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Maternal exposure to ambient PM10 during pregnancy increases the risk of congenital heart defects: Evidence from machine learning models
Ren, Zhoupeng1; Zhu, Jun2,3; Gao, Yanfang1; Yin, Qian1; Hu, Maogui1; Dai, Li2; Deng, Changfei2; Yi, Lin3; Deng, Kui3; Wang, Yanping2; Li, Xiaohong3,4; Wang, Jinfeng1,5
2018-07-15
Source PublicationSCIENCE OF THE TOTAL ENVIRONMENT
ISSN0048-9697
Volume630Pages:1-10
Corresponding AuthorLi, Xiaohong(iiaoong@163.com) ; Wang, Jinfeng(wangjf@lreis.ac.cn)
AbstractPrevious research suggested an association between maternal exposure to ambient air pollutants and risk of congenital heart defects (CHDs), though the effects of particulate matter <= 10 mu m in aerodynamic diameter (PM10) on CHDs arc inconsistent. We used two machine learning models (i.e., random forest (RE) and gradient boosting (GB)) to investigate the non-linear effects of PM10 exposure during the critical time window, weeks 3-8 in pregnancy, on risk of CHDs. From 2009 through 2012, we carried out a population-based birth cohort study on 39,053 live-born infants in Beijing. Rr and GB models were used to calculate odds ratios for CHDs associated with increase in PM10 exposure, adjusting for maternal and perinatal characteristics. Maternal exposure to PM10 was identified as the primary risk factor for CHDs in all machine learning models. We observed a clear non-linear effect of maternal exposure to PM10 on CHDs risk. Compared to 40 mu g m(-3), the following odds ratios resulted: 1) 92 mu g m(-3) [RF: 1.16 (95% CI: 1.06, 1.28); GB: 1.26 (95% CI: 1.17,135)]; 2) 111 mu g m(-3) [RF: 1.04 (95% CI: 0.96,1.14); GB: 1.04 (95% CI: 0.99,1.08)1; 3) 124 mu g m(-3) [RF: 1.01 (95% CI: 0.94, 1.10); GB: 0.98 (95% CI: 0.93,1.02)]; 4) 190 mu g m(-3) [RF: 129 (95% CI: 1.14, 1.44); GB: 1.71 (95% CI: 1.04, 2.17)1. Overall, both machine models showed an association between maternal exposure to ambient PM10 and CHDs in Beijing, highlighting the need for non-linear methods to investigate dose-response relationships. (C) 2018 Elsevier B.V. All rights reserved.
KeywordCongenital heart defects Machine learning Air pollution Birth defects Particulate matter
DOI10.1016/j.scitotenv.2018.02.181
WOS KeywordSAN-JOAQUIN VALLEY ; AIR-POLLUTION ; PRETERM BIRTH ; SYSTEMATIC ANALYSIS ; PARTICULATE MATTER ; UNDER-5 MORTALITY ; CHILD-MORTALITY ; NORTH-CAROLINA ; CHINA ; DISEASE
Indexed BySCI
Language英语
Funding ProjectNational Twelfth Five-Year Plan for Science & Technology Support[2014BAI06B01] ; National Key Research and Development Project[2017YFC0211705] ; National Science Foundation[41531179] ; National Science Foundation[41421001] ; National Science Foundation[81573165] ; National Science Foundation for Young Scholars of China[81502818]
Funding OrganizationNational Twelfth Five-Year Plan for Science & Technology Support ; National Key Research and Development Project ; National Science Foundation ; National Science Foundation for Young Scholars of China
WOS Research AreaEnvironmental Sciences & Ecology
WOS SubjectEnvironmental Sciences
WOS IDWOS:000432467700001
PublisherELSEVIER SCIENCE BV
Citation statistics
Document Type期刊论文
Identifierhttp://ir.igsnrr.ac.cn/handle/311030/54895
Collection中国科学院地理科学与资源研究所
Corresponding AuthorLi, Xiaohong; Wang, Jinfeng
Affiliation1.Chinese Acad Sci, Inst Geog Sci & Nat Resource Res, State Key Lab Resources & Environm Informat Syst, Beijing, Peoples R China
2.Sichuan Univ, West China Univ Hosp 2, Dept Obstet, Natl Off Maternal & Child Hlth Surveillance China, Chengdu, Sichuan, Peoples R China
3.Sichuan Univ, West China Univ Hosp 2, Dept Pediat, Natl Ctr Birth Defect Monitoring China, Chengdu, Sichuan, Peoples R China
4.Sichuan Univ, Minist Educ, Key Lab Birth Defects & Related Dis Women & Child, Chengdu, Sichuan, Peoples R China
5.Univ Chinese Acad Sci, Beijing, Peoples R China
Recommended Citation
GB/T 7714
Ren, Zhoupeng,Zhu, Jun,Gao, Yanfang,et al. Maternal exposure to ambient PM10 during pregnancy increases the risk of congenital heart defects: Evidence from machine learning models[J]. SCIENCE OF THE TOTAL ENVIRONMENT,2018,630:1-10.
APA Ren, Zhoupeng.,Zhu, Jun.,Gao, Yanfang.,Yin, Qian.,Hu, Maogui.,...&Wang, Jinfeng.(2018).Maternal exposure to ambient PM10 during pregnancy increases the risk of congenital heart defects: Evidence from machine learning models.SCIENCE OF THE TOTAL ENVIRONMENT,630,1-10.
MLA Ren, Zhoupeng,et al."Maternal exposure to ambient PM10 during pregnancy increases the risk of congenital heart defects: Evidence from machine learning models".SCIENCE OF THE TOTAL ENVIRONMENT 630(2018):1-10.
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