Understanding Geo-demographics of Parkinson's Disease Among African Americans
Khadar Haroun1, Demetrius Geiger1, Kevin Lane2, Chantale Branson1
1Morehouse School of Medicine, 2Boston University School of Public Health
Determine the demographics within a safety-net hospital to identify the geographic distribution of PD in the metropolitan Atlanta area. 
Understanding racial differences and community characteristics of patients with Parkinson’s disease (PD) by analyzing census data within a racially diverse area. 
People with a diagnosis based on ICD10 codes for Parkinson’s disease between 2014 to 2019 were included in this study. De-identified information was analyzed through redcap to review demographics, including age, race, address, onset, and diagnosis of PD generating a database. The selected data extracted from electronic health records were linked with geospatial data to identify any factors that may increase the risk of PD. The PD database was expanded by geocoding and linking census tract data. Researchers at Boston University’s (BU) Biostatistics and Epidemiology Data Analytics Center (BEDAC) conducted geocoding using geographic information system software and addresses were assigned to the Census tract. We conducted spatial analyses of the PD data to identify tract level clusters using hotspot and Anselin Moran’s I test for spatial autocorrelation.

64.6% of the patients were over the age of 70 years old, 57.6% were African American and 30.1% were non-Hispanic White or Caucasian with a diagnosis of PD. The percentage of PD among Black/African Americans below the poverty level was 37.6% based on their residential census tract.


We found a significant association among low-income regions within the metropolitan areas and PD. As the percentage of AA increased within the census tract there was an increased odds of PD. We also identified significant spatial clusters within the metropolitan compared to non-metro regions for PD. This may suggest an environmental cause associated with the diagnosis of PD within the southeastern area, but additional analyses of these factors, such as environmental toxins or lack of accessibility to affordable food.