TY - JOUR
T1 - Development of population-specific prediction equations for bioelectrical impedance analyses in Vietnamese children
AU - Nguyen, Phuong Hong
AU - Young, Melissa F.
AU - Khuong, Long Quynh
AU - Ramakrishnan, Usha
AU - Martorell, Reynaldo
AU - Hoffman, Daniel J.
N1 - Publisher Copyright: © 2020 The Author(s). Published by Cambridge University Press on behalf of The Nutrition Society. Copyright: Copyright 2021 Elsevier B.V., All rights reserved.
PY - 2020/12/28
Y1 - 2020/12/28
N2 - 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.
AB - 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.
KW - Bioelectric impedance analysis
KW - Body composition
KW - Children
KW - Fat mass
KW - Prediction
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U2 - https://doi.org/10.1017/S000711452000241X
DO - https://doi.org/10.1017/S000711452000241X
M3 - Article
C2 - 32616079
SN - 0007-1145
VL - 124
SP - 1345
EP - 1352
JO - British Journal of Nutrition
JF - British Journal of Nutrition
IS - 12
ER -