For example you say
>There is no causality here; just correlation and many potential cofounders...
what does this specifically mean? When A and B are correlated to statistical significance, either A causes B, B causes A, or something else is causing both A and B. So, how could the future act of living longer be causing people to eat more protein? Or, what possible things could be causing people to eat more animal protein and live longer at the same time? I can't think of anything plausible.
It is fair to say that this study is very good evidence, as good as anything can be, that animal protein is important for longevity.
It seems to me that the parent comment doesn't aim to "hand wave away" this paper, but instead to suggest that it is a singular datum whose findings should be tested by larger, more in-depth, research (which could test for a whole set of confounding variables that might come to mind). The authors of the original study state the same thing right in their abstract!
I'm not sure why you think that point is not meaningful. IMO, that is exactly how science should be done ---interesting correlations should be stress-tested. If the findings hold up, then we can be especially confident in whatever choices we make. If the findings don't hold up, we then have new avenues to research.