P M Catalano1, A J Thomas, D A Avallone, S B Amini. 1. Department of Reproductive Biology, Case Western Reserve University, MetroHealth Medical Center, Cleveland, OH 44109, USA.
Abstract
OBJECTIVE: Estimation of neonatal body composition can be useful in the understanding of fetal growth. However, body composition methods such as total body water and total body electric conductivity are expensive and not readily available. Our primary purpose was to develop an anthropometric model to estimate neonatal body composition and prospectively validate the model against total body electric conductivity and secondarily to compare our anthropometric model and a previously published anthropometric formula with total body electric conductivity. STUDY DESIGN: A total of 194 neonates had estimates of body composition according to total body electric conductivity (group 1). Parental morphometrics, gestational age, race, sex, parity, and neonatal measurements including birth weight, length, head circumference, and skinfolds (triceps, subscapular, flank, and thigh) were correlated with body fat by use of stepwise regression analysis. The model was validated in a second group of 65 neonates (group 2). RESULTS: There were no significant differences in any of the parental or neonatal measurements between groups 1 and 2. In group 1, 78% of the variance in body fat with the use of total body electric conductivity was explained by birth weight, length, and flank skinfold (R2 = 0.78, p = 0.0001). When prospectively validated by the subjects in group 2, the model had significant and stronger correlation (R2 = 0.84, p = 0.0001) with body fat estimated by total body electric conductivity as compared with the other anthropometric model (R2 = 0.54, p = 0.0001). There was no significant (p = 0.11) difference between our anthropometric estimate of body fat and total body electric conductivity. CONCLUSIONS: The anthropometric model developed can be used to reasonably predict neonatal body fat mass at birth.
OBJECTIVE: Estimation of neonatal body composition can be useful in the understanding of fetal growth. However, body composition methods such as total body water and total body electric conductivity are expensive and not readily available. Our primary purpose was to develop an anthropometric model to estimate neonatal body composition and prospectively validate the model against total body electric conductivity and secondarily to compare our anthropometric model and a previously published anthropometric formula with total body electric conductivity. STUDY DESIGN: A total of 194 neonates had estimates of body composition according to total body electric conductivity (group 1). Parental morphometrics, gestational age, race, sex, parity, and neonatal measurements including birth weight, length, head circumference, and skinfolds (triceps, subscapular, flank, and thigh) were correlated with body fat by use of stepwise regression analysis. The model was validated in a second group of 65 neonates (group 2). RESULTS: There were no significant differences in any of the parental or neonatal measurements between groups 1 and 2. In group 1, 78% of the variance in body fat with the use of total body electric conductivity was explained by birth weight, length, and flank skinfold (R2 = 0.78, p = 0.0001). When prospectively validated by the subjects in group 2, the model had significant and stronger correlation (R2 = 0.84, p = 0.0001) with body fat estimated by total body electric conductivity as compared with the other anthropometric model (R2 = 0.54, p = 0.0001). There was no significant (p = 0.11) difference between our anthropometric estimate of body fat and total body electric conductivity. CONCLUSIONS: The anthropometric model developed can be used to reasonably predict neonatal body fat mass at birth.
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