• Journal of the Korea Convergence Society
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• v.11 no.12
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• pp.283-290
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• 2020

The purpose of this study was to evaluate the usefulness of the triglyceride and glucose(TyG) index to predict the risk of hyperuricemia in Korean adults. This study included 14,266 men and 9,033 women over 20 years old who underwent health screenings from 2017 to 2019 at a general hospital in Seoul. To confirm the risk of hyperuricemia and predictive ability of the TyG index, logistic regression analysis and ROC curves were obtained. The accuracy of the TyG index for predicting hyperuricemia was 0.68, 0.61 for men and 0.67 for women(respectively p<0.001). The risk of hyperuricemia in the TyG index was 1.69 times higher in the fourth quartile than in the first quartile, 2.03 times higher in men and 2.07 times higher in women(respectively p<0.05). Thus the TyG index was not of high diagnostic usefulness as a screening test for hyperuricemia, but it was related to the TyG index and hyperuricemia.

• 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.25 no.3
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• pp.256-266
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• 2019

In this study, obese adults were compared for their ability to predict obesity and lipid related variables and their optimal cutoff values to predict metabolic syndrome and insulin resistance. In this study, 9,256 adults aged 20 years or older and less than 80 years old, who were in the Gyeonggi region from January 2014 to December 2016 and who were examined at a general hospital, were enrolled. The diagnostic criteria for obesity were WHO (World Health Organization), and BMI $25kg/m^2$ or more presented in the Asia-Pacific region. Metabolic syndrome was diagnosed based on the criteria of American Heart Association / National Heart, Lung, and Blood Institute (AHA / NHLBI). According to the results of receiver operating characteristic curve (ROC) analysis, Triglyceride / HDL-cholesterol (TG / HDL-C), Triglyceride and Glucose (TyG) index, lipid accumulation product (LAP) and visceral adiposity index (VAI) showed high predictive power for diagnosing metabolic syndrome. The diagnostic accuracy of LAP (AUC: 0.854) for males and VAI (0.888) for females was the highest. The optimal cutoff value of LAP was 42.71 for male and 35.44 for female, and the cutoff value of VAI was 1.92 for male and 2.15 for female. In addition, WHtR (waist to height ratio), TyG index, and LAP were used as predictors of insulin resistance in obese adults. Therefore, LAP and VAI were superior to other indicators in predicting metabolic syndrome in obese 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.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.10 no.4
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• pp.111-117
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• 2001

In this paper, we will propose the new method that estimates the sensing ability of smart sensor. A study is estimation method that evaluates the sensing ability about smart sensor respectively. According to acceleration(g) and displacement changing, we estimated the sensing ability of smart sensor using the SAI(Sensing Ability Index) method respectively. We made the smart sensors in our experiment. The types of smart sensor are three types(H1, H1, H3 smart sensor). The smart sensors were developed for recognition of materials. Experiments and analysis were executed to estimated the sensing abili-ty of smarty sensor. Dynamic characteristics of smart sensors(acceleration changing) were evaluated respectively through a new method(SAI) that uses the power spectrum density.

• Annals of Occupational and Environmental Medicine
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• v.34
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• pp.28.1-28.12
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• 2022

Background: Haenyeo is a woman who has the job of collecting seafood in the Jeju Sea at an average temperature of 13℃-14℃. The purpose of this study was to examine the cold acclimatization and occupational characteristics of Haenyeo through biomarkers such as orexin and irisin related to heat generation in the body. Methods: Twenty-one Haenyeo and 25 people with similar age, body type, and body mass index were selected as the control group (Control G). In the cold exposure experiment, a climate chamber was set to 5℃ and both feet were immersed in a 15℃ water tank for 30 minutes. Tympanic temperature (T_ty) and skin temperature (T_sk) were measured, and the mean body temperature (mT_b) was calculated. Blood samples were collected before and immediately after the examination. Orexin and irisin levels were analyzed. Results: Orexin levels were elevated after cold stimulation from 12.17 ± 4.44 to 12.95 ± 4.53 ng/mL (Haenyeo group [Haenyeo G], p < 0.01) and 10.37 ± 3.84 to 11.25 ± 4.02 ng/mL (Control G, p < 0.001). Irisin levels were elevated after cold stimulation from 4.83 ± 2.28 to 5.36 ± 2.23 ng/mL (Haenyeo G, p < 0.001) and 3.73 ± 1.59 to 4.18 ± 2.04 ng/mL (Control G, p < 0.001). The difference between Haenyeo G and Control G values in orexin and irisin appears not only in pre-exposure but also in post-exposure (p < 0.05). Conclusions: Our experimental results suggest that Haenyeo G were relatively superior in cold tolerance to Control G under cold exposure conditions. Haenyeo's cold acclimatization is due to the basic differences in pyrogens regarding body temperature control such as orexin and irisin. This means that Haenyeo are advantageous for cold survival.