Hospital Morbidity due to Parkinson's Disease in Brazilian Regions between 2020 and 2024

Introduction: Parkinson's disease (PD) is a slow and progressive neurological condition that causes loss of functional movement in humans due to the destruction of dopamine-producing cells. As in the rest of the world, Brazil is also negatively affected by this disease. It is crucial to analyze hospital morbidity patterns in the country, given that this disease influences the five different Brazilian macroregions and may be related to certain common characteristics among them. Methods: A time series analysis of hospitalizations for Parkinson's disease over the last five years was performed. Macroregional data on hospital morbidity were selected and associated with their respective population projections, extracted from Brazil's public health database, DataSUS, to compare the prevalence of the disease in the five regions of the country. Results and Discussion: A total of 4,945 hospital admissions for PD were recorded during the study period. The Southeast region accounted for the highest number of admissions (2,294; 46.3%), followed by the South (1,413; 28.6%), Northeast (779; 15.7%), Central–West (275; 5.6%), and North (184; 3.7%) regions. The year 2024 had the highest incidence (1,227 cases; 24.8%), while 2020 had the lowest (349 cases; 7%). Considering population distribution, the South region had a disproportionately high rate of hospitalizations compared to its demographic size, suggesting a higher prevalence of the disease, better diagnostic capacity, or differences in access to healthcare. Conclusions: Hospital morbidity due to PD in Brazil reveals significant regional disparities, with the Southeast and South regions accounting for the majority of admissions. These findings highlight the need to strengthen diagnostic strategies, improve access to care, and adapt regional health policies to address the growing burden of PD. Further research is needed to explore the socioeconomic and health factors that influence these disparities.