Staff Publications

Staff Publications

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    'Staff publications' is the digital repository of Wageningen University & Research

    'Staff publications' contains references to publications authored by Wageningen University staff from 1976 onward.

    Publications authored by the staff of the Research Institutes are available from 1995 onwards.

    Full text documents are added when available. The database is updated daily and currently holds about 240,000 items, of which 72,000 in open access.

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Record number 539163
Title Food identification by barcode scanning in the Netherlands : a quality assessment of labelled food product databases underlying popular nutrition applications
Author(s) Maringer, Marcus; Wisse-Voorwinden, Nancy; Veer, Pieter van 't; Geelen, Anouk
Source Public Health Nutrition (2018). - ISSN 1368-9800 - 8 p.
DOI https://doi.org/10.1017/S136898001800157X
Department(s) Human Nutrition (HNE)
VLAG
Chair Nutrition and Health over the Lifecourse
Chair Nutrition and Disease
Publication type Refereed Article in a scientific journal
Publication year 2018
Keyword(s) Barcode scanning - Barcodes - Diet apps - Dietary intake assessment - Food database - Food identification - Labelled food products - Technological innovations
Abstract

Objective: The quality of labelled food product databases underlying popular diet applications (apps) with barcode scanners was investigated. Design: Product identification rates for the scanned products and the availability and accuracy of nutrient values were calculated. Setting: One hundred food products were selected from the two largest supermarket chains in the Netherlands. Using the barcode scanners of the selected apps, the products were scanned and the results recorded as food diary entries. The collected data were exported. Subjects: Seven diet apps with barcode scanner and food recording feature were selected from the Google Play and Apple app stores. Results: Energy values were available for 99 % of the scanned products, of which on average 79 % deviated not more than 5 % from the true value. MyFitnessPal provided values for sixteen nutrients, while Virtuagym Food and Yazio provided values for only four nutrients. MyFitnessPal also showed the largest percentage of correctly identified products (i.e. 96 %) and SparkPeople the smallest (i.e. 5 %). The accuracy of the provided nutrient values varied greatly between apps and nutrients. Conclusions: While energy was the most consistently and accurately reported value, the availability and accuracy of other values varied greatly between apps. Whereas popular diet apps with barcode scanners might be valuable tools for dietary assessments on the product and energy level, they appear less suitable for assessments on the nutrient level. The presence of user-generated database entries implies that the availability of food products might vary depending on the size and diversity of an app’s user base.

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