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http://hdl.handle.net/10397/116845
| Title: | Identification of proactive health behavior clusters in atrial fibrillation-related ischemic stroke patients : a multi-center latent class analysis | Authors: | Guo, L Guo, Y Montayre, J Ning, W Namassevayam, G Zhang, M Xie, Y Zhou, X Zhao, P Wang, J Di, R |
Issue Date: | 2025 | Source: | Vascular health and risk management, 2025, v. 21, p. 749-758 | Abstract: | Objective: This study aims to identify latent classes of proactive health behavior and to explore the predictive factors associated with various clusters of proactive health behavior among patients with atrial fibrillation-related ischemic stroke. Methods: A multi-center cross-sectional study was conducted, recruiting a total of 1,250 participants through cluster random sampling from January 2023 to May 2024. Latent class analysis was performed to identify classes of proactive health behavior within the sample of atrial fibrillation-related ischemic stroke patients. Additionally, multinomial regression analyses were utilized to investigate the predictive factors associated with the different latent classes identified. This study adhered to the STROBE checklist. Results: Out of the 1,250 participants, 1,196 (91.6%) completed the survey, including 809 males and 387 females, with 71% of them reporting moderate or lower levels of proactive health behavior. The findings revealed three latent classes: (1) low proactive health behavior with health responsibility deficiency (n=426, 35.6%); (2) moderate proactive health behavior with stress and coping disorder (n=464, 38.7%); and (3) high proactive health behavior with light physical activity (n=306, 25.5%). Factors correlated with the latent classes of proactive health behavior were identified. Protective factors included a high level of stroke knowledge, strong awareness of health beliefs, and better environmental and social support (all p < 0.05). Conversely, risk factors for the latent classes of proactive health behavior included low education, being unmarried, lack of thrombolysis, and low household income (all p < 0.05). Conclusion: This study successfully identified three different latent classes of proactive health behaviors and their related predictors in Chinese atrial fibrillation-related ischemic stroke patients. These findings provide theoretical guidance and practical insights for the development of targeted intervention programs aimed at improving proactive health behaviors in patients with atrial fibrillation-related ischemic stroke patients. |
Keywords: | Atrial fibrillation Ischemic stroke Latent class analysis Multi-center study Proactive health behavior |
Publisher: | Dove Medical Press Ltd. | Journal: | Vascular health and risk management | ISSN: | 1176-6344 | EISSN: | 1178-2048 | DOI: | 10.2147/VHRM.S534357 | Rights: | © 2025 Guo et al. This work is published and licensed by Dove Medical Press Limited. The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution – Non Commercial (unported, v4.0) License (http://creativecommons.org/licenses/by-nc/4.0/). By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. For permission for commercial use of this work, please see paragraphs 4.2 and 5 of our Terms (https://www.dovepress.com/terms.php). The following publication Guo L, Guo Y, Montayre J, Ning W, Namassevayam G, Zhang M, Xie Y, Zhou X, Zhao P, Wang J, Di R. Identification of Proactive Health Behavior Clusters in Atrial Fibrillation-Related Ischemic Stroke Patients: A Multi-Center Latent Class Analysis. Vasc Health Risk Manag. 2025;21:749-758 is available at https://doi.org/10.2147/VHRM.S534357. |
| Appears in Collections: | Journal/Magazine Article |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| Guo_Identification_Proactive_Health.pdf | 1.51 MB | Adobe PDF | View/Open |
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