Innovative Approaches to Investigating Social Determinants of Health - Social Networks, Environmental Effects and Intersectionality

Abstract

Contexts are important social determinants of individual health trajectories and population level patterns of health disparities. This dissertation examines three types of contexts—social networks, physical environments, and social positions—using innovative quantitative approaches. Chapter 1 examines the intersectional social positions created by interlocking social identities—race/ethnicity, sex, income, education, and age—and their relationship to health disparities in the obesity epidemic. We outline an innovative analytic approach to evaluating intersectionality using multilevel models. After adjustment for the contributions of the main effects, a large intersectional effect remains. While clear social patterning emerges, interactions are not necessarily patterned according to ‘multiple jeopardy’ and ‘multiplicative benefit’ as might have been expected. These findings reveal the complex social patterning of the obesity epidemic, and challenge us to consider possible refinements to intersectionality theory. Chapter 2 evaluates whether U.S. adolescent social networks are segregated by family income level. Network segregation or integration may affect adolescent health trajectories through a variety of pathways, yet the extent to which networks are socioeconomically segregated is poorly understood. We approach the evaluation of income segregation through a novel lens by explicitly considering three scales of analysis within social networks: the network community level, the dyadic level, and a level in between. We find evidence of income segregation at all three levels, though this segregation is neither extreme nor universal. Family income appears to be a socially salient factor in the structure of adolescent social networks. In Chapter 3, three contexts of relevance to the adolescent obesity epidemic—schools, neighborhoods, and social networks—are examined simultaneously. Using a novel combination of social network community detection and cross-classified multilevel modeling, we compare the contributions of each of these contexts to the total variation in adolescent body mass index. After adjusting for relevant covariates, we find that the school-level and neighborhood-level contributions to the variance are modest compared with the network community-level. These results are robust to multiple sensitivity tests. This study highlights the salience of adolescent social networks and indicates that they may be a promising context to address in the design of health promotion programs.