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Model Development for Fat Mass Assessment Using Near-Infrared Reflectance in South African Infants and Young Children
Alexander Miller1, Jacqueline Huvanandana1, Peter Jones1
1School of Electrical and Information Engineering, University of Sydney, Darlington, NSW 2008, Australia.
Sensors (Basel, Switzerland)
|April 3, 2021
Summary
Undernutrition is a major global issue. This study developed a new, affordable near-infrared reflectance (NIR) model to accurately assess body fat in infants and young children, aiding growth monitoring.
Area of Science:
- Pediatric Nutrition
- Body Composition Analysis
- Biomedical Engineering
Background:
- Undernutrition in infants and young children is a critical global health problem, contributing to millions of deaths annually.
- Accurate body composition assessment is vital for identifying malnutrition and guiding interventions.
- Existing methods for body fat measurement can be costly, complex, or less accurate in young children.
Purpose of the Study:
- To develop and validate a novel model for body composition assessment in infants and young children using near-infrared reflectance (NIR).
- To evaluate the efficacy of NIR technology in accurately predicting fat mass compared to established methods.
- To provide an accessible tool for growth monitoring in low-resource settings.
Main Methods:
- A cohort of 164 infants and young children aged 3-24 months was recruited.
- Fat mass was measured using dual-energy x-ray absorptiometry (DXA), deuterium dilution (DD), and skin fold thickness (SFT) as reference methods.
- A predictive model for fat mass was developed using NIR technology and validated against a multi-compartment model.
Main Results:
- The NIR model demonstrated strong correlations with the multi-compartment reference method (r=0.885 for all subjects, r=0.904 for 0-6 months, r=0.818 for 7-24 months).
- NIR performance surpassed conventional methods like SFT, body mass index, and anthropometry in accuracy.
- The study confirmed NIR as a reliable tool for estimating fat mass in the target age group.
Conclusions:
- Near-infrared reflectance (NIR) offers a promising, affordable, and portable method for assessing body fat in infants and young children.
- This technology can significantly aid in the growth monitoring of children in low-middle income settings, particularly in South Africa.
- The validated NIR model provides a valuable tool for early identification of undernutrition and low body fat.
