Trends and Disparities in Parkinson’s Disease Mortality in the United States with Predictions Using Machine Learning
Background: Parkinson’s disease (PD) is a progressive neurodegenerative condition characterized by the degradation of dopaminergic pathways in the brain. As the population in the United States continues to age, it is essential to understand the trends in mortality related to PD. This analysis of PD’...
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MDPI AG
2025-01-01
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| author | Henry Weresh Kallin Hermann Ali Al-Salahat Amna Noor Taylor Billion Yu-Ting Chen Abubakar Tauseef Ali Bin Abdul Jabbar |
| author_facet | Henry Weresh Kallin Hermann Ali Al-Salahat Amna Noor Taylor Billion Yu-Ting Chen Abubakar Tauseef Ali Bin Abdul Jabbar |
| author_sort | Henry Weresh |
| collection | DOAJ |
| description | Background: Parkinson’s disease (PD) is a progressive neurodegenerative condition characterized by the degradation of dopaminergic pathways in the brain. As the population in the United States continues to age, it is essential to understand the trends in mortality related to PD. This analysis of PD’s mortality characterizes temporal shifts, examines demographic and regional differences, and provides machine-learning predictions. Methods: PD-related deaths in the United States were gathered from CDC WONDER. Age-adjusted mortality rates (AAMR) were collected, and trends were analyzed based on gender, race, region, age, and place of death. Annual percent change and average annual percent change were calculated using Joinpoint Regression program. Forecasts were obtained using the optimal Autoregressive Integrated Moving Average (ARIMA) model. Results: Overall mortality rate due to Parkinson’s increased from 1999 to 2022. Male gender, White race, Southern region, and older ages were associated with higher mortality compared to other groups. Deaths at home decreased and hospice deaths increased during the study period. Conclusions: This study highlights the increasing rate of PD AAMR and how it may become even more prevalent with time, emphasizing the value of increasing knowledge surrounding the disease and its trends to better prepare health systems and individual families for the burden of PD. |
| format | Article |
| id | doaj-art-ba74e0163a8e400cad2a937a7716fb3e |
| institution | DOAJ |
| issn | 2673-4087 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | NeuroSci |
| spelling | doaj-art-ba74e0163a8e400cad2a937a7716fb3e2025-08-20T02:42:23ZengMDPI AGNeuroSci2673-40872025-01-0161610.3390/neurosci6010006Trends and Disparities in Parkinson’s Disease Mortality in the United States with Predictions Using Machine LearningHenry Weresh0Kallin Hermann1Ali Al-Salahat2Amna Noor3Taylor Billion4Yu-Ting Chen5Abubakar Tauseef6Ali Bin Abdul Jabbar7School of Medicine, Creighton University, Omaha, NE 68178, USASchool of Medicine, Creighton University, Omaha, NE 68178, USANeurology Department, Creighton University, Omaha, NE 68178, USAServices Hospital, Lahore 40050, PakistanSchool of Medicine, Creighton University, Omaha, NE 68178, USANeurology Department, Creighton University, Omaha, NE 68178, USADepartment of Medicine, Creighton University, Omaha, NE 68178, USADepartment of Medicine, Creighton University, Omaha, NE 68178, USABackground: Parkinson’s disease (PD) is a progressive neurodegenerative condition characterized by the degradation of dopaminergic pathways in the brain. As the population in the United States continues to age, it is essential to understand the trends in mortality related to PD. This analysis of PD’s mortality characterizes temporal shifts, examines demographic and regional differences, and provides machine-learning predictions. Methods: PD-related deaths in the United States were gathered from CDC WONDER. Age-adjusted mortality rates (AAMR) were collected, and trends were analyzed based on gender, race, region, age, and place of death. Annual percent change and average annual percent change were calculated using Joinpoint Regression program. Forecasts were obtained using the optimal Autoregressive Integrated Moving Average (ARIMA) model. Results: Overall mortality rate due to Parkinson’s increased from 1999 to 2022. Male gender, White race, Southern region, and older ages were associated with higher mortality compared to other groups. Deaths at home decreased and hospice deaths increased during the study period. Conclusions: This study highlights the increasing rate of PD AAMR and how it may become even more prevalent with time, emphasizing the value of increasing knowledge surrounding the disease and its trends to better prepare health systems and individual families for the burden of PD.https://www.mdpi.com/2673-4087/6/1/6Parkinson diseasemortalityhealthcare disparitiesParkinson disease mortalitymachine learning |
| spellingShingle | Henry Weresh Kallin Hermann Ali Al-Salahat Amna Noor Taylor Billion Yu-Ting Chen Abubakar Tauseef Ali Bin Abdul Jabbar Trends and Disparities in Parkinson’s Disease Mortality in the United States with Predictions Using Machine Learning NeuroSci Parkinson disease mortality healthcare disparities Parkinson disease mortality machine learning |
| title | Trends and Disparities in Parkinson’s Disease Mortality in the United States with Predictions Using Machine Learning |
| title_full | Trends and Disparities in Parkinson’s Disease Mortality in the United States with Predictions Using Machine Learning |
| title_fullStr | Trends and Disparities in Parkinson’s Disease Mortality in the United States with Predictions Using Machine Learning |
| title_full_unstemmed | Trends and Disparities in Parkinson’s Disease Mortality in the United States with Predictions Using Machine Learning |
| title_short | Trends and Disparities in Parkinson’s Disease Mortality in the United States with Predictions Using Machine Learning |
| title_sort | trends and disparities in parkinson s disease mortality in the united states with predictions using machine learning |
| topic | Parkinson disease mortality healthcare disparities Parkinson disease mortality machine learning |
| url | https://www.mdpi.com/2673-4087/6/1/6 |
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