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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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Autores principales: Qin, Hong-yun, Zhao, Xu-dong, Zhu, Bing-gen, Hu, Cheng-ping
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7031731/
https://www.ncbi.nlm.nih.gov/pubmed/32090075
http://dx.doi.org/10.1155/2020/3054373
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author Qin, Hong-yun
Zhao, Xu-dong
Zhu, Bing-gen
Hu, Cheng-ping
author_facet Qin, Hong-yun
Zhao, Xu-dong
Zhu, Bing-gen
Hu, Cheng-ping
author_sort Qin, Hong-yun
collection PubMed
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 < 0.001), heights (p < 0.001), heights (p < 0.001), heights ( 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.
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spelling pubmed-70317312020-02-21 Demographic Factors and Cognitive Function Assessments Associated with Mild Cognitive Impairment Progression for the Elderly Qin, Hong-yun Zhao, Xu-dong Zhu, Bing-gen Hu, Cheng-ping Biomed Res Int Research Article 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 < 0.001), heights (p < 0.001), heights (p < 0.001), heights ( 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. Hindawi 2020-02-08 /pmc/articles/PMC7031731/ /pubmed/32090075 http://dx.doi.org/10.1155/2020/3054373 Text en Copyright © 2020 Hong-yun Qin et al. http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Qin, Hong-yun
Zhao, Xu-dong
Zhu, Bing-gen
Hu, Cheng-ping
Demographic Factors and Cognitive Function Assessments Associated with Mild Cognitive Impairment Progression for the Elderly
title 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_short 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
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7031731/
https://www.ncbi.nlm.nih.gov/pubmed/32090075
http://dx.doi.org/10.1155/2020/3054373
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