Epidemiological studies in general are flawed and hard to trust due to omitted variables that you don't know about, p-hacking and publication bias making it difficult or impossible to interpret causality. You say "of course" as if it's a foregone conclusion that the results should be trusted and the authors have done a good job, when the default should be disbelief and scepticism in this particular approach unless shown otherwise with unusually strong results. I only have a positive reaction and belief by default in large scale RCTs. Epidemiological studies have not earned the benefit of the doubt. At best they are indications of future experimental research directions, i.e. they are a means to an end.

I've worked in academic applied statistics research and seen how the cookie crumbles, it's not pretty, and yes there are groups and industries of people who may be individually intelligent but nevertheless act like idiots given the incentives they face to churn out low-effort publications. Search for "hegemony" or "Fuzzy neural net Dow Jones" in Google Scholar to see 140 IQ people mass produce drivel. Just because I am not trained in medicine doesn't mean I am not allowed to draw this conclusion, I have years of experience in statistics and know a bullshit application of these tools when I see it, and I don't appreciate appeals to authority or other arguments that try to invalidly shut down people's opinions without knowing why those opinions were formed in the first place.