PM2100: Exploring the Impact of Gentrification on Pediatric Asthma Outcomes

Background: Asthma is one of the most common childhood diagnoses in the United States. While there is a strong genetic component to asthma, there is growing evidence that there are significant social and environmental determinants of health (SEDoH) that are associated with increased risk of developing asthma. Of these SEDoH, gentrification, displacement, and shifting community support structures are important factors to consider. Patients of color and of lower socioeconomic status are disproportionately affected by gentrification and may have worse health outcomes as a result. While there is some growing sociologic research on the distribution and effects of gentrification, there is no significant literature that highlights the health outcomes of displaced individuals and communities.

Methods: This will be a retrospective chart review. We will look at three groups of patients who had ED visits or hospital admissions for asthma or asthma-related outcomes for the following date ranges: January 1, 2010 to December 31, 2010; January 1, 2015 to December 31, 2015; and January 1, 2020 to December 31, 2020. We will identify patients in these three years who have had an ED visit or hospital admission with ICD9-/ICD-10 diagnosis codes for any asthma-related diagnoses (including “asthma”, “asthma exacerbation”, and “status asthmaticus”). From the charts, we will extract patient demographics, specifically home address at time of admission, age, gender, race/ethnicity, and insurance status. Using the patient address, the extracted data will be enriched with publicly available social determinants of health data. Patient addresses will be used to identify which census tracts patients originate from. The aggregate American Communities Survey (ACS) variables for each census tract will be pulled from the ACS website and compared between 2010, 2015, and 2020. Patient information will be de-identified and encrypted to maintain patient confidentiality.

Results: Once all the data is collected, statistical analysis will be run to identify correlations between patient demographics, clinical outcomes, and neighborhood characteristics as they pertain to gentrification. T-test and ANOVA or Mann-Whitney U test and Kruskall-Wallis H test will be used to identify associations. We will compare the results for 2010 vs. 2015 vs. 2020.

Conclusion: Given the rapidly changing world and neighborhood demographics, it is important to understand that gentrification can play a significant role in the development of asthma and its associated outcomes. This may help both patients and providers in better understanding asthma, being socially conscious of SEDoH of asthma, and tailoring/individualizing management of asthma in patients. This work may also serve as important context when considering health and urban policy that may exacerbate gentrification and displacement in particularly vulnerable neighborhoods.