摘要
Racial residential segregation in the United States is generally associated differences in health outcomes among Blacks and Whites due to differential exposures to physical, social and economic resources. While several studies have explored the association between segregation and several chronic conditions in the US, few have specifically examined diabetes using a nationally representative population-based sample. The current study relies on 2005 data from both the Behavioral Risk Factor Surveillance Survey (BRFSS) and the American Community Survey (ACS) to explore the association between segregation, socioeconomic status and diabetes. Using multilevel mixed-effects logistic regression, we present models that account for clustering of individuals within metropolitan areas and are adjusted for objective environmental measures (including segregation) and potential individual-level confounders (including education, employment, and income) among a sample of 121,321 adults who were at least 18 years old. After controlling for individual-level factors, Blacks residing in highly segregated areas have the same odds of being diagnosed with diabetes as Whites. Whites are more likely to be diagnosed with diabetes in areas where there are higher percentages of Blacks than in areas with low Black representation. Moreover, in this national sample, there is no statistical association between Blacks residing in highly segregated neighborhoods and diabetes risk. However, the increased prevalence of diabetes among Whites living in Black metropolitan areas suggests that future studies are needed to explore the linkages between levels of segregation and diabetes risk.
Racial residential segregation in the United States is generally associated differences in health outcomes among Blacks and Whites due to differential exposures to physical, social and economic resources. While several studies have explored the association between segregation and several chronic conditions in the US, few have specifically examined diabetes using a nationally representative population-based sample. The current study relies on 2005 data from both the Behavioral Risk Factor Surveillance Survey (BRFSS) and the American Community Survey (ACS) to explore the association between segregation, socioeconomic status and diabetes. Using multilevel mixed-effects logistic regression, we present models that account for clustering of individuals within metropolitan areas and are adjusted for objective environmental measures (including segregation) and potential individual-level confounders (including education, employment, and income) among a sample of 121,321 adults who were at least 18 years old. After controlling for individual-level factors, Blacks residing in highly segregated areas have the same odds of being diagnosed with diabetes as Whites. Whites are more likely to be diagnosed with diabetes in areas where there are higher percentages of Blacks than in areas with low Black representation. Moreover, in this national sample, there is no statistical association between Blacks residing in highly segregated neighborhoods and diabetes risk. However, the increased prevalence of diabetes among Whites living in Black metropolitan areas suggests that future studies are needed to explore the linkages between levels of segregation and diabetes risk.
