A time series analysis of ambient air pollution and low birth weight in Xuzhou, China

ABSTRACT

The objective of this study was to examine the relationship between weekly specific maternal air pollution exposures and low birth weight. We fitted a distributed lag nonlinear model (DLNM) to analyze the nonlinear exposure-response association and delayed effects of air pollutants on the risk for low birth weight. The model assumed that all live births have 40 gestational weeks.The 1st week lag was the 40th gestational week, and 40th lag week was the 1st gestational week.The study included 71,809 live births (from July 1, 2016, to June 30, 2019), of which 2,391 (3.33%) exhibited low birth weight. The results demonstrated that exposure of pregnant women to PM10 at lag 22-30 weeks was significantly associated with low birth weight risk, with the greatest impact at the lag 30 week. Exposure to SO2 at lag 29-37 weeks was significantly associated with low birth weight risk. The sensitive exposure window for NO2 began at lag 25-37 weeks of pregnancy. The lag 6-10 weeks constituted the susceptible exposure window for O3. Therefore we concluded that maternal exposures to PM10, SO2, NO2, and O3 were associated with increased risk for low birth weight.

KEYWORDS:

• Ambient air pollution
• low birth weight
• distributed lag nonlinear model
• time series
• cumulative effects

Acknowledgments

The authors acknowledge the key role of Xuzhou Maternal and Child Health Family Planning Service Center in recruiting study participants. The authors would like to express their gratitude to EditSprings (https://www.editsprings.com/) for the expert linguistic services provided.

Author Contributions

Conceptualization, S.L. and W.N.F.; Formal analysis, P.C. and L.J.D.; Funding acquisition, J.H.H.; Project administration, F.Y.; Resources, C.Z and P.L.; Writing—original draft, J.W.H.; Writing—review and editing, J.W.H.

Disclosure statement

The authors declare no conflict of interest.

Supplementary material

Supplemental data for this article can be accessed here.

Additional information

Funding

This work was supported by the National Natural Science Foundation of China (No.81573164 and No. 81872635).