ABSTRACT
BACKGROUND/OBJECTIVES: Assessment of infant body composition (BC) is crucial to understand the consequences of suboptimal nutritional status and postnatal growth, and the effects of public health interventions. Bioelectrical impedance analysis (BIA) is a feasible, relatively inexpensive and noninvasive method for assessing BC. However, very little research has been conducted in low- and middle-income populations, where efforts to prevent or treat malnutrition in early life are a public health priority. We aimed to develop equations for predicting fat-free mass (FFM) and fat mass (FM) based on BIA in 0- to 6-month-old Ethiopian infants. SUBJECTS/METHODS: The study comprised a total of 186 BC assessments performed in 101 healthy infants, delivered at Jimma University Specialized Hospital. Infant air-displacement plethysmography (IADP) was the criterion method, whereas weight, length, sex, age and an impedance index (L(2)/Z50) were predictors. Prediction equations were developed using stepwise multiple linear regression and the accuracy was evaluated with a 10-fold cross-validation approach. RESULTS: A linear regression model based on body weight, age and sex predicted FFM, estimated by IADP, with an adjusted R(2) and root mean square error (RMSE) of 0.94 and 200 g, respectively. Adding impedance index to the model resulted in a significantly improved model fit (R(2)=0.95; RMSE=181 g). For infants below 3 months of age, inclusion of impedance index did not contribute to an improved model fit for predicting FFM compared with a model already comprising weight, sex and age. CONCLUSIONS: The derived equations predicted FFM with acceptable accuracy and may be used in future field surveys, epidemiological studies and clinical trials conducted in similar sub-Saharan African population groups aged 0-6 months.
