INTRODUCTION: The prevalence of Parkinson's disease (PD) has increased globally, especially in China, and emerged as a critical public health challenge. AIM OF THE STUDY: Based on the Global Burden of Disease (GBD) and the China Health and Retirement Longitudinal Study (CHARLS) databases, this study explores temporal trends in Parkinson's disease (PD) prevalence and its risk factors among middle-aged and older Chinese adults from 1992 to 2021. MATERIAL AND METHODS: The age-period-cohort (APC) model was used to analyze the effects of age, period, and birth cohort on PD prevalence. Chi-square tests were used to determine risk and protective factors for PD. The autoregressive integrated moving average (ARIMA) model was used to predict trends in PD prevalence in China and worldwide over the next 10 years, and several machine learning models were used to develop a classifier for the early screening of PD. RESULTS: The results showed that the average annual growth rate of PD prevalence in China was twice the global average, and this high growth rate is projected to continue in the next decade. Analysis of the CHARLS data showed that aging, urban residence, and metabolic diseases such as diabetes, hypertension, and dyslipidemia were significantly associated with the risk of PD, while moderate alcohol consumption may have a protective effect. Among the machine learning models, the random forest model had the best performance for the early screening of PD (sensitivity 0.968), confirming the significant value of artificial intelligence methods in the precise prevention of PD. CONCLUSIONS AND CLINICAL IMPLICATIONS: This study revealed that population aging and advances in diagnostic and treatment systems have led to a heavy burden of PD in China. Public health prevention of PD in China should strengthen the precise screening of high-risk groups and early intervention for risk factors, thereby enabling public health departments to more effectively alleviate the medical and socioeconomic burden of the disease.
Tan et al. (Tue,) studied this question.