Investigating Parkinson's disease in the United States: An exploration of environmental and socio-economic variables and distance to treatment centers

Authors: Alexandria Reimold*, University of North Carolina Wilmington, Department of Earth and Ocean Sciences, Joanne Halls, University of North Carolina Wilmington, Department of Earth and Ocean Sciences, Barbara Lutz, University of North Carolina Wilmington, School of Nursing, Steele Olsen, University of North Carolina Wilmington, Department of Earth and Ocean Sciences
Topics: Medical and Health Geography
Keywords: Parkinson’s disease, GIS, deep brain stimulation, socioeconomic status
Session Type: Poster
Day: 4/4/2019
Start / End Time: 3:05 PM / 4:45 PM
Room: Lincoln 2, Marriott, Exhibition Level
Presentation File: No File Uploaded


Parkinson’s disease (PD) is a neurodegenerative disease that causes difficulty with motor function and eventually death. Although research has indicated a relationship between PD and socio-economic and environmental characteristics, there is no known cause. Deep brain stimulation (DBS) is an effective procedure for treating PD by improving motor functioning and quality of life. Therefore, the purpose of this project was to investigate the relationships between the rate of PD with environmental and socio-economic characteristics and to assess accessibility to DBS treatment centers. PD death rate data (from 1999 to 2014) were obtained from the Center for Disease Control, environmental and agricultural data were obtained from the US Geological Survey, and socio-economic characteristics were obtained from the US Census Bureau. DBS treatment center addresses were obtained from Medtronic’s Physician Finder Portal then geocoded. Underserved population data were gathered from the Health Resources & Services Administration Data Warehouse. All data were summarized to counties for the coterminous United States then spatial statistics and geospatial models were created. Results indicate: 1) The upper Midwest has the largest geographic extent and significant cluster of PD, 2) there is significant clustering in all independent variables at local, regional, and national scales, and 3) the percent white and the percent 65 and older populations both directly relate to the PD death rate. Spatial models were derived to predict the rate of PD and regional differences were identified. Distance metrics identified critically underserved areas for DBS treatment at greater spatial resolution than the national underserved area database.

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