A quasi-fix could be to control for the most obvious sources of vitamin D: how often do you go outside, how long do you go outside, do you take vitamin D supple

A quasi-fix could be to control for the most obvious sources of vitamin D: how often do you go outside, how long do you go outside, do you take vitamin D supplements, how often and with which strength. You can do this kind of analysis alongside any type of study, don't need full coverage and get some preliminary results. All you need is a Bayesian on your team (: partially in jest) or the willingness to open up your data after you publish. In my opinion as someone who practices non-medical statistics the trope of correlation vs. causation and interventional vs. observational are somewhat overblown. Andrew Gelman posted somewhat snarky about MDs and statistics recently [1]. I see that this post is in (very) good faith, but it does have the MD-bias to statistics in it. [1] https://statmodeling.stat.columbia.edu/2020/08/11/that-not-a-real-doctor-thing-its-kind-of-silly-for-people-to-think-that-going-to-medical-school-for-a-few-years-will-give-you-the-skills-necessary-to-be-able-to-evaluate-research-claims-in/ https://statmodeling.stat.columbia.edu/2020/08/11/that-not-a...