(Renaming, since there has been a response)
I recall a presentation some years ago on a problem (in the life sciences, in this example, but potentially elsewhere) that you'd draw some samples from your test subjects, and because it was so hard to get the experiment set up and approved, you would end up running all sorts of tests on the subjects. Not being in the field I can't recall what the tests were, but apparently you would test for dozens of different effects. The problem being that you were looking for a p-value > 0.05, and statistically speaking, you would do enough tests (>20) where a false positive would be expected to pop up.
So you have the same problem here. if you start looking for correlations, you will eventually find them, without them being causal. (one of my favorites is that buying certain types of cars correlates with voting for a particular party is mistaken for causation , i.e. the situation where one might claim buying a Ford pickup truck causes you to vote republican)
This is one reason why you don't rely on one study, and also why you need to find a causative agent that you can independently test.
So they say there's correlation, and you see a correlation, but word this as if you disagree?