Poster Presentation ANZOS-Breakthrough Discoveries Joint Annual Scientific Meeting 2018

Cost-effectiveness of community-based obesity prevention interventions in Australia (#343)

Jaithri Ananthapavan 1 2 , Phuong Nguyen 1 2 , Steven J Bowe 3 , Gary Sacks 2 , Ana Maria Mantilla Herrera 4 , Boyd Swinburn 5 , Victoria Brown 1 2 , Rohan Sweeney 1 2 , Anita Lal 1 2 , Claudia Strugnell 2 , Marj Moodie 1 2
  1. Deakin Health Economics, Faculty of Health, Deakin University, Geelong, VIC, Australia
  2. Global Obesity Centre (GLOBE), Faculty of Health , Deakin University, Geelong, VIC, Australia
  3. Deakin Biostatistics Unit, Faculty of Health, Deakin University, Geelong, VIC, Australia
  4. School of Public Health, University of Queensland, Brisbane, Queensland, Australia
  5. School of Population Health, University of Auckland, Auckland, New Zealand

Background: Community-based interventions (CBIs) that include multifaceted community level strategies to increase physical activity and improve nutrition, implemented in multiple settings, have been shown to be effective in reducing unhealthy weight gain in children. This study synthesises the evidence of effectiveness of CBIs and assesses the cost-effectiveness of CBIs implemented in the Australian setting.

Methods: The effectiveness of CBIs, measured by mean difference in body mass index (BMI) z-scores between intervention and control communities, was determined by undertaking a scoping literature review and meta-analysis, using a random effects model, of trials published between 1990 and 2016. Although the strategies implemented are typically unique to each CBI community, for the purposes of this economic evaluation a generic hypothetical CBI appropriate for the Australian setting, incorporating commonly implemented strategies was costed (in 2010 Australian dollars). A multiple cohort Markov model that simulates diseases associated with overweight and obesity was used to estimate the long term health benefits and cost outcomes induced by reductions in BMI. Outcome measures were health adjusted life years (HALYs) saved, healthcare-related cost savings, and the incremental cost-effectiveness ratio (ICER). Health and cost outcomes were estimated over the lifetime of the target population (5-18 year olds).

Results: The meta-analysis revealed a small but significant difference in BMI z-score (mean difference of -0.07 (95% uncertainty interval (UI): -0.13 to -0.01) favouring the CBI community compared to the control. The net cost of implementing CBIs across all local government areas in Australia was approximately AUD426 million (M) (95% UI: AUD3M to AUD823M) over three years and resulted in savings of 51,792 HALYs (95% UI: 6,816 to 96,972). The mean ICER was AUD8,155 per HALY saved (95% UI: AUD237 to AUD81,021).

Conclusion: CBIs are cost-effective obesity prevention initiatives, however implementation across Australia would be expensive (relative to existing investments in prevention).