• Biomedical Science Letters
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• v.23 no.4
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• pp.348-354
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• 2017

TyG (triglyceride and glucose) index using triglyceride and fasting blood glucose is recommended as a useful marker for insulin resistance. The present study evaluated the usefulness of TyG index in diagnosing metabolic syndrome and suggested an optimal cut-off value. The subjects of this study were adult 4,415 adults aged 20 to 80 years who underwent health screening at J General Hospital from January 2016 to January 2017. Metabolic syndrome was based on AHA/NHLBI (American Heart Association/National Heart, Lung, and Blood Institute) criteria. TyG index correlated with metabolic syndrome risk factors including HOMA-IR. Compared with the participants in the lowest quartile of TyG index, odds ratios and 95% confidence intervals for metabolic syndrome were 8.5 (3.005~23.903), 20.0 (17.190~23.407) for those in the third, and the fourth quartile of TyG index. The optimal cut-off value of the metabolic syndrome was 8.81 for TyG index (sensitivity 86.7%, specificity 80.1%) and area under the ROC curve (AUC) was 0.894. In conclusion, TyG index is effective to identify individuals at risk for metabolic syndrome.

• Biomedical Science Letters
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• v.23 no.2
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• pp.57-63
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• 2017

A new body adiposity index (BAI) has been proposed that is expected to replace body mass index (BMI). We evaluated the correlations between metabolic syndrome risk factors and BAI, BMI, and other adiposity indices, such as waist circumference (WC), waist-to-hip ratio (WHR), and waist-to-height ratio (WHtR), by sex in the Korean population. We also evaluated whether BAI would be useful to diagnose metabolic syndrome. A total of 20,961 Korean adults who underwent health examinations were included in this study. The metabolic syndrome diagnostic criteria used in this study were those set by the American Heart Association/National Heart, Lung, and Blood Institute (AHA/NHLBI). In men (12,719), BMI and WHtR were more strongly correlated to metabolic syndrome risk than BAI, and in women (8,242), WHtR showed the strongest association with metabolic syndrome risk. BAI (area under the curve [AUC] = 0.678) presented lower discriminatory capacity than that of BMI (AUC = 0.836) for diagnosing metabolic syndrome. Moreover, BAI underestimated fat levels in men and women when considering the ability to discriminate overweight and obese individuals. In conclusion, WHtR and BMI in men, and WHtR in women may be better candidates than BAI to evaluate metabolic risk factors in Korean adults.

• Journal of radiological science and technology
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• v.46 no.5
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• pp.367-377
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• 2023

This study investigates the utility of the Triglyceride-glucose(TyG) index and Cardiometabolic Index(CMI) as predictors for diagnosing metabolic syndrome. The study involved 1970 males, 1459 females, totaling 3429 participants who underwent health checkups at P Hospital in Busan between January 2023 and June 2023. Metabolic syndrome diagnosis was based on the presence of 3 or more risk factors out of the 5 criteria outlined by the American Heart Association/National Heart, Lung, and Blood Institute(AHA/NHLBI), and participants with 2 or fewer risk factors were categorized as normal. Statistical analyses included independent sample t-tests, chi-square tests, Pearson's correlation analysis, Receiver Operating Characteristic(ROC) curve analysis, and logistic regression analysis, using the Statistical Package for the Social Sciences(SPSS) program. Significance was established at p<0.05. The comparison revealed that the metabolic syndrome group exhibited attributes such as advanced age, male gender, elevated systolic and diastolic blood pressures, high blood sugar, elevated triglycerides, reduced LDL-C, elevated HDL-C, higher Cardiometabolic Index, Triglyceride-glucose index, and components linked to abdominal obesity. Pearson correlation analysis showed strong positive correlations between waist circumference/height ratio, waist circumference, Cardiometabolic Index, and triglycerides. Weak positive correlations were observed between LDL-C, body mass index, and Cardiometabolic index, while a strong negative correlation was found between Cardiometabolic Index and HDL-C. ROC analysis indicated that the Cardiometabolic Index(CMI), Triglyceride-glucose(TyG) index, and waist circumference demonstrated the highest Area Under the Curve(AUC) values, indicating their efficacy in diagnosing metabolic syndrome. Optimal cut-off values were determined as >1.34, >8.86, and >84.5 for the Cardiometabolic Index, Triglyceride-glucose index, and waist circumference, respectively. Logistic regression analysis revealed significant differences for age(p=0.037), waist circumference(p<0.001), systolic blood pressure(p<0.001), triglycerides(p<0.001), LDL-C(p=0.028), fasting blood sugar(p<0.001), Cardiometabolic Index(p<0.001), and Triglyceride-glucose index (p<0.001). The odds ratios for these variables were 1.015, 1.179, 1.090, 3.03, and 69.16, respectively. In conclusion, the Cardiometabolic Index and Triglyceride-glucose index are robust predictive indicators closely associated with metabolic syndrome diagnosis, and waist circumference is identified as an excellent predictor. Integrating these variables into clinical practice holds the potential for enhancing early diagnosis and prevention of metabolic syndrome.

• Korean Journal of Radiology
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• v.23 no.10
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• pp.986-997
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• 2022

Objective: Whether metabolic redistribution occurs in patients with white matter hyperintensities (WMHs) on magnetic resonance imaging (MRI) is unknown. This study aimed 1) to propose a measure of the brain metabolic network for an individual patient and preliminarily apply it to identify impaired metabolic networks in patients with WMHs, and 2) to explore the clinical and imaging features of metabolic redistribution in patients with WMHs. Materials and Methods: This study included 50 patients with WMHs and 70 healthy controls (HCs) who underwent ¹⁸F-fluorodeoxyglucose-positron emission tomography/MRI. Various global property parameters according to graph theory and an individual parameter of brain metabolic network called "individual contribution index" were obtained. Parameter values were compared between the WMH and HC groups. The performance of the parameters in discriminating between the two groups was assessed using the area under the receiver operating characteristic curve (AUC). The correlation between the individual contribution index and Fazekas score was assessed, and the interaction between age and individual contribution index was determined. A generalized linear model was fitted with the individual contribution index as the dependent variable and the mean standardized uptake value (SUV_mean) of nodes in the whole-brain network or seven classic functional networks as independent variables to determine their association. Results: The means ± standard deviations of the individual contribution index were (0.697 ± 10.9) × 10^-3 and (0.0967 ± 0.0545) × 10^-3 in the WMH and HC groups, respectively (p < 0.001). The AUC of the individual contribution index was 0.864 (95% confidence interval, 0.785-0.943). A positive correlation was identified between the individual contribution index and the Fazekas scores in patients with WMHs (r = 0.57, p < 0.001). Age and individual contribution index demonstrated a significant interaction effect on the Fazekas score. A significant direct association was observed between the individual contribution index and the SUV_mean of the limbic network (p < 0.001). Conclusion: The individual contribution index may demonstrate the redistribution of the brain metabolic network in patients with WMHs.

• Journal of the Korean Society of Food Culture
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• v.37 no.4
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• pp.376-384
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• 2022

This study was performed to develop a K_diet-index based on the definitions and characteristics of traditional Korean food. The Korean Food Pattern Index (K_diet-index) for diseases was applied using dietary data from the 2017 National Health and Nutrition Examination Survey (KNHANES) and the association between K_diet-index and metabolic disease was confirmed. The study subjects were 1,971 Korean adults aged >40, and the components were classified according to 14 criteria used to establish the K_diet-index. Main ingredients up to the top 3 were designated using dish names, ingredients, and contents using KNHANES dietary data. K_diet-index was classified using scores of ≤3 points, 4-7 points, and ≥8 points and total K_diet-index were calculated by summing dietary scores. Correlations between K_diet-index and obesity, hypertension, hyperlipidemia, and diabetes were analyzed. The odds ratio (OR) and 95% confidence interval (CI) for obesity were 0.531, 0.385~0.732 and for elevated cholesterol (≥240 mg/dL) indices were 0.471, 0.282~0.788, respectively, which showed a significant decreased in the risk for each disease for K_diet-index of ≥8 points. This study confirms that metabolically related clinical results improved significantly as K_diet-index increased and that higher Korean food pattern indices are associated with lower risks of metabolic disease

• Korean Journal of Community Nutrition
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• v.25 no.1
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• pp.61-70
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• 2020

Objectives: This study examined the association of the total diet quality with the incidence risk of metabolic syndrome constituents and metabolic syndrome among Korean adults. Methods: Based on a community-based cohort of the Korean Genome and Epidemiology Study (KoGES) from 2001 to 2014, data from a total of 5,549 subjects (2,805 men & 2,744 women) aged 40~69 years at the baseline with a total follow-up period of 38,166 person-years were analyzed. The criteria of the National Cholesterol Education Program Adult Treatment Panel was employed to define metabolic syndrome. The total diet quality was estimated using the Korean Healthy Eating Index (KHEI). Hazard ratios (HR) and 95% confidence intervals (CI) for risk of metabolic syndrome constituents and metabolic syndrome in relation to KHEI quintile groups was calculated by multivariate Cox proportional hazards regression model. Results: After adjusting for age, energy intake, income, education, physical activity, smoking, and drinking, the incidence of abdominal obesity and high blood pressure was significantly lower, by approximately 29.7% (P < 0.01) and 25.2% (P < 0.01), respectively, in the fifth KHEI quintile compared to the first quintile in men. A significant decreasing trend of the metabolic syndrome incidence was observed across the improving levels of KHEI (HRq5vs.q1: 0.775, 95% CIq5vs.q1: 0.619~0.971, P for trend < 0.01). In women, the incidence of abdominal obesity and metabolic syndrome was significantly lower, by approximately 29.8% (P < 0.01) and 22.5% (P < 0.05), respectively, in the fifth KHEI quintile compared to the first quintile adjusting for multiple covariates. On the other hand, the linear trend of metabolic syndrome risk across the KHEI levels did not reach the significance level. Conclusions: A better diet quality can prevent future metabolic syndrome and its certain risk factors among Korean men and women.

• Journal of Physiology & Pathology in Korean Medicine
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• v.24 no.3
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• pp.519-524
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• 2010

This clinical study was done to examine comparison the prevalence of metabolic syndrome and obesity index between patients with silent lacunar infarction and normal controls. We compared the components of metabolic syndrome and obesity index between patients silent lacunar infarction(n=62) and normal controls(n=72). The analysis of the data was done by Frequency Analysis, two sample t-test, Chi-square Test. Hypertension and diabetes mellitus was significantly higher in patients of silent lacunar infarctions. Body mass index (BMI), waist-hip ratio (WHR), body fat percentage, obesity ratio, metabolic syndrome were higher significantly in patients of silent lacunar infarctions than normal controls. Although statistically insignificant, waist circumference showed relatively higher in patients of silent lacunar infarction. This result emphasizes the importance of managing that hypertension, diabetes, body mass index (BMI), waist-hip ratio (WHR), body fat percentage, obesity ratio, metabolic syndrome in silent lacunar infarction.

• Korean Journal of Community Nutrition
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• v.27 no.3
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• pp.223-244
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• 2022

Objectives: This study was designed to investigate the relationship between metabolic risk factors, Index of Nutrition Quality, and the dietary quality index score of Korean adults. Methods: The subjects were 18,652 Korean adults aged 19 years or older (7,899 males, 10,753 females) who participated in the 2016-2019 Korea National Health and Nutrition Examination Survey. Subjects were divided into normal, pre-metabolic syndrome, and metabolic syndrome (MetS) groups according to the number of their metabolic risk factors. Data were analyzed using the SPSS program. Results: About 44.7% of men in the MetS group were at least college graduates (P < 0.001), whereas 52.0% of women in the MetS group were middle school graduates or lower (P < 0.001). The frequency of fruit and dairy products intake tended to decrease as the number of metabolic risk factors increased in both men and women (P for trend < 0.001). As the number of metabolic risk factors decreased, the frequency of grain intake tended to decrease in men (P for trend < 0.001) while the frequency of intake of red meat (P for trend = 0.001), poultry (P for trend < 0.001), and eggs (P for trend < 0.001) decreased in women. The total scores of Diet Quality Index-International (DQI-I) (men P < 0.001, women P < 0.01) and Korean Healthy Eating Index (KHEI) (men and women P < 0.001) were significantly lower in the MetS group compared to the other groups, and the total score of DQI-I and KHEI tended to decrease as the number of metabolic risk factors increased. Conclusions: Dietary quality evaluation using various indices can provide more information on the dietary problems related to metabolic risk factors. Nutrients and foods that have been confirmed to be related to metabolic risk factors can be used to develop dietary guidelines for the nutritional management of metabolic diseases.

• Clinical and Experimental Pediatrics
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• v.50 no.7
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• pp.629-635
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• 2007

Purpose : This study was conducted to assess the usefulness of fat-free mass index (FFMI) and fat mass index (FMI) as novel expression methods of body composition in children. Methods : A total of 466 Second grade students-248 boys and 218 girls- from all elementary schools the Gwacheon City underwent anthropometric measures including bioelectrical impedance analysis (BIA) and biochemical tests. The correlation coefficients between obesity indices, including FMI and FFMI, and metabolic risk factors, were assessed. Metabolic risk factors of children with increased FMI were compared with those of children with normal FMI. We compared FMI and FFMI percentile distribution between this study's subjects and the subjects of the Fukuoka body composition study. Results : FMI was lower and FFMI was higher in this study's subjects compared to the subjects of the Fukuoka body composition study. FMI was correlated with other obesity indices and several metabolic risk factors. Metabolic risk was higher in children with increased FMI than in children with normal FMI. Conclusion : FMI and FFMI were useful indicators in comparing difference of body composition among children that had different body size and growth. High FMI was related to increase of metabolic risk in children.

• Journal of Korean society of Dental Hygiene
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• v.16 no.6
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• pp.979-991
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• 2016

Objectives: The objective of the study is to investigate the effect of oral health belief and metabolic syndrome on CPITN. Methods: A self-reported questionnaire was completed by 847 adult visitors over 20 years old in Busan from August 1 to December 31, 2011. Except incomplete answers, 776 data were analyzed by t-test, one way ANOVA, and logistic regression analysis using SPSS 20.0 program. The questionnaire comprised general characteristics of the subjects, oral health behavior, and metabolic syndrome related risk factors. Results: There was statistically significant difference of an oral health belief rating between the groups receiving oral health education. Community periodontal index had statistically significant difference depending on smoking and waist circumference. To analyze related factors of community periodontal index, multiple logistic regression analysis was performed. As the final outcome, gender, age, benefit, salience, scaling experience, experience of oral health education, and related factors and metabolic syndrome were shown to impact on significant influence (p<0.05). Conclusions: Thus, To manage the effective oral health, it is necessary to control the factors of metabolic syndrome and oral health.