Epidemiological analysis of Parkinson's disease in Krasnodar

Background. Parkinson's disease, a chronic progressive disease of the central nervous system, is the second most common neurodegenerative disease. Life expectancy has been steadily increasing in recent decades, therefore, the number of patients with Parkinson's disease will increase sharply in the coming decades both throughout the world and in Russia. Epidemiological data of Parkinson's disease are variable throughout the world and within one country. The results of studies of epidemiological indicators of Parkinson's disease in Russia differ significantly depending on the region where they were conducted, which may be due to the demographic characteristics of populations, migration processes, environmental influences, and differences in the organization of the healthcare system. The purpose of the study is to study the main epidemiological indicators for Parkinson's disease in Krasnodar, as well as the structure of some clinical characteristics. Results. A retrospective analysis was carried out with subsequent statistical processing of 693 outpatient records of patients with Parkinson's disease for 2021, who were under observation in the office of extrapyramidal disorders of the State Budgetary Healthcare Institution of the SBHI RCH named after Professor S. V. Ochapovsky for the period from 2013 to 2021, included in the database of the unified register of patients with Parkinson's disease in the territory of Krasnodar. The obtained data were processed by the method of variation statistics using a personal computer and statistical programs Statistica 10 and Microsoft Office Excel 2007. Prevalence of Parkinson's disease in Krasnodar is above the national average. The ratio between men and women is not statistically significant. The highest prevalence rate is in the age group from 60 to 80 years. The mixed (akinetic-rigid-tremorous) form, stage 3 of the disease, predominates in the population, moderate rate of progression. Conclusion. The data obtained can be used to expand the information in a unified database, identify existing problems at the diagnostic and treatment stage, which will improve the quality and life expectancy of patients.