Latent profile analysis of social participation among adults with cardiovascular disease based on the CHARLS

基于CHARLS数据对心血管疾病成人社会参与度进行潜在剖面分析。

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Abstract

Social participation is recognized as a critical factor in reducing mortality and promoting healthy aging in middle-aged and older adults with cardiovascular disease (CVD). However, the determinants influencing social participation within this demographic remain poorly understood. The present study sought to assess the social participation status of middle-aged and older individuals with CVD and identify the factors influencing their participation levels. A cross-sectional analysis was conducted using 2018 data from the China Health and Retirement Longitudinal Study (CHARLS) database. Descriptive statistics and analysis of variance (ANOVA) were employed to explore differences and correlations among variables. Latent class analysis was performed using Mplus 8.3 software, while logistic regression analysis was utilized to examine patterns of social participation and their associated factors. A total of 2388 participants were included in the analysis. Latent profile analysis identified four distinct social participation patterns: "individual participation," "group participation," "full participation," and "low participation." Significant differences (P < 0.05) were found across these patterns with regard to educational attainment, geographic location, living conditions, health insurance coverage, and alcohol consumption. Social participation was associated with health status, ADL, IADL, loneliness, and depression. High level of social participation as a component of healthy lifestyle has been identified to be effective in reducing CVD mortality. Therefore, targeted interventions to enhance social participation may improve cardiovascular health outcomes in middle-aged and older adults.

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