Body Mass Index and Facial Cues in Sasang Typology for Young and Elderly Persons

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

The Study of Misclassification Probability in Discriminant Model of Pattern Identification for Stroke

Background. Pattern identification (PI) is the basic system for diagnosis of patients in traditional Korean medicine (TKM). The purpose of this study was to identify misclassification objects in discriminant model of PI for improving the classification accuracy of PI for stroke. Methods. The study included 3306 patients with stroke who were admitted to 15 TKM hospitals from June 2006 to December 2012. We derive the four kinds of measure (D, R, S, and C score) based on the pattern of the profile graphs according to classification types. The proposed measures are applied to the data to evaluate how well those detect misclassification objects. Results. In 10–20% of the filtered data, misclassification rate of C score was highest compared to those rates of other scores (42.60%, 41.15%, resp.). In 30% of the filtered data, misclassification rate of R score was highest compared to those rates of other scores (40.32%). And, in 40–90% of the filtered data, misclassification rate of D score was highest compared to those rates of other scores. Additionally, we can derive the same result of C score from multiple regression model with two independent variables. Conclusions. The results of this study should assist the development of diagnostic standards in TKM

Semiparametric Inference Based on a Class of Zero-Altered Distributions

In modeling count data collected from manufacturing processes, eco-nomic series, disease outbreaks and ecological surveys, there are usually a relatively large or small number of zeros compared to positive counts. Such low or high frequencies of zero counts often require the use of un-der or over dispersed probability models for the underlying data generating mechanism. The commonly used models such as generalized or zero-inflated Poisson distributions can usually account for only the over dispersion, but such distributions are often found to be inadequate in modeling underdis-persion because of the need for awkward parameter or support restrictions. This article introduces a flexible class of semiparametric zero-altered models which account for both under and over dispersion and includes other famil-iar models such as those mentioned above as special cases. Consistency and asymptotic normality of the dispersion parameter are derived under general conditions. Numerical support for the performance of the proposed method of inference is presented for the case of common discrete distributions

Differences in Complexion between Cold- and Heat-Prescription Groups in Sasang Medicine

Sasang constitutional medicine (SCM) is a type of traditional Korean medicine (TKM) that classifies the human constitution into four types. The appearance of the complexion is one of the diagnostic factors of SCM but is rarely used in a quantitative and objective manner for diagnosis. In this study, an analysis using actual clinical data was conducted to assess the use of the complexion as a diagnostic element. A total of 528 Sasang medicine prescriptions from Korea Constitutional Multicenter Bank (KCMB) were classified into either a Cold-prescription group or a Heat-prescription group, and the complexion differences of the patients were analyzed using the L⁎a⁎b⁎ color space. After adjusting for age, BMI, and systolic blood pressure, significant differences were observed among the Cold- and Heat-prescription groups within each Sasang constitution. However, when the Sasang constitution was ignored, no significant difference was observed for either sex. This study quantitatively analyzed the complexion of patients, which is used as a diagnostic element in clinical practice. It is hoped that the results will contribute to objective medical treatments in the future, such as determining an appropriate herbal prescription based on the patient’s complexion

Prediction of Hypertension Based on Facial Complexion

This study aims to investigate the association between hypertension and facial complexion and determine whether facial complexion is a predictor for hypertension. Using the Commission internationale de l’éclairage L*a*b* (CIELAB) color space, the facial complexion variables of 1099 subjects were extracted in three regions (forehead, cheek, and nose) and the total face. Logistic regression was performed to analyze the association between hypertension and individual color variables. Four variable selection methods were also used to assess the association between hypertension and combined complexion variables and to compare the predictive powers of the models. The a* (green-red) complexion variables were identified as strong predictors in all facial regions in the crude analysis for both genders. However, this association in men disappeared, and L* (lightness) variables in women became the strongest predictors after adjusting for age and body mass index. Among the four prediction models based on combined complexion variables, the Bayesian approach obtained the best predictive in men. In women, models using three different methods but not the stepwise Akaike information criterion (AIC) obtained similar AUC values between 0.82 and 0.83. The use of combined facial complexion variables slightly improved the predictive power of hypertension in all four of the models compared with the use of individual variables

Modification of the Integrated Sasang Constitutional Diagnostic Model

In 2012, the Korea Institute of Oriental Medicine proposed an objective and comprehensive physical diagnostic model to address quantification problems in the existing Sasang constitutional diagnostic method. However, certain issues have been raised regarding a revision of the proposed diagnostic model. In this paper, we propose various methodological approaches to address the problems of the previous diagnostic model. Firstly, more useful variables are selected in each component. Secondly, the least absolute shrinkage and selection operator is used to reduce multicollinearity without the modification of explanatory variables. Thirdly, proportions of SC types and age are considered to construct individual diagnostic models and classify the training set and the test set for reflecting the characteristics of the entire dataset. Finally, an integrated model is constructed with explanatory variables of individual diagnosis models. The proposed integrated diagnostic model significantly improves the sensitivities for both the male SY type (36.4% → 62.0%) and the female SE type (43.7% → 64.5%), which were areas of limitation of the previous integrated diagnostic model. The ideas of these new algorithms are expected to contribute not only to the scientific development of Sasang constitutional medicine in Korea but also to that of other diagnostic methods for traditional medicine

Analysis of Sasang constitutional types using facial features with compensation for photographic distance

Background: Facial features are regarded as representative and reliable characteristics for diagnosing a person's Sasang Constitution (SC). However, the description of these features tends to depend on the interpretation and the opinion of the doctor that follows the SC approach. In this paper, we performed a facial feature analysis of SC types in an objective and quantitative manner. Here, site-to-site variability can be an obstacle to properly analyzing facial features when images are taken from various sites, which may have different experimental environments. A compensation technique to reduce the site-to-site variability was proposed before performing the feature analysis. Methods: The frontal and profile images of 1464 patients recruited from various oriental medical clinics (19 sites) were used. Candidate feature variables were created, which were inspired by the facial characteristics of the SC types described in the Sasang constitutional medicine literature. To resolve the problems involved in processing data collected from various sites with heterogeneous experimental environments, a compensation technique was proposed. Statistical analysis techniques were employed to observe the differences among the SC types and to demonstrate how effectively the site-to-site variability was reduced. Results: The facial features that were significant for diagnosing the SC types were identified by a statistical analysis, and it was verified that the compensation technique reduced the site-to-site variability produced by the differences in photographic distance. Conclusion: It is noted that the significant facial features represent common characteristics of each SC type in the sense that we collected extensive opinions from many Sasang constitutional medicine doctors with various points of view. Additionally, a compensation method for the photographic distance is needed to find the significant facial features. We expect these findings and the related compensation technique to contribute to establishing a scientific basis for the precise diagnosis of SC types in clinical practice

S: A study on the reliability of sasang constitutional body trunk measurement. Evid Based Complement Alternat Med 2012

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

A Study on the Diagnostic Elements of Cold-Heat Pattern Identification by Korean Medicine Doctors: Association with Objective and Subjective Body Temperature

Although the Cold-Heat Pattern is the most important diagnostic factor in Traditional Korean Medicine (TKM), its relationship to body temperature and subjective temperature has not been clearly revealed. In this study, based on clinical data from 551 patients, we classified patients treated with herbal medicines into a Cold-prescription group (CG) and a Heat-prescription group (HG), and we compared the ordinary symptoms between the two groups. Subjective body temperature was higher in the HG than in the CG (OR = 1.68, p<0.01) and digestive ability was better in the HG than in the CG (expert’s questionnaire, OR = 1.91, p<0.001). However, objectively measured body temperature did not show any significant difference between the HG and CG in both gender groups (p=0.383 and 0.181 for males and females, resp.). Our study suggests that the subjective body temperature and digestive ability may be the principal diagnostic elements of Cold-Heat Pattern identification by Korean Medicine Doctors. These findings may contribute to the investigation of an objective method to measure the Cold-Heat Pattern