A County-Level Analysis of the Relationship between Voter Behavior as a Proxy for Partisan Ideology, Income, and the Effects on Health Morbidity and Mortality Measures
Introduction: Domestic research studies focused on the interrelationships between political ideology characteristics inherent in policy decisions and the contributions these political determinants exert over health indicators and outcomes are limited. Given the paucity of research that focuses on political and policy support of health at the county-level, this study sets out to utilize the University of Wisconsin Population Health Institute’s (UWPHI) annual County Health Rankings data and examine them within the context of county-based majority political partisanship and economic measures. Methods: This exploratory ecological study examined differences between independent variables: partisan voting behavior (trichotomized as conservative, moderate, and liberal) and median per capita household income in U.S. dollars (by quartile) on dependent variables related to mortality (years of productive life lost) and morbidity (number of poor mental and physical health days) at the county-level to compare differences in political and ideological underpinnings that may act as influencers on health outcomes. Multiple data sources were combined and matched to all 3,140 counties located in the U.S. Two-way between-subjects ANOVA statistical tests were conducted to determine if there is an effect of partisan voter index category on the three aforementioned dependent variables related to health outcomes, and median per capita income by quartile. Results: There was a statistically significant main interaction between median per capita household income by quartile and partisan voter index category on years of productive life lost, F(6,2789) = 19.3, p \u3c .000, partial η2 = .040. While there were also statistically significant interactions between the independent and dependent variables of poor mental and physical health days, results of those analyses should be interpreted with caution. Pertaining to years of productive life lost, post hoc analyses of significant interactions revealed significant differences at the lower income quartile, but not in the expected direction. The conservative category had statistically significant lower years of productive life lost in comparison to the liberal category (M = -8.21, SE = 1.47, p = .000). Also, there were significant differences detected in the upper quartile suggesting that the liberal category has lower years of productive life lost in comparison to the conservative category (M = 7.06, SE = 1.06, p = .000). Conclusion: Results should be interpreted with caution and suggest more research and methodological refinements are needed, particularly related to categorizing county-level political dynamics
