Objective: The prognosis of coronary artery disease (CAD) is related to its severity and cardiovascular risk factors in both sexes. In women, social isolation, marital stress, sedentary lifestyle and depression predicted CAD progression and outcome within 3 to 5 years. We hypothesised that these behavioral factors would still be associated with all-cause mortality in female patients after 26 years.
Methods: We examined 292 patients with CAD and 300 healthy controls (mean age of 56 ± 7 y) within the Fem-Cor-Risk-Study at baseline. Their cardiac, behavioral, and psychosocial risk profiles, exercise, smoking, and dietary habits were assessed using standardized procedures. Physiological characteristics included a full lipid profile, the coagulation cascade and autonomic dysfunction (heart rate variability, HRV). A new exploratory analysis using machine-learning algorithms compared the effects of social and behavioral mechanisms with standard risk factors. Results: All-cause mortality records were completed in 286 (97.9%) patients and 299 (99.7%) healthy women. During a median follow-up of 26 years, 158 (55.2%) patients and 101 (33.9%) matched healthy controls died. The annualized mortality rate was 2.1% and 1.3%, respectively. After controlling for all available confounders, behavioral predictors of survival in patients were social integration (HR 0.99, 95% CI 0.99-1.0) and physical activity (HR 0.54, 95% CI 0.37-0.79). Smoking acted as a predictor of all-cause mortality (HR 1.56, 95% CI 1.03-2.36). Among healthy women, moderate physical activity (HR 0.42, 95% CI 0.24-0.74) and complete HRV recordings (≥50%) were found to be significant predictors of survival.
Conclusions: CAD patients with adequate social integration, who do not smoke and are physically active, have a favorable long-term prognosis. The exact survival times confirm that behavioral risk factors are associated with all-cause mortality in female CAD patients and healthy controls.
Copyright: © 2022 Deter et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.