Background: China's socioeconomic and population structures have evolved markedly during the past few decades, and consequently, monitoring the prevalence of Parkinson's disease (PD) is crucial.
Objective: This study aimed to investigate the prevalence of PD within Chinese communities, particularly in older people.
Methods: A nationwide study of 24,117 participants, aged 60 years or older, was carried out in 2015 using multistage clustered sampling. All participants were initially screened using a nine-item questionnaire, from which those suspected of having PD were examined by neurologists and a diagnosis was given, according to the 2015 Movement Disorder Society Clinical Diagnostic Criteria.
Results: The prevalence of PD was 1.37% (95% confidence interval 1.02%-1.73%) in people aged over 60 years. Thus, the estimated total number of people in China with PD could be as high as 3.62 million.
Conclusions: Although the PD population prevalence percentage did not change significantly, the total number of PD sufferers has increased with the increased population, which poses a significant challenge in a rapidly aging population. © 2021 International Parkinson and Movement Disorder Society.
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http://dx.doi.org/10.1002/mds.28762 | DOI Listing |
Comput Med Imaging Graph
January 2025
The SMART (Smart Medicine and AI-based Radiology Technology) Lab, Shanghai Institute for Advanced Communication and Data Science, Shanghai University, Shanghai, China; Key Laboratory of Specialty Fiber Optics and Optical Access Networks, School of Communication and Information Engineering, Shanghai University, Shanghai, China. Electronic address:
Parkinson disease (PD) is a prevalent neurodegenerative disorder, and its accurate diagnosis is crucial for timely intervention. We propose the PArkinson disease Denoising and Segmentation Network (PADS-Net), to simultaneously denoise and segment transcranial ultrasound images of midbrain for accurate PD diagnosis. The PADS-Net is built upon generative adversarial networks and incorporates a multi-task deep learning framework aimed at optimizing the tasks of denoising and segmentation for ultrasound images.
View Article and Find Full Text PDFNat Food
January 2025
School of Biological Sciences, University of Aberdeen, Aberdeen, UK.
Nutritional epidemiology aims to link dietary exposures to chronic disease, but the instruments for evaluating dietary intake are inaccurate. One way to identify unreliable data and the sources of errors is to compare estimated intakes with the total energy expenditure (TEE). In this study, we used the International Atomic Energy Agency Doubly Labeled Water Database to derive a predictive equation for TEE using 6,497 measures of TEE in individuals aged 4 to 96 years.
View Article and Find Full Text PDFFood Sci Nutr
January 2025
Gülhane School of Medicine, Department of Physical Medicine and Rehabilitation University of Health Sciences Turkey Ankara Turkey.
To demonstrate the prevalence of malnutrition risk in a specific rehabilitation setting. The secondary aim of the study was to compare Malnutrition Screening Tool (MST) and Malnutrition Universal Screening Tool (MUST) with Nutritional Risk Screening-2002 (NRS-2002). Patients diagnosed with stroke, anoxic brain injury, spinal cord injury, multiple sclerosis, arthritis, neuromuscular diseases, Parkinson's disease, and lymphedema who were admitted to a rehabilitation hospital were included.
View Article and Find Full Text PDFCogn Neurodyn
December 2025
Department of Physiology, School of Basic Medical Sciences, Chengdu Medical College, Sichuan, 610500 China.
Unlabelled: Parkinson's disease (PD) is a neurodegenerative disease with various clinical manifestations caused by multiple risk factors. However, the effect of different factors and relationships between different features related to PD and the extent of those factors leading to the incidence of PD remains unclear. we employed Bayesian network to construct a prediction model.
View Article and Find Full Text PDFSleep Epidemiol
December 2024
Health through Physical Activity, Lifestyle and Sport Research Centre and Division of Physiological Sciences, Department of Human Biology, Faculty of Health Sciences, University of Cape Town, Cape Town, South Africa.
Background: Risk factors for cardiovascular disease (CVD) and sleep health are well-known to be sex- and race-specific. To build on the established relationship between sleep duration and CVD risk, this cross-sectional study aimed to describe sex-specific associations between CVD risk and other sleep characteristics (sleep quality, sleep timing and sleep onset latency) in low-income adults of African descent.
Methods: Self-reported sleep (Pittsburgh Sleep Quality Index [PSQI], Epworth Sleepiness Scale [ESS], Insomnia Severity Index [ISI]), demographic and lifestyle data were collected in 412 adults (56 % women, 35.
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