Economics professor at University of Oklahoma


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I've been doing my own seed oil / obesity investigation for several months now, and I must commend this post for covering all of the major points. My only gripe is that I believe most meta-analyses are wrong because they don't weed out the bad studies (e.g. ones that are poorly designed from the outset or that mistakenly confound their analysis by, say, lumping omega-3 and omega-6 PUFAs together). I imagine the meta-analysts would want to remove these problematic studies so I understand that there are limits to what can be measured.

I posted a comment similar to the following on the Substack version of this post but was hoping to get some more feedback from the LW community:

One thing that puzzles me is that calories in the food supply, as well as calories in food diary data, have basically flattened in the US since 2000 but obesity has doubled since then. I've put together data from several US government sources in this writeup (all data + R code is available in this github repo).

From a raw data standpoint, per-capita supply of vegetable oil much more closely tracks obesity than does per-capita supply of calories or caloric sweeteners. People are also exercising a lot more than they used to (which one would expect given the public health advice to "eat less, move more").

While this is prima facie evidence in favor of seed oils, we also know that seed oils are combined with lots of other potential toxins in processed foods. If you haven't seen this study yet, it definitively shows that "ultra processed food" has a very low omega-3:omega-6 ratio, causes weight gain, messes with satiety and hunger hormones, and affects metabolism. 

The question then becomes "what exactly is it about 'ultra processed food' that is so bad?"

  • Seed oils or some form of omega-3/omega-6 imbalance?
  • MSG or other flavor enhancements?
  • Modified starches? [which are basically alternative forms of MSG]
  • Lecithins and other emulsifiers? [mono and diglycerides]
  • Artificial colors?

To answer this question we'd somehow have to make an "ultra processed diet" that was identical in content to the status quo "ultra processed diet" but didn't include the above substances. Which is likely infeasible.

The other major question I'm grappling with is why there is an obesity-elevation gradient. This has been litigated on LW in the past and my preferred theory at the moment is that there is some sort of relationship between hypoxic environment and cell metabolism that favors metabolic efficiency. However, it's not like high-elevation places are immune from obesity; they just have lower rates and more or less increase in parallel with low-elevation places. However, elevation isn't the whole story because there's plenty of low-elevation places that also have low-obesity. I don't think seed oils fit into this at all unless it is through how they influence cell metabolism.

...which leads me into my recent reading of Anthony Hulbert's Omega Balance. I've found it useful for understanding some basic biochemistry of cell membranes and how cell membrane fatty acid composition might interfere with basic metabolic processes. He probably oversteps the evidence with some of his arguments. But as a result of reading it, I've spent the last week eating high-omega-3 by focusing on consuming lots of flaxseed and chia seed. (It turns out a basic-sized salmon filet has <1g of omega-3 so fish isn't the most concentrated source of omega-3 even though it is for "long-chain" omega-3.) So far I've been pleased with the results: I feel like I've slept better and I've dropped a few pounds. Tonight for dinner we had people over and I ate a slice of Marie Calendar's cherry pie that has immediately given me a stomach ache. What does the pie have a lot of? Modified starch and seed oil.

I'm surprised that the AHA and similar continue to push high-omega-6 oils. Yes, they reduce cholesterol, but they seem to increase a lot of other long-term disease risks. I view the focus on cholesterol to be short-sighted and mistaken. But I'm no biochemist or physician.

I'm very interested in helping you solve your problem, but I am doubtful that it can be precisely solved with the data you have. Based on what I've read in the book Glucose Revolution (I am still critically evaluating its claims but so far appears to be solid), it seems that the body's insulin response to a given food varies with pre-/post-intake exercise, whether a fibrous food was eaten beforehand, which types of other food were in the same meal, baseline levels of stress/sleep/insulin, and a host of other factors. Moreover, blood glucose spikes seem to lead to lots of poor mental and physical health outcomes (again, I'm still evaluating these claims).

Have you ever worn a continuous glucose monitor (CGM)? I suspect that some of your quandary may be solved by looking at high-frequency blood glucose readings. You may also be interested in ZOE which is a healthcare startup mentioned at the end of the book. ZOE advertises that it will monitor what seem to be the major measurable factors that affect insulin response: blood glucose, blood fat, and microbiome. And it claims to give personalized insights. The subscription price is much cheaper than the bounty you're offering.

I'm not trying to promote Glucose Revolution or ZOE; just pointing out that blood sugar (as well as order-of-eating and other details) seems to be a key missing piece of your data. I applaud your desire to get the W on factory settings!

Feel free to reach out to me if you'd like to discuss offline; this is my same handle on twitter, Substack, GitHub, Gmail, etc. I will hope to write a Substack post soon looking deeper into the scientific backing of the book. I'm much more wary of these pop science books after Alexey Guzey destroyed Matthew Walker's Why We Sleep.

I found this from Slime Mold Time Mold's monthly links for Nov 2023. I imagine @underthesun did as well, but won't speak for them.

This looks super interesting. I've done something similar for myself here. It would be interesting if similar results were found in your data.