Affiliation:
1. V.L. Jenneson, F. Pontin, D.C. Greenwood, and M.A. Morris are with the Leeds Institute for Data Analytics, University of Leeds, Leeds, United Kingdom. V.L. Jenneson, F. Pontin, and G.P. Clarke are with the School of Geography, Faculty of Environment, University of Leeds, Leeds, United Kingdom. D.C. Greenwood and M.A. Morris are with the School of Medicine, Faculty of Medicine and Health, Universi
Abstract
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
Publisher
Oxford University Press (OUP)
Subject
Nutrition and Dietetics,Medicine (miscellaneous)
Reference98 articles.
1. Big data in public health: terminology, machine learning, and privacy;Mooney;Annu Rev Public Health.,2018
2. Comparative analysis of nutrition data from national, household, and individual levels: results from a WHO-CINDI collaborative project in Canada, Finland, Poland, and Spain;Serra-Majem;J Epidemiol Community Health.,2003
3. The use of supermarket till receipts to determine the fat and energy intake in a UK population;Ransley;Public Health Nutr.,2001
4. Use of supermarket receipts to estimate energy and fat content of food purchased by lean and overweight families;Ransley;Appetite,2003
Cited by
15 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献