Prescription Drug Safety

Recently I listened to an eye-opening podcast with Katherine Eban, who recently published a book, Bottle of Lies, on her 10 years of investigating generic drugs. This interview is well worth the listen, and I’d highly recommend it, but the short of it is that nearly 80% of the Indian and Chinese manufacturing plants that make most of the generic drugs on the market are tainted with fraud.

One of the bright spots/actionable followups on this was that there is actually a startup pharmacy, Valisure, which tests every single batch of medication that they sell (they developed their own mass-spec pipeline to do this efficiently/in a cost-effective manner).

Here’s a fascinating discussion with the CEO of Valisure on their discovery of super-high levels of the carcinogen NDMA in Zantac (Ranitidine) that’s also well worth a listen (if you are taking Zantac, including the branded versions, stop – it’s very likely that it’s an inherently unstable/carcinogenic drug!)

1 Year Personal Health Intervention Summary

For more general information, see also my previous overview post On Nutrition and Metabolism. This post drills into my personal n=1 experience this past year, covering the results, as well as a summary of the interventions, thought processes, and some of the research on what worked for me. This post will be a bit long…

After 15 years of slowly packing on pounds through stressful jobs, poor sleep, and eating too well (and also a few years after Metabolic Syndrome and NAFLD diagnoses but without any useful treatment, and more than a few failed “get healthy” attempts), I was feeling especially run down last year and decided that I really needed to take a hard look at this. I’d sort of run out of excuses and realized that I’d been putting off prioritizing my health for way too long, and that I really should at least try to figure it out.

After a couple weeks of research, it became pretty obvious that all the metabolic and nutritional knowledge I had ever been taught, told, or thought I knew (from the food pyramid on) was laughably wrong. My initial research convinced me to commit to giving a well-formulated ketogenic diet and time restricted eating/intermittent fasting a go for at least a month.

Ketogenic diets are a type of very-low carbohydrate diet that can be summarized as <20g of net carbohydrates (subtract fiber), or <50g of total carbs per day. While still somewhat contentious, recent research has shown this intervention to be extremely effective at rapidly improving almost all markers of cardio-metabolic health. Phinney and Volek, two early VLC researchers/clinical practitioners (and co-founders of Virta Health, a startup focused on T2D reversal via a continuous remote care model) have defined a Well Formulated Ketogenic Diet. Other sensible approaches include Eric Westman’s “No Sugar, No Starch” 4 pager, Diet Doctor’s Visual Guide, Ted Naiman’s Diet 2.0, or the Sapien Diet.

I focused on the highest quality, most nutrient dense, unprocessed whole foods that I could reasonably buy (although I’d guess you’d get 95% of the benefit as long as you just focused on the last part), and tracked my food consumption for the first few months with a food scale and either Cronometer (a not-great UI, but by far the best tool available for ballparking micronutrients) or Bitesnap, a tool with a much better UI that can be used as a food journal, with decent tracking capabilities. I don’t think this level of tracking is absolutely necessary for most people, but it was pretty useful for me. Starting out, it’s probably best to be relatively strict with carb consumption, but to eat ad libitum until you’ve started to fat adapt, and to pay attention to your body’s satiety signals, but it can also be useful to have something to aim for. Using a macro calculator with a reasonable deficit (15-20%) worked well for me. (There are some other interesting calculators that try to account for maximum fat oxidation rates under hypophagia and other factors.)

It’s worth noting that the biggest thing about trying out this way of eating is that you basically should be prepared on giving up most packaged and prepared foods until you figure things out, since sugar is basically in everything, and that keto-adaptation is a process that really takes a few weeks (or longer). I recommend making at least a 1-month commitment and carefully tracking results and how you feel to see if this is right for you if you’re trying it out. For me, making the decision to cut out sugar, carbs, and sweeteners completely was actually easier to stick to than previous half-measures since it was a lot simpler, and it also let my palette and habits reset as well (this is part of how mono-diets can work).

As you fat adapt, most people naturally get less hungry and eat less often, but I decided to go all in and kick start my keto eating simultaneously with a 16:8 time restricted feeding window (only eating 8 hours of the day and not the other 16). I used Zero to help track this, and it’s actually the most consistent tool I used throughout my year. I let my window length and times float quite a bit, although there’s research that’s suggestive that eating at regular times to help entrain your circadian rhythm is independently beneficial. While I can’t ever purposefully recall not eating for a day before, my first fast ended up being over 24 hours (the first couple days were miserable, and aided by copious drinking of hot green tea). Eventually, as I adapted, I aimed to work up to occasional (about once/quarter) longer fasts, as emerging evidence suggested copious long-term benefits of extended fasts (see: bestof).

Some Numbers

OK, on to some results. I’m a 5’6″ 38yo M and my max weight recorded was 210.2lb in Feb 2018 (I’ve been using a Withings scale on and off since 2012). I started keto/IF (after a week long low-carb paleo run-in with some delivered meals) at the end of last August weighing in at 200.1lb, and 1 year later, weighed in at 153.8lb. That’s -46.3lb (-23.1%) at the one year, -56.4lb (-26.8%) from my max weight:

1-year graph from Withings Scale and Happy Scale app

After a very steady drop of about 2lb/week, my weight “plateaued” a few months back just a couple pounds shy of my original (completely arbitrary) 150lb goal, but rather than forcing the last few pounds too much, I’ve been more focused on getting stronger and on body recomposition. For those frustrated about weight plateaus, I highly recommend taking regular body pics and taking tape measurements (my other measurements have continued to improve despite basically no movement in weight in the past few months).

The last time I was at this weight was probably around 2003, shortly after college and before I started simultaneously juggling work, multiple projects, and grad school.

Body Composition

I took 3 DXA scans (considered by most to be the “gold” standard for measuring body composition), one at 1mo, 6mo, and 1yr at a local Dexafit (I also measured my RMR twice via indirect calorimetry and showed a change in RQ towards fat adaptation (~0.85 at 6mo) and about the expected RMR both times (close to the Mifflin St Jeor formula). The non-DXA fat estimates are based on linear regression from the 1mo/6mo results and are included for ballpark reference.

Max (Est) Start (Est) 1mo DXA 6mo DXA 1yr DXA 1yr Change
Weight 210.2lb 200.1lb 193.4lb 161.0lb 155.1lb -45.0lb
BMI 33.9 32.3 31.2 26.0 25.0
Total BF% 38.0% 35.7% 34.2% 26.8% 24.4% -11.3%
Visceral Fat 3.46lb 3.11lb 2.88lb 1.77lb 1.02lb -2.09lb

One interesting note from my last DXA is that -5.4lb of my -5.9lb change was fat mass, with almost no lean mass lost, which impressed the technician, and IMO reflects well on my recomp efforts.

Visceral fat, particularly ectopic fat is the most dangerous kind, and can affect those who don’t have high BMI (TOFI=Thin Outside, Fat Inside), or who have low personal subcutaneous adipose tissue (low personal fat thresholds). The best way to track this at home is probably by measuring waist circumference.

(Also worth mentioning, don’t trust any home scales measuring body fat % using bioimpedance analysis, they are uselessly inaccurate.)

Reversal of Metabolic Syndrome

While my A1c had mostly stayed pretty well controlled (although it has still inched down this past year), over the past 10 years or so I was steadily adding Metabolic Syndrome markers. I had a solid 3/5 (positive MetS diagnosis), but over the course of the year, have reversed that to 0/5 (also, I’m now within the 12.2% of American adults that are “metabolically optimal” according to this recent analysis of NHANES data), so I’m pretty happy about that. My usual fasting glucose tends to hang around 100 (I will probably try out a Dexcom CGM at some point to get a better idea of the variability), but with my A1c and TG in a good range I’m not too worried about it either way, just curious to see what foods my affect me in which way and what the general AUC looks like.

ATP III Before 1mo 4mo 9mo 1yr 1yr Change
HbA1C % 5.6 5.4 5.2 5.3 5.3 -0.3%
Waist Circumference >40″ 43.0 42.0 38.5 36.8 35.9 -7.1″
Fasting Glucose >100mg/dL 100 101 92 99 89 n/c
Triglycerides >150mg/dL 396 153 95 95 -301mg/dL
HDL <40mg/dL 35 34 59 52 +24mg/dL
Hypertension >130/>85mmHg 122/78 124/84 126/74 117/74 115/77 n/c

A few notes on measurement. Some doctors will tell you that fasted measurements are unnecessary, but they’re probably wrong. While non-fasted FBG/TG measures may be useful, fasted measures are better for standard risk assessment if you’re only getting tested once or twice a year (and you don’t want to just test what you recently ate) and you need to be fasted to get fasting glucose and insulin levels anyway. You should try to standardize your draw as much as possible – eg fasting time (at least 12h, probably not more than 16h as LDL goes up as you fast), wake time (more than a few hours after waking up to minimize dawn effect), and probably not the day after a heavy workout either (high intensity or long duration tends to increase LDL, resistance training may decrease LDL). It’s important to recognize that even with all of this that lipid and glucose measurements are highly mobile even within the course of a day. Also, while A1c is sometimes a more reliable marker than FBG (summary: it generally represents a 90 day average of BG), it’s dependent on RBC turnover and when there’s discordance, you may need to crosscheck with Fructosamine and other markers). One interesting anecdotal note is that in a recent podcast, Peter Attia noted that in 75% of cases, A1c was discordant with CGM average glucose numbers.

Blood pressure is another highly mobile marker (the best way to lower it seems to be to measure again), and I did buy a pretty sci-fi looking Omron Bluetooth BP cuff a few months ago to try to get more frequent measurements/better averages.

Reversal of NAFLD

In 2016 my GP at the time recommended I get a liver ultrasound (he had gotten a new cart in the office it seems like) which showed some fatty deposit buildup. What was especially interesting to me is that despite having elevated liver markers for years, those markers (AST, ALT) were largely normalized within the first month of changing my diet.

The gold standard for NAFLD diagnosis is MRI (this is not often done outside of lab studies), but it turns out there are actually many proxy formulas. The NAFLD-LFS (which can have 95% sensitivity!) requires just your standard markers and fasting insulin (a less good formula, FLI can be used if you have GGT), however I only have fasting insulin for my most recent labs (nothing from any of my physicals in the past 10 years – more on this later). Considering NAFLD is estimated to affect 80-100M people just in the US, that seems pretty insane, but then again, I’m not a medical professional.

Reference Before 1mo 4mo 9mo 1yr 1yr Change
ALP 20-140IU/L 46 43 41 n/c
AST 11-34IU/L 48 26 25 20 25 -47.9%
ALT 9-59U/L 113 49 29 28 22 -80.5%
NAFLD LFS <-1.413 @ 95%sen -2.03 -2.63 reversal

For those interested in reading more about NAFL (or any metabolic research), it’s important to keep in mind that there are some conflicting translational studies because mice have very different liver/intestinal signaling than humans (and their rat chow is basically casein, industrially-processed seed oils, and sugar), and that when there are robust human research or clinical outcomes, those should always be preferred. Also, that at the end of the day, there’s so much bio-individuality and so much that we don’t know, that ultimately, measuring your own markers and results should always be what takes precedence.

Insulin Resistance

With my MetS and NAFLD, it was obvious I had some level of insulin resistance. As part of my baseline testing I wanted to get a fasting insulin with other blood work but my new doctor at the time balked and said the NMR would give me an IR score already and that I shouldn’t get my fasting insulin measured. I was just getting started with my research and I didn’t argue, but I regret that now, since without fasting insulin you can’t calculate the most well known/effective IR formulas (or as mentioned, your NAFLD LFS). Also, it turns out that a fasting insulin test is only a $30 test even if you have to pay out-of-pocket (LC004333). You could also get it as part of a bundle (LC100039) that is only $8 more than an A1c alone. This really pissed me off and I’ve since switched doctors to someone who’s significantly less clueless/much more interested in improving metabolic health. (I did write a “Doctor’s Note” to try to persuade my now ex-Dr that fasting insulin is maybe one of the most important markers to measure considering how much of a leading indicator it is, and how key it is in early diagnosis of conditions that are affecting almost all Americans, and how cheap it is, but it seems like it didn’t quite hit home. Still, maybe you or your GP will find it useful).

Reference Before 1mo 9mo 1yr
Fasting Glucose <100mg/dL 100 101 99 89
Fasting Insulin <8mcU/mL 4.9 2.2
METS-IR <51.13 60.21 51.79 35.20 35.21
TyG1 <8.82 9.89 8.95 8.46 8.35
TC/HDL <5.0 7.32 4.88 4.71
TG/HDL <2.8 11.31 4.50 1.61 1.83
LP-IR <=45 50 32
HOMA-IR* 0.5-1.4 1.10 0.48
HOMA2-IR* <1.18 0.66 <0.38
QUICKI* >0.339 0.37 0.44
McAuley Index* <5.3 2.17 2.71

* Requires Fasting Glucose and Fasting Insulin

One interesting note is that a fasting insulin of 2.9 mcU/mL is the minimum valid value for calculating HOMA2-IR. The general takeaway is that my insulin sensitivity is probably very good these days.

Also as a bit of an aside, my Vitamin D at my 6mo check (physical with the new doctor) was the highest (36ng/mL) it’s been over the past 10 years (as low as 11ng/mL and never higher than 30ng/mL even with a 50000IU prescription supplementation regimen), despite not getting much sun over the winter/spring. Vitamin D deficiency is associated with MetS among other bad things, so just thought I’d throw that in there.

CVD Risk

Cardiovascular disease risk is one of the most contentious points about about a ketogenic diet, which from my research, seems to be mostly due to decades (and layers) of misconceptions.

I’ll start with the easy part – on the health consequences of eating fat and saturated fat. Recent meta-analysis shows that saturated fat consumption is not associated with all-cause or CHD mortality. Here’s another meta-analysis showing no difference in risk with saturated fat consumption, and yet another meta-analysis showing no significant risk differences for just about any combination of fat consumption. The 2015 US dietary guidelines actually remove the fat % recommendations completely (which might give you an idea of how long this can take to fix once these become enshrined political positions, considering that the evidence simply wasn’t there to begin with when the guidelines were introduced in 1977 and 1983). These are all robust studies from disparate teams and a wide range of intellectual camps (you’ll have to take my word for it, once you read enough papers and watch enough talks you get to know most of the researchers and teams). While dietary fats still have a bad rap in public opinion, on a scientific basis, I believe the debate is pretty well settled.

The second part, on the risks high cholesterol, particularly LDL-C really requires its own very long deep dive, which I’m going to elide at the moment (I’ve written thousands of words on this topic as I’ve collected and sorted through research, but will save that for another time). For those simply concerned about what the research says about risk, simply know that Metabolic Syndrome (n=4483, HR 5.45, +445% risk CVD mortality) and the closely related Deadly Quartet (n=6428, HR 3.95, +295% risk ACM) far outweighs even the best-case high LDL risk I could find (n=36375, HR 1.5, +50% risk CVD mortality). IMO, there’s some crazy cognitive dissonance going on when the latest ESC Congress issues guidelines for ever-lower LDL levels, but also the blockbuster trial at the event (which had a 26% RR reduction of primary endpoints, 17% reduction in ACM – better than statins) is for a drug (SGLT2i) that actually increases LDL. Anyway, a much longer (and more nuanced) discussion for another time…

In any case, like for the Virta Health cohort, my LDL did jump up a bit this year (but only slightly). Also like the Virta results, the rest of my CVD markers improved, and also, using the ASCVD risk calculator (with some fudging since it doesn’t give an answer below 40yo) my risk has more than halved from 3.1% to 1.3%, even with the higher LDL numbers (your LDL doesn’t actually affect the risk algorithm results except at cut-off, which should also tell you something about how important LDL is as a risk factor).

Much more importantly than the LDL-C, my TG went from awful to very good (<100mg/dL), and my HDL also went from very bad to pretty good. My high remnants (which are much more dangerous as far as subfractions go) have also dropped down to optimal levels as well. TG:HDL-C ratio, another better risk marker, also dramatically improved.

Reference Before 1mo 9mo 1yr 1yr Change
Total Cholesterol <200mg/dL 264 249 288 245 -7.2%
HDL-C >40mg/dL 35 34 59 52 +48.6%
LDL-C (calc) <130mg/dL 150 184 210 174 +16.0%
Remnant <20mg/dL 79 31 19 19 -74.7%
Triglyceride <150mg/dL 396 153 95 95 -76.0%
TG:HDL-C <2 11.3 4.5 1.61 1.83 -83.8%

Note: I did get an NMR (advanced lipid panel) at 1mo and 9mo, and furthermore, I got a second NMR and Spectracell LPP+ 2 weeks later (due to a blood draw faffle – I really wanted to match results from the same draw as advanced lipid panel results differ greatly) which I paid out of pocket for just to get some more insights into particle sizes, counts, etc (my particle counts are high but notably I shifted from an unhealthy Pattern/Type B to a healthy Type A on the NMR, and the LPP+ shows very low sdLDL-IV) but my main conclusion is that even beyond the meager hazard ratios, lipid testing is only vaguely useful in a ballpark sort of way because serum lipids are so mobile – in the two week between draws with no major lifestyle changes, controlling for fasting/draw times, there was a 14% TC difference, a 25% HDL-C difference, a 26% TG difference (causing a 41% TG:HDL-C ratio change), and a 20% LDL-C difference. Even from the same draw, the NMR and LPP+ had a 15% difference in LDL-C results (it’s also unclear whether these are direct, Friedwald, or modified-Friedwald numbers).

If you are going for advanced lipid testing, IMO the Spectracell LPP+, while expensive ($190 was the cheapest I could find online) and a PITA to order (you’ll also want a phlebotomist familiar with Spectracell procedures or they will mess up), is the superior test. It includes insulin, homocysteine, hsCRP, apoB, apoA1, Lp(a), and is more granular with LDL and HDL sizes, and is the only US clinical test I could find that gives you a lipid graph so you can look at the actual particle distribution (sample report). That being said, I think unless you’re going to do regular followups with it, or know exactly what/why you are looking for, it’s probably not worth it. In fact, for the same ballpark cost ($100-150 out of pocket), I’d recommend a low-dose or ultra-low-dose coronary artery calcium scan if you’re tracking cardiovascular health. You should ideally be getting a score of 0 (and if you are, just get one every 5 years – your 10-year CVD risk will be <1% irrespective of your lipid markers).

Oh also, I am APOE2/3, but have the PPARγ polymorphism that suggests I might want to have more MUFAs, but in terms of general cardiometabolic health (I don’t have good RHR numbers since I switched devices last year), I think this before and after comparison probably says more than the lipid panels do:

Fasting Stats

As mentioned, I started with an unintentional 24h fast, but basically aimed for a 16:8 (although often went 18-20 or longer simply due to not being that hungry), with an occasional longer fast about once a quarter (first a 2 day, then 3, with an almost 4 day being my longest). Here’s my Zero stats:

As an aside, while I made a lot of dietary changes this past year, I’d say that fasting was the one that really changed my relationship and perspective on food the most. Knowing you can decide when to eat (or not), and having a much better understanding your hunger and satiety signals is really like a superpower and an amazing tool to have in the “metabolic toolbox.” I’d highly recommend everyone to at least eventually give it a try. Before doing my research last year I had dismissed it as a dumb techbro trend, or simply not for me (since it just seemed impossible), but it’s not such a hard or crazy thing once you start (the first couple days really did suck if you don’t ease into it or fat adapt first).

Ketone Testing

For non-therapeutic purposes, I don’t believe that ketone testing is necessary (or even all that interesting) unless you’re set on eating a lot of weird food products or trying to do some troubleshooting (even then I think just glucose testing or a CGM or even elimination might be easier/better). Also, the measurements often don’t tell you quite what you might think it does or that what you really want (as ketone utilization and fat oxidization rates will change differentially and for different reasons). I did however try out many of the acetone and BHB testers when I attended Low Carb Denver 2019 (loads of interesting talks).

I wasn’t eating quite my regular routine while traveling, but after morning sessions at the end of a regular (16h) fast, I was at about 1.2mmol BHB and pushing out lots of acetone breath apparently. ¯\_(ツ)_/¯

Fitness

I started my first couple months without doing much physical activity (hard to do when you’re feeling like crap, which seems to be another one of the “move more eat less” mantra’s failings), but about a couple months in, after I started feeling better, I did decide I should work on some fitness goals, with the aim of building some functional strength.

The main thing I picked was to get back to doing pull ups. When I started, I was able to do 0 pull ups (YouTube revealed a series of progressions, starting with body-weight rows I could do), and I’m up to about 7 now on a good day. I also went from 8 pushups max to 30, and I’ve started trying out diamond, pike, and other more challenging pushup variations now. YouTube started recommending (it looks like you like pulling yourself so you might like) some climbing videos a while back, and after watching those for a while I ended up joining a bouldering gym now as well.

I’m pretty averse to cardio training, but it turns out when you’re carrying fifty less pounds, walking, hiking, and biking all becomes much easier, so I’ve noticed huge improvements in my excursions despite the lack of any cardio-focused workouts.

NSVs

I also kept a list of various “non-scale victories” so I don’t forget just how drastically my life has changed from a year ago:

  • I’ve had acne and breakouts since I was a teenager that just never went away but my skin immediately improved when I started keto/IF. I’m sure all the excess carbage was driving lots of inflammation. I still get the occasional pimple, but it’s nowhere near as bad as it was. It also seems to reliably return when I go off-plan, so it seems to work as a good early reminder that what you eat matters to your health.
  • A few weeks after starting I decided to take a hike up a nearby mountain (just a few thousand feet of elevation) and realized I didn’t have my inhaler with me, but that my lifelong exercise-induced asthma (independent of weight) just didn’t seem to be a problem anymore. (Some recent research possibly explaining why). This was a wholly unexpected bonus.
  • Also few months in, I realized that my sleep apnea was basically going away, and a few months later (using the SnoreLab app), I discovered that my snoring had pretty much gone away as well. This is probably primarily from weight loss, although lowered inflammation probably plays a role as well.
  • Obviously sugar rots your teeth, but one surprising (well, maybe not in retrospect) thing I noticed is that my teeth also gets noticeably less plaquey without carbs.
  • Not being hungry and being able to pick and choose what and when I want to eat is really liberating. While I’ve never really had much in terms of food compulsions or emotional eating, I do have a much better understanding, sensitivity, and control now than I did before. Most of it is was gained through the experience of fasting, but also having a much better intellectual understanding of my metabolism as well.
  • Oh, and while I still have my off days, in terms of what kicked off this past year for me: having more energy and less fatigue? Well, I’m happy to report that subjectively, I feel loads better than when I started.

In terms of some additional practical advice, setting and tracking goals, NSVs, and picking surrogate and subjective markers that I could track were really helpful, as was the approach of thinking about each intervention (lifestyle change) as an experiment and finding out what worked and was sustainable for me, and what wasn’t.

While I’m much healthier than I have been in the past 15 years or so, there’s still a lot I know that I can improve on (particularly with sleep hygiene and circadian health), and I do have some goals of continuing to optimize my body composition this coming year (getting to <0.5 waist circumference:height ratio, and maybe 15% body fat as a stretch), and this writeup serves as a bit of a marker of what I’ve learned this past year, but also I hope that it’s actually useful as a way to begin to share some of those learnings in an accessible way.

(Again, since my research is ongoing, I’d like to try to get this out into a less “fixed” way, but since there’s so much I’ve gathered, I may just start posting some shorter bits, like nutrition facts or something. Nutrition Fact: most nutrition facts are wrong!)

On Nutrition and Metabolism

Last year I started getting really interested in nutritional and metabolic health (doing a pretty deep dive starting with lots of medical talks, and subsequently reviewing tons of the primary research (all about that PubMed and Sci-Hub life)). Honestly, I’ve been working on a variation of this post for almost a year, but as my collected research kept growing, I continued to put this off. This is long overdue, so I’ll just start off publishing some stuff and go from there (eventually, I will be shifting most of this to a platform that allows me to better update/revise things). A few of the things I’ve learned:

I’ll save the detailed look at my personal results for another post, but I’ll summarize a bit of my path. Early on, I ended up stumbling on an interview with Jason Fung, which seemed to make a lot of sense. Now, not being a complete nutritional nitwit (just a pretty average one), I had seen some of Robert Lustig’s talks and Gary Taube’s writing previously on how terrible sugar was for you, but despite cutting out sugary sodas, or doing bouts of paleo-ish meal plans, it never really stuck. However, as I dug more, I ended up finding that despite my original claim of not being a nutritional nitwit, that I actually was – most of the nutritional common wisdom I thought I knew was being contradicted. I’ve curated a list of some of the most interesting YouTube talks/presentations I’ve come across. These are all well sourced, and starts first w/ some more general overviews of the hormonal mechanisms of metabolism etc, and then moves into deeper topics from there:

If you’re like me, you’re probably (rightly) skeptical of using YT talks/presentations as primary sources, especially in a field like nutritional science, where snake oil and bad science is the norm. So I started spelunking through the sources, and after collecting a few dozen, realize that I need a better research manager and downloaded Zotero for the first time in about a decade (it’s better than it was back then, a little worse recently as many of the integrations/plugins are now broken). I also started writing my own custom exporter, but luckily, I found a nice one called zotsite that works great, and I’ve written a cronjob for it now.

I’ve embedded an export of the nutrition sources I’ve collected below, but you can also access it directly at https://randomfoo.net/nutrition/ – it’s about 3500 sources at the moment (abstracts/articles/studies/reviews etc). I’m still adding onto this (turns out, tracking down/reading nutrition/medical research has been a bit of a full time hobby this past year), but I hope to make a second pass where I do a better job organizing these soon, adding notes, and getting any missing full PDFs through sci-hub or academic institution access. For the less ambitious/more sane, I have also curated a few reviews/overviews that I feel are the most compelling/interesting things I’ve stumbled across: https://randomfoo.net/nutrition-bestof/

As an aside: early on I stumbled on SCI-FIT which has also been collecting references, but mine is sourced almost entirely independently – again, when I get a chance, I’d like to sit down and cross-reference (I feel like being able to properly annotate/narrativize all these resources is a real weakness w/ Zotero, though).

As I mentioned, my plan is to try to publish some writeups into a better platform at some point, but in the meantime, I’ll probably be a little less precious and post some stuff on the blog as well.