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“红绿灯”营养标签和“垃圾食品”税:预防肥胖的成本效益模型比较。

'Traffic-light' nutrition labelling and 'junk-food' tax: a modelled comparison of cost-effectiveness for obesity prevention.

机构信息

WHO Collaborating Centre for Obesity Prevention, Deakin University, Melbourne, Victoria, Australia.

出版信息

Int J Obes (Lond). 2011 Jul;35(7):1001-9. doi: 10.1038/ijo.2010.228. Epub 2010 Nov 16.

Abstract

INTRODUCTION

Cost-effectiveness analyses are important tools in efforts to prioritise interventions for obesity prevention. Modelling facilitates evaluation of multiple scenarios with varying assumptions. This study compares the cost-effectiveness of conservative scenarios for two commonly proposed policy-based interventions: front-of-pack 'traffic-light' nutrition labelling (traffic-light labelling) and a tax on unhealthy foods ('junk-food' tax).

METHODS

For traffic-light labelling, estimates of changes in energy intake were based on an assumed 10% shift in consumption towards healthier options in four food categories (breakfast cereals, pastries, sausages and preprepared meals) in 10% of adults. For the 'junk-food' tax, price elasticities were used to estimate a change in energy intake in response to a 10% price increase in seven food categories (including soft drinks, confectionery and snack foods). Changes in population weight and body mass index by sex were then estimated based on these changes in population energy intake, along with subsequent impacts on disability-adjusted life years (DALYs). Associated resource use was measured and costed using pathway analysis, based on a health sector perspective (with some industry costs included). Costs and health outcomes were discounted at 3%. The cost-effectiveness of each intervention was modelled for the 2003 Australian adult population.

RESULTS

Both interventions resulted in reduced mean weight (traffic-light labelling: 1.3 kg (95% uncertainty interval (UI): 1.2; 1.4); 'junk-food' tax: 1.6 kg (95% UI: 1.5; 1.7)); and DALYs averted (traffic-light labelling: 45,100 (95% UI: 37,700; 60,100); 'junk-food' tax: 559,000 (95% UI: 459,500; 676,000)). Cost outlays were AUD81 million (95% UI: 44.7; 108.0) for traffic-light labelling and AUD18 million (95% UI: 14.4; 21.6) for 'junk-food' tax. Cost-effectiveness analysis showed both interventions were 'dominant' (effective and cost-saving).

CONCLUSION

Policy-based population-wide interventions such as traffic-light nutrition labelling and taxes on unhealthy foods are likely to offer excellent 'value for money' as obesity prevention measures.

摘要

简介

成本效益分析是优先考虑肥胖预防干预措施的重要工具。建模有助于评估具有不同假设的多种情况。本研究比较了两种常见的基于政策的干预措施(包装正面“红绿灯”营养标签(红绿灯标签)和对不健康食品征税(“垃圾食品”税)的保守情景的成本效益。

方法

对于红绿灯标签,基于假设的成年人中 10%的消费向四种食品(早餐谷物、糕点、香肠和预制餐)中更健康的选择转移,估计了能量摄入的变化。对于“垃圾食品”税,使用价格弹性来估计在七种食品(包括软饮料、糖果和零食)的价格上涨 10%时能量摄入的变化。然后,根据这些人群能量摄入的变化,以及随后对残疾调整生命年(DALY)的影响,估计了男性和女性的人群体重和体重指数的变化。基于健康部门的观点(包括一些行业成本),通过途径分析来衡量和定价相关资源的使用。成本和健康结果以 3%贴现。为 2003 年澳大利亚成年人口对每种干预措施进行了建模。

结果

两种干预措施均导致平均体重降低(红绿灯标签:1.3 公斤(95%置信区间(UI):1.2;1.4);“垃圾食品”税:1.6 公斤(95% UI:1.5;1.7))和避免的 DALY(红绿灯标签:45100(95% UI:37700;60100);“垃圾食品”税:559000(95% UI:459500;676000))。红绿灯标签的支出为 8100 万澳元(95% UI:4470 万;1080 万),“垃圾食品”税为 1800 万澳元(95% UI:1440 万;2160 万)。成本效益分析表明,这两种干预措施均为“主导”(有效且节省成本)。

结论

作为肥胖预防措施,基于政策的全人群干预措施,如红绿灯营养标签和对不健康食品征税,可能具有极好的“性价比”。

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