"Interventions Tend To Combine Synergistically To Extend Life Span A Little, But The Typical Improvement Is Statistically Insignificant"; another production from Kingsley's ginormous spreadsheet. Abstract:

"I used the results of previous life span experiments to test the statistical hypothesis that interventions tend to work as well individually as in combination. I included previous experimental results reporting the risk of people dying from any cause, and changes to the mean and maximum life spans of lab animals, Combinations trended toward extending life spans more in all three, but the improvements were statistically insignificant."

My comments on GRG:

"If I'm understanding this right, you're treating this as basically a vote-counting model: a single study yields a single data point of a single/multiple binary variable & a average lifespan increase % (experimental minus control).

This seems like it could be masking a huge amount of variables and relevant info. For example, do multiple intervention studies administer the same net amount of substances as the single intervention studies? If a multiple intervention studies administers 10mg of 10 substances and a single intervention administers 100mg of 1 substance, and there are increasing returns like a U-curve, then the combined additive or multiplicative effect of the multiple-interventions could equal the single intervention. Or could there be a bias in subject selection? It's probably easier to get big humans to eat multiple substances than a tiny hydra or yeast cell, and human studies don't seem to work well in general regardless of multiple vs single, so that could produce a lack of effectiveness (the multiples look ineffective, because they tend to be done in humans; and the single look effective, because smaller simpler animals will tend more to receive singles). You can probably think of a few other plausible covariates."