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

Zongqiu Wang,1,* Jiwen Hou,2,* Yu Shi,3 Qiaowen Tan,1 Lin Peng,1 Zhiying Deng,1 Zhihong Wang,1 Zongjun Guo1 1Department of Geriatrics, The Affiliated Hospital of Qingdao University, Qingdao, People’s Republic of China; 2Department of Geriatrics, The Affiliated Hospital of Chengdu Universit...

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Autores principales:	Wang Z, Hou J, Shi Y, Tan Q, Peng L, Deng Z, Guo Z
Formato:	article
Lenguaje:	EN
Publicado:	Dove Medical Press 2020
Materias:	lifestyle behaviours habit mild cognitive impairment influencing factors decision tree model Geriatrics RC952-954.6
Acceso en línea:	https://doaj.org/article/2903010b44ce4582918eae47db4172f0
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spelling	oai:doaj.org-article:2903010b44ce4582918eae47db4172f02021-12-02T12:31:39ZInfluence of Lifestyles on Mild Cognitive Impairment: A Decision Tree Model Study1178-1998https://doaj.org/article/2903010b44ce4582918eae47db4172f02020-10-01T00:00:00Zhttps://www.dovepress.com/influence-of-lifestyles-on-mild-cognitive-impairment-a-decision-tree-m-peer-reviewed-article-CIAhttps://doaj.org/toc/1178-1998Zongqiu Wang,1,* Jiwen Hou,2,* Yu Shi,3 Qiaowen Tan,1 Lin Peng,1 Zhiying Deng,1 Zhihong Wang,1 Zongjun Guo1 1Department of Geriatrics, The Affiliated Hospital of Qingdao University, Qingdao, People’s Republic of China; 2Department of Geriatrics, The Affiliated Hospital of Chengdu University, Chengdu, People’s Republic of China; 3Department of Critical Medicine, Weihai Central Hospital, Weihai, People’s Republic of China*These authors contributed equally to this workCorrespondence: Zongjun GuoDepartment of Geriatrics, The Affiliated Hospital of Qingdao University, No. 16 Jiangsu Road, Qingdao, Shandong 266003, People’s Republic of ChinaEmail guozjj@163.comObjective: 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 χ2 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&sim; 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.Keywords: lifestyle, behaviours habit, mild cognitive impairment, influencing factors, decision tree modelWang ZHou JShi YTan QPeng LDeng ZWang ZGuo ZDove Medical Pressarticlelifestylebehaviours habitmild cognitive impairmentinfluencing factorsdecision tree modelGeriatricsRC952-954.6ENClinical Interventions in Aging, Vol Volume 15, Pp 2009-2017 (2020)
institution	DOAJ
collection	DOAJ
language	EN
topic	lifestyle behaviours habit mild cognitive impairment influencing factors decision tree model Geriatrics RC952-954.6
spellingShingle	lifestyle behaviours habit mild cognitive impairment influencing factors decision tree model Geriatrics RC952-954.6 Wang Z Hou J Shi Y Tan Q Peng L Deng Z Wang Z Guo Z Influence of Lifestyles on Mild Cognitive Impairment: A Decision Tree Model Study
description	Zongqiu Wang,1,* Jiwen Hou,2,* Yu Shi,3 Qiaowen Tan,1 Lin Peng,1 Zhiying Deng,1 Zhihong Wang,1 Zongjun Guo1 1Department of Geriatrics, The Affiliated Hospital of Qingdao University, Qingdao, People’s Republic of China; 2Department of Geriatrics, The Affiliated Hospital of Chengdu University, Chengdu, People’s Republic of China; 3Department of Critical Medicine, Weihai Central Hospital, Weihai, People’s Republic of China*These authors contributed equally to this workCorrespondence: Zongjun GuoDepartment of Geriatrics, The Affiliated Hospital of Qingdao University, No. 16 Jiangsu Road, Qingdao, Shandong 266003, People’s Republic of ChinaEmail guozjj@163.comObjective: 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 χ2 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&sim; 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.Keywords: lifestyle, behaviours habit, mild cognitive impairment, influencing factors, decision tree model
format	article
author	Wang Z Hou J Shi Y Tan Q Peng L Deng Z Wang Z Guo Z
author_facet	Wang Z Hou J Shi Y Tan Q Peng L Deng Z Wang Z Guo Z
author_sort	Wang Z
title	Influence of Lifestyles on Mild Cognitive Impairment: A Decision Tree Model Study
title_short	Influence of Lifestyles on Mild Cognitive Impairment: A Decision Tree Model Study
title_full	Influence of Lifestyles on Mild Cognitive Impairment: A Decision Tree Model Study
title_fullStr	Influence of Lifestyles on Mild Cognitive Impairment: A Decision Tree Model Study
title_full_unstemmed	Influence of Lifestyles on Mild Cognitive Impairment: A Decision Tree Model Study
title_sort	influence of lifestyles on mild cognitive impairment: a decision tree model study
publisher	Dove Medical Press
publishDate	2020
url	https://doaj.org/article/2903010b44ce4582918eae47db4172f0
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Influence of Lifestyles on Mild Cognitive Impairment: A Decision Tree Model Study

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