Restricting promotions of ‘less healthy’ foods and beverages by price and location: A big data application of UK Nutrient Profiling Models to a retail product dataset

Abstract

The UK government plans to limit price‐based and location‐based promotions for products high in saturated fat, salt and sugars. The 2004/2005 UK Nutrient Profiling Model (NPM) is the proposed legislative basis, but may be superseded by the draft 2018 NPM. This study develops an algorithm to apply both NPMs to a large food composition database (FCDB), and assesses implementation challenges. UK NPMs were applied algorithmically to the myfood24 FCDB, representing ~45 000 retail products. Pass rates – indicating free or restricted promotions – and micronutrient compositions were compared. Challenges were assessed, and recommendations addressed the legislation’s public consultation questions. For products in scope (75% of total), 6% fewer passed the 2018 NPM (36%, P < 0.001) compared with the 2004/2005 NPM (42%). Beverages showed the greatest reduction in pass rate (75%). Under both models, micronutrient contents (per 100 g of product) were generally lower for products that passed; except folate, vitamin C and vitamin D were no different for passed and failed products. Compared with products passing the 2004/2005 NPM, products passing the 2018 NPM on average had marginally higher amounts of iron (0.05 mg, 95% CI: 0.02, 0.08, P < 0.001) and magnesium (1.00 mg, 95% CI: 0.00, 1.17, P = 0.029), but marginally lower levels of calcium (−0.42 mg, 95% CI: −2.00, −0.40, P = 0.025). Missing ingredient information and heterogeneous product categories were challenges for both NPMs. Free sugars calculation further complicated 2018 NPM application. To balance feasibility and public health benefit, the proposed legislative basis may not be appropriate.

A comparison of four different Nutritional Profile models in their scoring of critical nutrient levels in food products targeted at Brazilian children

“…In addition, we could not discriminate the amount of free sugars of the total sugars declared in the ‘fruit’ drinks and ‘dairy’ drinks. This challenge is also mentioned by other authors, and although they estimated that dairy drinks contained 50% of sugars as free sugars, they also recognised that this assumption may not be accurate for all products (Jenneson et al, 2020). These limitations would also impact the national implementation of a FOP labelling, and so, in October 2020, a Normative Instruction nº 75 was published, determining the mandatory declaration of the sugars content (total and added) on food nutritional labels (Brasil, 2020).…”

Dietary Patterns Derived from UK Supermarket Transaction Data with Nutrient and Socioeconomic Profiles

“…These types of data would enable comprehensive modelling of proposed nutritional policies, such as the planned legislation expected to be announced in summer 2021 to restrict price and location promotions of high fat, sugar and salt products [ 29 ]. It has been recognised that there are limitations in the data that retailers hold which would enable them to successfully implement these new rules across their whole product portfolio [ 30 ], but this new dataset, which combines sales and nutrient composition data, would make that easier and would also enable, for the first time, quantification of the impact of legislation in objective sales weighted data, not subject to the limitations of self-reporting, and therefore unlike survey and panel data.…”

Data considerations for the success of policy to restrict in‐store food promotions: A commentary from a food industry nutritionist consultation

“…While the consultation now confirms the 2004/2005 UK NPM is to be the basis of the legislative proposal (GOV.UK 2020), this was unknown at the time of analysis. Thus, we included the hypothetical scenario that the new NPM may eventually supersede it, in an assessment of the challenges of implementing the proposal (Jenneson et al 2020a).…”

“…Thus, it broadly represents the scale and diversity of a retailer product portfolio. An algorithm was developed (Jenneson 2020) to automate the application of the NPM at scale and compared the feasibility and performance of the current (DH 2011) and draft 2018 UK NPM (PHE 2018a) as the legislative basis (Jenneson et al 2020a).…”

“…However, without clarity on the details of the proposal, it is not possible to model the actual implications for either businesses or for public health. The quantitative case study highlighted a mismatch between the data held by retailer and that required to implement the legislative rules (Jenneson et al 2020a). Challenges include the availability and accuracy of information required for decision-making and compliance, for example, the high degree of missing ingredient information in commercial product datasets, and the need for information not available on the product back of pack (Jenneson et al 2020a).…”