J Martin1, A Peeters2, S Honisett3, H Mavoa4, B Swinburn4, A de Silva-Sanigorski5. 1. The Obesity Policy Coalition, Australia. Electronic address: Jane.Martin@cancervic.org.au. 2. Baker IDI Heart and Diabetes Institute, Australia. Electronic address: anna.peeters@bakeridi.edu.au. 3. The Cancer Council Victoria, Australia. 4. Deakin University, Australia. 5. University of Melbourne, Australia.
Abstract
BACKGROUND: Successful obesity prevention will require a leading role for governments, but internationally they have been slow to act. League tables of benchmark indicators of action can be a valuable advocacy and evaluation tool. OBJECTIVE: To develop a benchmarking tool for government action on obesity prevention, implement it across Australian jurisdictions and to publicly award the best and worst performers. DESIGN: A framework was developed which encompassed nine domains, reflecting best practice government action on obesity prevention: whole-of-government approaches; marketing restrictions; access to affordable, healthy food; school food and physical activity; food in public facilities; urban design and transport; leisure and local environments; health services, and; social marketing. A scoring system was used by non-government key informants to rate the performance of their government. National rankings were generated and the results were communicated to all Premiers/Chief Ministers, the media and the national obesity research and practice community. RESULTS: Evaluation of the initial tool in 2010 showed it to be feasible to implement and able to discriminate the better and worse performing governments. Evaluation of the rubric in 2011 confirmed this to be a robust and useful method. In relation to government action, the best performing governments were those with whole-of-government approaches, had extended common initiatives and demonstrated innovation and strong political will. CONCLUSION: This new benchmarking tool, the Obesity Action Award, has enabled identification of leading government action on obesity prevention and the key characteristics associated with their success. We recommend this tool for other multi-state/country comparisons.
BACKGROUND: Successful obesity prevention will require a leading role for governments, but internationally they have been slow to act. League tables of benchmark indicators of action can be a valuable advocacy and evaluation tool. OBJECTIVE: To develop a benchmarking tool for government action on obesity prevention, implement it across Australian jurisdictions and to publicly award the best and worst performers. DESIGN: A framework was developed which encompassed nine domains, reflecting best practice government action on obesity prevention: whole-of-government approaches; marketing restrictions; access to affordable, healthy food; school food and physical activity; food in public facilities; urban design and transport; leisure and local environments; health services, and; social marketing. A scoring system was used by non-government key informants to rate the performance of their government. National rankings were generated and the results were communicated to all Premiers/Chief Ministers, the media and the national obesity research and practice community. RESULTS: Evaluation of the initial tool in 2010 showed it to be feasible to implement and able to discriminate the better and worse performing governments. Evaluation of the rubric in 2011 confirmed this to be a robust and useful method. In relation to government action, the best performing governments were those with whole-of-government approaches, had extended common initiatives and demonstrated innovation and strong political will. CONCLUSION: This new benchmarking tool, the Obesity Action Award, has enabled identification of leading government action on obesity prevention and the key characteristics associated with their success. We recommend this tool for other multi-state/country comparisons.
Authors: Anna-Marie Hendriks; Jolanda M Habraken; Stef P J Kremers; Maria W J Jansen; Hans van Oers; Albertine J Schuit Journal: Biomed Res Int Date: 2016-09-07 Impact factor: 3.411