Premature infants are born before the final weeks of pregnancy, a period when the body normally undergoes rapid and highly coordinated growth. After birth, their progress is tracked closely through weight, length and head circumference, measurements that help clinicians judge nutrition, organ development and vulnerability to complications. Yet a striking question has remained difficult to answer: when two preterm infants grow differently, how much of that difference reflects the babies themselves, and how much reflects the neonatal intensive care unit where they receive treatment? A new analysis from the New Jersey statewide neonatal collaborative focuses directly on that problem, examining the extent to which growth variability is associated with differences among NICUs.
The study, titled “Growth disparities among NICUs: insights from the New Jersey statewide neonatal collaborative,” was led by Michael Cohen, D.R. Brown and B. Rai and published in the Journal of Perinatology. Its central goal was not simply to compare which hospitals recorded larger or smaller infants, but to determine how much of the overall variation in growth could be statistically attributed to the NICU level. That distinction is crucial. Hospitals care for different populations, and infants arriving at one center may differ from those arriving at another in gestational age, birth weight, illness severity, genetic background and the circumstances surrounding delivery. A meaningful comparison therefore requires separating patient-level risk from the influence of institutional care.
Growth in extremely premature infants is a particularly sensitive measure of neonatal care because it reflects a chain of decisions made over days and weeks. Clinicians must balance adequate calories and protein against immature digestive systems, unstable circulation and the risk of complications such as necrotizing enterocolitis. Nutrition may begin through intravenous solutions before advancing to human milk or fortified feeds. The timing and intensity of these steps, along with respiratory support, infection prevention and management of fluid balance, can all affect a baby’s growth trajectory. Even small differences in practice, repeated over many weeks, may become visible in weight or head circumference by the time an infant leaves the hospital.
The New Jersey collaborative provides a setting in which those differences can be studied across a statewide network rather than within a single institution. Collaborative neonatal programs typically allow hospitals to share data, compare outcomes and identify patterns that may be invisible when each center examines its own patients in isolation. In this context, the investigators’ question is both statistical and clinical: do infants with similar medical profiles show different growth patterns depending on where they are treated? If the answer is yes, the next challenge is to determine whether the gap reflects modifiable practices, differences in resources, local protocols or the complex case mix of each unit.
Technically, this type of question is often addressed with hierarchical or multilevel statistical models. Infants are the individual observations, but they are grouped within NICUs, meaning that babies treated in the same unit may share exposure to the same feeding protocols, staffing structures, equipment, clinical culture and discharge policies. A model that ignores this clustering can underestimate uncertainty and make institutional differences appear more certain than they really are. By partitioning variation into infant-level and NICU-level components, researchers can estimate an intraclass correlation or related variance measure—an indication of how much outcomes resemble one another within the same hospital compared with across hospitals.
That calculation does not automatically prove that a hospital caused a particular growth outcome. A higher or lower NICU-associated component may reflect unmeasured differences among patients, such as illness severity or socioeconomic conditions, as well as care processes. Researchers therefore need to account for factors that strongly influence growth, including gestational age, birth weight, sex, major medical complications and length of hospitalization. The interpretation also depends on how growth is defined. A raw change in grams is not equivalent to a change in weight-for-age z-score, which compares an infant’s size with a reference population while adjusting for age and, in some approaches, sex. For premature infants, corrected age and appropriate growth standards are especially important.
The study’s focus on disparities among NICUs arrives at a moment when neonatal medicine is increasingly moving from broad outcome reporting toward precision quality improvement. Survival remains the first priority for critically premature infants, but survival alone does not capture the full experience of neonatal care. Growth failure can be associated with prolonged hospitalization and may signal inadequate nutrient delivery, inflammation or severe illness. At the same time, pushing weight gain without considering body composition or neurodevelopment would be an incomplete strategy. The value of a statewide analysis is that it can reveal whether variation is concentrated in particular dimensions of growth and whether the pattern is consistent enough to justify a coordinated response.
For families, the issue is deeply personal. Parents may assume that the major determinants of a premature baby’s growth are fixed at birth, yet hospital care can shape the weeks that follow. Differences in feeding plans, fortification practices, monitoring schedules and responses to feeding intolerance may influence how quickly an infant gains weight. However, hospital comparisons must be communicated carefully. A NICU serving the sickest infants may appear to have poorer growth outcomes simply because its patients face greater challenges. Conversely, an apparently favorable average may conceal differences in the babies who were admitted or transferred. The purpose of rigorous statistical adjustment is not to produce a simplistic ranking, but to identify patterns that can guide fairer and safer care.
The New Jersey findings therefore have potential significance beyond the state, even though their generalizability must be evaluated cautiously. Neonatal units differ in staffing, regional referral patterns, donor milk access, clinical guidelines and population characteristics. A pattern observed in one collaborative may not look identical elsewhere. Still, the analytical framework offers a practical way to ask whether institutional variation is larger than expected and where future improvement efforts should be directed. If meaningful NICU-level variation remains after accounting for infant characteristics, researchers can investigate specific practices that might explain it. If the variation is small, that result would also be informative, suggesting that patient-level biology and illness may dominate the growth outcomes measured.
The study ultimately shifts attention from the question of whether premature infants grow differently to the more actionable question of why. By quantifying the share of variability linked to the NICU, the researchers provide a foundation for distinguishing unavoidable clinical complexity from potentially preventable differences in care. The work does not reduce neonatal growth to a single number, nor does it imply that one measure can define the quality of an intensive care unit. Instead, it frames growth as a systems-level outcome—one shaped by biology, nutrition, medical decision-making and institutional practice. For neonatal medicine, that perspective could turn routine growth charts into a powerful tool for detecting hidden disparities and improving care across entire networks.
Subject of Research: Variability in the growth of preterm infants and the extent to which differences among neonatal intensive care units contribute to that variability.
Article Title: Growth disparities among NICUs: insights from the New Jersey statewide neonatal collaborative
Article References: Cohen, M., Brown, D.R., Rai, B. et al. Growth disparities among NICUs: insights from the New Jersey statewide neonatal collaborative. J Perinatol (2026). https://doi.org/10.1038/s41372-026-02871-y
Image Credits: AI Generated
DOI: 10.1038/s41372-026-02871-y
Keywords: preterm infants, neonatal intensive care units, infant growth, growth disparities, neonatal nutrition, quality improvement, New Jersey statewide neonatal collaborative, NICU outcomes
Tags: healthcare disparities in neonatal carehospital-based growth variabilityinfant nutrition and organ developmentneonatal care outcome analysisneonatal growth measurementneonatal intensive care unit variationneonatal research publicationsNew Jersey neonatal collaborativeNICU quality assessmentperinatology clinical studiesPremature infant growth disparitiespreterm infant development
