학술논문

The Neighborhood Atlas Area Deprivation Index For Measuring Socioeconomic Status: An Overemphasis On Home Value.
Document Type
Academic Journal
Author
Hannan EL; Edward L. Hannan (edward.hannan@health.ny.gov), State University of New York at Albany, Rensselaer, New York.; Wu Y; Yifeng Wu, State University of New York at Albany.; Cozzens K; Kimberly Cozzens, State University of New York at Albany.; Anderson B; Brett Anderson, NewYork-Presbyterian Columbia-Irving Medical Center, New York, New York.
Source
Publisher: Project Hope Country of Publication: United States NLM ID: 8303128 Publication Model: Print Cited Medium: Internet ISSN: 1544-5208 (Electronic) Linking ISSN: 02782715 NLM ISO Abbreviation: Health Aff (Millwood) Subsets: MEDLINE
Subject
Language
English
Abstract
The Area Deprivation Index (ADI), popularized by the Neighborhood Atlas, is a multifaceted proxy measure for assessing socioeconomic disadvantage that captures social risk factors that are not available in typical clinical registries and that are related to adverse health outcomes. In applying the ADI to New York State, we found that the downstate regions (New York City and its suburbs) were as deprived as or more deprived than the other regions for thirteen of the seventeen ADI variables (all but the ones measured in dollars), but the Neighborhood Atlas-computed overall ADI deprivation was much less in the downstate areas. Numerous census block groups with high home values (indicating low deprivation) accompanied by high deprivation in the other ADI variables had overall ADI scores as computed by the Neighborhood Atlas in the same or contiguous deciles as the home values. We concluded that Neighborhood Atlas-computed ADI scores for New York block groups are mainly representative of median home value. This can be especially problematic when considering quality assessment, funding, and resource allocation in regions with large variations in cost of living, and it may result in underresourcing for disadvantaged communities with high housing prices. We conclude that the Neighborhood Atlas ADI would be more accurate for comparing block groups if variables were standardized before computing the overall index.