The relationship between neighborhood typologies and self-rated health in Maryland: A latent class analysis.

Abstract

Despite widespread evidence that neighborhood conditions impact health, few studies apply theory to clarify the physical and social factors in communities that drive health outcomes. Latent class analysis (LCA) addresses such gaps by identifying distinct neighborhood typologies and the joint influence that neighborhood-level factors play in health promotion. In the current study, we conducted a theory-driven investigation to describe Maryland neighborhood typologies and examined differences in area-level self-rated poor mental and physical health across typologies. We conducted an LCA of Maryland census tracts (n=1384) using 21 indicators of physical and social characteristics. We estimated differences in tract-level self-rated physical and mental health across neighborhood typologies using global Wald tests and pairwise comparisons. Five neighborhood classes emerged: Suburban Resourced (n=410, 29.6%), Rural Resourced (n=313, 22.6%), Urban Underserved (n=283, 20.4%), Urban Transient (n=226, 16.3%), Rural Health Shortage (n=152, 11.0%). Prevalence of self-rated poor physical and mental health varied significantly (p<0.0001) by neighborhood typology, with the Suburban Resourced neighborhood class demonstrating the lowest prevalence of poor health and the Urban Underserved neighborhoods demonstrating the poorest health. Our results highlight the complexity of defining "healthy" neighborhoods and areas of focus to mitigate community-level health disparities to achieve health equity.