Related Experiment Video
Updated: Dec 16, 2025
Author Spotlight: Unveiling Prognostic Indicators in Heart Failure - The Role of Phase Angle and Bioelectrical Impedance Analysis
Published on: June 30, 2023
Development of population-specific prediction equations for bioelectrical impedance analyses in Vietnamese children
Phuong Hong Nguyen1,2, Melissa F Young3, Long Quynh Khuong4
1Poverty, Health and Nutrition Division, International Food Policy Research Institute (IFPRI), Washington, DC20006, USA.
Insights
Researchers developed new, accurate bioelectrical impedance analysis (BIA) equations to measure body composition in Vietnamese children. This method provides a field-friendly tool for assessing fat mass, fat-free mass, and body fat percentage in young populations.
Area of Science:
- Pediatric Nutrition
- Body Composition Assessment
- Biomedical Engineering
Background:
- Accurate body composition assessment in children is crucial, especially in resource-poor settings.
- Bioelectrical impedance analysis (BIA) offers a promising, field-friendly alternative to traditional methods.
- Limited validation exists for BIA in young children in diverse populations.
Purpose of the Study:
- To develop and validate population-specific BIA prediction equations for total fat mass (FM), fat-free mass (FFM), and percentage body fat (PBF).
- To assess these parameters in Vietnamese children aged 4-7 years.
- To utilize BIA, anthropometry, and demographic data for equation development.
Main Methods:
- A cross-sectional survey of 120 Vietnamese children (4-7 years).
- Body composition measured using dual-energy X-ray absorptiometry (DXA) as the reference standard, BIA, and anthropometry.
- Data split into development (70%) and validation (30%) sets for equation creation and testing.
Main Results:
- A top-performing model was identified using age, sex, weight, and resistance index (or resistance and height).
- The model demonstrated high predictive accuracy with low RMSE and MAE, and high R2 values for FM, FFM, and PBF.
- Minimal differences were observed between predicted and DXA-measured body composition values.
Conclusions:
- The study presents the first validated, highly predictive BIA equations for estimating FM, FFM, and PBF in Vietnamese children.
- These equations offer a reliable and accessible tool for assessing body composition in this demographic.
- Findings support future research on the double burden of disease and obesity risks in young children.
Abstract:
There is a need for accurate, inexpensive and field-friendly methods to assess body composition in children. Bioelectrical impedance analysis (BIA) is a promising approach; however, there have been limited validation and use among young children in resource-poor settings. We aim to develop and validate population-specific prediction equations for estimating total fat mass (FM), fat free-mass (FFM) and percentage body fat (PBF) in Vietnamese children (4-7 years) using reactance and resistance from BIA, anthropometric variables and demographic information. We conducted a cross-sectional survey of 120 children. Body composition was measured using dual-energy X-ray absorptiometry (DXA), BIA and anthropometry. To develop prediction equations, we split all data into development (70 %) and validation datasets (30 %). The model performance was evaluated using predicted residual error sum of squares, root mean squared error (RMSE), mean absolute error (MAE) and R2. We identified a top performing model with the least number of parameters (age, sex, weight and resistance index or resistance and height), low RMSE (FM 0·70, FFM 0·74, PBF 3·10), low MAE (FM 0·55, FFM 0·62, PBF 2·49), high R2 (FM 0·95, FFM 0·92, PBF 0·82) and the least difference between predicted values and actual values from DXA (FM 0·03 kg or 0·01 sd, FFM 0·06 kg or 0·02 sd, PBF 0·27 % or 0·04 sd). In conclusion, we developed the first valid and highly predictive equations to estimate FM, FFM and PBF in Vietnamese children using BIA. These findings have important implications for future research on the double burden of disease and risks associated with overweight and obesity in young children.
