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Measuring the spatial distribution of health rankings in the United States
Author(s) -
Davis Will,
Gordan Alexander,
Tchernis Rusty
Publication year - 2021
Publication title -
health economics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.55
H-Index - 109
eISSN - 1099-1050
pISSN - 1057-9230
DOI - 10.1002/hec.4416
Subject(s) - imputation (statistics) , econometrics , rank (graph theory) , population , statistics , stock (firearms) , geography , bayesian probability , distribution (mathematics) , missing data , mathematics , demography , sociology , mathematical analysis , archaeology , combinatorics
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 is a substantial quantity of uncertainty in rankings throughout the rank distribution. Analyzing the health of counties both within and across state lines shows notable degrees of disparity in county health. While we find some disagreement between the ranks of our model and the CHRs, we show that there is additional information gained by utilizing the rankings produced by both methods.