Abstract
BackgroundMost of the studies regarding air pollution and preterm birth (PTB) in highly polluted areas have estimated the exposure level based on fixed-site monitoring. However, exposure assessment methods relying on monitors have the potential to cause exposure misclassification due to a lack of spatial variation. In this study, we utilized a land use regression (LUR) model to assess individual exposure, and explored the association between PM2.5 exposure during each time window and the risk of preterm birth in Wuhan city, China.MethodsInformation on 2101 singleton births, which were ≥ 20 weeks of gestation and born between November 1, 2013 and May 31, 2014; between January 1, 2015 and August 31, 2015, was obtained from the Obstetrics Department in one 3A hospital in Wuhan. Air quality index (AQI) data were accessed from the Wuhan Environmental Protection Bureau website. Individual exposure during pregnancy was assessed by LUR models and Kriging interpolation. Logistic regression analyses were conducted to determine the association between women exposure to PM2.5 and the risk of different subtypes of PTB.ResultsDuring the study period, the average individual exposure concentration of PM2.5 during the entire pregnancy was 84.54 μg/m3. A 10 μg/m3 increase of PM2.5 exposure in the first trimester (OR: 1.169; 95% CI: 1.077, 1.262), the second trimester (OR: 1.056; 95% CI: 1.015, 1.097), the third trimester (OR: 1.052; 95% CI: 1.002, 1.101), and the entire pregnancy (OR: 1.263; 95% CI: 1.158, 1.368) was significantly associated with an increased risk of PTB. For the PTB subgroup, the hazard of PM2.5 exposure during pregnancy was stronger for very preterm births (VPTB) than moderate preterm births (MPTB). The first trimester was the most susceptible exposure window. Moreover, women who had less than 9 years of education or who conceived during the cold season tended to be more susceptible to the PM2.5 exposure during pregnancy.ConclusionsMaternal exposure to PM2.5 increased the risk of PTB, and this risk was stronger for VPTB than for MPTB, especially during the first trimester.
Highlights
Most of the studies regarding air pollution and preterm birth (PTB) in highly polluted areas have estimated the exposure level based on fixed-site monitoring
We examined whether specific subgroups were more vulnerable to the effect of maternal PM2.5 exposure, subgroups were stratified by sex of infant, years of education (≤9, 10–13, ≥14 years), and season of conception [warm (March–August) or cold (September–February)]
Among the PTB group, the percentages of women who were younger than 24 years old, had less than 9 years of education, were pregnant before, had gestational hypertension and gestational diabetes, and who conceived during the cold season were significantly higher than term birth group (Table 1)
Summary
Most of the studies regarding air pollution and preterm birth (PTB) in highly polluted areas have estimated the exposure level based on fixed-site monitoring. We utilized a land use regression (LUR) model to assess individual exposure, and explored the association between PM2.5 exposure during each time window and the risk of preterm birth in Wuhan city, China. A previous study found that different subtypes of PTB, defined by gestational age, have been associated with different risk factors, including air pollution [15]. Researchers have explored the trimester-specific association between PM2.5 exposure and PTB [11, 12, 17], the results regarding the most susceptible exposure window have been inconsistent and remain controversial [18]. Aside from the heterogeneity of study areas and populations, the different methods of exposure assessment are an important reason for the estimate bias, which cannot be ignored [19]
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