• Journal of the Korean Regional Science Association
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• v.35 no.4
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• pp.61-73
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• 2019

Urban development and densification have led to the Urban Heat Island Effect, in which the temperature of urban space is higher than the surrounding areas, and the intensity is increasing with climate change. In addition, when the city's air temperature rises in summer, low-income, elderly population, and socially vulnerable people who have health problems lack the ability to cope with the elevated heat environment. Therefore, this study aimed to identify the urban heat island area of Seoul through Hotspot analysis, which is a spatial statistics technique, and explored physical environments, demographic and socioeconomic characteristics of urban heat island effect areas using logistic regression models. This study performed urban heat island hotspot analysis using the average air temperatures of the 423 administrative dongs in Seoul. Analysis results identified that the urban heat islands were concentrated in Jung-gu, Jongno-gu, Yongsan-gu, and Yeongdeungpo-gu. Logistic regression analysis results indicated that urban heat island areas of Seoul were affected by residential floor area ratio, commercial facility floor area ratio, overall floor area ratio, impervious surface ratio, and normalized difference vegetation index(NDVI). In addition, as a result of analyzing the vulnerable area of thermal environment considering the demographic and socioeconomic characteristics of the heat island area, urban heat island areas of Seoul were significantly associated with the proportion of low-income elderly living alone. The result of this study provided useful insights for urban thermal environmental design and policy development that could improve the thermal environment for the socially disadvantaged urban population.

• Therapeutic Science for Rehabilitation
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• v.10 no.2
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• pp.75-93
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• 2021

Objective : The aim of this study was to identify subgroups of older adults with respect to their lifestyle patterns and examine the characteristics of each subgroup in order to provide a basic evidence for improving the health and quality of life. Methods : This cross-sectional study was conducted in South Korea. Community-dwelling older adults (n=184) above the age of 65 years were surveyed from April 2019 to May 2019. This study used latent profile analysis to examine the subgroups. Chi-squared (χ²) and multinomial logistic regression measures were then used to analyze individual characteristics and influencing factors. Results : The pattern of physical activity which is one of the lifestyle domains in elderly was categorized into three types: 'passive exercise type (31.1%)', 'low intensity exercise type (54.5%)', and 'balanced exercise type(14.5%)'. Activity participation was divided into three patterns: 'inactive type (12%)', 'self-management type (61%)', and 'balanced activity participation type (27%)'. In terms of nutrition, there were only two groups: 'overall malnutrition type (13.5%)' and 'balanced nutrition type (86.5%)'. Furthermore, as a result of the multinomial logistic regression analysis to understand the effects of lifestyle types on the health and quality of life of the elderly, it was confirmed that the health and quality of life were higher in those following an active and balanced lifestyle. In addition, gender, education level and residential area were analyzed as predictive factors. Conclusion : The health and quality of life of the elderly can be improved when they have balanced lifestyle. Therefore, an empirical and policy intervention strategy should be developed and implemented to enhance the health and quality of life of the elderly.