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Calibration of bioelectrical impedance analysis for body composition assessment in Ethiopian infants using
R Wibæk1,2, P Kæstel1, S R Skov1,2
1Department of Nutrition, Exercise and Sports, Faculty of Science, University of Copenhagen, Copenhagen, Denmark.
Insights
Accurate infant body composition prediction is vital for assessing malnutrition. New equations using bioelectrical impedance analysis (BIA) in Ethiopian infants show promising results for field studies.
Area of Science:
- Pediatric Nutrition
- Body Composition Assessment
- Public Health Interventions
Background:
- Infant body composition (BC) assessment is crucial for understanding nutritional status and growth.
- Bioelectrical impedance analysis (BIA) is a feasible, noninvasive BC assessment method.
- Limited research exists on BIA in low- and middle-income populations for infant malnutrition.
Purpose of the Study:
- Develop predictive equations for fat-free mass (FFM) and fat mass (FM) using BIA.
- Assess BIA's utility in Ethiopian infants aged 0-6 months.
- Improve BC assessment in resource-limited settings.
Main Methods:
- Used infant air-displacement plethysmography (IADP) as the criterion method.
- Collected data on weight, length, sex, age, and impedance index (L(2)/Z50) from 101 healthy infants.
- Developed prediction equations using stepwise multiple linear regression and 10-fold cross-validation.
Main Results:
- A model with body weight, age, and sex predicted FFM with R(2)=0.94.
- Adding the impedance index significantly improved FFM prediction (R(2)=0.95).
- For infants <3 months, the impedance index did not improve FFM prediction beyond weight, sex, and age.
Conclusions:
- Derived equations predict FFM with acceptable accuracy in Ethiopian infants.
- These equations are suitable for field surveys, epidemiological studies, and clinical trials.
- The findings support BIA's use in sub-Saharan African infant populations aged 0-6 months.
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.
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