Hiring in life sciences? Share your open positions with our professional community. Read more Close

Advertisement

A Model-Based National Estimate of Gambling Harm in Australia: Integrating Person-Counting with Health-Related Quality of Life Data.

Created on 10 Jul 2026

Authors

Catherine Tulloch, Matthew Browne

Published in

Journal of gambling studies. Jul 09, 2026. Epub Jul 09, 2026.

Abstract

Estimating the population-level impact of gambling harm has been historically challenged by inconsistent methods for counting affected individuals and quantifying their health loss. This study integrates two recent methodological advances, a novel reconciliation framework (Browne et al., 2026), and synthesised health disutility weights (Tulloch et al., 2026), and applies them to the 2025 Australian population. The model estimates that approximately 3.29 million Australians aged 5 years and over are affected annually by their own or another person's gambling, including approximately 1.38 million adult affected others and a reference-case estimate of a further 280,000 affected children. The model also indicates a concentration of harm among individuals experiencing dual exposure from both their own and another person's gambling; this group carries 25.9% of the total adult health burden despite representing only 11.2% of affected adults. The annual health loss associated with gambling-related harm in Australian adults is estimated at over 400,000 Years Lived with Disability (YLDs). These estimates should be interpreted as model-derived approximations conditional on the input assumptions and data sources. Requiring only the adult population size as input, the framework generates this full suite of estimates in a single transparent workflow, enabling direct replication by researchers or policymakers seeking a model-based estimate of the scope of gambling harm in the community.

PMID:
42426409
Bibliographic data and abstract were imported from PubMed on 10 Jul 2026.

Read full publication at:
Please sign in to see all details.

Advertisement

Stats

  • Community rating n/a 0 votes
  • Reviewers' rating n/a 0 votes
  • Your rating

1-terrible, 9-excellent. How would you rate this publication? Sign in in to submit your rating.

  • Recommendations n/a n/a positive of 0 vote(s)
  • Views 1
  • Comments 0

Recommended by

  • No recommendations yet.

Post a comment

You need to be signed in to post comments. You can sign in here.

Comments

There are no comments yet.

Advertisement