作者: Silviya P. Nikolova , Eusebius Small , Claudia Campillo
DOI: 10.1016/J.DHJO.2015.03.004
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摘要: Abstract Background In low and high income countries alike, disability exacerbates social, economic, health disparities, in spite of their differences. Objective This study seeks to identify factors that predict the circumstances people with disabilities face, including poverty. Methods A cross-sectional design was employed using census track level data for cities Monterrey, Nuevo Leon, Dallas, Texas, from Mexico 2010 USA 2000 collections. Two methods, spatial autocorrelation geographically weighted regression were used patterns explore relation between context-specific socio-demographic factors. Results indicated living below poverty line experience segregation levels semi-central zones Dallas. clustered central areas city. Geographically Weighted Regression (GWR) both analyses reported goodness fit (R ≥ 0.8 Dallas R ≥ 0.7 Monterrey data, respectively) predictability prevalence when social disadvantage such as unemployment, housing insecurity, household conditions, lack education present. Conclusions The divergent sometimes conflicting trends practices policies addressing environments renders a reexamination framework disability. An understanding local characteristics joins grounded socio-cultural various contexts shape location-based networks political decisions providing an analysis.