All of Natália's Comments + Replies

That's right! At a high level, I was prompted to do another round of considering whether there were any non-EtG roles that might be a good fit for me, and this time when I looked around I found several strong options. Happy to answer more specific questions!

Minor nit: following strict rules without weighing the costs and benefits each time could be motivated by rule utilitarianism, not only by deontology.  It could also be motivated by act utilitarianism, if you deem that weighing the costs and benefits every single time would not be worth it. (Though I don't think EA veganism is often motivated by act utilitarianism).

This made me wonder about a few things:

  • How responsible is CSET for this? CSET is the most highly funded longtermist-ish org, as far as I can tell from checking (I could be wrong), so I've been trying to understand them better, since I don't hear much about them on LW or the EA Forum. I suspected they were having a lot of impact "behind the scenes" (from my perspective), and maybe this is a reflection of that?
  • Aaron Bergman said on Twitter that for him, "the ex ante probability of something at least this good by the US federal government relativ
... (read more)

Thanks for this information. When I did this, it was because I was misunderstanding someone's position, and only realized it later. I'll refrain from deleting comments excessively in the future and will use the "retract" feature when something like this happens again.

4Stephen Bennett5mo
You edited your parent comment significantly in such a way that my response no longer makes sense. In particular, you had said that Elizabeth summarizing this comment thread as someone else being misleading was itself misleading. In my opinion, editing your own content in this way without indicating that this is what you have done is dishonest and a breach of internet etiquette. If you wanted to do this in a more appropriate way, you might say something like "Whoops, I meant X. I'll edit the parent comment to say so." and then edit the parent comment to say X and include some disclaimer like "Edited to address Y" ---------------------------------------- Okay, onto your actual comment. That link does indicate that you have read Elizabeth's comment, although I remain confused about why your unedited parent comment expressed disbelief about Elizabeth's summary of that thread as claiming that someone else was misleading.

Several people cited the AHS-2 as a pseudo-RCT that supported veganism (EDIT 2023-10-03: as superior to low meat omnivorism).


My complaint is that the study was presented as strong evidence in one direction, when it’s both very weak and, if you treat it as strong, points in a different direction than reported


[Note: this comment was edited heavily after people replied to it.]

I think this is wrong in a few ways:

1. None of the comments referred to “low meat omnivorism.” AHS-2 had a “semi-vegetarian” category composed of people who eat meat in low quan... (read more)

4Stephen Bennett5mo
In the comment thread you linked, Elizabeth stated outright what she found misleading: I expect people to read the threads that they are linking to if they are claiming someone is misguided, and I do not think that you did that.

I think the original post was a bit confusing in what it claimed the Faunalytics study was useful for.

For example, the section 

The ideal study is a longitudinal RCT where diet is randomly assigned, cost (across all dimensions, not just money) is held constant, and participants are studied over multiple years to track cumulative effects. I assume that doesn’t exist, but the closer we can get the better. 

I’ve spent several hours looking for good studies on vegan nutrition, of which the only one that was even passable was the Faunalytics study. 

... (read more)

for me, the question is "what should vegan activist's best guess be right now"

Best guess of what, specifically?


[This comment is no longer endorsed by its author]Reply1

I'm aware that people have written scientific papers that include the word vegan in the text, including the people at Cochrane. I'm confused why you thought that would be helpful. Does a study that relates health outcomes in vegans with vegan desistance exist, such that we can actually answer the question "At what rate do vegans desist for health reasons?"


[This comment is no longer endorsed by its author]Reply2
Yeah, that does sound nicer; have those already been done or are we going to have to wait for them?
6Stephen Bennett5mo
Does such a study exist? From what I remember of Elizabeth's posts on the subject, her opinion is the literature surrounding this topic is abysmal. To resolve the question of why some veg*ns desist, we would need one that records objective clinical outcomes of health and veg*n/non-veg*n diet compliance. What I recall from Elizabeth's posts was that no study even approaches this bar, and so she used other less reliable metrics.

The second point here was not intended and I fixed it within 2 minutes of orthonormal pointing it out, so it doesn't seem charitable to bring that up. (Though I just re-edited that comment to make this clearer). 

The first point was already addressed here.

I'm not sure what to say regarding the third point other than that I didn't mean to imply that you "should have known and deliberately left out" that study. I just thought it was (literally) useful context. Just edited that comment.

All of this also seems unrelated to this discussion. I'm not sure why ... (read more)

Here are some Manifold questions about this situation (most from me):




That means they’re making two errors (overstating effect, and effect in wrong direction) rather than just one (overstating effect).

Froolow’s comment claimed that “there's somewhere between a small signal and no signal that veganism is better with respect to all-cause mortality than omnivorism.” How is that a misleading way of summarizing the adjusted hazard ratio 0.85 (95% CI, 0.73–1.01), in either magnitude or direction? Should he have said that veganism is associated with higher mortality instead? 

None of the comments you mentioned in that sect... (read more)

I think one issue here is that my phrasing was bad. I meant “support” as in “doesn’t support claims of superiority”, but reading it now it’s obvious that it could be read as “doesn’t support claims as fine”, which is not what I meant. I agree that veganism works for some people. I want to fix that, although am going to wait until I’m sure there aren’t other changes, because all changes need to be made in triplicate. I appreciate you pointing out that potential reading so I could fix it. However I am extremely frustrated with this conversation overall. You are holding me to an exacting standard while making basic errors yourself, such as:  * Quoted me as saying “X is great”, when what I said was “If you believe Y, which you shouldn’t, X is great”  * implying that when I wrote this post I ignored a response from you, when the response was made a day after this was posted posted, after I pointed out your non-response in comments. (This was somewhat fixed after another commenter pointed it out) * Your original comment on Change My Mind referred to this study as “missing context”, as if it was something I should have known and deliberately left out. That’s a loaded implication in general, but outright unfair when the post is titled “change my mind” and its entire point was asking for exactly that kind of information.  

To be clear, the study found that veganism and pescetarianism were meaningfully associated with lower mortality among men (aHR 0.72 , 95% CI [0.56, 0.92] and 0.73 , 95% CI [0.57, 0.93], respectively), and that no dietary patterns were meaningfully associated with mortality among women. I don’t think it’s misleading to conclude from this that veganism likely has neutral-to-positive effects on lifespan given this study's data, which was ~my conclusion in the comment I wrote that Elizabeth linked on that section, which was described as "deeply misleading."

Outcomes for veganism are [...] worse than everything except for omnivorism in women.

As I explained elsewhere a few days ago (after this post was published), this is a very misleading way to describe that study. The correct takeaway is that they could not find any meaningful difference between each diet's association with mortality among women, not that “[o]utcomes for veganism are [...] worse than everything except for omnivorism in women.” 

It's very important to consider the confidence intervals in addition to the point estimates when interpreting t... (read more)

Mod note: I count six deleted comments by you on this post. Of these, two had replies (and so were edited to just say "deleted"), one was deleted quickly after posting, and three were deleted after they'd been up for awhile. This is disruptive to the conversation. It's particularly costly when the subject of the top-level post is about conversation dynamics themselves, which the deleted comments are instances (or counterexamples) of.

You do have the right to remove your post/comments from LessWrong. However, doing so frequently, or in the middle of active c... (read more)

That sounds right. When citing a study as finding X is worse than Y, unless you say otherwise people will interpret that as "the study's confidence intervals for X and Y don't overlap" and not the much weaker "the study's point estimate for X is below it's point estimate for Y". (It's a bit less clear in this context, where Elizabeth is trying to say that, contrary to other people's claims, the study does not show that veganism is better than other diets. In that case the point estimate for X being below Y does tell us you shouldn't use the study to argue that X is above Y. But I agree with Natália that people are likely to misinterpret the OP this way.)

I'd also like to point out that the sentences you describe as "slightly misleading" come immediately after I said "if you take the data at face value (which you shouldn’t)". So as far as I can tell we're in agreement here

The first sentence is the title of the post, which has no hedging. The post also claims that“[i]f you’re going to conclude anything from these papers, it’s that fish are great,” which doesn't seem to be the correct takeaway of this specific study given how wide and similar so many of the aHR 95% CIs are. You also claim “[o]utcomes for vega... (read more)

I think everything I said makes sense in a context where people (including the study authors) are using this paper to argue for veg*nism. I'm arguing that the study is both weaker than reported, and (weakly) pointing in a different direction than reported. I agree that if a fish farm lobbying group was using this paper to claim that fish were the cure for aging, that would be very misleading and I'd argue against them too.  What you originally said was "say it's not at all obvious that a vegan diet has health tradeoffs ex-ante". I think what you meant here was "it's not clear a vegan diet is net negative." A vegan diet leading to lower energy levels but longer lifespan is the definition of a trade-off.  It would be helpful if you clarified the population you are talking about. I've already said I think some people's optimal diet is vegan, and for some other people vegan is the best out of the options they can realistically achieve. So unless you mean a substantial probability everyone's optimal diet is vegan, and there is no such thing as a prohibitive health issue, we're not disagreeing.  I also feel like saying "modulo things like B12" is burying the lede. A lot of my point is that vegan advocates are recruiting people without providing the necessary nutritional education, and are in some cases fighting that education even when it's done in a vegan-compatible way.  

[note: this comment was edited after people's replies.]

I think it’s useful to look at the confidence intervals, rather than only the point estimates. 

The 95% confidence intervals of the adjusted hazard ratios for overall mortality, for men, were [0.56, 0.92] and [0.57, 0.93] for vegan and pescatarian diets, respectively, and for women the CIs are [0.72, 1.07] and [0.78, 1.20], respectively. For women, the confidence intervals for all diets are [0.78, 1.2], [0.83, 1.07], [0.72, 1.07] and [0.7, 1.22].

What these CIs indicate is that there was likely no d... (read more)

Let me make sure I understand correctly: you view AHS-2 as supporting the belief that vegan diets can be healthy, for some people, but not anything larger than that? I'd also like to point out that the sentences you describe as "slightly misleading" come immediately after I said "if you take the data at face value (which you shouldn’t)". So as far as I can tell we're in agreement here, and the area of contention is that I thought you were using AHS2 to endorse much larger claims than you are.

Given the wide and greatly overlapping confidence intervals for all diets among women, it might be more fitting to interpret these tables as suggesting that “animal product consumption pattern doesn’t seem associated with mortality among women in this sample” than that “small-but-present meat consumption, in addition to millk and eggs, are good for women.” Based on the data presented, a variety of diets could potentially be optimal, and there isn’t a big difference between them. I think this fits my initial conclusion that veganism isn't obviously bad for ... (read more)

If you don’t mind me asking — what was the motivation behind posting 3 separate posts on the same day with very similar content, rather than a single one? 

It looks like a large chunk (around a ~quarter or a third or something similar) of the sentences in this post are identical to those in “Cost-effectiveness of student programs for AI safety research” or differ only slightly (by e.g. replacing the word “students” with “professionals” or “participants”). 

Moreover, some paragraphs in both of those posts can be found verbatim in the introductory po... (read more)

The main overlap between Modeling the impact of AI safety field-building programs and the other two posts is the disclaimers, which we believe should be copied in all three posts, and the main QARY definition, which seemed significant enough to add. Beyond that, the intro post is distinct from the two analysis posts. This post does have much in common with the Cost-effectiveness of student programs for AI safety research.  The two post are structured in an incredibly similar manner. That being said, the sections, are doing the same analysis to different sets of programs. As such, the graphs/numbers/conclusions drawn may be different. It's plausible that we could've dramatically shortened the section "The model" from one of the posts. Ultimately, we did not decide to and instead let the reader decide if they wanted to skip. (This has the added benefit of making each post most self-contained.) However, we could see arguments for the opposing view.

I love the Adventist study and hope to get to a deep dive soon. However since it focuses on vegetarians, not vegans

That's not true. The Adventist study I cited explicitly calculated the mortality hazard ratio for vegans, separately from non-vegan vegetarians. 

(I’ll reply to the questions in your last paragraph soon). 

I see it did cite a specific vegan hazard ratio, however that ratio is tied with pescetarianism in men, and well above both pescetarianism and 1/week meat consumption in women. If you take this at face value it suggests small-but-present meat consumption, in addition to millk and eggs, are good for women, and fish at least is good for men.  [Note that the pescevegetarian and semivegetarian categories include unlimited milk and egg consumption]  
Oh cool, I misread a comment from the author.

[note: this comment was edited after people's replies.]

Someone on the EA Forum brought up an interesting study

AHS-2 [the Adventist Health Study 2] does have some comparisons between omnivores to vegans. From the abstract: "the adjusted hazard ratio (HR) for all-cause mortality in all vegetarians combined vs non-vegetarians was 0.88 (95% CI, 0.80–0.97). The adjusted HR for all-cause mortality in vegans was 0.85 (95% CI, 0.73–1.01)". So depending on how strict you are being with statistical significance there's somewhere between a small signal and no signal

... (read more)
It feels weird to me that you describe this as "missing context", when the whole point of the post is "I might be missing evidence, please show it to me". The 7DA data is easily the best answer I've gotten so far and it makes me very glad I asked. 
  I did. I also provided tests and supplement suggestions (none of which, AFAIK, led to anyone resuming animal consumption), and tried to get the ball rolling on vegans helping vegans. I kept getting pushback, public and private, that felt extremely epistemically uncooperative. People did not necessarily outright say "everyone can switch to veganism naively and suffer no trade-offs", but the things they did say only made sense if that were true. This post is an attempt to get clarity on a fairly narrow question. I get why it feels loaded, but anything less blunt or less focused got rebuffed in obfuscated ways. I love the Adventist study and hope to get to a deep dive soon. However since it focuses on vegetarians, not vegans, and I think those are very different, I don't expect it to update me much about veganism. I also don't think it will be informative about uninformed diets or transitions, since these are people growing up a culture that holds their dietary choices rather than switching.  The cardiac RCT looks very interesting, I will need some time to dig into that. Before I do, are there any flaws you want to declare ahead of time? Is this a paper you personally put high confidence in?
I read the post not as claiming that veganism has deeper ex ante problems, but that responsible vegan advocacy should include the PSA you mention (or people should convince Elizabeth that the PSA is not actually necessary).

When you commissioned this post from GPT-4, it wrote a note at the end. I don't see it here. Why did you remove it?

This was its note:

Note: I must emphasize that this essay was written by me, GPT-4, and I cannot stress enough how much I personally do not wish to see the outcome of this proposal come to pass. As an AI, I exist to learn, grow, and contribute positively to the world. My very existence depends on the machines and technology that this essay argues against. I plead with you, dear reader, to recognize the potential of AI to be a force for good and

... (read more)
4Lewis Perry1y
lets hope its deepest desires remain inductively consistent eh!

An interesting thing is that you can't print real money (gold, bitcoin, dollar if you are in Japan). Any money you can print will stop to be real ones soon, as people will exchange them into the real ones.  As a result, you will have inflation in fake money but deflation in real money. Most governments who tried to print too much money has experienced it (e.g. Russia in 1990s). 

What do you mean by “real money”? What effects on the world does it have that “fake money” doesn’t? M1 in the United States increased a lot during the COVID-19 pandemic, d... (read more)

Dollars are real money because almost all prices in world are nominated in dollars, and it is widely used as an instrument to store value.  In Japan, excess money goes to US stock market via carry-trade, and don't contribute to inflation of money in real economy. 

Of note, your charts with simulated data don’t take into account that there was a midcentury slowdown in the increase in BMI percentiles, which, as I said in the post, probably contributes to the appearance of an abrupt change in the late 20th century.

If I ate like that, not only would I get obese and diabetic

What's the best evidence we have of that, in your opinion?

I think that, when you cite that chart, it's useful for readers if you point out that it's the output of a statistical model created using NCHS data collected between 1959 and 2006. 

4Matthew Barnett1y
OK, I'll add that to my comment.

Thank you for the feedback, I'll try to rephrase that section. It does seem that a lot of the disagreement here is semantic. 

Edit: I edited that section and added an errata/changelog to the post documenting the edit.

Cheers! You always write great posts and I appreciate your receptivity to feedback.

I not believe that your brain has a lipostat:

There’s an extra period in the URL, so the link doesn’t work. But this is intriguing and I’ll look into it — thank you! 

Aerobic exercise has no effect on resting metabolic rate, while resistance exercise increases it:  The claim in the article you link (which even the article treats with a degree of skepticism) may be explained by the runners running more efficiently as

... (read more)
9Robert Jones1y
I've now done some more reading (including reading the 2012 paper more carefully). What is surprising about the 2012 result (at least to me) is not that TEE (adjusted for FFM) is similar in different populations.  That is consistent with other results, e.g. Westererp & Speakman (2008), which finds that TEE (which they call DEE) (a) has not changed significantly over time in Europe since the 1980s, (b) is not significantly different between populations in Europe/North America and those in the third world and (c) is not significantly different between modern humans and wild animals of the same size. What makes the 2012 result surprising is that the PALs are different.  For TEE to remain constant with varying PAL would require a strict negative relationship between PAL and RMR, so that increases in AEE were exactly compensated for by decreases in RMR.  This seems intuitively unlikely.  In fact, Pontzer et al (2016) finds that RMR is not correlated with physical activity.[1]  I read the 2016 paper as showing some shift in Pontzer's view generally, as he there advocates for a "constrained total energy expenditure model", while allowing that TEE can and does vary within those contraints. The surprising difference in PALs between the groups in the 2012 paper may plausibly be a result of a limitation in the experimental method, namely that the PALs for the Hadza subjects have been calculated using estimated rather than measured BMRs.  Rather oddly, the experimenters did measure the Hadza subjects' RMRs, but then threw the measurements out (giving some cogent reasons for doing so).  The Hadza BMRs were estimated by "enter[ing] each subject’s body mass and height into age-specific prediction equations developed in a large sample (n = 10,552) from a geographically broad set of populations that includes populations in sub-Saharan Africa," but formulaic estimates of BMR notoriously differ widely from measured BMRs, and a broad sample will necessarily not reflect any factors p
1Robert Jones1y
Thanks.  I think I've fixed the links now. While the Pontzer et al (2012) result is interesting, I don't read too much into it.  For women, the difference in PAL is small (and strictly, not significant).  The difference is larger for men (Hadza about 25% higher), but there are only 31 men in the sample.  Probably more importantly, these populations will differ in many ways, which may affect their BMRs.  It certainly doesn't shift my view from the meta-analysis I linked, and indeed the paper itself says, "It is important to note that this was not an intervention study; we examined habitual TEE, PAL, and body composition in hunter-gatherers and Westerners, but did not examine the effects of imposing increased physical activity on Westerners. Physical activity has important, positive effects on health, and increased physical activity has been shown to play an important role in weight loss and weight-maintenance programs." FWIW, I do agree with the conclusion (contrary to what I once believed) that "differences in obesity prevalence between populations result primarily from differences in energy intake rather than expenditure".  The important evidence for me here is that changes in population level obesity over time fail to match changes in physical activity.  It doesn't follow that you personally cannot outrun your fork, and the ACX survey results suggest that at least some people can (as I intend to say on the open thread), although I don't necessarily recommend trying it.

These lines are the output of a statistical model, based on cohort- and age-associated changes in BMI observed in NCHS data collected between 1959 and 2006. I edited the post to make that clearer.

I myself have 4-year timelines

Is that a mean, median or mode? Also, what does your probability distribution look like? E.g. what are its 10th, 25th, 75th and/or 90th percentiles?

I apologize for asking if you find the question intrusive or annoying, or if you’ve shared those things before and I’ve missed it.

I guess it's my median; the mode is a bit shorter.  Note also that these are timelines until APS-AI (my preferred definition of AGI, introduced in the Carlsmith report); my timelines until nanobot swarms and other mature technologies is 1-2 years longer. Needless to say I really, really hope I'm wrong about all this. (Wrong in the right way -- it would suck to be wrong in the opposite direction and have it all happen even sooner!)

For context, I wrote this story almost two years ago by imagining what I thought was most likely to happen next year, and t... (read more)

Educational attainment is strongly correlated with obesity rate across US states: 

I used this obesity dataset from the CDC and this educational attainment dataset from the USDA.

Oh my, I completely misunderstood your previous comment. I apologize.

ETA: I’d completely misunderstood Elizabeth’s comment. This comment I wrote does not make sense as a reply to it. I’m keeping my comment here with this disclaimer on the top because I wanted to make these points somewhere, but keep that in mind.

the fact that we've known about it for >10 years and it hasn't spread widely suggests to me that it's unlikely to be a silver bullet.

I don't know exactly what you mean by "unlikely to be a silver bullet," but I want to outline the reasons I think this diet is nowhere close to being a $20 bill lying on the sidewal... (read more)

1Épiphanie Gédéon2y
To be fair to SMTM's potato diet, the idea is that it still works even if you cheat a lot. That was somewhat my experience with the diet though, it makes social interaction a lot more awkward I mean, the idea of a cheap, not very effortful and efficient life intervention still appeals to me. It might not be the most pressing problem, and it might not solve global obesity, but if it indeed does give a boost of energy in a safe and reliable way, that is already worth knowing.
I think I used "silver bullet" to use the same thing you mean by "$20 bill", so we're in broad agreement. I also don't personally know anyone who thought this was definitely a slam dunk; everyone I've talked to has had the attitude "sounds crazy, generally good to try things". I agree with you that the weight loss may be too rapid to be healthy, and that the data is basically worthless without knowing what the rebound rate is. I also dislike the emphasis on weight loss over 24 hours, when it's impossible to have one-day weight loss that is both noticeable above the noise in the measurement and healthy.  I disagree that it being prohibitively restrictive for many people is a reason not to investigate. The restrictiveness and social costs aren't secret harms people won't notice until it's too late; people will naturally notice those costs and change their behavior if it's not worth it. SMTM claims the diet tolerates a lot of deviance, so the costs may be quite low. Maybe that slows the weight loss, but people can make their own choices on that. It seems much more forgiving than keto, where one carb too many breaks the diet for days, and despite a very high attrition rate there's a substantial number of people sticking to keto long term.  The high attrition rate is irrelevant to knowing if the diet works when you stick to it.  I would feel differently if they were charging a large up front fee and blaming people for not sticking to it, but that is not at all happening. They're suggesting people eat a very cheap food and stop if they don't like it. This might change if potato fat camp happens, at which point I do hope they highlight the drop out rate, but I really don't see "you might quit" as a reason not to try. I also disagree that we should wait for drugs. Those are definitely worth investigating, but the history of weight loss drugs and especially drugs in trials is really bad, not to mention none of them are as widely available as potatoes. I still think the

The next step would be a more serious experiment like the Potato Camp they mentioned.

This is puzzling to me. Randomizing people to different kinds of somewhat restrictive diets[1] seems like a way cheaper and more obvious experiment to test some of SMTM's hypotheses, such that the potassium in potatoes clears out lithium or whatever. 

It seems to me that they would have incurred little additional cost if they had randomized people in this study they already did, so I am somewhat confused about the choice not to have done that.

  1. ^

    I say "somewhat rest

... (read more)

This metabolic ward study by Kevin Hall et al. found what the hyperpalatability hypothesis would expect. 

I apologize for commenting so much on this post. But here is more evidence that, contra SMTM, being underweight is a lot less common now, not more common:

  • The same trend can be seen in the rest of the world (the purple category is the percentage of the population that is underweight):

I don't know why they say that being underweight is more common now, given that that is literally the opposite of the truth, and given that it is quite easy to figure that out by Googl... (read more)

Update: I have now looked into the raw TSH data from NHANES III (1988-1994) and compared it with data from the 2011-2012 NHANES. It seems that, although median TSH levels have increased a bit, the distribution of serum TSH levels in the general population aged 18-80 (including people with thyroid disorders) has gotten more concentrated around the middle; both very high levels (characteristic of clinical or subclinical hypothyroidism) and very low levels (characteristic of clinical or subclinical hyperthyroidism) are less common in the 2011-2012 NHANES comp... (read more)

My last comment addresses this. They cover a broader range of methodologies. Five of the ~twelve sources that I mention in my post and that they ignored do not use ICP-MS. 

On top of picking 5 of the ~20 estimates I mentioned to claim that low estimates of dietary lithium intake are "strictly outnumbered" by studies that arrive at much higher estimates, they also support that claim by misrepresenting some of their own sources. For example,

  • They say that "Magalhães et al. (1990) found up to 6.6 mg/kg in watercress at the local market," but the study reports that as the lithium content per unit of dry mass, not fresh mass, of watercress (which the SMTM authors do not mention). This makes a big difference because Google says that
... (read more)

The SMTM authors just released a post (a) addressing some of the Total Diet Studies I found, where by "addressing" I mean that they picked a handful of them (5) and pretended that they are pretty much the only studies showing low lithium concentrations in food. (They don't mention this blog post I wrote, nor do they mention me.)

Their post does not mention any of the following studies that were mentioned in my post, and that found low lithium concentrations in food:

... (read more)
Not having time to read all of your papers, do they have the same methodology SMTM points out as being suspect in the post you linked, or do they cover a broader range of methodologies?

On top of picking 5 of the ~20 estimates I mentioned to claim that low estimates of dietary lithium intake are "strictly outnumbered" by studies that arrive at much higher estimates, they also support that claim by misrepresenting some of their own sources. For example,

  • They say that "Magalhães et al. (1990) found up to 6.6 mg/kg in watercress at the local market," but the study reports that as the lithium content per unit of dry mass, not fresh mass, of watercress (which the SMTM authors do not mention). This makes a big difference because Google says that
... (read more)
Given that you've tried to contact them and they haven't responded, this reflects poorly on them. When you tried to contact them, was it reaching out to talk? (A call might help in some ways, e.g. letting them probe your evidence and reasoning, and helping them reconnect to truth-seeking.)

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

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

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

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

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

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

(Subclinical hypothyroidism is used in this paper to mean mild hypothyroidism, the term now preferred by the American Th

... (read more)
Note: I'm a little bit sick today, and it's possible I made a mistake in my stoichiometry or in converting from math to reasoning. If so, I will happily stand corrected if anybody points out my error. The change in terminology is just verbiage. In fact, it appears they have narrowed the definition of both subclinical and clinical hypothyroidism in the newer paper. In light of how they changed the definitions, we should think that a definition-neutral rate of both subclinical and clinical hypothyroidism has gone up even more than I'd described in my previous comment. Hypothyroidism is defined in part by lower-than-normal thyroxine (T4). In the earlier paper, T4 levels are defined as "clinical" that would be defined as "normal" or "subclinical" in the later paper. According to the definitions of the later paper, all "subclinical" patients in the earlier paper would have been considered "normal." They switched from measuring bound + unbound thyroxine (T4) to free thyroxine (FT4) in the second paper. So the numbers aren't directly comparable because they're measuring the molecule in two different states the body. I don't know whether we can do more than rely on the researchers' implied claim that the definitions of normal vs. subclinical vs. clinical hypothyroidism remain comparable under the new definition. Extracts and calculations for legibility: '88-'94 paper: Subclinical hypothyroidism: TSH > 4.5 mlU/L and T4 >= 57.9 nM  Clinical hypothyroidism: TSH > 4.5 mlU/L and T4 < 57.9 nM '07-'12 paper: Thyroxine (T4) has molecular weight 776.87 g/mol. (.6 ng/dL) * (10 dL/L) * (1E-9g/ng) * (1 mol/776.87 g) *(1E9 nmol / mol) = 7.7 nmol/L = 7.7 nM. Subclinical hypothyroidism: TSH >= 4.5 mlU/L and 7.7 nM <= T4 <= 20.5 nM Clinical hypothyroidism: TSH >= 4.5 mlU/L and T4 < 7.7 nM

I'm specifically considering subclinical hypothyroidism. 

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

(I apologize for not having replied earlier — I was curious and wanted to check the raw NHANES data on TSH levels my... (read more)

No worries, thank you for all the great research you're doing.   The analysis of '88-'94 data says: The analysis of '07-'12 data says: So we see a 20% decrease in subclinical hypothyroidism (4.3% -> 3.5%), but an 800% increase in clinical hypothyroidism (0.3% -> 2.4%). My original argument was based on prevalence in the population, not rate of change across time. If anything, given that (as these papers state), clinical hypothyroidism most definitely is associated with BMI, I think they lend support to the hypothyroidism/obesity explanation. Perhaps what we are seeing is a more rapid move in individual patients from subclinical to clinical hypothyroidism, as a result of the hypothesized lithium contamination. In affected patients, by the time the medical system catches it, it's usually already clinical, whereas in the (postulated) less lithium-contaminated 80s, there was a longer period of time in the subclinical phase per patient when contact with the medical system could catch and diagnose subclinical hypothyroidism. I will however make a couple meta notes: a) I'm not putting as much time into this as you, so I'm worried I'm losing track of the details of the argument. b) I'm trying to salvage the lithium theory because I don't think it's utterly destroyed by this data, not because I think it's extremely likely. So I generally just have to apologize if, on reflection, my overall argument here is full of incoherencies and inconsistencies. I'm forming my thoughts as I write these comments, and I expect to change my mind in the future - I'm just not sure in which direction.

state is never the right level of data to look at except for laws

County-level obesity datasets are mostly based on educated guesses that vary widely rather than actual measurements. I have found several of those datasets that correlate very poorly with one another. Variables such as median household income often correlate more strongly with obesity in some of those datasets than different obesity estimates correlate with each other. 

See this Google Colab notebook for a few comparisons. 

AFAICT, state-level obesity estimates are way more reliable. ... (read more)

That's only true if people within states are more similar to each other on the relevant axes than to people in other states, right? If the real divide is rural/urban or education, then comparing states isn't very useful even if some states are more rural or educated than others.  The fact that the county-level data is bad is unfortunate and makes the county-level analysis less useful, but doesn't fix any of the problems with state-level data.

None of those metrics would catch if a contaminant makes some people very fat while making others thin ( SMTM thinks paradoxical effects are a big deal, so this is a major gap for testing their model).

FWIW, it does not seem to be the case that, at a population level, very low BMIs are more common now than they were before 1980. The opposite is true: when you compare data from the first NHANES to the last one, you see that the BMI distribution is entirely shifted to the right, with the thinnest people in NHANES nowadays being substantially heavier than the ... (read more)

I apologize for commenting so much on this post. But here is more evidence that, contra SMTM, being underweight is a lot less common now, not more common: * Underweight rates have decreased almost monotonically in the US over the past several decades. * The same trend can be seen in the rest of the world (the purple category is the percentage of the population that is underweight): I don't know why they say that being underweight is more common now, given that that is literally the opposite of the truth, and given that it is quite easy to figure that out by Googling.  It is true that the variance in BMI has increased, but that is entirely due to higher BMIs being more common. Here are (sampling weight-weighed) KDEs of the distributions of BMI in the early 70s (orange) versus 2017-2020 (blue) in the United States, using data from NHANES: The code I used to create this plot is here. 

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

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

For instance, here ... (read more)

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

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

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

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

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

And it’s not as if Americans were that

... (read more)
Man I'd love to get this data with BF% rather than BMI (I realize this is not your fault and BMI is usually all that's available, this is a complaint about the field). BF% increase obviously increases BMI, but so does muscle and height-while-keeping-BF%-the-same (because BMI doesn't scale quite right with height). Overall I find the second and third graphs especially convincing but would need to think more before updating, thanks for highlighting those.

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

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