Using linked Census ancestry data to examine all-cause mortality by ethnicity in Australia

利用关联的人口普查祖籍数据,研究澳大利亚各族裔的全因死亡率

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Abstract

INTRODUCTION: Ethnicity in Australia's non-Indigenous population is not collected routinely in health data but the proxy of ancestry is collected in the Census. OBJECTIVES: We aimed to develop an approach to using ancestry data to examine health inequalities by ethnicity in Australia's non-Indigenous population. We then applied this to the example of all-cause mortality. METHODS: We established an expert and community panel to inform our approach to categorising ancestry data. This included shifting those identifying as 'Australian' or 'New Zealander' from the Oceanian to the European continental category; prioritising ethnic minority identities over national identities in those with two ancestries; and examining outcomes using the smallest ethnicity categories possible. We examined how results compared to existing approaches based on country of birth or ancestry (without our modifications) in the detection of mortality inequalities using 2016 Australian Census data linked to death registrations for 2016-2021 in 20.3 million people. RESULTS: We found important differences in mortality inequalities observed in Māori and Pasifika populations in Australia based on the method used. Ancestry data was able to demonstrate significantly higher mortality that was not observed when using country of birth in Māori females (747 vs 507 per 100,000 person-years), Melanesian and Papuan males (1684 vs 617 per 100,000 person-years) and Polynesian males and females (928 vs 724 in males and 693 vs 569 per 100,000 person-years in females). The size of the inequalities observed was larger using our expert and community informed approach compared to existing approaches (e.g. Polynesian males 928 vs 853 per 100,000 person-years). CONCLUSIONS: We demonstrated an approach to using ancestry data from the Australian Census that improved identification of mortality inequalities in Māori and Pasifika ethnic groups. Inequalities were either hidden or underestimated when country of birth or the standard approach to ancestry data was used.

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