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Evaluation of acceptability, functionality, and validity of a passive image-based dietary intake assessment method in adults and children of Ghanaian and Kenyan origin living in London, UK
Journal article   Open access   Peer reviewed

Evaluation of acceptability, functionality, and validity of a passive image-based dietary intake assessment method in adults and children of Ghanaian and Kenyan origin living in London, UK

Modou L. Jobarteh, Megan A. Mccrory, Benny Lo, Konstantinos K. Triantafyllidis, Jianing Qiu, Jennifer P. Griffin, Edward Sazonov, Mingui Sun, Wenyan Jia, Tom Baranowski, …
Nutrients, Vol.15(18), 4075
2023
PMID: 37764857
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Published1.62 MBDownloadView
Published (Version of Record) Open Access CC BY V4.0

Abstract

dietary intake assessment wearable camera food nutrients portion size nutritional analysis
Background Accurate estimation of dietary intake is challenging. However, whilst some progress has been made in high-income countries, low- and middle-income countries (LMICs) remain behind, contributing to critical nutritional data gaps. This study aimed to validate an objective, passive image-based dietary intake assessment method against weighed food records in London, UK, for onward deployment to LMICs. Methods Wearable camera devices were used to capture food intake on eating occasions in 18 adults and 17 children of Ghanaian and Kenyan origin living in London. Participants were provided pre-weighed meals of Ghanaian and Kenyan cuisine and camera devices to automatically capture images of the eating occasions. Food images were assessed for portion size, energy, nutrient intake, and the relative validity of the method compared to the weighed food records. Results The Pearson and Intraclass correlation coefficients of estimates of intakes of food, energy, and 19 nutrients ranged from 0.60 to 0.95 and 0.67 to 0.90, respectively. Bland-Altman analysis showed good agreement between the image-based method and the weighed food record. Under-estimation of dietary intake by the image-based method ranged from 4 to 23%. Conclusions Passive food image capture and analysis provides an objective assessment of dietary intake comparable to weighed food records.

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UN Sustainable Development Goals (SDGs)

This output has contributed to the advancement of the following goals:

#3 Good Health and Well-Being
#10 Reduced Inequalities

Source: SDGs in the Output

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