• Journal of Korean society of Dental Hygiene
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• v.20 no.3
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• pp.303-312
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• 2020

Objectives: The purpose of this study was to investigate the relationship between periodontal disease, number of remaining teeth with high-sensitivity C-Reactive protein in Korean adults aged 40 and older. Methods: The study used the Sixth Korea National Health and Nutrition Examination Survey (KNHANES VI-3), 2015. The study sample consisted of 3,883 aged 40 years or older who had completed the health survey and the health examination. Logistic regression analyses were performed to examine the odds ratios of high-sensitivity C-Reactive protein by periodontal disease and number of remaining teeth, adjusting for demographic characteristics, chronic diseases and oral health behavior-related variables. Results: When the demographic and chronic diseases were adjusted, the risk of high-sensitivity C-Reactive protein (hs-CRP) average 1.23 mg/L or higher was 1.36 times higher in patients with periodontal disease between the ages of 40 and 49, but it was not significant (OR=1.36; 95% CI=0.82-2.23). In addition, in the group of 0~23 remaining teeth aged 40~49 years, the risk of higher than the average 1.23 mg/L of high-sensitivity C-Reactive protein was 2.03 times higher (OR=2.03; 95% CI=1.10-3.74), and 1.49 times higher in 60~69 years (OR=1.07; 95% CI=1.04-2.76). Conclusions: This study found that periodontal disease and tooth loss in Korean adults aged 40 and older was significantly associated with high-sensitivity C-reactive protein.

• Nutrition Research and Practice
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• v.13 no.2
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• pp.150-158
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• 2019

BACKGROUND/OBJECTIVES: Inflammation is known to be a risk factor for metabolic diseases. This study aimed to develop a Food-based Index of Dietary Inflammatory Potential (FBDI) and examine its association with metabolic biomarkers. SUBJECTS/METHODS: This study analyzed the raw data from the 2012-2014 Korean Genome and Epidemiology Study data of 17,771 people. To analyze the relationship between foods consumed by Koreans and inflammation, we conducted a correlation analysis between 51 food groups and hs-CRP levels. The FBDI was developed from 17 food groups selected by multiple regression method. We examined whether FBDI was associated with metabolic markers (waist circumference, blood pressure, fasting glucose, triglyceride, and HDL-cholesterol) in the 6th Korea National Health and Nutrition Examination Survey (KNHANES). We used binary logistic regression analysis to examine the association. RESULTS: The FBDI model included seven of the anti-inflammatory food groups and three of the pro-inflammatory food groups. The FBDI formula was calculated by multiplying the intake of food group by ${\beta}$-coefficients derived from the multiple regression model based on the correlation analysis. The FBDI was significantly associated with waist circumference (P < 0.001), blood pressure (P < 0.001), triglyceride level (P < 0.001), and HDL-cholesterol (P < 0.001) level among adults aged 20-64 years in the KNHANES. The prevalence of metabolic syndrome was 2.618 times higher in the group with the highest FBDI than in the group with the lowest one (95% confidence interval: 1.778-3.856, P for trend < 0.001). CONCLUSIONS: This study established an FBDI reflecting food intake patterns of Koreans, which showed a significant relationship with the prevalence of metabolic syndrome.

• Journal of Haehwa Medicine
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• v.24 no.2
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• pp.35-57
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• 2016

Objectives : The purpose of this study is to prove the effect and mechanism of Gamikyejakjimogawusul-tang(GKHA) herbal acupuncture on induced rheumatoid arthritis model of DBA/1 mice. Methods : We check effect of GKHA extract on the AST, ALT, Creatinine, BUN of serum and cell viability of GK extract in RAW 264.7 cells to test the stability of this study. In vitro, we measure total phenol contents, total flavonoid contents, DPPH free radical scavenging activity, ABTS cation radical scavenging activity of Gamikyejakjimogawusul-tang, effect of GK extract on ROS(Reactive Ooxygen Species) production to estimate a anti-oxidant capacity, and we also measure effect of GK extract on NO (Nitric Oxid), IL-$1{\beta}$, IL-6, IL-17, IL-21, TNF-${\alpha}$, MCP-1, GM-CSF production in RAW 264.7 cells to estimate a anti-inflammatory efficacy. In vivo, we compare a rheumatoid arthritis manifestation between control and experimental group and estimate a AI. Then we check effect of GKHA on the level of WBC, neutrophil, lympocyte, monocyte in the blood to see the effect of immune cells in blood. In addition we measure effect of GKHA on the level of hs-CRP, IgM, IgG, IL-$1{\beta}$, IL-6, IL-17, IL-21, TNF-${\alpha}$, MCP-1, GM-CSF in serum. We observe effects of GKHA on imaging of cartilage degeneration using micro CT-arthrography in paw hind. And we calculate effects of GKHA that reduced BV ratio, BS/BV ratio using 3D Micro-CT. Lastly we observe effects of GKHA histopathologic examination analysis. Results : 1. The toxicity on liver and kidney was disregardable and the cytotoxicity against RAW 264.7 cells was also disregardable. 1. Total phenol contents and total flavonoid contents in GK extract were in high level. 2. DPPH free radical scavenging activity and ABTS cation radical scavenging activity were increased according to concentration of GK extract 3. ROS production was significantly decreased in GK extract (at 10, $100{\mu}g/ml$). 4. NO, IL-6, TNF-${\alpha}$, MCP-1 production were significantly decreased in GK extract(at 10, $100{\mu}g/ml$). IL-17, GM-CSF production were significantly decreased in GK extract(at 1, 10, $100{\mu}g/ml$). IL-$1{\beta}$, IL-21 production were also decreased but there was no statistical significance. 5. 25x observation after H&E and M-T staining, infiltration of immune cells and subsidence of the cartilage and damage to the synovial cells were decreased. Conclusions : This study showed that GKHA extract had anti-oxidant capacity, anti-inflammatory efficacy. GKHA extract also had inhibiting effect on the process of rheumatoid arthritis and can protect joint and cartilage. So we expect that GKHA extract can be a meaningful treatment to rheumatoid arthritis patients.

• Journal of Korean Medicine Rehabilitation
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• v.24 no.4
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• pp.155-162
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• 2014

Objectives Advanced researches on the relationship between obesity and heart rate variability (HRV), heretofore, focused on characteristics of HRV depending on the state of obesity. However, the previous researches have not quantified predictive power of HRV toward the obesity-related variables, which is rather more meaningful for clinicians who regularly treat obese patients. Hence, we designed a research to investigate whether HRV could predict serum levels of obesity-related metabolites. Methods Ninety obese premenopausal women meeting the inclusion criteria were recruited. The HRV test, blood sampling, and measurement of physical traits were conducted. Multiple regression analysis of the measurement data was carried out, putting obesity-related metabolites (insulin, glucose, triglyceride, hs-CRP, HDL, LDL, total cholesterol) as outcome variables and the others as predictors. To select appropriate predictive variables, the Akaike's Information Criterion (AIC) was applied. Normality and homoskedasticity of residuals for each model were tested to identify if there were any violations of the regression analysis's basic assumption. Logarithm transformation was used for the values of the concentration of metabolites and the HRV. Results The regression model including Total Power (TP) value and BMI had significant predictive power for serum insulin concentration (F(2, 88)=835.7, p<0.001, $R^2=0.95$). The regression coefficient of ln (TP) was -0.1002. However, it was not sure if the HRV could predict concentrations of other metabolites. Conclusions The results suggest that the Total Power (TP) value of the HRV can predict the level of serum insulin. If the BMI could be assumed as being constant, when the TP value is multiplied by n, the predicted change of insulin could be drawn by multiplying $n^{-0.1002}$. The uncertainty of this model can be assumed as approximately 5%.

• Toxicological Research
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• v.30 no.2
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• pp.91-97
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• 2014

This study aimed to identify changes in the level of neuropeptides among current smokers, former smokers, and individuals who had never smoked, and how smoking habits affect obesity and metabolic syndrome (MetS). Neuropeptide levels, anthropometric parameters, and metabolic syndrome diagnostic indices were determined among male workers; 117 of these had never smoked, whereas 58 and 198 were former and current smokers, respectively. The total sample comprised 373 male workers. The results obtained from anthropometric measurements showed that current smokers attained significantly lower body weight, body mass index, waist circumference, and abdominal fat thickness values than former smokers and those who had never smoked. Current smokers' eating habits proved worse than those of non-smokers and individuals who had never smoked. The level of brain-derived neurotrophic factor (BDNF) in the neuropeptides in the case of former smokers was $23.6{\pm}9.2pg/ml$, higher than that of current smokers ($20.4{\pm}6.1$) and individuals who had never smoked ($22.4{\pm}5.8$) (F = 6.520, p = 0.002). The level of adiponectin among former smokers was somewhat lower than that of current smokers, whereas leptin levels were higher among former smokers than current smokers; these results were not statistically significant. A relationship was found between adiponectin and triglyceride among non-smokers (odds ratio = 0.660, ${\beta}$ value=-0.416, p < 0.01) and smokers (odds ratio = 0.827, ${\beta}$ value=-0.190, p < 0.05). Further, waist circumference among non-smokers (odds ratio = 1.622, ${\beta}$ value=0.483, p < 0.001) and smokers (odds ratio = 1.895, ${\beta}$ value=0.639, p < 0.001) was associated with leptin. It was concluded that cigarette smoking leads to an imbalance of energy expenditure and appetite by changing the concentration of neuropeptides such as adiponectin, BDNF, leptin, and hsCRP, and influences food intake, body weight, the body mass index, blood pressure, and abdominal fat, which are risk factors for MetS and cardiovascular disease.

• Korean Journal of Clinical Laboratory Science
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• v.49 no.3
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• pp.239-247
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• 2017

Among the commonly known tools to diagnose diabetes are fasting plasma glucose (FPG), HbA1c., and OGTT known as gold standard. However, there can be many disagreements on the ways to diagnose diabetes. In this study, we examined the differences of the types of diabetes according to the applicability of FPG and HbA1c. Moreover, we evaluated the concordance of diagnosis. We excluded subjects with missing glucose and HbA1c data, as well as those previously diagnosed with diabetes, and those who fasted less than 8 hours. The data of 4,502 subjects (1,956 men and 2,546 women) from the 2015 KNHNES were analyzed. We divided these patients into three categories which are normal, prediabetes, and diabetes, based on the FPG and HbA1c. In men, the number of subjects with FPG ranging from 100 to 125 mg/dL and HbA1c ${\geq}6.5%$ was 23 out of 664, and the number of subjects with FPG < 126 mg/dL and HbA1c ${\geq}6.5%$ was 39 out of 86 newly diagnosed diabetes patients. The concordance rate was as follows: Normal 80.3%, prediabetes 44.9%, and diabetes 54.7%. The coefficient of Cohen's Kappa was 0.322 in men and 0.362 in women; this suggests that both gender showed a low concordance rate. However, when we divided them into two categories (nondiabetes and diabetes), Kappa was 0.582 in men and 0.637 in women, showing a relatively high concordance rate. While all subjects with FPG ${\geq}126mg/dL$ showed a significantly high HOMA IR, all subjects with FPG < 126 mg/dL showed a significantly high QUICKI. Considering the low concordance rate for the diagnosis of diabetes and characteristic of diagnostic tests, it is necessary to combine the related tests for diagnosing diabetes.