write good software was to assemble an elite team of expert coders and plan things out carefully from the very beginning. But instead of doing that, Linus just started working, put his code out on the internet, and took part-time help from whoever decided to drop by. Everyone was very surprised when this approach ended up putting out a solid operating system. The success has pretty much continued without stopping — Android is based on Linux, and over 90% of servers today run a Linux OS.
Before Linux, most people thought software had to be meticulously designed and implemented by a team of specialists, who could make sure all the parts came together properly, like a cathedral. But Linus showed that software could be created by inviting everyone to show up at roughly the same time and place and just letting them do their own thing, like an open-air market, a bazaar.
Let’s consider in particular Chapter 4, Release Early, Release Often. One really weird thing Linus did was he kept putting out new versions of the software all the time, sometimes more than once a day. New versions would go out with the paint still wet, no matter how much of a mess they were.
People found this confusing. They thought putting out early versions was bad policy, “because early versions are almost by definition buggy versions and you don’t want to wear out the patience of your users.” Why the hell would you put out software if it were still crawling with bugs? Well,
Linus was behaving as though he believed something like this:
> Given a large enough beta-tester and co-developer base, almost every problem will be characterized quickly and the fix obvious to someone.
Or, less formally, “Given enough eyeballs, all bugs are shallow.” I dub this: “Linus’s Law”.
This bottom-up method benefits from two key advantages: the Delphi Effect and self-selection.
More users find more bugs because adding more users adds more different ways of stressing the program. This effect is amplified when the users are co-developers. Each one approaches the task of bug characterization with a slightly different perceptual set and analytical toolkit, a different angle on the problem. The “Delphi effect” seems to work precisely because of this variation. In the specific context of debugging, the variation also tends to reduce duplication of effort.
So adding more beta-testers may not reduce the complexity of the current “deepest” bug from the developer’s point of view, but it increases the probability that someone’s toolkit will be matched to the problem in such a way that the bug is shallow to that person.
One special feature of the Linux situation that clearly helps along the Delphi effect is the fact that the contributors for any given project are self-selected. An early respondent pointed out that contributions are received not from a random sample, but from people who are interested enough to use the software, learn about how it works, attempt to find solutions to problems they encounter, and actually produce an apparently reasonable fix. Anyone who passes all these filters is highly likely to have something useful to contribute.
Linus’s Law can be rephrased as “Debugging is parallelizable”. Although debugging requires debuggers to communicate with some coordinating developer, it doesn’t require significant coordination between debuggers. Thus it doesn’t fall prey to the same quadratic complexity and management costs that make adding developers problematic.
In practice, the theoretical loss of efficiency due to duplication of work by debuggers almost never seems to be an issue in the Linux world. One effect of a “release early and often” policy is to minimize such duplication by propagating fed-back fixes quickly.
Without a huge research budget and dozens of managers, you won’t be able to coordinate a ton of researchers. But the good news is, you didn’t really want to coordinate everyone anyways. You can just open the gates and let people get to work. It works fine for software!
The best way to have troubleshooting happen is to let it happen in parallel. And the only way to make that possible is for everyone to release early and release often. If you sit on your work, you’re only robbing yourself of the debugging you could be getting for free from every interested rando in the world.
In the course of our obesity research, we’ve talked to water treatment engineers, social psychologists, software engineers, emeritus diabetes researchers, oncologists, biologists, someone who used to run a major primate lab, multiple economists, entrepreneurs, crypto enthusiasts, physicians from California, Germany, Austria, and Australia, an MD/PhD student, a retired anthropologist, a mouse neuroscientist, and a partridge in a pear treea guy from Scotland.
Some of them contributed a little; some of them contributed a lot! Every one had a slightly different toolkit, a different angle on the problem. Bugs that were invisible to us were immediate and obvious to them, and each of them pointed out different things about the problem.
For example, in our post recruiting for the potato diet community trial, we originally said that we weren’t sure how Andrew Taylor went a year without supplementing vitamin A, and speculated that maybe there was enough in the hot sauces he was using. But u/alraban on reddit noticed that Andrew included sweet potatoes in his diet, which are high in vitamin A. We totally missed this, and hadn’t realized that sweet potatoes are high in vitamin A. But now we recommend that people either eat some sweet potato or supplement vitamin A. We wouldn’t have caught this one without alraban.
In another discussion on reddit, u/evocomp challenged us to consider the Pima, a small ethnic group in the American southwest that were about 50% obese well before 1980, totally bucking the global trend. “What’s the chance that [this] population … [is] highly sensitive and equally exposed to Lithium, PFAS, or whatever contaminants are in SPAM or white bread?” evocomp asked. This led us to discover that the Pima in fact had been exposed to abnormal levels of lithium very early on, about 50x the median American exposure in the early 1970s. Before this, lithium had been just one hypothesis among many, but evocamp’s challenge and the resulting discoveries promoted it to the point where we now think it is the best explanation for the obesity epidemic. Good thing the community is helping us debug!
My original formulation was that every problem “will be transparent to somebody”. Linus demurred that the person who understands and fixes the problem is not necessarily or even usually the person who first characterizes it. “Somebody finds the problem,” he says, “and somebody else understands it. And I’ll go on record as saying that finding it is the bigger challenge.”
This is a classic in the history of science. One person notices something weird; then, 100 years later, someone else figures out what is going on.
Brownian motion was first described by the botanist Robert Brown in 1827. He was looking at a bit of pollen in water and was startled to see it jumping all over the place, but he couldn’t figure out why it would do that. This bug sat unsolved for almost eighty years, until Einstein came up with a statistical explanation in 1905, in one of his four Annus Mirabilis papers. Bits of pollen jumping around in a glass of water doesn’t sound very interesting or mysterious, but this was a big deal because Einstein showed that Brownian motion is consistent with what would happen if the pollen was being bombarded from all sides by tiny water molecules. This was strong evidence for the idea that all matter is made up of tiny indivisible particles, which was not yet well-established in 1905!
Or consider DNA. DNA was first isolated from pus and salmon sperm by the Swiss biologist Friedrich Miescher in 1869, but it took until the 1950s before people figured out DNA’s structure.
Complex multi-symptom errors also tend to have multiple trace paths from surface symptoms back to the actual bug. … each developer and tester samples a semi-random set of the program’s state space when looking for the etiology of a symptom. The more subtle and complex the bug, the less likely that skill will be able to guarantee the relevance of that sample.
For simple and easily reproducible bugs, then, the accent will be on the “semi” rather than the “random”; debugging skill and intimacy with the code and its architecture will matter a lot. But for complex bugs, the accent will be on the “random”. Under these circumstances many people running traces will be much more effective than a few people running traces sequentially—even if the few have a much higher average skill level.
This is making an important point: if you want to catch a lot of bugs, a bunch of experts isn’t enough — you want as many people as possible. You do want experts, but you gain an additional level of scrutiny from having the whole fuckin’ world look at it.
Simple bugs can be caught by experts. But complex or subtle bugs are more insane. For those bugs, the number of people looking at the problem is much more important than the average skill of the readers. This is a strong particular argument for putting things on the internet and making them super enjoyable and accessible, rather than putting them in places where only experts will see them.
Not that we need any more reasons, but this is also a strong argument for publishing your research on blogs and vlogs instead of in stuffy formal journals. If you notice something weird that you can’t figure out, you should get it in front of the scientifically-inclined public as soon as possible, because one of them has the best chance of spotting whatever you have missed. Back in the day, the fastest way to get an idea in front of the scientifically-inclined public was to send a manuscript to the closest guy with a printing press, who would put it in the next journal. (Or if possible, go to a conference and give a talk about it.)
Job postings are a kinda weird phenomenon. For one thing, they’re very modern. It used to be that most people either inherited a job (I’m a baker because my pa was a baker and our tiny hamlet needs a baker) or noticed an opportunity and ran with it (lots of hungry travelers cross that bridge every day, I bet I could make a living selling pancakes).
We’re talking about the second thing today, the opportunity just waiting for someone to snap it up. This is a job posting, but we’re not hiring. Reddit is hiring. Well, not REDDIT. The abstract spirit of reddit is hiring. The universe is hiring.
Let us try to explain.
Czar was originally a term for East and South Slavic monarchs, most notably the Russian emperor — it’s another spelling of Tsar and yet another corruption of the Roman title Caesar, just like Kaiser. But at some point in the middle of the 20th century it became a term in the US and UK for government officials “granted broad power to address a particular issue”. The Industry Czar is in charge of industry, the Milk Czar is in charge of milk, the Asian Carp Czar is in charge of Asian Carp (no, really), and so on and so forth.
There are lots of problems in the world; some are covered, but there are many others where existing institutions have totally dropped the ball. Often, more research would help. But the academy just doesn’t move as fast as it used to. If you’ve ever looked at something and been like, “someone should do a study”, you know what we mean.
This means there are lots of special populations on reddit, people who have a condition or illness, maybe a rare one, who are extreme outliers (e.g. very tall and/or live in a submarine), or who have a burning obsession with some niche idea. Subreddits bring people together, to commiserate, to try to help each other solve a problem, or to post insane fanart.
These people are all very interested in their shared topic. They are all highly motivated. Many of them are ready to self-experiment, or are already self-experimenting. A lot of things count as self-experimentation. If you’re doing a diet, or trying to get more sunlight, or even just trying to drink more water, that’s self-experimentation too. So a subreddit for a given problem or topic is a powder keg of interest and motivation, just waiting for a spark.
Because while subreddits are very motivated, they’re largely untapped for organized research. Even in subreddits with good leadership, it’s rare for the leadership to have a research background. Most communities lack someone with the methods skills to design a good study, and the statistical analysis skills to examine the data afterwards.
If you have these skills, and you are familiar with reddit, you could show up and start helping people organize research. You could collaborate with people to help them solve their problems, or at least learn more about their problems, and you could start doing it tomorrow.
Crowdsourcing research like this is under-explored. Almost no one has ever done studies organized like this, so in our opinion, there’s virtually guaranteed to be low-hanging fruit all over the place. Anything that isn’t sexy enough for a major journal or doesn’t sound serious enough for the NIH to spend their time on is ripe for the picking.
The current research world is very narrow-minded. Doctors and researchers are quick to blame a person’s behavior or hygiene and very slow to blame environmental contaminants. If you’re more creative or more open-minded, and you’re willing to consider other paradigms, you can just move faster. If doctors don’t take the pathogen paradigm for chronic disease and digestive disorders seriously, then by becoming the “Pathogenic Disease Czar”, you might be able to rack up discoveries really quickly.
There’s also the question of “why now”? Part of it is that the research world has slowed down. But another part is that the rest of the world has sped up. We’re more coordinated than ever. Today you can get 100 people reading your latest newsletter in 20 minutes. Today you can pop by a subreddit and consult with thousands of people in a matter of hours. Today you can cold-email an emeritus professor who worked on the problem in the 1970s and be on a Zoom call with them next week.
Research tools are also opening up, getting more accessible every day. If you’re leading the reddit charge on some rare glandular disorder, it now takes only a couple hundred dollars per person for everyone involved to get their genome sequenced and it’s getting cheaper all the time. If there’s a genetic explanation, or genetics is involved in some way, it’s only recently gotten cheap enough that communities might able to find it on their own.
There are lots of interesting ideas where the only support for them is a single paper with 20 participants from 1994. If you can get a couple dozen volunteers together, boom, you’ve just advanced the state of the field, and discovered whether or not there was anything to that interesting idea.
How do we get stronger evidence [for the potato diet]? Well someone has to go out on a limb and run an experiment. This is a particularly important motivation for me. If this were not part of a larger study, I wouldn’t spend my energy on it (after all, it probably won’t work). But the fact that it might yield useful data makes it much more appealing.
Obesity and related issues (heart disease, diabetes, etc.) is just one example of a serious problem that people are invested in solving. It seems like there are lots of problems where we might be able to quickly learn a lot by rigorous self-experimentation and community research.
Depression and anxiety are classic unsolved problems. Sure, we have some mildly effective treatments, but why don’t we have great ones? Why does a given treatment work for some people and not others? What about people with treatment-resistant depression? Why are things like exhaustion and brain fog symptoms of depression? Where does depression come from? There’s been a lot of discussion but our take is still “no one knows” or at least, “the jury’s still out”. We see that r/depression/ has over 800,000 members and a couple thousand are usually online at a given time. If you think you could help, they seem like they would be glad to have it.
Crohn’s disease is debilitating and remains very poorly understood — Wikipedia, for example, says, “While the precise causes of Crohn’s disease (CD) are unknown, it is believed to be caused by a combination of environmental, immune, and bacterial factors in genetically susceptible individuals. … While Crohn’s is an immune-related disease, it does not appear to be an autoimmune disease (in that the immune system is not being triggered by the body itself). The exact underlying immune problem is not clear; however, it may be an immunodeficiency state.” Sounds like more research is needed, and r/CrohnsDisease/ has 42,000 members.
If that’s not mysterious enough for your taste, there are all the really inexplicable digestive conditions, which go by names like IBS (irritable bowel syndrome) and GERD (gastroesophageal reflux disease). These can really fuck you up, so people will be really motivated to try things and find a treatment. And there might be weird treatments out there that really work. You can drop by r/ibs/ with 74,000 members or r/GERD/ with 42,000 members and start putting out surveys, today if you want! (But talk to the mods first, don’t get kicked out for being a weirdo.)
There are also some populations that will be interesting not because they are facing a problem they want to solve, but because they are special in some other way. Trans people would love to have better resources for transitioning, and you could certainly drop by to help them study that. But we think the real reason to drop by r/TransDIY/ and similar subreddits is because you have literally thousands of people conducting n = 1 endocrinology experiments.
There’s a good chance the next great endocrinologist will be trans, just because of their personal familiarity with the subject and ability to self-experiment. If you want to see what effect testosterone/estrogen/progesterone/estradiol has on mood/energy/digestion/attention/nerve growth/body temperature/whatever, this is one of your few and best chances to get experimental data.
This is nowhere near a complete list. In fact, please drop other subreddits that might be excited to do more community research in the comments.
We call this a job posting because we think this could easily be a full-time job. If you help a community or two get closer to solving their problem, even if you just help them coordinate and give them HOPE that their problem is solvable, it would be pretty easy to convince lots of them to chip in. It’s hard for an individual to hire an expert, but some of these communities have tens or hundreds of thousands of members. For a community that size, hiring some full-time research muscle is easy.
You set up a Patreon or a newsletter (we recommend Ghost), and ask for support. If you can get 1000 people to give you $3 a month, that’s $36,000 a year, enough to start thinking about doing this full-time.
You don’t need to solve anything up front. You just need to convince 1000 people that you’re doing enough to justify them spending $3 a month on something they think is important, which is not a hard sell. And if you get 10,000 people on board for $1, you’re even better off. (Incidentally, here is our patreon.)
Crowdfunding is the best and noblest option, but it’s not the only route you can take. Some communities will have a millionaire or two in the ranks, and if you start doing good work, people will come out of the woodwork to help. There are lots of granting agencies out there looking for stunning projects to throw money at. Start coordinating reddit research for a few months, show that you’re serious, make a little progress, and it should be easy to make the case for some grants.
And actually, you might also be able to get funding from reddit, up to $50,000! Starting June 2022, reddit will start distributing one million dollars in community funding to different subreddits. If you can make the case to a subreddit that you can lead their community research for a year, they can apply for $40,000 to be your salary, and there’s a good chance they’ll get it. The article linked above says, “I can’t wait to see what wild project the r/WallStreetBets crew tries to get $50,000 to pull off.” Yeah holy shit.
Finally, if you are financially independent / have a good job that gives you lots of free time, then this is DEFINITELY a job suited for you. You already don’t have to worry about money; maybe you even have enough that you could pay for a statistician / the chemical analysis of samples / new air quality monitors / sundry other research expenses. You’re looking for something interesting to spend your time on, something that also makes the world a better place. If you have the skills and inclination, nothing could be a better fit!
It’s worth touching for a moment on the skills we think would be important. Any research on reddit would probably start with a lot of surveys, so someone with lots of experience with survey-based methods might have the advantage here. Possibly a sociologist or psychologist? But on the other hand, a lot of the problems reddit communities would be interested in solving are medical, so maybe someone with a medical background is the best person for the role. On the other other hand, a lot of the advantage here might be statistical, having the skill to work with big strange datasets, so maybe a data scientist.
Or form a cabal if you want:
Anyways, if this is the job you want, and you think you have the skills to do it, there are two general ways to approach this…
If you are a person who is a member of one of these communities, who is inclined towards research and wants to rally people to solve the problem, going specific might be the approach for you.
There are a couple winning examples already, let’s take a look. These two don’t use reddit for the most part — they have communities elsewhere — but it’s not hard to imagine recreating some of their successes in a subreddit rather than on a blog or on twitter.
Whorelord and “mad social scientist” Aella is kind of de facto sex worker / sex research czar for the whole internet. She also does psychology and psychedelics research, which must be reasonably well-regarded because her twitter followers include some big names in psychology, like Paul Bloom and Uri Simonsohn (and see this interaction). But mostly it’s sex stuff, and the quality of her research puts the average social science publication to shame:
Scott is a rationalist and Aella has lots of sex / is a (former) sex worker, so they’re perfectly positioned to be the research czars for their communities. We’d recommend that the “go narrow” approach be taken with communities you are a part of as well.
There are clear advantages to going narrow. First off, you can self-experiment. You can pilot-test studies on yourself, and you can show people that you would never ask them to do anything you aren’t willing to try first. You can specialize and learn a lot about this one area of research. And you’ll understand the topic better, because you’ve lived it.
There are also a couple of disadvantages. This has a smaller scope, but some of you might like that. It’s less exciting, and maybe harder to get support and raise money for projects. But it’s also more practical.
In this approach, you try to work with lots of different subreddits, lots of different communities, and try to solve lots of different problems. Instead of focusing on just one mystery at a time, you go broad.
If you are a generalist with good research chops, who spends a lot of time on reddit and knows how it works, who likes the idea of working with tons of different people, on dozens of projects, this might be the approach for you.
This approach has some clear advantages. If you work on more projects, you will be able to get funding from more quarters. As you try more and more things, you’ll learn a lot about the metascience of doing this new kind of community research. You can switch between projects when you’re waiting for results. If you hit a dead end on one question, you can take some time off and switch to something else. More things to work on means it’s more likely something will be a success.
There are also a few disadvantages. You’ll always risk getting spread too thin, and you will spend lots of time getting familiar with new topics, instead of going deep on just a few. You probably won’t share most of the problems you want to help solve. Since you don’t have these diseases/conditions/whatevers, you won’t be able to self-experiment, and self-experimentation is an important part of research. And some communities won’t want or appreciate help from an outsider.
To Sum Up
Reddit is a big place. There’s a lot of questions to answer, problems to solve, and communities to rally to the mad science crusade.
Probably by 2030 there will be several major researchers on reddit, and two or three of them will be getting close to being household names. Some of them will be generalists who hop around different subreddits, consulting on different problems. Some of them will be specialists, organizing their communities against shared problems. Different research czars will work together to make bigger and better projects, and problems will get solved faster than anyone today thinks possible.
But why wait to see other people do it? If you think you have what it takes (or half of what it takes; don’t be afraid to learn on the job), there’s nothing stopping you from doing this starting tomorrow. We’d be happy to consult on stats and methods — and if you do anything interesting, we might blog about it. If you declare yourself Czar of X and you make a big breakthrough, we will send you a crown (though it will not be this nice).
In French, the word for potato is pomme de terre. This literally translates to apple of the earth. By this logic, potatoes are the lowest-hanging fruit of all.
More seriously: We keep getting more and more interested in the all-potato diet. This is a diet where you eat nothing but potatoes (and sometimes a bit of seasoning) for a few weeks to a few months. It sounds like a dumb gimmick that could never work, but there are a surprising number of people out there saying that they tried it, it worked for them, and they kept the weight off for months or even years after.
Anecdotes are limited in all sorts of ways, but there are a surprising number of very strong anecdotes about the all-potato diet causing huge amounts of easy, sustainable weight loss:
There also have been a few attempts on reddit, like this one, where user AdFair8076 said, “Potato’s are a super food imho. Lost 9 lbs in a week and haven’t put it back. Appetite is better!” EDIT: also u/DovesOfWar, u/caleb-garth, u/window-sil, etc.
Again, anecdotes by themselves are limited. We don’t know how many people tried this diet and didn’t get such stunning weight loss. We don’t know how long the weight stays off for. And the sample size is really small. Someone should really do a study or something, and figure this thing out.
Well, ok, if you insist. But you all have to help!
Tl;dr, we’re looking for people to volunteer to eat nothing but potatoes (and a small amount of oil & seasoning) for at least four weeks, and to share their data so we can do an analysis. You can sign up below.
Aren’t there already diets that work? Well, maybe, but we certainly don’t have any that work reliably. Reviews of meta-analyses say things like, “Numerous randomized trials comparing diets differing in macronutrient compositions (eg, low-carbohydrate, low-fat, Mediterranean) have demonstrated differences in weight loss and metabolic risk factors that are small (ie, a mean difference of <1 kg) and inconsistent.” And The Lancet says, “unlike other major causes of preventable death and disability, such as tobacco use, injuries, and infectious diseases, there are no exemplar populations in which the obesity epidemic has been reversed by public health measures.” We could go on like this all day — actually wait, we already did.
There are all sorts of crazy fad diets out there that haven’t been formally tested, and many of them have anecdotes that sound at least this good. Some of you may have even tried one. So why are we so interested in this over all the others?
Most diets are unpleasant and require you to use a lot of willpower to eat the right stuff or avoid the wrong stuff. On most diets, people are hungry all the time and feel terrible and gain the weight back as soon as they stop dieting. But the potato diet, at least according to the anecdotes, isn’t unpleasant at all — it’s quite easy. This isn’t a willpower diet. If the diet works, and it’s as easy to stick to as they say, that would be an important finding.
Most diets are hard to follow in that the instructions are precise and/or complicated — you have to eat exactly the right ratio of stuff to other stuff, carefully weigh and measure all your portions, count calories, do a lot of math in your head, check all the ingredients in everything you buy, etc. In contrast, the all-potato diet is really simple. No complex principles. No weighing and measuring your food. No checking ingredients. Just potato.
Some diets claim they won’t work unless you do everything just right. If you don’t lose weight on one of these diets, fans of the diet can always fall back on saying, maybe you did it wrong. In comparison, potato diet is easy. We don’t think it really matters if you accidentally eat a chocolate bar, as long as you are eating mostly potatoes. If you eat mostly potatoes and you don’t lose weight, then the diet doesn’t work, no one will be saying “you did it wrong.”
The potato diet also appears to have a huge effect size — 20 lbs for Chris Voigt, 114 lbs for Andrew Taylor, etc. — which should make it easy to study. We’re not fiddling around with a diet that might make you lose 5 lbs. If most people lose as much weight as Chris and Andrew, that will be really obvious. And if it doesn’t work for most people, well, that’s an important finding too.
Finally, one of the most interesting things about the potato diet is that people seem to keep the weight off afterwards, which is basically unheard of for diets. If we can confirm that in a study, it will be a pretty big deal.
So that’s why we want to study the potato diet in particular. It should be easy to get a straight answer about this diet. If it works, people will be able to use this diet to lose weight and gain energy, if that’s what they want. And if it works, it probably provides some kind of hint about why the obesity epidemic is happening in the first place. So let’s do a study.
To figure out how to run this study, we needed to figure out what kind of all-potato diet seems to work for weight loss. To do this, we took a close look at the case studies we mentioned above. Some of these accounts are pretty detailed, so we won’t bore you with it up front. If you want more detail, we give an overview of each case study in the appendices.
The overall picture looks pretty clear. The basis of the all-potato diet is, unsurprisingly, eating almost nothing but potatoes.
In the most extreme cases, like Penn Jillette and the Krocks, people appear to eat literally nothing but potatoes, with no seasonings, and drink nothing but water. This seems to work pretty well but sounds like it would be hard to stick to. It’s notable that both of these examples kept it up for only two weeks, though they did lose impressive amounts of weight.
In comparison, Andrew Taylor was able to stick to an all-potato diet for a full year. He let himself use spices and seasonings, drank things other than water, and he still lost more than 100 pounds. He just made sure to take a B12 vitamin and kept away from oil and dairy.
Chris Voigt lost the least weight, but he seems to have had a pretty easy time of it. He was able to lose 21 lbs while using all kinds of salt and seasonings and cooking his potatoes in oil, and he wasn’t even trying to lose weight at all. This suggests, to us at least, that stricter versions of the diet aren’t necessary to see the benefits.
Potatoes are indeed very nutritious (here’s the USDA page for russet potatoes). The official word is that they don’t contain any vitamin A and don’t contain any B12. We’re not sure about the vitamin A — Andrew Taylor went a year without supplementing vitamin A (he did take B12), but maybe he got all the vitamin A he needed from the sauces he used? In any case, a vitamin B12 supplement is appropriate, and a vitamin A supplement seems like a good idea. [EDIT: u/alraban on reddit points out that Andrew ate sweet potatoes, which are high in Vitamin A. This is a good point, so now our recommendation is that you should either include sweet potatoes or take a Vitamin A supplement.] If you take a normal multivitamin you should be totally covered — but again, none of the case studies seem to have needed it.
Based on these examples taken together, our version of the diet is:
THE POTATO DIET
Drink mostly water. You can also have some other beverages. Chris Voigt had coffee, tea, and diet soda. Andrew Taylor sometimes had beer, even. Just don’t take them with cream or sugar and try not to get too many of your daily calories from your drinks.
Eat potatoes. Buy organic if you can, and eat the peels whenever possible. Start with whole potatoes and cook them yourself when you can, but in a pinch you can eat potato chips or fries if you need to. You can calculate how many potatoes to eat (a potato is about 100 calories, so if you need 2000 kcal/day, eat about 20), but we think it’s better to eat the potatoes ad libitum — make a lot of potatoes and just eat as much as you want.
Perfect adherence isn’t necessary. If you can’t get potatoes, eat something else rather than go hungry, and pick up the potatoes again when you can.
Seasonings are ok. Chris used seasonings like Tabasco sauce, chives fresh out of his garden, a Thai herb/pepper paste, and bouillon cubes in water for fake gravy. Andrew used seasonings like dried herbs, fat-free sweet chili, barbecue sauce, and soy milk (in mashed potatoes). Do what you can to keep yourself from getting bored.
Oil is ok. Chris used it, Andrew and Penn didn’t. You can go either way. In fact, it would be great for us if some of you use oil and others of you don’t, so we can see if there is any difference. If you do use oil, probably use olive oil, which seems to be what Chris used. Maybe consider imported olive oil from Europe, which we suspect contains fewer contaminants, in case the contamination theory is correct.
Take a daily B12 supplement, since potatoes don’t contain any. We like this version but use whatever you like. Take vitamin A if you’re not eating sweet potatoes. A multivitamin would also be fine as long as it contains B12.
Everyone seems to agree: No dairy. Maybe this doesn’t matter, but on the off chance this is really important for some reason, please avoid all dairy products.
If in doubt, pick one of the examples we describe in the appendices and follow their example. You can always ask yourself, what would Chris Voigt do? And then do that.
In the spirit of self-experimentation, and because we were curious, one of us decided to try the all-potato diet for ourselves. That author is currently on day 11 of the all-potato diet. In that author’s own words:
I was originally going to do just one or two days of the potato diet to see what it was like, but it was so easy that I figured I should try to keep to it for a full week. But it was still easy at a week, and now I’m just curious how long I can keep going for.
I feel fine, totally normal. I don’t feel more energetic than normal, but I’m pretty energetic to begin with. My mood is a little better, and I’m maybe sleeping better. Exercise seems easier, or at least it’s not any harder, kind of surprising when all my protein comes from potatoes. I haven’t lost any weight but I’m not overweight so I didn’t have much to lose in the first place.
It doesn’t require any willpower. I don’t crave anything else, I’m not tempted to buy other food at the grocery store, I’m not jealous when people around me are eating pizza or chocolate. I’m happy to sit down to a pile of potatoes every meal. They still smell delicious. If anything, I like potatoes even more now. The hardest part is the logistics of preparing that many potatoes every single day.
I’m using European olive oil, salt, spices, vinegar, and a couple of hot sauces to keep the potatoes interesting. I want to say that it would be much harder without them, but honestly, this is so much easier than I expected, I don’t know what to expect anymore. Maybe it would be just as easy without oil and hot sauce.
Here’s my advice based on my personal experience. You should get a wide variety of potatoes. When you’re eating nothing but potatoes, the differences between different varieties become very obvious. At first I was happy with yukon gold but after a few days I began to crave russet potatoes. Make a lot every time you cook, you will eat more than you expect. And make sure to drink lots of water, I keep finding it hard to remember and end up feeling dehydrated.
UPDATE DAY 13: For the last two days I tried nothing but baked potatoes with no oil and barely any spices. It was really easy, I feel super energetic, and I started losing weight. So if the diet isn’t having any effect for you, consider trying it with no oil.
That’s the diet we’re thinking of. What about the study design?
Official-sounding diet studies from like the NIH and stuff don’t always run all their subjects at the same time, so we won’t bother doing that either. We’ve made it so you can sign up and participate in this study at any time. Rolling admissions.
There’s no need for a control group because the spontaneous remission rate for obesity is so low. For example, if someone said they had invented a medicine that could re-grow lost limbs, we wouldn’t need a control group for that trial, because the spontaneous limb regrowth rate is almost exactly zero (in humans anyways). If anyone regrew their arms or legs, that would be pretty convincing evidence that the medicine works as promised. Similarly, people almost never spontaneously drop 20 pounds, so we don’t need a control group.
This is also a trap. We expect that some people will come back with “but there wasn’t a control group!” This is a sign that they didn’t actually read what we’ve written and are boneheads who don’t understand how research works.
We’re not worried about tight experimental control. Maybe this diet would work better in the lab, but what we are actually interested in is how it works when implemented by normal people in the comfort of their home. If it doesn’t work in those circumstances, we want to know that! If the potato diet can’t be used practically, we don’t really care if it works in the lab, we know which side our potato is buttered sprinkled with garlic salt on. If it doesn’t work with this design, it just doesn’t work. And if it does work at home, it would presumably work even better in the lab.
We’re also interested in the huge effect size described in the anecdotes above. We’re not worried about tiny amounts of noise from things like what you’re wearing or what time of day you weigh yourself. If the experience of Chris Voigt is at all typical — if the average person loses about 20 lbs — these tiny differences won’t matter.
And we’re not all that worried about adherence. If the 100% potato diet works, the 90% potato diet probably works too. So while we prefer that anyone sending us their data tries to refrain from eating any delicious pickles during the diet, if you do eat a pickle, it probably doesn’t matter.
Sign up to Eat Potatoes for the Glory of Science
This looks pretty promising, so let’s try to go past the anecdotes and do this in something like a rigorous fashion. Who wants to eat some ‘taters?
The only prerequisite for signing up is being willing to eat nothing but potatoes for at least four weeks, and being willing to share your weight data with us.
(And being an adult, having a scale, not being allergic to potatoes, etc. etc.)
One reason to sign up is that you hope this will help you lose weight, lower your blood pressure, make you less depressed, or see one of the other effects reported by people like Chris Voigt and Andrew Taylor. But another reason you might want to sign up is to help advance the state of nutritional science. In a small way, this study will tell us something about nutrition, weight loss, and obesity that we don’t currently know. If the diet works, it will give us a practical intervention that people can use to reduce their weight, which we don’t really have right now.
And beyond that, running a study like this through volunteers on the internet is a small step towards making science faster, smarter, and more democratic. Imagine a future where every time we’re like, “why is no one doing this?”, every time we’re like, “dietary scientists, what the hell?”, we get together and WE do it, and we get an answer. And if we get a half-answer, we iterate on the design and get closer and closer every time.
That seems like a future worth dreaming of. If you sign up, you get us closer to that future. We hope that this is only the first of what will be a century full of community-run scientific trials on the internet. Maybe by 2030, the redditors will have found a way to triple your lifespan. But for the first study, let’s start with potato.
We understand that eating nothing but potatoes for four weeks sounds pretty daunting. But based on the case studies above, and our own experience, we want to reassure you that it will probably be much easier than you expect. In fact, here’s our suggestion: If you are at all interested in trying it, go ahead and sign up and start collecting your data. Try the first day or two and see how it feels.
If it’s really hard for you to stay on the diet and you just can’t continue, go ahead and stop, just send us an email and close out the diet as normal (see instructions below). We’re interested in the diet as a whole, and if 40% of people can’t stick to the diet for more than two days, that’s important information about how effective the diet is in a practical sense. We’d be happy to have that information.
But based on our own experience, we suspect that most of you who try it for a couple days will be like, “wow this is so easy! I could do this for a couple weeks no problem.” If that’s how you feel, keep collecting your data and see if you can keep it up for four weeks.
If you want to go for longer than four weeks, that’s great, we would be happy to have more data.
If at any point you get sick or begin having side-effects, stop the diet immediately. We can still use your data up to that point, and we don’t want anything to happen to you.
If you are taking potassium supplements, often given as blood pressure medications (like Losartan) please take this extra seriously. A diet of 20 potatoes a day will give you about 300% your recommended potassium. While this should be safe by itself, it might be a problem if you are already taking a potassium supplement. Don’t sign up if you have bad kidneys, kidney disease, or diabetes (you can check with your doctor). Be aware of the signs of hyperkalemia.
We are mostly interested in weight loss effects for people who are overweight (BMI 25+) or obese (BMI 30+), but the energy and mental health effects reported in some of the case studies are interesting too. If you are “normal weight” (BMI 20-25) you can also sign up, especially if you want to feel more energetic or you want to tackle depression and anxiety or something.
And for everyone, please consult with your doctor before trying this or any other weight loss regimen. We are not doctors. We are 20 rats in a trenchcoat. eee! eee! eee!
Anyways, to sign up:
Fill out this google form, where you give us your basic demographics and contact info. You will assign yourself a subject number, which will keep your data anonymous in the future.[UPDATE: Signups are now closed, but we plan to do more potato diet studies in the future. If you’re interested in participating in a future potato diet study, you can give us your email at this link and we’ll let you know when we run the next study.]
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.
On the first day, weigh yourself in the morning. If you’re a “morning pooper”, measure yourself “after your first void”; if not, don’t worry about it. We don’t care if you wear pajamas or what, just keep it consistent. Note down your weight and the other measures (mood, energy, etc.) on the google sheet. Then spend day 1 eating nothing but potatoes. On day 2, weigh yourself in the morning, note down data in the sheet, then spend day 2 eating nothing but potatoes. On day 3, etc.
We prefer that you stick closely to the diet for at least four weeks. But if you do break the diet at some point, just note that down in the appropriate column and try to stick to the diet the next day. Again, we’re interested in how the diet works for normal people at home, and so imperfect adherence is ok. If you totally can’t stand the diet, just stop doing it and end the study per the next instructions.
Whenever you are done with the diet (preferably four weeks, or longer if you want, we’re happy to have more data if you are enjoying the diet), weigh yourself and fill out one last morning’s data so we have an endpoint, then stop the diet.
Then, send us an email with the subject line “[SUBJECT ID] Potato Diet Complete”. This will let us know to go grab your data. This is also your opportunity to tell us all about how the diet went for you. Please tell us all the data that doesn’t easily fit into the spreadsheet — how you felt on the diet, what brand of oil you used, what kind of potatoes you bought, where you got them from, what kind of cookware you used, before and after pictures (if you want), advice to other people trying the diet, etc. We think there’s a pretty good chance that this diet will work for some people and not for others, and if that happens, we will dig into these accounts to see if we can figure out why (e.g. maybe this works with olive oil but not with vegetable oil, or something).
If we have our act together, we will send each of you a brief google form following up at 6 months and at 1 year, and maybe at future intervals (5 years?).
Assuming we get 20 or so people, we will write up our results and publish them on the blog. We would really like to get a couple hundred people, though, since at that point it becomes possible to do more complex statistical analyses. So if you think this is an interesting idea, please tell your friends.
We’ll keep this updated with roughly how many people have signed up and stuff, until we get bored or decide the study is closed:
Signed Up: 220 [CLOSED]
Past the 4-Week Mark: 46
We’re pretty happy with this study design. In particular, we don’t think it’s a weakness that people are doing this at home, since those are the conditions that we actually want to understand the diet under. We want to know how it works when it’s applied like it would actually be applied.
That said, if you are a wealthy donor and you want to fund a more controlled version of this — maybe, send 30 overweight and obese volunteers to a campground in Colorado for a couple weeks and feed them nothing but potatoes while they’re there, and hire a nurse or two to check up on them every day — please contact us. It’d be cheap as far as nutrition research goes, and we’ll make you a mixtape of potato songs.
Appendix A: Super Basic Potato Preparation
Use whatever recipes you want, but here are two very simple ways to prepare them.
Here’s how to roast any kind of potato:
Preheat oven to 425 F.
Spread a thin layer of olive oil on a large cookie sheet.
Wash potatoes and make sure they do not have any dirt or anything gross on them.
Cut off any gross spots on the outside of the potatoes.
Cut the potatoes into any of the following: large fries, slices about a quarter inch thick, or chunks a little bigger than a grape. Do the whole batch with the same method.
If you find any other bad spots while you’re cutting up the potatoes, cut them off and throw them away.
Put the cut potatoes in a large bowl and dress them with olive oil, salt, and whatever seasonings you want (salt, pepper, garlic powder, rosemary, etc.). Mix them so the oil and seasoning is all over the potatoes.
Put the potatoes on the cookie sheet and make sure they are all well seasoned / well oiled.
Put them in the oven for 20 minutes, then take them out and stir them with a wooden spoon or spatula. They will probably stick to the cookie sheet a bit, this is normal.
Put them back in for another 20 minutes and then take them out again. Let one cool and try it, making sure not to burn your mouth. If it seems done and edible, turn off the oven, your potatoes are done. If it still seems a little raw, put them back in for another 10 minutes.
When done, eat with your favorite no-calorie sauces and vinegars.
Here’s how to boil any kind of potato:
Fill a pot with enough water to cover however many potatoes you’re making. Salt the water and set it on the stove on high to boil.
Wash potatoes and make sure they do not have any dirt or anything gross on them.
Cut off any gross spots on the outside of the potatoes.
Cut the potatoes into small chunks. Any size is fine, but smaller chunks will cook faster.
If you find any other bad spots while you’re cutting up the potatoes, cut them off and throw them away.
When the water boils, put the potatoes in and turn the heat to medium.
Every five minutes, pull out a potato chunk, let it cool, and taste it to see if it’s ready.
When they are done, turn off the heat and pour the potatoes out into a colander.
Dress the potatoes with spices and olive oil (you probably want to add salt) and eat with your favorite no-calorie sauces and vinegars.
Chris was the Executive Director of the Washington State Potatoes Commission, and he was tired of hearing all the myths about potatoes being unhealthy. He wanted to remind people about the amazing nutrients contained in this everyday vegetable. So as a demonstration of the power of potato, he decided to eat nothing but 20 potatoes a day, for 60 days straight:
Chris started his diet on October 1, 2010, and didn’t use any milk, butter or cheese toppings for mashing his potatoes. The only way he had them were fried, boiled, mashed, steamed, chipped or baked. His diet continued for 60 straight days and ended on November 29, 2010.
Chris wasn’t trying to lose weight. In an interview conducted years later, he said, “I was kind of hoping to be alive at the end of the 60 days… I wasn’t trying to lose weight.” He was 197 pounds at the start of his diet and he describes himself as “six foot one and a half”, so his starting BMI was about 26, just slightly overweight. He seems to have been eating a pretty healthy diet beforehand and he wasn’t seriously overweight, which is why he didn’t think he would lose weight. In fact, he based his daily potato consumption off of a calculation of how much he would need to eat to maintain his starting weight. In response to an early comment on his blog, he said, “I’m eating 20 potatoes a day because that’s how many I’ll have to eat to maintain my current weight.”
But despite his best efforts, by the end of the 60 days, he weighed 176 lbs, a loss of 21 lbs to a BMI of 23.2. His cholesterol also went from 214 to 147, and his glucose went from 104 to 94. In fact, seems like almost everything that could be measured improved: “My cholesterol went down 67 points, my blood sugar came down and all the other blood chemistry — the iron, the calcium, the protein — all of those either stayed the same or got better.” (Here’s a page where someone has compiled a bunch of these numbers.)
Chris did all this in consultation with his doctor, and he does suggest that you have to have a baseline level of health for this to be safe:
Chris Voigt didn’t go on 20 potatoes and a diet blindly. He first carried out thorough consultations with his dietician and doctor to be sure that he could actually live on potatoes for 60 days straight. After all, you need hale and hearty kidneys for processing the excessive potassium provided by 20 potatoes every day. In addition, you should have also stored ample amounts of necessary nutrients that are lacking in potatoes, for instance vitamin A, for avoiding any harmful side effects.
Those were his results. What was the diet like?
In the abstract, Chris describes his diet like this:
Literally, I just ate potatoes and nothing else. There were a few seasonings, but no gravy, no butter, no sour cream, and just a little bit of oil for cooking. That was it.
That isn’t quite enough detail for our purposes. But older archives of Chris’s site have the blog, which gets a lot more specific. Read it for yourself for the full story, but here are some highlights, focusing on what kinds of potatoes he ate and how he prepared them:
Day 1 – So I had 5 baked red potatoes for breakfast, mashed potatoes with a little garlic seasoning for lunch, and while my family had all the fixing at the steakhouse celebrating my wife’s birthday, I had garlic mashed potatoes and an order of steak fries. The all potato diet wasn’t too bad today, but I did cringe a little when everyone had ice cream for dessert.
Day 2 – I’m really struggling to eat enough calories. I had two baked potatoes this morning with a couple shots of Tabasco sauce, a serving of mashed potatoes sprinkled with a few BBQ potato chips for a change in texture, and another serving of mashed potatoes and 5 roasted small red potatoes. I didn’t hit the 2200 calories I was hoping for today. I didn’t realize how filling the potatoes would make me feel.
Day 4 – My wife made me 3 pounds of roasted red potatoes that were lightly coated in olive oil with some of her special seasonings. While I made two containers of russet mashed potatoes, one with chives fresh out of our garden and one with a Thai herb/pepper paste I’ve never had before. My wife tells me the paste goes a long way and be careful not to use too much.
Day 6 – I was in potato Nirvana tonight. My wife boiled a bouillon cube with potato starch to make me “psuedo gravy”. It was awesome! She smothered Yukon Gold and Purple potato slices in this gravy and baked it in the oven for an hour. Then cooked homemade yellow and purple chips with artifical sweetner and cinnamon for dessert. It was heaven for a flavor deprived husband. I would marry her all over again because of this!
Day 11 – So one thing people keep asking about is, “What about my weight?” I’ve been hesitant to talk about this because I don’t want people to think of this as a weight loss diet. It is not, and it’s not something I want people to replicate. … So let me step down from my nutrition soap box and talk about weight. I started this diet at 197 pounds. I’m six foot one and a half so according to my BMI, I was a little over weight. I should be in the 175-185 range. Right now, I’m at 189 pounds. Most of that weigh loss happened early, only because I was struggling to eat enough potatoes. I seemed full the whole time so it was hard to keep eating. But now, my weight loss has become more stable.
Day 15 – I feel good. Lot’s of energy, I’m dropping a few pounds which I needed to, and no weird side effects. And mentally, I think I’ve found my groove. Weekdays are pretty easy but weekends are a little tougher, still have desires for other foods but I think those a waning a bit as I get further into this diet.
Day 19 – So my family had potstickers last night while I had roasted red potatoes. For the potstickers, my wife made a dipping sauce that I tried on my red potato wedges. It was pretty good. The sauce was soy sauce, ginger, and some off the shelf dry asian seasoning. It was a nice change of pace. It added a flavor I haven’t had in a long time.
Day 22 – I had about a pound of hash browns this morning for breakfast, two pounds of mashed potatoes with black pepper for lunch, which means I have to eat close to 4 more pounds before bed. I’m leaning towards baked potatoes with balsamic vinegar for dinner but I’m not sure I’m ready for 4 pounds of it.
Day 24 – So here is a new one for you that my wife made up. Fake ice cream made from potatoes. She took 1/2 cup cocoa powder, 1/2 cup artificial sweetner, and a little water to make a chocolate sauce. Then mixed it with about 2 cups of “riced” potatoes and ice. Blended it and put in freezer. It was actually really good, ju…st a strange texture though. I love my wife! What a treat!
Day 26 – I brought my food for the day and stuffed it in the office fridge. Two pounds of purple mashed potatoes topped with garlic salt, 6 smalled baked red potatoes that I’ll probably put balsamic vinegar on, and about 10 oz of gnocchi made with riced potatoes and potato flour, then lightly fried. Can’t boil them because they fall apart since they don’t have the egg in them that you would normally use.
… I drove to Spokane Sunday night and caught an early flight to Boise the next day. Must remember to prepare better! Nearly starved! I broke into a small emergency stash of instant potatoes I had with me for breakfast, had 3 small bags of …chips and 1 baked potato for lunch, and an order of fries at McD’s for dinner.
Day 28 – So here is what I had yesterday to eat. About 2 pounds of roasted red potatoes lightly seasoned and with a little olive oil, 3 pounds of purple mashed potatoes sprinkled with garlic salt, and about a pound and a half of “riced” potatoes that were fried up lightly. It was kind of like light fluffy hash browns. And a few handfuls of potato chips for a change in texture.
… think about how weird and unusual this diet is. Health professionals actually suggested I include some fries and chips prepared in healthy oils as part of my diet to make me more healthy during this diet. Doesn’t that sound so weird out loud or written in this blog? You have to remember that there is absolutely no fat in a potato, no fat in any of the seasonings or herbs I’m eating. But there are 2 fatty acids that are essential to bodily functions and are needed by your body. The healthy oils from the fries and chips are supplying me those fatty acids. Without them, I would not look or feel very good at the end of these 60 days. The take home message, you need those fatty acids to live but the reality for most people is that we eat too many of them. Live in moderation!
Day 33 – Got out of the house this morning without any seasonings for my spuds. So far, I’ve eaten 6 boiled, yellow flesh, plain potatoes. You know…I really think this is getting easier. I’m not having the intense cravings for other foods that I use to have. Maybe I’ve found my groove.
… I thought I’d take a moment to answer a couple questions I always get from folks about the diet. One is, “Are you taking any supplements?” No. This diet is about nutrition, there are so many nutrients in potatoes that you could literally live off them for an extended period of time without any major impacts to your health. If I could take supplements, I think you could probably do this diet for a really long time! Also, I get asked about beverages. I drink mostly water, but can have things that don’t add calories or any major nutrients. I do drink some black coffee, plain black tea, or an occasional diet soda.
Day 45 – I just ate about a kilo of purple mashed potatoes for dinner tonight. But I think I added too much garlic salt. Probably shouldn’t do any major kissing tonight. 🙂
Day 50 – Just in case I’m subjected to a lie detector test at some point, I have to come clean on 3 incidents. There were 3 separate times in the previous 50 days where I was making my kids lunch, peanut butter and jelly sandwiches, and without thinking, it was more of a reflex move, I licked clean the peanut or jelly that had gotten on my fingers. Its been bugging me so I needed to share.
Day 60 – So here are most of the stats from my latest medical exam and how it compares to where I was prior to the start of the diet. Weight, started at 197, finished at 176. Cholesterol, started at borderline high of 214, finished at 147. Glucose, started at 104, dropped to 94. So improvements in each of those catagories. I don’t have a hard copy yet, will try to get that tomorrow and will post online. Me Happy!!
Day 61 – (Diet officially over) Its funny because I still have yet to eat something else besides potatoes. I’ve been a little busy this morning so I wasn’t able to pack a lunch or breakfast. But the fridge in our office still had a couple of my potato only dishes. So guess what I had for my first meal at the end of the diet. Potatoes! Hopefully that will change later today. And I bet there will still be potatoes tonight, but with something on them or with them!
… One more thing, a few new folks have joined our little community and have sent me questions about the diet. First, I took no other supplements. It literally was just potatoes, seasonings, and oil for cooking. Now there were a few things we did classify as seasonings since they didn’t really add any significant nutrients, such as Tabasco Sauce which is really just dried peppers and vinegar. Had balsalmic vinegar a few times, and an occasional bouillon cube that was used in mashed potatoes or mixed with potato starch to form something like gravy. THe cubes were 5 calories and really only added sodium to the diet, which we consider a seasoning.
Day 63 – A big thank you to the Washington Beef, Dairy, and Apple producers. They, along with the Washington Potato Commission, hosted a dinner at the Moses Lake Head Start facility for all the kids and their parents. We did crafts and a short nutrition workshop on the importance of eating healthy, well balanced meals. Not just 20 potatoes a day 🙂 And a big thank you to the staff for all of their work on this and the wonderful Mr. Potato Head they gave me. We had lean beef strips for our tortillas, along with roasted onions, peppers, and potatoes, and apple slices and low fat milk. I sampled everything and wanted to chow down but my doctor has advised me to ease back slowly into other foods. So I’m still eating a lot of potatoes!
On the one hand, Chris took the potato diet very seriously. He really did get almost all his calories from potatoes for about 60 days. He stuck to the plan.
On the other hand, he didn’t take it too seriously. He used cooking oil, spices, and a bunch of different seasonings. He still had coffee, tea, and the “occasional diet soda”. But this didn’t ruin the diet — he still lost weight and gained energy.
The results do seem astounding. More energy, better sleep, lower cholesterol, etc. etc. And how was it subjectively? “I’m really struggling to eat enough calories. … I didn’t realize how filling the potatoes would make me feel. … I feel good.”
The weight loss results aren’t that extreme, but Chris wasn’t very overweight to begin with. He went from a BMI of 26 to an “ideal” BMI of 23. He didn’t really have many more excess pounds to lose. So let’s take a look at a more extreme example.
Appendix C: Andrew Taylor
Andrew Taylor is an Australian man who did an all-potato diet for a full year. He started at 334 pounds and he lost 117 pounds over the course of what he called his “Spud Fit Challenge.”
The physical benefits of Taylor’s Spud Fit Challenge remain, he says. “I’ve maintained the weight loss and I’m still free of the daily grind of battling with food addiction. I had a check up a few weeks ago and my doctor was very happy with the state of my health.”
Taylor says that he was clinically depressed and anxious before undertaking his all-potato diet, “which is no longer an issue for me,” he says. “My mental health is much better these days.”
During his challenge, Taylor ate all kinds of potatoes, including sweet potatoes. To add flavor to his meals, he used a sprinkle of dried herbs or fat-free sweet chili or barbecue sauce. If he made mashed potatoes, he only added oil-free soy milk.
He drank mostly water, with the occasional beer thrown in (proof that no man can resist a great brew). Because his diet completely lacked meat, he supplemented with a B12 vitamin.
He also didn’t restrict the amount he consumed. Instead, Taylor ate as many potatoes as he needed to satisfy his hunger. For the first month, he didn’t work out at all and still dropped 22 pounds, but then he added 90 minutes of exercise to his routine every day.
“I feel amazing and incredible! I’m sleeping better, I no longer have joint pain from old football injuries, I’m full of energy, I have better mental clarity and focus,” he writes on his site.
Taylor said has had medical supervision, including regular blood tests, throughout the year. His cholesterol has improved and his blood-sugar levels, blood pressure and other health indicators are good, he explained. He feels “totally amazing,” noting he no longer has problems with clinical depression and anxiety, sleeps better, feels more energetic and is physically stronger.
Andrew is now running spudfit.com. For the specifics of Andrew’s diet, the FAQ is pretty detailed:
A combination of all kinds of potatoes, including sweet potatoes. I used minimal dried and fresh herbs, spices and fat-free sauces (such as sweet chilli, tomato sauce or barbecue sauce) for a bit of flavour. I also use some soy milk (no added oil) when I make mashed potatoes.
I drank only water and the occasional beer. I didn’t drink any tea or coffee but I’ve never liked them anyway. If you want to drink tea or coffee I think that would be fine as long as you use a low fat (no added oil) plant based milk.
For the first month I did no exercise and still lost 10kgs. After that I tried to do around 90 minutes of training every day. I DID NOT exercise for weight loss, I did it because for the first time in years I had excess energy to burn, enjoyed it and it made me feel good. I think that whatever the amount of exercise I did, my body adjusted my hunger levels to make sure I take in enough food. If I didn’t let myself go hungry then I was fine.
Rule 1: Do your own research and make educated decisions – don’t just do things because you saw some weird bloke on the internet doing it! Also get medical supervision to make sure everything is going well for you, especially if you are taking any medications.
Rule 2: Eat a combination of all kinds of potatoes, including sweet potatoes. I have minimal herbs, spices and fat-free sauces for a bit of flavour. I also use some soy (or other plant-based with no added oil) milk when I make mashed potatoes. Also take a B12 supplement if you plan on doing this for longer than a few months. Definitely no oil – of any kind – or anything fatty such as meats, cheeses, eggs or dairy products (even lean or low-fat versions).
Rule 3: DO NOT RESTRICT OR COUNT CALORIES. I eat as much as I like, as often as I like, I do not allow myself to go hungry if I can help it.
I used a non-stick granite pan and fry in water or salt reduced vegetable stock. When I used the oven I just put the potatoes straight on the tray. I also liked to cook potatoes in my pressure cooker and my air fryer.
I felt amazing and incredible and I still do! My sleep improved, joint pain from old football injuries went away, I gained energy and improved mental clarity and focus. Also I lost 52.3 kilograms (117 pounds) over the course of the year. By far the best part is that I no longer suffer with clinical depression and anxiety.
I tried to keep it as simple as possible. I didn’t own an air fryer or a pressure cooker or any other special gadgets. Most of what I ate was either boiled, baked or mashed potatoes. I would make a really big batch of one type and then eat it for a day or two until it was gone and then repeat.
(did you eat the skins?) I did but if you don’t want to that’s ok too.
This is the most surprising thing of all, I can’t explain why but I’m not at all bored of my potato meals.
Over the month of January, following the completion of my Spud Fit Challenge, I lost another 2kg (4lbs). This took my total weight loss to 55kg (121lbs) and meant I weighed the same as I did when I was 15 years old – 96kg (211lbs)! Since then I’ve stopped weighing myself so I can’t be sure of what I actually weigh, my new clothes still all fit though and I still feel good so I guess my weight is around the same (nearly 15 months later at the time of writing this).
This diet looks pretty similar to what Chris did. All potatoes but not wildly strict — he would have seasonings and sauces and even an occasional beer. The big difference is that Andrew studiously avoided added oils, and took a B12 supplement.
The B12 seems like a good addition to us, especially since Andrew was doing this for a full year, because potatoes contain almost no B12. Hard to say if avoiding oil was important but using oil didn’t keep Chris Voigt from seeing a lot of benefits from potatoes. On the other hand, Andrew didn’t seem to miss it.
Appendix D: Penn Jillette
Penn Jillette, of the famous magician duo Penn & Teller, lost over 100 lbs, down from “probably over 340”, on a diet that started with a 2-week period of nothing but potatoes.
I didn’t mind not being energetic and stuff. But I started having blood pressure that was stupid high like, you know, like English voltage, like 220 even on blood pressure medicine.
If you take medical advice from a Las Vegas magician you are an idiot who deserves to die. You have to do this for yourself and with your proper medical professionals.
And one of the really good ways to do that that worked tremendously for me is what’s called the mono diet which is just what you think from the root, eating the exact same thing.
And I could have chosen anything. I could have chosen corn or beans or whatever. Not hot fudge but anything. And I chose potatoes because it’s a funny thing and a funny word.
For two weeks I ate potatoes, complete potatoes – skin and everything and nothing added, nothing subtracted. When I say nothing subtracted I mean no skin taken off but also no water. You can’t cut it up and make it chips in a microwave. Don’t take water out of it.
Leave the potato completely – so that means baked or boiled and not at any mealtime. You don’t get up in the morning, eat a potato. You don’t eat it at lunch or dinner. Mealtimes are obliterated. When you really need to eat, eat a potato. And over that first two weeks I lost I believe 14 pounds. So already I’m a different person.
Then after that two weeks I went to, you know, bean stew and tomatoes and salads. But still no fruit and no nuts. Certainly no animal products. And I lost an average – these words are careful – an average of 0.9 pounds a day. So I took off pretty much all the weight in three or four months, in a season, in a winter.
And that was 17 months ago. So I’ve kept the weight off for 17 months. Now two years is magic. Very few people keep it off for two years. I’ve got seven more months to go. I think I have a shot at it.
I feel better. I’m happier. I’m off most of my blood pressure meds. Not all of them, it takes a while for the vascular system to catch up with the weight loss. I have more fun. I believe I’m kinder.
All of that having been said now that I’m at target weight I also – this is important – I also didn’t exercise while I was losing the weight. Exercising is body building. It’s a different thing. Wait until you hit the target weight, then you exercise. Then it’s easy. Then it really does good. But while you’re losing weight make it winter. Sleep a little more. Get sluggish. Let your body just eat the fat that you’ve stored up just the way you should. Hibernate a little bit. Let it eat the fat. Be a little bit like a bear.
Again, a pretty impressive story. And, as of 2019, he seems to be keeping it off.
He was 35 when we started this journey and tipped the scales at 514 pounds. My own weight was approaching 300 pounds and my health was starting to suffer. High blood pressure, anxiety and acne were just the start of my issues.
We picked a start date on the calendar (June 22, 2018 – which also happened to be the 11th anniversary of when we first started dating) and started doing research. The first book I read was Penn Jillette’s Presto!: How I Made Over 100 Pounds Disappear and Other Magical Tales. It was exactly what I needed to get into the right frame of mind for starting this journey. It wasn’t a book from a doctor or a nutritionist or someone telling me why eating the way I did was going to kill me. It was a book from someone who KNEW the real struggle we have dealt with for years. Someone who spend years overweight, LOVED food, and didn’t buy into the whole “eat in moderation” philosophy a lot of our past failed diets relied on.
The first day of potatoes sucked. I seriously contemplated quitting during the FIRST day. After eating my first round of potatoes, I literally walked from our apartment to a grocery store to look at the extra cheesy hot-and-ready pizza I thought I needed. I gazed at the pizza and walked around the store looking for something to eat. Luckily, I was able to keep it together and walk out of the store and back home to my pantry full of potatoes.
I’m not trying to be dramatic, but it was seriously one of the hardest things I’ve done in my life. It took more will power than I thought either of us had.
Even when we started the two weeks of potatoes, we still weren’t sure what the heck we were supposed to do after that. We knew it was vegan. We knew we wouldn’t be able to use added salt, sugar, oil, etc. But that was about it. So we did a lot of research during those two weeks of eating nothing but potatoes. From what I could tell, after the two weeks of potatoes, Penn Jillette followed a whole food, plant-based diet for the most part, so we decided to stick with that.
We will never go back to eating the way we used to eat. As hokey as it might sound: This is not a diet – it is a lifestyle. We know if we go back to our old ways, we’ll gain the weight back again. The best part is… we don’t want to go back to how we ate before! We actually enjoy food more now than we did before. We have a better relationship with food. We feel like we eat MORE variety now. Eating a whole food, plant-based diet has opened our minds and palates to a new world of food that we would not have given a second thought to before.
They seem to have had a harder time than the other examples we looked at. But we also notice they are the heaviest people we’ve looked at so far, so it’s not hard to imagine that it might have been roughest for them. But even so, it seems to have worked.
As far as we can tell, they are following Penn’s approach over what Chris and Andrew did — no oil or nothin’, just potatoes. Our sense is that this is probably more hardcore than what is necessary but like, more power to them. On the other hand, this may be part of what made it so difficult. Even Andrew used seasonings! Detailed instructions for how they prepare Taters appear in their videos.
The Krocks are still making videos, and if you look at their channel, they seem to have kept a lot of weight off.
Red and yellow potatoes work the best, because after they are boiled they keep longer than Russet potatoes, which tend to get mushy quicker. However, Russet potatoes do work. Try all potato types.
Sweet potatoes are not potatoes. They can work for some people, but not nearly as well. If you can not handle nightshades, purple yams with white flesh can be a substitute. Weight loss is likely to be slower when you don’t use regular potatoes.
The only way to make the potato fattening is to process it and cook it in oil. So avoid fries and chips. For the potato hack to work the potatoes need to be cooked only in water. Boil, steam, or pressure cook.
When cooked potatoes are cooled overnight in the refrigerator they develop something called resistant starch. Resistant starch is beneficial to our gut flora, balances blood sugar, and other additional health benefits. These resistant starches are not digested in the same manner as regular calories, so they have the effect of reducing the calories of potatoes.
Refrigerating cooked potatoes overnight will reduce the calories by about 17%. The potatoes can be reheated before eating without losing any of the resistant starch.
The potato hack will still work if you don’t refrigerate the potatoes, so although this step is encouraged, it is optional.
Eat the potatoes plain. Salt if you must. You can add a splash of malt or red wine vinegar if a blood sugar spike is a concern, although cooling the potatoes will reduce the glycemic response.
To get the full benefit of the potato hack, it is strongly advised to eat the potatoes plain. You are teaching your brain how to get full without flavor. This is the opposite approach taken in dieting where one continues to get flavorful food but in a restrictive manner.
With the potato diet, do not walk away from the table hungry. Eat until full.
This is a little more finicky (what potatoes to use, how to store them, etc.) but overall looks a lot like the other examples we’ve considered.
The hack also links to some testimonies, including this one guy’s particular approach. We’ll include it here because it gives an unusual amount of detail about purchasing and preparation:
If your time is valuable to purchase organic, because you will not need to peel the potatoes, plus they have more nutrition. If you want to save money, purchase non-organic. I cycle between both options.
The three most common options for potatoes are going to be red, yellow, and russet. 98% of the time I will purchase red or yellow. They hold up much better structurally when you take them in and out of the refrigerator over a day or two.
Russet potatoes get mushy quickly. The only time I get Russet is if I get a really good price and I know I’m doing a strict potato hack, so I’m not using those potatoes two days later.
I’ve boiled so many potatoes in the last two years, my hands have developed muscle memory as if I were driving a manual car. Here is how I’ve optimized my potato preparation.
1. Peel directly into colander if the potatoes are not organic.
2. Place the potato directly into the cleaned and dried storage container.
3. Fill the storage container. When I first started hacking, I would weigh the potatoes. Once I figured out my container could hold 5.5 pounds, then I put my scale away.
4. Remove each potato. If it is small, place it in a stockpot, otherwise chop it into parts. For me, a medium potato is 2 or 3 parts. A large potato will be more. My goal is to have approximately equal size potato parts. I want them to boil at the same rate.
5. Once that is complete, I rinse the potatoes in the stockpot.
6. Refill stockpot with clean water and boil.
7. While the potatoes are boiling, empty peels in a compost bin.
8. Boil until done to your liking. I tend to cook mine a little longer than Tim Steele describes in his book The Potato Hack, but whatever you like is the right answer. Experiment.
9. Drain and let potatoes cool. The reason I want the potatoes to cool is that if I don’t, the steam will collect on the roof of the storage container and drain down onto the potatoes, making them mushy more quickly. If I want the potatoes to cool fast, I will spread them on a cookie sheet and place them outside (provided outside is cooler than inside).
10 Put the cooled potatoes in the storage bin and refrigerate.
That is my optimized path. I’m sure you’ll find your own.
The title isn’t some weird Walden II reference — there’s a Part I and Part III as well. Part I reviews the obesity epidemic (in case you’re not already familiar?) and argues that obesity “likely has origins in utero.”
Part III basically argues that we should move away from doing obesity research with cells isolated in test tubes (probably a good idea TBH) and move towards “model organisms such as Drosophila, C. elegans, zebrafish, and medaka.” Sounds fishy to us but whatever, you’re the doctor.
This paper, Part II, makes the case that environmental contaminants “play a vital role in” the obesity epidemic, and presents the evidence in favor of a long list of candidate contaminants. We’re going to stick with Part II today because that’s what we’re really interested in.
For some reason the editors of this journal have hidden away the peer reviews instead of publishing them alongside the paper, like any reasonable person would. After all, who could possibly evaluate a piece of research without knowing what three anonymous faculty members said about it? The editors must have just forgotten to add them. But that’s ok — WE are these people’s peers as well, so we would be happy to fill the gap. Consider this our peer review:
This is an ok paper. They cite some good references. And they do cite a lot of references (740 to be exact), which definitely took some poor grad students a long time and should probably count for something. But the only way to express how we really feel is:
Seriously, 43 authors from 33 different institutions coming together to tell you that “ubiquitous environmental chemicals called obesogens play a vital role in the obesity pandemic”? We could have told you that a year ago, on a budget of $0.
This wasted months, maybe years of their lives, and millions of taxpayer dollars making this paper that is just like, really boring and not very good. Meanwhile we wrote the first draft of A Chemical Hunger in a month (pretty much straight through in October 2020) and the only reason you didn’t see it sooner was because we were sending drafts around to specialists to make sure there wasn’t anything major that we overlooked (there wasn’t).
We don’t want to pick on the actual authors because, frankly, we’re sure this paper must have been a nightmare to work on. Most of the authors are passengers of this trainwreck — involved, but not responsible. We blame the system they work under.
We hope this doesn’t seem like a priority dispute. We don’t claim priority for the contamination hypothesis — here are four papers from 2008, 2009, 2010, and 2014, way before our work on the subject, all arguing in favor of the idea that contaminants cause obesity. If the contamination hypothesis turns out to be right, give David B. Allison the credit, or maybe someone even earlier. We just think we did an exceptionally good job making the case for the hypothesis. Our only original contributions (so far) are arguing that the obesity epidemic is 100% (ok, >90%) caused by contaminants, and suggesting lithium as a likely candidate.
So we’re not trying to say that these authors are a bunch of johnny-come-latelies (though they kind of are, you see the papers up there from e.g. 2008?). The authors are victims here of a vicious system that has put them in such a bad spot that, for all their gifts, they can now only produce rubbish papers, and we think they know this in their hearts. It’s no wonder grad students are so depressed!
So to us, this paper looks like a serious condemnation of the current academic system, and of the medical research system in particular. And while we don’t want to criticize the researchers, we do want to criticize the paper for being an indecisive snoozefest.
Long Paper is Long
The best part of this paper is that comes out so strongly against “traditional wisdom” about the obesity epidemic:
The prevailing view is that obesity results from an imbalance between energy intake and expenditure caused by overeating and insufficient exercise. We describe another environmental element that can alter the balance between energy intake and energy expenditure: obesogens. … Obesogens can determine how much food is needed to maintain homeostasis and thereby increase the susceptibility to obesity.
In particular we like how they point out how, from the contaminant perspective, measures of how much people eat are just not that interesting. If chemicals in your carpet raise your set point, you may need to eat more just to maintain homeostasis, and you might get fat. This means that more consumption, of calories or anything else you want to measure, is consistent with contaminants causing obesity. We made the same point in Interlude A. Anyways, don’t come at us about CICO unless you’ve done your homework.
We also think the paper’s heart is in the right place in terms of treatment:
The focus in the obesity field has been to reduce obesity via medicines, surgery, or diets. These interventions have not been efficacious as most people fail to lose weight, and even those who successfully lose substantial amounts of weight regain it. A better approach would be to prevent obesity from occurring in the first place. … A significant advantage of the obesogen hypothesis is that obesity results from an endocrine disorder and is thus amenable to a focus on prevention.
So for this we say: preach, brothers and sisters.
The rest of the paper is boring to read and inconclusive. If you think we’re being unfair about how boring it is, we encourage you to go try to read it yourself.
The paper doesn’t even do a good job assessing the evidence for the contaminants it lists. For example, glyphosate. Here is their entire review:
Glyphosate is the most used herbicide globally, focusing on corn, soy and canola . Glyphosate was negative in 3T3-L1 adipogenic assays , . Interestingly, three different formulations of commercial glyphosate, in addition to glyphosate itself, inhibited adipocyte proliferation and differentiation from 3T3-L1 cells . There are also no animal studies focusing on developmental exposure and weight gain in the offspring. An intriguing study exposed pregnant rats to 25mg/kg/day during days 8-14 of gestation . The offspring were then bred within the lineage to generate F2 offspring and bread to generate the F3 progeny. About 40% of the males and females of the F2 and F3 had abdominal obesity and increased adipocyte size revealing transgenerational inheritance. Interestingly, the F1 offspring did not show these effects. These results need verification before glyphosate can be designated as an obesogen.
For comparison, here’s our review of glyphosate. We try to, you know, come to a conclusion. We spend more than a paragraph on it. We cite more than four sources.
We cite their  as well, but we like, ya know, evaluate it critically and in the context of other exposure to the same compound. We take a close look at our sources, and we tell the reader we don’t think glyphosate is a major contributor to the obesity epidemic because the evidence doesn’t look very strong to us. This is bare-bones due diligence stuff. Take a look:
The best evidence for glyphosate causing weight gain that we could find was from a 2019 study in rats. In this study, they exposed female rats (the original generation, F0) to 25 mg/kg body weight glyphosate daily, during days 8 to 14 of gestation. There was essentially no effect of glyphosate exposure on these rats, or in their children (F1), but there was a significant increase in the rates of obesity in their grandchildren (F2) and great-grandchildren (F3). There are some multiple comparison issues, but the differences are relatively robust, and are present in both male and female descendants, so we’re inclined to think that there’s something here.
There are a few problems with extending these results to humans, however, and we don’t just mean that the study subjects are all rats. The dose they give is pretty high, 25 mg/kg/day, in comparison to (again) farmers working directly with the stuff getting a dose closer to 0.004 mg/kg.
The timeline also doesn’t seem to line up. If we take this finding and apply it to humans at face value, glyphosate would only make you obese if your grandmother or great-grandmother was exposed during gestation. But glyphosate wasn’t brought to market until 1974 and didn’t see much use until the 1990s. There are some grandparents today who could have been exposed when they were pregnant, but obesity began rising in the 1980s. If glyphosate had been invented in the 1920s, this would be much more concerning, but it wasn’t.
Frankly, if they aren’t going to put in the work to engage with studies at this level, they shouldn’t have put them in this review.
If this were a team of three people or something, that would be one thing. But this is 43 specialists working on this problem for what we assume was several months. We wrote our glyphosate post in maybe a week?
Some of the reviews are better than this — their review of BPA goes into more detail and cites a lot more studies. But the average review is pretty cruddy. For example, here’s the whole review for MSG:
Monosodium glutamate (MSG) is a flavor enhancer used worldwide. Multiple animal studies provided causal and mechanistic evidence that parenteral MSG intake caused increased abdominal fat, dyslipidemia, total body weight gain, hyperphagia and T2D by affecting the hypothalamic feeding center , , . MSG increased glucagon-like peptide-1 (GLP-1) secretion from the pGIP/neo: STC-1 cell line indicating a possible action on the gastrointestinal (GI) tract in addition to its effects on the brain . It is challenging to show similar results in humans because there is no control population due to the ubiquitous presence of MSG in foods. MSG is an obesogen.
Seems kind of extreme to unequivocally declare “MSG is an obesogen” on the basis of just four papers. On the basis of results that seem to be in mice, rats, mice, and cells in a test tube, as far as we can tell (two of the citations are review articles, which makes it hard for us to know what studies they specifically had in mind). Somehow this is enough to declare MSG a “Class I Obesogen” — Animal evidence: Strong. In vitro evidence: Strong. Regulatory action: to be banned. Really?
Instead, we support the idea of — thinking about it for five minutes. For example, MSG occurs naturally in many foods. If MSG were a serious obesogen, tomatoes and dashi broth would both make you obese. Why are Italy and Japan not more obese? The Japanese first purified MSG and they love it so much, they have a factory tour for the stuff that is practically a theme park — “there is a 360-degree immersive movie experience, a diorama and museum of factory history, a peek inside the fermentation tanks (yum!), and finally, an opportunity to make and taste your own MSG seasoning.” Yet Japan is one of the leanest countries in the world.
As far as we can tell, Asia in general consumes way more MSG than any other part of the world. “Mainland China, Indonesia, Vietnam, Thailand, and Taiwan are the major producing countries in Asia.” Why are these countries not more obese? MSG first went on the market in 1909. Why didn’t the obesity epidemic start then? We just don’t think it adds up.
(Also kind of weird to put this seasoning invented in Asia, and most popular in Asia, under your section on “Western diet.”)
Let’s also look at their section on DDT. This one, at least, is several paragraphs long, so we won’t quote it in full. But here’s the summary:
A 2017 systematic review of in vitro, animal and epidemiological data on DDT exposures and obesity concluded the evidence indicated that DDT was “presumed” to be obesogenic for humans . The in vitro and animal data strongly support DDT as an obesogen. Based on the number of positive prospective human studies, DDT is highly likely to be a human obesogen. Animal and human studies showed obesogenic transmission across generations. Thus, a POP banned almost 50 years ago is still playing a role in the current obesity pandemic, which indicates the need for caution with other chemical exposures that can cause multigenerational effects.
We’re open to being convinced otherwise, but again, this doesn’t really seem to add up. DDT was gradually banned across different countries and was eventually banned worldwide. Why do we not see reversals or lags in the growth of obesity in those countries those years? They mention that DDT is still used in India and Africa, sometimes in defiance of the ban. So why are obesity rates in India and Africa so low? We’d love to know what they think of this and see it contextualized more in terms of things like occupation and human exposure timeline.
With a long list of chemicals given only the briefest examination, it’s hard not to see this paper as overly inclusive to the point of being useless. It makes the paper feel like a cheap land grab to stake a claim to being correct in the future if any of the chemicals on the list pan out.
Maybe their goal is just to list and categorize every study that has ever been conducted that might be relevant. We can sort of understand this but — why no critical approach to the material? Which of these studies are ruined by obvious confounders? How many of them have been p-hacked to hell? Seems like the kind of thing you would want to know!
You can’t just list papers and assume that it will get you closer to understanding. In medicine, the reference for this problem is Ioannidis’s Why Most Published Research Findings Are False. WMPRFAF was published in 2005, you don’t have an excuse for not thinking critically about your sources.
Despite this, they don’t even mention lithium, which seems like an oversight.
We wish the paper tried to provide a useful conclusion. It would have been great to read them making their best case for pretty much anything. Contaminants are responsible for 50% of the epidemic. Contaminants are responsible for no more than 10% of the epidemic. Contaminants are responsible for more than 90% of the epidemic. We think phthalates are the biggest cause. We think DDT is the biggest cause. We think it’s air pollution and atrazine. Make a case for something. That would be cool.
What is not cool is showing up being like: Hey we have a big paper! The obesity epidemic is caused by chemicals, perhaps, in what might possibly be your food and water, or at work, though if it’s not, they aren’t. This is a huge deal if this is what caused the epidemic, possibly, unless it didn’t. The epidemic is caused by any of these several dozen compounds, unless it’s just one, or maybe none of them. What percentage of the epidemic is caused by these compounds? It’s impossible to say. But if we had to guess, somewhere between zero and one hundred percent. Unless it isn’t.
The paper spends almost no time talking about effect size, which we think is 1) a weird choice and 2) the wrong approach for this question.
We don’t just care about which contaminants make you gain weight. We care about which contaminants make you gain a concerning amount of weight. We want to know which contaminants have led to the ~40 lbs gain in average body weight since 1970, not which of them can cause 0.1 lbs of weight gain if you’re inhaling them every day at work. These differences are more than just important, they’re the question we’re actually interested in!
For comparison: coffee and airplane travel are both carcinogens, but they increase your risk of cancer by such a small degree that it’s not even worth thinking about, unless you’re a pilot with an espresso addiction. When the paper says “Chemical ABC is an obesogen”, it would be great to see some analysis of whether it’s an obesogen like how getting 10 minutes of sunshine is a carcinogen, or whether it’s an obesogen like how spending a day at the Chernobyl plant is a carcinogen. Otherwise we’re on to “bananas are radioactive” levels of science reporting — technically true, but useless and kind of misleading.
The huge number of contaminants they list does seem like a mark in favor of a “the obesity epidemic is massively multi-causal” hypothesis (which we discussed a bit in this interview), but again it’s hard to tell without seeing a better attempt to estimate effect sizes. The closest thing to an estimate that we saw was this line: “Population attributable risk of obesity from maternal smoking was estimated at 5.5% in the US and up to 10% in areas with higher smoking rates”.
Their conclusion is especially lacking. It’s one thing to point out that what we’re studying is hard, but it’s another thing to deny the possibility of victory. Let’s look at a few quotes:
“A persistent key question is what percent of obesity is due to genetics, stress, overnutrition, lack of exercise, viruses, drugs or obesogens? It is virtually impossible to answer that question for any contributing factors… it is difficult to determine the exact effects of obesogens on obesity because each chemical is different, people are different, and exposures vary regionally and globally.”
Imagine going to an oncology conference and the keynote speaker gets up and says, “it is difficult to determine the exact effects of radiation on cancer because each radiation source is different, people are different, and exposures vary regionally and globally”. While much of this is true, oncologists don’t say this sort of thing (we hope?) because they understand that while the problem is indeed hard, it’s important, and hold out hope that solving that problem is not “virtually impossible”. Indeed, we’re pretty sure it’s not.
They’re pretty pessimistic about future research options:
“We cannot run actual ‘clinical trials’ where exposure to obesogens and their effects are monitored over time. Thus, we focus on assessing the strength of the data for each obesogen.”
Assessing the strength of the data is a good idea, but this is leaving a lot on the table. Natural experiments are happening all the time, and you don’t need clinical trials to infer causality. We’d like to chastise this paper with the following words:
[Before] we set about instructing our colleagues in other fields, it will be proper to consider a problem fundamental to our own. How in the first place do we detect these relationships between sickness, injury and conditions of work? How do we determine what are physical, chemical and psychological hazards of occupation, and in particular those that are rare and not easily recognized?
There are, of course, instances in which we can reasonably answer these questions from the general body of medical knowledge. A particular, and perhaps extreme, physical environment cannot fail to be harmful; a particular chemical is known to be toxic to man and therefore suspect on the factory floor. Sometimes, alternatively, we may be able to consider what might a particular environment do to man, and then see whether such consequences are indeed to be found. But more often than not we have no such guidance, no such means of proceeding; more often than not we are dependent upon our observation and enumeration of defined events for which we then seek antecedents.
… However, before deducing ‘causation’ and taking action we shall not invariably have to sit around awaiting the results of the research. The whole chain may have to be unraveled or a few links may suffice. It will depend upon circumstances.
So we think the “no clinical trials” thing is a non-issue. Sir Austin Bradford Hill and colleagues were able to discover the connection between cigarette smoking and lung cancer without forcing people to smoke more than they were already smoking. You really can do medical research without clinical trials.
But even so, the paper is just wrong. We can run clinical trials. People do occasionally lose weight, sometimes huge amounts of weight. So we can try removing potential obesogens from the environment and seeing if that leads to weight loss. If we do it in a controlled manner, we can get some pretty strong evidence about whether or not specific contaminants are causing obesity.
Our final and biggest problem with this paper is that it is so tragically defeatist. It leaves you totally unsure as to what would be informative additional research. It doesn’t show a clear path forward. It’s pessimistic. And it’s tedious as hell. All of this is bad for morale.
When you have a lab, you need grant money. Not just for yourself, but for the postdoctoral researchers and PhDs who depend on you for their livelihoods. … much of what goes on in academia is really the Science Game™. … varying some variable with infinite degrees of freedom and then throwing statistics at it until you get that reportable p-value and write up a narrative short story around it.
Think of it like grasping a dial, and each time you turn it slightly you produce a unique scientific publication. Such repeatable mechanisms for scientific papers are the dials everyone wants. Playing the Science Game™ means asking a question with a slightly different methodology each time, maybe throwing in a slightly different statistical analysis. When you’re done with all those variations, just go back and vary the original question a little bit. Publications galore.
If this is your MO, then “more research is needed” is the happiest sound in the world. Actually solving a problem, on the other hand, is kind of terrifying. You would need to find a new thing to investigate! It’s much safer to do inconclusive work on the same problem for decades.
This is part of why we find the suggestion to move towards research with “model organisms such as Drosophila, C. elegans, zebrafish, and medaka” so suspicious. Will this solve the obesity epidemic? Probably not, and certainly not any time this decade. Will it allow you to generate a lot of different papers on exposing Drosophila, C. elegans, zebrafish, and medaka to slightly different amounts of every chemical imaginable? Absolutely.
(As Paul Graham describes, “research must be substantial– and awkward systems yield meatier papers, because you can write about the obstacles you have to overcome in order to get things done. Nothing yields meaty problems like starting with the wrong assumptions.’”)
With all due respect to this approach, we do NOT want to work on obesity for the rest of our lives. We want to solve obesity in the next few years and move on to something else. We think that this is what you want to happen too! Wouldn’t it be nice to at least consider that we might make immediate progress on serious problems? What ever happened to that?
Political Scientist Adolph Reed Jr. once wrote that modern liberalism has no particular place it wants to go. “Its métier,” he said, “is bearing witness, demonstrating solidarity, and the event or the gesture. Its reflex is to ‘send messages’ to those in power, to make statements, and to stand with or for the oppressed. This dilettantish politics is partly the heritage of a generation of defeat and marginalization, of decades without any possibility of challenging power or influencing policy.“
In this paper, we encounter a scientific tradition that no longer has any place it wants to go (“curing obesity? what’s that?”), that makes stands but has a hard time imagining taking action, that is the heir to a generation of defeat and marginalization. All that remains is a reflex of bearing witness to suffering.
We think research can be better than this. That it can be active and optimistic. That it can dare to dream. That it can make an effort to be interesting.
Why do we keep complaining about this paper being boring? Why does it matter? It matters because when the paper is boring, it suggests that the idea that obesity is caused by contaminants isn’t important enough to bother spending time on the writing. It suggests people won’t be interested to read the paper, that no one cares, that no care should be taken in the discussion. That nothing can be gained by thinking clearly about these ideas. It suggests that the prospect of curing obesity isn’t exciting. But we think that the prospect of curing obesity is very exciting, and we hope you do too!
Early on in science there would never even could be a replication crisis or anything because everyone was just trying all the stuff. They were writing letters to each other with directions, trying each others’ studies, and seeing what they could confirm for themselves.
I have a particular cookbook that I love, and even though I follow the recipes as closely as I can, the food somehow never quite looks as good as it does in the photos. Does this mean that the recipes are deficient, perhaps even that the authors have misrepresented the quality of their food? Or could it be that there is more to great cooking than just following what’s printed in a recipe? I do wish the authors would specify how many millimeters constitutes a “thinly” sliced onion, or the maximum torque allowed when “fluffing” rice, or even just the acceptable range in degrees Fahrenheit for “medium” heat. They don’t, because they assume that I share tacit knowledge of certain culinary conventions and techniques; they also do not tell me that the onion needs to be peeled and that the chicken should be plucked free of feathers before browning. … Likewise, there is more to being a successful experimenter than merely following what’s printed in a method section. Experimenters develop a sense, honed over many years, of how to use a method successfully. Much of this knowledge is implicit.
Mitchell believes in a world where findings are so fragile that only extreme insiders, close collaborators of the original team, could possibly hope to reproduce their findings. The implicit message here is something like, “don’t bother replicating ever; please take my word for my findings.”
The general understanding of replication is slightly less extreme. To most researchers, replication is when one group of scientists at a major university reproduce the work of another group of scientists at a different major university. There’s also a minority position that replications should be done by many labs, that replication is an internal process of double-checking: “take the community’s word”.
But this doesn’t seem quite right to us either. If a finding can’t be confirmed by outsiders like you — if you can’t see it for yourself — it doesn’t really “count” as replication. This used to be the standard of evidence (confirm it for yourself or don’t feel bound to take it seriously) and we think this is a better standard to hold ourselves to.
It’s not that Mitchell is wrong — he’s right, there is a lot of implicit knowledge involved in doing anything worth doing. Sometimes science is really subtle and hard to replicate at home; other times, it isn’t. But whether or not a particular study is easy or hard to replicate is a dodge. This argument is a load of crap because the whole reason to do research in the first place is a fight against received wisdom.
The motto of the Royal Society, one of the first scientific societies, was and still is nullius in verba. Roughly translated, this means, “take no one’s word” or “don’t take anyone’s word for it”. We think this is a great motto. It’s a good summary of the kind of spirit you need to investigate the world. You have the right to see for yourself and make up your own mind; you shouldn’t have to take someone’s word. If you can take someone else’s word for it — a king, maybe — then why bother?
In the early 1670s, Antonie van Leeuwenhoek started writing to the Royal Society, talking about all the “little animals” he was seeing in drops of pond water when he examined them under his new microscopes. Long particles with green streaks, wound about like serpents, or the copper tubing in a distillery. Animals fashioned like tiny bells with long tails. Animals spinning like tops, or shooting through the water like pikes. “Little creatures,” he said, “above a thousand times smaller than the smallest ones I have ever yet seen upon the rind of cheese.”
Naturally, the Royal Society found these reports a little hard to believe. They had published some of van Leewenhoek’s letters before, so they had some sense of who the guy was, but this was almost too much:
Christiaan Huygens (son of Constanijn), then in Paris, who at that time remained sceptical, as was his wont: ‘I should greatly like to know how much credence our Mr Leeuwenhoek’s observations obtain among you. He resolves everything into little globules; but for my part, after vainly trying to see some of the things which he sees, I much misdoubt me whether they be not illusions of his sight’. The Royal Society tasked Nehemiah Grew, the botanist, to reproduce Leeuwenhoek’s work, but Grew failed; so in 1677, on succeeding Grew as Secretary, Hooke himself turned his mind back to microscopy. Hooke too initially failed, but on his third attempt to reproduce Leeuwenhoek’s findings with pepper-water (and other infusions), Hooke did succeed in seeing the animalcules—‘some of these so exceeding small that millions of millions might be contained in one drop of water’
People were skeptical and didn’t take van Leewenhoek at his word alone. They tried to get the same results, to see these little animals for themselves, and for a number of years they failed. They got no further help from van Leewenhoek, who refused to share his methods, or the secrets of how he made his superior microscopes. Yet even without a precise recipe, Hooke was eventually able to see the tiny, wonderful creatures for himself. And when he did, van Leewenhoek became a scientific celebrity almost overnight.
If something is the truth about how the world works, the truth will come out, even if it takes Robert Hooke a few years to confirm your crazy stories about the little animals you saw in your spit. Yes, research is very exacting, and can demand great care and precision. Yes, there is a lot of implicit knowledge involved. The people who want to see for themselves might have to work for it. But if you think what you found is the real McCoy, then you should expect that other people should be able to go out and see it for themselves. And assuming you are more helpful than van Leewenhoek, you should be happy to help them do it. If you don’t think people will be able to replicate it at their own bench, are you sure you think you’ve discovered something?
Fast forward to the early 1900s. Famous French Physicist Prosper-René Blondlot is studying the X-Rays, which had been first described by Wilhelm Röntgen in 1895. This was an exciting time for rays of all stripes — several forms of invisible radiation had just been discovered, not only X-Rays but ultraviolet light, gamma rays, and cathode rays.
So Blondlot was excited, but not all that surprised, when he discovered yet another new form of radiation. He was firing X-rays through a quartz prism and noticed that a detector was glowing when it shouldn’t be. He performed more experiments and in 1903 he announced the discovery of: N-rays!
Blondlot was a famous physicist at a big university in France, so everyone took this seriously and they were all very excited. Soon other scientists had replicated his work in their own labs and were publishing scores of papers on the subject. They began documenting the many strange properties of N-rays. The new radiation would pass right through many substances that blocked light, like wood and aluminum, but were obstructed by water, clouds, and salt. They were emitted by the sun and by human bodies (especially flexed muscles and certain areas of the brain), as well as rocks that had been left in the sun and been allowed to “soak up” the N-rays from sunlight.
The procedure for detecting these rays wasn’t easy. You had to do everything just right — you had to use phosphorescent screens as detectors, you had to stay in perfect darkness for a half hour so your eyes could acclimate, etc. Fortunately Blondlot was extremely forthcoming and always went out of his way to help provide these implicit details he might not have been able to fit in his reports. And he was vindicated, because with his help, labs all over the place were able to reproduce and extend his findings.
Well, all over France. Some physicists outside France, including some very famous ones, weren’t able to reproduce Blondlot’s findings at all. But as before, Blondlot was very forthcoming and did his best to answer everyone’s questions.
Even so, over time some of the foreigners began to get a little suspicious. Eventually some of them convinced an American physicist, Robert W. Wood, to go visit Blondlot in France to see if he could figure out what was going on.
Blondlot took Wood in and gave him several demonstrations. To make a long story short (you can read Wood’s full account here; it’s pretty interesting), Wood found a number of problems with Blondlot’s experiments. The game was really up when Wood secretly removed a critical prism from one of the experiments, and Blondlot continued reporting the same results as if nothing had happened. Wood concluded that N-rays and all the reports had been the work of self-deception, calling them “purely imaginary”. Within a couple of years, no one believed in N-rays anymore, and today they’re seen as a cautionary tale.
So much for the subtlety and implicit knowledge needed to do cutting-edge work. Maybe your results are hard to get right, but maybe if other people can’t reproduce your findings, they shouldn’t take your word for it.
This is the point of all those chemistry sets your parents (or cool uncle) gave you when you were a kid. This is the point of all those tedious lab classes in high school. They were poorly executed and all but this was the idea. If whatever Röntgen or Pasteur or Millikan or whoever found is for real, you should be able to reproduce the same thing for yourself in your high school with only the stoner kid for a lab assistant (joke’s on you, stoners make great chemists — they’re highly motivated).
Some people will scoff. After all, what kind of teenager can replicate the projects reported in a major scientific journal? Well, as just one example, take Dennis Gabor: “during his childhood in Budapest, Gabor showed an advanced aptitude for science; in their home laboratory, he and his brother would often duplicate the experiments they read about in scientific journals.”
Clearly some studies will be so complicated that Hungarian teenagers won’t be able to replicate them, or may require equipment they don’t have access to. And of course the Gabor brothers were not your average teenagers. But it used to be possible, and it should be made possible whenever possible. Because otherwise you are asking the majority of people to take your claims on faith. If a scientist is choosing between two lines of work of equal importance, one that requires a nuclear reactor and the other that her neighbor’s kids can do in their basement, she should go with the basement.
It’s good if one big lab can recreate what another big lab claims to have found. But YOU are under no obligation to believe it unless you can replicate it for yourself.
You can of course CHOOSE to trust the big lab, look at their report and decide for yourself. But that’s not really replication. It’s taking someone’s word for something.
There’s nothing wrong with taking someone’s word; you do it all the time. Some things you can’t look into for yourself; and even if you could, you don’t have enough time to look into everything. So we are all practical people and take the word of people we trust for lots of things. But that’s not replication.
Something that you personally can replicate is replication. Watching someone else do it is also pretty close, since you still get to see it for yourself. Something that a big lab would be able to replicate is not really replication. It’s nice to have confirmation from a second lab, but now you’re just taking two people’s word for it instead of one person’s. Something that can in principle be replicated, but isn’t practical for anyone to actually attempt, is not replication at all.
If it cannot be replicated even in principle, then what exactly do you think you’re doing? What exactly do you think you’ve discovered here?
We find it kind of concerning that “does replicate” or “doesn’t replicate” have come to be used as synonyms of “true” and “untrue”. It’s not enough to say that things replicate or not. Blondlot’s N-ray experiments were replicated hundreds of times around France, until all of a sudden they weren’t; van Leeuwenhoek’s observations of tiny critters in pond water weren’t replicated for years, until they were. The modern take on replication (lots of replications from big labs = good) would have gotten both of these wrong.
If knowing the truth about some result is important to you, don’t just take someone’s word for it. Don’t leave it up to the rest of the world to do this work; we’re all bunglers, you should know that. If you can, you should try it for yourself.
So let’s look at some examples of REAL replication. We’ll take our examples from psychology, since as we saw earlier, they’re in the thick of the modern fight over replication.
We also want to take a minute to defend the psychologists, at least on the topic of replication (psychology has other sins, but that’s a subject for another time). Psychology has gotten a lot of heat for being the epicenter of the replication crisis. Lots of psychology studies haven’t replicated under scrutiny. There have been many high-profile disputes and attacks. Lots of famous findings seem to be made out of straw.
Some people have taken this as a sign that psychology is all bunkum. They couldn’t be more wrong — it’s more like this. One family in town gets worried and hires someone to take a look at their house. The specialist shows up and sure enough, their house has termites. Some of the walls are unsafe; parts of the structure are compromised. The family is very worried but they start fumigating and replacing boards that the termites have damaged to keep their house standing. All the other families in town laugh at them and assume that their house is the most likely to fall down. But the opposite is true. No other family has even checked their home for termites; but if termites are in one house in town, they are in other houses for sure. The first family to check is embarrassed, yes, but they’re also the only family who is working to repair the damage.
The same thing is going on in psychology. It’s very embarrassing for the field to have their big mistakes aired in public; but psychology is also distinct for being the first field willing to take a long hard look at themselves and make a serious effort to change for the better. They haven’t done a great job, but they’re one of the only fields that is even trying. We won’t name names but you can bet that other fields have just as many problems with p-hacking — the only difference is that those fields are doing a worse job rooting it out.
The worst thing you can say about psychology is that it is still a very young field. But try looking at physics or chemistry when they were only 100 years old, and see how well they were doing. From this perspective, psychology is doing pretty ok.
Despite setbacks, there has been some real progress in psychology. So here are a few examples of psychological findings that can actually be replicated, by any independent researcher in an afternoon. You don’t have to take our word or anyone else’s word for these findings if you don’t want to. Try it for yourself! Please do try this at home, that’s the point.
Are these the most important psychology findings? Probably not — we picked them because they’re easy to replicate, and you should be able to confirm their results from your sofa (disclaimer: for some of them, you may have to leave your sofa). But all of them are things we didn’t know about 150 years ago, so they represent a real advance in what we know about the mind.
For most of these you will need a small group of people, because most of these are statistically true results, not guaranteed to work in every case. But as long as you have a dozen people or so, they should be pretty reliable.
Draw a Bicycle — Here’s a tricky one you can do all on your own. You’ve seen a bicycle before, right? You know what they look like? Ok, draw one.
Unless you’re a bicycle mechanic, chances are you’ll be really rubbish at this — most people are. While you can recognize a bicycle no problem, you don’t actually know what one looks like. Most people produce drawings that look something like this:
Needless to say, that’s not a good representation of the average bicycle.
Seriously, try this one yourself right now. Don’t look up what a bicycle looks like; draw it as best you can from memory and see what you get. We’ll put a picture of what a bicycle actually looks like at the end of this post.
(A similar example: which of the images below shows what a penny looks like?)
Wisdom of the Crowd — Wisdom of the crowd refers to the fact that people tend to make pretty good guesses on average even when their individual guesses aren’t that good.
You can do this by having a group of people guess how many jellybeans are in a jar of jellybeans, or how much an ox weighs. If you average all the guesses together, most of the time it will be pretty close to the right answer. But we’ve found it’s more fun to stand up there and ask everyone to guess your age.
We’ve had some fun doing this one ourselves, it’s a nice trick, though you need a group of people who don’t know you all that well. It works pretty well in a classroom.
This only works if everyone makes their judgments independently. To make sure they don’t influence each other’s guesses, have them all write down their guesses on a piece of paper before blurting it out.
Individual answers are often comically wrong — sometimes off by up to a decade in both directions — but we’ve been very impressed. In our experience the average of all the guesses is very accurate, often to within a couple of months. But give it a try for yourself.
Emotion in the Face — You look at someone’s face to see how they’re feeling, right? Well, maybe. There’s a neat paper from a few years ago that has an interesting demonstration of how this isn’t always true.
They took photos of tennis players who had just won a point or who had just lost a point, and cut apart their faces and bodies (in the photos; no tennis pros were harmed, etc.). Then they showed people just the bodies or just the faces and asked them to rate how positively or negatively the person was feeling:
They found that people could usually tell that a winning body was someone who was feeling good, and a losing body was someone feeling bad. But with just the faces, they couldn’t tell at all. Just look above – for just the bodies, which guy just won a point? How about for the faces, who won there?
Then they pushed it a step further by putting winning faces on losing bodies, and losing faces on winning bodies, like so:
Again, the faces didn’t seem to matter. People thought chimeras with winning bodies felt better than chimeras with losing bodies, and seemed to ignore the faces.
This one should be pretty easy to test for yourself. Go find some tennis videos on the internet, and take screenshots of the players when they win or lose a point. Cut out the faces and bodies and show them to a couple friends, and ask them to rate how happy/sad each of the bodies and faces seems, or to guess which have just won a point and which have just lost. You could do this one in an afternoon.
Anchoring — This one is a little dicey, and you’ll need a decent-sized group to have a good chance of seeing it.
Ask a room of people to write down some number that will be different for each of them — like the last four digits of their cell phone number, or the last two digits of their student ID or something. Don’t ask for part of their social security number or something that should be kept private.
Let’s assume it’s a classroom. Everyone takes out their student ID and writes down the last two digits of their ID number. If your student ID number is 28568734, you write down “34”.
Now ask everyone to guess how old Mahatma Gandhi was when he died, and write that down too. If this question bores you, you can ask them something else — the average temperature in Antarctica, the average number of floors in buildings in Manhattan, whatever you like.
Then ask everyone to share their answers with you, and write them on the board. You should see that people who have higher numbers as the last two digits of their student ID number (e.g. 78 rather than 22) will guess higher numbers for the second question, even though the two numbers are unrelated. They call this anchoring. You can plot the student ID digits and the estimates of Gandhi’s age on a scatterplot if you like, or even calculate the correlation. It should come out positive.
Inattentional Blindness — If you’ve taken an intro psych class, then you’re familiar with the “Invisible Gorilla” (for everyone else, sorry for spoiling). In the biz they call this “inattentional blindness” — when you aren’t paying attention, or your attention is focused on one task, you miss a lot of stuff.
Turns out this is super easy to replicate, especially a variant called “change blindness”, where you change something but people don’t notice. You can swap out whole people and about half the time, no one picks up on it.
False Memory — For this task you need a small group of people. Have them put away their phones and writing tools; no notes. Tell them you’re doing a memory task — you’ll show them a list of words for 30 seconds, and you want them to remember as many words as possible.
Then, show them the following list of words for 30 seconds or so:
After 30 seconds, hide or take down the list.
Then, wait a while for the second half of the task. If you’re doing this in a classroom, do the first step at the beginning of class, and the second half near the end.
Anyways, after waiting at least 10 minutes, show them these words and ask them, which of the words was on the original list?
Most people will incorrectly remember “sleep” as being on the original list, even though, if you go back and check, it’s not. What’s going on here? Well, all of the words on the original list are related to sleep — sleep adjectives, sleep sounds, sleep paraphernalia — and this leads to a false memory that “sleep” was on the list as well.
You can do the same thing for other words if you want — showing people a list of words like “sour”, “candy”, and “sugar” should lead to false memories of the word “sweet”. You can also read the list of words aloud instead of showing it on a screen for 30 seconds, you should get the same result either way.
Draw your own conclusions about what this tells us about memory, but the effect should be pretty easy to reproduce for yourself.
We don’t think all false memory findings in psychology bear out. We think some of them aren’t true, like the famous Loftus & Palmer (1974) study, which we think is probably bullshit. But we do think it’s clear that it’s easy to create false memories under the right circumstances, and you can do it in the classroom using the approach we describe above.
You can even use something like the inattentional blindness paradigms above to give people false memories about their political opinions. A little on the tricky side but you should also be able to replicate this one if you can get the magic trick right. And if this seems incredible, ridiculous, unbelievable — try it for yourself!