Obesity and hypertension are major public health problems in the United States (US). One particular approach taken by several public health departments, including New York City, is to provide consumers with dietary information at the point of food purchase—a practice known as ‘menu labeling’. The inclusion of dietary information alongside dollar cost on menus allows consumers to consider potential health costs. However, research on the efficacy of menu labeling interventions has yielded mixed results. The mixed results can be attributed to variations in study design, which include differences in demographic and socioeconomic determinants such as education and income. These predictors have each been identified as affecting health behaviors in theories of health behavior and variations in such may obfuscate the true efficacy of menu labeling interventions. Intervention designers would therefore benefit from systematically exploring how varying combinations of these determinants affect the efficacy of menu labeling interventions. Such research could then allow public health professionals to tailor menu labeling interventions with specific subgroups, leading to healthier dietary choices for even marginal groups, and ultimately reducing the burden of obesity and hypertension in the US.

Tackling the problem of obesity

Obesity and hypertension are significant public health problems in the US. The Centers for Disease Control (CDC) estimated that 40.3% of adults in the US were obese (Emmerich et al., 2024) from August 2021 to 2023. According to data collected between 2017 and March 2020, the CDC estimated that 19.7% of US children and adolescents were obese (Stierman et al., 2021). In 2021, approximately 190,000 Americans died due to overweight- and obesity-related causes (Al Ta’ani et al., 2024). In a 2020 study, approximately 119.9 million of US adults had hypertension, and hypertension contributed to 664,470 deaths in 2023 (Million Hearts, 2023). From a financial perspective, the cost of either condition are similarly staggering: obesity costs the US $215 billion annually while hypertension costs $219 billion (Hammond & Levine, 2010; Wang et al., 2024). The prevailing sentiment is that the prevalence of these conditions is driven by increased food consumption away from the home (Bates et al., 2009).

To combat obesity and hypertension, public health programs have taken to providing dietary information to consumers at the point of purchase in a practice known as menu labeling. The first was calorie menu labeling: in 2008, New York City started requiring restaurants with 15 or more locations nationwide to indicate the calorie amounts for menu items in font similar to the item’s dollar price. The Affordable Care Act would implement a similar requirement for franchises with 20 or more locations across the United States in 2010. Sodium menu labeling began being enforced in 2016 and 2019 for New York City and Philadelphia, respectively. In the former municipality, this meant that food establishments with more than 15 or more locations nationwide were required to display a salt shaker warning icon next to menu options that exceeded the federally recommended of 2300 milligrams of sodium. Most recently, New York City implemented the Sweet Truth Act on December 15, 2021, which was then signed into law in November 2023. The law went into effect on October 4, 2025, requiring food establishments with at least 15 locations across the US to display a sugar content warning (an image of a sugar-laden spoon) next to menu options that exceed the daily limit of at least 50 grams of added sugars.

Each of these menu labeling interventions aim to foster healthier dietary choices by providing consumers with health-related information at the point of sale. One New York City Department of Health webpage states that the aim of sodium menu labeling is to ensure consumers “have the information necessary to make informed decisions about their diets and their health when purchasing items at chain restaurants” (NYC Health Department, 2025). A similar intention was shared for sugar labeling as Health Commissioner Dr. Michelle Morse stated, “Through this rule, we aim for New Yorkers to have more insight into the amount of sugar in certain products to make more informed choices” (2025). In fact, Moran and colleagues found that consumers underestimated how much sodium was in a given meal (Moran et al., 2017), supporting the notion that consumers would benefit from more information.

Do menu labeling interventions work?

Existing literature suggests that menu labeling interventions have mixed results. One systematic review performed three years after New York City implemented calorie menu labeling found that the policy had no effect on calorie ordering or consumption (Swartz et al., 2011). In contrast, a later review found calorie menu labeling to have an effect on consumers’ calorie purchasing or consumption, but only primarily in cafeteria- and laboratory-based settings (Bleich et al., 2017; Kiszko et al., 2014). Sodium menu labeling also yielded mixed results with a review finding five valid studies, but only two of the five studies led to reductions in either the sodium content of menu items or the amount of sodium purchased after the implementation of sodium menu labeling (Alexander et al., 2021). 

Several studies note subgroup differences in the use of menu labeling interventions. Bassett and colleagues (2008) noted that residents of more affluent communities, women, and young adults are specific subgroups that are likely to use caloric labeling information. Self-reported dieters were more likely to be influenced by calorie menu labels compared to non-dieters (Girz et al., 2011). One study found that women chose lower calorie amounts compared to men after being provided caloric information (Gerend, 2009) while another found that men were more influenced by caloric information, although this may be due to floor effects as women in that study had already been ordering less calories compared to men even in the absence of caloric information (Bates et al., 2009). Lastly, although children from high and low SES backgrounds both utilized a “heart symbol” intervention (indicating healthier options), only children from high SES backgrounds utilized nutrition information (Stutts et al., 2011).

Future research

The mixed results can be attributed to study designs’ variations in location or setting, utilization of a comparison group, and behavioral outcomes (e.g. calorie ordering versus calorie consumption), as well as demographic and socioeconomic factors (e.g. gender, age, and education). Demographic and socioeconomic factors are known determinants of health behaviors (Hagger, 2025) and between-study differences in such can obfuscate the true efficacy of menu labeling interventions and inadvertently lead to discrepancies between demographic and socioeconomic strata.

Cases where only specific segments of the population initially leverage a health intervention is reminiscent of the inverse equity hypothesis, which has been observed in health decision-making settings before. Koc and Kippersluis (2017) found that educational level, which is already a predictor of life expectancy (Sylte et al., 2025), also drives use of nutritional information. Similarly, women can extend their already longer life expectancies over men (Yan et al., 2024) by leveraging menu labeling more effectively than men. In the spirit of health equity, menu labeling interventions would greatly benefit from systematically exploring how the efficacies of menu labeling interventions differ by specific socioeconomic intersections. One potential approach could be to specifically conduct a series of studies with participants from varied financial and educational backgrounds while utilizing factorial designs newly popularized in implementation and behavior sciences. The targeted sampling allows for researchers to more clearly describe the relationship between income, education, and intervention efficacy while the factorial design will enable researchers to understand which behavioral intervention components are more effective with specific populations. Another approach would be to address more upstream determinants of such disparities, such as narrowing income and educational gaps or at least investigating and addressing the mechanisms by which these determinants actually affect health behaviors (Andrews et al., 2017).

By doing so, intervention designers can not only better understand underlying mechanisms of health behaviors, but also design more tailored interventions that specifically help those who would most benefit from menu labeling interventions. Broadly, future policies benefit from comprehensive theoretical frameworks that uncover the underlying mechanisms of menu labeling interventions that would benefit all demographic and socioeconomic populations.

References

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