Next Article in Journal
Predictive Validity of Image-Based Motivation-to-Eat Visual Analogue Scales in Normal Weight Children and Adolescents Aged 9–14 Years
Previous Article in Journal
An Infant Formula with Large, Milk Phospholipid-Coated Lipid Droplets Supports Adequate Growth and Is Well-Tolerated in Healthy, Term Asian Infants: A Randomized, Controlled Double-Blind Clinical Trial
Article

Performance of the Digital Dietary Assessment Tool MyFoodRepo

1
Center for Primary Care and Public Health (Unisanté), University of Lausanne, 1010 Lausanne, Switzerland
2
Institute of Social and Preventive Medicine (ISPM), University of Bern, 3012 Bern, Switzerland
3
Department of Nutrition and Dietetics, School of Health Sciences (HEdS-GE), University of Applied Sciences and Arts Western Switzerland (HES-SO), 1227 Carouge, Switzerland
4
Department of Endocrinology, Diabetology and Metabolism, Lausanne University Hospital (CHUV), 1011 Lausanne, Switzerland
*
Author to whom correspondence should be addressed.
Academic Editor: Janette Walton
Nutrients 2022, 14(3), 635; https://doi.org/10.3390/nu14030635
Received: 31 December 2021 / Revised: 26 January 2022 / Accepted: 27 January 2022 / Published: 1 February 2022
(This article belongs to the Section Nutrition Methodology & Assessment)
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. View Full-Text
Keywords: dietary assessment; accuracy; validation; food intake; diet; mobile food record; app dietary assessment; accuracy; validation; food intake; diet; mobile food record; app
Show Figures

Figure 1

MDPI and ACS Style

Zuppinger, C.; Taffé, P.; Burger, G.; Badran-Amstutz, W.; Niemi, T.; Cornuz, C.; Belle, F.N.; Chatelan, A.; Paclet Lafaille, M.; Bochud, M.; Gonseth Nusslé, S. Performance of the Digital Dietary Assessment Tool MyFoodRepo. Nutrients 2022, 14, 635. https://doi.org/10.3390/nu14030635

AMA Style

Zuppinger C, Taffé P, Burger G, Badran-Amstutz W, Niemi T, Cornuz C, Belle FN, Chatelan A, Paclet Lafaille M, Bochud M, Gonseth Nusslé S. Performance of the Digital Dietary Assessment Tool MyFoodRepo. Nutrients. 2022; 14(3):635. https://doi.org/10.3390/nu14030635

Chicago/Turabian Style

Zuppinger, Claire, Patrick Taffé, Gerrit Burger, Wafa Badran-Amstutz, Tapio Niemi, Clémence Cornuz, Fabiën N. Belle, Angeline Chatelan, Muriel Paclet Lafaille, Murielle Bochud, and Semira Gonseth Nusslé. 2022. "Performance of the Digital Dietary Assessment Tool MyFoodRepo" Nutrients 14, no. 3: 635. https://doi.org/10.3390/nu14030635

Find Other Styles
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Back to TopTop