Innovative data science and geospatial methods to identify environmental drivers of disparities in hypertensive disorders of pregnancy and blood pressure over time

Hypertensive disorders of pregnancy (HDP) are one of the most common pregnancy complications, and a leading cause of perinatal mortality and morbidity. People with HDP are at increased risk of life-threatening pregnancy complications and postnatal cardiovascular disease, stroke, and type 2 diabetes. In the US, prevalence of HDP has increased over time and exhibits stark health disparities; neither trend is explained by known risk factors. Environmental exposures, particularly those that disrupt endothelial and placental function, may contribute to HDP risk. A developing body of work examines whether ubiquitous, modifiable environmental exposures such as air pollution, temperature extremes, and lack of greenness – all biologically plausible and potentially modifiable – relate to HDP risk. However, studies are limited to HDP only, not repeated measures of blood pressure (BP trajectories), use pre-specified time windows of exposure, and have reported mixed results. For a common condition with rising incidence and profound short- and long-term health consequences, the links between environmental exposures, HDP, and BP are understudied. Utilizing electronic health records (EHR) from health systems in Durham, NC; Chicago, IL; and New York, NY, we link EHR of >320,000 individuals across pre-pregnancy, prenatal, and post-partum periods (2010-2019) with finely-resolved environmental exposure data. Our overarching objective is to understand if and how air pollutants, temperature extremes, and lack of greenness are associated with HDP in pregnancy and BP trajectories. We pursue three aims: (1) Model spatial and temporal trends in neighborhood-level HDP rates and health disparities in HDP to identify high risk neighborhoods; (2) Evaluate flexible time windows of association between multiple environmental exposures, HDP risk, and health disparities in HDP risk; and (3) Investigate relationships between multiple environmental exposures, BP trajectories (including post-pregnancy) and health disparities in BP trajectories. Our innovative, Bayesian spatiotemporal modeling approach and individual-level, longitudinal data from three regions of the US allow us to assess consistency and generalizability of findings across different samples of women with varying exposure mixtures. The proposed research will transform our understanding of which environmental exposures are most strongly associated with HDP and BP trajectories, and the extent to which the environment affects health disparities. As the country strives to improve maternal health, our findings will inform the type, timing, and tailoring of interventions to improve health.