Evidence map›Paper›PMID 40017932›Full record

ArticleBMJ public health2025

Insights from a codesigned dynamic modelling study of child and adolescent obesity in Australia.

Simon Keith Chiu, Louise A Baur, Jo-An Occhipinti, Joseph Carrello, Rebecca K Golley, Alison Hayes, Kylie E Hunter, L Kurt Kreuger, Kenny Lawson, Anthony D Okely and 3 more

Abstract read
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In one paragraph

Article in BMJ public health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed, 2 pooled it
–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

4 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Article
  4. 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

13 authors.

Simon Keith ChiuThe University of Newcastle Hunter Medical Research Institute, Newcastle, New South Wales, Australia.ORCID 0000-0001-7351-6508
Louise A BaurSchool of Public Health, University of Sydney, Sydney, New South Wales, Australia.ORCID 0000-0002-4521-9482
Jo-An OcchipintiThe Bain and Mind Centre, The University of Sydney, Sydney, New South Wales, Australia.ORCID 0000-0002-2380-1092
Joseph CarrelloMelbourne School of Population and Global Health, Centre for Health Policy, University of Melbourne, Melbourne, Victoria, Australia.ORCID 0000-0001-6423-6555
Rebecca K GolleyFlinders University Caring Futures Institute, Adelaide, South Australia, Australia.ORCID 0000-0001-5197-7987
Alison HayesSchool of Public Health, University of Sydney, Sydney, New South Wales, Australia.ORCID 0000-0002-8679-6040
Kylie E HunterNHMRC Clinical Trials Centre, University of Sydney, Sydney, New South Wales, Australia.ORCID 0000-0002-2796-9220
L Kurt KreugerKreuger Consulting, Fort Worth, Texas, USA.ORCID 0000-0002-7163-564X
Kenny LawsonWestern Sydney University, Penrith, New South Wales, Australia.ORCID 0000-0002-9959-2442
Anthony D OkelySchool of Health and Society, University of Wollongong, Wollongong, New South Wales, Australia.ORCID 0000-0002-1626-8170
Anna Lene SeidlerNHMRC Clinical Trials Centre, University of Sydney, Sydney, New South Wales, Australia.ORCID 0000-0002-0027-1623
Rebecca WyseSchool of Medicine and Public Health, The University of Newcastle, Newcastle, New South Wales, Australia.ORCID 0000-0002-4872-2112
Louise FreebairnThe Australian Prevention Partnership Centre, The Sax Institute, Sydney, New South Wales, Australia.ORCID 0000-0002-7434-870X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Child and adolescent obesity is associated with a range of immediate health issues and influences obesity in adulthood. The complex nature of health determinants that contribute to obesity makes it challenging to deliver effective public health interventions. This research presents insights from a system dynamics model of childhood and adolescent obesity aimed at supporting evidence-based decision-making. Methods: A system dynamics model was developed using the best available evidence and data, with input from research and industry experts to map the hypothetical causal structure of the factors contributing to childhood and adolescent obesity in Australia. The model was calibrated to fit the historical prevalence of obesity ( Results: A series of interventions were explored in the model, including changes in early childhood behaviours, changes to diet and physical activity in childcare and school settings, financial support for organised sports and sugar-sweetened beverage taxation. The most promising individually implemented intervention scenario for reducing the prevalence of childhood and adolescent obesity was a sugar-sweetened beverage tax (0.57 percentage points and 0.61 percentage points, respectively) and government funding of organised sports (0.42 percentage points and 0.63 percentage points, respectively). When all interventions were implemented in combination, childhood obesity was reduced by 1.43 percentage points and 1.81 percentage points in adolescents. Conclusions: The findings highlight the challenges faced by policy-makers and public health practitioners working to reduce childhood and adolescent obesity. Insights from the model emphasise the value of public health programmes over the life course. Implementing initiatives with broad reach that support healthy choices may reduce obesity, resulting in a healthier Australian population.

Indexed as

Body Mass IndexEpidemiologyPublic Health

Identifiers

PMID40017932
PMCPMC11812886

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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.