• Land and Housing Review
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• v.12 no.2
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• pp.47-59
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• 2021

This study aims to review the trends of the population outflows in the metropolitan area of Busan and to investigate the factors that affect population out-migration to the Seoul metropolitan area. The following variables are considered for analysis: traditional population movement variables and quality of life variables, such as population, society, employment, housing, culture, safety, medical care, greenery, education, and childcare. The 'domestic population movement data', provided by the MDIS of the National Statistical Office, was used for this research. Out of the total of 57 million population movement data in the period 2012 - 2017, population outmigration from Busan to the Seoul metropolitan area was extracted. Independent variables were drawn from public data sources in accordance with the temporal and spatial settings of the study. The multiple linear regression model was specified based on the dataset, and the fit of the model was measured by the p-value, and the values of Adjusted R2, Durbin-Watson analysis, and F-statistics. The results of the analysis showed that the variables that have a significant effect on population movement from Busan to the Seoul metropolitan area were as follows: 'single-person households', 'the elderly population', 'the total birth rate', 'the number of companies', 'the number of employees', 'the housing sales price index', 'cultural facilities', and 'the number of students per teacher'. More positive (+) influences of the population out-movement were observed in areas with higher numbers of single-person households, lowers proportions of the elderly, lower numbers of businesses, higher numbers of employees, higher numbers of housing sales, lower numbers of cultural facilities, and lower numbers of students. The findings suggest that policies should enhance the environments such as quality jobs, culture, and welfare that can retain young people within Busan. Improvements in the quality of life and job creation are critical factors that can mitigate the outflows of the Busan residents to the Seoul metropolitan area.

• Korean Journal of Psychosomatic Medicine
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• v.25 no.2
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• pp.200-209
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• 2017

Objectives : The aim of this study was to analyze the relationship between depressive symptoms and sociodemographic factors associated with geriatric depression and insomnia and to examine the effects of these factors on depression. Methods : The severities of insomnia and depression in elderly aged 60 and older lived in Gwangmyeong city were evaluated and the related sociodemographic factors were investigated. From April 20, 2016 to December 1, 2016, Gwangmyeong city Mental Health Sevices consignment by department of psychiatry of a university-affiliated general hospital conducted surveys and interviews for total 837 elderly peoples lived in Gwangmyeong city by visiting welfare center and wards located in the city. Structured interviews were conducted using Insomnia Severity Index(ISI) and Short form-Geriatric Depression Scale(S-GDS) to examine the relationship between sociodemographic factors and the severities of insomnia and depression. Results : There were significant differences in S-GDS mean scores and age(below 70 years old, 70s, 80s, above 90 years old), type of health care(health insurance, medical aid), type of residency(own, not own) and marital status(single, married, divorced or widowed).There was a significant difference in education level, especially between not educated(and/or) elementary graduates and college graduate(F=3.227, p=0.012). Also, there were significant differences in age, type of health care, type of residency, number of household on divided S-GDS score above and below 10 scores(p<0.05). Insomnia measured by ISI was not significantly associated with sociodemographic factors(p>0.05), but was significantly associated with depressive symptoms(p<0.05). These findings suggest more severe insomnia symptom indicated the higher probability of depression and elderly with depressive symptoms had more severe insomnia. Conclusions : Geriatric depression has significant relationships with age, type of health care, type of residency, marital status, education and number of households. In addition, insomnia which is main symptom of depression in elderly, has important role in predicting the severity and diagnosis of depression.

• Health Policy and Management
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• v.34 no.2
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• pp.141-155
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• 2024

Background: This study aimed to identified the relationship between the risk of obstructive sleep apnea, subjective health, and health-related quality of life among the middle-aged and elderly population in Korea. Methods: Adults aged 40 or older were extracted from the total 22,559 respondents to the 2019-2020 Korea National Health and Nutrition Examination Survey VIII, and secondary analysis was conducted on a total of 6,659 middle-aged and elderly people with no missing values. Logistic regression analysis and multiple regression analysis were conducted to examine the relationship between obstructive sleep apnea risk factors and subjective health as well as quality of life. Results: The subjective health status decline in the high-risk group compared to the non-risk group for obstructive sleep apnea was statistically significantly higher, with an odds ratio of 1.84 (p<0.001). The health-related quality of life was also statistically significantly lower by 0.02 points (β, -0.02; p<0.001). As a result of subgroup analysis on specific variables, the association between the risk of obstructive sleep apnea and subjective health and health-related quality of life was statistically significant depending on gender, sleep time, presence of depression, household income, and number of household members. Based on the obstructive sleep apnea risk group, women had a higher correlation with low subjective health and lower health-related quality of life scores than men. Sleeping time of more than 8 hours or less than 6 hours was more associated with low subjective health and lower health-related quality of life score than sleeping time of 6-8 hours. Patients with depression were more likely to have low subjective health than those without depression. The lower the household income level and the smaller the number of household members, the higher the association with low subjective health and the lower the health-related quality of life score. Conclusion: It is essential to recognize that the risk of obstructive sleep apnea not only directly affects sleep disorders but also impacts individuals' subjective health and quality of life. Consequently, social support and education should be provided to raise awareness of this issue. Particularly, programs for preventing and managing obstructive sleep apnea should target vulnerable groups such as women, individuals in single-person households, low household income, and those with depression, aiming to improve their subjective health and quality of life.