• 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.