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Updated: Dec 2, 2025

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
Influence of Lifestyles on Mild Cognitive Impairment: A Decision Tree Model Study
Zongqiu Wang1, Jiwen Hou2, Yu Shi3
1Department of Geriatrics, The Affiliated Hospital of Qingdao University, Qingdao, People's Republic of China.
Objective:
To explore the effects of different lifestyle choices on mild cognitive impairment (MCI) and to establish a decision tree model to analyse their predictive significance on the incidence of MCI.
Methods:
Study participants were recruited from geriatric and physical examination centres from October 2015 to October 2019: 330 MCI patients and 295 normal cognitive (NC) patients. Cognitive function was evaluated by the Mini-Mental State Examination Scale (MMSE) and Clinical Dementia Scale (CDR), while the Barthel Index (BI) was used to evaluate life ability. Statistical analysis included the χ 2 test, logistic regression, and decision tree. The ROC curve was drawn to evaluate the predictive ability of the decision tree model.
Results:
Logistic regression analysis showed that low education, living alone, smoking, and a high-fat diet were risk factors for MCI, while young age, tea drinking, afternoon naps, social engagement, and hobbies were protective factors for MCI. Social engagement, a high-fat diet, hobbies, living condition, tea drinking, and smoking entered all nodes of the decision tree model, with social engagement as the root node variable. The importance of predictive variables in the decision tree model showed social engagement, a high-fat diet, tea drinking, hobbies, living condition, and smoking as 33.57%, 27.74%, 22.14%, 11.94%, 4.61%, and 0%, respectively. The area under the ROC curve predicted by the decision tree model was 0.827 (95% CI: 0.795~0.856).
Conclusion:
The decision tree model has good predictive ability. MCI was closely related to lifestyle; social engagement was the most important factor in predicting the occurrence of MCI.
Insights
Social engagement is key to preventing mild cognitive impairment (MCI). Lifestyle choices like diet and hobbies significantly impact cognitive health, with a predictive model showing strong accuracy.
Area of Science:
- Gerontology
- Neuroscience
- Public Health
Background:
- Mild cognitive impairment (MCI) poses a growing public health challenge.
- Understanding lifestyle impacts on cognitive decline is crucial for prevention strategies.
Purpose of the Study:
- To investigate the influence of various lifestyle choices on the incidence of MCI.
- To develop a predictive decision tree model for MCI risk assessment.
Main Methods:
- Cross-sectional study involving 330 MCI and 295 normal cognitive (NC) participants.
- Cognitive function assessed using MMSE and CDR; life ability evaluated by BI.
- Statistical analysis included logistic regression and decision tree modeling with ROC curve analysis.
Main Results:
- Low education, living alone, smoking, and high-fat diet identified as MCI risk factors.
- Young age, tea drinking, naps, social engagement, and hobbies emerged as protective factors.
- Decision tree model highlighted social engagement (33.57%) and high-fat diet (27.74%) as primary predictors; ROC AUC was 0.827.
Conclusions:
- Lifestyle significantly influences MCI development, with social engagement being the most critical predictive factor.
- The developed decision tree model demonstrates robust predictive capabilities for MCI incidence.
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