An interesting critique of observational data by John Cook. I think that the author raises an interesting point but that it is more true of cross-sectional studies than longitudinal ones. If you have a baseline modifiable factor and look at the predictors of change then you have a pretty useful measure of consequence. It might be confounded or it might have issues with indication bias, but it's still a pretty interesting prediction.
With cross sectional studies, on the other hand, reverse causality is always a concern.
Of course, the other trick is that the risk factor really has to be modifiable. Drugs (my own favorite example) often are. But even diet and exercise get tricky to modify when you look at them closely (as they are linked to other characteristics of the individual and are a very drastic change in lifestyle patterns).
It's a hard area and this is is why we use experiments as our gold standard!
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