Syndemics of psychosocial problems and HIV risk: A systematic review of empirical tests of the disease interaction concept

In the theory of syndemics, diseases co-occur in particular temporal or geographical contexts due to harmful social conditions (disease concentration) and interact at the level of populations and individuals, with mutually enhancing deleterious consequences for health (disease interaction). This theory has widespread adherents in the field, but the extent to which there is empirical support for the concept of disease interaction remains unclear. In January 2015 we systematically searched 7 bibliographic databases and tracked citations to highly cited publications associated with the theory of syndemics. Of the 783 records, we ultimately included 34 published journal articles, 5 dissertations, and 1 conference abstract. Most studies were based on a cross-sectional design (32 [80%]), were conducted in the U.S. (32 [80%]), and focused on men who have sex with men (21 [53%]). The most frequently studied psychosocial problems were related to mental health (33 [83%]), substance abuse (36 [90%]), and violence (27 [68%]); while the most frequently studied outcome variables were HIV transmission risk behaviors (29 [73%]) or HIV infection (9 [23%]). To test the disease interaction concept, 11 (28%) studies used some variation of a product term, with less than half of these (5/11 [45%]) providing sufficient information to interpret interaction both on an additive and on a multiplicative scale. The most frequently used specification (31 [78%]) to test the disease interaction concept was the sum score corresponding to the total count of psychosocial problems. Although the count variable approach does not test hypotheses about interactions between psychosocial problems, these studies were much more likely than others (14/31 [45%] vs. 0/9 [0%]; χ2 = 6.25, P = 0.01) to incorporate language about “synergy” or “interaction” that was inconsistent with the statistical models used. Therefore, more evidence is needed to assess the extent to which diseases interact, either at the level of populations or individuals, to amplify HIV risk.