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Air pollution-induced missed abortion risk for pregnancies

Nature Sustainability volume 2, pages 1011–1017 (2019)Cite this article

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Abstract

Fetus death risk reduction is included in the United Nations Sustainable Development Goals. However, little is known about how missed abortion in the first trimester (MAFT) is related to maternal air pollution exposure. We quantify the link between air pollution exposure and MAFT in Beijing, China, a region with severe MAFT and air quality problems. We analyse the records of 255,668 pregnant women from 2009 to 2017 and contrast them with maternal exposure to air pollutants (particulate matter PM2.5, SO2, O3 and CO). We adjust for confounding factors such as sociodemographic characteristics, spatial autocorrelation and ambient temperature. We find that, for all four pollutants, an increased risk of MAFT is associated with rises in pollutant concentrations and the adjusted odds ratios (ORs) of these associations increase with higher concentrations. For example, the adjusted OR of MAFT risk for a 10.0 μg m−3 increase in SO2 exposure is between 1.29 and 1.41 at concentrations of 7.1–19.5 μg m−3; it drops to 1.17 below this range and rises to 1.52 above it at higher SO2 concentrations. This means that the risk increase is not linear but becomes more severe the higher the pollutant concentration. The findings provide evidence linking fetus disease burden and maternal air pollution exposure.

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Fig. 1: The ORs and 95% CIs of MAFT associated with maternal exposure to each pollutant in Phase 4.
Fig. 2: The ORs and 95% CIs of the MAFT risks associated with maternal exposure to different average annual air pollutant concentrations.

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Data availability

The collected data are available from the corresponding authors on reasonable request.

Code availability

The source code is available from the corresponding authors on reasonable request. It is copyrighted by Beijing Normal University and Beijing Obstetrics and Gynecology Hospital and is to be used only for educational and research purposes. Any commercial use is prohibited.

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Acknowledgements

This work was carried out with the support of the National Key Research and Development Program of China (grant no. 2018YFC0213600), the National Natural Science Foundation of China (grant nos. 41775115 and 41371324) and the Beijing Natural Science Foundation (grant no. 7173258).

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Author notes

  1. These authors contributed equally: Liqiang Zhang, Weiwei Liu, Kun Hou.

Authors and Affiliations

  1. State Key Laboratory of Remote Sensing Science, Faculty of Geographical Science, Beijing Normal University, Beijing, China

    Liqiang Zhang, Kun Hou, Ziye Wang, Yuebin Wang, Yanxiao Jiang, Yibo Zheng, Suhong Liu & Panpan Zhu

  2. Beijing Obstetrics and Gynecology Hospital, Capital Medical University, Beijing, China

    Weiwei Liu & Yonglian Lan

  3. Laboratory for Climate and Ocean-Atmosphere Studies, Department of Atmospheric and Oceanic Sciences, School of Physics, Peking University, Beijing, China

    Jintai Lin, Ziwei Wang, Ruijing Ni & Mengyao Liu

  4. State Key Laboratory of Resources and Environment Information System, Institute of Geographical Science and Natural Resources, Chinese Academy of Sciences, Beijing, China

    Chenghu Zhou

  5. School of Surveying and Geo-informatics, Tongji University, Shanghai, China

    Xiaohua Tong

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Contributions

L.Z. and W.L. jointly designed the study, collected data, performed the analysis and wrote the manuscript. K.H. contributed to the model of the paper. J.L. contributed to the research framework, provided air pollution and meteorological data, contributed to results analysis and edited the paper. C.Z. and X.T. improved the research framework and edited the paper. Z.Y.W., Y.B.W. and Y.L. organized the neonatal and maternal datasets. Z.W.W., R.N. and M.L. generated the air pollution and meteorological datasets. Y.J., Y.Z., S.L. and P.Z. developed the maps and edited figures.

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Correspondence to Liqiang Zhang, Jintai Lin or Chenghu Zhou.

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Zhang, L., Liu, W., Hou, K. et al. Air pollution-induced missed abortion risk for pregnancies. Nat Sustain 2, 1011–1017 (2019). https://doi.org/10.1038/s41893-019-0387-y

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