Category: Uncategorized

Ketamine Part 1: Dosing

I’m currently investigating ketamine, with the goal of assessing the risks of chronic use. For reasons I will get into in the real post, this is going to rely mostly on in vitro data, at least for neural damage, which means I need a way to translate real-world dosages into the concentration of ketamine in the brain. This post gets into those details so I can use it as a reference post for the one you actually want to read, and invite correction early from the three of you who read it all the way through.

If you’re excited for the main post (or for some inexplicable reason, this post), you can help me out by tax-deductibly donating to support it, or joining my (not tax deductible) Patreon. 

Cliff Notes

What I care about for purposes of the next post is the concentration of ketamine in the brain. Unfortunately, ethics committees really hate when you set up a tap in people’s skulls and draw a fresh sample every five minutes. The best you can do is a lumbar puncture, which draws cerebrospinal fluid (CSF) from the spine. Unfortunately, spinal fluid and cranial fluid concentrations are not interchangeable. Tentatively, brain concentrations of most substances in this class tend to be lower, so we can still use CSF concentrations as a rough upper bound. 

Most long-term, medically supervised ketamine users use a  lozenge or nasal spray.. However, the only paper that measures ketamine in the cerebrospinal fluid delivered the ketamine by IV. Therefore, to have any hope of contextualizing the in vitro data, I need to translate from ketamine dose (nasal or lozenge) (measured in either straight milligrams, or milligrams per kilogram of body weight) -> plasma concentration -> CSF concentration (also measured in nano- or micro-grams of ketamine per milliliter of fluid). 

There are two metrics we might consider when comparing doses of drugs. The first is peak concentration, which is the highest dose of ketamine your brain experiences at any point. The second is the total cumulative exposure (AKA area under the curve or AUC). These unfortunately have pretty different translations from IV to sublingual doses, and unfortunately I saw no evidence about which of these was more important. I report both just in case. 

Assuming (incorrectly) a linear response, 1 mg of ketamine taken sublingually (under the tongue) or buccally (in the cheek) leads to a mean peak concentration in plasma (blood) of 0.83 – 2.8 ng/ml and a mean total dose (area under curve, AUC) of 1.8-7.4 ng/ml.

1 mg of ketamine taken via a nasal spray leads to a mean peak in plasma of 1.2 ng/ml and a mean total dose of 3 ng*h/ml (based on a single study).

Peak CSF concentration was 37% of plasma concentration, and came 80 minutes later. Total CSF dose was 92% of total plasma dose, indicating almost total diffusion into CSF, eventually. Both findings are from a single study.  

Combining these two results, 1mg sublingual ketamine leads to a median measured peak brain concentration of < 1.1 ng/ml and a total brain dose of < 6.7ng*h/ml. 

On the other hand, 1mg nasal ketamine leads to a median peak concentration of < 0.45 ng/ml and median measured total brain dose of < 2.7ng*h/ml.

The rest of the post goes more deeply into the findings and methodology of individual papers. 

Context and Caveats

Like most 3D molecules, ketamine exists in two forms that are mirror images of each other (called enantiomers). One version is sold under the name eskatamine; the other is not commercially available on its own). Some papers administered only esketamine, some both separately, and some both together (a racemic mix). The pharmacokinetics of these aren’t different enough to be worth distinguishing for my purposes. 

My list of papers is cribbed from Undermind.AI. I occasionally found papers via references, but when I checked those papers were always on Undermind’s list as well. I also looked on Perplexity, but it found only a subset of the papers on Undermind (Perplexity has tragically enshittified over the last few months). 

I treat the translation of dose to concentration in the body as linear. This is almost certainly false, but more likely to be an overestimate. 

I did not even attempt to combine results in some sort of weighted fashion, which would have incorrectly combined subtly different mechanisms of delivery. The numbers you see above are the range of values I saw. 

“Peak” concentration always means “among times samples were taken”, not actual peak.

I mentioned that I assume a linear dose-concentration curve to ketamine (meaning that if you double the amount of ketamine you take, you get double the plasma or CSF concentration). Linear sounds like a nice safe assumption, but it can go wrong in both directions. Your body may absorb a substance less efficiently as you take more, leading to an asymptotic curve. Or your body may only be able to clear so much of a substance at a time, so an increased dose has an outsized impact on concentration. In the case of ketamine there’s very mild evidence that the curve is sublinear, which makes treating it as linear an overestimate. That’s the direction I want to err on, so I went with linear. 

Translating nasal/sublingual doses to plasma concentration

To find out what dose translates to what plasma concentration, we need to give subjects ketamine through whatever route of administration, take repeated blood samples, and measure the concentration of ketamine in that blood. My ideal paper had the following traits:

  1. Studied adult humans.
  2. Delivered ketamine nasally, sublingually, or buccally.
  3. Sampled plasma at least every 10 minutes for the first hour, ideally more often. Only a handful of papers met this criteria, so I had to give a little on this criteria. 
  4. Tracked concentration and total dose received. 

Combining the results below, and assuming (incorrectly) a linear response I get the following results:

  •  1 mg of ketamine taken sublingually or buccally leads to a mean peak concentration in plasma (blood) of 0.83 – 2.8 ng/ml and a mean total dose (area under curve, AUC) of 1.8-7.4 ng/ml
  • 1 mg of ketamine taken nasally leads to a mean peak in plasma of 1.2 ng/ml and a mean total dose of 3 ng*h/ml (based on a single study).

S-Ketamine Oral Thin Film—Part 1: Population Pharmacokinetics of S-Ketamine, S-Norketamine and S-Hydroxynorketamine

This paper was definitely selling something and that thing is an “oral thin film” delivery mechanism. 

This study design is a little complicated. N=15 people were given one and two sublingual films (50mg S-ketamine each) on two separate occasions (so everyone received 150mg total, over two doses), and ordered not to swallow for 10 minutes (I have my doubts). Another 5 were given the same doses, but buccally (in the cheek). Buccal and sublingual had indistinguishable pharmacokinetics (at their tiny sample sizes) so we’ll treat them as interchangable from now on. Subjects had blood samples taken at t = 0 (= oral thin film placement) 5, 10, 20, 40, 60, 90, 120, 180, 240, 300, 360 minutes, after which they were given 20mg IV ketamine over 20 minutes, with new samples taken at 2, 4, 10, 15, 20, 30, 40, 60, 75, 90, and 120 min.

Figure 1. Mean measured plasma concentrations following application of the 50 and 100 mg S-ketamine oral thin film (OTF): (A) S-ketamine, (B) S-norketamine, and (C) S-hydroxynorketamine. Individual concentrations are given in panels (D–F) for the 50 mg oral thin film and (G–I) for the 100 mg oral thin film. In black the results of placement below the tongue, in red buccal placement. The OTF was administered at t = 0 min for 10 min (green bars); at t = 360 min, an intravenous dose of 20 mg S-ketamine was administered over 20 min (light orange bars).

There’s a few key points to take from this graph. First, sublingual (under the tongue) and buccal (between cheek and gum) are indistinguishable, at least at this sample size. Second, the 100mg sublingual dose doesn’t have near double peak concentration or AUC of the 50mg dose, although this is not statistically significant. You can see the exact numbers in table 1.

(CMAX = peak concentration, Tmax = time to peak concentration, S-norketamine = a psychoactive metabolite of ketamine, S-hydroxynorketamine=an inactive metabolite of ketamine)

Given that, we have, for peak concentration

 50 mg = 96ng/ml -> 1mg = 1.9ng/ml

100 mg = 144ng/ml -> 1mg = 1.4ng/ml

Which makes a linear dose-concentration relationship look unlikely, although at these sample sizes the difference isn’t significant. 

For AUC:

50mg = 8362 ng*min/ml     -> 1mg = 170 ng*min/ml

100mg = 13,347 ng*min/ml -> 1mg =  130ng*min/ml

Plasma concentration profiles of ketamine and norketamine after administration of various ketamine preparations to healthy Japanese volunteers

This is my favorite paper, looking at no fewer than 5 different methods of delivery. 

This isn’t the primary take-home, but because they injected racemic ketamine but measured the two enantiomers (S- and R- ketamine) we can see that their pharmacokinetics are close enough that I can ignore the difference between them, and use S-ketamine data to inform estimates of racemic ketamine. For the results below I averaged the S- and R- results together

The only routes of administration I care about from this list are sublingual tablet and nasal spray.

For peak concentration, we see:

50 mg sublingual = (42.6+40.4)/2 ng/ml -> 1 mg = 0.83ng/ml

25mg nasal spray = (29.4+29.3)/2 ng/ml  -> 1 mg = 1.2 ng/ml

For area under the curve, we see:

50 mg sublingual = (108.8+110.5)/2 ng*h/ml -> 1 mg = 2.2ng*h/ml = 130 ng*min/ml

25mg nasal spray = (76.8+72.7)/2 ng*h/ml -> 1 mg = 3 ng*h/ml = 180 ng*min/ml

The absolute bioavailability of racemic ketamine from a novel sublingual formulation

You know the drill: 8 subjects were given 25mg sublingual or 10mg IV ketamine

This paper uses geometric mean (the nth root of n numbers multiplied together) rather than arithmetic (sum of numbers divided by their count), so is not directly comparable to the other studies. But roughly, for peak concentration (Cmax) of the sublingual dose: 

25 mg ketamine  = 71.1 ng/ml -> 1mg = 2.8 ng/ml

And for total dose (AUC)

25 mg ketamine = 184.6 ng*h/ml -> 1 mg ketamine = 7.4 ng*h/ml = 443 ng*min/ml

Why I’m ignoring ketamine’s chirality

Combined Recirculatory-compartmental Population Pharmacokinetic Modeling of Arterial and Venous Plasma S(+) and R(–) Ketamine Concentrations

10 healthy male subjects aged 24 to 62 yr, weighing 68 to 92 kg, were administered approximately 7 mg of S(+) or R(–) ketamine via a 30-min constant rate IV infusion on two occasions at least 3 days apart. Radial artery and arm vein samples were drawn at 0, 5, 10, 15, 20, 25, 30, 40, 50, 60, 120, 180, and 300 min after the start of the S(+) ketamine infusion and at 0, 5, 10, 15, 20, 25, 30, 36, 43, 50, 180, 300, and 420 min after the start of the R(–) ketamine infusion.

Red = arterial blood, Blue = venous blood

As you can see, arterial and venous blood are quite different, but S- and R- ketamine are close enough for government work. 

Translating plasma concentrations to cerebrospinal fluid concentrations

Cerebrospinal fluid exploratory proteomics and ketamine metabolite pharmacokinetics in human volunteers after ketamine infusion

These heroes gave a dose of ketamine via IV, then monitored both plasma concentration and cerebrospinal fluid. 

Peak CSF concentration was 37% of plasma concentration, and came 80 minutes later.

Total CSF dose was 92% of total plasma dose, indicating almost total diffusion into CSF, eventually. 

Papers I Want to Complain About

Bioavailability, Pharmacokinetics, and Analgesic Activity of Ketamine in Humans

I mention this paper only to explain why I am mad at it. This 1981 study took beautiful measurements of pain sensitivity as well as plasma concentration of ketamine, and then didn’t publish any of them. They used only intramuscular injection and oral solution, which doesn’t allow me to translate to the more standard IV concentration. Also oral is a terrible route for ketamine, your body processes most of it before it hits your system. 

Population pharmacokinetics of S-ketamine and norketamine in healthy volunteers after intravenous and oral dosing

For reasons I don’t understand, this paper studies IV alone versus IV + oral ketamine together. Also not useful for our purposes, except for establishing that ketamine taken orally (as in, a pill you swallow and absorb through the digestive track) isn’t very good.

Development of a sublingual/oral formulation of ketamine for use in neuropathic pain

This paper measured concentration in arterial blood, where every other paper used venous blood. One paper that measured both showed that they were shockingly different. I could attempt to translate from arterial to venous concentrations, but the paper also uses an unpopular delivery mechanism so I haven’t bothered. 

Acknowledgements

Thanks to R. Craig Van Nostrand for statistical and paper-reading help, Anonymous Weirdo for many discussions on pharmacokinetics, Ozy Brennan and Justis Mills for editing, and my Patreon patrons and Timothy Telleen-Lawton for financial support. 

What do you Want out of Literature Reviews?

Tl;dr how can I improve my literature-review based posts?

I write a fair number of blog posts that present the data from scientific papers. There’s a balancing act to this- too much detail and people bounce off, too little and I’m misleading people. I don’t even think I’m on the pareto frontier of this- probably I could get better at which details I share and how I share them, to improve readability and rigor at the same time. This post is a little bit my thoughts on the matter and a lot of requests for input from readers- what do you actually want to see? What are examples of doing this well? Any requests for me personally?

I ask for audience feedback explicitly at a few points, but please don’t limit yourself to those. I’m interested in all suggestions and examples .

Context

If you’re just tuning in, here’s a few examples of posts I mean:

These are all posts where the bulk of the text is describing individual papers, but I have some conclusion I would like the reader to consider.

My motivating example is my project on the risks of long term ketamine use. Right now I’m working on a technical post on how to translate doses consumed by humans into concentrations in the cerebro spinal fluid (draft ), which is reference material for a post people might actually read.

Principles

Epistemic Legibility

My goal is always to present information to people they can interpret for themselves, rather than rely on my summaries. My proudest moment as a researcher was when I was hired by a couple to investigate a particular risk during pregnancy, and due to different risk tolerances they came to opposite conclusions from the same model. To accomplish this, I need to give people the relevant details, in as digestible a format as possible. 

What helps you connect with scientific posts? Some ideas:

  1. My search process
  2. My selection criteria
  3. My conclusions
  4. Motivation
  5. Your ideas here

Then there’s the papers themselves. For the ketamine dosing post, there’s  <20, maybe <10 papers in the world that meet my criteria for inclusion, so it’s feasible to include details on each of them. But which details help people understand, and which aren’t worth the attention they cost? 

Some paper details I could include:

  1. Sample size. 
  2. Experimental set up
  3. Key graphs
  4. Description of results
    1. Averages, or with confidence intervals?
  5. My criticisms
  6. Your ideas here

Readability

All else equal, it’s better for a post to take less energy to read than more. Actually that’s not quite true- for posts that would be especially costly if I’m wrong or I expect to be misinterpreted, I will often bury the conclusion, like I did in this post on binge drinking. But we’ll ignore that for now and focus on the much more common case of wanting posts to be as accessible as possible. 

Detail and readability often trade off against each other, but what I’m looking for here is ways to improve readability while holding detail constant. Some ideas I have:

  1. Formatting, probably? Seems like it should help but I don’t know what specifically.
  2. Humor
    1. Unfortunately the easiest way to do this is to make fun of bad studies, which gets repetitive. 
  3. Explaining relevance to the main question
  4. Make the goal/main question clear
  5. Pictures? I’m unconvinced of this
  6. Your ideas here

Audience

Everyone says to have an audience in mind. There are two major audiences and two minor.

People who are Interested in the Opinions of Uncredentialed Internet Weirdos

This is a tautology, but refers to something much more specific than it looks at first. People who are interested in hearing uncredentialed randos describe and interpret academic papers have a lot more in common than just their willingness to do that. 

Some other traits they share: 

  1. Statistical literacy
  2. Desire for interpretations to be quantified
  3. Higher risk tolerance
  4. Your ideas here
  5. Interested in the specific topic- such as ketamine use, or long covid risk.
    1. It’s rare I want to convince people that they should be in a topic when they weren’t before. 
  6. Your ideas here

Fishing for Corrections

Some posts aren’t meant to be read widely. They’re meant to be a reference in other, more readable post, and to invite corrections from the three people who will read them. This is my intention for the ketamine dosage translation post– it’ll be lucky if it’s read by 10 people when it’s first published, but one of those might be quite useful. 

The primary benefit to me is catching mistakes before I write an entire 10,000 word post with information that could hurt people I’m wrong that depends on the false conclusion. It also feels virtuous to explain my reasoning in detail, even if nothing specifically good comes from it.  

Myself

Writing lets me think through things. I always budget at least as much time for the “writing” phase of a project as research, because there are gaps I don’t notice until I start writing them down. 

I’m interested in how this works for other people- have you found ways to improve your writing for yourself?

Potential clients

I make my living as a freelance researcher, with my blog being the major evidence I am good at this. I’d like clients who read my posts to be able to assess my skill level, even if they’re not interested in the topic and have no context. 

Conclusion, such as it is

I would like to get better at writing the kind of posts I write. In particular, I’d like to get better at conveying relevant information, in ways that take as little work from the reader as possible, but no less than that. I will be very grateful for feedback that helps me improve or that helps me create a framework by which I can improve. I expect that to mostly be critical, but compliments are helpful too- I’d hate to throw out the baby with the bathwater.

Ivan Gayton: A Right and a Duty

In this episode of the podcast I talk with Ivan Gayton, former mission head at Doctors Without Borders and currently obsessed with placing mapping technology in the hands of the developing world.

If you prefer the written word, you can see the transcript here.

Some highlights:

  • How Ivan thinks about being fractionally responsible for saving the lives of hundreds of thousands of people, but pretty directly responsible for the killing of 12 (utilitarian deontologicalism, I think?).
  • Why humanitarianism is a right and a duty, but development is merely nice (humanitarianism is countering the intervention of another human being).
  • Casually devastating criticism of various international aid agencies (Tanzania is where aid workers go to retire while still drawing a check).
  • Why accurate open maps are instrumental to humanitarian and development goals in developing countries (contact tracing during epidemics, aid distribution, municipal services, utilities)
  • How you can contribute to mapping with money or programming talent (especially mobile, Unity or other 3D mapping engines, FPGA, AI, especially for vision, and blockchain). Programming positions are potentially paid, although not at competitive rates.

Links and other references:

  • Ivan mentions starting his mapping project with Ping. This refers to Ka-Ping Yee, another former co-worker of mine.
  • The organization Ivan works with most directly is Humanitarian Open Street Maps team.
  • If you’re interested in working with him you can reach him at [firstname].[lastname]@hotosm.org.
  • Missing Maps Project
  • Ivan mentions a blog post with the title “Free Software is Racial Justice”. That can be found here.

Bandwidth Rules Everything Around Me: Oliver Habryka on OpenPhil and GoodVentures

In this episode of our podcast, Timothy Telleen-Lawton and I talk to Oliver Habryka of Lightcone Infrastructure about his thoughts on the Open Philanthropy Project, which he believes has become stifled by the PR demands of its primary funder, Good Ventures.

Oliver’s main claim is that around mid 2023 or early 2024, Good Ventures founder Dustin Moskovitz became more concerned about his reputation, and this put a straight jacket over what Open Phil could fund. Moreover it was not enough for a project to be good and pose low reputational risk; it had to be obviously low reputational risk, because OP employees didn’t have enough communication with Good Ventures to pitch exceptions.  According to Habryka.

That’s a big caveat. This podcast is pretty one sided, which none of us are happy about (Habryka included). We of course invited OpenPhil to send a representative to record their own episode, but they declined (they did send a written response to this episode, which is linked below and read at end of the episode). If anyone out there wants to asynchronously argue with Habryka on a separate episode, we’d love to hear from you. 

Transcript available here.

Links from the episode:

An Update From Good Ventures (note: Dustin has deleted his account and his comments are listed as anonymous, but are not the only anonymous)

CEA announcing the sale of Wytham Abbey

OpenPhli career page

Job reporting to Amy WL

Zach’s “this is false”

Luke Muelhauser on GV not funding right of center work

Will MacAskill on decentralization and EA

Alexander Berger regrets the Wytham Abbey grant

Single Chan-Zuckerberg employee demanding resignation over failure to moderate Trump posts on Facebook

Letter from 70+ CZ employees asking for more DEI within Chan Zuckerberg Initiative.

OpenPhil’s response

Journal of Null Results: EZMelt sublingual vitamins

4 months ago I described my success curing my hypothyroidism by gargling liquid iodine, when iodine pills had failed. The good news is that the cure has held– my thyroid numbers continue to be in the desirable range. 

The bad news is I’ve failed to replicate this success with a multivitamin. Shortly after the thyroid post I was handed a perfect opportunity to put sublingual vitamins to the test when my doctor took me off all my oral vitamins to give my gut a rest. I had already started on EZMelt Multivitamin + Iron (2x standard dosing every other day, because I absorb iron better that way), but now we’d removed all potential assistance (“except food, right?” no. My gut has never been good at extracting vitamins from food except right after I discovered Boswelia. Mold Winter rolled back those gains).

I recently got my nutrition test results back and they suck. I can’t prove I wouldn’t have been even worse off without these vitamins, but there’s a profound absence of positive evidence. However the issue could just be these particular vitamins; after a break I’m now trying Feroglobin, which is a thick liquid iron supplement with a smattering of other vitamins. It’s not intended to be taken sublingually but I don’t live by their rules, man.

Between getting the results and publishing this post I made a market on Manifold, asking whether the EZMelts would work. The market was trading just under 50% “no, not helpful” for most of the week, but in the final hours fluctuated between 30-40% “no”. Seems like a very mild victory for prediction markets. 

I’ve created a similar market for Feroglobin here. This run is not going to be quite as clean- my doctor put me back on oral vitamins, plus I finally found a place that does IV nutrition. So this will be more of a best guess, probably resolved as a probability rather than flat Yes/No. 

Predict the impact of sublingual vitamins

4 months ago I shared that I was taking sublingual vitamins and would test their effect on my nutrition in 2025. This ended up being an unusually good time to test because my stomach was struggling and my doctor took me off almost all vitamins, so the sublinguals were my major non-food source (and I’ve been never good at extracting vitamins from food). I now have the “after” test results. I will announce results in 8 days- but before then, you can bet on Manifold. Will I judge my nutrition results to have been noticeably improved over the previous results?

Austin Chen on Winning, Risk-Taking, and FTX

Timothy and I have recorded a new episode of our podcast with Austin Chen of Manifund (formerly of Manifold, behind the scenes at Manifest).

The start of the conversation was contrasting each of our North Stars- Winning (Austin), Truthseeking (me), and Flow (Timothy), but I think the actual theme might be “what is an acceptable amount of risk taking?” We eventually got into a discussion of Sam Bankman-Fried, where Austin very bravely shared his position that SBF has been unwisely demonized and should be “freed and put back to work”. He by no means convinced me or Timothy of this, but I deeply appreciate the chance for a public debate.

Episode:

Transcript (this time with filler words removed by AI)

Editing policy: we allow guests (and hosts) to redact things they said, on the theory that this is no worse than not saying them in the first place. We aspire but don’t guarantee to note serious redactions in the recording. I also edit for interest and time. 

Feedback loops for exercise (VO2Max)

The perfect exercise doesn’t exist. The good-enough exercise is anything you do regularly without injuring yourself. But maybe you want more than good enough. One place you could look for insight is studies on how 20 college sophomores responded to a particular 4 week exercise program, but you will be looking for a long time. What you really need are metrics that help you fine tune your own exercise program.

VO2max (a measure of how hard you are capable of performing cardio) is a promising metric for fine tuning your workout plan. It is meaningful (1 additional point in VO2max, which is 20 to 35% of a standard deviation in the unathletic, is correlated with 10% lower annual all-cause mortality), responsive (studies find exercise newbies can see gains in 6 weeks), and easy to approximate (using two numbers from your fitbit). 

In this post I’m going to cover the basics of VO2max, why I estimate such a high return to improvements, and what kind of exercise can raise it the fastest.

What is VO2max?

A person’s VO₂ max is the maximum volume of oxygen they can consume in one minute. Higher VO2max lets you cardio more intensely, and is correlated with better health and longer lifespan (we’ll quantify this later). This is 100% of what you need to know, the rest is thrown in for fun. 

VO2max is measured in ml O2/kg bodyweight/minute. It is sometimes given in Metabolic Equivalents (METs). 1 MET = 3.5ml O2/kg of bodyweight/minute. This is approximately your metabolic expenditure while sitting still. 

What physically causes increase in VO2max? It’s a mix of many factors:

  1. Strengthened heart allows you to pump blood faster
  2. Improved lung capacity, which breaks down to
    1. Expansion of the chest cavity, in part due to strengthening of the diaphragm and rib muscles.
    2. Recruitment of new alveoli (the features in your lungs that exchange carbon dioxide and oxygen) 

(source)

  1. Improved lung elasticity
  2. Production of a surfactant that maintains alveoli in fighting form 
  1. Increased mitochondrial activity allows cells (especially muscle cells) to use more oxygen
  2. More blood to carry the oxygen
  3. New capillaries grow to deliver more blood to your muscles

What can induce these changes? Exercise, especially high intensity interval training. We’ll talk more about that in a bit. 

Why do I care about VO2Max?

Obligatory boring part: VO2max is a crude measurement whose impact depends on many factors blah blah blah blah

Shocking headline: 1 MET (aka 3.5 points VO2max ) = 10% reduction in relative risk of all-cause mortality. So if your normal risk of death is 1%, gaining one MET would lower it to 0.9%).

The catch: that meta-analysis averaged together results from multiple studies of very different durations. “That’s okay, they could correct for that, at least crudely” you might be saying to yourself, in which case, congratulations on being better at meta-analysis than these authors, who AFAICT dumped every study into a bag and shook it. 

More realistic, yet more shocking headline: an increase of 1 point in VO2max is correlated with 10% lower annual all-cause mortality. 

This is based on the largest study in the meta-analysis, Kokkinos et al. Important facts from this study include: 

  1. In male veterans, going from low fitness to moderate fitness (defined below) lowered risk of dying by 40%. This was shockingly consistent across age groups, and whether you considered a 5 year or 10 year period. Getting to a high fitness level dropped their mortality rate by another 30%.
  2. I too am wondering why the % change in risk of death doesn’t get larger when you consider a longer period of time. 
    1. The middle (“threshold”) range for 4 age categories were 8 to 9, 7 to 8, 6 to 7, and 5 to 6 METs for <50, 50 to 59, 60 to 69, and ≥70 years, respectively. Another source gives average MET for those categories (substituting 40-50 for <50 and 70-80 for >70)  as 10, 8.6, 7.3, and 6.1, so the threshold starts 1-2 points lower than average and they converge by your 70s.
  4. Low fitness is the range between the floor of the threshold, and 2 METs lower than that, moderate fitness is the ceiling of the threshold plus 2 METs. If distribution within buckets were uniform, we could treat moving from low fitness to moderate fitness as an increase of 2 METs. If you assume a normal distribution centered around the threshold, it’s somewhat smaller than that.I went with the latter assumption, but not very rigorously.

Caveats

VO2max is measured per kg of total body weight, not lean weight. That means that if you lost 10% of your bodyweight via liposuction but otherwise stayed exactly the same, your VO2max would rise by 1/0.9. This makes VO2max a partial proxy for weight. However the relationship between weight and health, and weight and exercise, is much more complicated than is typically acknowledged. 

VO2 is also a proxy for exercise. Right now we don’t have enough information to say that increased VO2, or increased aveoli surfactant, increases lifespan or is merely downstream of exercise that does some other helpful thing. 

I’m going to ignore both of these for now, but when you’re doing your own math you should not add effects from potential weight loss, because that might be double counting.

Exercise science sucks. Lifespan is affected by 1000 different factors, none of which scientists can properly control. Lots of researchers have their bottom line already written.

While we’re at it, I should note that I haven’t done deep investigations on any other metrics. Very early in the process I considered others, and VO2max won due to a combination of being promising and easy to measure at home. I don’t have the information to say if VO2max is more or less accurate than other metrics.

How can I measure my VO2Max?

(note: this section is based primarily off of Client’s research, not mine)

The official way involves a mask and measuring equipment and 20 minutes of excruciatingly intense exercise. This is technically the most accurate, but only if it’s set up properly, and is expensive. If you’d like to trade accuracy for ease, use this formula

VO2max ≈ (HRmax/HRrest) ∗ magic_constant

If you would like to get a number without understanding it, you can enter your heart rate in this spreadsheet. If you would like to learn about the magic constant, I’ve defined the terms below. 

  • HRRest is your lowest heart rate when measured first thing in the morning, or ask your friendly neighborhood wearable. 
  • HRMax is your heart rate after exercising at ever increasing intensity until you cannot stand it. If you don’t know this, you can use 208 − 0.7 ∗ age. However if you do so you’ll miss any gains that come from increasing your maximum heart rate, which I’d expect to be at least half. 
  • magic_constant = 17.27 − 0.08 ∗ age − 0.59 ∗ BMI_category − 0.40 ∗ smoking_status + 0.14 ∗ TPA
  • BMI_category =
    • normal: 0
    • overweight: 1
    • obese: 2
  • smoking_status:
    • never: 0
    • former: 1
    • current: 2
  • TPA (total physical activity) =
    • moderate: 2 (< 43 MET hours / day)
    • active: 1 (43 – 50 MET hours / day)
    • highly active: 0 (> 50 MET hours / day)
    • This definition is circular, because MET hours is a function of hours exercised * exertion level. A decent level of physical fitness will burn 10 MET per hour of very intense exercise. 

You may be tempted to use wearable-calculated VO2Max.  This is a bad idea because your device has no way to separately track how hard you are working from how hard your heart is beating (Apple Watch attempts this, but simplifies things by assuming all exercise is running on a flat surface).

What are you aiming for?  Here is a convenient chart (source). This is measured in ml/kg/min, not METs.

How can I raise my VO2Max?

The best exercise is still the one you do consistently without injuring yourself. Optimization within that is for people who have many choices they enjoy, or who don’t enjoy any but can nonetheless force themselves to work out reliably. 

The next best exercises appear to be rich people sports (lifespan wise, you’re better off being an amateur raquetballer than an olympic marathoner, despite racquetball’s barely-above-average VO2max). I didn’t find numbers for polo players but I assume they’re stunning. We’re going to ignore these findings even though the papers claim to have controlled for income. 

After that, you have two choices: high intensity interval training (HIIT), and using cross country skiing as your regular mode of transportation. 

Why those two? No one has proven an answer, but my wild ass speculation is that you raise VO2max by proving to your body that your existing VO2max is insufficient. You do this by operating at capacity. Since it’s impossible to operate at peak capacity for very long, this can be done in the form of interval training, or by working at near-peak capacity for so long that it uses up your reserves. Or so I surmise.

Back to the literature: within interval training, the number one most important property is still that you do it at all, followed by how much you do it, with one possible cheat. According to this meta-analysis even short interval, low volume, low calendar-time was beneficial, but in order to beat moderate-intensity exercise you need to work a little harder: intervals of >2 minutes, total time of >15 minutes, and at least 4 weeks (number of times per week was not specified, but in other papers it was 2-3).

What’s the cheat? Repeated Sprint Training (RST), in which you go absolutely balls out for 10 seconds and then take a nice 2-4 minute gentle stroll. I love RST because there’s a little bit of lag between working very hard and being miserable, and that lag is longer than the interval. By the time the misery catches up with me I’ve already stopped trying. So I’d really like to believe this, but ShortIT (10-30 second intervals) scored poorly relative to longer intervals, so there’s either some sort of horseshoe effect or the success of RST is a mirage. 

Here is the full chart from that paper, which is beautiful except for its absolutely incomprehensible labels. Translations below. 

Within Training Periods (how many weeks people exercised according to the plan), the options are short (<= 4 weeks), medium, and long term (>=12 weeks).

Within Session Volume, the options are low (<=4 cumulative minutes under load), medium, and high (>=16 minutes of work). Please join me in a moment of annoyance that  L sometimes mean smallest and sometimes biggest.

Within Work Intervals (duration of a single intense bout), the options are short, medium, long, very very short (SIT) (10-30s) and itty bitty (RST) (10s).

MICT stands for “moderate intensity cardio training”, aka non-HIIT exercise. CON stands for control. The longer you go (in calendar time) the less of an advantage HIIT has over MICT, which suggests they are both approaching the same asymptote, HIIT just gets there faster. 

SMD stands for “standard mean difference”, which is the difference of the means of the treatment and control groups, divided by the standard deviation. The size of SMD differs between the treatment groups, but you can round it to 3 ml O2/kg body weight/person. 

What if I already exercise?

In one study, even Olympic athletes were able to raise VO2max via HIIT training (albeit slower than couch potatoes). If you’re not specifically targeting peak capacity, you can probably improve it. However I believe this asymptotes, so if you’re already doing HIIT in particular there may not be much gains left on the table. The client who commissioned this research was a hard-core pilates practitioner and he did not find HIIT to increase his VO2. 

Next Steps

Iamnotadoctor, nor do I hold any other relevant qualifications. But if you’re full of inspiration to follow up on this, here is my suggested plan:

  1. Estimate your VO2Max as described above, or use the spreadsheet.
  2. Identify a form of exercise that is highly accessible to you, that can be done safely at very high intensity.
    1. The more of your body it uses the better, but prioritize lowering obstacles. if your office only has an exercise bike that’s better than needing to travel to an elliptical, even though the elliptical uses your arms and the bike doesn’t.
  3. If you’re new to exercise, spend a few sessions playing around on your activity of choice, to get a sense of where your limits are.
  4. If you believe the research on RST (10 seconds of peak exertion followed by 3 minutes of barely moving. If your environment is cold enough you shouldn’t even sweat), do that. 
  5. If you don’t believe the research on RST, gradually increase your time under intensity until you reach 4 non-continuous minutes under intense load.
    1. If your intense intervals are longer than 2 minutes they’re probably not actually peak intensity, so you should have at least 2. 
    2. Especially at first, aim for sustainability rather than peak achievement. If going 20% slower is the difference between quitting or sticking through it, slower is obviously the correct choice. You can build up over time. 
  6. After 6 weeks, estimate VO2max again. The meta-analysis described above suggests you can expect at least 1 MET (3.5 ml O2/kg body weight/min) over 6 weeks. 

Thanks to anonymous client and my Patreon patrons for supporting this post.

Can we rescue Effective Altruism?

Last year Timothy Telleen-Lawton and I recorded a podcast episode talking about why I quit Effective Altruism and thought he should too. This week we have a new episode, talking about what he sees in Effective Altruism and the start of a road map for rescuing it. 

Audio recording

Transcript

Thanks to everyone who listened to the last one, and especially our Manifund donors, my Patreon patrons, and the EAIF for funding our work.