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  3. Multidimensional Approaches To Ranking State-level Rurality To Enhance Comparisons Across States.
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Multidimensional Approaches to Ranking State-Level Rurality to Enhance Comparisons Across States.

Daniel Baslock1, Nari Yoo2

  • 1Virginia Commonwealth University School of Social Work.

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View abstract on PubMed

Summary
This summary is machine-generated.

A new multidimensional rurality index reveals diverse rural profiles across US states, improving health policy research beyond single indicators like population percentage. This tool aids targeted comparisons for better resource allocation.

Keywords:
Borda countPCAcomposite indexhealth disparitieshealth policyrural healthrural populationstate comparisons

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Area of Science:

  • Rural Health Policy
  • Geographic Health Disparities
  • Sociodemographic Indicators

Background:

  • Current state-level rurality measures, often single indicators like population percentage or density, are inadequate for comprehensive analysis.
  • These simplistic measures obscure crucial differences among states, leading to overgeneralization in health policy research and resource allocation.
  • A multidimensional approach is essential for accurately characterizing rurality and informing research on health care access, quality, and equity.

Purpose of the Study:

  • To develop a composite, multidimensional rurality index for all 50 US states.
  • To create a more nuanced ranking system that moves beyond single-indicator limitations.
  • To provide a tool for more accurate comparisons of rural states for policy and research.

Main Methods:

  • Developed a composite index using three key indicators: rural population percentage, rural land area percentage, and rural population density.
  • Employed Borda count and dominance count ranking methods to integrate the indicators.
  • Utilized Principal Component Analysis (PCA) for data visualization and identification of states with similar rural profiles.

Main Results:

  • Mountain West states (e.g., Alaska, Montana, Wyoming) ranked highest on the multidimensional rurality index.
  • States like Vermont and Maine, often considered rural by population share alone, showed profiles similar to less traditionally rural states (e.g., Mississippi, Arkansas).
  • PCA distinguished between land-based rurality (vast, sparsely populated areas) and population-based rurality (high proportion of residents in rural towns).

Conclusions:

  • The developed multidimensional rurality index offers a superior tool for health policy research compared to single indicators.
  • It enables more targeted and meaningful comparisons among diverse rural states.
  • This index can guide research on rural health care infrastructure, workforce challenges, and health equity by acknowledging the varied nature of rurality.