Simulating the Impact of Sugar-Sweetened Beverage Warning Labels in Three Cities.

Simulating the Impact of Sugar-Sweetened Beverage Warning Labels in Three Cities.
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模拟三个城市中的糖粉饮料警告标签的影响。

DOI:
10.1016/j.amepre.2017.11.003
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发表时间:
2018-03
影响因子:
5.5
通讯作者:
Brown ST
Brown ST
中科院分区:
医学2区
文献类型:
--
作者:
Lee BY;Ferguson MC;Hertenstein DL;Adam A;Zenkov E;Wang PI;Wong MS;Gittelsohn J;Mui Y;Brown ST

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许多地方一直在考虑在含糖饮料购买点实施警告标签政策,以帮助解决青少年超重和肥胖患病率上升的问题。为了探索此类政策的影响,2016 年,利用 2005 年至 2014 年期间收集的各种来源的数据,开发了巴尔的摩、费城和旧金山的详细基于主体的模型,代表其人口、学校地点和食物来源。该模型模拟了 7 年期间每个城市的 BMI 和肥胖流行率因含糖饮料警告标签政策而发生的平均变化。 2016年至2017年间进行的数据分析发现,在所有含糖饮料零售商实施含糖饮料警告标签后,这三个城市的青少年肥胖率均有所降低。功效为 8% 的购买点标签(即标签将含糖饮料消费的可能性降低 8%)导致肥胖患病率发生以下百分比变化: 巴尔的摩:-1.69%(95% CI= -2.75,-0.97,p<0.001);旧金山:-4.08%(95% CI=-5.96,-2.2,p<0.001);费城:-2.17%(95%范围=-3.07,-1.42,p<0.001)。基于代理的模拟显示了警告标签如何在各种情况下降低超重和肥胖的患病率,并将标签功效和识字率确定为潜在驱动因素。实施警告标签政策可能会降低肥胖患病率。关注警告标签设计和商店合规性,特别是在超市,可能会进一步增加对健康的影响。
A number of locations have been considering sugar-sweetened beverage point of purchase warning label policies to help address rising adolescent overweight and obesity prevalence. To explore the impact of such policies, in 2016 detailed agent-based models of Baltimore, Philadelphia, and San Francisco were developed, representing their populations, school locations, and food sources, using data from various sources collected between 2005 and 2014. The model simulated, over a 7-year period, the mean change in BMI and obesity prevalence in each of the cities from sugar-sweetened beverage warning label policies. Data analysis conducted between 2016 and 2017 found that implementing sugar-sweetened beverage warning labels at all sugar-sweetened beverage retailers lowered obesity prevalence among adolescents in all three cities. Point of purchase labels with 8% efficacy (i.e., labels reducing probability of sugar-sweetened beverage consumption by 8%) resulted in the following percentage changes in obesity prevalence: Baltimore: −1.69% (95% CI= −2.75, −0.97, p<0.001); San Francisco: −4.08% (95% CI= −5.96, −2.2, p<0.001); Philadelphia: −2.17% (95% range= −3.07, −1.42, p<0.001). Agent-based simulations showed how warning labels may decrease overweight and obesity prevalence in a variety of circumstances with label efficacy and literacy rate identified as potential drivers. Implementing a warning label policy may lead to a reduction in obesity prevalence. Focusing on warning label design and store compliance, especially at supermarkets, may further increase the health impact.
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