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Fat-Free Mass Predictions From Anthropometrics in South African Prepubertal Children
Zelda White1, Lauren M Walsh1, Adeline Pretorius2
1Department Human Nutrition, Faculty of Health Sciences, University of Pretoria, Pretoria, South Africa.
Insights
Simple anthropometric measurements can predict fat-free mass in children, aiding body composition assessment in resource-limited settings. This research addresses malnutrition challenges in South African children.
Area of Science:
- Pediatric Nutrition
- Body Composition Analysis
- Anthropometry
Background:
- South African children experience dual malnutrition: undernutrition and rising obesity.
- Accurate fat-free mass estimation is crucial for health assessment.
- Existing methods like bioelectrical impedance analysis have limitations in low-resource settings.
Purpose of the Study:
- To develop and validate prediction equations for fat-free mass.
- Utilize simple anthropometric measurements for estimation.
- Target children aged 6-9 years.
Main Methods:
- Cross-sectional study involving 117 children for equation development.
- Used bioelectrical impedance analysis as a reference.
- Externally validated four equations in 75 Black prepubertal children using DXA as standard.
Main Results:
- Developed fourteen prediction equations (R²: 0.88-0.92) using 5-9 variables.
- Four equations showed strong correlation (r > 0.95) with DXA-derived fat-free mass.
- Three equations demonstrated acceptable agreement (mean difference: 0.16-0.94 kg).
Conclusions:
- Fat-free mass in prepubertal children is predictable using simple anthropometric data.
- Enables body composition assessment in resource-limited environments.
- Provides a practical tool for monitoring child health.
Background:
South African children face a double burden of malnutrition from undernutrition and rising obesity. Simple, accurate methods to estimate fat-free mass, a key health indicator, are needed, as bioelectrical impedance analysis is limited by cost, availability and lack of local validation.
Objectives:
To develop and validate prediction equations for fat-free mass using simple anthropometric measurements in children aged 6-9 years.
Methods:
In this cross-sectional study, anthropometric and bioelectrical impedance data were obtained from 117 children. Bioelectrical impedance-derived fat-free mass was used as reference in multivariable regression models. Four equations were externally validated in 75 Black prepubertal children, using dual-energy X-ray absorptiometry-derived fat-free mass as standard. Relationships, mean differences, and agreement were assessed using Pearson's correlation, independent t-tests and Bland-Altman plots, respectively.
Results:
Fourteen prediction equations, containing five to nine variables, were developed (R 2 range: 0.88-0.92) in the sample of children (51% Black; 55% boys; 7.9 ± 0.8 years). Four equations were strongly correlated with dual-energy X-ray absorptiometry-derived fat-free mass (r > 0.95; p < 0.001) in the validation sample (8.5 ± 1.3 years), and three yielded estimates with acceptable agreement (mean difference: 0.16-0.94 kg; limit of agreement: ±5 kg).
Conclusion:
Fat-free mass of prepubertal children can be predicted using simple anthropometric measurements, allowing assessment of body composition in low-resource settings.
