Alzheimer’s disease (AD) is a neurodegenerative disease resulting in loss of cognitive function and is not considered part of the typical aging process. Recently, research is being conducted to study environmental effects on AD because the exact molecular mechanisms behind AD are not known. The associations between various toxins and AD have been mixed and unclear. In order to better understand the role of the environment and toxic substances on AD, we conducted a literature review and geospatial analysis of environmental, specifically wastewater, contaminants that have biological plausibility for increasing risk of development or exacerbation of AD. This literature review assisted us in selecting 10 wastewater toxic substances that displayed a mixed or one-sided relationship with the symptoms or prevalence of Alzheimer’s for our data analysis. We utilized data of toxic substances in wastewater treatment plants and compared them to the crude rate of AD in the different Census regions of the United States to test for possible linear relationships. Using data from the Targeted National Sewage Sludge Survey (TNSSS) and the Centers for Disease Control and Prevention (CDC), we developed an application using R Shiny to allow users to interactively visualize both datasets as choropleths of the United States and understand the importance of this area of research. Pearson’s correlation coefficient was calculated resulting in arsenic and cadmium displaying positive linear correlations with AD. Other analytes from this statistical analysis demonstrated mixed correlations with AD. This application and data analysis serve as a model in the methodology for further geospatial analysis on AD. Further data analysis and visualization at a lower level in terms of scope is necessary for more accurate and reliable evidence of a causal relationship between the wastewater substance analytes and AD.
GitHub Repository: https://github.com/komal-agrawal/AD_GIS.git