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Clustering of lifestyle behaviours and analysis of their associations with MAFLD: a cross-sectional study of 196,515 individuals in China

BACKGROUND: The aggregation of lifestyle behaviours and their association with metabolic-associated fatty liver disease (MAFLD) remain unclear. We identified lifestyle patterns and investigated their association with the risk of developing MAFLD in a sample of Chinese adults who underwent annual phy...

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Autores principales: Zhou, Bingqian, Gong, Ni, He, Qingnan, Huang, Xinjuan, Zhu, Jingchi, Zhang, Lijun, Huang, Yanyan, Tan, Xinyun, Xia, Yuanqin, Zheng, Yu, Shi, Qiuling, Qin, Chunxiang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10664514/
https://www.ncbi.nlm.nih.gov/pubmed/37990228
http://dx.doi.org/10.1186/s12889-023-17177-3
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author Zhou, Bingqian
Gong, Ni
He, Qingnan
Huang, Xinjuan
Zhu, Jingchi
Zhang, Lijun
Huang, Yanyan
Tan, Xinyun
Xia, Yuanqin
Zheng, Yu
Shi, Qiuling
Qin, Chunxiang
author_facet Zhou, Bingqian
Gong, Ni
He, Qingnan
Huang, Xinjuan
Zhu, Jingchi
Zhang, Lijun
Huang, Yanyan
Tan, Xinyun
Xia, Yuanqin
Zheng, Yu
Shi, Qiuling
Qin, Chunxiang
author_sort Zhou, Bingqian
collection PubMed
description BACKGROUND: The aggregation of lifestyle behaviours and their association with metabolic-associated fatty liver disease (MAFLD) remain unclear. We identified lifestyle patterns and investigated their association with the risk of developing MAFLD in a sample of Chinese adults who underwent annual physical examinations. METHODS: Annual physical examination data of Chinese adults from January 2016 to December 2020 were used in this study. We created a scoring system for lifestyle items combining a statistical method (multivariate analysis of variance) and clinical expertise (Delphi method). Subsequently, principal component analysis and two-step cluster analysis were implemented to derive the lifestyle patterns of men and women. Binary logistic regression analysis was used to explore the prevalence risk of MAFLD among lifestyle patterns stratified by sex. RESULTS: A total of 196,515 subjects were included in the analysis. Based on the defined lifestyle scoring system, nine and four lifestyle patterns were identified for men and women, respectively, which included “healthy or unhealthy” patterns and mixed patterns containing a combination of healthy and risky lifestyle behaviours. This study showed that subjects with an unhealthy or mixed pattern had a significantly higher risk of developing MAFLD than subjects with a relatively healthy pattern, especially among men. CONCLUSIONS: Clusters of unfavourable behaviours are more prominent in men than in women. Lifestyle patterns, as important factors influencing the development of MAFLD, show significant sex differences in the risk of MAFLD. There is a strong need for future research to develop targeted MAFLD interventions based on the identified behavioural clusters by sex stratification. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12889-023-17177-3.
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spelling pubmed-106645142023-11-21 Clustering of lifestyle behaviours and analysis of their associations with MAFLD: a cross-sectional study of 196,515 individuals in China Zhou, Bingqian Gong, Ni He, Qingnan Huang, Xinjuan Zhu, Jingchi Zhang, Lijun Huang, Yanyan Tan, Xinyun Xia, Yuanqin Zheng, Yu Shi, Qiuling Qin, Chunxiang BMC Public Health Research BACKGROUND: The aggregation of lifestyle behaviours and their association with metabolic-associated fatty liver disease (MAFLD) remain unclear. We identified lifestyle patterns and investigated their association with the risk of developing MAFLD in a sample of Chinese adults who underwent annual physical examinations. METHODS: Annual physical examination data of Chinese adults from January 2016 to December 2020 were used in this study. We created a scoring system for lifestyle items combining a statistical method (multivariate analysis of variance) and clinical expertise (Delphi method). Subsequently, principal component analysis and two-step cluster analysis were implemented to derive the lifestyle patterns of men and women. Binary logistic regression analysis was used to explore the prevalence risk of MAFLD among lifestyle patterns stratified by sex. RESULTS: A total of 196,515 subjects were included in the analysis. Based on the defined lifestyle scoring system, nine and four lifestyle patterns were identified for men and women, respectively, which included “healthy or unhealthy” patterns and mixed patterns containing a combination of healthy and risky lifestyle behaviours. This study showed that subjects with an unhealthy or mixed pattern had a significantly higher risk of developing MAFLD than subjects with a relatively healthy pattern, especially among men. CONCLUSIONS: Clusters of unfavourable behaviours are more prominent in men than in women. Lifestyle patterns, as important factors influencing the development of MAFLD, show significant sex differences in the risk of MAFLD. There is a strong need for future research to develop targeted MAFLD interventions based on the identified behavioural clusters by sex stratification. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12889-023-17177-3. BioMed Central 2023-11-21 /pmc/articles/PMC10664514/ /pubmed/37990228 http://dx.doi.org/10.1186/s12889-023-17177-3 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This 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
Zhou, Bingqian
Gong, Ni
He, Qingnan
Huang, Xinjuan
Zhu, Jingchi
Zhang, Lijun
Huang, Yanyan
Tan, Xinyun
Xia, Yuanqin
Zheng, Yu
Shi, Qiuling
Qin, Chunxiang
Clustering of lifestyle behaviours and analysis of their associations with MAFLD: a cross-sectional study of 196,515 individuals in China
title Clustering of lifestyle behaviours and analysis of their associations with MAFLD: a cross-sectional study of 196,515 individuals in China
title_full Clustering of lifestyle behaviours and analysis of their associations with MAFLD: a cross-sectional study of 196,515 individuals in China
title_fullStr Clustering of lifestyle behaviours and analysis of their associations with MAFLD: a cross-sectional study of 196,515 individuals in China
title_full_unstemmed Clustering of lifestyle behaviours and analysis of their associations with MAFLD: a cross-sectional study of 196,515 individuals in China
title_short Clustering of lifestyle behaviours and analysis of their associations with MAFLD: a cross-sectional study of 196,515 individuals in China
title_sort clustering of lifestyle behaviours and analysis of their associations with mafld: a cross-sectional study of 196,515 individuals in china
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10664514/
https://www.ncbi.nlm.nih.gov/pubmed/37990228
http://dx.doi.org/10.1186/s12889-023-17177-3
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