비만도 평가 지표를 이용한 심혈관 질환 평가의 진단적 정확도

Abstract

The goal of this study was to investigate diagnostic accuracy of cadiovascular disease prediction using noninvasive methods such as WHR, % body fat, BMI for Korean middle-aged men and suggested a obesity-related cut off point. A total of 176 korean middle-aged men were recruited and separated into two groups; 102 men that had been diagnosed by doctors to have cardiovascular disease and 74 men who were healthy. Data of the men`s height, weight, % body fat, BMI, WHR, total cholesterol, blood sugar, and triglyceride. discriminant analysis and Receiver Operation Characteristic (ROC) curve analysis were measured. The significance level was set at .05. Five significant predictor variables were identified in six risk factors of cardiovascular disease: WHR, % body fat, blood sugar, BMI and triglyceride. The predictability was 25.7 % (R2=.257). Overall, 73.3% of the original grouped cases were correctly classified, and 71.6% of the cross-validated grouped cases were classified correctly. Three factors (WHR, % body fat, BMI) were identified as significant predictors in non-invasive collection variables. The predictability was 21.8 % (R2=.218). The original grouped cases were correctly classified, and 72.2% of the cross-validated grouped cases were classified correctly. The ROC curve analysis was used to determine the cut point of WHR, % body fat and BMI. It was found that a patient had high risk factors of cardiovascular disease when they exceed the cut point of WHR=.89, % body fat=20.2, and BMI=25.7. The results showed that examining three variables (WHR, % body fat, and BMI) could equally predict cardiovascular disease of korean middle-aged men, compared to examining all the risk factors. Obesity-related cut off points from ROC curve analysis might be used in diagnosing a cardiovascular disease.