Assessing U.S. County-Level Mental Health Outcomes: A Spatial Analysis of Quality of Life

Marina Armendariz , Pennsylvania State University
Stephen A. Matthews, Pennsylvania State University

Social and economic conditions are often cited as fundamental determinants of health and are spatially clustered. However, there is limited work examining the spatial distribution of subjective health, particularly quality of life (QoL). Our study explores the spatial patterning for three county-level self-reported health (SRH) outcomes: poor/fair health, physical distress, mental distress, as well as county-level disadvantaged socioeconomic status. A combination of exploratory spatial data analysis (ESDA) and spatial econometric techniques were utilized. These spatially informed findings revealed spatial autocorrelation, indicating spillover effects, in key explanatory and outcome variables. Moreover, findings from analytic models support the notion that county-level disadvantaged socioeconomic status contributes to health inequalities at the population level. Lastly, spatial regimes revealed regional differences in QoL outcomes between metro and non-metro counties. To begin improving population health, the spatial patterning and neighboring effects of health outcomes and the associated risk factors should be considered at various geographic levels.

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 Presented in Session 11. Health & Mortality 2