Food identification by barcode scanning in the Netherlands: a quality assessment of labelled food product databases underlying popular nutrition applications

The quality of labelled food product databases underlying popular diet applications (apps) with barcode scanners was investigated. Product identification rates for the scanned products and the availability and accuracy of nutrient values were calculated. One hundred food products were selected from...

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Published inPublic health nutrition Vol. 22; no. 7; pp. 1215 - 1222
Main Authors Maringer, Marcus, Wisse-Voorwinden, Nancy, Veer, Pieter van ’t, Geelen, Anouk
Format Journal Article
LanguageEnglish
Published Cambridge, UK Cambridge University Press 01.05.2019
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Online AccessGet full text
ISSN1368-9800
1475-2727
1475-2727
DOI10.1017/S136898001800157X

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Abstract The quality of labelled food product databases underlying popular diet applications (apps) with barcode scanners was investigated. Product identification rates for the scanned products and the availability and accuracy of nutrient values were calculated. 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. Seven diet apps with barcode scanner and food recording feature were selected from the Google Play and Apple app stores. 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. 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.
AbstractList 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.
ObjectiveThe quality of labelled food product databases underlying popular diet applications (apps) with barcode scanners was investigated.DesignProduct identification rates for the scanned products and the availability and accuracy of nutrient values were calculated.SettingOne 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.SubjectsSeven diet apps with barcode scanner and food recording feature were selected from the Google Play and Apple app stores.ResultsEnergy 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.ConclusionsWhile 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.
The quality of labelled food product databases underlying popular diet applications (apps) with barcode scanners was investigated. Product identification rates for the scanned products and the availability and accuracy of nutrient values were calculated. 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. Seven diet apps with barcode scanner and food recording feature were selected from the Google Play and Apple app stores. 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. 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.
The quality of labelled food product databases underlying popular diet applications (apps) with barcode scanners was investigated. Product identification rates for the scanned products and the availability and accuracy of nutrient values were calculated. 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. Seven diet apps with barcode scanner and food recording feature were selected from the Google Play and Apple app stores. 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. 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.
The quality of labelled food product databases underlying popular diet applications (apps) with barcode scanners was investigated.OBJECTIVEThe quality of labelled food product databases underlying popular diet applications (apps) with barcode scanners was investigated.Product identification rates for the scanned products and the availability and accuracy of nutrient values were calculated.DESIGNProduct identification rates for the scanned products and the availability and accuracy of nutrient values were calculated.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.SETTINGOne 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.Seven diet apps with barcode scanner and food recording feature were selected from the Google Play and Apple app stores.SUBJECTSSeven diet apps with barcode scanner and food recording feature were selected from the Google Play and Apple app stores.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.RESULTSEnergy 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.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.CONCLUSIONSWhile 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.
Author Veer, Pieter van ’t
Maringer, Marcus
Wisse-Voorwinden, Nancy
Geelen, Anouk
AuthorAffiliation Division of Human Nutrition , Wageningen University & Research , Stippeneng 4 , 6708 WE Wageningen , The Netherlands
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BackLink https://www.ncbi.nlm.nih.gov/pubmed/29962361$$D View this record in MEDLINE/PubMed
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CitedBy_id crossref_primary_10_3389_fnut_2021_663569
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Barcode scanning
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Diet apps
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Snippet The quality of labelled food product databases underlying popular diet applications (apps) with barcode scanners was investigated. Product identification rates...
ObjectiveThe quality of labelled food product databases underlying popular diet applications (apps) with barcode scanners was investigated.DesignProduct...
The quality of labelled food product databases underlying popular diet applications (apps) with barcode scanners was investigated.OBJECTIVEThe quality of...
The quality of labelled food product databases underlying popular diet applications (apps) with barcode scanners was investigated. Product identification rates...
Objective: The quality of labelled food product databases underlying popular diet applications (apps) with barcode scanners was investigated. Design: Product...
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SourceType Open Access Repository
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Enrichment Source
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StartPage 1215
SubjectTerms Accuracy
Availability
Barcode scanning
Barcodes
barcoding
Databases, Factual
Diet
Diet apps
Dietary intake assessment
Energy
Energy levels
Energy storage
Exports
Feasibility studies
Food
Food availability
Food database
Food identification
Food Labeling
Food products
Food quality
food records
Food security
Food selection
foods
Health informatics
HOT TOPIC: ICT Assisted Dietary Data Collection and Analysis
Humans
Identification
Inventory
Labelled food products
Market shares
Mobile Applications
Netherlands
nutrient content
Nutrients
Nutrition
nutrition assessment
Nutrition research
Nutritive Value
popular diets
Quality
Quality assessment
Quality control
Recording
Research Paper
Scanners
Smartphones
Supermarkets
Technological innovations
Usability
User interface
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Title Food identification by barcode scanning in the Netherlands: a quality assessment of labelled food product databases underlying popular nutrition applications
URI https://www.cambridge.org/core/product/identifier/S136898001800157X/type/journal_article
https://www.ncbi.nlm.nih.gov/pubmed/29962361
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https://pubmed.ncbi.nlm.nih.gov/PMC10260744
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Volume 22
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