A large-scale, long-term, randomized trial of nutrition labeling interventions

项目摘要 不良的饮食习惯与肥胖、2型糖尿病、心血管疾病和 某些癌症。全世界的政府和机构决策者都对粮食感兴趣 标签和信息作为一种具有成本效益的战略，以鼓励更健康的食物选择。 虽然有证据表明营养标签会影响行为，但究竟是哪种标签还不清楚 设计在改变不同教育水平的人的行为方面最有效。那里 有三种常见的营养标签：一个单一的标志，突出健康的选择，交通灯， 标签，或身体活动标签，将卡路里信息转化为燃烧所需的运动 卡路里。因为还没有大规模的长期随机试验比较 这些标签对行为的影响，这些标签方案的相对影响是未知的。 如此严格的评估是必要的，这样决策者就不必猜测。整体 这项申请的目的是比较四种理论上有根据的营养标签设计， 第一个长期的，大规模的营养信息随机试验。本研究将 与费城公共卫生部合作进行，这将使我们能够 将267台自动售货机（107台零食和160台饮料）随机分配到不同的营养标签 充分和传播饮料机将被随机分配到以下四种情况之一： 一个绿色交通灯标签，位于符合“健康”阈值的项目旁边; 2）多个交通灯 显示红色、黄色或绿色标签的灯光标签，用于指示范围从小于到 更健康; 3）身体活动标签，指示一个人必须 步行消耗每种食物或饮料中的卡路里;或4）与税收有关的信息（费城 在2017年1月实施了每盎司1.5美分的饮料税）。零食机将成为 随机分配到相同的条件，但税务消息传递除外，这不适用于 食品我们将使用三年多的自动售货机交易数据来比较影响力 每个标签都有平均卡路里和健康和不太健康的食物购买百分比 以及对销售的影响。我们还将对2,916名自动售货机顾客进行采访 评估受教育程度等因素是否对讯息影响有调节作用。本研究 将提供有价值的数据，以填补研究空白，并为决策者利用营养 标签和信息作为一种公共卫生方法，以鼓励更健康的选择， 解决健康差距问题。 !

PROJECT SUMMARY Poor dietary habits are associated with obesity, type 2 diabetes, cardiovascular disease, and certain cancers. Government and institutional policy makers worldwide are interested in food labeling and messaging as a cost-effective strategy to encourage healthier food choices. Although there is evidence that nutrition labels can influence behavior, it is unclear which label designs are most effective at altering behavior for people with different levels of education. There are three common types of nutrition labels: a single logo highlighting healthier choices, traffic light labels, or physical activity labels that translate calorie information into exercise required to burn off the calories. Because there have been no large-scale, long-term randomized trials comparing the effect of these labels on behavior, the relative impact of these labeling schemes is unknown. Such rigorous evaluations are needed so policy makers do not have to guess. The overall objective of this application is to compare four theoretically-informed nutrition label designs in the first long-term, large-scale randomized trial of nutrition messages. The study will be conducted in partnership with the Philadelphia Department of Public Health which will enable us to randomize 267 (107 snack and 160 beverage) vending machines to different nutrition label messages. Beverage machines will be randomized to one of the following four conditions: 1) A single green traffic light label next to items meeting a “healthy” threshold; 2) a multiple traffic light label that displays red, yellow, or green labels to indicate options that range from less to more healthy; 3) a physical activity label that indicates the number of minutes one would have to walk to burn off the calories in each food or beverage; or 4) tax-related messaging (Philadelphia implemented a 1.5 cents per ounce beverage tax in January 2017). Snack machines will be randomized to the same conditions except for the tax messaging, which does not apply to foods. We will use vending machine transaction data over three years to compare the influence each label has on average calories and percentage of healthy and less healthy items purchased as well as impact on sales. We will also conduct interviews with 2,916 vending machine patrons to evaluate whether education level and other factors moderate message influence. This study will provide valuable data to fill research gaps and inform policy makers’ efforts to use nutrition labeling and messaging as a public health approach to encourage healthier choices and address health disparities. !