Abstract TAC136: Sociodemographic Influences on Hypertension Prevalence Across New York Counties: A Multivariate Regression Analysis

Background: Hypertension (HTN) is a major public health concern, with significant variation in prevalence across New York counties. Understanding how factors like education, poverty, and language barriers relate to HTN prevalence is crucial for targeted public health interventions. Objective: This study examines how socioeconomic factors—specifically education, poverty, and the proportion of non-English speakers—contribute to hypertension prevalence rates across 62 New York counties. The aim is to assess how these variables influence disparities in hypertension control and inform region-specific public health strategies. Methods: County-level data from publicly available sources for 2023 were analyzed, including data from the New York State Department of Health (NYSDOH) and the National Institute on Minority Health and Health Disparities (NIMHD) HDPulse Data Portal. The dataset contained hypertension prevalence rates, educational attainment, poverty levels, and the proportion of non-English-speaking populations. Descriptive statistics were used to summarize the data, followed by multivariate linear regression to explore the relationship between hypertension prevalence and the selected sociodemographic predictors. Results: The average county-level hypertension rate in New York State in 2023 was 33.2% (SD = 4.3%). Orleans County had the highest rate at 45.9%, while Tompkins County had the lowest at 20.3%. The mean educational attainment was 31.2%, ranging from 64% in New York County to 17.5% in Orleans County. Poverty levels ranged from 3.4% in Hamilton County to 22.1% in Bronx County. Multivariate regression analysis showed that educational attainment, poverty levels, and the proportion of non-English speakers explained 56.2% of the variation in hypertension rates. Higher educational attainment was significantly associated with lower hypertension rates (β = -0.3129, p < 0.001). In contrast, poverty levels (p = 0.582) and non-English-speaking populations (p = 0.361) did not significantly predict hypertension prevalence. Conclusion: Higher educational attainment was identified as the most significant predictor of hypertension prevalence across New York State. This finding suggests that increased education may be linked to improved health literacy, enabling better management of chronic conditions like hypertension. Public health strategies targeting educational disparities could play a key role in reducing hypertension prevalence and improving overall health outcomes.