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Multi-state Markov model in outcome of mild cognitive impairments among community elderly residents in Mainland China

Published online by Cambridge University Press:  03 January 2013

Hong-mei Yu ,
Shan-shan Yang ,
Jian-wei Gao ,
Li-ye Zhou ,
Rui-feng Liang  and
Cheng-yi Qu
Hong-mei Yu*
Affiliation:
Department of Health Statistics, School of Public Health, Shanxi Medical University, People's Republic of China
Shan-shan Yang
Affiliation:
Guangwai Community Health Service Center of Beijing, Beijing, People's Republic of China
Jian-wei Gao
Affiliation:
Department of Health Statistics, School of Public Health, Shanxi Medical University, People's Republic of China
Li-ye Zhou
Affiliation:
Department of Health Statistics, School of Public Health, Shanxi Medical University, People's Republic of China
Rui-feng Liang
Affiliation:
Department of Health Statistics, School of Public Health, Shanxi Medical University, People's Republic of China
Cheng-yi Qu
Affiliation:
Department of Health Statistics, School of Public Health, Shanxi Medical University, People's Republic of China
*
Correspondence should be addressed to: Hong-mei Yu, Department of Health Statistics, School of Public Health, Shanxi Medical University, 56 South XinJian Road, Taiyuan, 030001, People's Republic of China. Phone: +86-351-4135049; Fax: +86-351-2027943. Email: yu_hongmei@hotmail.com.
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Abstract

Background: Although knowledge of established risk factors for Alzheimer's disease (AD) can logically contribute to the search for predictors of the progression of cognitive impairment, it has not yet been firmly established where in the cognitive impairment process these risk factors exert their effects and how to predict quantitatively for the progression of mild cognitive impairments (MCI) to AD. This study aimed to determine whether known risk factors increased the risk of progression from MCI to AD and to make prediction based on transition probabilities.

Methods: Based on ten examinations of 600 community-dwelling MCI residents and cognitive assessments to classify individuals into MCI, global impairment, and AD, a multi-state Markov Cox's regression model was used and the hazard ratios with their confidence intervals and transition probabilities were estimated.

Results: Multivariate analysis showed that gender, age, and hypertension were statistically significant predictors of transition from MCI to global impairment; age, education, and reading statistically influenced transition from global impairment to MCI; gender, age, hypertension, diabetes, and apolipoprotein E geneε4 status were statistically associated with transition from global impairment to AD. Subjects at MCI were more likely (67%) to remain in that cognitive state at the next cognitive assessment than to transition to cognitive deterioration. For global impairment, probability of remaining in the same state was only 18% and that of forward transition was three times more likely than that of backward transition.

Conclusions: Known risk factors influenced differently for different transitions. Transition from global impairment was more likely to worsen to severe cognitive deterioration than transition from MCI.

Keywords

Alzheimer's diseasemild cognitive impairmentslongitudinal studyprogressionrisk factorsmulti-state Markov model
Type
Research Article
Information
International Psychogeriatrics , Volume 25 , Issue 5 , May 2013 , pp. 797 - 804
Copyright
Copyright © International Psychogeriatric Association 2013

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