An anthropometric model to estimate neonatal fat mass using air displacement plethysmography

Background: Current validated neonatal body composition methods are limited/impractical for use outside of a clinical setting because they are labor intensive, time consuming, and require expensive equipment. The purpose of this study was to develop an anthropometric model to estimate neonatal fat mass (kg) using an air displacement plethysmography (PEA POD (R) Infant Body Composition System) as the criterion. Methods: A total of 128 healthy term infants, 60 females and 68 males, from a multiethnic cohort were included in the analyses. Gender, race/ethnicity, gestational age, age (in days), anthropometric measurements of weight, length, abdominal circumference, skin-fold thicknesses (triceps, biceps, sub scapular, and thigh), and body composition by PEA POD (R) were collected within 1 3 days of birth. Backward stepwise linear regression was used to determine the model that best predicted neonatal fat mass. Results: The statistical model that best predicted neonatal fat mass (kg) was: -0.012-0.064*gender + 0.024*day of measurement post-delivery -0.150*weight (kg) + 0.055*weight (kg)(2) + 0.046*ethnicity + 0.020*sum of three skin-fold thicknesses (triceps, sub scapular, and thigh); R-2 = 0.81, MSE = 0.08 kg. Conclusions: Our anthropometric model explained 81% of the variance in neonatal fat mass. Future studies with a greater variety of neonatal anthropometric measurements may provide equations that explain more of the variance.