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January 5, 2026
Quarterly Article
Daniel Baslock
Nari Yoo
Back to The Milbank Quarterly
Policy Points:
Context: Inadequate descriptions of rurality limit comparisons across rural areas and can lead to overgeneralizations in health policy research. Single indicators of state-level rurality, such as rural population percentage or population density, are often used in isolation and fail to capture the multidimensional nature of rural character, obscuring important differences among states. A more holistic measure is needed to inform research on health care access, quality, and health disparities.
Methods: This study developed a composite state-level rurality index for the 50 US states for three indicators: rural population percentage, rural land area percentage, and rural population density. We used Borda count and dominance count ranking methods to integrate these indicators into a final ranking. Principal component analysis (PCA) was then used to visualize the data and identify states with similar profiles.
Findings: Mountain West states, including Alaska, Montana, and Wyoming, ranked highest in multidimensional rurality. States traditionally considered highly rural based on a single indicator, such as Vermont and Maine (owing to high rural population share), exhibited rural profiles more similar to states such as Mississippi and Arkansas. The PCA visually distinguished between states with land-based rurality (e.g., vast, sparsely populated areas) and those with population-based rurality (e.g., high proportion of residents in rural towns).
Conclusions: This multidimensional index provides a tool for health policy research, facilitating more targeted and meaningful comparisons among rural states. It can help guide the study of health care infrastructure, workforce challenges, and health equity by moving beyond less nuanced classifications and highlighting the diverse forms of rurality across the United States.
