Identifying windows of susceptibility for maternal exposure to ambient air pollution and preterm birth
Maternal exposure to ambient air pollution has been associated with preterm birth (PTB), however, entire pregnancy or trimester-specific associations were generally reported, which may not sufficiently identify windows of susceptibility. Using birth registry data from Guangzhou, a megacity of southe...
| Main Authors: | , , , , , , , , , , , , |
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| Format: | Article |
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Elsevier
2018-12-01
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| Series: | Environment International |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S0160412018310778 |
| _version_ | 1818297794183561216 |
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| author | Qiong Wang Tarik Benmarhnia Huanhuan Zhang Luke D. Knibbs Paige Sheridan Changchang Li Junzhe Bao Meng Ren Suhan Wang Yiling He Yawei Zhang Qingguo Zhao Cunrui Huang |
| author_facet | Qiong Wang Tarik Benmarhnia Huanhuan Zhang Luke D. Knibbs Paige Sheridan Changchang Li Junzhe Bao Meng Ren Suhan Wang Yiling He Yawei Zhang Qingguo Zhao Cunrui Huang |
| author_sort | Qiong Wang |
| collection | DOAJ |
| description | Maternal exposure to ambient air pollution has been associated with preterm birth (PTB), however, entire pregnancy or trimester-specific associations were generally reported, which may not sufficiently identify windows of susceptibility. Using birth registry data from Guangzhou, a megacity of southern China (population ~14.5 million), including 469,975 singleton live births between January 2015 and July 2017, we assessed the association between weekly air pollution exposure and PTB in a retrospective cohort study. Daily average concentrations of PM2.5, PM10, NO2, SO2, and O3 from 11 monitoring stations were used to estimate district-specific exposures for each participant based on their district residency during pregnancy. Distributed lag models (DLMs) incorporating Cox proportional hazard models were applied to estimate the association between weekly maternal exposure to air pollutant and PTB risk (as a time-to-event outcome), after controlling for temperature, seasonality, and individual-level covariates. We also considered moderate PTB (32–36 gestational weeks) and very PTB (28–31 gestational weeks) as outcomes of interest. Hazard ratios (HRs) and 95% confidential intervals (95% CIs) were calculated for an interquartile range (IQR) increase in air pollutants during the study period. An IQR increase in PM2.5 exposure during the 20th to 28th gestational weeks (27.0 μg/m3) was significantly associated with PTB risk, with the strongest effect in the 25th week (HR = 1.034, 95% CI:1.010–1.059). The significant exposure windows were the 19th–28th weeks for PM10, the 18th–31st weeks for NO2, and the 23rd–31st weeks for O3, respectively. The strongest associations were observed in the 25th week for PM10 (IQR = 37.0 μg/m3; HR = 1.048, 95% CI:1.034–1.062), the 26th week for NO2 (IQR = 29.0 μg/m3; HR = 1.060, 95% CI:1.028–1.094), and in the 28th week for O3 (IQR = 90.0 μg/m3; HR = 1.063, 95% CI:1.046–1.081). Similar patterns were observed for moderate PTB (32–36 gestational weeks) and very PTB (28–31 gestational weeks) for PM2.5, PM10, NO2 exposure, but the effects were greater for very PTB. We did not observe any association between pregnancy SO2 exposure and the risk of PTB. Our results suggest that middle to late pregnancy is the most susceptible air pollution exposure window for air pollution and PTB among women in Guangzhou, China. Keywords: Air pollution, Preterm birth, Distributed lag model, Susceptible exposure window |
| first_indexed | 2024-12-13T04:25:05Z |
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| institution | Directory Open Access Journal |
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| publishDate | 2018-12-01 |
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| series | Environment International |
| spelling | doaj.art-c8f3aa421ff64d49822ee56d3779e90c2022-12-21T23:59:42ZengElsevierEnvironment International0160-41202018-12-01121317324Identifying windows of susceptibility for maternal exposure to ambient air pollution and preterm birthQiong Wang0Tarik Benmarhnia1Huanhuan Zhang2Luke D. Knibbs3Paige Sheridan4Changchang Li5Junzhe Bao6Meng Ren7Suhan Wang8Yiling He9Yawei Zhang10Qingguo Zhao11Cunrui Huang12School of Public Health, Sun Yat-sen University, Guangzhou, China; Guangzhou Key Laboratory of Environmental Pollution and Health Risk Assessment, School of Public Health, Sun Yat-sen University, Guangzhou, ChinaDepartment of Family Medicine and Public Health, University of California, San Diego, La Jolla, CA, USA; Scripps Institution of Oceanography, University of California, San Diego, CA, USASchool of Public Health, Sun Yat-sen University, Guangzhou, China; Guangzhou Key Laboratory of Environmental Pollution and Health Risk Assessment, School of Public Health, Sun Yat-sen University, Guangzhou, ChinaSchool of Public Health, The University of Queensland, Herston, AustraliaDepartment of Family Medicine and Public Health, University of California, San Diego, La Jolla, CA, USA; Graduate School of Public Health, San Diego State University, San Diego, CA, USASchool of Public Health, Sun Yat-sen University, Guangzhou, ChinaSchool of Public Health, Sun Yat-sen University, Guangzhou, ChinaSchool of Public Health, Sun Yat-sen University, Guangzhou, ChinaSchool of Public Health, Sun Yat-sen University, Guangzhou, ChinaSchool of Public Health, Sun Yat-sen University, Guangzhou, ChinaSchool of Public Health, Yale University, New Haven, CT, USAEpidemiological Research Office of Key Laboratory of Male Reproduction and Genetics (National Health and Family Planning Commission), Family Planning Research Institute of Guangdong Province, Guangzhou, China; Epidemiological Research Office of Key Laboratory of Male Reproduction and Genetics (National Health and Family Planning Commission), Family Planning Special Hospital of Guangdong Province, Guangzhou, China; Correspondence to: Q. Zhao, Family Planning Special Hospital of Guangdong Province, 17 Meidong Road, Guangzhou 510600, China.School of Public Health, Sun Yat-sen University, Guangzhou, China; Guangzhou Key Laboratory of Environmental Pollution and Health Risk Assessment, School of Public Health, Sun Yat-sen University, Guangzhou, China; Correspondence to: C. Huang, School of Public Health, Sun Yat-sen University, 74 Zhongshan 2nd Road, Guangzhou 510080, China.Maternal exposure to ambient air pollution has been associated with preterm birth (PTB), however, entire pregnancy or trimester-specific associations were generally reported, which may not sufficiently identify windows of susceptibility. Using birth registry data from Guangzhou, a megacity of southern China (population ~14.5 million), including 469,975 singleton live births between January 2015 and July 2017, we assessed the association between weekly air pollution exposure and PTB in a retrospective cohort study. Daily average concentrations of PM2.5, PM10, NO2, SO2, and O3 from 11 monitoring stations were used to estimate district-specific exposures for each participant based on their district residency during pregnancy. Distributed lag models (DLMs) incorporating Cox proportional hazard models were applied to estimate the association between weekly maternal exposure to air pollutant and PTB risk (as a time-to-event outcome), after controlling for temperature, seasonality, and individual-level covariates. We also considered moderate PTB (32–36 gestational weeks) and very PTB (28–31 gestational weeks) as outcomes of interest. Hazard ratios (HRs) and 95% confidential intervals (95% CIs) were calculated for an interquartile range (IQR) increase in air pollutants during the study period. An IQR increase in PM2.5 exposure during the 20th to 28th gestational weeks (27.0 μg/m3) was significantly associated with PTB risk, with the strongest effect in the 25th week (HR = 1.034, 95% CI:1.010–1.059). The significant exposure windows were the 19th–28th weeks for PM10, the 18th–31st weeks for NO2, and the 23rd–31st weeks for O3, respectively. The strongest associations were observed in the 25th week for PM10 (IQR = 37.0 μg/m3; HR = 1.048, 95% CI:1.034–1.062), the 26th week for NO2 (IQR = 29.0 μg/m3; HR = 1.060, 95% CI:1.028–1.094), and in the 28th week for O3 (IQR = 90.0 μg/m3; HR = 1.063, 95% CI:1.046–1.081). Similar patterns were observed for moderate PTB (32–36 gestational weeks) and very PTB (28–31 gestational weeks) for PM2.5, PM10, NO2 exposure, but the effects were greater for very PTB. We did not observe any association between pregnancy SO2 exposure and the risk of PTB. Our results suggest that middle to late pregnancy is the most susceptible air pollution exposure window for air pollution and PTB among women in Guangzhou, China. Keywords: Air pollution, Preterm birth, Distributed lag model, Susceptible exposure windowhttp://www.sciencedirect.com/science/article/pii/S0160412018310778 |
| spellingShingle | Qiong Wang Tarik Benmarhnia Huanhuan Zhang Luke D. Knibbs Paige Sheridan Changchang Li Junzhe Bao Meng Ren Suhan Wang Yiling He Yawei Zhang Qingguo Zhao Cunrui Huang Identifying windows of susceptibility for maternal exposure to ambient air pollution and preterm birth Environment International |
| title | Identifying windows of susceptibility for maternal exposure to ambient air pollution and preterm birth |
| title_full | Identifying windows of susceptibility for maternal exposure to ambient air pollution and preterm birth |
| title_fullStr | Identifying windows of susceptibility for maternal exposure to ambient air pollution and preterm birth |
| title_full_unstemmed | Identifying windows of susceptibility for maternal exposure to ambient air pollution and preterm birth |
| title_short | Identifying windows of susceptibility for maternal exposure to ambient air pollution and preterm birth |
| title_sort | identifying windows of susceptibility for maternal exposure to ambient air pollution and preterm birth |
| url | http://www.sciencedirect.com/science/article/pii/S0160412018310778 |
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