1. the authors fit a certain model, adjusted for certain covariates, and observe that a certain effect of interest is statistically significant.
2. therefore, if (a) the model is "correct" i.e. sufficiently well approximates the observed data distribution, and (b) the regression coefficient and structural coefficient coincide i.e. the true generative DAG is compatible with the chosen set of covariates, then a causal association from the predictor to the outcome exists with high probability.
3. the authors simply assume (2) and therefore imply that a causal relation likely exists.
https://www.cnn.com/2012/09/25/health/eunuchs-lifespan/index...
(Europe and the United States immediately follow suit with programs for their men, meanwhile China organizes a yearly parade of its sexual supermen, Russia creates single Pornhub VIP account for the entire country and publishes the password in state newspapers.)
Sounds like the opposite of the headline
https://healthland.time.com/2012/09/25/do-eunuchs-really-liv...
...but this was a historical look at 81 Korean imperial eunuchs from the 14th to early 20th centuries, and compared them to other male imperial court members.
Anyone want to signup for a modern test?
...but before you dismiss this completely - modern animal mammalian studies have confirmed this result and it also helps explain why women live longer. ...though the studies only looked at castration prior to puberty. That's important because overall height (a proxy for mass and cell count) is inversely correlated with longevity.
I find the title here inline with that enough.
Further the link is a short but accurate summary of the paper. Seriously just read it and then comment.