• The Korean Journal of Health Service Management
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• v.8 no.2
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• pp.11-22
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• 2014

This study purposed to analyze the regional variation of the local-out rates of inpatient services. Multiple data sources collected from National Health Insurance Corporation and statistics Korea were merged to produce the analysis data set. The unit of analysis in this study was city, Gun, Gu, and all of them were included in analysis. The dependent variable measured the local-out rate of inpatient cost in study regions. Local environments were measured by variables in three dimensions: provider factors, socio-demographic factors, and health status. Along with the traditional ordinary least square (OLS) based regression model, geographically weighted regression (GWR) model were applied to test their effects. SPSS v21 and ArcMap v10.2 were applied for the statistical analysis. Results from OLS regression showed that most variables had significant relationships with the local-out rate of inpatient services. However, some variables had shown diverse directions in regression coefficients depending on regions in GWR. This implied that the study variables might not have consistent effects and they may varied depending the locations.

• Journal of Korean Academy of Nursing
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• v.53 no.1
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• pp.101-114
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• 2023

Purpose: This study aimed to identify regional differences in problem drinking among adult males in single-person households and predict the determinants. Methods: This study used data from the 2019 Community Health Survey. Geographically weighted regression analysis was performed on 8,625 adult males in single-person households who had been consuming alcohol for the past year. The Si-Gun-Gu was selected as the spatial unit. Results: The top 10 regions for problem drinking among adult males in single-person households were located in the Jeju-do and Jeollanam-do areas near the southern coast, whereas the bottom 10 regions were located in the Incheon and northern Gyeonggi-do areas. Smoking, economic activity, and educational level were common factors affecting problem drinking among this population. Among the determinants of regional disparities in problem drinking among adult males in single-person households, personal factors included age, smoking, depression level, economic activity, educational level, and leisure activity, while regional factors included population and karaoke venue ratio. Conclusion: Problem drinking among adult males in single-person households varies by region, and the variables affecting each particular area differ. Therefore, it is necessary to develop interventions tailored to individuals and regions that reflect the characteristics of each region by prioritizing smoking, economic activity, and educational level as the common factors.

• Journal of Cadastre & Land InformatiX
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• v.44 no.2
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• pp.155-175
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• 2014

This study targets to recognize needs of spatial pattern analysis and to draw the relationship between relocation of Capital Region firms and population outflow in Capital Region through the regression analysis. The population outflow in Capital Region has moved to and around Yesan-gun and Asan-si. Also, such outflow is found to compose mostly one or two household members for their jobs. In addition to this study has analyzed to find effect factors through the Geographically Weighted Regression. The results of the analysis has confirmed that the most decisive factors affecting population flow from Capital Region to Chungcheongnam-do were population factors and transportation factors and others. Thus, the below policy implications could be derived and also may be applied toward Sejong City which are currently experiencing the relocating of Public sectors and new constructions. Firstly, the effect of Capital Region firms movement on population inflows could be better observed in small-scale towns like "kun" than larger-scale towns like "si.". On the other hand, people in Capital Region moved to larger-scale towns like "si" unlike the Capital Region firms. This difference implicates that people select their residence according to not only their jobs but also residential environment. Secondly, moving people from Capital Region to another region for their jobs are expected to appear more in a form of family units rather than individual units. Sejong city, where public organizations are being relocated, should recognize this particular Chungcheonnam-do phenomenon and be prepared to be more effectively used in perspectives of land use as well as urban planning.

• Korean Journal of Remote Sensing
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• v.28 no.1
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• pp.129-143
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• 2012

This paper demonstrates the effectiveness of advanced spatial modeling techniques for environmental monitoring and impact assessment through a case study of Chernobyl nuclear accident occurred in 1986. Land-cover types changed after the accident are analysed by a post classification comparison method using bi-temporal Landsat TM data acquired in 1986 and 1992 near the accident site. Spatial modeling including various kriging algorithms are also applied to analyze the relationships between Cesium concentrations in soil and thyroid cancer incidence rates in Belarus, which was greatly damaged by the accident. The change detection results clearly showed the decrease of croplands and the increase of abandoned lands, and concrete structures were newly built around the nuclear plant to prevent the spread of radioactive contamination. In Belarus, high Cesium concentrations were observed in southern areas with high thyroid cancer risk estimated by Poisson kriging. Geographically weighted regression, which could account for geographic variations of independent variables including Cesium concentrations and distances from the Chernobyl nuclear power plant, was applied to extract the relationships between the independent variables and the thyroid cancer risk. The estimated risk values showed a correlation coefficient value of 0.98 with respect to the thyroid cancer risk values, which implied that the thyroid cancer risk in Belarus was affected by the accident. In conclusion, it is expected that advanced spatial modeling techniques applied in this study would be useful for environmental impact assessment and public health research.

• Journal of the Korean association of regional geographers
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• v.14 no.6
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• pp.736-751
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• 2008

Although a growing number of studies have commonly used a simple areal weighting interpolation method to quantify demographic characteristics of impacted areas in environmental equity analysis, the results obtained are inevitably imprecise because of the method's unrealistic assumption that population is evenly distributed within a census enumeration unit. Two alternative areal interpolation methods such as intelligent areal weighting and regression methods can account for the distributional biases in the estimation of impacted populations by making use of additional information about the geographic distribution of population. This research explores five areal interpolation methods for estimating the population characteristics of impacted areas in environmental equity analysis and evaluates the sensitivity of the outcomes of environmental equity analysis to areal interpolation methods. This study used GIS techniques to allow areal interpolation to be informed by the distribution of land cover types, as inferred from a satellite image. in both the source and target units. Independent samples t-test statistics were measured to verify the environmental equity hypothesis while coefficients of variation were calculated to compare the relative variability and consistency in the socioeconomic characteristics of populations at risk over different areal interpolation methods. Results show that the outcomes of environmental equity analysis in the study area are not sensitive to the areal interpolation methods used in estimating affected populations, but the population estimates within the impacted areas are largely variable as different areal interpolation methods are used. This implies that the use of different areal interpolation methods may to some degree alter the statistical results of environmental equity analysis.