Comparing Across Health Indices: Differences by Rurality, Missingness, and Associations With Health Outcomes
Area-level indices of vulnerability, deprivation, prosperity, and the like are increasingly being applied in policy, reimbursement methods, and resource allocation. Measures captured within these indices are often described as reflecting the social determinants of health, social risk factors, health-related social needs, and similar constructs. Examples of such indices include the Prosperity Index, Social Vulnerability Index, Social Deprivation Index, Opportunity Index, and many others. However, the underlying evidence base lacks a sufficient focus on rurality to inform such uses and to understand their implications for rural communities. The purpose of this study is to compare the area-level indices and score missingness by measures of rurality. Further, researchers will examine associations between indices and health-related outcomes of interest. This study will provide policymakers and researchers with a deeper understanding of how indices compare and their relationships with health outcomes in rural communities. Findings could guide the selection and application of area-level indices in policy, practice, and research with considerations for any potential differential findings in rural communities.
This study will utilize publicly available data and a quantitative, cross-sectional design to compare scores and missingness of indices by rurality and associations with health outcomes of interest. Researchers will select indices that meet several criteria including: national in scope, created for a general purpose, publicly available or can be calculated using publicly available data and methodologies, available either at the census tract or county-level, and updated since 2019. Researchers will conduct bivariate and multivariate analyses of the associations between indices and health outcomes, and differences by rurality. Given that counties are the primary spatial unit for operational levels of emergency management and public health statistics in the U.S., researchers will conduct these analyses on a subset of indices available at the county-level. Health outcomes of interest may be related to cost, quality, access to care, or health status. Examples may include Medicare expenditures and utilization, insurance coverage, mortality rates, and supply of health care providers. These analyses will use multivariate linear and logistic regression, and spatial analyses such as spatial lag/error regression may be considered. To better describe relationships between indices and health outcomes, researchers may conduct analyses to detect the potential mediating role of rurality (e.g., formal mediation analyses or stratified analyses). Other measures of community health, economic, demographic, and policy context may be included as controls, but may vary by index.