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RESEARCH ARTICLE
Contents Vol 49(3)

A guide to using measures of socio-economic status, remoteness and population denominators from the Australian Bureau of Statistics for epidemiological studies

David Youens A C * , Nita Sodhi-Berry A , Ingrid Stacey A B , Marwan Ahmed A and Judith M. Katzenellenbogen A
+ Author Affiliations
- Author Affiliations

A Cardiovascular Epidemiology Research Centre, School of Population and Global Health, The University of Western Australia, Nedlands, WA, Australia.

B Cardiology Population Health Laboratory, Victor Chang Cardiac Research Institute, Nedlands, WA, Australia.

C Present address: School of Population Health, Curtin University, Building 400, Kent Street, Bentley, WA 6102, Australia.

* Correspondence to: david.youens@curtin.edu.au

Australian Health Review 49, AH24324 https://doi.org/10.1071/AH24324
Submitted: 28 November 2024  Accepted: 26 April 2025  Published: 19 May 2025

© 2025 The Author(s) (or their employer(s)). Published by CSIRO Publishing on behalf of AHHA.

Abstract

Objective

Australian Bureau of Statistics data on socio-economic status, service accessibility/remoteness and population denominators are useful in epidemiology, though complex to understand and apply. We provide information and resources to facilitate their use.

Methods

We compiled data from the Socio-Economic Indexes for Areas (SEIFA), the Accessibility/Remoteness Index of Australia (ARIA) and population estimates from across multiple years, taking into account changes in availability and formats of these data over time. Syntax was written to support use of these data in studies using administrative health data, alongside a user guide with notes and instructions.

Results

Where research data contains an event date plus a postcode, Statistical Area Level 2 and/or Statistical Local Area, these resources can be used to attach a SEIFA score and decile, remoteness areas and age-sex-specific population denominators to each record for years 2000–2025 (population denominators to 2023). These variables can be used as cohort descriptors, as model covariates or to calculate ARIA/SEIFA stratified rates.

Conclusions

These resources are useful for individual research projects, while also contributing to building capacity in the use of geographical measures. We focused on the measures most commonly used in Australia, although the approach outlined can be applied to other geographical measures.

Keywords: Accessibility/Remoteness Index of Australia, administrative health data, census data, epidemology, longitudinal studies, population denominators, population health, Socio-Economic Indexes for Areas.

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