Evidence map›Paper›PMID 42057501›Full record

ArticleAddiction (Abingdon, England)2026

Age period cohort trends in alcohol treatment episodes across Australia from 2003 to 2022.

Wing See Yuen, Mia Miller, Nicola Man, Michael Livingston, Agata Chrzanowska, Philip Clare, Jane Akhurst, Louise Tierney, Kristina Da Silva, Parker Blakey and 4 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Addiction (Abingdon, England), 2026. 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

14 authors.

Wing See YuenNational Drug and Alcohol Research Centre, UNSW Sydney, Sydney, Australia.ORCID https://orcid.org/0000-0002-2791-6858
Mia MillerNational Drug and Alcohol Research Centre, UNSW Sydney, Sydney, Australia.ORCID https://orcid.org/0000-0003-0755-8624
Nicola ManNational Drug and Alcohol Research Centre, UNSW Sydney, Sydney, Australia.ORCID https://orcid.org/0000-0003-2224-9301
Michael LivingstonNational Drug Research Institute, enAble Institute, Faculty of Health Sciences, Curtin University, Perth, Australia.ORCID https://orcid.org/0000-0002-8995-9386
Agata ChrzanowskaNational Drug and Alcohol Research Centre, UNSW Sydney, Sydney, Australia.ORCID https://orcid.org/0000-0002-1811-7851
Philip ClareNational Drug and Alcohol Research Centre, UNSW Sydney, Sydney, Australia.ORCID https://orcid.org/0000-0002-2009-7386
Jane AkhurstAustralian Institute of Health and Welfare, Canberra, Australia.ORCID https://orcid.org/0000-0001-6542-2579
Louise TierneyAustralian Institute of Health and Welfare, Canberra, Australia.
Kristina Da SilvaAustralian Institute of Health and Welfare, Canberra, Australia.
Parker BlakeyAustralian Institute of Health and Welfare, Canberra, Australia.
Willow BryantAustralian Institute of Health and Welfare, Canberra, Australia.
Gary ChanNational Centre for Youth Substance Use Research, School of Psychology, The University of Queensland, Brisbane, Australia.ORCID https://orcid.org/0000-0002-7569-1948
Janni LeungNational Centre for Youth Substance Use Research, School of Psychology, The University of Queensland, Brisbane, Australia.ORCID https://orcid.org/0000-0001-5816-2959
Amy PeacockNational Drug and Alcohol Research Centre, UNSW Sydney, Sydney, Australia.ORCID https://orcid.org/0000-0002-5705-2026

Funding

Australian Government Department of Health, Disability and AgeingAustralian National Health and Medical Research Council 1174630Australian Research Council FT210100656New South Wales Ministry of Health
6 · The paper itself

Abstract

aimsTo measure trends in alcohol treatment episodes in Australia, disaggregated by age, period and birth cohort. DESIGN AND

settingAge, period, cohort modelling with restricted cubic splines, using Australian alcohol treatment administrative data from July 2002 to June 2022.

participants1 253 548 closed treatment episodes where alcohol was the primary drug of concern from people aged 10 to 100 years who received treatment for their own substance use in publicly funded specialist alcohol and other drug treatment services. MEASUREMENTS: Count of alcohol treatment episodes by age, period, birth cohort and sex.

findingsAlcohol treatment episode rates increased over time, peaking in 2022 (330.11 per 100 000 population). Age trends first peaked at around 21 years of age [cross-sectional prevalence = 444.30, 95% confidence interval (CI) = 440.82-447.80; longitudinal prevalence = 462.45, 95% CI = 458.06-466.89], followed by a lifetime peak between 37 and 44 years and declining with older age. Cohorts born from 1974 to 1979 had the highest alcohol treatment episode rates, and the oldest and youngest birth cohorts had the lowest alcohol treatment episode rates. Males were overall 1.8 times as likely as females to have an alcohol treatment episode, but this gap closed with more recent birth cohorts.

conclusionsAlcohol treatment episode rates increased in Australia between 2003 and 2022, and particularly from 2017. Young to middle-aged adults and people born in the 1970s were most at risk, alongside a persistent but narrowing gap between males and females.

Indexed as

AlcoholismAdolescentAdultAgedAged, 80 and overAge DistributionAge FactorsAustraliaChildCohort StudiesCross-Sectional StudiesFemaleHumansMaleMiddle AgedPrevalenceage period cohortalcoholalcohol epidemiologyalcohol treatmentdescriptive epidemiologytrends

Identifiers

PMID42057501
PMCPMC13357926

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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.