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

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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.