Related Experiment Videos
Body composition in human infants at birth and postnatally
W W Koo1, J C Walters, E M Hockman
1Departments of Pediatrics, Obstetrics and Gynecology, University of Tennessee, Memphis, TN, USA.
Insights
Body weight and length accurately predict infant lean mass (LM) and fat mass (FM) using dual energy X-ray absorptiometry (DXA). These measurements are crucial for nutritional studies in infants.
Area of Science:
- Pediatric Nutrition
- Body Composition Analysis
- Anthropometry
Background:
- Accurate assessment of infant body composition, including lean mass (LM) and fat mass (FM), is vital for monitoring growth and the efficacy of nutritional interventions.
- Dual energy X-ray absorptiometry (DXA) is a key technology for measuring body composition, but its application in infants requires understanding predictive factors.
Purpose of the Study:
- To determine the predictive values of various factors (anthropometric measurements, race, gender, age, season) for DXA-derived body composition in infants.
- To assess the predictive value of body weight, LM, and FM for DXA bone measurements.
- To provide data for designing and evaluating infant nutritional intervention studies.
Main Methods:
- DXA scans were performed on 214 singleton infants (Caucasian and African American) aged 27-42 weeks gestational age, studied from birth to 391 days.
- Predictive values of anthropometric measurements, race, gender, gestational and postnatal ages, and season were analyzed for LM, FM, and %FM.
- Software version 5.64p was used to analyze scans acquired with a Hologic QDR 1000/W densitometer.
Main Results:
- Body weight, length, gender, and postnatal age were significant predictors of LM (adjusted R² >0.94) and FM (adjusted R² >0.85).
- Body weight was the primary predictor for LM and FM; length showed similar LM predictive value with increasing age.
- Physiological variables had limited predictive value for %FM, except in newborns (adjusted R² 0.69). Female infants exhibited lower LM and higher FM.
- LM or FM did not improve bone mass prediction compared to body weight.
Conclusions:
- DXA is a valuable tool for infant body composition assessment.
- Infant body weight and length are strong predictors of LM and FM, essential for nutritional study design.
- Understanding these predictive factors aids in the accurate assessment and design of nutritional interventions for infants.
Abstract:
The predictive values of anthropometric measurements, race, gender, gestational and postnatal ages, and season at birth and at study for the total body dual energy X-ray absorptiometry (DXA)-derived lean mass (LM), fat mass (FM) and fat mass as a percentage of body weight (%FM) were determined in 214 singleton appropriate birth weight for gestational age infants [101 Caucasian (60 boys, 41 girls) and 113 African American (55 boys, 58 girls)]. Gestational ages were 27-42 wk and the infants were studied between birth and 391 d, weighing between 851 and 13446 g. In addition, predictive value of body weight, LM and FM for DXA bone measurements was also determined. Scan acquisition used Hologic QDR 1000/W densitometer and infant platform and scans without significant movement artifacts were analyzed using software 5.64p. Body weight, length, gender and postnatal age were significant predictors of LM (adjusted R:(2) >0. 94) and FM (adjusted R:(2) >0.85). Physiologic variables had little predictive value for %FM except in the newborns (adjusted R:(2) 0. 69). Body weight was the dominant predictor of LM and FM, although length had similar predictive value for LM with increasing postnatal age. Female infants had less LM and more FM throughout infancy (P: < 0.01). LM or FM offered no advantage over body weight in the prediction of bone mass measurements. DXA is a useful means with which to determine body composition, and our data are important in the design and assessment of nutritional intervention studies.