Estimating the environmental impacts of 57,000 food products.

Understanding and communicating the environmental impacts of food products is key to enabling transitions to environmentally sustainable food systems [El Bilali and Allahyari, Inf. Process. Agric. 5, 456-464 (2018)]. While previous analyses compared the impacts of food commodities such as fruits, wheat, and beef [Poore and Nemecek, Science 360, 987-992 (2018)], most food products contain numerous ingredients. However, because the amount of each ingredient in a product is often known only by the manufacturer, it has been difficult to assess their environmental impacts. Here, we develop an approach to overcome this limitation. It uses prior knowledge from ingredient lists to infer the composition of each ingredient, and then pairs this with environmental databases [Poore and Nemecek Science 360, 987-992 (2018); Gephart et al., Nature 597, 360-365 (2021)] to derive estimates of a food product's environmental impact across four indicators: greenhouse gas emissions, land use, water stress, and eutrophication potential. Using the approach on 57,000 products in the United Kingdom and Ireland shows food types have low (e.g., sugary beverages, fruits, breads), to intermediate (e.g., many desserts, pastries), to high environmental impacts (e.g., meat, fish, cheese). Incorporating NutriScore reveals more nutritious products are often more environmentally sustainable but there are exceptions to this trend, and foods consumers may view as substitutable can have markedly different impacts. Sensitivity analyses indicate the approach is robust to uncertainty in ingredient composition and in most cases sourcing. This approach provides a step toward enabling consumers, retailers, and policy makers to make informed decisions on the environmental impacts of food products.

The sugar content of foods in the UK by category and company: A repeated cross-sectional study, 2015-2018.

BACKGROUND: Consumption of free sugars in the UK greatly exceeds dietary recommendations. Public Health England (PHE) has set voluntary targets for industry to reduce the sales-weighted mean sugar content of key food categories contributing to sugar intake by 5% by 2018 and 20% by 2020. The aim of this study was to assess changes in the sales-weighted mean sugar content and total volume sales of sugar in selected food categories among UK companies between 2015 and 2018. METHODS AND FINDINGS: We used sales data from Euromonitor, which estimates total annual retail sales of packaged foods, for 5 categories-biscuits and cereal bars, breakfast cereals, chocolate confectionery, sugar confectionery, and yoghurts-for 4 consecutive years (2015-2018). This analysis includes 353 brands (groups of products with the same name) sold by 99 different companies. These data were linked with nutrient composition data collected online from supermarket websites over 2015-2018 by Edge by Ascential. The main outcome measures were sales volume, sales-weighted mean sugar content, and total volume of sugar sold by category and company. Our results show that between 2015 and 2018 the sales-weighted mean sugar content of all included foods fell by 5.2% (95% CI -9.4%, -1.4%), from 28.7 g/100 g (95% CI 27.2, 30.4) to 27.2 g/100 g (95% CI 25.8, 28.4). The greatest change seen was in yoghurts (-17.0% [95% CI -26.8%, -7.1%]) and breakfast cereals (-13.3% [95% CI -19.2%, -7.4%]), with only small reductions in sugar confectionery (-2.4% [95% CI -4.2%, -0.6%]) and chocolate confectionery (-1.0% [95% CI -3.1, 1.2]). Our results show that total volume of sugars sold per capita fell from 21.4 g/d (95% CI 20.3, 22.7) to 19.7 g/d (95% CI 18.8, 20.7), a reduction of 7.5% (95% CI -13.1%, -2.8%). Of the 50 companies representing the top 10 companies in each category, 24 met the 5% reduction target set by PHE for 2018. The key limitations of this study are that it does not encompass the whole food market and is limited by its use of brand-level sales data, rather than individual product sales data. CONCLUSIONS: Our findings show there has been a small reduction in total volume sales of sugar in the included categories, primarily due to reductions in the sugar content of yoghurts and breakfast cereals. Additional policy measures may be needed to accelerate progress in categories such as sugar confectionery and chocolate confectionery if the 2020 PHE voluntary sugar reduction targets are to be met.

A systematic review, and meta-analysis, examining the prevalence of price promotions on foods and whether they are more likely to be found on less-healthy foods.

OBJECTIVE: There are concerns that price promotions encourage unhealthy dietary choices. This review aims to answer the following research questions (RQ1) what is the prevalence of price promotions on foods in high-income settings, and (RQ2) are price promotions more likely to be found on unhealthy foods? DESIGN: Systematic review of articles published in English, in peer-review journals, after 1 January 2000. SETTING: Included studies measured the prevalence of price promotions (i.e. percentage of foods carrying a price promotion out of the total number of foods available to purchase) in retail settings, in upper-mid to high-income countries. PARTICIPANTS: 'Price promotion' was defined as a consumer-facing temporary price reduction or discount available to all customers. The control group/comparator was the equivalent products without promotions. The primary outcome for this review was the prevalence of price promotions, and the secondary outcome was the difference between the proportions of price promotions on healthy and unhealthy foods. RESULTS: Nine studies (239 344 observations) were included for the meta-analysis for RQ1, the prevalence of price promotions ranged from 6 % (95 % CI 2 %, 15 %) for energy-dense nutrient-poor foods to 15 % (95 % CI 9 %, 25 %) for cereals, grains, breads and other starchy carbohydrates. However, the I-squared statistic was 99 % suggesting a very high level of heterogeneity. Four studies were included for the analysis of RQ2, of which two supported the hypothesis that price promotions were more likely to be found on unhealthy foods. CONCLUSIONS: The prevalence of price promotions is very context specific, and any proposed regulations should be supported by studies conducted within the proposed setting(s).

Impact of the announcement and implementation of the UK Soft Drinks Industry Levy on sugar content, price, product size and number of available soft drinks in the UK, 2015-19: A controlled interrupted time series analysis.

BACKGROUND: Dietary sugar, especially in liquid form, increases risk of dental caries, adiposity, and type 2 diabetes. The United Kingdom Soft Drinks Industry Levy (SDIL) was announced in March 2016 and implemented in April 2018 and charges manufacturers and importers at £0.24 per litre for drinks with over 8 g sugar per 100 mL (high levy category), £0.18 per litre for drinks with 5 to 8 g sugar per 100 mL (low levy category), and no charge for drinks with less than 5 g sugar per 100 mL (no levy category). Fruit juices and milk-based drinks are exempt. We measured the impact of the SDIL on price, product size, number of soft drinks on the marketplace, and the proportion of drinks over the lower levy threshold of 5 g sugar per 100 mL. METHODS AND FINDINGS: We analysed data on a total of 209,637 observations of soft drinks over 85 time points between September 2015 and February 2019, collected from the websites of the leading supermarkets in the UK. The data set was structured as a repeat cross-sectional study. We used controlled interrupted time series to assess the impact of the SDIL on changes in level and slope for the 4 outcome variables. Equivalent models were run for potentially levy-eligible drink categories ('intervention' drinks) and levy-exempt fruit juices and milk-based drinks ('control' drinks). Observed results were compared with counterfactual scenarios based on extrapolation of pre-SDIL trends. We found that in February 2019, the proportion of intervention drinks over the lower levy sugar threshold had fallen by 33.8 percentage points (95% CI: 33.3-34.4, p < 0.001). The price of intervention drinks in the high levy category had risen by £0.075 (£0.037-0.115, p < 0.001) per litre-a 31% pass through rate-whilst prices of intervention drinks in the low levy category and no levy category had fallen and risen by smaller amounts, respectively. Whilst the product size of branded high levy and low levy drinks barely changed after implementation of the SDIL (-7 mL [-23 to 11 mL] and 16 mL [6-27ml], respectively), there were large changes to product size of own-brand drinks with an increase of 172 mL (133-214 mL) for high levy drinks and a decrease of 141 mL (111-170 mL) for low levy drinks. The number of available drinks that were in the high levy category when the SDIL was announced was reduced by 3 (-6 to 12) by the implementation of the SDIL. Equivalent models for control drinks provided little evidence of impact of the SDIL. These results are not sales weighted, so do not give an account of how sugar consumption from drinks may have changed over the time period. CONCLUSIONS: The results suggest that the SDIL incentivised many manufacturers to reduce sugar in soft drinks. Some of the cost of the levy to manufacturers and importers was passed on to consumers as higher prices but not always on targeted drinks. These changes could reduce population exposure to liquid sugars and associated health risks.

A Pilot Randomized Controlled Trial of a Digital Intervention Aimed at Improving Food Purchasing Behavior: The Front-of-Pack Food Labels Impact on Consumer Choice Study.

BACKGROUND: Most food in the United Kingdom is purchased in supermarkets, and many of these purchases are routinely tracked through supermarket loyalty card data. Using such data may be an effective way to develop remote public health interventions and to measure objectively their effectiveness at changing food purchasing behavior. OBJECTIVE: The Front-of-pack food Labels: Impact on Consumer Choice (FLICC) study is a pilot randomized controlled trial of a digital behavior change intervention. This pilot trial aimed to collect data on recruitment and retention rates and to provide estimates of effect sizes for the primary outcome (healthiness of ready meals and pizzas purchased) to inform a larger trial. METHODS: The intervention consisted of a website where participants could access tailored feedback on previous purchases of ready meals and pizzas, set goals for behavior change, and model and practice the recommended healthy shopping behavior using traffic light labels. The control consisted of Web-based information on traffic light labeling. Participants were recruited via email from a list of loyalty card holders held by the participating supermarket. All food and drink purchases for the participants for the 6 months before recruitment, during the 6-week intervention period, and during a 12-week washout period were transferred to the research team by the participating supermarket. Healthiness of ready meals and pizzas was measured using a predeveloped scale based solely on the traffic light colors on the foods. Questionnaires were completed at recruitment, end of the intervention, and end of washout to estimate the effect of the intervention on variables that mediate behavior change (eg, belief and intention formation). RESULTS: We recruited 496 participants from an initial email to 50,000 people. Only 3 people withdrew from the study, and purchase data were received for all other participants. A total of 208 participants completed all 3 questionnaires. There was no difference in the healthiness of purchased ready meals and pizzas between the intervention and control arms either during the intervention period (P=.32) or at washout (P=.59). CONCLUSIONS: Although the FLICC study did not find evidence of an impact of the intervention on food purchasing behavior, the unique methods used in this pilot trial are informative for future studies that plan to use supermarket loyalty card data in collaboration with supermarket partners. The experience of the trial showcases the possibilities and challenges associated with the use of loyalty card data in public health research. TRIAL REGISTRATION: ISRCTN Registry ISRCTN19316955; http://www.isrctn.com/ISRCTN19316955 (Archived by WebCite at http://www.webcitation.org/76IVZ9WjK). INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.1186/s40814-015-0015-1.

Protocol for a pilot randomised controlled trial of an intervention to increase the use of traffic light food labelling in UK shoppers (the FLICC trial).

BACKGROUND: Traffic light labelling of foods-a system that incorporates a colour-coded assessment of the level of total fat, saturated fat, sugar and salt on the front of packaged foods-has been recommended by the UK Government and is currently in use or being phased in by many UK manufacturers and retailers. This paper describes a protocol for a pilot randomised controlled trial of an intervention designed to increase the use of traffic light labelling during real-life food purchase decisions. METHODS/DESIGN: The objectives of this two-arm randomised controlled pilot trial are to assess recruitment, retention and data completion rates, to generate potential effect size estimates to inform sample size calculations for the main trial and to assess the feasibility of conducting such a trial. Participants will be recruited by email from a loyalty card database of a UK supermarket chain. Eligible participants will be over 18 and regular shoppers who frequently purchase ready meals or pizzas. The intervention is informed by a review of previous interventions encouraging the use of nutrition labelling and the broader behaviour change literature. It is designed to impact on mechanisms affecting belief and behavioural intention formation as well as those associated with planning and goal setting and the adoption and maintenance of the behaviour of interest, namely traffic light label use during purchases of ready meals and pizzas. Data will be collected using electronic sales data via supermarket loyalty cards and web-based questionnaires and will be used to estimate the effect of the intervention on the nutrition profile of purchased ready meals and pizzas and the behavioural mechanisms associated with label use. Data collection will take place over 48 weeks. A process evaluation including semi-structured interviews and web analytics will be conducted to assess feasibility of a full trial. DISCUSSION: The design of the pilot trial allows for efficient recruitment and data collection. The intervention could be generalised to a wider population if shown to be feasible in the main trial. TRIAL REGISTRATION: ISRCTN: ISRCTN19316955.

The Preventable Risk Integrated ModEl and Its Use to Estimate the Health Impact of Public Health Policy Scenarios.

Noncommunicable disease (NCD) scenario models are an essential part of the public health toolkit, allowing for an estimate of the health impact of population-level interventions that are not amenable to assessment by standard epidemiological study designs (e.g., health-related food taxes and physical infrastructure projects) and extrapolating results from small samples to the whole population. The PRIME (Preventable Risk Integrated ModEl) is an openly available NCD scenario model that estimates the effect of population-level changes in diet, physical activity, and alcohol and tobacco consumption on NCD mortality. The structure and methods employed in the PRIME are described here in detail, including the development of open source code that will support a PRIME web application to be launched in 2015. This paper reviews scenario results from eleven papers that have used the PRIME, including estimates of the impact of achieving government recommendations for healthy diets, health-related food taxes and subsidies, and low-carbon diets. Future challenges for NCD scenario modelling, including the need for more comparisons between models and the improvement of future prediction of NCD rates, are also discussed.