The association of prenatal exposure to intensive traffic with early preterm infant neurobehavioral development as reflected by the NICU Network Neurobehavioral Scale (NNNS)

Xueying Zhang, Emily Spear, Chris Gennings, Paul C. Curtin, Allan C. Just, Jennifer B. Bragg, Annemarie Stroustrup

Research output: Contribution to journalArticlepeer-review

15 Scopus citations

Abstract

Introduction: Traffic-related air pollution has been shown to be neurotoxic to the developing fetus and in term-born infants during early childhood. It is unknown whether there is an increased risk of adverse neurobehavioral outcome in preterm infants exposed to higher levels of air pollution during the fetal period. Objective: To assess the association between prenatal exposure to traffic-related air pollution on early preterm infant neurobehavior. Methods: Air pollution exposure was estimated by two methods: density of major roads and density of vehicle-miles traveled (VMT), each at multiple buffering areas around residential addresses. We examined the association between prenatal exposure to traffic-related air pollution and performance on the Neonate Intensive Care Unit (NICU) Network Behavioral Scale (NNNS), a measure of neurobehavioral outcome in infancy for 240 preterm neonates enrolled in the NICU-Hospital Exposures and Long-Term Health cohort. Linear regression analysis was conducted for exposure and individual NNNS subscales. Latent profile analysis (LPA) was applied to classify infants into distinct NNNS phenotypes. Multinomial logistic regression analysis was conducted between exposure and LPA groups. Covariates included gestational age, birth weight z-score, post-menstrual age at NNNS assessment, socioeconomic status, race, delivery type, maternal smoking status, and medical morbidities during the NICU stay. Results: Among all 13 NNNS subscales, hypotonia was significantly associated with VMT (104 vehicle-mile/km2) in 150 m (β = 0.01, P-value<0.001), 300 m (β = 0.01, P-value = 0.003), and 500 m (β = 0.01, P-value = 0.002) buffering areas, as well as with road density in a 500 m buffering area (β = 0.03, P-value = 0.03). We identified three NNNS phenotypes by LPA. Among them, high density of major roads within 150 m, 300 m, and 500 m buffers of the residential address was significantly associated with the same phenotype (P < 0.05). Conclusion: Prenatal exposure to intensive air pollution emitted from major roads may impact early neurodevelopment of preterm infants. Motor development may be particularly sensitive to air pollution-related toxicity.

Original languageEnglish
Article number109204
JournalEnvironmental Research
Volume183
DOIs
StatePublished - Apr 2020

Keywords

  • Latent profile analysis
  • NNNS
  • Traffic-related air pollution

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