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This study aimed to investigate the influence of demographic and health-related characteristics on sleep duration among middle-aged women aged 44–64. Utilizing raw data from the 2022 Community Health Survey, a cross-sectional analysis was conducted. The study included middle-aged women who participated in the survey, with data collected through structured interviews. χ2 tests and logistic regression analysis were employed to assess associations between sleep duration and demographic as well as health-related factors. The findings revealed that sleep duration in middle-aged women was significantly associated with multiple factors. Age (p <.001), spouse status (p =.001), occupation (p <.001), self-rated health (p =.004), perceived stress (p <.001), depression (p <.001), cognitive impairment (p =.009), unmet medical needs (p =.034), current cigarette smoking (p =.001), and binge drinking (p =.006) were all identified as important determinants of sleep duration. The results highlight the need for targeted interventions that address both health and psychological risk factors contributing to sleep disturbances among middle-aged women. An integrated approach, considering these factors, is essential to improve sleep health in this vulnerable population. [ABSTRACT FROM AUTHOR]

COVID-19 vaccination is a critical public health measure to control the pandemic, but disparities in vaccination uptake remain a concern. This study investigates the determinants of COVID-19 vaccination among Korean adults using the Andersen model. Data from 231,784 participants in the community health survey were analyzed using chi-square testing and logistic regression. The risk of non-vaccination was higher among those aged 19–64 (95% CI: 1.52–1.74), males (95% CI: 1.11–1.24), the unemployed (95% CI: 2.21–2.47), unmarried individuals (95% CI: 1.12–1.24), those with unmet healthcare needs (95% CI: 1.41–1.67), recipients of national basic livelihood guarantees (95% CI: 1.45–1.73), those with lower subjective health (95% CI: 1.20–1.30), individuals with depression (95% CI: 1.28–1.44), current smokers (95% CI: 1.13–1.30), and those skipping breakfast (95% CI: 1.04–1.16). Conversely, the risk was lower for those with less than a high school education (95% CI: 0.72–0.81), individuals with psychological concerns about infection (0.87, 95% CI: 0.82–0.92) or public criticism (0.91, 95% CI: 0.86–0.97), individuals with chronic diseases (95% CI: 0.64–0.72), and current alcohol consumers (95% CI: 0.52–0.58). These findings underscore the need for targeted intervention strategies and support systems to promote vaccination in vulnerable populations. Further research should explore the long-term impact of these interventions on vaccination uptake. [ABSTRACT FROM AUTHOR]

Objectives: This study, utilizing data from the 2021 Korean Community Health Survey (KCHS), aimed to investigate the role of health literacy in mitigating depression among individuals with chronic diseases, particularly focusing on how sociodemographic and subjective factors influence this relationship. Methods: With a sample of 77,133 subjects primarily dealing with hypertension and diabetes, the study employed various analytical tools to identify factors associated with an increased risk of depression. Results: These factors included marital status (OR 1.47, 95% CI 1.40–1.54), residential district (OR 1.43, 95% CI 1.39–1.50), unemployment (OR 1.47, 95% CI 1.41–1.54), enrollment in the national basic living security program (OR 1.50, 95% CI 1.40–1.62), unmet healthcare needs (OR 2.32, 95% CI 2.14–2.51), fair subjective health status (OR 1.74, 95% CI 1.63–1.90), poor subjective health status (OR 4.33, 95% CI 4.05–4.63), and stress (OR 4.56, 95% CI 4.36–4.77). Notably, individuals with higher health literacy showed a significantly lower susceptibility to depression (OR 0.74, 95% CI 0.68–0.75), underscoring the importance of health literacy as a critical factor in mental health outcomes. Conclusions: Such initiatives could serve as effective preventive measures against depression in this vulnerable population. [ABSTRACT FROM AUTHOR]

This study attempted to identify the level of health literacy among older adults by applying the Andersen model and analyzing the factors affecting this level. We used the nationwide secondary data from the 2021 Korea Community Health Survey. Data obtained from 74,492 older adults aged 65 years or more were analyzed using the t-test, Pearson's correlation coefficient, and multiple regression analysis. As a result of applying the Anderson model to the health literacy ability of older adults, statistically significant variables were predisposing (age, sex, spouse), enabling (education level), and need (subjective health status) factors for health literacy. Based on the results of this study, we conclude that it is necessary to establish a public healthcare program to improve the health literacy and welfare of older adults. [ABSTRACT FROM AUTHOR]

Background: The COVID-19 pandemic caused changes in individuals' daily lives, including drinking habits. This study attempted to identify factors of Korean adolescents' current alcohol drinking due to the COVID-19 pandemic., Methods: The study used secondary data from the 17th Korean Youth Risk Behavior Web-based Survey that included 54 848 individuals. In this study, current alcohol drinking was defined as consuming at least 1 alcoholic drink per day for the past month. Changes in physical activity, mealtimes, smoking, and depressive symptoms were recorded., Results: The multiple logistic regression results show that the risk for current alcohol drinking due to the COVID-19 pandemic was 1.14 times higher in increased physical activity (95% CI: 1.04-1.25, P  = .007); 1.18 times higher in increased skipping breakfast (95% CI: 1.07-1.30, P  = .001); 1.22 times higher in decrease skipping breakfast (95% CI: 1.10-1.36, P < .001); and 15.69 times higher in increase smoking (95% CI: 12.53-19.64, P < .001)., Conclusion: It is necessary to improve social support systems and related policies for adolescents who experienced a change in daily habits due to the COVID-19 pandemic. Our results may contribute to preparing strategies and support measures to reduce drinking by developing personalized healthcare in the future., (2022 authors.)

A biosensor is composed of a bioreceptor, an associated recognition molecule, and a signal transducer that can selectively detect target substances for analysis. DNA based biosensors utilize receptor molecules that allow hybridization with the target analyte. However, most DNA biosensor research uses oligonucleotides as the target analytes and does not address the potential problems of real samples. The identification of recognition molecules suitable for real target analyte samples is an important step towards further development of DNA biosensors. This study examines the characteristics of DNA used as bioreceptors and proposes a hybrid evolution-based DNA sequence generating algorithm, based on DNA computing, to identify suitable DNA bioreceptor recognition molecules for stable hybridization with real target substances. The Traveling Salesman Problem (TSP) approach is applied in the proposed algorithm to evaluate the safety and fitness of the generated DNA sequences. This approach improves efficiency and stability for enhanced and variable-length DNA sequence generation and allows extension to generation of variable-length DNA sequences with diverse receptor recognition requirements.