Predicting gestational personal exposure to PM from satellite-driven ambient concentrations in Shanghai.

Background: It has been widely reported that gestational exposure to fine particulate matters (PM) is associated with a series of adverse birth outcomes. However, the discrepancy between ambient PM concentrations and personal PM exposure would significantly affect the estimation of exposure-response relationship.

Objective: Our study aimed to predict gestational personal exposure to PM from the satellite-driven ambient concentrations and analyze the influence of other potential determinants.

Method: We collected 762 72-h personal exposure samples from a panel of 329 pregnant women in Shanghai, China as well as their time-activity patterns from Feb 2017 to Jun 2018. We established an ambient PM model based on MAIAC AOD at 1 km resolution, then used its output as a major predictor to develop a personal exposure model.

Results: Our ambient PM model yielded a cross-validation R of 0.96. Personal PM exposure levels were almost identical to the corresponding ambient concentrations. After adjusting for time-activity patterns and meteorological factors, our personal exposure has a CV R of 0.76.

Conclusion: We established a prediction model for gestational personal exposure to PM from satellite-based ambient concentrations and provided a methodological reference for further epidemiological studies.