The headline is broadly defensible, but the qualifications matter. Effect sizes vary by population, the strongest claims rest on shorter trials, and credible voices push back on how it's typically framed.
now that's a real thing in terms of like cohort studies and cross-sectional data observational data it is a real thing but when you're dealing with something that's kind of a healthy user bias typically you'll see like the data is not consistent right like some one study will say one thing one study might have no Effect one study by say a different thing
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Bookmarking — the dossier-vs-overview split is the right call. Most of the time I want overview; sometimes I want receipts.
Would love a "what would change this verdict" RSS feed. Sign me up if it exists.
epidemiology, in particular, nutritional epidemiology, um, tends to be heavily confounded by healthy user bias. Um, and that means that people who are doing one healthy thing, for example, like eating a high-fiber diet, tend to be doing many other healthy things. They might be exercising more. They're much less likely to smoke. They're probably getting more sleep.
In other words, you are very likely to be capturing other healthy habits when you're trying to simply measure one thing.