Modeling epilepsy disparities among ethnic groups in Philadelphia, PA

• Type of Material: Article
• Authors: David Wheeler, Emory University; Lance Waller, Emory University; John O. Elliott, Ohio State University
• Language: English
• Date: 2008-09-10
• Publisher: Wiley: 12 months
• Publication Version: Author Accepted Manuscript (After Peer Review)
• Copyright Statement: Copyright © 2008 John Wiley & Sons, Ltd.
• Final Published Version (URL): http://dx.doi.org/10.1002/sim.3261
• Title of Journal or Parent Work: Statistics in Medicine
• ISSN: 0277-6715
• Volume: 27
• Issue: 20
• Start Page: 4069
• End Page: 4085
• Keywords: Medicine, Research & Experimental; spatial epidemiology; health disparities; Physical Sciences; POPULATION; HEALTH; PREVALENCE; Science & Technology; Medical Informatics; Public, Environmental & Occupational Health; Statistics & Probability; Research & Experimental Medicine; Life Sciences & Biomedicine; hierarchical Bayesian regression; SEIZURES; MCMC; Mathematical & Computational Biology; spatial statistics; Mathematics
• Research Categories: Biology, Biostatistics; Biology, Neuroscience

Abstract

The Centers for Disease Control and Prevention defined epilepsy as an emerging public health issue in a recent report and emphasized the importance of epilepsy studies in minorities and people of low socioeconomic status. Previous research has suggested that the incidence rate for epilepsy is positively associated with various measures of social and economic disadvantage. In response, we utilize hierarchical Bayesian models to analyze health disparities in epilepsy and seizure risks among multiple ethnicities in the city of Philadelphia, Pennsylvania. The goals of the analysis are to highlight any overall significant disparities in epilepsy risks between the populations of Caucasians, African Americans, and Hispanics in the study area during the years 2002-2004 and to visualize the spatial pattern of epilepsy risks by ethnicity to indicate where certain ethnic populations were most adversely affected by epilepsy within the study area. Results of the Bayesian model indicate that Hispanics have the highest epilepsy risk overall, followed by African Americans, and then Caucasians. There are significant increases in relative risk for both African Americans and Hispanics when compared with Caucasians, as indicated by the posterior mean estimates of 2.09 with a 95 per cent credible interval of (1.67, 2.62) for African Americans and 2.97 with a 95 per cent credible interval of (2.37, 3.71) for Hispanics. Results also demonstrate that using a Bayesian analysis in combination with geographic information system (GIS) technology can reveal spatial patterns in patient data and highlight areas of disparity in epilepsy risk among subgroups of the population.