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

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.


Background
Sasang constitutional medicine (SCM) is a Korean traditional medicine system that originated in 1894. SCM classifies human beings into four defined types, called Sasang constitutional (SC) types. Based on individual phenotypic characteristics such as body shape, personality, voice, and visceral organ functions [1], the four types, Tae-yang (TY), Tae-eum (TE), So-yang (SY), and So-eum (SE), were classified with different disease susceptibilities and treatment responses [1,2]. Considering these specific susceptibilities of the SC types, different treatments for patients with the same disease are implemented. Previous studies related to the risk prediction model with the SC types have reported that the SC type was a strong indicator for type 2 diabetes [3] and cardiovascular diseases [4]. Recent studies have provided scientific evidence to prove vulnerable organs and related diseases for each SC type. According to the theory of classifying SC types, vulnerable hypoactive organs and the corresponding susceptible diseases were specified [1,2,5], confirmed with a recent systematic review with 15 studies [6].
For example, individuals with the TE type are considered to be vulnerable to lung-related diseases [1,2,5]. Additionally, individuals with the SY type have been known to have kidney as a vulnerable organ and have a greater risk of susceptible diseases such as urinary or renal diseases [1,2]. Further, individuals with the SE type have been considered to have pancreas as a hypoactive organ and have an increased risk of gastrointestinal diseases [5].
Metabolic syndrome is diagnosed when at least three of the five following components are present: abdominal obesity, high blood pressure, decreased high density lipoprotein (HDL) cholesterol level, elevated triglyceride level, and impaired glucose tolerance [7]. Metabolic syndrome has been reported to increase the risk of developing type 2 diabetes, cardiovascular diseases, and all-cause mortality [8]. According to the National Health and Nutrition Examination Survey (NHANES) 2003-2012, the prevalence of metabolic syndrome was 35% for all adults and 50% for adults over 60 years of age [9]. Further assessing the prevalence by the SC type, individuals with the TE (Odds Ratio [OR] =4.52, 95% Confidence Intervals [CIs] 3.36, 6.07) and the SY (OR =2.00, 95% CI 1.47, 2.74) types illustrated a higher risk for metabolic syndrome than those with the SE type. The prevalence rates of metabolic syndrome for the TE, SY, and SE types were 48.85%, 30.59%, and 18.02%, respectively [10].
However, studies have not investigated whether using the SC type classification, based on body configuration, organ functions, or personality would increase the accuracy of risk prediction for metabolic syndrome. Therefore,

Study population
An ongoing prospective cohort study, the Korean Genome Epidemiology Study (KoGES), was initiated in 2001. Detailed information on the study design and procedure has been previously reported [11]. At enrollment, the initial cohort of 10,030 participants, 40 to 69 years of age, was randomly recruited from two study sites, with 5012 participants from the urban community of Ansan (2518 men and 2494 women) and 5018 participants from the rural community of Ansung (2240 men and 2778 women). The participants were randomly selected from the general population by telephone, mail, and door-to-door visits. These participants have been biennially followed up. The participants underwent comprehensive tests, when visiting a research site, including physical examinations, biochemical and clinical examinations, and interviewer-administrated questionnaires. All participants provided written informed consent, and the study protocol was approved by the Human Subjects Review Committee at Korea University Ansan Hospital and Ajou University School of Medicine. The SC type for each participant was identified from 2009 to 2012. Of 6878 eligible participants, 5840 were successfully classified by the SC type. Considering the SC type as a unique individual trait, we estimated the risk of developing a newly diagnosed metabolic syndrome according to the SC types for approximately 14 years from 2001 to 2014. At baseline, of 5840 participants who were classified into an SC type, we excluded 1860 adults who already had metabolic syndrome. Fifty-nine individuals were further excluded when diagnosed with an established cardiovascular disease. Additionally, fifty-six individuals were excluded due to missing data from any of covariates at the baseline examination (age; n = 1, sex; n = 1, body mass index (BMI); n = 1, education; n = 27, and glucose n = 26). Additionally, 336 participants were excluded for missing one or more follow-up examinations over the 14 years of the study. Therefore, 3529 participants (1769 men and 1760 women) were involved in the final analyses.

Classification of Sasang constitutional types
A new diagnostic model was used to identify the subjects' SC types. Detailed information on this new diagnostic model has been previously reported [12]. Briefly, this is based on a probability model using multivariable logistic regression with individual data on facial image, body shape, voice features, and questionnaire results. Specifically, facial images obtained with a digital camera were processed to extract the variables of facial characteristics. Eight circumference measurements, at the forehead, neck, axilla, chest, ribs, waist, pelvis, and hips, were measured to process the variables of body shape. The variables of voice features were processed with the Hidden Markov Model Toolkit (Cambridge University Engineering Department, Cambridge, United Kingdom) and the Praat voice analysis program (University of Amsterdam, Amsterdam, Netherlands). The questionnaire consisted of 67 multiple-choice questions about general temperament, eating habits, and physiological symptoms, and was processed for the variables of personality characteristics and Fig. 1 Estimated risk of the incident metabolic syndrome (n = 3529). The risk was adjusted for age, sex, BMI, education, income, smoking, drinking, and physical activity physiological symptoms. Since no participants were classified into the TY type, the SC types in this study involved just three types, TE, SE, and SY.

Definition of metabolic syndrome
Metabolic syndrome was defined according to the criteria of the National Cholesterol Education Program Adult Treatment Panel III [13]. Participants were identified with newly diagnosed metabolic syndrome if they had at least three out of the five following components: abdominal obesity (waist circumference for Asia-Pacific adults ≥90 cm for men and ≥80 cm for women) [14], elevated triglycerides (triglyceride ≥150 mg/dl), low HDL cholesterol (<40 mg/dl for men and <50 mg/dl for women), high blood pressure (systolic/diastolic pressure ≥ 130/85 mmHg or treatment with antihypertensive drugs), and elevated fasting blood glucose (≥110 mg/dl or treatment with anti-diabetic drug).

Other measurements
Following a standardized protocol, professionally trained interviewers and health professionals help all

Results
General characteristics of the study participants  (Fig. 1). The risk of developing metabolic syndrome was the highest among individuals with the TE type, followed by the SY type and the SE type.
Comparison of the risk prediction models for incident metabolic syndrome according to the Sasang constitutional types Table 2 presents four prediction models to compare the accuracy of the prediction risk for developing metabolic syndrome, and Fig. 2

Discussion
In a 14-year longitudinal study among 3529 individuals, we found that utilizing the SC types of the participants significantly increased the accuracy of the risk prediction for incident metabolic syndrome. Particularly, an increase in the accuracy of the risk prediction using the SC types was observed in a model that already had traditional risk factors and sub-components of metabolic syndrome.
It is important to predict the risk of developing metabolic syndrome in order to prevent cardiometabolic disorders, because metabolic syndrome has been known to increase the risk of type 2 diabetes and cardiovascular diseases [8]. A previous study demonstrated that the SC type was a significant risk factor for metabolic syndrome [15,16]. Additionally, individuals of the TE type have an increased risk for metabolic syndrome as the number of components of metabolic syndrome increased [16]. Consistent with previous studies [10,15,16], our finding demonstrated that the TE type was the most prevalent, accounting for 45.03% of participants, and was associated with a greater risk of developing metabolic syndrome than the other types (OR = 2.03, 95% CI 1.63, 2.54). Individuals with the TE type, who have been known to have a greater predisposition to metabolic syndrome, are characterized with larger waist circumferences and higher frequencies of smoking and heavy drinking [1], as confirmed in our findings. In contrast, individuals with the SE type indicated a reduced risk of developing metabolic syndrome than the other types [10]. With more than 100 years of accumulated experience and empirical methods, the SC types of a traditional Korean medicine, initiated by Jema Lee (1837Lee ( -1900, specifies individual's physical features including facial color and shape, voice, personality, behavioral tendency, and other characteristics [1]. Thus, the SC types have allowed a distinct advantage in identifying disease susceptibilities. For example, individuals with the same disease would have a different prognosis and treatment, depending on each patient's SC type.
The underlying mechanism on how the SC types increase the accuracy of the risk prediction for incident metabolic syndrome in a general population has not been clearly explained. However, recent evidence has been accumulated on susceptible organs and vulnerable diseases according to the SC types including the recent systematic review [6]. Future studies are warranted to examine the phenotypic characteristics of each SC type.
This study has strengths and a limitation. First, the study participants were randomly selected from a general population through telephone contacts, mails, and door-to-door visits. The general population has no particular characteristics, so that the results might be applicable to others. Additionally, this study was based on a 14-year longitudinal cohort study that allows us to assess causal relationship. However, this study has a limitation to consider when interpreting our results. A sub-study of the SC types was initiated from the fifth wave (year 2009/2010). Thus, the study participants of the SC type were only based on the number of the participants who visited at the fifth and six waves.

Conclusions
In conclusion, in a 14-year longitudinal prospective cohort study among 3529 individuals (1769 men and 1760 women), we observed that utilizing the SC types significantly contributed to increasing the accuracy of predicting the risk of developing metabolic syndrome, though the increment was small. Based on our observation that SC type played a significant role in predicting the risk, the SC types may need to be included into a risk prediction model for metabolic syndrome.