Although calorie labels did not limit intake, they did make customers more mindful of calories and a little better at estimating the caloric content of their meals.
Study: Assessing the association between the introduction of mandatory calorie labeling and energy consumed using observational data from the food-out-of-home sector in England. Image credit: faizol musa / Shutterstock
In a recent study published in the journal Nature Human Behaviora team of researchers assessed whether the introduction of mandatory calorie labeling in England’s out-of-home food sector (OHFS) affected consumer behaviour, including calorie awareness, shopping and consumption.
Background
OHFS often offers high-energy, high-calorie foods, contributing to the risk of obesity. In the United Kingdom (UK), 27% of adults consume OHFS meals weekly, a concern given the 26% prevalence of obesity in England and its association with diseases such as type 2 diabetes, cardiovascular disease and some cancers.
Despite voluntary kilocalorie (kcal) labeling initiatives since 2011, compliance has been limited, leading to mandatory legislation in 2022 for large businesses.
Evidence from other countries, such as the United States (US) and Canada, suggests that kcal labeling can modestly influence consumer behavior, but the effects are context dependent. Further research is needed to explore its effects in different populations.
About the study
In the present study, participants provided informed verbal consent and were compensated with a £5 shopping voucher for their participation. The study protocol and analysis plan were pre-registered in the Open Science Framework.
An observational study design compared data collected before and after the implementation of mandatory calorie labeling legislation in England.
Data collection took place in four areas, which were chosen to represent a range of levels of deprivation in different geographical areas. Businesses subject to the legislation, which were identified through official registers, were stratified and randomly sampled to ensure representation of different types of food outlets. Outlets that did not allow data collection or were not legally eligible were replaced by re-sampling.
Customer exit surveys were conducted outside selected stores to collect data on calories purchased and consumed, awareness of calorie labeling and label usage. Participants aged 16 and over provided demographic information and details about their purchases.
Calorie content was calculated using a nutritional information database supplemented with company-specific data. Survey timing and methodology were consistent across the pre- and post-implementation periods to minimize bias.
Data were analyzed using regression models adjusted for demographic and outcome characteristics. Results were tested for differences before and after the legislation, with additional analyzes exploring interactions with demographic variables.
Study results
A total of 6,578 participants were interviewed, with 3,308 respondents pre-implementation and 3,270 post-implementation. Demographic characteristics, including age, gender, and ethnicity, were consistent across time points, although the pre-implementation sample included a higher proportion of participants with lower socioeconomic statuses (SEP). Participants were recruited from a variety of establishments, including pubs, restaurants, fast food outlets, coffee shops and entertainment venues, with similar sample proportions pre- and post-implementation.
Mean energy purchased increased slightly from 1,007 kcal (standard deviation (sd) 630) before the application to 1,081 kcal (sd 650) after the application, while energy consumed increased from 909 kcal (sd 547) to 983 kcal ( sd 58). However, regression models showed no statistically significant differences in calories purchased (Beta (B) = 11.31, P = 0.564) or consumed (B = 18.51, P = 0.279) between time points. Bayes factors in unadjusted models showed strong support for the null hypothesis for kcals purchased and consumed.
Demographic factors have influenced purchasing patterns. For example, younger adults and men purchased more calories, while nonwhites purchased fewer calories. Time of day and day of the week also affected calorie purchases, with higher prices seen for evening meals and weekends.
Customers underestimated the calorie content of their meals at both time points. The degree of underestimation decreased slightly after implementation, from 247 kcal to 217 kcal, but the Bayes factors supported the null hypothesis. Regression models revealed that participants from higher SEPs and white ethnicity demonstrated greater caloric estimation accuracy.
Underestimation was more pronounced for meals purchased from restaurants and fast food outlets than from cafeterias.
Observing calorie labels increased significantly from 16.5% pre-implementation to 31.8% post-implementation (odds ratio [OR] 2.25, P < 0.001). Of those who noticed the labels, 19% reported using the information before the app, increasing to 22% after the app (OR 2.15, P < 0.001).
Most participants who used the labels did so to choose lower-calorie options. Observation and use of calorie labels was influenced by demographic factors, with women and those with higher SEP reporting greater adherence.
Participants in less affluent areas were more likely to notice calorie labels than those in affluent areas. Differences in type of outlets and market conditions also affected observation rates, with higher observations reported in pubs compared to coffee shops. A related study found that compliance rates with labeling laws are around 80%, which could explain the policy’s limited impact.
conclusions
In summary, the study found no significant changes in kcals purchased or consumed in OHFS in England from before to after the implementation of mandatory calorie labeling legislation. Although calorie labels were observed to increase and customers slightly improved their calorie estimates, reported label use remained low (3% increase).
Strengths included a diverse, large sample across multiple regions, but reliance on self-reported data and limited compliance with labeling requirements may have influenced the results. The policy alone has shown little impact, but may contribute to broader public health strategies. Future research should investigate the potential need for public education campaigns to increase understanding and use of calorie labels, as well as the impact of menu reformulation on overall calorie consumption.
