). The subjects were classified as nonsmokers, former smokers, and current smokers by gender. Logistic regression analysis was used to calculate the odds ratios(ORs) and the 95% confidence intervals(CIs) for the effects of smoking status on depressive symptoms, and depression diagnosed by a doctor. Results: Compared to nonsmokers, the ORs of depressive symptoms for current smokers were 1.11(95% CI, 1.11-1.12) among males, and 1.64(95% CI, 1.63-1.64) among females. Compared to former smokers, the ORs of depressive symptoms for current smokers were 1.05(95% CI, 1.05-1.05) among males, and 1.89(95% CI 1.88-1.90) among females. Compared to nonsmokers, the ORs of depression for current smokers were 0.94(95% CI, 0.94-0.95) among males, and 1.40(95% CI, 1.39-1.41) among females. Compared to former smokers, the ORs of depression for current smokers were 1.09(95% CI, 1.09-1.10) among males, and 0.99(95% CI, 0.99-1.00) among females. Conclusions: Smoking is associated with depressive symptoms among Korean adults. Therefore, it is necessary to consider depressive symptoms with the management of tobacco control policies.

BackgroundThe purpose of this study was to investigate the association between diabetes and depressive symptoms among Korean women.MethodsWe performed an analysis of data for 6,572 women aged 30 or over obtained from the Fifth Korean National Health and Nutrition Examination Survey conducted in 2010 to 2011. We examined the presence of depressive symptoms and the treatment of depression according to diabetes status.ResultsThe presence of depressive symptoms was observed in 22.6% of subjects with diabetes. In the multiple logistic regression model, diabetes was associated with an increased risk of depressive symptoms (odds ratio [OR], 1.21; 95% confidence interval [CI], 1.20 to 1.21) but the treatment of depression among diabetics was less common (OR, 0.54; 95% CI, 0.54 to 0.55). Uncontrolled diabetes (glycosylated hemoglobin ≥ 7%) was associated with an increased risk of depressive symptoms (OR, 1.71; 95% CI, 1.69 to 1.73) among diabetics.ConclusionPhysicians should manage individuals with diabetes in consideration of the presence of depressive symptoms, especially in those with uncontrolled diabetes.

BackgroundThis research investigated the sensitivity and specificity of heavy and binge drinking for screening of alcohol use disorder.MethodsThis retrospective study was conducted with 976 adults who visited the Sun Health Screening Center for health screenings in 2015. Daily drinking amount, drinking frequency per week, and weekly drinking amount were investigated. Using criteria from the National Institute on Alcohol Abuse and Alcoholism, participants were classified as normal drinkers, heavy drinkers, or binge drinkers, and grouped by age and sex. The sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of heavy and binge drinking were compared for the diagnosis of alcohol abuse and alcohol dependence using the Diagnostic and Statistical Manual of Mental Disorders (DSM) 4th edition-text revision and alcohol use disorder using the DSM 5th edition.ResultsThe sensitivity of heavy and binge drinking for the diagnosis of alcohol abuse, alcohol dependence, and alcohol use disorder were 51.7%, 43.8%, and 35.3%, and 69.0%, 62.5%, and 48.2%, respectively. The specificity of these were 90.1%, 91.7%, and 95.5%, and 84.3%, 86.8%, and 91.2%, respectively. The PPV of these were 24.8%, 40.5%, and 72.7%, and 21.7%, 38.0%, and 65.2%, respectively. The NPV of these were 96.7%, 92.6%, and 81.2%, and 97.8%, 94.7%, and 83.7%, respectively.ConclusionHeavy and binge drinking did not show enough diagnostic power to screen DSM alcohol use disorder although they did show high specificity and NPV.

Background: This research investigated the usefulness of heavy drinking standards of 'guidelines for moderate alcohol drinking amount for Koreans' for diagnosis of Diagnostic and Statistical Manual of Mental Disorders 5th edition (DSM-5) alcohol use disorder. Methods: This retrospective study was conducted with 976 adults who visited an health screening center in Daejeon for health check-up in 2015. Daily drinking amount, drinking frequency per week, and weekly drinking amount were investigated. Using the heavy drinking criteria of Korean guideline, participants were grouped by age and gender and classified as normal or heavy drinkers. The sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), Positive likelihood ratio (LR+), Negative likelihood ratio (LR-), odds ratio (OR) and Youden's Index of heavy drinking according to Korean guideline for diagnosis of DSM-5 alcohol use disorder were calculated. Results: The Area under the receiver operating characteristic (ROC) curve of a model screening DSM-5 alcohol use disorder by weekly drinking amount were 0.812 in males up to age 65 years and 0.931 in males over age 65 years and females respectively. The sensitivity, specificity, PPV and NPV of Korean guideline heavy drinking group for diagnosis of DSM-5 alcohol use disorder were 61.0%, 89.7%, 67.0%, and 87.05% respectively. The LR+, LR-, OR and Youden's Index of those were 5. 917 (4.704-7.435), 0.434 (0.379-0.497), 13.623 (9.607-19.317

Objectives This study tried to explore the direction of language network analysis-related research in the field of special education in the future by analyzing the trends of studies using language network analysis methods in the field of special education in Korea. Methods For this purpose, 28 studies using language network analysis in the domestic special education field were analyzed from 2007 to June 2022. Based on previous research, the analysis criteria were set as ‘year of publication and published journal, research topic, analysis tool, visualization analysis method, and analysis index’. Results As a result of the study, it was found that the largest number of studies were conducted in ‘Special Education Rehabilitation Science Research’ and ‘Intellectual Disability Research’. was found to have been carried out. In addition, most of the research was conducted on the subject of research trend and knowledge structure analysis, and it was found that the majority of collected texts were articles published in academic journals. As a network analysis tool, ‘UCINET’ was used the most, and the most studies that visualized the results through a network map were the most. In all 28 papers to be analyzed, the centrality scale was used as an analysis index, and methods such as clustering and ego network analysis were also used. Conclusions These results have significance in providing a direction for conducting language network research in the field of special education in the future, and the need for continuous expansion of qualitatively more diverse topics, as well as network analysis tools, visualization presentation methods, and analysis suitable for research purposes and topics. The necessity of presenting the research results abundantly using indicators was suggested.