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Using National Sales Data to Understand the Influence of Menu Labeling Policy

Using National Sales Data to Understand the Influence of Menu Labeling Policy
利用全国销售数据了解菜单标签政策的影响
批准号:
9763803
负责人:
Brian Elbel
金额:
$84.09万
依托单位国家:
美国
项目类别:
财政年份:
2019
资助国家:
美国
项目状态:
已结题
起止时间:
2019-04-01 至 2023-03-31

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中文摘要
翻译
项目总结/摘要 肥胖在美国是一个普遍的健康问题,不良的饮食习惯是导致肥胖的最大原因。 除了引起心血管疾病、癌症和糖尿病外,还导致过早死亡。虽然一些 已经制定了通过改变购买食物的环境来解决肥胖问题的政策, 需要进行研究,以了解这些政策可能对食品购买和肥胖产生的影响。菜单 标签就是这样一项政策,要求连锁店以文字形式披露菜单项的卡路里值 让消费者可以做出更明智的选择。这些政策始于2008年, 2018年根据联邦法律在全国实施。先前对菜单标签的研究是有价值的,但缺乏一个 更好地理解标签影响所需的关键特征:大量购买的大规模数据, 这将允许估计小但有意义的累积效应(即,产生的影响 人口水平的饮食改善)。我们通过使用塔可钟提供的数据来解决这个问题, 在美国拥有超过7,000家门店的连锁店,自2007年以来超过50亿笔交易。本公司亦为其附属公司给予 我们完全访问收据级别的数据,这意味着我们可以确定每个订单的确切项目(和卡路里) 购买.这些数据以及2008年至2018年全国范围内菜单标签政策的交错推出 将允许我们使用准实验设计来证明菜单标签对项目的影响, 以一种令人难以置信的强大和微妙的方式购买卡路里。我们不知道任何其他的 检查菜单标签,利用这种大规模的销售数据,包括在国家一级。 我们的具体目标是: 目标1:确定卡路里标签对塔可钟消费者购买的卡路里的影响。 ·目标2:确定标签的影响因社区特征而异的程度, 包括a)社区的人口统计数据(收入和种族/民族),以及B)社区的城市化程度。 餐厅位置 ·目标3:确定标签的影响因购买的特点而异的程度, 包括a)一天中的时间,B)周末或工作日,以及c)开车经过或在餐馆中订购。
英文摘要
Project Summary/Abstract Obesity is a pervasive health problem in the United States, and poor diet is now the largest contributor to premature mortality in addition to causing cardiovascular disease, cancer and diabetes. Although a number of policies have been developed to address obesity by changing the environment in which food is purchased, research is needed to understand the impact these policies might have on food purchasing and obesity. Menu labeling is one such policy, requiring chain establishments to disclose the caloric value of menu items in text alongside each menu item so consumers can make more informed choices. These policies began in 2008 and were implemented nationwide under federal law in 2018. Prior studies of menu labeling are valuable yet lack a key feature needed to better understand the impact of labeling: large scale data on a vast number of purchases, which would allow for the estimation of small but meaningful cumulative effects (i.e., effects that produce population-level dietary improvements). We address this problem by using data provided from Taco Bell, a chain that has over 7,000 stores in the U.S., with over 5 billion transactions since 2007. The company has given us full access to receipt-level data, meaning we can identify the exact items (and calories) ordered for each purchase. These data and the staggered rollout of menu labeling policies across the nation from 2008 – 2018 will allow us to use a quasi-experimental design to demonstrate the impact of menu labeling on items and calories purchased in an incredibly well-powered and nuanced manner. We are unaware of any other examination of menu labeling that leverages such large-scale sales data, including at a national level. Our specific aims are: • Aim 1: Determine the impact of calorie labeling on calories purchased by Taco Bell consumers. • Aim 2: Determine the extent to which the impact of labeling differs by characteristics of the community, including a) demographics of the community (income and race/ethnicity), and b) urbanicity of the restaurant location. • Aim 3: Determine the extent to which the impact of labeling differs by characteristics of the purchase, including a) time of day, b) weekend or weekday, and c) drive through or ordered in the restaurant.
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