Calorie (energy) labelling for changing selection and consumption of food or alcohol.

BACKGROUND

Overconsumption of food and consumption of any amount of alcohol increases the risk of non-communicable diseases. Calorie (energy) labelling is advocated as a means to reduce energy intake from food and alcoholic drinks. However, there is continued uncertainty about these potential impacts, with a 2018 Cochrane review identifying only a small body of low-certainty evidence. This review updates and extends the 2018 Cochrane review to provide a timely reassessment of evidence for the effects of calorie labelling on people's selection and consumption of food or alcoholic drinks.

OBJECTIVES

• To estimate the effect of calorie labelling for food (including non-alcoholic drinks) and alcoholic drinks on selection (with or without purchasing) and consumption. - To assess possible modifiers - label type, setting, and socioeconomic status - of the effect of calorie labelling on selection (with or without purchasing) and consumption of food and alcohol.

SEARCH METHODS

We searched CENTRAL, MEDLINE, Embase, PsycINFO, five other published or grey literature databases, trial registries, and key websites, followed by backwards and forwards citation searches. Using a semi-automated workflow, we searched for and selected records and corresponding reports of eligible studies, with these searches current to 2 August 2021. Updated searches were conducted in September 2023 but their results are not fully integrated into this version of the review.

SELECTION CRITERIA

Eligible studies were randomised controlled trials (RCTs) or quasi-RCTs with between-subjects (parallel group) or within-subjects (cross-over) designs, interrupted time series studies, or controlled before-after studies comparing calorie labelling with no calorie labelling, applied to food (including non-alcoholic drinks) or alcoholic drinks. Eligible studies also needed to objectively measure participants' selection (with or without purchasing) or consumption, in real-world, naturalistic laboratory, or laboratory settings.

DATA COLLECTION AND ANALYSIS

Two review authors independently selected studies for inclusion and extracted study data. We applied the Cochrane RoB 2 tool and ROBINS-I to assess risk of bias in included studies. Where possible, we used (random-effects) meta-analyses to estimate summary effect sizes as standardised mean differences (SMDs) with 95% confidence intervals (CIs), and subgroup analyses to investigate potential effect modifiers, including study, intervention, and participant characteristics. We synthesised data from other studies in a narrative summary. We rated the certainty of evidence using GRADE.

MAIN RESULTS

We included 25 studies (23 food, 2 alcohol and food), comprising 18 RCTs, one quasi-RCT, two interrupted time series studies, and four controlled before-after studies. Most studies were conducted in real-world field settings (16/25, with 13 of these in restaurants or cafeterias and three in supermarkets); six studies were conducted in naturalistic laboratories that attempted to mimic a real-world setting; and three studies were conducted in laboratory settings. Most studies assessed the impact of calorie labelling on menus or menu boards (18/25); six studies assessed the impact of calorie labelling directly on, or placed adjacent to, products or their packaging; and one study assessed labels on both menus and on product packaging. The most frequently assessed labelling type was simple calorie labelling (20/25), with other studies assessing calorie labelling with information about at least one other nutrient, or calories with physical activity calorie equivalent (PACE) labelling (or both). Twenty-four studies were conducted in high-income countries, with 15 in the USA, six in the UK, one in Ireland, one in France, and one in Canada. Most studies (18/25) were conducted in high socioeconomic status populations, while six studies included both low and high socioeconomic groups, and one study included only participants from low socioeconomic groups. Twenty-four studies included a measure of selection of food (with or without purchasing), most of which measured selection with purchasing (17/24), and eight studies included a measure of consumption of food. Calorie labelling of food led to a small reduction in energy selected (SMD -0.06, 95% CI -0.08 to -0.03; 16 randomised studies, 19 comparisons, 9850 participants; high-certainty evidence), with near-identical effects when including only studies at low risk of bias, and when including only studies of selection with purchasing. There may be a larger reduction in consumption (SMD -0.19, 95% CI -0.33 to -0.05; 8 randomised studies, 10 comparisons, 2134 participants; low-certainty evidence). These effect sizes suggest that, for an average meal of 600 kcal, adults exposed to calorie labelling would select 11 kcal less (equivalent to a 1.8% reduction), and consume 35 kcal less (equivalent to a 5.9% reduction). The direction of effect observed in the six non-randomised studies was broadly consistent with that observed in the 16 randomised studies. Only two studies focused on alcoholic drinks, and these studies also included a measure of selection of food (including non-alcoholic drinks). Their results were inconclusive, with inconsistent effects and wide 95% CIs encompassing both harm and benefit, and the evidence was of very low certainty.

AUTHORS' CONCLUSIONS: Current evidence suggests that calorie labelling of food (including non-alcoholic drinks) on menus, products, and packaging leads to small reductions in energy selected and purchased, with potentially meaningful impacts on population health when applied at scale. The evidence assessing the impact of calorie labelling of food on consumption suggests a similar effect to that observed for selection and purchasing, although there is less evidence and it is of lower certainty. There is insufficient evidence to estimate the effect of calorie labelling of alcoholic drinks, and more high-quality studies are needed. Further research is needed to assess potential moderators of the intervention effect observed for food, particularly socioeconomic status. Wider potential effects of implementation that are not assessed by this review also merit further examination, including systemic impacts of calorie labelling on industry actions, and potential individual harms and benefits.