Development of a predictive model of body fat mass for newborns and infants

Nutrition. 2023 Oct:114:112133. doi: 10.1016/j.nut.2023.112133. Epub 2023 Jun 15.

Abstract

Objectives: The aim of this study is to develop predictive body fat mass models, one for newborns and one for infants, using air displacement plethysmography as a reference method.

Methods: The study was carried out with 125 newborns (1-5 d of age) and 71 infants (≥3-6 mo). The stepwise method was used to estimate the final model from the predictors of sex, weight, length, triceps skinfold, waist circumference, mean arm circumference, and gestational age. The quality of the models was evaluated by the determination coefficient, variance inflation factor, and residual analysis. The paired t test and Bland-Altman plot were used to assess the agreement between observed and estimated values.

Results: The final model for newborns was - 0.76638 + 0.2512 * weight (kg) + 0.0620 * PCT (mm) + 0.0754 * gender (R² = 70%) and the final model for infants: -2.22748 + 0.4928 * weight (kg) + 0.0737 * TSF (mm) + 0.2647 * gender (R² = 84%).

Conclusions: This work determined equations to estimate the BFM of term newborns and infants. The models can be used in clinical practice, especially in health units without access to technologies for measuring body composition, adding important information for nutritional monitoring.

Keywords: Anthropometry; Body composition; Infant; Newborn; Plethysmography; Predictive mode.

MeSH terms

  • Adipose Tissue*
  • Aged
  • Anthropometry / methods
  • Body Composition*
  • Body Weight
  • Gestational Age
  • Humans
  • Infant
  • Infant, Newborn
  • Plethysmography / methods