title: Invited commentary: residential segregation and health--the complexity of modeling separate social contexts.
abstract: When researching racial disparities in health, residential segregation cannot be ignored. Because of segregation, contextual differences by race are so pronounced that ignoring them may lead to mis-estimating the effect of individual-level factors. However, given the stark racial separation of social contexts, researching how residential segregation and neighborhood inequality contribute to racial health disparities remains methodologically challenging. Estimating the contribution of neighborhood effects to health disparities would require overlap in the racial distributions of neighborhood environment, for example, in the distributions of neighborhood poverty. Because of segregation, though, the extent of such overlap is extremely restricted. Previous analyses of the 2000 US Census found, on average, only a 24% overlap between the distribution of neighborhood poverty for black children and that for white children in metropolitan areas. Propensity score methods may be 1 useful tool for addressing limited overlap or exchangeability. However, as shown by their application to the segregation and health relation, their use should be informed by a sound conceptualization of the scale of the social exposure of interest, the hypothesized pathways between the exposure and the health outcome, and possible unmeasured confounders.
authors.affiliation: Department of Society, Human Development and Health, Harvard School of Public Health, 766 Huntington Avenue, Boston, MA 02115, USA. dacevedo@hsph.harvard.edu
authors.forename: Dolores
authors.initials: D
authors.lastname: Acevedo-Garcia
authors.forename: Theresa L
authors.initials: TL
authors.lastname: Osypuk
mesh_terms: D000328:Adult; D001741:Black or African American / Q000706:statistics & numerical data*; D001719:Birth Certificates; D003644:Death Certificates; D005260:Female; D006304:Health Status; D006801:Humans; D007223:Infant; D007226:Infant Mortality; D007231:Infant, Newborn; D038801:International Classification of Diseases; D008297:Male; D008875:Middle Aged; D011287:Prejudice; D012042:Registries; D012111:Residence Characteristics / Q000706:statistics & numerical data*; D012934:Social Isolation; D014481:United States / Q000208:ethnology; D044465:White People / Q000706:statistics & numerical data*