Cargando…
Sarcopenia Transitions and Influencing Factors Among Chinese Older Adults With Multistate Markov Model
BACKGROUND AND OBJECTIVES: Little is known about the sarcopenia transition process across different stages among Chinese community-dwelling older adults. We aimed to explore dynamic transitions of sarcopenia and its influencing factors in Chinese older adults. RESEARCH DESIGN AND METHODS: Data were...
Autores principales: | , , , , , , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10637947/ https://www.ncbi.nlm.nih.gov/pubmed/37954524 http://dx.doi.org/10.1093/geroni/igad105 |
_version_ | 1785133507972956160 |
---|---|
author | Sun, Boran Li, Shatao Wang, Yanbo Xiao, Wenbo Zhao, Han Liu, Xuewei Liu, Yang Lu, Xinlin Gao, Bei Zhou, Jiangtao Wang, Bingyi Wang, Yuan Chen, Yongjie Lu, Wenli |
author_facet | Sun, Boran Li, Shatao Wang, Yanbo Xiao, Wenbo Zhao, Han Liu, Xuewei Liu, Yang Lu, Xinlin Gao, Bei Zhou, Jiangtao Wang, Bingyi Wang, Yuan Chen, Yongjie Lu, Wenli |
author_sort | Sun, Boran |
collection | PubMed |
description | BACKGROUND AND OBJECTIVES: Little is known about the sarcopenia transition process across different stages among Chinese community-dwelling older adults. We aimed to explore dynamic transitions of sarcopenia and its influencing factors in Chinese older adults. RESEARCH DESIGN AND METHODS: Data were derived from the China Health and Retirement Longitudinal Study. A total of 2856 older adults with complete data in the 2011, 2013, and 2015 waves were included in our study. Participants were categorized into 3 states: no sarcopenia, possible sarcopenia, and sarcopenia according to the Asian Working Group for Sarcopenia 2019 (AWGS 2019) criteria. Continuous-time multistate Markov model was performed to estimate the 1-year transition probabilities and the associated factors of sarcopenia transitions. The association strength was expressed as hazard ratio and 95% confidence interval. RESULTS: The progression and reversion rates between no sarcopenia and sarcopenia state were 6.01 and 9.20 per 100 person-years, respectively. The 1-year progression probability to possible sarcopenia was higher compared with the likelihood of moving to the sarcopenia state (0.127 vs 0.034). The reversion probability to no sarcopenia was also higher among those with possible sarcopenia (0.281 vs 0.157). Older age, rural living, worse cognition status, higher chronic disease numbers, and lower nutrition status measured by body mass index accelerated the sarcopenia progression. Cognition status and body mass index level were related to higher chances of reverting. DISCUSSION AND IMPLICATIONS: Possible sarcopenia might be a critical time window to promote sarcopenia reversion. Timely interventions aimed at delaying the progression and facilitating sarcopenia recovery should focus on improving cognitive function and nutrition levels. |
format | Online Article Text |
id | pubmed-10637947 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-106379472023-11-11 Sarcopenia Transitions and Influencing Factors Among Chinese Older Adults With Multistate Markov Model Sun, Boran Li, Shatao Wang, Yanbo Xiao, Wenbo Zhao, Han Liu, Xuewei Liu, Yang Lu, Xinlin Gao, Bei Zhou, Jiangtao Wang, Bingyi Wang, Yuan Chen, Yongjie Lu, Wenli Innov Aging Original Research Article BACKGROUND AND OBJECTIVES: Little is known about the sarcopenia transition process across different stages among Chinese community-dwelling older adults. We aimed to explore dynamic transitions of sarcopenia and its influencing factors in Chinese older adults. RESEARCH DESIGN AND METHODS: Data were derived from the China Health and Retirement Longitudinal Study. A total of 2856 older adults with complete data in the 2011, 2013, and 2015 waves were included in our study. Participants were categorized into 3 states: no sarcopenia, possible sarcopenia, and sarcopenia according to the Asian Working Group for Sarcopenia 2019 (AWGS 2019) criteria. Continuous-time multistate Markov model was performed to estimate the 1-year transition probabilities and the associated factors of sarcopenia transitions. The association strength was expressed as hazard ratio and 95% confidence interval. RESULTS: The progression and reversion rates between no sarcopenia and sarcopenia state were 6.01 and 9.20 per 100 person-years, respectively. The 1-year progression probability to possible sarcopenia was higher compared with the likelihood of moving to the sarcopenia state (0.127 vs 0.034). The reversion probability to no sarcopenia was also higher among those with possible sarcopenia (0.281 vs 0.157). Older age, rural living, worse cognition status, higher chronic disease numbers, and lower nutrition status measured by body mass index accelerated the sarcopenia progression. Cognition status and body mass index level were related to higher chances of reverting. DISCUSSION AND IMPLICATIONS: Possible sarcopenia might be a critical time window to promote sarcopenia reversion. Timely interventions aimed at delaying the progression and facilitating sarcopenia recovery should focus on improving cognitive function and nutrition levels. Oxford University Press 2023-09-20 /pmc/articles/PMC10637947/ /pubmed/37954524 http://dx.doi.org/10.1093/geroni/igad105 Text en © The Author(s) 2023. Published by Oxford University Press on behalf of The Gerontological Society of America. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Original Research Article Sun, Boran Li, Shatao Wang, Yanbo Xiao, Wenbo Zhao, Han Liu, Xuewei Liu, Yang Lu, Xinlin Gao, Bei Zhou, Jiangtao Wang, Bingyi Wang, Yuan Chen, Yongjie Lu, Wenli Sarcopenia Transitions and Influencing Factors Among Chinese Older Adults With Multistate Markov Model |
title | Sarcopenia Transitions and Influencing Factors Among Chinese Older Adults With Multistate Markov Model |
title_full | Sarcopenia Transitions and Influencing Factors Among Chinese Older Adults With Multistate Markov Model |
title_fullStr | Sarcopenia Transitions and Influencing Factors Among Chinese Older Adults With Multistate Markov Model |
title_full_unstemmed | Sarcopenia Transitions and Influencing Factors Among Chinese Older Adults With Multistate Markov Model |
title_short | Sarcopenia Transitions and Influencing Factors Among Chinese Older Adults With Multistate Markov Model |
title_sort | sarcopenia transitions and influencing factors among chinese older adults with multistate markov model |
topic | Original Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10637947/ https://www.ncbi.nlm.nih.gov/pubmed/37954524 http://dx.doi.org/10.1093/geroni/igad105 |
work_keys_str_mv | AT sunboran sarcopeniatransitionsandinfluencingfactorsamongchineseolderadultswithmultistatemarkovmodel AT lishatao sarcopeniatransitionsandinfluencingfactorsamongchineseolderadultswithmultistatemarkovmodel AT wangyanbo sarcopeniatransitionsandinfluencingfactorsamongchineseolderadultswithmultistatemarkovmodel AT xiaowenbo sarcopeniatransitionsandinfluencingfactorsamongchineseolderadultswithmultistatemarkovmodel AT zhaohan sarcopeniatransitionsandinfluencingfactorsamongchineseolderadultswithmultistatemarkovmodel AT liuxuewei sarcopeniatransitionsandinfluencingfactorsamongchineseolderadultswithmultistatemarkovmodel AT liuyang sarcopeniatransitionsandinfluencingfactorsamongchineseolderadultswithmultistatemarkovmodel AT luxinlin sarcopeniatransitionsandinfluencingfactorsamongchineseolderadultswithmultistatemarkovmodel AT gaobei sarcopeniatransitionsandinfluencingfactorsamongchineseolderadultswithmultistatemarkovmodel AT zhoujiangtao sarcopeniatransitionsandinfluencingfactorsamongchineseolderadultswithmultistatemarkovmodel AT wangbingyi sarcopeniatransitionsandinfluencingfactorsamongchineseolderadultswithmultistatemarkovmodel AT wangyuan sarcopeniatransitionsandinfluencingfactorsamongchineseolderadultswithmultistatemarkovmodel AT chenyongjie sarcopeniatransitionsandinfluencingfactorsamongchineseolderadultswithmultistatemarkovmodel AT luwenli sarcopeniatransitionsandinfluencingfactorsamongchineseolderadultswithmultistatemarkovmodel |