Energy labelling of alcoholic drinks: An important or inconsequential obesity policy?

Alcohol is calorie dense, but unlike food products, alcoholic drinks tend to be exempt from nutritional labelling laws that require energy content information to be displayed on packaging or at point of purchase. This review provides a perspective on the likely efficacy of alcoholic drink energy labelling as a public health policy to reduce obesity and discusses key questions to be addressed by future research. First, the contribution that alcohol makes to population level daily energy intake and obesity is outlined. Next, consumer need for alcohol energy labelling and the potential impacts on both consumer and industry behavior are discussed. Pathways and mechanisms by which energy labelling of alcoholic drinks could reduce obesity are considered, as well as possible unintended consequences of alcoholic drink energy labelling. Would widespread energy labelling of alcoholic drinks reduce obesity? The unclear effect that alcohol has on population level obesity, the modest contribution calories from alcohol make to daily energy intake and limited impact nutritional labelling policies tend to have on behavior, suggest alcohol energy labelling may have limited impact on population obesity prevalence as a standalone policy. However, there are a number of questions that will need to be answered by future research to make definitive conclusions on the potential for alcohol energy labelling policies to reduce obesity.

The energy and nutritional content of snacks sold at supermarkets and coffee shops in the UK.

BACKGROUND: Snacking is associated with a higher daily energy intake and dietary guidelines recommend snacks of no more than 200 kcal for adults and 100 kcal for children. The present study examines the energy content, nutritional quality and price of single-serving snack food products sold by major supermarket and coffee shop chains in the UK. METHODS: Energy content, nutritional content and price of single-serving snack products were recorded in 2019 via the websites of 14 major chains (seven supermarkets; seven coffee shops). RESULTS: The mean energy content of all eligible snack products (n = 2283) was 186 kcal [95% confidence interval (CI) = 182-190]. The mean energy content of the snack products sold at coffee shops (n = 379; 282 kcal [95% CI = 269-295]) was significantly higher than the energy content of the snack products sold at supermarkets (n = 1904; 167 kcal [95% CI = 164-170]). Seventy nine % of supermarket snacks exceeded energy recommendations for children and 32% for adults. In coffee shops, 91% exceeded recommendations for children and 73% for adults. Forty one % of snacks were high in fat, 42% were high in saturated fat, 39% were high in sugar and 7% were high in salt. Cheaper snack products were more likely to be of lower nutritional quality. CONCLUSIONS: The high proportion of snack products that do not meet public health recommendations for energy content may contribute to the association between snacking and increased energy intake. Public health measures to increase the availability and reduce the price of snack products that meet public health energy content recommendations may reduce population-level obesity.

Alcohol, calories, and obesity: A rapid systematic review and meta-analysis of consumer knowledge, support, and behavioral effects of energy labeling on alcoholic drinks.

Mandatory energy (calorie) labeling of alcoholic drinks is a public health measure that could be used to address both alcohol consumption and obesity. We systematically reviewed studies examining consumer knowledge of the energy content of alcoholic drinks, public support for energy labeling, and the effect of energy labeling of alcoholic drinks on consumption behavior. Eighteen studies were included. Among studies examining consumer knowledge of the energy content of alcoholic drinks (N = 8) and support for energy labeling (N = 9), there was moderate evidence that people are unaware of the energy content of alcoholic drinks (pooled estimate: 74% [95% CI: 64%-82%] of participants inaccurate) and support energy labeling (pooled estimate: 64% [95% CI: 53%-73%] of participants support policy). Six studies examined the effect of energy labeling on consumption behavior. In these studies, there was no evidence of a beneficial effect of labeling on alcohol drinking-related outcome measures. However, the majority of studies were of low methodological quality and used proxy outcome measures, and none of the studies were conducted in real-world settings, resulting in a very low level of evidence and high degree of uncertainty. Further research is required to determine whether energy labeling of alcoholic drinks is likely to be an effective public health policy.

Identification of Behavior Change Techniques From Successful Web-Based Interventions Targeting Alcohol Consumption, Binge Eating, and Gambling: Systematic Review.

BACKGROUND: Web-based interventions are thought to overcome barriers to treatment, such as accessibility and geographical location, which can undermine the effectiveness of traditional face-to-face interventions. Owing to these features, researchers are increasingly testing the efficacy of web-based interventions as ways to reduce alcohol misuse, binge eating, and gambling. However, many web-based interventions have poorly defined mechanisms of action; therefore, it is often uncertain how they propose to bring about behavior change. OBJECTIVE: This systematic review aims to identify effective behavior change techniques (BCTs) present in web-based interventions aimed at reducing alcohol consumption, binge eating, or gambling. METHODS: This systematic review covered research conducted in the last 20 years. Inclusion criteria for interventions were web-based administration; targeting alcohol use, binge eating, and/or gambling; and reporting on baseline and postintervention measures of behavior. The PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-analyses) guidelines were followed. We coded intervention effectiveness, study quality, and BCTs present in the interventions. RESULTS: Following removal of 4152 ineligible articles, 45 were included in the review: 32 (71%) targeted alcohol misuse, 6 (13%) targeted binge eating, and 7 (16%) targeted gambling. In total, 5 frequency counts were performed to identify the most commonly used BCTs: all studies, effective interventions, high-quality studies at 2 thresholds, and both high quality and effective studies. The results obtained from this were integrated to identify 7 BCTs. These 7 BCTs were problem solving, feedback on behavior, self-monitoring of behavior, self-monitoring of outcomes, instruction on how to perform a behavior, information about social and health consequences, and social comparison. A total of 4 BCTs were found in all frequency counts: feedback on behavior, self-monitoring of behavior, instruction on how to perform a behavior, and social comparison. Self-monitoring of outcomes of behavior was found in 3 of the 5 frequency counts, problem solving was found in 2 frequency counts, and information about social and health consequences was found in 1 frequency count. CONCLUSIONS: This systematic review identified 7 of the most frequently used BCTs used in web-based interventions focused on alcohol misuse, binge eating, and gambling. These results can inform the development of evidence-based eHealth interventions that have the potential to lead to effective, positive behavior changes in all 3 areas.