Background: Sasang constitutional medicine (SCM) is a unique form of traditional Korean medicine that divides human beings into four constitutional types (Tae-Yang: TY, Tae-Eum: TE, So-Yang: SY, and So-Eum: SE), which differ in inherited characteristics, such as external appearance, personality traits, susceptibility to particular diseases, drug responses, and equilibrium among internal organ functions. According to SCM, herbs that belong to a certain constitution cannot be used in patients with other constitutions; otherwise, this practice may result in no effect or in an adverse effect. Thus, the diagnosis of SC type is the most crucial step in SCM practice. The diagnosis, however, tends to be subjective due to a lack of quantitative standards for SC diagnosis.Methods: We have attempted to make the diagnosis method as objective as possible by basing it on an analysis of quantitative data from various Oriental medical clinics. Four individual diagnostic models were developed with multinomial logistic regression based on face, body shape, voice, and questionnaire responses. Inspired by SCM practitioners’ holistic diagnostic processes, an integrated diagnostic model was then proposed by combining the four individual models.Results: The diagnostic accuracies in the test set, after the four individual models had been integrated into a single model, improved to 64.0% and 55.2% in the male and female patient groups, respectively. Using a cut-off value for the integrated SC score, such as 1.6, the accuracies increased by 14.7% in male patients and by 4.6% in female patients, which showed that a higher integrated SC score corresponded to a higher diagnostic accuracy.Conclusions: This study represents the first trial of integrating the objectification of SC diagnosis based on quantitative data and SCM practitioners’ holistic diagnostic processes. Although the diagnostic accuracy was not great, it is noted that the proposed diagnostic model represents common rules among practitioners who have various points of view. Our results are expected to contribute as a desirable research guide for objective diagnosis in traditional medicine, as well as to contribute to the precise diagnosis of SC types in an objective manner in clinical practice.

The aim of this study was to develop and evaluate a questionnaire for Cold and Heat pathologic pattern identification in the context of Traditional Chinese Medicine (TCM). This questionnaire was intended to classify subjects into Cold or Heat pattern groups, a distinction that is useful in clinical trials of both herbal and acupuncture treatments. A questionnaire that had been developed in a previous study was completed by 63 patients (Group A) and 64 patients (Group B) from TCM hospitals. Each patient was diagnosed by a TCM doctor as one of three patterns: Cold, Heat, and Complex. The questionnaire results were analyzed for internal reliability and validity based on the doctor's diagnosis. Cronbach's alpha coefficients were 0.579 for the 10 Cold items and 0.718 for the 10 Heat items. There were significant differences in the mean questionnaire scores between the Cold and Heat groups. The classification accuracy of this questionnaire for Group A was 94.9%, and for Group B it was 92.3%. Our results suggest that the questionnaire meets certain basic and fundamental requirements and that it may be useful as an adjunct diagnostic tool. Further studies using a greater number and variety of patients will be needed to evaluate its usefulness in clinical trials and in basic physiologic research.

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.

Objective. Body trunk measurement for human plays an important diagnostic role not only in conventional medicine but also in Sasang constitutional medicine (SCM). The Sasang constitutional body trunk measurement (SCBTM) consists of the 5-widths and the 8-circumferences which are standard locations currently employed in the SCM society. This study suggests to what extent a comprehensive training can improve the reliability of the SCBTM.Methods. We recruited 10 male subjects and 5 male observers with no experience of anthropometric measurement. We conducted measurements twice before and after a comprehensive training. Relative technical error of measurement (%TEMs) was produced to assess intra and inter observer reliabilities.Results. Post-training intra-observer %TEMs of the SCBTM were 0.27% to 1.85% reduced from 0.27% to 6.26% in pre-training, respectively. Post-training inter-observer %TEMs of those were 0.56% to 1.66% reduced from 1.00% to 9.60% in pre-training, respectively. Post-training % total TEMs which represent the whole reliability were 0.68% to 2.18% reduced from maximum value of 10.18%.Conclusion. A comprehensive training makes the SCBTM more reliable, hence giving a sufficiently confident diagnostic tool. It is strongly recommended to give a comprehensive training in advance to take the SCBTM.

This paper is concerned with measuring influence of rows and columns on the eigenvalues obtained in correspondence analysis (CA) of two-way contingency tables. As in principal component analysis, the eigenvalues are of great importance in CA. The goodness of a two dimensional correspondence plot is determined by the ratio of the sum of the two largest eigenvalues to the sum of all the eigenvalues. By investigating those rows and columns with high influence, a correspondence plot may be improved. In the paper the influence function (IF) of rows on the eigenvalues is derived along with its sample version, the empirical influence function (EIF). A numerical example is presented to evaluate the EIF. The sample influence function (SIF) is also evaluated to check the adequacy of the EIF.