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http://dx.doi.org/10.1158/1055-9965.EPI-06-1076

has been cited by the following article:

• TITLE: Statistical Assessment of Neighborhood Socioeconomic Deprivation Environment in Spatial Epidemiologic Studies

  AUTHORS: Min Lian, James Struthers, Ying Liu

  KEYWORDS: Assessment, Neighborhood, Socioeconomic, Deprivation, Spatial Epidemiology

  JOURNAL NAME: Open Journal of Statistics, Vol.6 No.3, June 14, 2016

  ABSTRACT: Neighborhood socioeconomic deprivation has been associated with health behaviors and outcomes. However, neighborhood socioeconomic status has been measured inconsistently across studies. It remains unclear whether appropriate socioeconomic indicators vary over geographic areas and geographic levels. The aim of this study is to compare the composite socioeconomic index to six socioeconomic indicators reflecting different aspects of socioeconomic environment by both geographic areas and levels. Using 2000 U.S. Census data, we performed a multivariate common factor analysis to identify significant socioeconomic resources and constructed 12 composite indexes at the county, the census tract, and the block group levels across the nation and for three states, respectively. We assessed the agreement between composite indexes and single socioeconomic variables. The component of the composite index varied across geographic areas. At a specific geographic region, the component of the composite index was similar at the levels of census tracts and block groups but different from that at the county level. The percentage of population below federal poverty line was a significant contributor to the composite index, regardless of geographic areas and levels. Compared with non-component socioeconomic indicators, component variables were more agreeable to the composite index. Based on these findings, we conclude that a composite index is better as a measure of neighborhood socioeconomic deprivation than a single indicator, and it should be constructed on an area- and unit-specific basis to accurately identify and quantify small-area socioeconomic inequalities over a specific study region.