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

Abstract 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.
PMID
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Authors

Mayor MeshTerms
Keywords

Metabolic syndrome

Prediction

Sasang constitutional types

Journal Title bmc complementary and alternative medicine
Publication Year Start




PMID- 28865470
OWN - NLM
STAT- MEDLINE
DA  - 20170903
DCOM- 20170908
LR  - 20170908
IS  - 1472-6882 (Electronic)
IS  - 1472-6882 (Linking)
VI  - 17
IP  - 1
DP  - 2017 Sep 02
TI  - Sasang constitutional types for the risk prediction of metabolic syndrome: a
      14-year longitudinal prospective cohort study.
PG  - 438
LID - 10.1186/s12906-017-1936-4 [doi]
AB  - 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.
FAU - Lee, Sunghee
AU  - Lee S
AD  - Department of Food and Nutrition, College of Health Science, Kangwon National
      University, Chuncheon, Gangwon, Republic of Korea.
FAU - Lee, Seung Ku
AU  - Lee SK
AD  - Institute of Human Genomic Study, College of Medicine, Korea University Ansan
      Hospital, Ansan, Republic of Korea.
FAU - Kim, Jong Yeol
AU  - Kim JY
AD  - Medical Research Division, Korea Institute of Oriental Medicine, Yuseong-gu,
      Republic of Korea.
FAU - Cho, Namhan
AU  - Cho N
AD  - Department of Preventive Medicine, Ajou University School of Medicine, Suwon,
      Republic of Korea.
FAU - Shin, Chol
AU  - Shin C
AD  - Institute of Human Genomic Study, College of Medicine, Korea University Ansan
      Hospital, Ansan, Republic of Korea. [email protected]
AD  - Department of Pulmonary, Sleep and Critical Care Medicine, Department of Internal
      Medicine, Korea University Ansan Hospital, Ansan, Republic of Korea.
      [email protected]
AD  - Institute of Human Genomic Study, Department of Internal Medicine, Ansan Hospital
      Korea University, 516 Gojan-1-dong, Danwon-gu, Ansan-si, Gyeonggi-do, 425-707,
      South Korea. [email protected]
LA  - eng
PT  - Journal Article
DEP - 20170902
PL  - England
TA  - BMC Complement Altern Med
JT  - BMC complementary and alternative medicine
JID - 101088661
RN  - 0 (Blood Glucose)
RN  - 0 (Lipoproteins, HDL)
SB  - IM
MH  - Adult
MH  - Aged
MH  - Blood Glucose/metabolism
MH  - Body Mass Index
MH  - Female
MH  - Humans
MH  - Lipoproteins, HDL/metabolism
MH  - Longitudinal Studies
MH  - Male
MH  - Metabolic Syndrome X/*diagnosis/metabolism/physiopathology
MH  - Middle Aged
MH  - Prospective Studies
MH  - Risk Factors
MH  - Waist Circumference
PMC - PMC5581468
OTO - NOTNLM
OT  - Metabolic syndrome
OT  - Prediction
OT  - Sasang constitutional types
EDAT- 2017/09/04 06:00
MHDA- 2017/09/09 06:00
CRDT- 2017/09/04 06:00
PHST- 2017/01/09 [received]
PHST- 2017/08/18 [accepted]
AID - 10.1186/s12906-017-1936-4 [doi]
AID - 10.1186/s12906-017-1936-4 [pii]
PST - epublish
SO  - BMC Complement Altern Med. 2017 Sep 2;17(1):438. doi: 10.1186/s12906-017-1936-4.