The social environment, both in early life and adulthood, is one of the strongest predictors of morbidity and mortality risk in humans. Evidence from long-term studies of other social mammals indicates that this relationship is similar across many species. In addition, experimental studies show that social interactions can causally alter animal physiology, disease risk, and life span itself. These findings highlight the importance of the social environment to health and mortality as well as Darwinian fitness—outcomes of interest to social scientists and biologists alike. They thus emphasize the utility of cross-species analysis for understanding the predictors of, and mechanisms underlying, social gradients in health.

Agencies engaged in humanitarian efforts to prevent the further spread of HIV have emphasized the importance of voluntary counseling and testing (VCT), and most high-prevalence countries now have facilities that offer testing free of charge. The utilization of these services is disappointingly low, however, despite high numbers reporting that they would like to be tested. Explanations of this discrepancy typically rely on responses to hypothetical questions posed in terms of psychological or social barriers; often, the explanation is that people fear learning that they are infected with a disease that they understand to be fatal and stigmatizing. Yet when we offered door-to-door rapid blood testing for HIV as part of a longitudinal study in rural Malawi, the overwhelming majority agreed to be tested and to receive their results immediately. Thus, in this paper, we ask: why are more people not getting tested? Using an explanatory research design, we find that rural Malawians are responsive to door-to-door HIV testing for the following reasons: it is convenient, confidential, and the rapid blood test is credible. Our study suggests that attention to these factors in VCT strategies may mitigate the fear of HIV testing, and ultimately increase uptake in rural African settings.

SignificanceCollege graduates enjoy healthier, longer lives compared with individuals who do not graduate from college. However, the health benefit of educational attainment is not as great for blacks as it is for whites. Moreover, college completion may not erase the detrimental effects of early-life disadvantage for blacks and Hispanics. We use nationally representative data on young adults to test whether American minorities experience differential returns to educational attainment. We find that college completion predicts lower rates of depression for all racial groups. It also predicts lower metabolic syndrome among whites. However, college completion predicts higher metabolic syndrome among black and Hispanic adults from disadvantaged backgrounds, suggesting upward mobility may come at a health cost to young minorities in America.

Two seemingly-associated demographic trends have generated considerable interest: income stagnation and rising premature mortality from suicides, drug poisoning, and alcoholic liver disease among U.S. white non-Hispanics with low education. Economists interpret these population-level trends to indicate that despair, induced by financial stressors, is a shared pathway to these causes of death. Although we now have the catchy term “deaths of despair” (DoD), we have yet to study its central empirical claim: that conceptually defined and empirically assessed “despair” is indeed a common pathway to several causes of death. At the level of the person, despair comprises cognitive, emotional, behavioral, and biological domains. Despair can also permeate social relationships, networks, institutions, and communities. Extant longitudinal datasets feature repeated measures of despair—before, during, and after the Great Recession—offering resources to test the role of economic decline-induced despair in premature morbidity/mortality. Such tests must also focus on protective factors that could shield individuals. DoD is more than a phrase; it is a hypothesis that deserves conceptual mapping and empirical study with longitudinal, multi-level data.