Anthropometry-based indicators of body composition in children: 3 to 24-month multicenter study

Abstract

AbstractBackgroundAccurate assessment of body composition during infancy is important, especially for understanding the effects of early growth on later health. This study aimed to develop an anthropometry-based approach to predict body composition in 3–24 month old infants from diverse socioeconomic settings and ethnic groups.MethodsAn observational, longitudinal, prospective, multinational study of infants from birth to 24 months. Body composition was assessed at 3, 6, 9, 12, 18, and 24 months using deuterium dilution (DD) and anthropometry. Linear mixed modelling was utilized to generate sex-specific fat mass(FM) and fat-free mass(FFM) prediction equations. Length(m), weight-for-length(kg/m), triceps and subscapular skinfolds and Asian ethnicity were used as predictor variables. The study sample consisted of 1896(942 measurements from 310 girls) training data sets, 941(441 measurements from 154 girls) validation data sets from Brazil, Pakistan, South Africa and Sri Lanka, and 349(185 measurements from 124 girls) data sets of infants at 6 months from South Africa, Australia and India of external validation group.ResultsSex-specific equations for three age categories (3-9 months; 10-18 months; 19-24 months) were developed and validated and an external validation was performed on the test group. The root mean squared error(RMSE) was similar between validation and test data for assessment of FM and FFM. Root mean squared percentage error(RMSPE) and mean absolute percentage error(MAPE) in validation data were higher for predicting FM but lower for FFM compared to test data.ConclusionsAnthropometry-based FFM prediction equations provide acceptable results which have the potential to be developed as a field tool.