Measuring the spatial distribution of health rankings in the United States

Abstract We rank counties in the United States with respect to population health. We utilize the five observable county health variables used to construct the University of Wisconsin Population Health Institute's County Health Rankings (CHRs). Our method relies on a Bayesian factor analysis model that estimates data-driven weights for our rankings, incorporates county population sizes into the level of rank uncertainty, and allows for spillovers of health stock across county lines. We find that demographic and economic variation explains a large portion of the variation in health rankings. We address the importance of uncertainty caused by imputation of missing data and show that there i...

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