Hyper-localized air pollution measures and preterm birth in the Bay Area

Principal Investigators:
Maria Glymour, ScD, MS | Epidemiology & Biostatistics | UCSF School of Medicine

Background

One in ten babies in the U.S. are born preterm and 1 in 25 mothers experiences preeclampsia during pregnancy. Air pollution may play a role. In conventional studies, researchers measure air pollution using stationary monitors fixed at a single site. This provides estimates of air pollution levels across large areas, like entire communities. However, while we cannot see it, we know that air pollution levels can change block-to-block within neighborhoods. Here, we use Google Street View cars with mobile air monitors that repeatedly measured traffic-related air pollution every 30-meters to estimate hyperlocal levels of pollution.

Objective

To understand the relationship between traffic-related air pollution and preterm birth and preeclampsia, as well as racial/ethnic disparities, at hyperlocal levels in the Bay Area.

Method

We used birth registry data and electronic health record data from Sutter Health to link baby and mothers’ health outcomes to Google Street View measures of traffic-related air pollution. We used statistical analyses to look at links between air pollution and preterm birth and preeclampsia.

Results

Increased levels of black carbon was associated with increased risk of preterm birth for Black and Latina mothers. Both black carbon and nitrogen dioxide were related to increased risk of preeclampsia and the relationship was the strongest for Black mothers.

Conclusions

Reducing levels of traffic-related air pollution should reduce risks of preterm birth and preeclampsia, especially for Black mothers who currently have the highest rates of both adverse outcomes. We may be able to reduce health disparities by lowering pollution levels in the Bay Area.