Exercise self-efficacy in older adults with metabolic-associated fatty liver disease: A latent profile analysis

Abstract

China has a high prevalence rate of Metabolic-associated fatty liver disease (MAFLD), and there is currently limited understanding of the levels of exercise self-efficacy (ESE) among individuals with MAFLD. The objective was to explore the potential ESE patterns in older adults with MAFLD. A cross-sectional study was conducted on 800 older adults with fatty liver disease from five communities from April 20, 2023 to August 15, 2023. Latent profile analysis (LPA) and k-means clustering were used to determine the optimal number of ESE groups. Using univariate analysis and multivariate logistic regression to investigate the factors influencing profiles of ESE. A sample of 775 subjects met the diagnostic criteria for MAFLD. LPA yielded three profiles: the low-ESE, mild-ESE, and high-ESE groups, which comprised 25%, 28%, and 47% of the sample, respectively. K-means clustering further supported the categorization of ESE into three distinct classes. The multivariate logistic regression analysis revealed that diabetes, arthritis and/or arthrosis, as well as companionship during PA were significant influencing factors for the different profiles (p < 0.05). Our findings suggest that the ESE of older patients with MAFLD is primarily at a moderate level or above. There was population heterogeneity in ESE among older patients with MAFLD. Diabetes mellitus, arthritis, and/or arthrosis, as well as companionship during PA were significant factors in influencing the likelihood of having high ESE.

Keywords

Metabolic-associated fatty liver disease / Exercise self-efficacy / Older adults / Latent profile analysis

Ethical approval statement

The study was approved by the Ethics Committee of Jiangnan University (JNU202212011RB25), and conformed to the principles of the World Medical Association Declaration of Helsinki. Prior to gather data, each participant signed an informed consent statement.

Funding

This study was founded by the Wuxi Social development technology demonstration project (N20201003) and Top Talent Support Program for young and middle-aged people of Wuxi Health Committee (BJ 2023049).

Data availability statement

All relevant data are available from the manuscript.

CRediT authorship contribution statement

Huimin Zhou: Writing - original draft, Methodology, Investigation, Conceptualization. Haiyan Chen: Writing - original draft, Investigation. Di Wu: Writing - review & editing. Hanxiao Lu: Data curation. Bo Wu: Data curation. Zhixia Dong: Validation. Jun Yang: Writing - review & editing, Supervision, Resources.

Conflict of interest

The authors declare no conflict of interest.

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