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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. | LitMetric

AI Article Synopsis

  • Malnutrition is a significant issue in low- and middle-income countries, but accurate assessments of nutritional deficiencies are lacking.
  • This study aims to create and validate a new method using wearable cameras to automatically capture food intake images from household members in Ghana and Uganda.
  • The captured images will help objectively estimate food and nutrient intake—like protein and fat—providing better insights into nutritional status and potentially addressing malnutrition challenges in these regions.

Article 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).

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7031207PMC
http://dx.doi.org/10.1093/cdn/nzaa020DOI Listing

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