PDF(Pubmed)
Abstract：
UNASSIGNED: To investigate the association between exposure to atmospheric pollutants and preterm birth in a river valley-type city and its critical exposure windows.
UNASSIGNED: A retrospective cohort study was used to collect data from the medical records of preterm and full-term deliveries in two hospitals in urban areas of a typical river valley-type city from January 2018 to December 2019. A total of 7,288 cases were included in the study with general information such as pregnancy times, the number of cesarean sections, occupation, season of conception and regularity of the menstrual cycle. And confounding factors affecting preterm birth were inferred using the chi-square test. The effects of exposure to each pollutant, including particulate matter 2.5 (PM2.5), particulate matter 10 (PM10), nitrogen dioxide (NO2), sulfur dioxide (SO2), carbon monoxide (CO) and ozone (O3), during pregnancy on preterm birth and the main exposure windows were explored by establishing a logistic regression model with pollutants introduced as continuous variables.
UNASSIGNED: Maternal age, pregnancy times, number of births, number of cesarean sections, season of conception, complications diseases, comorbidities diseases, hypertension disorder of pregnancy and neonatal low birth weight of the newborn were significantly different between preterm and term pregnant women. Logistic regression analysis after adjusting for the above confounders showed that the risk of preterm birth increases by 0.9, 0.6, 2.4% in T2 and by 1.0, 0.9, 2.5% in T3 for each 10 μg/m3 increase in PM2.5, PM10, NO2 concentrations, respectively. The risk of preterm birth increases by 4.3% in T2 for each 10 μg/m3 increase in SO2 concentrations. The risk of preterm birth increases by 123.5% in T2 and increases by 188.5% in T3 for each 10 mg/m3 increase in CO concentrations.
UNASSIGNED: Maternal exposure to PM2.5, PM10, NO2, CO was associated with increased risk on preterm birth in mid-pregnancy (T2) and late pregnancy (T3), SO2 exposure was associated with increased risk on preterm birth in mid-pregnancy (T2).
UNASSIGNED: A retrospective cohort study was used to collect data from the medical records of preterm and full-term deliveries in two hospitals in urban areas of a typical river valley-type city from January 2018 to December 2019. A total of 7,288 cases were included in the study with general information such as pregnancy times, the number of cesarean sections, occupation, season of conception and regularity of the menstrual cycle. And confounding factors affecting preterm birth were inferred using the chi-square test. The effects of exposure to each pollutant, including particulate matter 2.5 (PM2.5), particulate matter 10 (PM10), nitrogen dioxide (NO2), sulfur dioxide (SO2), carbon monoxide (CO) and ozone (O3), during pregnancy on preterm birth and the main exposure windows were explored by establishing a logistic regression model with pollutants introduced as continuous variables.
UNASSIGNED: Maternal age, pregnancy times, number of births, number of cesarean sections, season of conception, complications diseases, comorbidities diseases, hypertension disorder of pregnancy and neonatal low birth weight of the newborn were significantly different between preterm and term pregnant women. Logistic regression analysis after adjusting for the above confounders showed that the risk of preterm birth increases by 0.9, 0.6, 2.4% in T2 and by 1.0, 0.9, 2.5% in T3 for each 10 μg/m3 increase in PM2.5, PM10, NO2 concentrations, respectively. The risk of preterm birth increases by 4.3% in T2 for each 10 μg/m3 increase in SO2 concentrations. The risk of preterm birth increases by 123.5% in T2 and increases by 188.5% in T3 for each 10 mg/m3 increase in CO concentrations.
UNASSIGNED: Maternal exposure to PM2.5, PM10, NO2, CO was associated with increased risk on preterm birth in mid-pregnancy (T2) and late pregnancy (T3), SO2 exposure was associated with increased risk on preterm birth in mid-pregnancy (T2).
摘要：
■在河谷型城市及其临界暴露窗口中，调查暴露于大气污染物与早产之间的关联。
一项回顾性队列研究用于收集2018年1月至2019年12月在典型河谷型城市市区的两家医院中早产和足月分娩的病历数据。共有7,288例病例被纳入研究，包括怀孕时间等一般信息。剖宫产的次数,职业,受孕季节和月经周期的规律性。采用卡方检验推断影响早产的混杂因素。暴露于每种污染物的影响，包括颗粒物2.5（PM2.5），颗粒物10（PM10），二氧化氮(NO2),二氧化硫(SO2),一氧化碳（CO）和臭氧（O3），通过建立以污染物为连续变量的logistic回归模型，探讨了怀孕期间早产和主要暴露窗口。
■产妇年龄，怀孕时间,出生人数,剖宫产次数,受孕的季节，并发症疾病，合并症疾病，妊娠高血压疾病和新生儿低出生体重在早产和足月孕妇之间有显著差异。调整上述混杂因素后的Logistic回归分析显示,PM2.5、PM10、NO2浓度每增加10μg/m3,T2早产风险分别增加0.9、0.6、2.4%,T3早产风险分别增加1.0、0.9、2.5%,分别。SO2浓度每增加10μg/m3，T2中早产的风险增加4.3％。CO浓度每增加10mg/m3，T2的早产风险增加123.5％，T3的早产风险增加188.5％。
母亲接触PM2.5、PM10、NO2、CO与妊娠中期(T2)和妊娠晚期(T3)早产风险增加有关。SO2暴露与妊娠中期（T2）早产风险增加相关。
一项回顾性队列研究用于收集2018年1月至2019年12月在典型河谷型城市市区的两家医院中早产和足月分娩的病历数据。共有7,288例病例被纳入研究，包括怀孕时间等一般信息。剖宫产的次数,职业,受孕季节和月经周期的规律性。采用卡方检验推断影响早产的混杂因素。暴露于每种污染物的影响，包括颗粒物2.5（PM2.5），颗粒物10（PM10），二氧化氮(NO2),二氧化硫(SO2),一氧化碳（CO）和臭氧（O3），通过建立以污染物为连续变量的logistic回归模型，探讨了怀孕期间早产和主要暴露窗口。
■产妇年龄，怀孕时间,出生人数,剖宫产次数,受孕的季节，并发症疾病，合并症疾病，妊娠高血压疾病和新生儿低出生体重在早产和足月孕妇之间有显著差异。调整上述混杂因素后的Logistic回归分析显示,PM2.5、PM10、NO2浓度每增加10μg/m3,T2早产风险分别增加0.9、0.6、2.4%,T3早产风险分别增加1.0、0.9、2.5%,分别。SO2浓度每增加10μg/m3，T2中早产的风险增加4.3％。CO浓度每增加10mg/m3，T2的早产风险增加123.5％，T3的早产风险增加188.5％。
母亲接触PM2.5、PM10、NO2、CO与妊娠中期(T2)和妊娠晚期(T3)早产风险增加有关。SO2暴露与妊娠中期（T2）早产风险增加相关。
