Evidence map›Paper›PMID 41190238›Full record

ArticleInternational journal of population data science2025

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

Fiona Stanaway, Lin Zhu, Bree McDonald, Jioji Ravulo, Michelle Dickson, Natasha Nassar, Mei Ling Yap, Louisa Jorm, Sarah Aitken, Leonard Kritharides and 6 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in International journal of population data science, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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0cells of the map it votes in
1citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

16 authors.

Fiona StanawaySydney School of Public Health, Faculty of Medicine and Health, University of Sydney, Sydney, NSW 2006, Australia.
Lin ZhuSydney School of Public Health, Faculty of Medicine and Health, University of Sydney, Sydney, NSW 2006, Australia.
Bree McDonaldSydney School of Public Health, Faculty of Medicine and Health, University of Sydney, Sydney, NSW 2006, Australia.
Jioji RavuloSydney School of Public Health, Faculty of Medicine and Health, University of Sydney, Sydney, NSW 2006, Australia.
Michelle DicksonSydney School of Public Health, Faculty of Medicine and Health, University of Sydney, Sydney, NSW 2006, Australia.
Natasha NassarSydney School of Public Health, Faculty of Medicine and Health, University of Sydney, Sydney, NSW 2006, Australia.
Mei Ling YapThe George Institute for Global Health, UNSW Sydney, Sydney, NSW 2000, Australia.
Louisa JormCentre for Big Data Research in Health, UNSW Sydney, Sydney, NSW 2052, Australia.
Sarah AitkenConcord General Hospital, Sydney Local Health District, Sydney, NSW 2139, Australia.
Leonard KritharidesConcord General Hospital, Sydney Local Health District, Sydney, NSW 2139, Australia.
Andrew WilsonSydney School of Public Health, Faculty of Medicine and Health, University of Sydney, Sydney, NSW 2006, Australia.
Fiona M BlythSydney School of Public Health, Faculty of Medicine and Health, University of Sydney, Sydney, NSW 2006, Australia.
Carmen Huckel SchneiderSydney School of Public Health, Faculty of Medicine and Health, University of Sydney, Sydney, NSW 2006, Australia.
Saman Khalatbari SoltaniSydney School of Public Health, Faculty of Medicine and Health, University of Sydney, Sydney, NSW 2006, Australia.
Benjumin HsuMarcus Institute for Aging Research, Harvard Medical School, Boston, MA 02115, United States of America.
Liz AllenCollege of Arts and Social Sciences, Australian National University, Canberra, ACT 0200, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

CensusesEthnicityHealth Status DisparitiesMortalityAdultAgedAustraliaCause of DeathFemaleHumansMaleMiddle AgedNew Zealandcensusdata linkageethnicityinequalitiesmortality

Identifiers

PMID41190238
PMCPMC12581141

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.