Don't Count Calorie Labeling Out: Calorie Counts on the Left Side of Menu Items Lead to Lower Calorie Food Choices

Abstract

Providing calorie counts on restaurants’ menus/menu boards is one of the most prominent policy interventions that has been implemented to combat the obesity epidemic in America. However, previous research across multiple disciplines has found little effect of providing calorie counts on calories ordered, leading some to call calorie provision a failed policy. The authors propose that this failure is partly due to not considering how people process information when making food choices: Americans read from left‐to‐right, processing calorie information only after processing the food item's name. Thus, the authors test a simple way to improve the effectiveness of calorie counts: display calorie counts to the left (vs. right) of food items. A field study and a laboratory study with American participants found that calorie counts to the left (vs. right) decreased calories ordered by 16.31%. A final laboratory study demonstrated that this effect is reversed among Hebrew‐speakers, who read from right‐to‐left, providing further evidence that the order in which calorie information is processed matters. Accordingly, calling calorie labeling a policy failure may be premature.

Strategic ignorance of health risk: its causes and policy consequences

“…The apparent widespread prevalence of strategic ignorance may then call for measures that make calorie information harder to ignore. For instance, Ellison et al (2013Ellison et al ( , 2014 show that symbolic traffic light labels enhance the effectiveness of numeric calorie information on menus, and Dallas et al (2019) show that people respond more to calorie information displayed to the left (rather than the usual right) of menu items. Public information campaigns could also be used to make negative health consequences of calorie overconsumption more salient, and thereby increase the perceived cost of ignorance.…”

Excess success in “Don’t count calorie labeling out: Calorie counts on the left side of menu items lead to lower calorie food choices”

“…The mean, standard deviation, and sample size for each condition in each experiment reported by Dallas et al (2019) is reproduced in Table 1, together with the key hypotheses used to support their theoretical conclusions. Each of the six reported experiments fully satisfied the hypotheses, thereby providing uniform support for the conclusions.…”

“…We evaluated the plausibility of all six studies producing uniform success, by computing estimates of experimental power for replications of each of the studies. These power estimates are based on the statistics reported by Dallas et al (2019), so our analysis starts by supposing that the reported findings are valid and accurate. Since the studies are statistically independent, we can then compute the probability of the full set of studies being uniformly successful by multiplying the estimates of the individual studies.…”

“…Here, we use a Test for Excess Success (TES) analysis (Francis, 2013;Ioannidis & Trikalinos, 2007;Schimmack, 2012) to show that the results of a recent article by Dallas et al (2019) seem overly successful. Based on six successful studies, Dallas et al (2019) conclude that consumers opt for lower calorie food items when calorie information is displayed on the menubut only when it is placed so that it is read before the food names. According to the authors, previous failures to show an effect of calorie labeling on menus can be attributed to the fact that the calorie information was placed to the right of, and were thus read after, the food names.…”

Information presentation and consumer choice: Evidence from Assisted Reproductive Technology (ART) Success Rate Reports

“…This paper is also related to the behavioral economics literature documenting inattentive behaviors. 4 For example, Dallas, Liu, and Ubel (2019) find that presenting calorie counts on the left side of menu items lead to lower calorie food choices because Americans read from left to right. For non-health care settings, studies have shown the existence of behavioral biases when employees choose retirement plans and find that employee choice is influenced by default contribution rates (Bernheim, Fradkin, & Popov, 2015), anchoring, goal setting and savings threshold (Choi, Haisley, Kurkoski, & Massey, 2017), income projections (Goda, Manchester, & Sojourner, 2014), and framing effects (Brown, Kling, Mullainathan, & Wrobel, 2008).…”