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Multimorbidity patterns in old adults and their associated multi-layered factors: a cross-sectional study

BACKGROUND: Influenced by various factors such as socio-demographic characteristics, behavioral lifestyles and socio-cultural environment, the multimorbidity patterns in old adults remain complex. This study aims to identify their characteristics and associated multi-layered factors based on health...

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Autores principales: Lu, Jiao, Wang, Yuan, Hou, Lihong, Zuo, Zhenxing, Zhang, Na, Wei, Anle
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8214251/
https://www.ncbi.nlm.nih.gov/pubmed/34147073
http://dx.doi.org/10.1186/s12877-021-02292-w
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author Lu, Jiao
Wang, Yuan
Hou, Lihong
Zuo, Zhenxing
Zhang, Na
Wei, Anle
author_facet Lu, Jiao
Wang, Yuan
Hou, Lihong
Zuo, Zhenxing
Zhang, Na
Wei, Anle
author_sort Lu, Jiao
collection PubMed
description BACKGROUND: Influenced by various factors such as socio-demographic characteristics, behavioral lifestyles and socio-cultural environment, the multimorbidity patterns in old adults remain complex. This study aims to identify their characteristics and associated multi-layered factors based on health ecological model. METHODS: In 2019, we surveyed a total of 7480 participants aged 60+ by using a multi-stage random cluster sampling method in Shanxi province, China. Latent class analysis was used to discriminate the multimorbidity patterns in old adults, and hierarchical regression was performed to determine the multi-layered factors associated with their various multimorbidity patterns. RESULTS: The prevalence of multimorbidity was 34.70% among the old patients with chronic disease. Over half (60.59%) of the patients with multimorbidity had two co-existing chronic diseases. “Degenerative/digestive diseases”, “metabolic diseases” and “cardiovascular diseases” were three specific multimorbidity patterns. Behavioral lifestyles-layered factors had the most explanatory power for the three patterns, whose proportions of explanatory power were 54.00, 43.90 and 48.15% individually. But the contributions of other multi-layered factors were different in different patterns; balanced diet, medication adherence, the size of family and friendship network, and different types of basic medical insurance might have the opposite effect on the three multimorbidity patterns (p < 0.05). CONCLUSIONS: In management of old patients with multimorbidity, we should prioritize both the “lifestyle change”-centered systematic management strategy and group-customized intervention programs. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12877-021-02292-w.
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spelling pubmed-82142512021-06-23 Multimorbidity patterns in old adults and their associated multi-layered factors: a cross-sectional study Lu, Jiao Wang, Yuan Hou, Lihong Zuo, Zhenxing Zhang, Na Wei, Anle BMC Geriatr Research Article BACKGROUND: Influenced by various factors such as socio-demographic characteristics, behavioral lifestyles and socio-cultural environment, the multimorbidity patterns in old adults remain complex. This study aims to identify their characteristics and associated multi-layered factors based on health ecological model. METHODS: In 2019, we surveyed a total of 7480 participants aged 60+ by using a multi-stage random cluster sampling method in Shanxi province, China. Latent class analysis was used to discriminate the multimorbidity patterns in old adults, and hierarchical regression was performed to determine the multi-layered factors associated with their various multimorbidity patterns. RESULTS: The prevalence of multimorbidity was 34.70% among the old patients with chronic disease. Over half (60.59%) of the patients with multimorbidity had two co-existing chronic diseases. “Degenerative/digestive diseases”, “metabolic diseases” and “cardiovascular diseases” were three specific multimorbidity patterns. Behavioral lifestyles-layered factors had the most explanatory power for the three patterns, whose proportions of explanatory power were 54.00, 43.90 and 48.15% individually. But the contributions of other multi-layered factors were different in different patterns; balanced diet, medication adherence, the size of family and friendship network, and different types of basic medical insurance might have the opposite effect on the three multimorbidity patterns (p < 0.05). CONCLUSIONS: In management of old patients with multimorbidity, we should prioritize both the “lifestyle change”-centered systematic management strategy and group-customized intervention programs. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12877-021-02292-w. BioMed Central 2021-06-19 /pmc/articles/PMC8214251/ /pubmed/34147073 http://dx.doi.org/10.1186/s12877-021-02292-w Text en © The Author(s) 2021 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 Article
Lu, Jiao
Wang, Yuan
Hou, Lihong
Zuo, Zhenxing
Zhang, Na
Wei, Anle
Multimorbidity patterns in old adults and their associated multi-layered factors: a cross-sectional study
title Multimorbidity patterns in old adults and their associated multi-layered factors: a cross-sectional study
title_full Multimorbidity patterns in old adults and their associated multi-layered factors: a cross-sectional study
title_fullStr Multimorbidity patterns in old adults and their associated multi-layered factors: a cross-sectional study
title_full_unstemmed Multimorbidity patterns in old adults and their associated multi-layered factors: a cross-sectional study
title_short Multimorbidity patterns in old adults and their associated multi-layered factors: a cross-sectional study
title_sort multimorbidity patterns in old adults and their associated multi-layered factors: a cross-sectional study
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8214251/
https://www.ncbi.nlm.nih.gov/pubmed/34147073
http://dx.doi.org/10.1186/s12877-021-02292-w
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