Spatial autocorrelation of disease prevalence in South Korea using 2012 community health survey data

Won Seob Oh, Cong Hieu Nguyen, Sang Min Kim, Jung Woo Sohn, Joon Heo

Research output: Contribution to journalArticle

2 Citations (Scopus)

Abstract

As a basic research to investigate geographical variations of diseases, this study analyzes and compares spatial patterns of 24 different diseases in South Korea using prevalence rate data provided by Community Health Survey in 2012. Descriptive statistical analysis, global Moran's I computation, and disease mapping were conducted to examine spatial associations and patterns of each disease. After the unique spatial patterns and distinctive spatial associations of each disease were observed, we concluded that 12 diseases displayed statistically significant spatial autocorrelation while the other 12 showed no spatial associations. This study suggests that diseases are caused by different risk factors and possess different etiological mechanisms. Furthermore, the study may lay foundation for future studies of geographical variations of disease prevalence in South Korea.

Original languageEnglish
Pages (from-to)253-262
Number of pages10
JournalJournal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
Volume34
Issue number3
DOIs
Publication statusPublished - 2016 Jun

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disease prevalence
health survey
autocorrelation
geographical variation
risk factor
statistical analysis

All Science Journal Classification (ASJC) codes

  • Earth and Planetary Sciences(all)

Cite this

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abstract = "As a basic research to investigate geographical variations of diseases, this study analyzes and compares spatial patterns of 24 different diseases in South Korea using prevalence rate data provided by Community Health Survey in 2012. Descriptive statistical analysis, global Moran's I computation, and disease mapping were conducted to examine spatial associations and patterns of each disease. After the unique spatial patterns and distinctive spatial associations of each disease were observed, we concluded that 12 diseases displayed statistically significant spatial autocorrelation while the other 12 showed no spatial associations. This study suggests that diseases are caused by different risk factors and possess different etiological mechanisms. Furthermore, the study may lay foundation for future studies of geographical variations of disease prevalence in South Korea.",
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Spatial autocorrelation of disease prevalence in South Korea using 2012 community health survey data. / Oh, Won Seob; Nguyen, Cong Hieu; Kim, Sang Min; Sohn, Jung Woo; Heo, Joon.

In: Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography, Vol. 34, No. 3, 06.2016, p. 253-262.

Research output: Contribution to journalArticle

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