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Updated: Sep 2, 2026
Assessment of Child Anthropometry in a Large Epidemiologic Study
Published on: February 2, 2017
Predicting body fat percentage at 36 weeks of postmenstrual age in infants born preterm: A diagnostic accuracy study
Jacqueline Razzaghy1, Li Zhang2, Nengjun Yi2
1Department of Pediatrics, Division of Neonatology, School of Medicine, University of Alabama at Birmingham, Birmingham, Alabama, USA.
Insights
A new predictive equation accurately estimates body fat percentage in preterm infants using weight gain, length, midarm circumference, sex, and fluid intake. This offers a practical method for assessing body composition in this vulnerable population.
Area of Science:
- Neonatalogy
- Pediatric Nutrition
- Body Composition Analysis
Background:
- Current methods for assessing infant body composition are often expensive and complex.
- There is a clinical need for a predictive model for body composition in preterm infants.
Purpose of the Study:
- To develop a broadly applicable predictive equation for body fat percentage in preterm infants.
- To integrate clinical and anthropometric factors for accurate body composition assessment.
Main Methods:
- Analyzed prospective anthropometric and clinical data from very preterm infants (born ≤32 weeks gestation).
- Employed Bayesian linear regression models and leave-one-out cross-validation.
- Integrated variables significantly associated with adiposity into the predictive equation.
Main Results:
- The final model, incorporating weight gain, length increase, midarm circumference, male sex, and enteral fluid intake, achieved an R² of 0.65.
- A high correlation (r=0.82) was observed between predicted and actual body fat percentage.
- Key predictors included weekly weight and length gain, midarm circumference, male sex, and high enteral fluid intake.
Conclusions:
- Established significant predictors of body fat percentage at 36 weeks postmenstrual age in very preterm infants.
- The developed equation provides a reliable, non-invasive method for body composition assessment.
- Findings support the use of clinical and anthropometric data for estimating adiposity in preterm neonates.
Background:
Current standards for assessing body composition can be costly and technically challenging. There is a need for a predictive equation that combines multiple clinical and anthropometric factors to predictbody composition outcomes at 36 weeks of postmenstrual age (PMA) or discharge.
Methods:
To develop a widely applicable equation that predicts body fat percentage in preterm infants, we analyzed anthropometric data collected prospectively from a cohort of infants born very preterm between 2017 and 2018. We integrated clinical variables significantly associated with adiposity into a predictive equation using Bayesian linear regression models and leave-one-out cross-validation.
Results:
We analyzed data from 86 infants born at 32 weeks of gestation or less (median gestational age, 30 weeks; mean birthweight, 1471 ± 270 g). Weight gain and increase in length per week from birth to 36 weeks of PMA, midarm circumference at 36 weeks of PMA, male sex, and higher enteral fluid intake (>180 ml/kg/day) were the strongest predictors of body fat percentage in the model with the highest predictive value (R2 = 0.65). The correlation between actual and predicted body fat percentage using this Bayesian model was high (r = 0.82).
Conclusions:
Weight gain and increase in length per week from birth to 36 weeks of PMA, midarm circumference at 36 weeks of PMA, male sex, and enteral fluid intake are significant predictors of body fat percentage at 36 weeks of PMA in very preterm infants.
