| > Are you familiar with how we might convert death HR into an expected lifespan delta for the average person? You'd have to integrate over lifespan using an actuarial table, I assume. This figure of 1.8 wasn't for all-cause mortality, but rather for heart-disease deaths among breakfast-skippers. I wouldn't worry (much) for a bunch of related reasons: - The more complexity you need to specify a statistic, the more evidence you need to overcome a presumption it's an artifact. (Some of this caveat shows up in how they report it ("multivariable-adjusted", "95% confidence interval"), but these frequentist-statistics methods don't really account for all the real-world reasons for doubt.) - This study was observational, not interventional. It's one study. Observational studies, particularly in epidemiology, particularly for diet, are often misleading. - What'd be the mechanism making skipping breakfast have this big an effect? There could well be a good answer to that, but it doesn't spring to mind for me. In other words, what was your prior on this hypothesis, before this paper? - I haven't read the paper beyond the abstract linked to, but https://news.ycombinator.com/item?id=34883541 lists some potential problems. - The process that brings a particular medical paper to your attention, unfortunately, is not much like one that optimizes for the most significant updates to the probability distribution you should have over hypotheses. Unless you have a much better news feed than most of us, anyway. I think of a result like this as a little bit of evidence to keep in mind as you learn more. It's not making me do anything different right now. That might seem harsh about a study involving "185,398 person-years of follow-up period" -- that must've taken a fuck-ton of work -- but it seems to be the world we're in. |