The big issue is sub populations. I work on similar large studies including genomic data and it is quite frequent to see associations of the form "central americans have a lower rate of disease x" and "central americans have a higher rait of factor y."

This produces a statistical association but, especially with genomic factors, factor y can just be something that randomly identifies the group.

Similarly in this data set you might find a group of people who have higher strength because of genomic factors that make it easier for them to build strength from the same workouts as "normall" people. These people might also come from a subpopulation (farm famlies, people of Slavic heritage who knows) that has lower rates of cancer for genomic or cultural reasons. Even a small number of such people can make the association look significant though it will disappear once you remove them.

It could also be something like a certain food or diet making it both easier to build strength and preventing cancer.