Purpose This study aims to confirm the influence of type D personality and health literacy on resilience of patients hospitalized for Cardiovascular Diseases (CVDs), and provide basic information for improving resilience as a post-discharge strategy to promote self-care among patients with chronic diseases.
Methods A questionnaire-based survey was carried out in this cross-sectional study. The subjects were 142 patients who were being treated at a tertiary general hospital for CVDs such as coronary artery disease, arrhythmia, and heart failure. Data were collected from July to October 2022 using a structured questionnaire, and then analyzed using the SPSS program version 26.0.
Results 75.3% of the study subjects (n=107) had type D personalities, and the average health literacy and resilience scores were 48.96±9.13 points and 68.27±13.02 points, respectively, indicating relatively low grades. Following a hierarchical regression analysis, low monthly income (β=-.62, p<.001), current smokers (β=-.23, p=.010), patients with type D personality (β=-.24, p=.001), and patients with low health literacy (β=.27, p<.001) were identified as significant predictors of resilience (Adjusted R2=.57, F=14.32, p<.001).
Conclusion In order to increase the resilience of patients hospitalized for CVD, it is necessary to identify and take into account smokers with low socioeconomic status, poor health literacy, and type D personality. We advise doing a follow-up study to ascertain if the resilience of patients hospitalized for CVD influences post-discharge self-care and clinical outcomes.
Purpose This study aimed to identify socioeconomic clusters of older adults and compare cardiovascular health among the identified clusters.
Methods: A secondary analysis was performed using the data from 3,303 older adults (over 65 years of age; 56.5% women) who participated in the Korean National Health and Nutrition Examination Survey (2016~2017). A two-step cluster analysis was used to identify older adults’ socioeconomic clusters based on 11 factors associated with Socioeconomic Status (SES). Differences in the cardiovascular health outcomes among the identified clusters were analyzed using the x2 test and one-way ANOVA. Results: A three-cluster solution was selected (p<.001) composed of low (n=715), middle (n=1,425), and high-SES clusters (n=1,163). The three clusters differed significantly in the prevalence of diabetes (p<.010), hypertension (p<.001), and metabolic syndrome (p<.001), with greater prevalence in the lower SES clusters. Similarly, systolic blood pressure (p<.001), body mass index (p<.010), and total cholesterol (p<.010) differed significantly among the clusters in the same pattern.
Conclusion: Older adults of lower SES clusters should be a crucial target group for health promotion interventions aimed at the prevention and management of cardiovascular disease risk factors. Tailored interventions can be developed by understanding intersecting SES risk factors in this group.
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