• Korean Journal of Community Nutrition
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• v.4 no.2
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• pp.157-165
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• 1999

This study was conducted to identify the determinants of regional body fat distribution of obesity(upper body obesity and lower body obesity) for adolescents. The macronutrient consumption pattern utilized the most important variables to test for potential determinants. A total of 726 adolescents living in rural areas in Korea had been observed for four years from 1992 to 1996 about their diet, sexual maturation, serum components and physical growth. The study design was similar to that of a case control study. Logistic regression analysis were used as an analytical method to identify the determinants of upper body obesity and lower body obesity. Odd ratios were estimated from the regression to identify the determinants of upper body obesity and lower body obesity. Odd ratios were estimated from the regression to identify the risk factors. Fat consumption pattern was the most frequent one among the three macronutrient consumption pattern of carbohydrate, fat and protein. Prevalence of obesity for the subjects was 9.5%. Prevalence of upper body obesity was higher in malestudents than in female students. On the other had, prevalence of lower body obesity was higher in females. The results of the logicstic regression analysis showed that the risk factor for upper body obesity was sexual maturity rather than dietary factors. None of the factors included in the analysis for lower body obesity appear to be the risk factor. The result may suggest that to develop a determinant model for obesity of adolescents, the model should include a wider range of variables other than diet, sexual maturity and changes in blood serum.

• Korean Journal of Remote Sensing
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• v.4 no.1
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• pp.49-60
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• 1988

Principal Component Analysis (PCA) was applied for regional geological mapping to a multivariate data set of the Landsat TM data in the heavily vegetated and topographically rugged Chungju area. The multivariate data set selection was made by statistical analysis based on the magnitude of regression of squares in multiple regression, and it includes R1/2/R3/4, R2/3, R5/7/R4/3, R1/2, R3/4. R4/3. AND R4/5. As a result of application of PCA, some of later principal components (in this study PC 3 and PC 5) are geologically more significant than earlier major components, PC 1 and PC 2 herein. The earlier two major components which comprise 96% of the total information of the data set, mainly represent reflectance of vegetation and topographic effects, while though the rest represent 3% of the total information which statistically indicates the information unstable, geological significance of PC3 and PC5 in the study implies that application of the technique in more favorable areas should lead to much better results.

• Korea Journal of Hospital Management
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• v.22 no.3
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• pp.46-60
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• 2017

The purpose of this study is to analyze the difference of productivity according to environmental factors among 25 Regional base public hospitals. Also this study is to propose a method to improve the productivity of Regional base public hospitals in the future by improving the public performance and stable management performance by studying the productivity variables affecting profitability. The survey period was based on the last three years, and 25 Regional base public hospitals were selected for the survey. The dependent variable is the total capital medical marginal profitability and the medical profit marginal profitability which are the indicators of profitability. The independent variable, productivity, is classified into three indicators: capital productivity, labor productivity, and value added productivity. The ANOVA analysis method was used to analyze the productivity difference according to the frequency factor and the environmental factors of the Regional base public hospitals. Finally, we conducted a hierarchical regression analysis to examine the productivity variables affecting profitability. The results of this study showed that there were differences in productivity due to environmental factors such as hospital size, competition in the local medical market, and differences in management performance. The difference in productivity and profitability depending on the environmental factors suggests that it is difficult for Regional base public hospitals in each regional base to perform a balanced public service. In order to overcome this, it is necessary to provide balanced medical services such as government financial support expansion, regional medical demand forecasting and facility infrastructure construction.

• Journal of Digital Convergence
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• v.20 no.4
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• pp.469-482
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• 2022

The purpose of this study is to analyze regional variation factors of hypertension treatment rate in COVID-19 based on the analysis results based on ecological methodology. To this end, data suitable for ecological analysis were collected from the Korea Centers for Disease Control and Prevention's regional health statistics, local government COVID-19 confirmed cases, National Health Insurance Corporation, Health Insurance Review and Assessment Service's welfare statistics, and Korea Transport Institute's traffic access index. Descriptive statistics and correlation analysis were conducted using SPSS Statistics 23 for regional variation and related factors in hypertension treatment rate, and geographical weighted regression analysis was conducted using Arc GIS for regional variation factors. As a result of the study, the overall explanatory power of the calculated geo-weighted regression model was 27.6%, distributed from 23.1% to 33.4% by region. As factors affecting the treatment rate of hypertension, the higher the rate of basic living security medical benefits, diabetes treatment rate, and health institutions per 100,000 population, the higher the rate of hypertension treatment, the lower the number of COVID-19 confirmed patients, the lower the rate of physical activity, and the alcohol consumption. Percentage of alcohol consumption decreased due to COVID-19 pandemic. It was analyzed that the lower the ratio, the higher the treatment rate for hypertension. Based on these results, the analysis of regional variables in the treatment rate of hypertension in COVID-19 can be expected to be effective in managing the treatment rate of hypertension, and furthermore, it is expected to be used to establish community-centered health promotion policies.

• Journal of Korean Society of Rural Planning
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• v.20 no.1
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• pp.127-134
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• 2014

This study, in order to complement instability of analysis result stemming from the choice between reference point and comparison point which is pointed out as the defect of shift-share analysis, conducted shift-share analysis using Gross Regional Domestic Product (GRDP) trend of Geumgang area, Chungcheongnam-do for the period from 2000 to 2011. As a result of the analysis, (1) industries that had both the positive Regional Share Effect (RSE) and Industrial Mixed Effect (IME) were service industries such as manufacturing industry, electricity gas, transportation industry, art, etc., which are positively influencing the regional industry. (2) industries that had both the negative RSE and IME were other service industries such as wholesale and retail businesses, lodging industry, food industry, real estate business and leasing service, business service industry, public administration, etc., which provide basic livelihood services for the residents. (3) industries that had the positive RSE and negative IME were agriculture, forestry and fishery industry, mining industry, construction industry, and educational service industry. (4) industries that had the negative RSE and positive IME were info-communications industry, financial and insurance businesses, health industry, etc.

• Health Policy and Management
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• v.24 no.2
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• pp.143-152
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• 2014

Background: Previous studies showed that the characteristics of population and regions were related to the suicide rates. This study purposed to analyze the relationships between regional factors and suicide rates with spatial analysis model. Methods: This is a cross sectional study based on the statistics of 2011 which was extracted from the 229 City Gun Gu administrative districts in Korea. Cause of death statistics on each district was used to produce the age-, sex-adjusted mortality rates resulting from suicide. Regional characteristics were measured by the number of doctors engaged in medical institutions per 1,000 population, divorced people's rate per 1,000 population, number of marriages per 1,000 population, and percent of welfare budget in general accounting. Statistical analysis was performed by using SAS ver. 9.3 and ArcGIS ver. 10.2 was used for geographically weighted regression (GWR). Results: In ordinary least square (OLS) regression, divorced people's rate per 1,000 population had a significant positive relationship with the standardized mortality rate per 100,000 population. Marriages per 1,000 population and the proportion of welfare budget in the general accounting had significant negative relationships with the mortality rates. Meanwhile, GWR provided that the directions of variable, divorced people's rate per 1,000 population, were varied depending on regions. The adjusted $R^2$ was improved from the 0.32 in OLS to the 0.46 in GWR. Conclusion: Results of GWR showed that regional factors had different effects on the suicide rates depending on locations. It suggested that policy interventions for reducing the suicide rate should consider the regional characteristics in obtaining policy objectives.

• Journal of Korean Foot and Ankle Society
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• v.23 no.3
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• pp.121-130
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• 2019

Purpose: To investigate the spatial distribution of diabetes-related lower limb amputations and analyze the relationship between the spatial distribution of diabetes-related lower limb amputations and regional factors. Materials and Methods: This study was performed based on the data from the Korean Health Insurance Review and Assessment Service, in 2016. The unit of analysis was the administrative districts of city·gun·gu. The dependent variable was the age- and sex-adjusted incidence of diabetes-related lower limb amputations and the regional variables were selected to represent two aspects: socioeconomic factors, and health and medical factors. Along with traditional ordinary least square (OLS) regression analysis, geographically weighted regression (GWR) was applied for spatial analysis. Results: The age- and sex-adjusted incidence of diabetes-related lower limb amputation varied according to region. OLS regression showed that the incidence of diabetes-related lower limb amputation had significant relationships with the health and medical factors (number of healthcare institution and doctors per 100,000 population). In GWR, the effects of regional factors were not consistent. Conclusion: The spatial distribution of the incidence of diabetes-related lower limb amputations and the effects of regional factors varied according to the regions. The regional characteristics should be considered when establishing health policy related to diabetic foot care.

• Journal of the Korean Regional Science Association
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• v.40 no.2
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• pp.21-38
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• 2024

Understanding the interrelationship between regional population dynamics and cultivated land is crucial for promoting regional economic vitality and enhancing food security. While prior research often addressed population migration and changes in crop area separately, this study employs a Panel Vector Auto Regression Model to examine the dynamic interaction between regional population shifts, changes in crop area, and the influx of foreign workers in agriculture. The results reveal a reciprocal relationship between population influx and crop area, indicating a negative impact on each other. Moreover, the analysis demonstrates that an expansion in crop area, particularly in field cultivation, significantly correlates with an increase in foreign workers. These findings underscore the mutual influence of labor shortages and diminished land availability in agriculture, with the influx of foreign workers potentially offering a positive impact on addressing structural challenges in rural areas.

• 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.

• Health Policy and Management
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• v.29 no.4
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• pp.482-495
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• 2019

Background: An important function of the regional public hospital is to satisfy the basic medical needs of the community through the stable provision of high-quality medical services. The purpose of this study was to identify the relevance index (RI) of the regional public hospital and to identify the factors that affect the RI. Methods: Data were obtained from the 2017 regional public hospital operation evaluation report and 2017 medical monitoring report for vulnerable area. RI of the regional public hospital was a dependent variable, and multiple regression analysis was performed with observed variables of medical supply-demand condition, medical supply, and medical supply structure. Direct effects and indirect effects were confirmed by the analysis of structural equation models (SEM) to see if there were mediating effects. Results: The RI was 13.1%, and the average of all percentage refined diagnosis-related group (RDRG) was 29.4%. Factors affecting RI were medical supply-demand conditions, medical supply, and medical supply structure. As a result of multiple regression analysis, RI was higher when high percentage RDRG of the regional public hospital (t=4.117, p<0.05), the size of regional public hospital location (t=-2.554, p<0.05), and the population of regional public hospital location (t =-2.415, p<0.05) were smaller. The results of the SEM analysis show that the higher the medical supply-demand conditions, the more direct effect of decreasing the RI and the indirect effect of decreasing the effect of reduction through the medical supply (direct effect=-1.322, total effect=-0.573, p<0.01). The higher the medical supply structure, the more direct effect on the RI (direct effect=1.047, p<0.05) and the higher the medical supply, the more indirect effect of RI through the medical supply structure (total effect=direct effect=0.619, p<0.05). Conclusion: It has been confirmed that the provision of medical services can affect the RI the regional public hospital which should be considered in carrying out future policies.