A systematic review of supermarket automated electronic sales data for population dietary surveillance

Abstract

Context Most dietary assessment methods are limited by self-report biases, how long they take for participants to complete, and cost of time for dietitians to extract content. Electronically recorded, supermarket-obtained transactions are an objective measure of food purchases, with reduced bias and improved timeliness and scale. Objective The use, breadth, context, and utility of electronic purchase records for dietary research is assessed and discussed in this systematic review. Data sources Four electronic databases (MEDLINE, EMBASE, PsycINFO, Global Health) were searched. Included studies used electronically recorded supermarket transactions to investigate the diet of healthy, free-living adults. Data extraction Searches identified 3422 articles, of which 145 full texts were retrieved and 72 met inclusion criteria. Study quality was assessed using the National Institutes of Health Quality Assessment Tool for Observational Cohort and Cross-Sectional Studies. Data analysis Purchase records were used in observational studies, policy evaluations, and experimental designs. Nutrition outcomes included dietary patterns, nutrients, and food category sales. Transactions were linked to nutrient data from retailers, commercial data sources, and national food composition databases. Conclusion Electronic sales data have the potential to transform dietary assessment and worldwide understanding of dietary behavior. Validation studies are warranted to understand limits to agreement and extrapolation to individual-level diets. Systematic Review Registration PROSPERO registration no. CRD42018103470

Exploring the Geographic Variation in Fruit and Vegetable Purchasing Behaviour Using Supermarket Transaction Data

“…Demographic information is available for this study thanks to loyalty card information provided by the retailer and linkage with area-level demographic data. This enables assessment of sample representativeness, which is noted as important [ 48 ] and lacking [ 49 ] in previous applications of transaction data for public health nutrition research. The customer samples are mostly female, with an older age distribution than Leeds as a whole.…”

Algorithm-based mapping of products in a branded Canadian food and beverage database to their equivalents in Health Canada’s Canadian Nutrient File

“…When used with food composition information, these data can be especially useful for health professionals and scholars, including clinicians, dietitians, and epidemiologists studying the impact of population diet and nutrition on the prevalence and incidence of certain diet-related chronic conditions ( 4 ). Innovative approaches to monitoring public health and community nutrition are particularly critical and can be enabled using these kinds of datasets ( 1 , 5 ).…”

“…Prior studies have reported various approaches to linking food retail and marketing datasets to food group and composition data for the study of population health and nutrition, including both manual and algorithm-based approaches ( 1 , 4 , 5 , 6 ). The traditional way of mapping a database of products to their respective food composition (nutrient content) is by manual matching; generally, this means a product is matched to a food or beverage item code in a food composition database, which then pulls in those nutrient data for use with that now-linked product ( 8 ).…”

Impact on purchasing behaviour of implementing ‘junk free checkouts’: A pre‐post study

“…Some research has collected till receipts as an objective measure of purchases (Ransley et al, 2001), but this remains restricted to a self‐selecting sample. The use of sales transaction records directly from retailers is becoming more prevalent around the world, from a variety of retailers (Aiello et al, 2020; Clark et al, 2021; Jenneson et al, 2022).…”