This study examined the relationship between Body mass index (BMI) classification and the occurrence of dyslipidemia using 3 years of health examination data from a university hospital in Changwon, and seeked to find other factors that affect dyslipidemia. Multivariate logistic regression analysis investigated the most common risk factors for developing dyslipidemia and used Kaplan-Meier survival curves to predict the probability of developing dyslipidemia according to BMI class. We then analyzed the effects of metabolic indicators such as smoking habits, alcohol consumption, blood pressure, glucose, hemoglobin A1c (HbA1c), and insulin. The Type I error rate was controlled through Bonferroni correction for multiple comparisons to extract reliable statistical data. in the present study, these results showed that the probability of developing dyslipidemia was high in the obese group, and confirmed that lifestyle habits such as smoking and drinking were highly correlated with the occurrence of dyslipidemia. Therefore, we suggest that dyslipidemia management and prevention strategies require public health policies that comprehensively manage lifestyle factors such as gender and weight management, smoking cessation, and drinking habits.

Tuberculosis is a potentially deadly infectious disease caused by the Mycobacterium tuberculosis (M. tuberculosis). Tuberculosis is diagnosed by proving the M. tuberculosis in sputum samples based on the results of acid-resistant staining, culture, and nucleic acid amplification tests. However, there is a report that the detection rate of M. tuberculosis is low in acid-resistant staining using tissue specimens. It has been suspected that the cause is a potential loss of acid resistance by the organic solvents used for tissue specimen preparation. Therefore, this study was pursued to find out if Gram staining and fluorescent staining in addition to acid-resistant staining would be helpful in diagnosing tuberculosis. We used four tissue (lung, small intestine, large intestine, and lymph node) samples with chronic granulomatous inflammation observed in HE staining and positive results in real-time PCR. These detection rates and staining properties were investigated through microscopic examination using the Ziehl-Neelsen, Gram, and Auramin rhodamine staining. In this studies, M. tuberculosis were observed by Ziehl-Neelsen, Gram, and Auramin rhodamine staining in all four samples. In the evaluation of clinical microbiology proficiency testing (CMPT), the Ziehl-Neelsen and Gram staining were the same result, but the Auramin rhodamine staining was relatively low. These data indicated that Gram staining is useful for detecting M. tuberculosis in formalin-fixed tissue specimens. Therefore, if the Ziehl-Neelsen and Gram staining are combined as the M. tuberculosis staining method in tissue specimens, a better direction may be provided for tuberculosis diagnosis.