Application of Decision Analysis Techniques' in Huge Health-checkup Database to Explore the High-risk Group With Metabolic Syndrome

According to the American Heart Association（AHA）modified Adult Treatment Panel III（ATP-III） and the criteria of Health Promotion Administration, Taiwan. Five indices are used to define metabolic syndrome（MetS): including waist circumference （WC), high blood pressure（H/P）, fasting plasma glucose（FPG）, triglyceride（TG）, and high-density lipoprotein-cholesterol（HDL-C）. The recent researches showed us, there was no research applying the five criteria into their decision model. This study proposal will be the first study which evaluated the importance of the criteria related to apply these indices and decision model into the clinic for risk factors assessment.

This study was divided into 2 stages: (1) to analyze the big database of health examination to find out the major decision-making analysis module of MetS, including the level of importance and decision-making weight of 5 indicators, which can be provided as reference for suggestions on clinical medical treatments or health education focuses of health management of sub-health population; (2) to analyze other demographic variables of the database (educational background, residence, occupation, etc.) and the variables affecting health patterns (including smoking, drinking, long-term sitting work pattern) to find out the important variables affecting high risk group for MetS among populations of all ages, in order to investigate the improvement strategies for early prevention or intervention of important variables. As aging society is coming, it is estimated that the elderly people over the age of 65 in Taiwan will reach 20% by 2025. According to the estimation of Executive Yuan, the growth rate of healthcare service industry will reach at least 17%, and the annual output value will reach USD 18 billion. Therefore, this study intends to develop strategies for preventing chronic illness in the middle-aged and elderly people and find out the characteristic variables of high risk group according to different age groups to further reduce the incidence of MetS or CVD.