Urban sprawl, natural environments, and mortality inequality: Socioeconomic pathways and spatial heterogeneity across U.S. counties

Mortality patterns exhibit substantial spatial variation, yet potential geographic influences are not well-understood. This study develops an integrated framework to investigate how urban sprawl and natural environments contribute to county-level all-cause mortality risk and to examine intergenerational mobility (IM) as a mediator. The analysis incorporates machine learning and spatial regression methods with U.S. county data. Using a small-area disease risk model, we identify clusters of high mortality risk in the Southeast while lower-risk counties concentrate along the Pacific Coast, the Northern Great Plains, and the Northeastern metropolitan corridor. Using random forest regression, poverty exerted the strongest influence, with an importance index of 0.38, far exceeding that of built and natural environment factors. Yet, when nonlinear relationships are considered, the built and natural environments are more clearly associated with mortality risk. Specifically, population centering, employment mix, land-use mix, and transportation accessibility are associated with lower mortality rates while higher population density corresponds to elevated risk, but only within specific ranges of each variable. Air pollution is consistently associated with higher mortality risk, whereas green space composition exhibits an inverted U-shaped relationship with mortality. In structural equation models, IM was a critical pathway linking urban sprawl characteristics to mortality outcomes, as population centering and land-use mix are associated with lower mortality through higher IM, while employment centering increases mortality by suppressing IM. Substantial spatial heterogeneity characterizes these relationships. The results highlight the need for regionally tailored interventions that integrate urban form, the natural environment, and opportunity structures to reduce mortality inequalities. • Mortality risk exhibits pronounced spatial clustering across U.S. counties. • Socioeconomic conditions dominate mortality inequality, with stronger effects than sprawl and natural factors in linear models. • Accounting for nonlinear and threshold effects shows urban sprawl and natural environments more strongly shape mortality risk. • Polycentric form, employment and land-use mix, and accessibility lower mortality within specific value ranges; high density raises risk. • Intergenerational mobility mediates how urban sprawl shapes mortality, producing both protective and adverse effects.