Evidence map›Paper›PMID 40130290›Full record

ArticleInternal medicine journal2025

Shorter-term and longer-term mortality prediction in the Australian Diabetes, Obesity and Lifestyle (AusDiab) study.

Dunya Tomic, Agus Salim, Elizabeth L M Barr, Paul Z Zimmet, Dianna J Magliano, Jonathan E Shaw

Abstract read
In one paragraph

Article in Internal medicine journal, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
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

2 citing papers in PubMed.

  1. Article
  2. 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

6 authors.

Dunya TomicSchool of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia.ORCID 0000-0003-2471-2523
Agus SalimDiabetes and Population Health, Baker Heart and Diabetes Institute, Melbourne, Victoria, Australia.
Elizabeth L M BarrDiabetes and Population Health, Baker Heart and Diabetes Institute, Melbourne, Victoria, Australia.
Paul Z ZimmetDepartment of Diabetes, Monash University, Melbourne, Victoria, Australia.
Dianna J MaglianoSchool of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia.
Jonathan E ShawSchool of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia.

Funding

Abbott Australasia Pty LtdAlphapharm Pty LtdAmgen AustraliaAstraZeneca AustraliaBristol-Myers SquibbCilagDepartment of Health and Aged Care, Australian GovernmentEli Lilly AustraliaEstate of the Late Edward WilsonGlaxoSmithKline AustraliaJack Brockhoff FoundationKidney Health AustraliaMarian & FH Flack TrustMerck Sharp and Dohme AustraliaNational Health and Medical Research Council 1007544National Health and Medical Research Council 233200Novartis AustraliaNovo NordiskPfizer AustraliaPratt FoundationRoche DiagnosticsSanofi Australiasanofi-synthelabo
6 · The paper itself

Abstract

backgroundWhile identification of key risk factors for mortality has contributed to advances in healthcare, the effect of these risk factors in predicting mortality over different time horizons remains unclear.

aimsWe sought to determine how risk factors predicted shorter-term and longer-term mortality across the age spectrum in adults.

methodsWe used data from 11 247 adults of the Australian Diabetes, Obesity and Lifestyle (AusDiab) study. Cox multivariable regression models were used to estimate hazard ratios (HRs) of shorter-term (0-10 years) and longer-term (10-20 years) all-cause and cardiovascular disease (CVD)-related mortality associated with risk factors. Models with interaction between baseline age and each risk factor were also fitted.

resultsDuring a 20-year follow-up, 2185 deaths occurred. Smoking, diabetes, male sex and albuminuria all independently predicted shorter- and longer-term all-cause and CVD mortality. Most associations were stronger in the shorter term compared to the longer term. A notable exception was the association between smoking and CVD mortality, which was stronger in the longer term (HR 3.55, 95% confidence interval (CI) 2.57-4.90) compared to the shorter term (HR 2.06, 95% CI 1.33-3.20). The magnitude of association between most risk factors and mortality attenuated with age.

conclusionsClassical risk factors for total and CVD mortality remain important up to 20 years after their measurement. In unselected adult cohorts, longer-term follow-up (e.g. beyond 10 years) may not provide additional information on associations of risk factors with mortality beyond that obtained in shorter-term follow-up.

Indexed as

Cardiovascular DiseasesDiabetes MellitusLife StyleObesityAdultAgedAustraliaFemaleFollow-Up StudiesHumansMaleMiddle AgedMortalityRisk FactorsSmokingTime Factorscardiovascular diseasecohort studydiabetes mellitusmortalityrisk factor

Identifiers

PMID40130290
PMCPMC12155081

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.