A method for the inclusion of physical activity-related health benefits in cost-benefit analysis of built environment initiatives

被引:11
|
作者
Zapata-Diomedi, Belen [1 ]
Gunn, Lucy [2 ]
Giles-Corti, Billie [2 ]
Shiell, Alan [3 ]
Veerman, J. Lennert [1 ,4 ,5 ]
机构
[1] Univ Queensland, Sch Publ Hlth, Herston Rd, Brisbane, Qld 4006, Australia
[2] RMIT Univ, Hlth Liveable Cities Grp, Ctr Urban Res, Melbourne, Vic 3000, Australia
[3] La Trobe Univ, Dept Publ Hlth, Plenty Rd, Bundoora, Vic 3083, Australia
[4] Canc Council NSW, Sydney, NSW 2011, Australia
[5] Sydney Med Sch, Sydney, NSW 2006, Australia
基金
英国医学研究理事会; 澳大利亚国家健康与医学研究理事会;
关键词
Cost benefit analysis; Physical activity; Health; Built environment; Urban planning; Transport; Active transport; TRANSPORT; IMPACT; TRAVEL; RISK;
D O I
10.1016/j.ypmed.2017.11.009
中图分类号
R1 [预防医学、卫生学];
学科分类号
1004 ; 120402 ;
摘要
The built environment has a significant influence on population levels of physical activity (PA) and therefore health. However, PA-related health benefits are seldom considered in transport and urban planning (i.e. built environment interventions) cost-benefit analysis. Cost-benefit analysis implies that the benefits of any initiative are valued in monetary terms to make them commensurable with costs. This leads to the need for monetised values of the health benefits of PA. The aim of this study was to explore a method for the incorporation of monetised PA-related health benefits in cost-benefit analysis of built environment interventions. Firstly, we estimated the change in population level of PA attributable to a change in the built environment due to the intervention. Then, changes in population levels of PA were translated into monetary values. For the first step we used estimates from the literature for the association of built environment features with physical activity outcomes. For the second step we used the multi-cohort proportional multi-state life table model to predict changes in health-adjusted life years and health care costs as a function of changes in PA. Finally, we monetised health-adjusted life years using the value of a statistical life year. Future research could adapt these methods to assess the health and economic impacts of specific urban development scenarios by working in collaboration with urban planners.
引用
收藏
页码:224 / 230
页数:7
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