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

dietary assessment dietary surveillance methods supermarket transactions

Journal

Nutrition reviews
ISSN: 1753-4887
Titre abrégé: Nutr Rev
Pays: United States
ID NLM: 0376405

Informations de publication

Date de publication:
09 05 2022
Historique:
pubmed: 11 11 2021
medline: 12 5 2022
entrez: 10 11 2021
Statut: ppublish

Résumé

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. The use, breadth, context, and utility of electronic purchase records for dietary research is assessed and discussed in this systematic review. 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. 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. 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. 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. PROSPERO registration no. CRD42018103470.

Identifiants

pubmed: 34757399
pii: 6425025
doi: 10.1093/nutrit/nuab089
pmc: PMC9086796
doi:

Types de publication

Journal Article Systematic Review Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

1711-1722

Informations de copyright

© The Author(s) 2021. Published by Oxford University Press on behalf of the International Life Sciences Institute.

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Auteurs

Victoria L Jenneson (VL)

Leeds Institute for Data Analytics, University of Leeds, Leeds, United Kingdom.
School of Geography, Faculty of Environment, University of Leeds, Leeds, United Kingdom.

Francesca Pontin (F)

Leeds Institute for Data Analytics, University of Leeds, Leeds, United Kingdom.
School of Geography, Faculty of Environment, University of Leeds, Leeds, United Kingdom.

Darren C Greenwood (DC)

Leeds Institute for Data Analytics, University of Leeds, Leeds, United Kingdom.
School of Medicine, Faculty of Medicine and Health, University of Leeds, Leeds, United Kingdom.

Graham P Clarke (GP)

School of Geography, Faculty of Environment, University of Leeds, Leeds, United Kingdom.

Michelle A Morris (MA)

Leeds Institute for Data Analytics, University of Leeds, Leeds, United Kingdom.
School of Medicine, Faculty of Medicine and Health, University of Leeds, Leeds, United Kingdom.

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Classifications MeSH