OBJECTIVE:Scalable methods are required for population dietary monitoring. The Supermarket Transaction Records In Dietary Evaluation (STRIDE) study compares dietary estimates from supermarket transactions with an online FFQ. DESIGN:Participants were recruited in four waves, accounting for seasonal dietary variation. Purchases were collected for 1 year during and 1 year prior to the study. Bland-Altman agreement and limits of agreement (LoA) were calculated for energy, sugar, fat, saturated fat, protein and sodium (absolute and relative). SETTING:This study was partnered with a large UK retailer. PARTICIPANTS:Totally, 1788 participants from four UK regions were recruited from the retailer's loyalty card customer database, according to breadth and frequency of purchases. Six hundred and eighty-six participants were included for analysis. RESULTS:The analysis sample were mostly female (72 %), with a mean age of 56 years (sd 13). The ratio of purchases to intakes varied depending on amounts purchased and consumed; purchases under-estimated intakes for smaller amounts on average, but over-estimated for larger amounts. For absolute measures, the LoA across households were wide, for example, for energy intake of 2000 kcal, purchases could under- or over-estimate intake by a factor of 5; values could be between 400 kcal and 10000 kcal. LoA for relative (energy-adjusted) estimates were smaller, for example, for 14 % of total energy from saturated fat, purchase estimates may be between 7 % and 27 %. CONCLUSIONS:Agreement between purchases and intake was highly variable, strongest for smaller loyal households and for relative values. For some customers, relative nutrient purchases are a reasonable proxy for dietary composition indicating utility in population-level dietary research.

Online supermarket platforms present an opportunity for encouraging healthier consumer purchases. A parallel, double-blind randomised controlled trial tested whether promoting healthier products (e.g. lower fat and lower calorie) on the Sainsbury's online supermarket platform would increase purchases of those products. Participants were Nectar loyalty membership scheme cardholders who shopped online with Sainsbury's between 20th September and 10th October 2017. Intervention arm customers saw advertisement banners and recipe ingredient lists containing healthier versions of the products presented in control arm banners and ingredient lists. The primary outcome measure was purchases of healthier products. Additional outcome measures were banner clicks, purchases of standard products, overall purchases and energy (kcal) purchased. Sample sizes were small due to customers navigating the website differently than expected. The intervention encouraged purchases of some promoted healthier products (spaghetti [B = 2.10, p < 0.001], spaghetti sauce [B = 2.06, p < 0.001], spaghetti cheese [B = 2.45, p = 0.001], sour cream [B = 2.52, p < 0.001], fajita wraps [B = 2.10, p < 0.001], fajita cheese [B = 1.19, p < 0.001], bakery aisle products (B = 3.05, p = 0.003) and cola aisle products [B = 0.97, p < 0.002]) but not others (spaghetti mince, or products in the yogurt and ice cream aisles). There was little evidence of effects on banner clicks and energy purchased. Small sample sizes may affect the robustness of these findings. We discuss the benefits of collaborating to share expertise and implement a trial in a live commercial environment, alongside key learnings for future collaborative research in similar contexts.

The existence of dietary inequalities is well-known. Dietary behaviours are impacted by the food environment and are thus likely to follow a spatial pattern. Using 12 months of transaction records for around 50,000 ‘primary’ supermarket loyalty card holders, this study explores fruit and vegetable purchasing at the neighbourhood level across the city of Leeds, England. Determinants of small-area-level fruit and vegetable purchasing were identified using multiple linear regression. Results show that fruit and vegetable purchasing is spatially clustered. Areas purchasing fewer fruit and vegetable portions typically had younger residents, were less affluent, and spent less per month with the retailer.