Evidence map›Paper›PMID 40653571›Full record

ArticleScientific reports2025

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

ShuLin Zhu, WeiYe Yang, AnNa Ma, LiNa Wang, Tong Zhao, XiaoLei Gao

Abstract read
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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2citing papers in PubMed
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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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2 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

ShuLin Zhu *School of Nursing, Xinxiang Medical University, No. 601, JinSui Street, Xinxiang, 453003, Henan, China.
WeiYe Yang *School of Nursing, Xinxiang Medical University, No. 601, JinSui Street, Xinxiang, 453003, Henan, China.
AnNa MaSchool of Nursing, Xinxiang Medical University, No. 601, JinSui Street, Xinxiang, 453003, Henan, China.
LiNa WangSchool of Nursing, Xinxiang Medical University, No. 601, JinSui Street, Xinxiang, 453003, Henan, China.
Tong ZhaoDepartment of Psychiatry, Quzhou Third Municipal Hospital, Quzhou, China.
XiaoLei GaoSchool of Nursing, Xinxiang Medical University, No. 601, JinSui Street, Xinxiang, 453003, Henan, China. Gaoxiaolei0926@163.com.

Funding

Henan province humanities and social sciences research project 2024-ZZJH-300Natural Science Foundation of Henan province 242300420113Xinxiang Medical University Doctor Startup Fund 505431
6 · The paper itself

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.

Indexed as

Cardiovascular DiseasesSocial ParticipationAgedChinaCross-Sectional StudiesFemaleHealth StatusHumansLatent Class AnalysisLongitudinal StudiesMaleMiddle AgedCardiovascular diseaseHealth statusLatent profile analysisMiddle-aged and older adultsSocial participation

Identifiers

PMID40653571
PMCPMC12256607

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