Bo-Yi Yang1, Yanji Qu2, Yuming Guo3, Iana Markevych4, Joachim Heinrich5, Michael S Bloom6, Zhipeng Bai7, Luke C Knibbs8, Shanshan Li3, Gongbo Chen1, Bin Jalaludin9, Lidia Morawska10, Meng Gao11, Bin Han7, Yunjiang Yu12, Xiao-Xuan Liu1, Yanqiu Ou2, Jinzhuang Mai2, Xiangmin Gao2, Yong Wu2, Zhiqiang Nie2, Xiao-Wen Zeng1, Li-Wen Hu1, Xubo Shen13, Yuanzhong Zhou13, Shao Lin14, Xiaoqing Liu15, Guang-Hui Dong16. 1. Guangdong Provincial Engineering Technology Research Center of Environmental and Health Risk Assessment, Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China. 2. Department of Epidemiology, Guangdong Cardiovascular Institute, Guangdong General Hospital, China. 3. Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC 3004, Australia. 4. Institute of Psychology, Jagiellonian University, Poland. 5. Institute and Clinic for Occupational, Social and Environmental Medicine, University Hospital, LMU Munich, Ziemssenstraße 1, 80336 Munich, Germany; Comprehensive Pneumology Center Munich, German Center for Lung Research, Ziemssenstraße 1, 80336 Munich, Germany. 6. Departments of Environmental Health Sciences and Epidemiology and Biostatics, University at Albany, State University of New York, Rensselaer, NY 12144, USA. 7. State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, China. 8. School of Public Health, The University of Queensland, Herston, Queensland 4006, Australia. 9. Centre for Air Quality and Health Research and Evaluation, Glebe, NSW 2037, Australia; Population Health, South Western Sydney Local Health District, Liverpool, NSW 2170, Australia; Ingham Institute for Applied Medical Research, Liverpool, NSW 2170, Australia; School of Public Health and Community Medicine, The University of New South Wales, Kensington, NSW 2052, Australia. 10. International Laboratory for Air Quality and Health, Queensland University of Technology (QUT), GPO Box 2434, Brisbane, Queensland 4001, Australia. 11. Department of Geography, Hong Kong Baptist University, Hong Kong Special Administrative Region. 12. State Environmental Protection Key Laboratory of Environmental Pollution Health Risk Assessment, South China Institute of Environmental Sciences, Ministry of Environmental Protection, Guangzhou, China. 13. School of Public Health, Zunyi Medical University, Zunyi 563060, China. 14. Departments of Environmental Health Sciences and Epidemiology and Biostatics, University at Albany, State University of New York, Rensselaer, NY 12144, USA. Electronic address: slin@albany.edu. 15. Department of Epidemiology, Guangdong Cardiovascular Institute, Guangdong General Hospital, China. Electronic address: drxqliu@21cn.com. 16. Guangdong Provincial Engineering Technology Research Center of Environmental and Health Risk Assessment, Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China. Electronic address: donggh5@mail.sysu.edu.cn.
Abstract
BACKGROUND: Evidence of maternal exposure to ambient air pollution on congenital heart defects (CHD) has been mixed and are still relatively limited in developing countries. We aimed to investigate the association between maternal exposure to air pollution and CHD in China. METHOD: This longitudinal, population-based, case-control study consecutively recruited fetuses with CHD and healthy volunteers from 21 cities, Southern China, between January 2006 and December 2016. Residential address at delivery was linked to random forests models to estimate maternal exposure to particulate matter with an aerodynamic diameter of ≤ 1 µm (PM1), ≤2.5 µm, and ≤10 µm as well as nitrogen dioxides, in three trimesters. The CHD cases were evaluated by obstetrician, pediatrician, or cardiologist, and confirmed by cardia ultrasound. The CHD subtypes were coded using the International Classification Diseases. Adjusted logistic regression models were used to assess the associations between air pollutants and CHD and its subtypes. RESULTS: A total of 7055 isolated CHD and 6423 controls were included in the current analysis. Maternal air pollution exposures were consistently higher among cases than those among controls. Logistic regression analyses showed that maternal exposure to all air pollutants during the first trimester was associated with an increased odds of CHD (e.g., an interquartile range [13.3 µg/m3] increase in PM1 was associated with 1.09-fold ([95% confidence interval, 1.01-1.18]) greater odds of CHD). No significant associations were observed for maternal air pollution exposures during the second trimester and the third trimester. The pattern of the associations between air pollutants and different CHD subtypes was mixed. CONCLUSIONS: Maternal exposure to greater levels of air pollutants during the pregnancy, especially the first trimester, is associated with higher odds of CHD in offspring. Further longitudinal well-designed studies are warranted to confirm our findings.
BACKGROUND: Evidence of maternal exposure to ambient air pollution on congenital heart defects (CHD) has been mixed and are still relatively limited in developing countries. We aimed to investigate the association between maternal exposure to air pollution and CHD in China. METHOD: This longitudinal, population-based, case-control study consecutively recruited fetuses with CHD and healthy volunteers from 21 cities, Southern China, between January 2006 and December 2016. Residential address at delivery was linked to random forests models to estimate maternal exposure to particulate matter with an aerodynamic diameter of ≤ 1 µm (PM1), ≤2.5 µm, and ≤10 µm as well as nitrogen dioxides, in three trimesters. The CHD cases were evaluated by obstetrician, pediatrician, or cardiologist, and confirmed by cardia ultrasound. The CHD subtypes were coded using the International Classification Diseases. Adjusted logistic regression models were used to assess the associations between air pollutants and CHD and its subtypes. RESULTS: A total of 7055 isolated CHD and 6423 controls were included in the current analysis. Maternal air pollution exposures were consistently higher among cases than those among controls. Logistic regression analyses showed that maternal exposure to all air pollutants during the first trimester was associated with an increased odds of CHD (e.g., an interquartile range [13.3 µg/m3] increase in PM1 was associated with 1.09-fold ([95% confidence interval, 1.01-1.18]) greater odds of CHD). No significant associations were observed for maternal air pollution exposures during the second trimester and the third trimester. The pattern of the associations between air pollutants and different CHD subtypes was mixed. CONCLUSIONS: Maternal exposure to greater levels of air pollutants during the pregnancy, especially the first trimester, is associated with higher odds of CHD in offspring. Further longitudinal well-designed studies are warranted to confirm our findings.
Authors: Will Simmons; Shao Lin; Thomas J Luben; Scott C Sheridan; Peter H Langlois; Gary M Shaw; Jennita Reefhuis; Paul A Romitti; Marcia L Feldkamp; Wendy N Nembhard; Tania A Desrosiers; Marilyn L Browne; Jeanette A Stingone Journal: Sci Total Environ Date: 2021-12-03 Impact factor: 10.753