Hamilton's rule predicts anticipated social support in humans

Abstract

Hamilton’s rule predicts that individuals should be more likely to altruistically help closer kin and this theory is well supported from zoological studies of nonhumans. In contrast, there is a paucity of relevant human data. This is largely due to the difficulties of either experimentally testing relatives or of collecting data on genuinely costly cooperation. We test Hamilton’s rule in humans by seeing if the availability of help in times of crises is predicted by the degree of genetic relatedness. In social network research, the pool of people that one can go to for support during times of crisis is termed the support network. By definition, the members of a support network provide various benefits in times of need, and larger support networks have been shown to be important for general health. As this level of support bears costs for the providers and has clear benefits for the receivers, it therefore allows us to test Hamilton’s rule. We use an Internet sample to analyze the composition of 540 people’s support networks. We had people rank their support network members in order of who would be most likely to help and found that relatives were more likely to be ranked in primary positions and that the degree of relatedness correlated with rank.