Hacker News new | ask | show | jobs
by devbent 743 days ago
Diet studies can also fall into a similar trap.

Huge sample size, but all food intake is self reported, or a tiny sample size where test subjects were locked into a chamber that measures all energy output from their body while being fed a carefully controlled diet.

The later is super expensive, but you can be pretty confident of the results. On the flip side it also miss any conditions that only present in a small % of the population.

You can see this with larger dietary studies where out of 2 cohorts of 100 each doing different diets, 15 or 20% on each group does really well on some "extreme" diet (e.g. Keto) but the group on average has no unexpected results.

If your sample size is 5, it is quite possible none of your test subjects are going to be strong responders to, for example, keto.

So then the study deadline comes out "Keto doesn't work! Well controlled expensive trial!"

Meanwhile the large cohort study releases results saying "on average Keto doesn't work".

But in reality, it works really well for some % of the population!

Some non-stimulant ADHD drugs have a similar problem. If a drug only works for 20% of the population, you need to be aware of that when doing the study design.

1 comments

You seem to be implying that subgroup analysis never happens?

I guess I don't follow weight loss research closely, but I would be genuinely amazed that they don't do it, too, given how ubiquitous it is everywhere else in medical science. And the literature on ketogenic diets goes back over a century now, so it's hard to imagine nobody has done one. Could it be instead that people did do the subgroup analysis, but didn't find a success predictor that was useful for the purposes of establishing medical standards of care or public health policy? Or some other wrinkle? Or maybe people are still actively working on it but have yet to figure out anything quite so conclusive as we might wish? But that this nuance didn't make it into any of the science reporting or popular weight loss literature, because of course it didn't, details like that never do?

Disclaimer, I'm absolutely not here to trash keto diets in general. I have loved ones who've had great success with such a diet. My concern is more about the tendency for health science discussions to devolve into a partisan flag-waving contest where the first useless thing to get chucked out the window is a sober and nuanced reading of the entirety of the available body of evidence.

> Could it be instead that people did do the subgroup analysis, but didn't find a success predictor that was useful for the purposes of establishing medical standards of care or public health policy?

If we are all being generous with assumptions, this could very well be the reason.

I haven't seen much research on efforts of trying to predict what dietary interventions will most effective an individualized treatment basis, but I also haven't kept up a literature for five or six years.

Then again the same promises for ADHD medicine where now they are some early genetic studies showing perhaps how we could guide treatments, but the current standard of care remain throw different pills at the patient and see what they works best with the fewest side effects.

Of course dietary stuff is complicated due to epigenetics, environmental factors, and gut microbiomes.

That said progress is being made and the knowledge we have now is world's different than the knowledge we had 20 years ago, but sadly it seems outcomes for weight loss are not improving.