The multidimensional clustering of health and its ecological risk factors

Abstract

A diverse set of research has examined the ways in which population-level health and its ecological risk factors are embedded within self-reinforcing structures. Syndemic theory, for example, focuses on the co-occurrence of multiple diseases, whereas the spatial diffusion literature highlights the concentration of poor health among communities sharing geographic boundaries. This study combines these related but disciplinarily-isolated perspectives to examine the clustering of population-level health and its determinants across four dimensions: co-occurrence, spatial, temporal, and social network. Using data on U.S. county-level health outcomes and health factors from the Robert Wood Johnson Foundation's County Health Rankings, this study estimates associations between health outcomes within communities and the co-occurrence of community-level factors theorized to influence ecological health. Not only do health outcomes and their ecological risk factors cluster within counties, but also between geographically adjacent counties and counties connected via migration network pathways. Moreover, the self-reinforcing structures uncovered across the co-occurrence, spatial and network dimensions persist over time, and this clustering has consequences on county health and well-being. Rather than adopting the perspective that either health and its community-level factors should be broadly targeted and detached from local context or communities are different, have unique needs and thus should be treated in isolation, the approach advanced in this study identifies shared vulnerabilities in a way that allows for the development of knowledge networks between communities dealing with similar issues.

Keywords: Migration; Social determinants of health; Social networks; Spatial analysis; Syndemic.