Background : Although the adverse effects of air pollution on health have aroused widespread concern in academia, there is little evidence about the impact of PM2.5 on perinatal mortality rates.
Methods: Using the spatial analysis function of ArcGIS, we get the haze pollution data from the satellite remote sensing data. We adopt fixed effects model, spatial Durbin model (SDM) and the instrument variable method to investigate the causality between PM2.5 and perinatal mortality rates.
Results: We find that PM2.5 has a significantly positive effect on perinatal mortality rates. A 1% increase of log-transformed average concentrations and maximum concentrations of PM2.5 result in 1.76‰ and 2.31‰ increase of perinatal mortality rates, respectively. In spatial econometrics analysis, we find PM2.5 has significant spatial autocorrelation characteristics. A 1% increase of concentrations of log-transformed average and maximum PM2.5 lead to a 2.49‰ and 2.19‰ increase of perinatal mortality rates, respectively. Using instrument variable method to deal with the endogeneity, the result is similar. The potential mechanism through which air pollution has an impact on perinatal mortality rates is infant weight.
Conclusions: PM2.5 pollution has a significant and positive effect on perinatal mortality. The results show that environmental pollution control should be strengthened and the exposure of pregnant women in polluted air should be reduced.