Health inequalities across socio-economic groups: comparing geographic-area-based and individual-based indicators

Public Health. 2005 Dec;119(12):1097-104. doi: 10.1016/j.puhe.2005.02.008. Epub 2005 Sep 23.

Abstract

Objectives: To compare health inequality estimates obtained with different types of indicators of socio-economic status (SES), and study whether some of these are better predictors of health status, as indicated by observed disability data, than others.

Methods: Australian data were used to compare the use of the geographically based Socio-economic Index for Areas (SEIFA) in health inequality studies with two individual-based SES indicators able to account for family income and size. Inequalities in disability prevalences by SES were measured using age-standardized rate ratios. Logistic regression was used to determine which type of SES measure is a better predictor of the observed disability prevalences.

Results: Estimates of health inequalities obtained with the SEIFA were considerably lower than those obtained with the individual-based SES indicators. With the SEIFA, the proportion of disabled people amongst the most disadvantaged 20% of Australians was estimated to be 82% higher than amongst the most advantaged 20%, compared with over 150% with the individual-based SES measures. Also, the individual-based indicators were considerably better predictors of observed disability status than the SEIFA.

Conclusion: An individual-level SES indicator, such as one based on family income, is a better predictor of people with a disability than a geographic-area-based index. Also, the main reason for the considerably lower inequality estimates obtained with the SEIFA is that, unlike the individual-based indicators, such location-based indices cannot account for the significant, often age-related variations in SES that exist amongst people living in a particular area.

MeSH terms

  • Adolescent
  • Adult
  • Aged
  • Child
  • Child, Preschool
  • Disabled Persons
  • Female
  • Health Services Accessibility / economics*
  • Health Status*
  • Health Surveys
  • Humans
  • Infant
  • Infant, Newborn
  • Male
  • Middle Aged
  • Reproducibility of Results
  • Research Design / statistics & numerical data*
  • Socioeconomic Factors