Abstract
The purpose of this study was evaluate the usefulness of variables which were known to be related to blood pressure for discriminating between hypertensive and normotensive groups. Variables able such as smoking, alcohol, exercise, and stress, and demographic variables such as age, economical status, and education. The data were collected from 400 male clients who visited one university hospital located in Incheon, Republic of Korea, from May 1996 to December 1996 for a regular physical examination. Variables which showed significance for discriminating systolic blood pressure in this study were age, serum lipids, education, HDL, exercise, total smoking(in order of significance). By using the combination of these variables, the possibility of proper prediction for a high-systolic pressure group was 2%, predicting a normal-systolic pressure group was 70.3%, and total Hit Ratio was 70%. Variables which showed significance for discriminating diastolic blood pressure were exercise, triglyceride, alcohol, smoking, economical status, age and BMI(in order of significance). By using the combination of these variables, the possibility of proper prediction for a high-diastolic pressure group was 71.2%, predicting a normal-diastolic pressure group was 71.3%, and total Hit Ratio was 71.3%. Multiple regression analysis was performed to examine the association of systolic blood pressure with life style-related variables after adjustment for obesity, serum lipids, and demographic variables. First, the effect of demographic variable alone on the systolic blood pressure was statistically significant(p=.000) and adjusted R2 was 0.09. Adding the variable obesity on demographic variables resulted in raising adjusted R2 to 0.11(p=.000) ; therefore, the contribution rate of obesity on the systolic blood pressure was 2.0%. On the next step, adding the variable serum lipids on the obesity and demographic variables resulted in raising adjusted R2 to 0.12(p=.000) : therefore, the contribution rate of serum lipid on the systolic pressure was 1.0%. Finally, adding life style-related variables on all other variables resulted in raising the adjusted R2 to 0.18(p=.000) ; therefore, the contribution rate of life style-related variables on the systolic blood pressure after adjustment for obesity, serum lipids, and demographic variables was 6.0%. Multiple regression analysis was also performed to examine the association of diastolic blood pressure with life style-related variables after adjustment for obesity, serum lipids, and demographic variables. First, the effect of demographic variable alone on the diastolic blood pressure was statistically significant(p=.01) and adjusted R2 was 0.03. Adding the variable obesity on demographic variables resulted in raising adjusted R2 to 0.06(P=.000) ; therefore, the contribution rate of obesity on the diastolic blood pressure was 3.0%. On the next step, adding the variable serum lipids on the obesity and demographic variables resulted in raising the adjusted R2 to 0.09(p=.000) ; therefore, the contribution rate of serum lipid on the diastolic pressure was 3.0%. Finally, adding life style-related variables on all other variables resulted in raising the adjusted R2 to 0.12(p=.000) ; therefore, the contribution rate of life style-related variables on the systolic blood pressure after adjustment for obesity, serum lipids, and demographic variables was 3.0%.