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Updated: Jun 6, 2026
Assessment of Child Anthropometry in a Large Epidemiologic Study
Published on: February 2, 2017
Development and internal validation of a bioimpedance-based predictive model for assessing fat-free mass in infants,
Michela Perrone1, Paola Roggero1, Arianna Nicora1
1NICU, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, 20122 Milan, Italy.
Insights
A new bioelectrical impedance analysis (BIA) equation accurately estimates fat-free mass (FFM) in children and adolescents. This practical tool aids in monitoring pediatric growth and nutritional status.
Area of Science:
- Pediatric Body Composition Analysis
- Nutritional Assessment in Children
- Biomedical Engineering Applications
Background:
- Accurate body composition assessment is crucial for pediatric growth and nutritional monitoring.
- Reference methods like DXA and ADP are accurate but costly and limited.
- Bioelectrical impedance analysis (BIA) offers a portable, non-invasive alternative, but requires validated pediatric equations.
Purpose of the Study:
- To develop and validate a BIA-based predictive model for estimating fat-free mass (FFM) in healthy individuals from birth to 18 years.
- To utilize air displacement plethysmography (ADP) as the reference method for validation.
- To establish a practical and reliable tool for pediatric body composition assessment.
Main Methods:
- An exploratory cross-sectional study involving 142 participants (0-18 years).
- Collection of anthropometric and bioelectrical impedance parameters.
- Development of multiple linear regression models using training (70%) and validation (30%) cohorts, incorporating weight, sex, and impedance variables (L²/R₅₀).
Main Results:
- BIA-based models incorporating impedance index significantly outperformed anthropometry-only models.
- The optimal model (weight + sex + impedance index [L²/R₅₀]) demonstrated high predictive accuracy (0-1 year: R²=0.953; 2-18 years: R²=0.987).
- Bland-Altman analysis confirmed minimal bias and narrow limits of agreement between BIA-derived FFM and ADP.
Conclusions:
- The developed BIA-based equation is a practical, reliable, and accurate tool for estimating FFM across pediatric ages.
- The equation shows potential for widespread clinical application in monitoring pediatric growth and nutritional status.
- External validation in independent cohorts is recommended to confirm generalizability.
Background And Aims:
Accurate evaluation of body composition in infants, children and adolescents is essential for monitoring growth and nutritional status. Reference methods such as air displacement plethysmography (ADP) and dual-energy X-ray absorptiometry (DXA) offer high accuracy but are costly and limited to specialized settings. Bioelectrical impedance analysis (BIA) provides a portable, non-invasive alternative; however, predictive equations for estimating fat-free mass (FFM) in pediatric populations require further validation. Considering this, our study aimed to develop and validate a BIA-based predictive model for estimating FFM in healthy subjects from birth to 18 years, using ADP as reference method.
Methods:
An exploratory cross-sectional study was conducted on 142 participants (86 aged 0-1 year; 56 aged 2-18 years). Anthropometric and bioelectrical impedance parameters were collected following standardized protocols. Participants were randomly assigned to training (70%) and validation (30%) cohorts. Multiple linear regression models incorporating weight, length/height, sex, and impedance variables were tested. Model performance was evaluated using adjusted R2 and root mean square error (RMSE); agreement with ADP-derived FFM was assessed through Bland-Altman analysis.
Results:
In both age groups, models including impedance-index outperformed anthropometry-only models. The best model (weight + sex + impedance index [L2/R50]) achieved excellent predictive accuracy (0-1 year: adjusted R2 = 0.953, RMSE = 0.183 kg; 2-18 years: adjusted R2 = 0.987, RMSE = 1.409 kg). Bland-Altman analysis showed minimal bias and narrow limits of agreement.
Conclusions:
the proposed developed BIA-based equation provides a practical, reliable, and highly accurate tool for estimating FFM across pediatric ages, supporting its potential application in clinical practice. However, the present findings are based on an internal validation using a split-sample strategy, and external validation in independent cohorts is warranted to confirm the generalizability of the proposed equation.
