Associations between maternal weekly air pollutant exposures and low birth weight: a distributed lag non-linear model

When discussing the association between birth weight and air pollution, previous studies mainly focus on the maternal trimester-specific exposures during pregnancy, whereas the possible associations between birth weight and weekly-specific exposures have been largely neglected. We conducted a nested 1: 4 matched case-control study in Jinan, China to examine the weekly-specific associations during pregnancy between maternal fine particulate matter (aerodynamic diameter < 2.5 mu m, PM2.5), nitrogen dioxide (NO2), and sulfur dioxide (SO2) exposure and birth weight, which is under a representative scenario of very high pollution levels. Ambient air monitoring data from thirteen monitoring stations and daily mean temperature data for Jinan during 2013-2016 were continuously collected. Birth data were obtained from the largest maternity and child care hospital of this city during 2014-2016. Individual exposures to PM2.5, NO2, and SO2 during pregnancy were estimated using an inverse distance weighting method. Birth weight for gender-, gestational age-, and parity-specific standard score (BWGAP z-score) was calculated as the outcome of interest. Distributed lag non-linear models (DLNMs) were applied to estimate weekly-specific relationship between maternal air pollutant exposures and birth weight. For an increase of per inter-quartile range in maternal PM2.5 exposure concentration during pregnancy, the BWGAP z-score decreased significantly during the 27th-33th gestational weeks with the strongest association in the 30th gestational weeks (standard deviation units decrease in BWGAP z-score: -0.049, 95% CI: -0.080 -0.017, in three-pollutant model). No significant association between maternal weekly NO2 or SO2 BWGAP z-score was observed. In conclusion, this study provides evidence that maternal PM2.5 exposure during the 27th-33th gestational weeks may reduce the birth weight in the context of very high pollution level of PM2.5.