Demographic Factors and Cognitive Function Assessments Associated with Mild Cognitive Impairment Progression for the Elderly
Objectives. In this study, we aimed to conduct a 6-year follow-up and acquire a large sample dataset to analyze the most important demographic factors and cognitive function scale variables associated with mild cognitive impairment (MCI) progression for an elderly cohort (age ≥ 60 years old). Patien...
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Online Access: | http://dx.doi.org/10.1155/2020/3054373 |
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doaj-9b678ff805e1456eb7cae4cd5cd6dd9a2020-11-25T03:05:26ZengHindawi LimitedBioMed Research International2314-61332314-61412020-01-01202010.1155/2020/30543733054373Demographic Factors and Cognitive Function Assessments Associated with Mild Cognitive Impairment Progression for the ElderlyHong-yun Qin0Xu-dong Zhao1Bing-gen Zhu2Cheng-ping Hu3Department of Psychiatry, Shanghai Pudong New Area Mental Heath Center, Tongji University School of Medicine, Shanghai 200124, ChinaDepartment of Psychiatry, Shanghai Pudong New Area Mental Heath Center, Tongji University School of Medicine, Shanghai 200124, ChinaDepartment of Psychiatry, Shanghai Pudong New Area Mental Heath Center, Tongji University School of Medicine, Shanghai 200124, ChinaDepartment of Psychiatry, Shanghai Pudong New Area Mental Heath Center, Tongji University School of Medicine, Shanghai 200124, ChinaObjectives. In this study, we aimed to conduct a 6-year follow-up and acquire a large sample dataset to analyze the most important demographic factors and cognitive function scale variables associated with mild cognitive impairment (MCI) progression for an elderly cohort (age ≥ 60 years old). Patients and Methods. We analyzed the subjects who had participated in a survey in 2011 and were successfully contacted in the later survey in 2017. For each subject, the basic demographic information was recorded, including sex, age, education level, marital status, working status, income level, and physical mental illness history. Cognitive assessments were performed using the following scales if possible: (1) the mini-mental state examination (MMSE) scale, (2) Montreal cognitive assessment (MoCA), (3) the clinical dementia rating (CDR) scale, and (4) Hamilton Depression Scale (HAMD-17). Results. The progression outcomes were different between sexes, among age brackets, education degrees, occupations types, and income levels; different progression groups had distinct children numbers (p<0.001), heights (p<0.05), and body weights (p<0.01); the positive ends six years later were positively related to better performance in the MoCA and MMSE scales (progressed vs stable p<0.01). Moreover, we constructed some indicators using age, MoCA, and MMSE scores, which showed an efficiency in predicting the progression outcomes. Conclusions. In conclusion, the MCI progression outcomes were associated with sex, age, education degrees, occupations types, income level, children number, height, and weight. MoCA and MMSE scales are supporting tools to predict the progression outcomes, especially combined with the demographic data.http://dx.doi.org/10.1155/2020/3054373 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Hong-yun Qin Xu-dong Zhao Bing-gen Zhu Cheng-ping Hu |
spellingShingle |
Hong-yun Qin Xu-dong Zhao Bing-gen Zhu Cheng-ping Hu Demographic Factors and Cognitive Function Assessments Associated with Mild Cognitive Impairment Progression for the Elderly BioMed Research International |
author_facet |
Hong-yun Qin Xu-dong Zhao Bing-gen Zhu Cheng-ping Hu |
author_sort |
Hong-yun Qin |
title |
Demographic Factors and Cognitive Function Assessments Associated with Mild Cognitive Impairment Progression for the Elderly |
title_short |
Demographic Factors and Cognitive Function Assessments Associated with Mild Cognitive Impairment Progression for the Elderly |
title_full |
Demographic Factors and Cognitive Function Assessments Associated with Mild Cognitive Impairment Progression for the Elderly |
title_fullStr |
Demographic Factors and Cognitive Function Assessments Associated with Mild Cognitive Impairment Progression for the Elderly |
title_full_unstemmed |
Demographic Factors and Cognitive Function Assessments Associated with Mild Cognitive Impairment Progression for the Elderly |
title_sort |
demographic factors and cognitive function assessments associated with mild cognitive impairment progression for the elderly |
publisher |
Hindawi Limited |
series |
BioMed Research International |
issn |
2314-6133 2314-6141 |
publishDate |
2020-01-01 |
description |
Objectives. In this study, we aimed to conduct a 6-year follow-up and acquire a large sample dataset to analyze the most important demographic factors and cognitive function scale variables associated with mild cognitive impairment (MCI) progression for an elderly cohort (age ≥ 60 years old). Patients and Methods. We analyzed the subjects who had participated in a survey in 2011 and were successfully contacted in the later survey in 2017. For each subject, the basic demographic information was recorded, including sex, age, education level, marital status, working status, income level, and physical mental illness history. Cognitive assessments were performed using the following scales if possible: (1) the mini-mental state examination (MMSE) scale, (2) Montreal cognitive assessment (MoCA), (3) the clinical dementia rating (CDR) scale, and (4) Hamilton Depression Scale (HAMD-17). Results. The progression outcomes were different between sexes, among age brackets, education degrees, occupations types, and income levels; different progression groups had distinct children numbers (p<0.001), heights (p<0.05), and body weights (p<0.01); the positive ends six years later were positively related to better performance in the MoCA and MMSE scales (progressed vs stable p<0.01). Moreover, we constructed some indicators using age, MoCA, and MMSE scores, which showed an efficiency in predicting the progression outcomes. Conclusions. In conclusion, the MCI progression outcomes were associated with sex, age, education degrees, occupations types, income level, children number, height, and weight. MoCA and MMSE scales are supporting tools to predict the progression outcomes, especially combined with the demographic data. |
url |
http://dx.doi.org/10.1155/2020/3054373 |
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