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BMC Neurol ; 24(1): 221, 2024 Jun 27.
Article in English | MEDLINE | ID: mdl-38937689

ABSTRACT

BACKGROUND: Parkinson's disease (PD) is a progressive neurodegenerative disorder characterized by motor and nonmotor system manifestations and psychiatric symptoms. The aim of this study was to estimate the age- and sex-specific incidence of PD in Germany using an illness-death model and a corresponding partial differential equation (PDE) based on prevalence and mortality data. METHODS: Based on a PDE that describes the dynamics in an illness-death model, the age- and sex-specific incidence of PD in Germany was estimated using published prevalence and mortality rates. Prevalence rates were provided by the Central Institute for Statutory Health Insurance (Zi) for the period from 2010 to 2019. Parkinson's related mortality was estimated based on comparable population data from Norway. Bootstrapping was used for incidence estimation (median of 5000 samples) and to obtain 95% confidence intervals to interpret the accuracy of the incidence estimation. RESULTS: Men had higher incidences of PD than women at all ages. The highest incidences (median of 5000 bootstrap samples) for both groups were estimated for the age of 85 years with an incidence of 538.49 per 100,000 person-years (py) in men and 284.09 per 100,000 py in women, with an increasing width of bootstrapping 95% CIs showing greater uncertainty in the estimation at older ages. CONCLUSION: The illness-death model and the corresponding PDE, which describes changes in prevalence as a function of mortality and incidence, can be used to estimate the incidence of PD as a chronic disease. As overestimation of incidence is less likely with this method, we found incidence rates of Parkinson's disease that are suitable for further analyses with a lower risk of bias.


Subject(s)
Parkinson Disease , Humans , Parkinson Disease/epidemiology , Male , Germany/epidemiology , Female , Aged , Middle Aged , Incidence , Prevalence , Aged, 80 and over , Adult , Insurance, Health/statistics & numerical data , Young Adult , Adolescent
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