Development and Validation of an Objective, Passive Dietary Assessment Method for Estimating Food and Nutrient Intake in Households in Low- and Middle-Income Countries: A Study Protocol

Modou L Jobarteh, Megan A McCrory, Benny Lo, Mingui Sun, Edward Sazonov, Alex K Anderson, Wenyan Jia, Kathryn Maitland, Jianing Qiu, Matilda Steiner-Asiedu, Janine A Higgins, Tom Baranowski, Peter Olupot-Olupot, Gary Frost, Modou L Jobarteh, Megan A McCrory, Benny Lo, Mingui Sun, Edward Sazonov, Alex K Anderson, Wenyan Jia, Kathryn Maitland, Jianing Qiu, Matilda Steiner-Asiedu, Janine A Higgins, Tom Baranowski, Peter Olupot-Olupot, Gary Frost

Abstract

Malnutrition is a major concern in low- and middle-income countries (LMIC), but the full extent of nutritional deficiencies remains unknown largely due to lack of accurate assessment methods. This study seeks to develop and validate an objective, passive method of estimating food and nutrient intake in households in Ghana and Uganda. Household members (including under-5s and adolescents) are assigned a wearable camera device to capture images of their food intake during waking hours. Using custom software, images captured are then used to estimate an individual's food and nutrient (i.e., protein, fat, carbohydrate, energy, and micronutrients) intake. Passive food image capture and assessment provides an objective measure of food and nutrient intake in real time, minimizing some of the limitations associated with self-reported dietary intake methods. Its use in LMIC could potentially increase the understanding of a population's nutritional status, and the contribution of household food intake to the malnutrition burden. This project is registered at clinicaltrials.gov (NCT03723460).

Keywords: assessment; camera; devices; dietary; food; household; intake; nutrient; undernutrition; wearable.

Copyright © The Author(s) 2020.

Figures

FIGURE 1
FIGURE 1
Wearable camera devices used for passive capture of images of food intake and food-related activities in the households: (A) Foodcam, (B) Automatic Ingestion Monitor (AIM), (C) Ear-worn, (D) eButton, and (E) eHAT.
FIGURE 2
FIGURE 2
A schematic diagram of the study plan. Wearable and fixed camera devices will be used to collect images of food intake and related activities such as cooking in households in Ghana and Uganda. Images captured by the devices will be stored in cloud storage, and the stored food images will be used for food recognition and estimation of portion size and nutrient content, thus providing objective, passive dietary assessment.
FIGURE 3
FIGURE 3
The Automatic Ingestion Monitor (AIM) software—an image annotation and dietary intake assessment software. AIM distinguishes between eating (blue bars, bottom left) and noneating episodes. Clicking on the blue bar displays images from the detected eating event. The images can be browsed individually and magnified to provide a good view of all the foods on the image. The software supports the incorporation of standard food composition databases. The software also supports visual estimation of portion sizes.

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Source: PubMed

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