본문 바로가기
  • Home
Basic Search

Analysis of Association between Cancer Incidence and Geographical and Environmental Characteristics using Spatial Statistical Techniques

  • Journal of the Korean Cartographic Association
  • Abbr : JKCA
  • 2019, 19(3), pp.57~74
  • Publisher : The Korean Cartographic Association
  • Research Area : Social Science > Geography > Geography in general > Cartography
  • Received : December 3, 2019
  • Accepted : December 18, 2019
  • Published : December 31, 2019

Suk-Ho Lee 1,  Kamyoung Kim 2

1구천중학교
2경북대학교

Accredited

ABSTRACT

Cancer has long been the leading cause of death for Koreans, mainly due to environmental factors. Despite the high mortality caused by cancer, Korean studies on how geographical and environmental factors affect cancer are insufficient. The purpose of this study is to understand how the incidence of major cancers including thyroid, colorectal, stomach, lung, liver, prostate, and breast cancers differs according to geographical and environmental factors from a spatial perspective. For this purpose, Cancer incidence calculated at the si-gun-gu level was used as dependent variables, and 13 variables that were expected to affect cancer development were selected as independent variables. Global and local Moran's I statistics were used to identify spatial dependency and clustering of the dependent variables. OLS and spatial regression models were used to identify factors that affect cancer development. Global Moran’s I statistics and LISA cluster maps show spatial autocorrelation in spatial patterns of cancer development. The OLS regression analysis was performed to identify variables affecting cancer development. Since age effect was strong in most cancers, it was controlled. After confirming that spatial dependence is clearly shown in the residuals of OLS model, spatial regression analyses were performed to model spatial dependency. The results showed that the spatial regression models are suitable for explaining the incidence for all types of cancer. In particular, considering the spatial dependency, it was confirmed that factors affecting cancers may be different from those of OLS regression analysis. The results of this study showed that spatial statistical analysis can more accurately identify geographical and environmental factors affecting cancer development. These findings provide useful information on how to improve local environments to prevent cancer.

Statistics

  • 708 Viewed
  • 1 Downloaded

Tools

Issue List

Citation status

* References for papers published after 2023 are currently being built.

Basic Search Advanced Search