Background/Objectives: The purpose of this study is to provide basic data for nursing mediation program by grasping the factor that influence pain of osteoarthritis patients with depression. Methods/Statistical Analysis: The original data of ‘The 5th, 3rd year Korea National Health and Nutrition Examination Survey’ was used for this study. The 2012 national survey conducted by Ministry of Health and Welfare and Centers for Disease Control and Prevention, had total 8058 subjects and this study was conducted with 132 subjects who answered ‘yes’ in the question, asking about whether having osteoarthritis current or not and whether having depression or not. Findings: Subjective health status significantly correlated with stress (r = -.23, p = .006), walking time (r = .17, p = .044) and perceived level of pain (r = .33, p = .003). A significant correlation was also found between BMI and sleep hours (r = -.20, p = .019) and between BMI and perceived level of pain (r = .25, p = .025). To identify the explanation power of factors affecting pain, a linear regression analysis was conducted with pain of OA patients with depression as an independent variable and general variables, subjective health status, stress, walking duration, BMI, sleeping time, dining times, as dependent variables. The subjective health status (β = 0.331, p = .009) had an impact on the pain level with an explanatory power of 17.8%. Application/Improvements: Strategies that take into account perceptions of subjective health status are important for the development of targeted interventions aimed at reducing pain.

Factors Influencing the Experience of Pain in Depressed Patients with Osteoarthritis- Using Data from the Korean National Health and Nutrition Examination Survey

Objectives: India is one of major contributors to global burden of tuberculosis which alone accounted for an estimated one quarter (26%) of all tuberculosis cases worldwide. The estimation of disease burden of tuberculosis is a challenge, considering its varied epidemiology and dynamics of transmission. As true disease burden cannot be estimated with count data therefore, statistical modelling techniques have been employed to analyze the disease burden in terms of prevalence of tuberculosis among males and females. Methods: An attempt has been made to predict gender bias in the prevalence of tuberculosis. The statistical models for both male and female tuberculosis positivity are developed on the information taken from NHFS (2015-16). The gender wise prevalence of tuberculosis has been compared by considering different indicators. In our analysis, the binary logistic regression model has been used by considering some factors to know their impact on prevalence of the tuberculosis. Results: Some of the variables under socioeconomic factors, Demographic Factors, Cultural factors and Health factors have shown decline their impact on prevalence of tuberculosis in males as compared females. However rests of the variables have the impact on the prevalence of tuberculosis without any variation. Conclusion: The study reveals that there are some factors which are responsible for prevalence of tuberculosis in India among male as well as in females and these factors are continuously contributing in increasing the prevalence of tuberculosis. Hence it is suggested that there is a need to redesign the policies to minimize the risk factors generated on the part of the factors having same impact on the prevalence of tuberculosis to avoid gender bias.

Logistic Regression Approach for Prediction of Gender Bias in the Prevalence of Tuberculosis in India

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Logistic Regression Approach for Prediction of Gender Bias in the Prevalence of Tuberculosis in India