Jenneson, VL orcid.org/0000-0003-2468-8009, Pontin, F, Greenwood, DC orcid.org/0000-0001-7035-3096 et al. (2 more authors) (2021) A systematic review of supermarket automated electronic sales data for population dietary surveillance. Nutrition Reviews. ISSN 0029-6643
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
Metadata
Item Type: | Article |
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Authors/Creators: |
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Keywords: | dietary assessment, dietary surveillance, methods, supermarket, transactions. |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Environment (Leeds) > School of Geography (Leeds) The University of Leeds > Faculty of Medicine and Health (Leeds) > School of Medicine (Leeds) > Leeds Institute of Cardiovascular and Metabolic Medicine (LICAMM) > Clinical & Population Science Dept (Leeds) |
Funding Information: | Funder Grant number ESRC (Economic and Social Research Council) ES/S007164/1 Alan Turing Institute No ref given ESRC (Economic and Social Research Council) ES/L011891/1 |
Depositing User: | Symplectic Publications |
Date Deposited: | 02 Dec 2021 14:35 |
Last Modified: | 02 Dec 2021 14:35 |
Status: | Published online |
Publisher: | Oxford University Press |
Identification Number: | 10.1093/nutrit/nuab089 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:181114 |