Yu Li, Nossal Institute for Global Health
Tim Adair, University of Melbourne
Accurate measurement of mortality and multiple causes of death (MCOD) is crucial given the increased importance of chronic diseases as causes of death. This study uses linked datasets to measure the contribution of MCOD to mortality and address the knowledge gap about socio-economic inequalities in chronic disease mortality in Australia. The study uses the Australian Bureau of Statistics (ABS) Person Linked Integrated Data Asset (PLIDA), which links individual-level data from death registrations with socio-economic data from the Population Census, and employs a range of methods to measure the contribution of MCOD to mortality and their individual- and area-level socio-economic inequalities. The study’s findings are expected to show that both individual- and area-level inequalities in chronic disease mortality in Australia are significant, irrespective of the method used to measure the contribution of MCOD to mortality. It will identify inequalities in mortality from specific chronic diseases and combinations of diseases, and how these differ by sex and age group. More generally, the findings can help refine existing mortality measurement frameworks by incorporating critical insights gained from MCOD analysis and provide a deeper understanding of how different contributing causes influence overall mortality trends across diverse population groups.
Keywords: Mortality and Longevity, Census data, Linked data sets