Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Article
  • Published:

Cost-effectiveness of community-based childhood obesity prevention interventions in Australia

International Journal of Obesity volume 43, pages 1102–1112 (2019)Cite this article

Subjects

Abstract

Objectives

The objective of this study is to examine, from a limited societal perspective, the cost-effectiveness of community-based obesity prevention interventions (CBIs)-defined as a programme of community-level strategies to promote healthy eating and physical activity for Australian children (aged 5–18 years).

Methods

The effectiveness of CBIs was determined by undertaking a literature review and meta-analysis. Commonly implemented strategies to increase physical activity and improve nutrition were costed (in 2010 Australian dollars) to determine the average cost of a generic programme. A multiple cohort Markov model that simulates diseases associated with overweight and obesity was used to estimate the health benefits, measured as health-adjusted life years (HALYs) and healthcare-related cost offsets from diseases averted due to exposure to the intervention. Health and cost outcomes were estimated over the lifetime of the target population. Monte-Carlo simulation was used to assess second-order uncertainty of input parameters to estimate mean incremental cost-effectiveness ratios (ICER) with 95% uncertainty intervals (UIs). Scenario analyses tested variations in programme intensity, target population, and duration of effect.

Results

The meta-analysis revealed a small but significant difference in BMI z-score (mean difference of − 0.07 (95% UI: − 0.13 to − 0.01)) favouring the CBI community compared with the control. The estimated net cost of implementing CBIs across all local government areas (LGAs) in Australia was AUD426M (95% UI: AUD3M to AUD823M) over 3 years. This resulted in 51,792 HALYs gained (95% UI: 6816 to 96,972) over the lifetime of the cohort. The mean ICER was AUD8155 per HALY gained (95% UI: AUD237 to AUD81,021), with a 95% probability of being cost-effective at a willingness to pay threshold of AUD50,000 per HALY.

Conclusions

CBIs are cost-effective obesity prevention initiatives; however, implementation across Australia will be (relatively) expensive when compared with current investments in preventive health.

This is a preview of subscription content, access via your institution

Access options

Buy this article

  • Purchase on Springer Link
  • Instant access to full article PDF
Buy now

Prices may be subject to local taxes which are calculated during checkout

Fig. 1

Similar content being viewed by others

References

  1. Abarca-Gómez L, Abdeen ZA, Hamid ZA, Abu-Rmeileh NM, Acosta-Cazares B, Acuin C, et al. Worldwide trends in body-mass index, underweight, overweight, and obesity from 1975 to 2016: a pooled analysis of 2416 population-based measurement studies in 128· 9 million children, adolescents, and adults. Lancet. 2017;390:2627–42.

    Article  Google Scholar 

  2. Australian Institute of Health and Welfare. Australia’s health 2016. Canberra: AIHW; 2016.

    Google Scholar 

  3. Duckett S, Swerissen H, Wiltshire T. A sugary drinks tax: recovering the community costs of obesity. Melbourne: Grattan Institute; 2016.

  4. Colagiuri S, Lee CM, Colagiuri R, Magliano D, Shaw JE, Zimmet PZ, et al. The cost of overweight and obesity in Australia. Med J Aust. 2010;192:260–4.

    PubMed  Google Scholar 

  5. Swinburn BA, Sacks G, Hall KD, McPherson K, Finegood DT, Moodie ML, et al. The global obesity pandemic: shaped by global drivers and local environments. Lancet. 2011;378:804–14.

    Article  Google Scholar 

  6. Wolfenden L, Wyse R, Nichols M, Allender S, Millar L, McElduff P. A systematic review and meta-analysis of whole of community interventions to prevent excessive population weight gain. Prev Med. 2014;62:193–200.

    Article  Google Scholar 

  7. Waters E, Silva-Sanigorski Ad, Burford BJ, Brown T, Campbell KJ, Gao Y, et al. Interventions for preventing obesity in children. Cochrane Database Syst Rev. 2011;12:128–9.

    Google Scholar 

  8. Swinburn B, Malakellis M, Moodie M, Waters E, Gibbs L, Millar L, et al. Large reductions in child overweight and obesity in intervention and comparison communities 3 years after a community project. Pediatr Obes. 2014;9:455–62.

    Article  CAS  Google Scholar 

  9. Rush E, McLennan S, Obolonkin V, Vandal AC, Hamlin M, Simmons D, et al. Project Energize: whole-region primary school nutrition and physical activity programme; evaluation of body size and fitness 5 years after the randomised controlled trial. Br J Nutr. 2014;111:363–71.

    Article  CAS  Google Scholar 

  10. Borys JM, Le Bodo Y, Jebb SA, Seidell J, Summerbell C, Richard D, et al. EPODE approach for childhood obesity prevention: methods, progress and international development. Obes Rev. 2012;13:299–315.

    Article  Google Scholar 

  11. Romon M, Lommez A, Tafflet M, Basdevant A, Oppert JM, Bresson JL, et al. Downward trends in the prevalence of childhood overweight in the setting of 12-year school-and community-based programmes. Public Health Nutr. 2009;12:1735–42.

    Article  Google Scholar 

  12. Flego A, Keating C, Moodie M. Cost–effectiveness of whole-of-community obesity prevention programs: an overview of the evidence. Expert Rev Pharm Outcomes Res. 2015;14:719–27.

    Google Scholar 

  13. Bleich SN, Segal J, Wu Y, Wilson R, Wang Y. Systematic review of community-based childhood obesity prevention studies. Pediatrics. 2013;132:p201–10.

    Article  Google Scholar 

  14. Liberati A, Altman DG, Tetzlaff J, Mulrow C, Gøtzsche PC, Ioannidis JP, et al. The PRISMA statement for reporting systematic reviews and meta-analyses of studies that evaluate health care interventions: explanation and elaboration. PLoS Med. 2009;6:e1000100.

    Article  Google Scholar 

  15. EPHPP. Quality assessment tool for quantitative studies: Effective Public Health Practice Project 2010 [Available from: http://www.ephpp.ca/PDF/Quality%20Assessment%20Tool_2010_2.pdf].

  16. Duval S, Tweedie R. A nonparametric “trim and fill” method of accounting for publication bias in meta-analysis. J Am Stat Assoc. 2000;95:89–98.

    Google Scholar 

  17. Borys J, Valdeyron L, Levy E, Vinck J, Edell D, Walter L, et al. EPODE a model for reducing the incidence of obesity and weight-related comorbidities. Endocrinology. 2013;9:32–6.

    Google Scholar 

  18. Brown V, Moodie M, Cobiac L, Herrera AM, Carter R. Obesity-related health impacts of fuel excise taxation-an evidence review and cost-effectiveness study. BMC Public Health. 2017;17:359.

    Article  CAS  Google Scholar 

  19. Lal A, Mantilla-Herrera AM, Veerman L, Backholer K, Sacks G, Moodie M, et al. Modelled health benefits of a sugar-sweetened beverage tax across different socioeconomic groups in Australia: a cost-effectiveness and equity analysis. PLoS Med. 2017;14:e1002326.

    Article  Google Scholar 

  20. Crino M, Herrera AMM, Ananthapavan J, Wu JH, Neal B, Lee YY, et al. Modelled cost-effectiveness of a package size cap and a kilojoule reduction intervention to reduce energy intake from sugar-sweetened beverages in Australia. Nutrients. 2017;9:983.

    Article  Google Scholar 

  21. Brown V, Ananthapavan J, Veerman L, Sacks G, Lal A, Peeters A, et al. The potential cost-effectiveness and equity impacts of restricting television advertising of unhealthy food and beverages to Australian children. Nutrients. 2018;10:622.

    Article  Google Scholar 

  22. Mantilla Herrera A, Crino M, Erskine H, Sacks G, Ananthapavan J, Mhurchu C, et al. Cost-effectiveness of product reformulation in response to the health star rating food labelling system in Australia. Nutrients. 2018;10:614.

    Article  Google Scholar 

  23. Barendregt JJ, Veerman JL. Categorical versus continuous risk factors and the calculation of potential impact fractions. J Epidemiol Community Health. 2010;64:209–12.

    Article  Google Scholar 

  24. Murray CJ, Abraham J, Ali MK, Alvarado M, Atkinson C, Baddour LM, et al. The state of US health, 1990-2010: burden of diseases, injuries, and risk factors. JAMA. 2013;310:591–606.

    Article  CAS  Google Scholar 

  25. Global Burden of Disease Study 2010 (GBD 2010). Results by risk factor 1990–2010 [Internet]. Institute for Health Metrics and Evaluation (IHME); 2012. Available from: http://www.healthdata.org.

  26. Australian Bureau of Statistics. 2011 Census of population and housing. Canberra: Australian Bureau of Statistics; 2012.

  27. Salomon JA, Vos T, Hogan DR, Gagnon M, Naghavi M, Mokdad A, et al. Common values in assessing health outcomes from disease and injury: disability weights measurement study for the Global Burden of Disease Study 2010. Lancet. 2012;380:2129–43.

    Article  Google Scholar 

  28. Chen G, Ratcliffe J, Olds T, Magarey A, Jones M, Leslie E. BMI, health behaviors, and quality of life in children and adolescents: a school-based study. Pediatrics. 2014;133:e868–e74.

    Article  Google Scholar 

  29. Moodie ML, Herbert JK, Silva-Sanigorski AMd, Mavoa HM, Keating CL, Carter RC, et al. The cost-effectiveness of a successful community-based obesity prevention program: the be active eat well program. Obesity. 2013;21:2072–80.

    Article  Google Scholar 

  30. Sanigorski AM, Bell A, Kremer PJ, Cuttler R, Swinburn BA. Reducing unhealthy weight gain in children through community capacity-building: results of a quasi-experimental intervention program, Be Active Eat Well. Int J Obes. 2008;32:1060–67.

    Article  CAS  Google Scholar 

  31. Sanigorski A, Prosser L, Carpenter L, Honisett S, Gibbs L, Moodie M, et al. Evaluation of the childhood obesity prevention program Kids– ‘Go for your life’. BMC Public Health. 2010;10:288.

    Article  Google Scholar 

  32. Salmon J, Arundell L, Hume C, Brown H, Hesketh K, Dunstan DW, et al. A cluster-randomized controlled trial to reduce sedentary behavior and promote physical activity and health of 8-9 year olds: The Transform-Us! Study. BMC Public Health. 2011;11:759.

    Article  Google Scholar 

  33. Rush E, Obolonkin V, McLennan S, Graham D, Harris JD, Mernagh P, et al. Lifetime cost effectiveness of a through-school nutrition and physical programme: project Energize. Obes Res Clin Pract. 2014;8:e115–e22.

    Article  Google Scholar 

  34. McAuley KA, Taylor RW, Farmer VL, Hansen P, Williams SM, Booker CS, et al. Economic evaluation of a community-based obesity prevention program in children: the APPLE project. Obesity (Silver Spring, MD). 2010;18:131–6.

    Article  Google Scholar 

  35. Australian Bureau of Statistics. 6348.0 - Labour costs, Australia, 2010–11. Canberra: ABS; 2012.

    Google Scholar 

  36. Australian Bureau of Statistics. 63060DO001_201005 Employee earnings and hours, Australia, May 2010. Canberra: ABS; 2011.

    Google Scholar 

  37. Australian Bureau of Statistics. 63060DO011_201405 Employee earnings and hours, Australia, May 2014. Canberra: Australian Bureau of Statistics; 2015.

  38. Cadilhac D, Magnus A, Cumming T, Sheppard L, Pearce D, Carter R. The health and economic benefits of reducing disease risk factors. Melbourne: VicHealth; 2009.

  39. Australian Bureau of Statistics. 6302.0 - Average weekly earnings Australia. Canberra: ABS; 2010.

    Google Scholar 

  40. Australian Institute of Health and Welfare. Health system expenditure on disease and injury in Australia, 2000–01. Canberra: AIHW; 2004.

    Google Scholar 

  41. Australian Institute of Health and Welfare. Health expenditure Australia 2014–15. Canberra: AIHW; 2016.

    Google Scholar 

  42. Gold M, Siegel J, Russell L, Weinstein M. Cost-effectiveness in health and medicine. New York: Oxford Univ. Press; 1996.

  43. Stinnett AA, Paltiel AD. Estimating CE ratios under second-order uncertainty: the mean ratio versus the ratio of means. Med Decis Mak. 1997;17:483–9.

    Article  CAS  Google Scholar 

  44. George B, Harris A, Mitchell A. Cost-effectiveness analysis and the consistency of decision making: evidence from pharmaceutical reimbursement in Australia (1991 to 1996). Pharmacoeconomics. 2001;19:1103–9.

    Article  CAS  Google Scholar 

  45. Whelan J, Love P, Pettman T, Doyle J, Booth S, Smith E, et al. Cochrane update: predicting sustainability of intervention effects in public health evidence: identifying key elements to provide guidance. J Public Health (Bangk). 2014;36:347–51.

    Article  Google Scholar 

  46. De Coen V, De Bourdeaudhuij I, Vereecken C, Verbestel V, Haerens L, Huybrechts I, et al. Effects of a 2-year healthy eating and physical activity intervention for 3-6-year-olds in communities of high and low socio-economic status: the POP (Prevention of Overweight among Pre-school and school children) project. Public Health Nutr. 2012;15:1737–45.

    Article  Google Scholar 

  47. De Henauw S, Huybrechts I, De Bourdeaudhuij I, Bammann K, Barba G, Lissner L, et al. Effects of a community-oriented obesity prevention programme on indicators of body fatness in preschool and primary school children. Main results from the IDEFICS study. Obes Rev. 2015;16:16–29.

    Article  Google Scholar 

  48. Economos CD, Hyatt RR, Must A, Goldberg JP, Kuder J, Naumova EN, et al. Shape Up Somerville two-year results: a community-based environmental change intervention sustains weight reduction in children. Prev Med. 2013;57:322–7.

    Article  Google Scholar 

  49. Taylor RW, McAuley KA, Barbezat W, Strong A, Williams SM, Mann JI. APPLE Project: 2-y findings of a community-based obesity prevention program in primary school–age children. Am J Clin Nutr. 2007;86:735–42.

    Article  CAS  Google Scholar 

  50. Utter J, Scragg R, Robinson E, Warbrick J, Faeamani G, Foroughian S, et al. Evaluation of the Living 4 Life project: a youth‐led, school‐based obesity prevention study. Obes Rev. 2011;12(s2):51–60.

    Article  Google Scholar 

  51. Millar L, Kremer P, de Silva‐Sanigorski A, McCabe M, Mavoa H, Moodie M, et al. Reduction in overweight and obesity from a 3‐year community‐based intervention in Australia: the ‘It’s Your Move!’project. Obes Rev. 2011;12(s2):20–8.

    Article  Google Scholar 

  52. Fotu KF, Millar L, Mavoa H, Kremer P, Moodie M, Snowdon W, et al. Outcome results for the Ma’alahi Youth Project, a Tongan community-based obesity prevention programme for adolescents. Obes Rev. 2011;12:41–50.

    Article  Google Scholar 

  53. Kremer P, Waqa G, Vanualailai N, Schultz J, Roberts G, Moodie M, et al. Reducing unhealthy weight gain in Fijian adolescents: results of the Healthy Youth Healthy Communities study. Obes Rev. 2011;12(s2):29–40.

    Article  Google Scholar 

  54. Silva-Sanigorski AM, Bell AC, Kremer P, Nichols M, Crellin M, Smith M, et al. Reducing obesity in early childhood: results from Romp & Chomp, an Australian community-wide intervention program. Am J Clin Nutr. 2010;91:831–40.

    Article  CAS  Google Scholar 

  55. Australian Bureau of Statistics. Schools, Australia (cat. no. 4221.0). Canberra: ABS; 2011.

    Google Scholar 

  56. Hillier-Brown FC, Bambra CL, Cairns J-M, Kasim A, Moore HJ, Summerbell CD. A systematic review of the effectiveness of individual, community and societal level interventions at reducing socioeconomic inequalities in obesity amongst children. BMC Public Health. 2014;14:834.

    Article  Google Scholar 

  57. Bolton KA, Kremer P, Gibbs L, Swinburn B, Waters E, de Silva A. Expanding a successful community-based obesity prevention approach into new communities: Challenges and achievements. Obes Res Clin Pract. 2016;10:197–206.

    Article  Google Scholar 

  58. Council of Australian Governments. National partnership agreement on preventive health. Canberra: COAG; 2009.

  59. Sweeney R, Moodie M, Nguyen P, Fraser P, Bolton K, Brown A, et al. Protocol for an economic evaluation of WHO STOPS childhood obesity stepped-wedge cluster randomised controlled trial. BMJ Open. 2018;8:e020551.

    Article  Google Scholar 

  60. World Health Organization. Population-based approaches to childhood obesity prevention. Geneva: WHO; 2012.

Download references

Acknowledgements

The authors acknowledge the contribution of data from Dr Luke Wolfenden.

Funding source

The work was funded by a National Health and Medical Research Council (NHMRC) Centre of Research Excellence (CRE) on Obesity Policy and Food Systems (Grant number 1041020). GS is the recipient of an Australian Research Council Discovery Early Career Researcher Award (DE160100307).

Author information

Author notes

  1. These authors contributed equally: Jaithri Ananthapavan and Phuong K. Nguyen

Authors and Affiliations

  1. Deakin Health Economics, Institute for Health Transformation, Faculty of Health, Deakin University, Geelong, VIC, Australia

    Jaithri Ananthapavan, Phuong K. Nguyen, Vicki Brown, Rohan Sweeney, Anita Lal & Marj Moodie

  2. Global Obesity Centre (GLOBE), Institute for Health Transformation, Faculty of Health, Deakin University, Geelong, VIC, Australia

    Jaithri Ananthapavan, Phuong K. Nguyen, Gary Sacks, Boyd Swinburn, Vicki Brown, Rohan Sweeney, Anita Lal, Claudia Strugnell & Marj Moodie

  3. Deakin Biostatistics Unit, Faculty of Health, Deakin University, Geelong, VIC, Australia

    Steven J. Bowe

  4. School of Public Health, University of Queensland, Brisbane, QLD, Australia

    Ana Maria Mantilla Herrera

  5. School of Population Health, University of Auckland, Auckland, New Zealand

    Boyd Swinburn

  6. Centre for Health Economics, Monash Business School, Monash University, Melbourne, VIC, Australia

    Rohan Sweeney

Authors
  1. Jaithri Ananthapavan
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Phuong K. Nguyen
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Steven J. Bowe
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Gary Sacks
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Ana Maria Mantilla Herrera
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Boyd Swinburn
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Vicki Brown
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Rohan Sweeney
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Anita Lal
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Claudia Strugnell
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. Marj Moodie
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Jaithri Ananthapavan.

Ethics declarations

Conflict of interest

The authors declare that they have no conflict of interest.

Additional information

Publisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Ananthapavan, J., Nguyen, P.K., Bowe, S.J. et al. Cost-effectiveness of community-based childhood obesity prevention interventions in Australia. Int J Obes 43, 1102–1112 (2019). https://doi.org/10.1038/s41366-019-0341-0

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41366-019-0341-0

This article is cited by

Search

Advanced search

Quick links