摘要：Objectives. We examined the association between environmental quality measures and health outcomes by using the County Health Rankings data, and tested whether a revised environmental quality measure for 1 state could improve the models. Methods. We conducted state-by-state, county-level linear regression analyses to determine how often the model’s 4 health determinants (social and economic factors, health behaviors, clinical care, and physical environment) were associated with mortality and morbidity outcomes. We then developed a revised measure of environmental quality for West Virginia, and tested whether the revised measure was superior to the original measure. Results. Measures of social and economic conditions, and health behaviors, were related to health outcomes in 58% to 88% of state models; measures of environmental quality were related to outcomes in 0% to 8% of models. In West Virginia, the original measure of environmental quality was unrelated to any of the 8 health outcome measures, but the revised measure was significantly related to all 8. Conclusions. The County Health Rankings model underestimates the impact of the physical environment on public health outcomes. Suggestions for other data sources that may contribute to improved measurement of the physical environment are provided. A recent significant effort to characterize population health across counties in the United States is that of the County Health Rankings model developed by the University of Wisconsin’s Population Health Institute 1 based on the United Health Foundation America’s Health Rankings for states. 2 The model equally weights 2 health outcomes–morbidity and mortality–to form a total county health outcome score and identifies and weights 4 primary determinants of health. These determinants include social and economic factors (measured by education, employment, poverty, family and social support, single-parent households, and community safety) at 40% weight, health behaviors (tobacco use, obesity, physical inactivity, alcohol use, and unsafe intercourse) at 30% weight, clinical care (quality of care and access to care) at 20% weight, and physical environment (environmental quality and the built environment) at 10% weight. Considerations for choosing health determinants and assigning weights included existing studies, potential community modifiability of determinants, county availability and reliability of measures, and expert analysis paired with feedback. 1 Not included in the model are genetic determinants of health. In an often-cited model, McGinnis et al. 3 assigned 30% weight to genetic influences on health. The Working Paper for the County Health Rankings team recognized that genetics influence health outcomes, but the paper indicated that the contribution of genetic factors was excluded from the model because they were considered to be nonmodifiable and nonmeasurable. 4 Our study summarizes evidence regarding the interdependence of genetic structure and physical environment, along with evidence of increased exposure to environmental toxicants that has occurred during recent decades. We then conducted an analysis of the 2012 County Health Rankings data to test the hypothesis that the impact of environmental quality as measured in the County Health Rankings model is significantly underestimated. We tested the hypothesis by conducting a case study of 1 state to incorporate additional state-specific environmental quality indicators into a revised environmental quality measure.
