Weight for length measures may not accurately reflect adiposity in preterm infants born appropriate for gestational age during hospitalisation or after discharge from the neonatal intensive care unit

Defining Body Mass Index Using Weight and Length for Gestational Age in the Growth Assessment of Preterm Infants at Birth

OBJECTIVE

The objectives of this study were to describe (1) body mass indexes (BMIs) using weight and length for gestational age (GA) classifications, and (2) the additional information BMI, as a measure of body proportionality, provides for preterm infant growth assessment and care plans at birth.

STUDY DESIGN

Birth weight, length, and BMI of 188,646 preterm infants (24-36 weeks gestation) admitted to U.S. neonatal intensive care units (Pediatrix Clinical Data Warehouse, 2013-2018) were classified (Olsen curves) as small, appropriate, or large for GA (SGA < 10th, AGA 10-90th, LGA > 90th percentile for GA, respectively). The distribution for the 27 weight-length-BMI combinations was described.

RESULTS

At birth, most infants were appropriate for weight (80.0%), length (82.2%), head circumference (82.9%), and BMI (79.9%) for GA. Birth weight for GA identified approximately 20% of infants as SGA or LGA. Infants born SGA (or LGA) for both weight and length ("proportionate" in size) were usually appropriate for BMI (59.0% and 75.6%). BMI distinguished disproportionate weight for length in infants with SGA or LGA weight at birth (58.3%, 49.9%). BMI also identified 11.4% of AGA weight infants as small or large for BMI ("disproportionate" in size) at birth; only using weight for GA missed these underweight/overweight for length infants.

CONCLUSION

The unique, additional information provided by birth BMI further informs individualized preterm infant growth assessment by providing an assessment of an infant's body proportionality (weight relative to its length) in addition to the routine assessment of weight, length, and head circumference for GA and may better inform care plans and impact outcomes.

KEY POINTS

· Most preterm infants were born AGA for all growth measures.. · AGA weight infants may be under- or overweight for length.. · BMI distinguished body disproportionality in SGA/LGA infants.. · Recommend BMI assessed along with weight, length and head.. · Further research on BMI in preterm infants is needed..

Predicting body fat percentage at 36 weeks of postmenstrual age in infants born preterm: A diagnostic accuracy study

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.

Body composition measurement for the preterm neonate: using a clinical utility framework to translate research tools into clinical care

Body composition analysis to distinguish between fat mass and fat-free mass is an established research approach to assess nutritional status. Within neonatal medicine, preterm infant body composition is linked with later health outcomes including neurodevelopment and cardiometabolic health. Mounting evidence establishing fat-free mass as an indicator of nutritional status, coupled with the availability of testing approaches that are feasible to use in preterm infants, have enhanced interest in measuring body composition in the neonatal intensive care unit (NICU) setting. In this paper, we use the concept of clinical utility-the added value of a new methodology over current standard care-as a framework for assessing several existing body composition methodologies with potential for clinical application to preterm neonates. We also use this framework to identify remaining knowledge gaps and prioritize efforts to advance our understanding of clinically-oriented body composition testing in the NICU.