Evidence map›Paper›PMID 40169229›Full record

ArticleInternational journal of epidemiology2025

A novel tobacco forecasting model by multiple sociodemographic strata in Australia.

Samantha Howe, Tim Wilson, Coral Gartner, Tony Blakely, Driss Ait Ouakrim

Abstract read
In one paragraph

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

0numbers the graph read from it
0cells of the map it votes in
1citing 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

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

5 authors.

Samantha HoweMelbourne School of Population and Global Health, University of Melbourne, Parkville, Australia.ORCID 0000-0002-2793-6197
Tim WilsonMelbourne School of Population and Global Health, University of Melbourne, Parkville, Australia.
Coral GartnerSchool of Public Health, Faculty of Medicine, The University of Queensland, Brisbane, Australia.
Tony BlakelyMelbourne School of Population and Global Health, University of Melbourne, Parkville, Australia.ORCID 0000-0002-6995-4369
Driss Ait OuakrimMelbourne School of Population and Global Health, University of Melbourne, Parkville, Australia.

Funding

NHMRC Centre of Research Excellence on Achieving the Tobacco Endgame GNT1198301
6 · The paper itself

Abstract

backgroundAustralia is one of several countries aiming to achieve a commercial tobacco endgame, with a current target of ≤5% daily smoking prevalence by 2030. Like other jurisdictions, the Australian target ignores large variations in smoking across sociodemographic groups and risks perpetuating current smoking-related inequities. To help mitigate this risk, we calculated future smoking rates under business-as-usual for multiple sociodemographic categories and compared them to the endgame target.

methodsWe used a simulated annealing optimization approach to estimate historic daily smoking rates in Australia by six dimensions of sex, age, remoteness, index of relative socioeconomic advantage and disadvantage, and Indigenous status, using multiple datasets from 2001 to 2022-23. We applied logistic regression to the modelled outputs to forecast cohort smoking rates for 30 years.

resultsAt the population level, daily smoking is expected to reach 7.8% by 2030 under business-as-usual. Of the 15 strata combinations of remoteness and socioeconomic status in the model, only two met the ≤5% target by 2030, with smoking prevalence remaining highest (34.6% in 2030) for people living in the most disadvantaged (remote, SES1) areas.

conclusionsOur modelling suggests that if equity is not at the forefront of Australian tobacco policy, ongoing smoking disparities are likely to continue even if the endgame goal is achieved. Our approach offers a crucial baseline for assessing the impact of tobacco control interventions by different sociodemographic dimensions and presents a methodological framework that could be adapted for analysing smoking-related inequities in other jurisdictions. This framework should also be extended, incorporating uncertainty into modelled estimates.

Indexed as

SmokingAdolescentAdultAgedAustraliaFemaleForecastingHumansLogistic ModelsMaleMiddle AgedPrevalenceSociodemographic FactorsSocioeconomic FactorsYoung Adultforecastingpublic healthsocioeconomic disparities in healthstatistical modeltobacco smoking

Identifiers

PMID40169229
PMCPMC11961201

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.