Evidence map›Paper›PMID 34999874›Full record

ArticleInternational journal of epidemiology2022

Education-related inequalities in cause-specific mortality: first estimates for Australia using individual-level linked census and mortality data.

Jennifer Welsh, Grace Joshy, Lauren Moran, Kay Soga, Hsei-Di Law, Danielle Butler, Karen Bishop, Michelle Gourley, James Eynstone-Hinkins, Heather Booth and 5 more

Open access · bronzeAbstract read
In one paragraph

Article in International journal of epidemiology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
1.3field-weighted citation impact, top 17% of its field
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

11 citing papers in PubMed, 16 citations in OpenAlex.

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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

15 authors at 4 institutions in 2 countries.

Jennifer WelshResearch School of Population Health, Australian National University.ORCID 0000-0003-4415-5920
Grace JoshyResearch School of Population Health, Australian National University.
Lauren MoranAustralian Bureau of Statistics.
Kay SogaResearch School of Population Health, Australian National University.
Hsei-Di LawResearch School of Population Health, Australian National University.
Danielle ButlerResearch School of Population Health, Australian National University.
Karen BishopResearch School of Population Health, Australian National University.
Michelle GourleyAustralian Institute of Health and Welfare.
James Eynstone-HinkinsAustralian Bureau of Statistics.
Heather BoothSchool of Demography, Australian National University.
Lynelle MoonAustralian Institute of Health and Welfare.
Nicholas BiddleCentre for Social Research and Methods, Australian National University.
Antony BlakelyMelbourne School of Population and Global Health, University of Melbourne and.
Emily BanksResearch School of Population Health, Australian National University.
Rosemary J KordaResearch School of Population Health, Australian National University.
Australian National University · AUAustralian Bureau of Statistics · AUAustralian Institute of Health and Welfare · AUThe University of Melbourne · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSocioeconomic inequalities in mortality are evident in all high-income countries, and ongoing monitoring is recommended using linked census-mortality data. Using such data, we provide the first estimates of education-related inequalities in cause-specific mortality in Australia, suitable for international comparisons.

methodsWe used Australian Census (2016) linked to 13 months of Death Registrations (2016-17). We estimated relative rates (RR) and rate differences (RD, per 100 000 person-years), comparing rates in low (no qualifications) and intermediate (secondary school) with high (tertiary) education for individual causes of death (among those aged 25-84 years) and grouped according to preventability (25-74 years), separately by sex and age group, adjusting for age, using negative binomial regression.

resultsAmong 13.9 M people contributing 14 452 732 person-years, 84 743 deaths occurred. All-cause mortality rates among men and women aged 25-84 years with low education were 2.76 [95% confidence interval (CI): 2.61-2.91] and 2.13 (2.01-2.26) times the rates of those with high education, respectively. We observed inequalities in most causes of death in each age-sex group. Among men aged 25-44 years, relative and absolute inequalities were largest for injuries, e.g. transport accidents [RR = 10.1 (5.4-18.7), RD = 21.2 (14.5-27.9)]). Among those aged 45-64 years, inequalities were greatest for chronic diseases, e.g. lung cancer [men RR = 6.6 (4.9-8.9), RD = 57.7 (49.7-65.8)] and ischaemic heart disease [women RR = 5.8 (3.7-9.1), RD = 20.2 (15.8-24.6)], with similar patterns for people aged 65-84 years. When grouped according to preventability, inequalities were large for causes amenable to behaviour change and medical intervention for all ages and causes amenable to injury prevention among young men.

conclusionsAustralian education-related inequalities in mortality are substantial, generally higher than international estimates, and related to preventability. Findings highlight opportunities to reduce them and the potential to improve the health of the population.

Indexed as

CensusesMortalityAdultAgedAged, 80 and overAustraliaCause of DeathEducational StatusFemaleHumansMaleMiddle AgedSocioeconomic FactorsAustraliacause-specific mortalityeducationhealth inequalitieslinked datamortalitysocioeconomic position

Identifiers

PMID34999874
PMCPMC8743133
OpenAlexW3166685473

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.