Lindsay J. Underhill, Ph.D. (Year 1)
ABSTRACT
Non-communicable diseases (NCDs) are the primary cause of death and disability globally, accounting for 71% of the 41 million deaths annually. Among NCDs, hypertension (HTN) is a significant challenge in the United States, disproportionately affecting older, low-income, and minority communities. In St. Louis, HTN prevalence increased from 23% in 2007 to 36% in 2016, with a higher incidence in Black populations (44%) compared to white populations (31%).
In response, the US Surgeon General called for research on the impact of social determinants of health (SDOH)—the social and environmental conditions that affect health and well-being—on HTN development and management. Frameworks such as Healthy People 2023 emphasize healthcare accessibility and neighborhood and built environment factors as key health domains. However, these factors are often studied in isolation, highlighting the need for tools to comprehensively assess the multiple SDOH influencing HTN. To address this need, this project aims to establish a geospatial model to assess social and environmental risk factors associated with NCDs, focusing on HTN in Greater St. Louis. The model will merge objective and perceived data from two domains: healthcare accessibility and neighborhood and built environment. This will elucidate the complex associations between HTN and SDOH factors, serving as a scalable model for other health issues. The project will be guided by two concurrent aims: Aim 1 is to utilize a novel geospatial SDOH model to identify geographic disparities in HTN, healthcare accessibility, and neighborhood and built
environment factors in St. Louis. This model will integrate health and demographic data from approximately 1.5 million EMR patients from the BJC Network, GIS-modeled health accessibility (e.g., travel time estimates), outdoor air pollution, noise, and light exposure data for all EMR participants, and perceived health accessibility and environmental exposure data from a subset of 300 participants. Aim 2 is to utilize the geospatial SDOH model to evaluate the association between HTN and objective and perceived healthcare accessibility and neighborhood and built environment SDOH factors. This will serve as a “proof of concept” evaluation using advanced statistical models to assess the relationship between HTN and both objective measures (e.g., proximity to diagnosis locations, pharmacy locations, and geographical neighborhood characteristics) and perceived measures of healthcare access.
Additionally, to explore the interaction between environmental exposures and healthcare accessibility. We anticipate that objective and perceived measures of SDOH will
vary geographically, representing potential disparities in health services accessibility. We also expect that participant-reported accessibility barriers (e.g., travel costs, time, availability) will vary by objective measures (e.g., distance, travel time). In the Exploratory Aim, we expect that objective and perceived measures of accessibility will be associated with HTN. Overall, results will provide novel information regarding the local geographic drivers of HTN health services accessibility across diverse populations in St. Louis, MO. This information will support the future development of interventions aiming to reduce disparities related to HTN accessibility and outcomes.
Lay Summary
This project aims to establish a geospatial model to assess social and environmental risk factors associated with hypertension (HTN) in Greater St. Louis, merging objective and perceived data on healthcare accessibility and neighborhood factors. Guided by two aims, the study will identify geographic disparities in HTN and evaluate the association between HTN and both objective and perceived SDOH factors, including the interaction between environmental exposures and healthcare accessibility. The findings will inform the development of targeted interventions to reduce disparities in HTN accessibility and outcomes across diverse populations in St. Louis.
