Influence of Lifestyles on Mild Cognitive Impairment: A Decision Tree Model Study

被引:21
作者
Wang, Zongqiu [1 ]
Hou, Jiwen [2 ]
Shi, Yu [3 ]
Tan, Qiaowen [1 ]
Peng, Lin [1 ]
Deng, Zhiying [1 ]
Wang, Zhihong [1 ]
Guo, Zongjun [1 ]
机构
[1] Qingdao Univ, Dept Geriatr, Affiliated Hosp, 16 Jiangsu Rd, Qingdao 266003, Shandong, Peoples R China
[2] Chengdu Univ, Dept Geriatr, Affiliated Hosp, Chengdu, Peoples R China
[3] Weihai Cent Hosp, Dept Crit Med, Weihai, Peoples R China
关键词
lifestyle; behaviours habit; mild cognitive impairment; influencing factors; decision tree model; RISK-FACTORS; DEMENTIA; SMOKING; DECLINE; DISEASE;
D O I
10.2147/CIA.S265839
中图分类号
R592 [老年病学]; C [社会科学总论];
学科分类号
03 ; 0303 ; 100203 ;
摘要
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, 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.
引用
收藏
页码:2009 / 2017
页数:9
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