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고혈압, 당뇨, 뇌졸중 유병률에 대한 지역적 공간 자기상관 분석: 한국의 사례에 대하여

Other Titles
 Local Spatial Autocorrelation Analysis of 3 Disease Prevalence: A Case Study of Korea 
Authors
 주성하  ;  노주환  ;  김창수  ;  허준 
Citation
 Journal of Health Informatics and Statistics (보건정보통계학회지), Vol.42(4) : 301-308, 2017 
Journal Title
 Journal of Health Informatics and Statistics (보건정보통계학회지) 
ISSN
 2287-3708 
Issue Date
2017
Keywords
Hypertension ; Diabetes ; Stroke ; Disease prevalence ; Local spatial autocorrelation
Abstract
Objectives: This study aims to derive correlation between disease prevalence and geographical adjacency, by using global and local autocorrelation. Methods: In order to derive the correlation, data provided by community health survey was utilized. The data contains disease prevalence rate for hypertension, diabete mellitus, stroke in 2012, covering the whole South Korea. Global autocorrelation analysis was implemented to derive the spatial characteristics of each disease prevalence rate, and local autocorrelation analysis was implemented to derive local spatial patterns of each disease prevalence rate. All the results are visualized into disease prevalence map. Results: All three diseases had significant spatial autocorrelation, and unique local clustering patterns were derived when local autocorrelation analysis was conducted. Spatial outliers, where disease prevalence rate was significantly different, were found and analyzed accordingly. Conclusions: The result of the study brought new insight towards spatial patterns of disease prevalence rate. The patterns of each diseases were unique, and spatial adjacency factor was found to be a grave influential factor in terms of disease prevalence rate. Also outlier regions, where disease prevalence rate is critically higher or lower and adjacent regions, were used for further analysis to figure out the reasons for disease prevalence. This study allows understanding of spatial characteristics of disease prevalence rate, thus enabling the spatial factors to be considered in terms of disease causation analysis, which can aid in decision making and resolving unbalanced medical service of community.
Files in This Item:
T201705630.pdf Download
DOI
10.21032/jhis.2017.42.4.301
Appears in Collections:
1. College of Medicine (의과대학) > Dept. of Preventive Medicine and Public Health (예방의학교실) > 1. Journal Papers
Yonsei Authors
Kim, Chang Soo(김창수) ORCID logo https://orcid.org/0000-0002-5940-5649
Noh, Juhwan(노주환) ORCID logo https://orcid.org/0000-0003-0657-0082
URI
https://ir.ymlib.yonsei.ac.kr/handle/22282913/161714
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