• Journal of the Korean Geographical Society
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• v.49 no.6
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• pp.935-948
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• 2014

As chronic diseases have become more prevalent and problematic, effective cares for major chronic diseases have been a locus of the healthcare policy. In this regard, this study examines how region-specific characteristics affect the prevalence of hypertension in South Korea. To analyze, we combined a unique multi-year data set including key indicators of health conditions and health behaviors at the 237 small administrative districts. The data are collected from the Annual Community Health Survey between 2009 and 2011 by Korea Centers for Disease Control and Prevention and other government organizations. For the purpose of investigating regional variations, we estimated using Geographically Weighted Regression (GWR) and decision tree model. Our finding first suggests that using the multi-year data is more legitimate than using the single-year data for the geographical analysis of chronic diseases, because the significant annual differences are observed in most variables. We also find that the prevalence of hypertension is more likely to be positively associated with the prevalence of diabetes and obesity but to be negatively associated with population density. More importantly, noticeable geographical variations in these factors are observed according to the results from the GWR. In line with this result, additional findings from the decision tree model suggest that primary influential factors that affect the hypertension prevalence are indeed heterogeneous across regional groups. Taken as a whole, accounting for geographical variations of health conditions, health behaviors and other socioeconomic factors is very important when the regionally customized healthcare policy is implemented to mitigate the hypertension prevalence. In short, our study sheds light on possible ways to manage the chronic diseases for policy makers in the local government.

• Journal of Digital Convergence
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• v.17 no.1
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• pp.403-412
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• 2019

The purpose of this study is to analyze temporal and spatial variations of atopic dermatitis and to identify major factors. Data utilized in the study were collected by the Community Health Survey, KOSIS and so and on from 2009 to 2013. This study was analyzed using descriptive statistics and Geographically weighted regression model. As a result, regional diagnosis rate of atopic dermatitis was increased by 5 years, and difference related to geographic location was so large. The regional characteristics that contribute to the diagnosis of atopic dermatitis were as follows: older adults population ratio, ratio of basic living security received people, depression experience rate, high risk drinking rate, number of wastewater discharge business, number of tobacco retail business, number of fast food restaurant business. This study is meaningful in that it provided basic data on health policy direction and provided information on prioritization of health business in each region.

• The Journal of the Korea Contents Association
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• v.16 no.7
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• pp.207-220
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• 2016

Paradigm for supporting housing for low-middle income class has been changing from public rental housing to Housing Voucher. Housing Voucher started first in Seoul since 2010, and it has been expended to other areas in 2014. Given the dearth of previous research data, this study aims to analyze options determinants that the beneficiaries could consider in choosing their residential area. In this study, the researcher used for the research methods, a quantitative analysis by Geographically Weighted Regression (GWR) and Ordinary Least Square (OLS) has been conducted. As a result, the accessibility to social welfare centers, public transportation and job opportunities emerged main factors to for the Housing Voucher recipients in Seoul to choose their residential area. This is different results from previous research, which has two implications. First, reexamination of Housing Voucher is necessary. Second, Housing Voucher beneficiaries should include not only the housing but also support for family and welfare system access.

• Journal of Korean Society for Geospatial Information Science
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• v.22 no.1
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• pp.41-46
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• 2014

Bus service is easily adjusted to accommodate the changed demand. Despite the flexibility of that, its relocation should overcome the following problems: first, Bus line rearrangement should consider the balance between the demand and the supply to enhance the transit equity among the users scattered around the area that supply against demand imbalances. Second, the existing demand analysed is to crude since the demand was analysed based on TAZ. mainly based on the Dong unit. Utilization of the GWR and GIS-T data can resolve the problem. In this paper, the limitation of the conventional transit demand analysis model is overcome by deploying the GWR model which identifies the transit demand based on the geographic relation between the service location and those of the users. GWR model considers the spatial effect of the bus demand in accordance with the distance to the each bus stops using SCD(Smart Card Data) and BIS(Bus Information System). This demand map was then superimposes with the existing bus route which identified the areas where the balance between demand and supply is severly skewed. since the analysis was computed with SCD and BIS at every bus stops. the shortage and surplus of bus service of entire study area could computed. Further. based on this computational result and considering the entire bus service capacity data. Bus routes optimization from the oversupplied areas to the undersupplied area was illustrated thus this study clearly compared the benefits the GIS.

• Journal of Cadastre & Land InformatiX
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• v.48 no.1
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• pp.169-186
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• 2018

The social influence of the elderly population will accelerate in a rapidly aging society. The purpose of this study is to establish a methodology for extracting vulnerable districts of the welfare of the aged through machine learning(ML), artificial neural network(ANN) and geospatial analysis. In order to establish the direction of analysis, this progressed after an interview with volunteers who over 65-year old people, public officer and the manager of the aged welfare facility. The indicators are the geographic distance capacity, elderly welfare enjoyment, officially assessed land price and mobile communication based on old people activities where 500 m vector areal unit within 15 minutes in Yongin-city, Gyeonggi-do. As a result, the prediction accuracy of 83.2% in the support vector machine(SVM) of ML using the RBF kernel algorithm was obtained in simulation. Furthermore, the correlation result(0.63) was derived from ANN using backpropagation algorithm. A geographically weighted regression(GWR) was also performed to analyze spatial autocorrelation within variables. As a result of this analysis, the coefficient of determination was 70.1%, which showed good explanatory power. Moran's I and Getis-Ord Gi coefficients are analyzed to investigate spatially outlier as well as distribution patterns. This study can be used to solve the welfare imbalance of the aged considering the local conditions of the government recently.

• Journal of Digital Convergence
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• v.13 no.1
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• pp.353-366
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• 2015

The purpose of this study was to examine how region-specific characteristics affect the occurrence of cardiac arrest. To analyze, we combined a unique data set including key indicators of health condition and cardiac arrest occurrence at the 244 small administrative districts. Our data came from two main sources in Korea Center For Disease Control and Prevention (KCDC): 2010 Out-of-Hospital Cardiac Arrest Surveillance and Community Health Survey. We analyzed data by using multiple regression, geographically weighted regression and decision tree. Decision tree model is selected as the final model to explain regional variations of cardiac arrest. Factors of regional variations of cardiac arrest occurrence are population density, diagnosis rates of hypertension, stress level, participating screening level, high drinking rate, and smoking rate. Taken as a whole, accounting for geographical variations of health conditions, health behaviors and other socioeconomic factors are important when regionally customized health policy is implemented to decrease the cardiac arrest occurrence.

• Journal of the Korean Association of Geographic Information Studies
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• v.15 no.2
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• pp.35-45
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• 2012

Existing studies on land values tend to show the use of simple euclidean distances as the accessibility variable and OLS as the analysis method. However, applying such euclidean distance-based accessibility to dense CBD areas has limitations in the incorporating the characteristics of network structure whereas using OLS, the typical method for non-spatial data, tends to exclude spatial effects of spatial data. In this study, we analyzed land values focusing on the revised accessibility variables and the analytical technique that can include spatial effects. First, we adopted space syntax theory in order to consider not simple shortest distances along the streets but distances based on street network structure. Second, we compared OLS with GWR that includes spatial effects. Third, we used different size grid-cells for the spatial units considering MAUP theory and applied them to Gangnam-gu area. Each cell was analyzed for overall influence of independent variables using OLS, and coefficients were presented by GWR which enables local analysis and visualization. As a result, we found that suggested accessibility variables have a meaningful effects for land value analyses, and we were able to verify that GWR produces improved results compared to OLS. Also, we observed that the resulting values vary depending on the sizes of spatial units.

• Journal of Korean Society of Rural Planning
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• v.23 no.3
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• pp.13-20
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• 2017

본 연구는 가나의 비료 보조금 정책(Fertilizer subsidy program: FSP)의 농업 생산성에 대한 영향을 분석하였다. 가나의 군(district) 지역 수준의 농업 생산량 및 투입요소에 대한 자료를 사용하여, FSP 도입 이전과 FSP 도입 이후의 농업 생산성을 계측하였다. 지역적으로 상이한 수준의 농업 생산성을 반영하기 위한 지리적가중회귀(GWR)모형을 사용하여 계측의 오류를 줄이고 공간이질성을 고려하였다. 추정 결과를 바탕으로 ArcMap을 이용하여 생산성을 지도로 시각화 한 자료를 살펴보면, FSP 도입 이후 농업 생산성이 전반적으로 개선되었으며 그 중에서도 생산성이 크게 향상된 지역을 특정할 수 있다. 이러한 공간적 변화는 FSP의 지역적 할당의 효율성 증진을 위한 의사결정 자료로 이용 가능하며, 국내 ODA 추진기관에서 농업 지도 및 지원을 위해 유용한 정보로 사용할 수 있다.

• Journal of Dental Rehabilitation and Applied Science
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• v.31 no.4
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• pp.283-293
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• 2015

Purpose: The aims of this study are to analyze and to visualize distribution of patients visiting at a dental college hospital, using geographic information system (GIS). The visualized data can be utilized in patient care and treatment planning, ultimately leading to the assessment of risk evaluation and prevention of dental diseases. Materials and Methods: Patient information data was obtained from Dankook University Dental Hospital including the unit number, gender, date of birth, and address from 2007 to 2014. Patient distribution was visualized using GIS. Statistical analyses were performed using SAS 9.3 and ArcGIS 10.1. Five factors including proximity, accessibility, age, gender, and socioeconomic status were investigated as the explanatory variables of the patient distribution. Results: The visualized patient data showed a nationwide scale of the patient distribution. There was a little difference in characteristics for each department. As closer at Dankook University Dental Hospital, visitors increased. And it strongly showed that elderly patients in rural areas tend to visit more. Conclusion: The distribution of patients has been shown to be significantly affected by the proximity, accessibility, age, gender and socioeconomic status. The underlying reason remains to be further studied.

• Journal of Korean Academy of Nursing
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• v.53 no.4
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• pp.426-438
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• 2023

Purpose: Walking practice is a representative indicator of the level of physical activity of local residents. Although the world health organization addressed reduction in prevalence of insufficient physical activity as a global target, the rate of walking practice in Korea has not improved and there are large regional disparities. Therefore, this study aimed to explore the spatial variations of walking practice and its associated factors in Korea. Methods: A secondary analysis was conducted using Community Health Outcome and Health Determinants Database 1.3 from Korea Centers for Disease Control and Prevention. A total of 229 districts was included in the analysis. We compared the ordinary least squares (OLS) and the geographically weighted regression (GWR) to explore the associated factors of walking practice. MGWR 2.2.1 software was used to explore the spatial distribution of walking practice and modeling the GWR. Results: Walking practice had spatial variations across the country. The results showed that the GWR model had better accommodation of spatial autocorrelation than the OLS model. The GWR results indicated that different predictors of walking practice across regions of Korea. Conclusion: The findings of this study may provide insight to nursing researchers, health professionals, and policy makers in planning health programs to promote walking practices in their respective communities.