Effect of community characteristics on familial clustering of end-stage renal disease

Am J Nephrol. 2009;30(6):499-504. doi: 10.1159/000243716. Epub 2009 Sep 30.

Abstract

Background: Lower socioeconomic status is generally associated with an increased risk of end-stage renal disease (ESRD). The relationship between community characteristics reflecting socioeconomic status and familial aggregation of common forms of ESRD has not been studied.

Methods: Demographic data and family history of ESRD were collected from 23,880 incident dialysis patients in ESRD Network 6 between 1995 and 2003. Addresses were geocoded and linked to the 2000 census 5-digit zip code-level database that includes community demographic, social and economic characteristics. Clustering of patients having a family history of ESRD at the community level was accounted for using a generalized estimating equations (GEE) model. Multivariate analysis estimated associations between family history of ESRD and community-level characteristics.

Results: Twenty-three percent of patients reported a family history of ESRD. After adjusting for individual demographic characteristics, multivariate analyses failed to reveal statistically significant relationships between a family history of ESRD and indicators of community socioeconomic status such as median household income, percentage high school graduates, percentage vacant housing units or ethnic composition.

Conclusions: Although select community measures of lower socioeconomic status may contribute to the familial clustering of ESRD, non-socioeconomic factors, potentially inherited, appear to be more important contributors to familial aggregation of the common forms of ESRD.

Publication types

  • Research Support, N.I.H., Extramural

MeSH terms

  • Aged
  • Censuses
  • Cluster Analysis
  • Databases, Factual
  • Educational Status
  • Family Characteristics
  • Family Health
  • Female
  • Geography
  • Humans
  • Incidence
  • Kidney Failure, Chronic / epidemiology*
  • Kidney Failure, Chronic / genetics*
  • Male
  • Middle Aged
  • Multivariate Analysis
  • Residence Characteristics / statistics & numerical data*
  • Risk Factors
  • Social Class