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Korean Journal of Epidemiology 2006;28(2): 138-151.
Risk Factors of Impaired Fasting Glucose and Type 2 Diabetes Mellitus: Using Datamining.
Jongseon Ryu, Soonduck Kim, Jongsoon Park, Jesuk Lee
1Spondylous Center, Sun General Hospital, Korea.
2Department of Preventive Medicine, College of Medicine,Korea University, Korea. kimsd@korea.ac.kr
3Department of Public Health Graduate School, KoreaUniversity, Korea.
Abstract
PURPOSE:
This study aimed to contribute to overall public health by examining the prevalence rates of impaired fasting blood glucose and type 2 diabetes mellitus and developing a model to predict high risk factors for impaired fasting blood glucose and type 2 diabetes mellitus.
METHODS:
The 1998 Public Health Nutrition Survey data was used for this study. Subjects were 7,702 adult at the age of 20 or over. The frequency analysis, chisquared test was performed. A decision tree was utilized to define a model designed to predict high risk factors for impaired fasting glucose and type 2 diabetes mellitus.
RESULTS:
The prevalence rates of impaired fasting blood glucose was 10.8% and prevalence rates of type 2 diabetes mellitus was 9.4%. The decision tree analysis exhibited that age was strong factors for impaired fasting blood glucose. HDL cholesterol and kind of economic activities were high risk factors for impaired fasting blood glucose and type 2 diabetes mellitus on those in 20s. BMI, total cholesterol level, marriage status, sex for impaired fasting blood glucose and type 2 diabetes mellitus on those in 30s. The total cholesterol level, drinking and waist size were identified as risk factors on those in 40s. BMI, education level and hypertension seemed to have an impact on those in 50s. The waist size, sex and income had an impact on those in 60s.
CONCLUSIONS:
This study underscores the need for the public health infrastructure to improve various health promotion programs for those who have risk factors for impaired fasting blood glucose and type 2 diabetes mellius. The implementation of effective nutrition, workout and anti-drinking programs will boost public health.
Keywords: Impaired Fasting blood glucose; Type 2 diabetes mellitus; Data-mining; Decision tree


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