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The transitions and predictors of cognitive frailty with multi-state Markov model: a cohort study

BACKGROUND: Cognitive frailty (CF) is characterized by the simultaneous presence of physical frailty and cognitive impairment. Previous studies have investigated its prevalence and impact on different adverse health-related outcomes. Few studies have focused on the progression and reversibility of C...

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Autores principales: Yuan, Manqiong, Xu, Chuanhai, Fang, Ya
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9248089/
https://www.ncbi.nlm.nih.gov/pubmed/35778705
http://dx.doi.org/10.1186/s12877-022-03220-2
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author Yuan, Manqiong
Xu, Chuanhai
Fang, Ya
author_facet Yuan, Manqiong
Xu, Chuanhai
Fang, Ya
author_sort Yuan, Manqiong
collection PubMed
description BACKGROUND: Cognitive frailty (CF) is characterized by the simultaneous presence of physical frailty and cognitive impairment. Previous studies have investigated its prevalence and impact on different adverse health-related outcomes. Few studies have focused on the progression and reversibility of CF and their potential predictors. METHODS: Data were derived from the China Health and Retirement Longitudinal Study (CHARLS). A total of 4051 older adults with complete data on three waves of the survey (2011, 2013, and 2015) were included and categorized into four groups: normal state (NS), cognitive impairment (CI) only, physical frailty (PF) only and CF (with both PF and CI). A multi-state Markov model was constructed to explore the transitions and predicting factors of CF. RESULTS: The incidence and improvement rates of CF were 1.70 and 11.90 per 100 person-years, respectively. The 1-year transition probability of progression to CF in those with CI was higher than that in the PF population (0.340 vs. 0.054), and those with CF were more likely to move to PF (0.208). Being female [hazard ratio (HR) = 1.46, 95%CI = 1.06, 2.02)], dissatisfied with life (HR = 4.94, 95%CI = 1.04, 23.61), had a history of falls (HR = 2.36, 95%CI = 1.02, 5.51), rural household registration (HR = 2.98, 95%CI = 1.61, 5.48), multimorbidity (HR = 2.17, 95%CI = 1.03, 4.59), and depression (HR = 1.75, 95%CI = 1.26, 2.45) increased the risk of progression to CF, whereas literacy (HR = 0.46, 95%CI = 0.33, 0.64) decreased such risk. Depression (HR = 0.43, 95%CI = 0.22, 0.84) reduced the likelihood of CF improvement, whereas literacy (HR = 2.23, 95%CI = 1.63, 3.07) increased such likelihood. CONCLUSIONS: Cognitive frailty is a dynamically changing condition in older adults. Possible interventions aimed at preventing the onset and facilitating the recovery of cognitive frailty should focus on improving cognitive function in older adults. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12877-022-03220-2.
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spelling pubmed-92480892022-07-02 The transitions and predictors of cognitive frailty with multi-state Markov model: a cohort study Yuan, Manqiong Xu, Chuanhai Fang, Ya BMC Geriatr Research BACKGROUND: Cognitive frailty (CF) is characterized by the simultaneous presence of physical frailty and cognitive impairment. Previous studies have investigated its prevalence and impact on different adverse health-related outcomes. Few studies have focused on the progression and reversibility of CF and their potential predictors. METHODS: Data were derived from the China Health and Retirement Longitudinal Study (CHARLS). A total of 4051 older adults with complete data on three waves of the survey (2011, 2013, and 2015) were included and categorized into four groups: normal state (NS), cognitive impairment (CI) only, physical frailty (PF) only and CF (with both PF and CI). A multi-state Markov model was constructed to explore the transitions and predicting factors of CF. RESULTS: The incidence and improvement rates of CF were 1.70 and 11.90 per 100 person-years, respectively. The 1-year transition probability of progression to CF in those with CI was higher than that in the PF population (0.340 vs. 0.054), and those with CF were more likely to move to PF (0.208). Being female [hazard ratio (HR) = 1.46, 95%CI = 1.06, 2.02)], dissatisfied with life (HR = 4.94, 95%CI = 1.04, 23.61), had a history of falls (HR = 2.36, 95%CI = 1.02, 5.51), rural household registration (HR = 2.98, 95%CI = 1.61, 5.48), multimorbidity (HR = 2.17, 95%CI = 1.03, 4.59), and depression (HR = 1.75, 95%CI = 1.26, 2.45) increased the risk of progression to CF, whereas literacy (HR = 0.46, 95%CI = 0.33, 0.64) decreased such risk. Depression (HR = 0.43, 95%CI = 0.22, 0.84) reduced the likelihood of CF improvement, whereas literacy (HR = 2.23, 95%CI = 1.63, 3.07) increased such likelihood. CONCLUSIONS: Cognitive frailty is a dynamically changing condition in older adults. Possible interventions aimed at preventing the onset and facilitating the recovery of cognitive frailty should focus on improving cognitive function in older adults. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12877-022-03220-2. BioMed Central 2022-07-01 /pmc/articles/PMC9248089/ /pubmed/35778705 http://dx.doi.org/10.1186/s12877-022-03220-2 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Yuan, Manqiong
Xu, Chuanhai
Fang, Ya
The transitions and predictors of cognitive frailty with multi-state Markov model: a cohort study
title The transitions and predictors of cognitive frailty with multi-state Markov model: a cohort study
title_full The transitions and predictors of cognitive frailty with multi-state Markov model: a cohort study
title_fullStr The transitions and predictors of cognitive frailty with multi-state Markov model: a cohort study
title_full_unstemmed The transitions and predictors of cognitive frailty with multi-state Markov model: a cohort study
title_short The transitions and predictors of cognitive frailty with multi-state Markov model: a cohort study
title_sort transitions and predictors of cognitive frailty with multi-state markov model: a cohort study
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9248089/
https://www.ncbi.nlm.nih.gov/pubmed/35778705
http://dx.doi.org/10.1186/s12877-022-03220-2
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