PURPOSE: The study was done to compare quality of life by gender, and to identify factors which explain quality of life in individuals with coronary artery disease. METHODS: For the survey, 91 individuals (53 men and 38 women) agreed to participate in the study. Cardiovascular risk factors, systolic blood pressure, body mass index, total cholesterol, triglyceride, high density lipoprotein-cholesterol, and low density lipoprotein-cholesterol, health behavior as well as quality of life, were measured. Descriptive statistics, t-test, correlation and hierarchical multiple regression with SPSS WIN 12.0 were used to analyze the data. RESULTS: Significant gender differences were found for education, smoking status, chronic disease, perceived health status, and quality of life within sub-dimensions. Hierarchical regression analysis showed gender (men), age, perceived health status, cardiovascular risk scores, and health behaviors together explained 40.2% (adjusted R2) of variance in quality of life. CONCLUSION: As the factors explaining quality of life in individuals with coronary artery disease have been identified as gender (men), age, perceived health status, and health behaviors, health promotion programs designed for this population should focus on these factors for effective behavioral modification, and consequent improvement in quality of life.
PURPOSE: The study was done to compare quality of life by gender, and to identify factors which explain quality of life in individuals with coronary artery disease. METHODS: For the survey, 91 individuals (53 men and 38 women) agreed to participate in the study. Cardiovascular risk factors, systolic blood pressure, body mass index, total cholesterol, triglyceride, high density lipoprotein-cholesterol, and low density lipoprotein-cholesterol, health behavior as well as quality of life, were measured. Descriptive statistics, t-test, correlation and hierarchical multiple regression with SPSS WIN 12.0 were used to analyze the data. RESULTS: Significant gender differences were found for education, smoking status, chronic disease, perceived health status, and quality of life within sub-dimensions. Hierarchical regression analysis showed gender (men), age, perceived health status, cardiovascular risk scores, and health behaviors together explained 40.2% (adjusted R2) of variance in quality of life. CONCLUSION: As the factors explaining quality of life in individuals with coronary artery disease have been identified as gender (men), age, perceived health status, and health behaviors, health promotion programs designed for this population should focus on these factors for effective behavioral modification, and consequent improvement in quality of life.