Food identification by barcode scanning in the Netherlands
A quality assessment of labelled food product databases underlying popular nutrition applications
Bibliographic Data
| ID | 15091503 |
|---|---|
| Authors | Marcus Maringer (0000-0002-1914-5889, Wageningen University & Research, corresponding author), Nancy Wisse-Voorwinden (Wageningen University & Research), P van ’t Veer (0000-0002-9708-3513, Wageningen University & Research), Anouk Geelen (0000-0003-1799-4075, Wageningen University & Research) |
| Year | 2018 |
| Volume | 22 |
| Issue | 7 |
| Pages | 1-8 |
| Publication date | 2018-07-02 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Public Health Nutrition (JOURNAL) |
| Journal identifiers | ISSN: 1368-9800 • E-ISSN: 1475-2727 |
| Publisher | Cambridge University Press (CUP) (PUBLISHER) |
| DOI | 10.1017/s136898001800157x |
| PMID | 29962361 |
| OpenAlex | W2810228898 |
| Language | EN |
| Citations received | 3 |
| References cited | 17 |
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
Barcode · Biology · Database · Food products · Identification (biology · Nutrient · Nutrition facts label · Portion size · Product (mathematics · Quality (philosophy · Computer Science · Consumer Attitudes and Food Labeling · Mathematics · Mobile Health and mHealth Applications · Nutritional Studies and Diet · Food Science
| Unique citing works | 3 |
|---|---|
| Citations per year | 0,43 |
| Citation span | 2019 - 2024 (6) |
| Citation velocity | recent |
| Highly cited | No |
| Citation types | Neutral: 2 |