Environmental research · 2021
Exposure to air pollutants during pregnancy and after birth increases the risk of neonatal hyperbilirubinemia.
СтатьяМногоцентровое исследованиеПоддержка исследования: вне правительства СШАНазвание и аннотация: Перевод в очереди
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Zhuang Jialu, Hu Jie, Bei Fei, Huang Jiahu, Wang Liangjun, Zhao Junjie, Qian Ruiying, Sun Jianhua
Аннотация
OBJECTIVES: Exposure to air pollution is associated with increased risks of several adverse conditions in newborns, such as preterm birth. Whether air pollution is associated with neonatal hyperbilirubinemia remains unclear. We aimed to develop and validate an air-quality-based model to better predict neonatal hyperbilirubinemia.
METHODS: A multicenter, population-based cohort of neonates with a gestational age (GA) ≥35 weeks and birth weight ≥2000 g was enrolled in the study. The study was conducted in Shanghai, China, from July 2017 to December 2018. The daily average concentrations of particulate matter (PM) with aerodynamic diameters≤2.5 μm (PM2.5) and ≤10 μm (PM10), sulfur dioxide (SO2), nitrogen dioxide (NO2) and carbon monoxide (CO) were measured. Neonatal hyperbilirubinemia was diagnosed according to the American Academy of Pediatrics (AAP) guidelines by trained neonatologists. We used logistic least absolute shrinkage and selection operator (LASSO) regression to screen air pollutant indicators related to neonatal hyperbilirubinemia and build an air-quality signature for each patient. An air-quality-based nomogram was then established to predict the risk of neonatal hyperbilirubinemia.
RESULTS: A total of 11196 neonates were evaluated. Prenatal PM10, CO and NO2 exposure and postpartum SO2 exposure were significantly associated with neonatal hyperbilirubinemia. The air-quality score was calculated according to the hyperbilirubinemia-related pollutants. The air-quality score of the hyperbilirubinemia group was significantly higher than that of the nonhyperbilirubinemia group (P < .01, odds ratio = 2.97). An air-quality-based logistic regression model was built and showed good discrimination (C-statistic of 0.675 [95% CI (confidence interval), 0.658 to 0.692]) and good calibration. Decision curve analysis showed that the air-quality-based model was better than the traditional clinical model in predicting neonatal hyperbilirubinemia.
CONCLUSIONS: The findings of this study suggest that ambient air pollution exposure is associated with an increased risk of neonatal hyperbilirubinemia. Our results encourage further exploration of this possibility in future studies.
METHODS: A multicenter, population-based cohort of neonates with a gestational age (GA) ≥35 weeks and birth weight ≥2000 g was enrolled in the study. The study was conducted in Shanghai, China, from July 2017 to December 2018. The daily average concentrations of particulate matter (PM) with aerodynamic diameters≤2.5 μm (PM2.5) and ≤10 μm (PM10), sulfur dioxide (SO2), nitrogen dioxide (NO2) and carbon monoxide (CO) were measured. Neonatal hyperbilirubinemia was diagnosed according to the American Academy of Pediatrics (AAP) guidelines by trained neonatologists. We used logistic least absolute shrinkage and selection operator (LASSO) regression to screen air pollutant indicators related to neonatal hyperbilirubinemia and build an air-quality signature for each patient. An air-quality-based nomogram was then established to predict the risk of neonatal hyperbilirubinemia.
RESULTS: A total of 11196 neonates were evaluated. Prenatal PM10, CO and NO2 exposure and postpartum SO2 exposure were significantly associated with neonatal hyperbilirubinemia. The air-quality score was calculated according to the hyperbilirubinemia-related pollutants. The air-quality score of the hyperbilirubinemia group was significantly higher than that of the nonhyperbilirubinemia group (P < .01, odds ratio = 2.97). An air-quality-based logistic regression model was built and showed good discrimination (C-statistic of 0.675 [95% CI (confidence interval), 0.658 to 0.692]) and good calibration. Decision curve analysis showed that the air-quality-based model was better than the traditional clinical model in predicting neonatal hyperbilirubinemia.
CONCLUSIONS: The findings of this study suggest that ambient air pollution exposure is associated with an increased risk of neonatal hyperbilirubinemia. Our results encourage further exploration of this possibility in future studies.