the mention that they controlled for age also directly says they didn't correct for anything else. e.g. if for whatever reason the male study population has a s

the mention that they controlled for age also directly says they didn't correct for anything else. e.g. if for whatever reason the male study population has a significant shift into any direction (income, physical characteristics like height, weight, etc.) bam you're entire data set is essentially useless. and this is almost certainly going to be the case. it's nigh impossible to get similar averages for all metrics in a male between female comparison. the data is very valuable on its own. but once again I have no idea how they think it remotely allows them to draw the specific conclusions regarding causality that they do.