title: Prognostic relevance of census-derived individual respondent incomes versus household incomes.
abstract: BACKGROUND
  Census-based measures of income derived from median income of a geographic area are often used in health research. Many national census surveys gather information on both the respondent's individual income and the income for the entire household, giving researchers a choice of census income measures. We compared the extent to which individual respondent income and household income (both obtained from census data) are associated with outcomes in a cohort of patients with cardiac disease.
  
  
  METHODS
  We used data from the Alberta Provincial Project for Outcome Assessment in Coronary Heart Disease (APPROACH), where postal codes were linked to the Postal Code Conversion File (PCCF) to determine each patient's census Dissemination Areas (DA). DA-derived median household income and median individual income were obtained from the 2001 Canadian Census and survival outcomes were then directly determined for income groupings defined by quintile. Two-year survival adjusted for age and sex was described with a proportional hazards analysis.
  
  
  RESULTS
  There were 9,397 patients undergoing cardiac catheterization between January 1, 2001 and March 31, 2002, with complete DA-level median income measures. Household income quintiles yielded a wider spread of survival across quintiles (range of 2-year estimated survival, 91.8% to 95.9% for household income versus 92.8% to 95.6% for respondent income), as well as a more progressive decline in survival as income decreased. This progressive decline was not seen for the respondent income measure.
  
  
  CONCLUSIONS
  The greater spread and progressive decline of survival for household income relative to respondent income leads us to conclude that household income is the better socio-economic determinant of health in our data and for the outcome measure we studied.
authors.affiliation: University of Calgary, Calgary, AB, Department of Community Health Sciences.
authors.forename: Danielle A
authors.initials: DA
authors.lastname: Southern
authors.forename: Peter D
authors.initials: PD
authors.lastname: Faris
authors.forename: Merril L
authors.initials: ML
authors.lastname: Knudtson
authors.forename: William A
authors.initials: WA
authors.lastname: Ghali
mesh_terms: D000368:Aged; D000416:Alberta / Q000453:epidemiology; D006328:Cardiac Catheterization / Q000191:economics / Q000401:mortality*; D019352:Censuses; D015331:Cohort Studies; D005191:Family Characteristics; D005260:Female; D005843:Geography; D006801:Humans; D007182:Income / Q000145:classification* / Q000706:statistics & numerical data; D008297:Male; D008875:Middle Aged; D017063:Outcome Assessment, Health Care / Q000379:methods*; D011177:Postal Service; D011203:Poverty / Q000706:statistics & numerical data; D016016:Proportional Hazards Models; D012923:Social Class; D016019:Survival Analysis