Assessing community-level exposure to social vulnerability and isolation: spatial patterning and urban-rural
Nicole C Deziel1, Joshua L Warren2, Mercedes A Bravo3
1Yale School of Public Health, Department of Environmental Health Sciences, New Haven, CT, USA. nicole.deziel@yale.edu.
Journal of Exposure Science & Environmental Epidemiology
|April 7, 2022
Summary
Environmental health disparity research requires careful metric selection. Composite social vulnerability indices are highly correlated and can be used interchangeably, unlike single-domain metrics, which capture distinct aspects of community vulnerability.
Area of Science:
- Environmental Health
- Social Epidemiology
- Geospatial Analysis
Background:
- Environmental health disparity research uses metrics to assess community-level vulnerabilities and inequities.
- Existing vulnerability indices lack standardization and are primarily applied in urban settings, limiting their utility across diverse geographies.
Purpose of the Study:
- To evaluate the spatial distribution, variability, and relationships among social vulnerability and isolation metrics in urban and rural settings.
- To inform the interpretation and selection of metrics for environmental disparity research.
Main Methods:
- Principal components analysis of 23 socioeconomic/demographic variables for North Carolina census tracts (2010 Census/ACS).
- Calculation of neighborhood deprivation index (NDI), residential racial isolation index (RI), educational isolation index (EI), Gini coefficient, and social vulnerability index (SVI).
- Spatial analysis (Moran's I), urban-rural comparisons (t-tests), correlation (Pearson), and rank change analysis.
Main Results:
- Social vulnerability metrics showed significant spatial clustering (Moran's I ≥ 0.30, p < 0.01).
- Rural areas exhibited higher educational isolation and neighborhood deprivation; urban areas showed greater racial isolation.
- Composite metrics (NDI, SVI, PCA) were highly correlated (rho > 0.80) and interchangeable, unlike single-domain metrics (rho ≤ 0.36).
- Composite metrics correlated more strongly with racial isolation in urban (0.54-0.64) vs. rural tracts (0.36-0.48).
- Census tract rankings varied significantly depending on the metric used.
Conclusions:
- Composite social vulnerability metrics are largely interchangeable within urban and rural contexts due to high correlations.
- Single-domain metrics capture unique aspects of vulnerability and cannot be used interchangeably.
- Researchers must consider the complexities captured by different metrics in diverse urban and rural settings for accurate environmental disparity research.
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