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

Content Provider	Springer Nature : BioMed Central
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
Abstract	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.
Related Links	https://bmcpublichealth.biomedcentral.com/counter/pdf/10.1186/s12889-023-17177-3.pdf
Ending Page	12
Page Count	12
Starting Page	1
File Format	HTM / HTML
ISSN	14712458
DOI	10.1186/s12889-023-17177-3
Journal	BMC Public Health
Issue Number	1
Volume Number	23
Language	English
Publisher	BioMed Central
Publisher Date	2023-11-21
Access Restriction	Open
Subject Keyword	Public Health Medicine Epidemiology Biostatistics Vaccine Environmental Health Cluster analysis Multivariate analysis of variance Principal component analysis Lifestyle scoring system Lifestyle pattern MAFLD Medicine/Public Health
Content Type	Text
Resource Type	Article
Subject	Public Health, Environmental and Occupational Health
Journal Impact Factor	3.5/2023
5-Year Journal Impact Factor	3.9/2023

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