Cargando…
Canonical Correlation between Behavioral-Psychological Variables and Predictors of Coronary Artery Disease Prognosis
Metabolic syndrome (MetS) and severity of coronary artery disease (CAD) are considered predictors of CAD prognosis. Unhealthy lifestyles and type-D personality are associated with MetS and are potential causes of primary and secondary CAD. In this cross-sectional descriptive study, we aimed to inves...
Autores principales: | , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7084809/ https://www.ncbi.nlm.nih.gov/pubmed/32131511 http://dx.doi.org/10.3390/ijerph17051608 |
Sumario: | Metabolic syndrome (MetS) and severity of coronary artery disease (CAD) are considered predictors of CAD prognosis. Unhealthy lifestyles and type-D personality are associated with MetS and are potential causes of primary and secondary CAD. In this cross-sectional descriptive study, we aimed to investigate the relationship between behavioral-psychological variables and predictors of CAD prognosis. The behavioral-psychological variable set contained six lifestyle categories and two type-D personality categories. Descriptive analyses, t-tests, analysis of variance, Pearson’s correlation, and canonical correlation were used. The behavioral-psychological variable set was related to the predictor set for CAD prognosis, with a significant canonical variate of 0.67 (45% overlapping variance). Significant pairs of canonical variates indicated that poor physical activity and weight control (−0.77), poor dietary habits (−0.78), alcohol consumption and cigarette smoking (−0.37), lack of sleep and rest (−0.40), stress (−0.64) in the lifestyle set, higher negative affectivity (0.52), and social inhibition (0.71) in the type-D personality set were associated with a high MetS score (0.59) and severity of CAD (0.91). A combination of behavioral and psychological variables was found to be important in predicting the prognosis of CAD; therefore, interventions aimed at preventing combinations of these variables may be effective in improving CAD prognosis. |
---|