Why the study?
Health-promoting behaviors improve outcomes after aortic dissection surgery, but research on their trajectory among Chinese aortic dissection patients has been limited.
Patients recovering from aortic dissection surgery exhibit three distinct trajectories of health-promoting behaviors, highlighting the need for tailored interventions based on age, education, and comorbidity profiles.
Three trajectories of health-promoting behavior identified post-aortic dissection; leaves open whether targeted interventions improve outcomes.
Background Health-promoting behavior are important in improving health outcome indicators for patients after aortic dissection surgery. However, there has been limited research on the trajectory of health-promoting behavior among Chinese aortic dissection patients. Aims To explore the trajectory of health-promoting behavior in patients after aortic dissection surgery and identify influencing factors. Methods This prospective longitudinal study included patients who underwent aortic dissection at the cardiovascular surgery of Xiamen Hospital from August to December 2024. Patients with aortic dissection were evaluated at discharge (T0), 1 month (T1), 3 months (T2), and 6 months (T3) after the operation. Using the health-promoting behavior scale evaluated health-promoting behavior. Growth mixture model (GMM) analysis was used to identify heterogeneous health-promoting behavior subgroups in the four observation periods. Univariate and logistic regression analyses were used to identify factors affecting health-promoting behavior classification and independent risk factors. Results We identified three health-promoting behavior trajectories among aortic dissection patients: low-stability group (33.80%), medium-volatility group (43.20%) and high-increasing group trajectory groups (23%). Compared to the low-stability group, logistic regression analysis indicates that in the medium-volatility group, age (OR = 0.950, 95%CI: 0.925–0.975, p < 0.001) and having a history of hypertension (OR = 1.941, 95%CI: 1.049–3.590, p = 0.035) were significant influencing factors. The comparative Logistic regression analysis results between the high-increasing group and the low-stability group showed that age (OR = 0.923, 95%CI: 0.892–0.954, p < 0.001), educational level (OR = 2.507, 95%CI: 1.503–4.182, p < 0.001) and a history of hypertension (OR = 6.613, 95%CI: 3.056–14.313, p < 0.001) were both significant influencing factors. Conclusion We identified three health-promoting behavior trajectories, highlighting a significant heterogeneity in health-promoting behavior development. Understanding the characteristics of these developmental trajectories is crucial for realizing the dynamics of different health-promoting behavior subgroups and informing effective interventions.
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He et al. (2026) studied this question.
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