The impact of the UK soft drink industry levy on the soft drink marketplace, 2017–2020: An interrupted time series analysis with comparator series

Background: In April 2018, the UK government implemented a levy on soft drinks importers and manufacturers, tiered according to the amount of sugar in drinks. The stated aim was to encourage manufacturers to reduce sugar and portion sizes. Previous evidence suggests that the policy has been successful in reducing sugar in drinks in the short-term since implementation, but their sustained effects have not been explored. This study aimed to assess the impact of the soft drink industry levy (SDIL) on sugar levels, price, portion size and use of non-sugar sweeteners in the medium-term. Methods and findings: Product data from 30 November 2017 to 14 March 2020 from one major UK retail supermarket were analysed (112,452 observations, 126 weekly time points). We used interrupted time series analysis, to assess the impact of the soft-drink industry levy (SDIL) on levy-eligible soft drinks, with exempt drinks (i.e. 100% fruit juices, milks, flavoured milks) acting as a comparator series. At the point of implementation of the SDIL (April 2018) there was a step change in the proportion of eligible drinks with sugar content below the SDIL levy threshold (5g per 100ml) (+0.08, 95%CI: +0.04, +0.12), with a similar sized decrease in the proportion in the highest levy category (> = 8g sugar per 100ml) (-0.06, 95%CI: -0.10, -0.03). Between April 2018 and March 2020, the proportion of eligible drinks below the SDIL levy threshold continued to gradually increase (p = 0.003), while those in the highest levy category decreased (p = 0.007). There was a step change in price of eligible drinks in the higher levy category at the point of implementation of +£0.049 (95%CI: +£0.034, +£0.065) per 100mL (for comparison, the levy is set at £0.024 per 100mL for this group). Trends in price for the high levy category were not altered by the SDIL. In the no levy category, there was a step change in price at the implementation (+£0.012 per 100mL, 95%CI: +£0.008, +£0.023), followed by a second step change in October 2018 (-£0.018p per 100mL, 95%CI: -£0.033, -£0.001p). The volume of products in the higher levy group decreased at the time of the implementation (-305mL on average including multipacks, 95%CI: -511, -99). The change in trend for the product volume of drinks in the higher levy group between April 2018 and March 2020 was in the increasing direction (+704mL per year, 95%CI: -95, 1504), but it did not meet our threshold for statistical significance (p = 0.084). There were no changes observed in the volume of lower levy drinks or no levy drinks. There was a step change in the proportion of drinks with non-sugar sweeteners at the implementation of the SDIL (+0.04, 95%CI: +0.02, +0.06). Conclusion: These results suggest that the SDIL was successful in [1] producing reductions in sugar levels that were maintained over the medium term up to March 2020 and [2] a reduction in product volume for higher tier drinks that may be diminishing over time. Our results also show that the SDIL was associated with a maintained price differential between high and low sugar drinks

Assessing how commercial data on food retail sales can be used to monitor industry-led changes in the food supply in the UK

Introduction: A poor diet is one of the leading causes of morbidity and premature mortality around the world. National and international policymakers recognise that changing the food supply is a crucial part in changing the diets of a population, yet there are few established methods to monitor the actions of food manufacturers and retailers. Aim: The overarching aim of this thesis was to develop and apply a new method pairing food sales data and nutrition composition data to allow the nature of the food supply to be quantified and monitored over time. Method: A systematic review identified potential sources of food sales data. A cross comparison data study, led to the selection of Euromonitor as the most appropriate source for food sales data with nutrition composition data collected from supermarket websites by commercial company Brand View. The sales data and nutrition information were paired based on product name, brand name and category. This unique method was then applied in two ways: first, by analysing the changes in the sugar content of selected food and drinks in the UK between 2015 and 2018 in the context of the UK Government’s 20% sugar reduction targets and soft drinks industry levy (SDIL); and second by applying a nutrient profiling model to the top 10 UK companies’ product portfolios, to develop a benchmarking tool based on the healthiness of companies’ products. Results: Analysis showed that the sales-weighted mean sugar content of soft drinks fell by 34% between 2015 and 2018, from 4.4g/100ml to 2.9g/100ml. The total volume of sugars 2 sold from soft drinks decreased by 30%, from 15.5g per capita per day to 10.8g, a reduction of 4.7g. There was a much smaller decrease in the mean sugar content or sugar sales from food products included in the sugar reduction strategy. The total volume sales of sugar from the included categories fell by 8%, equating to 1.7g per capita per day with marked differences across food categories. However, there has been no significant change between 2015 and 2018 in the overall nutrient profiling score for the top 10 food and drink companies in the UK. In 2018, the sales-weighted mean score of all food and drinks was 65, below the score of 70 which can be considered ‘healthy’. No individual company had an overall score of above 70. There was little change in the number of individual products classified as healthy, although the proportion of total sales classified as healthy increased from 38% to 46%. Discussion: This thesis provides novel insights into how companies have responded to Government public health policies, including the sugar reduction programme. A new method has been developed in this thesis that has the potential to be used continually to monitor the nutritional composition of the food supply, to evaluate which companies are making efforts to improve public health nutrition and to monitor the pace of change

The development of a method for the global health community to assess the proportion of food and beverage companies’ sales that are derived from unhealthy foods

Abstract Context Corporate engagement with food and beverage companies who produce food associated with health harms is a divisive topic in the global nutrition community, with high-profile cases of conflict of interest increasingly coming under scrutiny. There is a need for an agreed method to support health organizations in deciding whether and how to engage with large food and beverage manufacturers. Aim The aim of this study was to develop a method to quantify the proportion of sales from food and beverage companies that are derived from unhealthy foods to support organizations in determining which companies might be considered high-risk for engagement. Methods The 2015 WHO Euro nutrient profile model was applied to 35,550 products from 1294 brands manufactured by the top 20 global food and beverage companies from seven countries (Australia, Brazil, China, India, South Africa, UK and USA). For the purpose of this study, products that met the WHO Euro criteria were classified as “healthier” and those that failed were classified as “unhealthy”. Products were grouped by brand and weighted by the brand’s value sales for 2020. The primary outcome was the proportion of each company’s sales that were classified as unhealthy and healthier by company and category. Results Overall, 89% of the top 20 companies’ brand sales were classified as unhealthy. For every USD$10 spent on the top 20 companies’ brands, only$1.10 was spent on products considered healthier. All companies saw the majority of their sales come from unhealthy foods, including soft drinks, confectionery and snacks. None of Red Bull or Ferrero’s sales were classified as healthier and less than 5% of total sales were healthier for Mondelēz, Mars, and PepsiCo. Some companies had higher proportions of sales deriving from healthier products, including Grupo Bimbo (48%), Danone (34%) and Conagra (32%), although the majority of their sales were still derived from unhealthy foods. Discussion The results presented in this study highlight the reliance the leading food and beverage companies have on sales of unhealthy products that are contributing to diet-related disease globally. The method and steps we have laid out here could be used by organizations in the global health community to identify companies that have conflicts of interest when it comes to engaging with governments, international organizations and public health bodies on issues of policy and regulation

Reply to Muzzioli et al. : Communicating nutrition and environmental information to food system stakeholders

This article replies to - Letter, April 17, 2023, How to communicate the healthiness and sustainability of foods to consumers? Luca Muzzioli, Eleonora Poggiogalle [...] Alessandro PintoNon peer reviewedPublisher PD

The impact of the UK soft drink industry levy on the soft drink marketplace, 2017-2020: An interrupted time series analysis with comparator series.

Funder: NIHR Oxford Biomedical Research Centre; funder-id: http://dx.doi.org/10.13039/501100013373Funder: National Institute for Health and Care Research Applied Research Collaboration Oxford and Thames Valley; funder-id: http://dx.doi.org/10.13039/501100023233BACKGROUND: In April 2018, the UK government implemented a levy on soft drinks importers and manufacturers, tiered according to the amount of sugar in drinks. The stated aim was to encourage manufacturers to reduce sugar and portion sizes. Previous evidence suggests that the policy has been successful in reducing sugar in drinks in the short-term since implementation, but their sustained effects have not been explored. This study aimed to assess the impact of the soft drink industry levy (SDIL) on sugar levels, price, portion size and use of non-sugar sweeteners in the medium-term. METHODS AND FINDINGS: Product data from 30 November 2017 to 14 March 2020 from one major UK retail supermarket were analysed (112,452 observations, 126 weekly time points). We used interrupted time series analysis, to assess the impact of the soft-drink industry levy (SDIL) on levy-eligible soft drinks, with exempt drinks (i.e. 100% fruit juices, milks, flavoured milks) acting as a comparator series. At the point of implementation of the SDIL (April 2018) there was a step change in the proportion of eligible drinks with sugar content below the SDIL levy threshold (5g per 100ml) (+0.08, 95%CI: +0.04, +0.12), with a similar sized decrease in the proportion in the highest levy category (> = 8g sugar per 100ml) (-0.06, 95%CI: -0.10, -0.03). Between April 2018 and March 2020, the proportion of eligible drinks below the SDIL levy threshold continued to gradually increase (p = 0.003), while those in the highest levy category decreased (p = 0.007). There was a step change in price of eligible drinks in the higher levy category at the point of implementation of +£0.049 (95%CI: +£0.034, +£0.065) per 100mL (for comparison, the levy is set at £0.024 per 100mL for this group). Trends in price for the high levy category were not altered by the SDIL. In the no levy category, there was a step change in price at the implementation (+£0.012 per 100mL, 95%CI: +£0.008, +£0.023), followed by a second step change in October 2018 (-£0.018p per 100mL, 95%CI: -£0.033, -£0.001p). The volume of products in the higher levy group decreased at the time of the implementation (-305mL on average including multipacks, 95%CI: -511, -99). The change in trend for the product volume of drinks in the higher levy group between April 2018 and March 2020 was in the increasing direction (+704mL per year, 95%CI: -95, 1504), but it did not meet our threshold for statistical significance (p = 0.084). There were no changes observed in the volume of lower levy drinks or no levy drinks. There was a step change in the proportion of drinks with non-sugar sweeteners at the implementation of the SDIL (+0.04, 95%CI: +0.02, +0.06). CONCLUSION: These results suggest that the SDIL was successful in [1] producing reductions in sugar levels that were maintained over the medium term up to March 2020 and [2] a reduction in product volume for higher tier drinks that may be diminishing over time. Our results also show that the SDIL was associated with a maintained price differential between high and low sugar drinks

The impact of altering restaurant and menu option position on food selected from an experimental food delivery platform: a randomised controlled trial

Abstract Background Overconsumption is one of the most serious public health challenges in the UK and has been linked to increased consumption of food ordered through delivery platforms. This study tested whether repositioning foods and/or restaurant options in a simulated food delivery platform could help to reduce the energy content of users’ shopping basket. Methods UK adult food delivery platform users (N = 9,003) selected a meal in a simulated platform. Participants were randomly allocated to a control condition (choices listed randomly) or to one of four intervention groups, (1) food options listed in ascending order of energy content, (2) restaurant options listed in ascending order of average energy content per main meal, (3) interventions 1 and 2 combined (4) interventions 1 and 2 combined, but food and restaurant options repositioned based on a kcal/price index to display options lower in energy but higher in price at the top. Gamma regressions assessed the impact of interventions on total energy content of baskets at checkout. Results The energy content of participants’ baskets in the control condition was 1382 kcals. All interventions significantly reduced energy content of baskets: Compared to control, repositioning both foods and restaurants purely based on energy content of options resulted in the greatest effect (-209kcal; 95%CIs: -248,-168), followed by repositioning restaurants (-161kcal; 95%CIs: -201,-121), repositioning restaurants and foods based on a kcal/price index (-117kcals; 95%CI: -158,-74) and repositioning foods based on energy content (-88kcals; 95%CI: -130,-45). All interventions reduced the basket price compared to the control, except for the intervention repositioning restaurants and foods based on a kcal/price index, which increased the basket price. Conclusions This proof-of-concept study suggests repositioning lower-energy options more prominently may encourage lower energy food choices in online delivery platforms and can be implemented in a sustainable business model

The effect of removing temporary price promotions or communication of temporary price promotions on unhealthy foods in a simulated online supermarket: A randomised controlled trial

This is a randomised controlled trial to explore how the removing discounts or removing communications of discounts on discretionary items that are high in fat, sugar, or salt (HFSS) affects the amount of calories purchased in a simulated online supermarket platfor