NYMC Student Theses and Dissertations

Date of Award

7-28-2023

Document Type

Doctoral Dissertation - Restricted (NYMC/Touro only) Access

Degree Name

Doctor of Public Health

Department

Public Health

First Advisor

Dr. Kenneth Knapp

Second Advisor

Dr. Elizabeth Drugge

Third Advisor

Dr. Michael Shakarjian

Abstract

Background: Many factors influence health outcomes, including environmental factors, demographics, socioeconomic status, and psychosocial stressors. One such health outcome is asthma. Low-income populations tend to demonstrate a greater negative health response to environmental exposures due to social vulnerabilities and are more frequently exposed to multiple environmental hazards and social stressors. They also find health insurance to be unaffordable and consider it secondary to meet more basic needs such as food and housing. California environmental quality has improved greatly over the last few decades. However, the pollution reduction and resulting health and environmental benefits are not uniformly distributed. Lack of insurance and being poor heighten the risk of unmet health care needs, which can lead to more emergency department visits; those more at risk for asthma tend to have insufficient access to care. Methods: This study used two datasets, the CalEnviroScreen mapping tool and the Census Bureau’s American Community Survey. These datasets were merged on the census tract identifier and a selection of key variables were chosen based on the literature to conduct pairwise correlations and a multiple linear regression. Results: The final linear regression model identified statistical significance among all variables and outcome variable asthma ED visits. Only the uninsured status variable was found to be not statistically significant at p < 0.05. However, the direction of percent change for some air pollution variables did not follow our expected hypothesis outcome. Conclusion: Though we found only weak associations between air pollution, insurance status and asthma ED visits, we did find that racial, socioeconomic, and sensitive population factors play a significant role.

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