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Journal article
Comparing Global and Spatial Composite Measures of Neighborhood Socioeconomic Status Across US Counties
Journal of urban health, v 99(3), pp 457-468
Jun 2022
PMID: 35484371
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
Area-level neighborhood socioeconomic status (NSES) is often measured without consideration of spatial autocorrelation and variation. In this paper, we compared a non-spatial NSES measure to a spatial NSES measure for counties in the USA using principal component analysis and geographically weighted principal component analysis (GWPCA), respectively. We assessed spatial variation in the loadings using a Monte Carlo randomization test. The results indicated that there was statistically significant variation (p = 0.004) in the loadings of the spatial index. The variability of the census variables explained by the spatial index ranged from 60 to 90%. We found that the first geographically weighted principal component explained the most variability in the census variables in counties in the Northeast and the West, and the least variability in counties in the Midwest. We also tested the two measures by assessing the associations with county-level diabetes prevalence using data from the CDC's US Diabetes Surveillance System. While associations of the two NSES measures with diabetes did not differ for this application, the descriptive results suggest that it might be important to consider a spatial index over a global index when constructing national county measures of NSES. The spatial approach may be useful in identifying what factors drive the socioeconomic status of a county and how they vary across counties. Furthermore, we offer suggestions on how a GWPCA-based NSES index may be replicated for smaller geographic scopes.
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Details
- Title
- Comparing Global and Spatial Composite Measures of Neighborhood Socioeconomic Status Across US Counties
- Creators
- S Shanika A De Silva - Drexel UniversityMelissa A Meeker - Drexel UniversityVictoria Ryan - Drexel UniversityYasemin Algur - Drexel UniversityD Leann Long - University of Alabama at BirminghamApril P Carson - University of Mississippi Medical CenterNyesha Black - Noire Analytics, Birmingham, AL, USA.Leslie A McClure - Drexel University
- Publication Details
- Journal of urban health, v 99(3), pp 457-468
- Publisher
- Springer Nature
- Grant note
- R01DK124400 / CDC HHS
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Epidemiology and Biostatistics
- Web of Science ID
- WOS:000788409100001
- Scopus ID
- 2-s2.0-85128966857
- Other Identifier
- 991019167534804721
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- Collaboration types
- Domestic collaboration
- Web of Science research areas
- Public, Environmental & Occupational Health