Sasang constitutional medicine (SCM) is a unique traditional Korean therapeutic alternative form of medicine. Based on the Yin and Yang theory and on Confucianism, humans are classified into four constitutions. These differ in terms of (i) sensitivity to certain groups of herbs and medicines, (ii) equilibrium among internal organic functions, (iii) physical features and (iv) psychological characteristics. We propose that two main axes in the physiopathology of SCM (food intake/waste discharge and consuming/storing Qi and body fluids) are equivalent to the process of internal–external exchange and catabolism/anabolism in modern physiology, respectively. We then used this hypothesis to discuss the physiological and pathological principles of SCM. Constitution-based medicine is based on the theory that some medicinal herbs and remedies are only appropriate for certain constitutions and can cause adverse effects in others. The constitutional approach of SCM share the same vision as tailored medicine; an individualized therapy that can minimize the risk of adverse reaction while increasing the efficacy and an individualized self-regulation that can help prevent specific susceptible chronic disease and live healthily. There is still a long way to this goal for both SCM and tailored medicine, but we may benefit from systems approaches such as systems biology. We suggest that constitutional perspective of SCM and our hypothesis of two main processes may provide a novel insight for further studies.

Facial characteristics may provide reliable information giving an insight into the inner nature of an individual. This study examines the differences in widely used facial metrics, including cheek-to-jaw width ratio (CJWR), width-to-height ratio (WHR), perimeter-to-area ratio (PAR), and facial masculinity indexes across Sasang constitutional types, to investigate the association between these facial cues and body mass index (BMI) and develop a predictive model for Sasang typing. 2D images of 911 participants were analyzed. The results indicated that TaeEum (TE) type generally has a squarer face, with the male TE type having a squarer and wider face than that of both SoYang (SY) and SoEum (SE) types. Male TE type has longer eyes than that of the SE type, and the lower face of the female TE type is longer than that of the SY type. PAR, WHR, CJWR, and eye size had associations with BMI, and the magnitude of correlation of CJWR in Korean men were twofold higher than that of the Caucasian and African men. BMI and facial metrics including PAR, WHR, CJWR, and eye size were good predictors for TE type, and the most parsimonious model for TE typing included BMI and CJWR with high predictive performances.

Sasang constitutional medicine (SCM), traditional Chinese medicine (TCM) and Ayurveda are three different forms of Asian traditional medicine. Although these traditions share a lot in common as holistic medicines, the different philosophical foundations found in each confer distinguishing attributes and unique qualities. SCM is based on a constitution-based approach, and is in this way relatively more similar to the Ayurvedic tradition than to the TCM, although many of the basic SCM theories were originally derived from TCM, a syndrome-based medicine. SCM and TCM use the same botanical materials that are distributed mainly in the East Asian region, but the basic principles of usage and the underlying rationale are completely different from each other. Meanwhile, the principles of the Ayurvedic use of botanical resources are very similar to those seen in SCM, but the medicinal herbs used in Ayurveda generally originate from the West Asian region which displays a different spectrum of flora.

It is well known that body fat distribution and obesity are important risk factors for type 2 diabetes. Prediction of type 2 diabetes using a combination of anthropometric measures remains a controversial issue. This study aims to predict the fasting plasma glucose (FPG) status that is used in the diagnosis of type 2 diabetes by a combination of various measures among Korean adults. A total of 4870 subjects (2955 females and 1915 males) participated in this study. Based on 37 anthropometric measures, we compared predictions of FPG status using individual versus combined measures using two machine-learning algorithms. The values of the area under the receiver operating characteristic curve in the predictions by logistic regression and naive Bayes classifier based on the combination of measures were 0.741 and 0.739 in females, respectively, and were 0.687 and 0.686 in males, respectively. Our results indicate that prediction of FPG status using a combination of anthropometric measures was superior to individual measures alone in both females and males. We show that using balanced data of normal and high FPG groups can improve the prediction and reduce the intrinsic bias of the model toward the majority class.