Health Disparities
Harmonizing Mixed-Scale Public Data to Build Ecological Indices of Institutional and Economic Barriers for Health Disparities Research Zonggui Li* Zonggui Li Li Li Li Li The University of Maryland Baltimore, School of Pharmacy
Background: Institutional and economic barriers shape access to resources and opportunities and lead to health disparities for Black and Hispanic populations in the U.S. Prior qualitative work identified 70 candidate ecological-level indicators to measure institutional and economic barriers across 4 domains (behavioral, physical/built environment, sociocultural, and healthcare system) and 3 levels (interpersonal, community, and societal). We conducted a data-availability review and identified 60 indicators that could be quantified using publicly available data.
Objectives: To systematically link public data sources to each indicator and generate multidimensional-multilevel (4 domains × 3 levels), ecological-level indices across geographic areas and years.
Methods: For each indicator, we: 1) cataloged data source, variable selection, temporal coverage, reporting frequency, and geographic resolution; 2) harmonized measures by aligning geographic identifiers; 3) standardized indicators and aligned indicator direction so higher values indicate greater barriers; 4) computed indices by domain using expert-derived weights; and 5) conducted sensitivity analyses varying standardization approach, weighting methods, and missing-data rules to assess robustness of spatial and temporal change in the developed index.
Results: We present the indicator–data source crosswalk, data coverage by geography and year, and state-level indices for each of the 4 domains for selected years. Figure 1 presents a preliminary heatmap for one of the domains, healthcare-system. The index (weighted z-score) was constructed using the most recent available data and ranged from -1.35 (California, least barriers) to 0.50 (Vermont, most barriers).
Conclusions: This project developed ecological-level indices and a data pipeline that advance methods for measuring institutional and economic barriers for Black and Hispanic populations, while documenting limitations due to statistical and data constraints.
