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Updated: May 4, 2026

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
The prevalence of mild cognitive impairment and its etiological subtypes in elderly Chinese
Jianping Jia1, Aihong Zhou1, Cuibai Wei1
1Department of Neurology, Xuan Wu Hospital, Capital Medical University, Beijing, People's Republic of China.
Background:
Epidemiologic studies on mild cognitive impairment (MCI) are limited in China.
Methods:
Using a multistage cluster sampling design, a total of 10,276 community residents (6096 urban, 4180 rural) aged 65 years or older were evaluated and diagnosed with normal cognition, MCI, or dementia. MCI was further categorized by imaging into MCI caused by prodromal Alzheimer's disease (MCI-A), MCI resulting from cerebrovascular disease (MCI-CVD), MCI with vascular risk factors (MCI-VRF), and MCI caused by other diseases (MCI-O).
Results:
The prevalences of overall MCI, MCI-A, MCI-CVD, MCI-VRF, and MCI-O were 20.8% (95% confidence interval [CI] = 20.0-21.6%), 6.1% (95% CI = 5.7-6.6%), 3.8% (95% CI = 3.4-4.2%), 4.9% (95% CI = 4.5-5.4%), and 5.9% (95% CI = 5.5-6.4%) respectively. The rural population had a higher prevalence of overall MCI (23.4% vs 16.8%, P < .001).
Conclusions:
The prevalence of MCI in elderly Chinese is higher in rural than in urban areas. Vascular-related MCI (MCI-CVD and MCI-VRF) was most common.
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