大气污染短期暴露与胎盘早剥关联的巢式病例对照研究  

Association between short-term air pollution exposure and placental abruption:a nested case-control study

作　　者：刘涵 王童 詹宇 郭瑛 凌曦 杨桓[2] 陈卿[2] 周文正 曹佳 LIU Han;WANG Tong;ZHAN Yu;GUO Ying;LING Xi;YANG Huan;CHEN Qing;ZHOU Wenzheng;CAO Jia(Department of Labor Health,School of Public Health,Shanxi Medical University,Taiyuan 030001,China;Institute of Toxicology,College of Preventive Medicine,Army Medical University(Third Military Medical University),Chongqing 400038,China;Department of Environmental Science and Engineering,College of Architecture and Environment,Sichuan University,Chengdu 610065,China;Clinical and Public Health Research Center,Women and Children′s Hospital of Chongqing Medical University,Chongqing 401147,China)

机构地区：[1]山西医科大学公共卫生学院劳动卫生教研室,太原030001 [2]陆军军医大学(第三军医大学)军事预防医学系军事毒理学研究所,重庆400038 [3]四川大学建筑与环境学院环境科学与工程系,成都610065 [4]重庆医科大学附属妇女儿童医院临床与公共卫生研究中心,重庆401147

出　　处：《中华疾病控制杂志》2024年第4期424-430,共7页Chinese Journal of Disease Control & Prevention

基　　金：国家重点研发计划(2022YFC2702900)。

摘　　要：目的探索大气污染短期暴露与胎盘早剥发病风险的关联。方法采用巢式病例对照研究,以重庆市大型出生队列2018年7月31日—2022年7月31日新发798例胎盘早剥孕妇作为病例组,按照年龄、孕周、孕次、产次和分娩日期的匹配因素以1∶4的比例匹配,匹配未发生胎盘早剥的对照组3192例。通过机器学习算法估算研究期间6种空气污染物(PM_(10)、PM_(2.5)、NO_(2)、CO、O_(3)和SO_(2))及气象因素数据集,并与每位研究对象居住地址的经纬度匹配。构建基于条件logistic回归的分布滞后非线性模型探索大气污染物短期暴露与胎盘早剥的暴露-反应关系,控制环境温度、相对湿度、风速、大气压力和归一化差异植被指数,以及孕妇年龄、孕周、孕次、产次、分娩季节、是否经历疫情、家庭住址的影响。结果单污染物模型结果显示,累积暴露4~7 d内,NO_(2)与胎盘早剥发病风险升高存在显著关联,NO_(2)每四分位数间距增加对应的OR值及95%CI为1.38(95%CI:1.11~1.73,P<0.001)~1.54(95%CI:1.18~2.02,P<0.001)。总体剂量-反应关系曲线显示,随着NO_(2)浓度升高,胎盘早剥发病风险增加,暴露-反应曲线近似呈线性,其他污染物短期暴露与胎盘早剥风险的关联均无统计学意义(均P>0.05)。结论NO_(2)短期暴露与胎盘早剥急性发病风险升高存在关联,可能是胎盘早剥的影响因素,未来有必要对此进一步开展研究加以验证。Objective To explore the association between short-term air pollution exposure and acute onset of placental abruption.Methods This study is a nested case-control study nested in the large birth cohort of Chongqing.A total of 798 pregnant women with new placental abruption from July 31,2018 to July 31,2022 were selected as the case group.A control group of 3,192 women without abruptio placentae was matched at a ratio of 1∶4 according to age,gestational age,gravidity,parity,and delivery date.The data set of six air pollutants(PM_(10),PM_(2.5),NO_(2),CO,O_(3),SO_(2))and meteorological factors was estimated by machine learning algorithm and matched with the longitude and latitude of each subject′s residence address.A distributed lag non-linear models based on conditional Logistic regression was constructed to explore the exposure-response relationship between short-term air pollutants exposure and placental abruption,controlling the effects of temperature,relative humidity,wind speed,atmospheric pressures and NDVI,as well as the age,gestation week,gravidity(first pregnancy/non-first pregnancy),pravity(first birth/non-first birth),delivery season(cool/warm seasons),whether experienced the epidemic(Yes/No),and residential address(urban/countryside).Results The results of single pollutant model showed that NO_(2) was significantly associated with the increased risk of placental abruption within 4 to 7 days of cumulative exposure,and the odds ratio for each increase in IQR of NO_(2) was 1.38(95%CI:1.11-1.73,P<0.001)to to 1.54(95%CI:1.18-2.02,P<0.001).The overall dose-response curve showed that the risk of placental abruption increased with the increase of NO_(2) concentration,and the exposure-response curve was approximately linear.There was no statistically significant association between short-term exposure to other pollutants and the risk of placental abruption.Conclusions Short-term exposure to NO_(2) is associated with an increased risk of acute onset of placental abruption,which may be an influencing factor of

关 键 词：空气污染物 胎盘早剥 分布滞后非线性模型 

分 类 号：R181.34[医药卫生—流行病学] R994.6[医药卫生—公共卫生与预防医学] R714.25