Abstract.
BACKGROUND: Body composition is a key metric for assessing nutrition in preterm infants. In many neonatal intensive care units body composition is estimated using anthropometric indices which mathematically combine body weight and length. However, the accuracy of these indices is unknown in preterm infants. In contrast, air-displacement plethysmography (ADP) has been shown to accurately measure neonatal fat mass, but it is not widely available.
OBJECTIVE: The aim was to determine which anthropometric index is most correlated to infant fat mass, as determined by ADP. DESIGN: We performed a retrospective observational study, comparing ADP-determined percent body fat at 366 time points for 239 preterm infants (born <32 weeks), with simultaneous weight and length measurements. Non-linear regression was performed to determine the best fit anthropometric index to the body fat percentage as determined by ADP. Our non-linear regression model, % fat = AxwtαxLβ, is the generalization of the most common anthropometric indices (BMI, ponderal index, etc.).
RESULTS: The best-fit regression formula most closely matched the formula for BMI. However, the regression explained only 51% of variability seen in body fat percentage at post-menstrual age <50 weeks, and 16% of variation seen at 50 weeks or greater.
CONCLUSION: Even optimal formulas relating weight and length to body fat percentage predict only a fraction of the variation seen in body composition, especially beyond 50 weeks. BMI was the anthropometric index most predictive of body fat percentage, but still has limited accuracy.