title: Disability Prevalence According to a Class, Race, and Sex (CSR) Hypothesis.
abstract: Disability has been shown to be related in definite ways to social class. In modern industrial societies, disability is influenced by and has the potential to contribute to the production and reproduction of social inequality. However, markers of social stratification processes are sometimes ignored determinants of health. A Class, Race, Sex (CRS) hypothesis is presented to argue that a "low-education disadvantage"; "racial-minority disadvantage"; and "female disadvantage" will compound to affect the risks for being disable. In particular, the CRS hypothesis posits that class is more important than race and the latter more than sex when predicting presence or severity of disability. The cross-sectional study of community-dwelling adults between the ages of 45 and 64 uses data from the American Community Survey (ACS) Public Use Microdata Sample (PUMS) 2008-2012 file. By using 3,429,523 individuals-which weighted equal to 61,726,420-the results of the study suggest the CRS hypothesis applies to both Non-Latino-Blacks and Non-Latino-Whites. There is a "male disadvantage" exception for Non-Latino-Whites. Decreasing between-group differences in health may be achieved by making the age-health association at lower socioeconomic stratum similar to that of the upper socioeconomic strata.
authors.affiliation: PhD, Department of Epidemiology, Graduate School of Public Health, University of Pittsburgh.
authors.forename: Carlos
authors.initials: C
authors.lastname: Siordia
mesh_terms: D001741:Black or African American / Q000706:statistics & numerical data*; D003430:Cross-Sectional Studies; D006233:Persons with Disabilities / Q000706:statistics & numerical data*; D005260:Female; D054624:Health Status Disparities; D006306:Health Surveys; D006801:Humans; D008297:Male; D008875:Middle Aged; D015995:Prevalence; D017678:Sex Distribution; D012923:Social Class; D014481:United States / Q000453:epidemiology; D044465:White People / Q000706:statistics & numerical data*
keywords: aging; function; inequality; public health; race