Using Linked Whole-Of-Population Data to Estimate Education-Related Inequalities in Cause-Specific Mortality in Australia

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Jennifer Welsh
Grace Joshy
Lauren Moran
Kay Soga
Hsei Di Law
Danielle Butler
Karen Bishop
Michelle Gourley
James Eynstone-Hinkins
Lynelle Moon
Anthony Blakely
Emily Banks
Rosemary J Korda


Official Australian estimates of socioeconomic inequalities in cause-specific mortality have been based on area-level socioeconomic measures. Using area-level measures is known to underestimate inequalities.

Objectives and Approach
Using recently released census linked to mortality data, we estimate education-related inequalities in cause-specific mortality for Australia. We used 2016 Australian Census and Death Registration data (2016-17) linked via a Person Linkage Spine (linkage rates: 92% and 97%, respectively) from the Multi-Agency Data Integration Project (MADIP). Education, from the Census, was categorised as low (no secondary school graduation or other qualification), intermediate (secondary graduation with/without other non-tertiary qualifications) and high (tertiary qualification). Cause of death was coded according to the underlying cause of death using the ICD-10. We used negative binomial regression to estimate relative rates (RR) for cause-specific mortality at ages 25-84 years, in the 12-months following Census, comparing low vs high education, separately by sex and 20-year age group, adjusting for age.

80,317 deaths occurred among 13,856,202 people. For those aged 25-44 years, relative inequalities were large for causes related to injury and smaller for less
preventable deaths (e.g. for men, suicide RR=5.6, 95%CI: 4.1-7.5 and brain cancer RR=1.3, 0.6-3.1). For those aged 45-64, inequalities were large for causes related to health behaviours and amenable to medical intervention, e.g. lung cancer (men RR= 6.4, 4.7-8.8) and ischaemic heart disease (women RR=5.0, 3.2-7.7), and were small for less preventable causes e.g. brain cancer (women RR=0.9, 0.6-1.3). Patterns among those aged 65-84years were similar to those aged 45-64 years.

Conclusion / Implications
In Australia, inequalities in mortality are substantial. Our findings highlight the health burden from inequalities, opportunities for prevention and provide insights on targets to effectively reduce them.

Article Details

How to Cite
Welsh, J., Joshy, G., Moran, L., Soga, K., Law, H. D., Butler, D., Bishop, K., Gourley, M., Eynstone-Hinkins, J., Moon, L., Blakely, A., Banks, E. and Korda, R. J. (2020) “Using Linked Whole-Of-Population Data to Estimate Education-Related Inequalities in Cause-Specific Mortality in Australia”, International Journal of Population Data Science, 5(5). doi: 10.23889/ijpds.v5i5.1555.

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