Sasang constitutional types for the risk prediction of metabolic syndrome: a 14-year longitudinal prospective cohort study.

Lee, Sunghee; Lee, Seung; Kim, Jong; Cho, Namhan; Shin, Chol

Background: To examine whether the use of Sasang constitutional (SC) types, such as Tae-yang (TY), Tae-eum (TE), So-yang (SY), and So-eum (SE) types, increases the accuracy of risk prediction for metabolic syndrome. Methods: From 2001 to 2014, 3529 individuals aged 40 to 69 years participated in a longitudinal prospective cohort. The Cox proportional hazard model was utilized to predict the risk of developing metabolic syndrome. Results: During the 14 year follow-up, 1591 incident events of metabolic syndrome were observed. Individuals with TE type had higher body mass indexes and waist circumferences than individuals with SY and SE types. The risk of developing metabolic syndrome was the highest among individuals with the TE type, followed by the SY type and the SE type. When the prediction risk models for incident metabolic syndrome were compared, the area under the curve for the model using SC types was significantly increased to 0.8173. Significant predictors for incident metabolic syndrome were different according to the SC types. For individuals with the TE type, the significant predictors were age, sex, body mass index (BMI), education, smoking, drinking, fasting glucose level, high-density lipoprotein (HDL) cholesterol level, systolic and diastolic blood pressure, and triglyceride level. For Individuals with the SE type, the predictors were sex, smoking, fasting glucose, HDL cholesterol level, systolic and diastolic blood pressure, and triglyceride level, while the predictors in individuals with the SY type were age, sex, BMI, smoking, drinking, total cholesterol level, fasting glucose level, HDL cholesterol level, systolic and diastolic blood pressure, and triglyceride level. Conclusions: In this prospective cohort study among 3529 individuals, we observed that utilizing the SC types significantly increased the accuracy of the risk prediction for the development of metabolic syndrome.

SOUTH Korea; AGE distribution; BLOOD pressure; BLOOD sugar; CHOLESTEROL; ALCOHOL drinking; LIPIDS; ASIAN medicine; RISK assessment; SEX distribution; SMOKING; METABOLIC syndrome; BODY mass index; RECEIVER operating characteristic curves; STATISTICAL models

BMC Complementary & Alternative Medicine, 2017, Vol 17, Issue 1, p1

1472-6882

Academic Journal

10.1186/s12906-017-1936-4