Zuppinger, Claire; Taffé, Patrick; Burger, Gerrit; Badran-Amstutz, Wafa; Niemi, Tapio; Cornuz, Clémence; Belle, Fabiën N; Chatelan, Angeline; Paclet Lafaille, Muriel; Bochud, Murielle; Gonseth Nusslé, Semira (2022). Performance of the Digital Dietary Assessment Tool MyFoodRepo. Nutrients, 14(3), p. 635. MDPI 10.3390/nu14030635
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Digital dietary assessment devices could help overcome the limitations of traditional tools to assess dietary intake in clinical and/or epidemiological studies. We evaluated the accuracy of the automated dietary app MyFoodRepo (MFR) against controlled reference values from weighted food diaries (WFD). MFR's capability to identify, classify and analyze the content of 189 different records was assessed using Cohen and uniform kappa coefficients and linear regressions. MFR identified 98.0% ± 1.5 of all edible components and was not affected by increasing numbers of ingredients. Linear regression analysis showed wide limits of agreement between MFR and WFD methods to estimate energy, carbohydrates, fat, proteins, fiber and alcohol contents of all records and a constant overestimation of proteins, likely reflecting the overestimation of portion sizes for meat, fish and seafood. The MFR mean portion size error was 9.2% ± 48.1 with individual errors ranging between -88.5% and +242.5% compared to true values. Beverages were impacted by the app's difficulty in correctly identifying the nature of liquids (41.9% ± 17.7 of composed beverages correctly classified). Fair estimations of portion size by MFR, along with its strong segmentation and classification capabilities, resulted in a generally good agreement between MFR and WFD which would be suited for the identification of dietary patterns, eating habits and regime types.
Item Type: |
Journal Article (Original Article) |
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Division/Institute: |
04 Faculty of Medicine > Pre-clinic Human Medicine > Institute of Social and Preventive Medicine (ISPM) |
UniBE Contributor: |
Belle, Fabien Naomi, Chatelan, Angéline |
Subjects: |
600 Technology > 610 Medicine & health 300 Social sciences, sociology & anthropology > 360 Social problems & social services |
ISSN: |
2072-6643 |
Publisher: |
MDPI |
Language: |
English |
Submitter: |
Pubmed Import |
Date Deposited: |
15 Mar 2022 11:08 |
Last Modified: |
07 Aug 2024 15:45 |
Publisher DOI: |
10.3390/nu14030635 |
PubMed ID: |
35276994 |
Uncontrolled Keywords: |
accuracy app diet dietary assessment food intake mobile food record validation |
BORIS DOI: |
10.48350/167392 |
URI: |
https://boris.unibe.ch/id/eprint/167392 |
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