Segregation, income disparities, and survival in hemodialysis patients

J Am Soc Nephrol. 2013 Feb;24(2):293-301. doi: 10.1681/ASN.2012070659. Epub 2013 Jan 18.

Abstract

Social and ecologic factors, such as residential segregation, are determinants of health in the general population, but how these factors associate with outcomes among patients with ESRD is not well understood. Here, we examined associations of income inequality and residence, as social determinants of health, with survival among black and white patients with ESRD. We merged U.S. Renal Data System data from 589,036 patients who started hemodialysis from 2000 through 2008 with race-specific median household income data from the Census Bureau. We used Gini Index coefficients to assess income distributional inequality and the Dissimilarity Index to determine residential segregation. Black patients lived in areas of lower median household income compared with white patients ($26,742 versus $41,922; P<0.001). Residence in areas with higher median household income was associated with improved survival. Among whites, income inequality was associated with mortality. Among blacks exclusively, residence in highly segregated areas was associated with increased mortality. In conclusion, black hemodialysis patients in the United States are particularly susceptible to gradients in income and residential segregation. Interventions directed at highly segregated black neighborhoods might favorably affect hemodialysis patient outcomes.

MeSH terms

  • Aged
  • Aged, 80 and over
  • Black People / statistics & numerical data*
  • Black or African American
  • Censuses
  • Female
  • Housing / statistics & numerical data
  • Humans
  • Kidney Failure, Chronic* / ethnology
  • Kidney Failure, Chronic* / mortality
  • Kidney Failure, Chronic* / therapy
  • Male
  • Middle Aged
  • Poverty / statistics & numerical data*
  • Proportional Hazards Models
  • Racism / statistics & numerical data*
  • Renal Dialysis / mortality*
  • Socioeconomic Factors
  • United States / epidemiology
  • White People / statistics & numerical data*