Disparities in Healthcare Utilization

Superfund Site vs. Neighboring Comparison Site

Bibliographic Data

ID15465822
AuthorsC T Stephens (0000-0002-0254-7136, University of Alabama at Birmingham), Young-Il Kim (0000-0001-6806-4551, University of Alabama at Birmingham), Rekha Ramachandran (0009-0002-0184-0426, University of Alabama at Birmingham), Monica L Baskin (0000-0002-5544-0412, University of Alabama at Birmingham), Veena B Antony (0000-0002-2326-352X, University of Alabama at Birmingham), Veena Antony (University of Alabama at Birmingham), Sejong Bae (0000-0001-9982-3223, University of Alabama at Birmingham, corresponding author)
Year2022
Volume19
Issue15
Pages9271-9271
Publication date2022-07-28
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueInternational Journal of Environmental Research and Public Health (JOURNAL)
Journal identifiersISSN: 1661-7827 • E-ISSN: 1660-4601
PublisherMultidisciplinary Digital Publishing Institute (PUBLISHER • CH)
DOI10.3390/ijerph19159271
PMID35954629
OpenAlexW4288436731
LanguageEN
Citations received4
References cited14

Inequities in pollution-attributable health disparities are similar in most urban areas throughout the United States, and appear to encompass racial and socio-demographic differences, thereby suggesting increased health risks for those living in these areas. Individuals residing in close proximity to Superfund sites, predominantly people of color, are increasingly stricken with lung diseases. The prevalence of chronic lung diseases, such as chronic obstructive pulmonary disease (COPD), asthma in children, and lower respiratory tract infections (LRTI), is significantly higher in the affected area compared to the neighboring control area, irrespective of smoking, socio-economic status, or demographics. We conducted a retrospective analysis using data collected from patients who obtained healthcare from the University of Alabama at Birmingham (UAB) Health System. The data were procured from the Enterprise Data Warehouse (UAB Informatics for Integrating Biology and the Bedside (i2b2)). We evaluated healthcare utilization and classification of disease (defined by ICD-10 codes) of patients residing in zip codes: affected (35207, 35217) and neighboring comparison (35214). The results of the analysis may provide evidence that can be used for risk mitigation strategies or outreach education campaign(s) for those who live in the affected area

Asthma · Economic growth · Environmental health · Health care · Health equity · Outreach · Pathology · Population · Public health · Rural area · Socioeconomic status · Superfund · Air Quality and Health Impacts · Environmental Justice and Health Disparities · Health disparities and outcomes · Medicine · Ecology · Gerontology