Spatial Information Research

Korea Spatial Information Society (대한공간정보학회)
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Exploring Multidimensional Public Health Data Using Self Organizing Map and GIS

자기조직화지도와 GIS를 이용한 다차원 공중보건자료의 탐구적 분석

  • Sohn, Chul (Dept. of Urban Planning and Real Estate, Gangneung-Wonju National University)
  • Received : 2012.06.11
  • Accepted : 2012.12.06
  • Published : 2012.12.31
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Abstract

This study applied an exploratory analysis based on Self Organizing Map and GIS to cause specific age-standardized regional death rates data related to ten types of male cancers to find meaning patterns in the data. Then the patterns revealed from the exploratory analysis was evaluated to investigate possible relationship between these patterns and regional socio-economic status represented by regional educational attainment levels of head of household. The results from this analysis show that SI-GUN-GUs in Korea can be clustered to eighteen unique clusters in the stand point of male cancer death rates and these clusters are also spatially clustered. Also, the results reveal that regions with higher socio-economic status show lower level of the death rates compared with the regions with lower socio-economic status. However, for some cancer types, the regions with higher socio-economic status show relatively higher death rates. These patterns imply that the prevention, detection, and treatment of male cancers might be strongly affected by regional factors such as socio-economic status, environmental factors, and cultures and norms in Korea. Especially, one of the eighteen clusters, which includes Gangnam-Gu and Seocho-Gu, shows lower death rates in many of male cancer types. This implies that socio-economic status may be one of the most influential factors for regional cancer control.

본 연구에서는 2005년에서 2010년까지의 통계청 남성암 유형별 연령표준화 시군구 사망률 데이터에 대해 자기조직화지도와 GIS를 이용한 탐구적 자료 분석을 수행하여 이들 데이터에 의미 있는 패턴이 내재되어 있는지 분석하였다. 그리고 지역의 사회경제적 수준을 대표하는 변수로 선정된 지역별 가구주의 교육수준과 분석된 패턴이 어떤 관련이 있는지 검토하였다. 분석결과 우리나라 시군구는 남성암 사망원인 측면에서 독특한 특성을 가진 18개의 지역 군집으로 구분될 수 있으며, 이들 군집 내 속한 시군구가 공간적으로도 군집되는 경향이 있음을 보여주었다. 또한 가구주의 교육수준이 높은 군집이 낮은 군집에 비해 남성암 사망률이 낮은 경향을 보이지만 일부 암의 경우 교육수준이 높은 군집에서 사망률이 높음을 보여주었다. 이 결과는 지역의 사회경제적 요인, 자연환경적 요인 등 암의 발생 및 관리에 영향을 미치는 지역적 요인에 양의 공간적 자기상관이 존재하며, 이러한 공간적 자기상관이 다양한 유형의 암 원인 사망에 영향을 미친 결과로 해석되어질 수 있다. 또한 18개의 군집 중 서울의 강남구 및 서초구를 포함한 군집은 대부분 유형의 암 원인 사망률에서 전체 18개 군집 중 하위 수준임을 보여 우리나라 암의 예방, 발생, 관리와 관련된 중요원인이 사회경제적 요인일 수 있음을 암시하였다.

Keywords

References

  1. Agarwal, Pragya; Skupin Andre 2008, Self Organizing Maps: Applications in Geographic Information Science, Ed. West Sussex, England: Wiley.
  2. Arendt, Jacob Nielsen. 2005, Dose Education Cause Better Health, Economics of Education Review 24:149-160. https://doi.org/10.1016/j.econedurev.2004.04.008
  3. Arribas-Bel, Daniel; Nijkamp, Peter; Scholten, Henk 2011. "Multidimensional Urban Sprawl in Europe: A Self-Organizing Map Approach," Computers, Environment and Urban Systems 35:263-275. https://doi.org/10.1016/j.compenvurbsys.2010.10.002
  4. Choi, Min-Hyeok; Cheong, Kyu-Seok; Cho, Byung-Mann; Hwang, In-Kyung; Kim, Chang-Hun; Kim, Myoung-Hee;p Hwang, Seung-Sik; Lim, Jeong-Hun; Yoon, Tae-Ho 2011, Deprivation and Mortality at the Town Level in Busan, Korea: An Ecological Study, Journal of Preventive Medicine and Public Health, 44(6):242-248. https://doi.org/10.3961/jpmph.2011.44.6.242
  5. Flowerdew, Robin; Manley, David J.; Sabel, Clive E. 2008, Neighbourhood Effects on Health: Does it matter where you draw the boundaries?, Social Science & Medicine 66:1241-1255. https://doi.org/10.1016/j.socscimed.2007.11.042
  6. Jeong, Baek-Geun; Jung, Kap-Yeol; Kim, Joon-Youn; Moon, Ok-Ryun; Lee, Yong-Hwan ; Hong, Young-Seoub; Yoon, Tae-Ho 2006, The Relationship between Regional Material Deprivation and the Standardized Mortality Ratio of the Community Residents Aged 15-64 in Korea, Journal of Preventive Medicine and Public Health, 39(1):46-52.
  7. Kaski, S.; Kohonen, T. 1996, Exploratoy Data Analysis by the Self-Organizing Map: Structures of Welfare and Poverty in the World," Proceeding of the Third International Conference on Neural Network in the Capital Markets, London, England, October 11-13, 1995.
  8. Kim, Chang-Seok; Yun, Sung-Cheol; Kim, Hye-Ryun; Kim, Young-Ho 2006, A Multilevel Study on the Relationship between the Residential Distribution of High Class (Power Elites) and Smoking in Seoul, Journal of Preventive Medicine and Public Health, 39(1): 30-38.
  9. Kim, Du-Seop; Park, Hyo-Jun 2003, Regional Differentials in Mortality in Korea, 1990-2000, The Population Association of Korea, 26(1): 1-30.
  10. Kim, Kang-Ho 2009, The Effect of Schooling and Training Participation on Wage of Employed Workers, Journal of Agricultural Education and Human Resource Development, 41(3):123-151. https://doi.org/10.23840/agehrd.2009.41.3.123
  11. Kim, Yoo-Sun 2009, Wage Determinants in the Korean Labour Market, Korean Journal of Industrial Relations, 19(2):1-25.
  12. Kim, Young-Chang; Chang, Jae-Woo 2009, Countinuous k-Nearest Neighbor Query Processing Algorithm for Distributed Grid Scheme, Journal of Korea Spatial Information System Society, 11(3):9-18.
  13. Lu; Hsin-Chung; Chang, Chung-Liang; Hsieh, Jen-Chieh 2006, Classification of $PM_{10}$ distributions in Taiwan, Atmospheric Environment 40:1452-1463. https://doi.org/10.1016/j.atmosenv.2005.10.051
  14. Park, Ji-Man; Hwang, Chul-Sue 2005, A Design and Practical Use of Spatial Data Warehouse for Spatial Decision Making, The Journal of GIS Association of Korea, 13(3):239-252.
  15. Shin, Kyung-Soo; Choi, Chang-Yeoul 2007, A Study on the Wage Gap by the Education Standards and Gender Productivity Gap, Productivity Review, 21(3):97-121. https://doi.org/10.15843/kpapr.21.3.200709.97
  16. Sim, Jeoung-Ha; Son, Mi-A 2009, The Relationship between Cerebrovascular Mortality and Community Health Indicators in Gangwondo, Journal of Agricultural Medicine and Community health, 34(1):1-12. https://doi.org/10.5393/JAMCH.2009.34.1.001
  17. Sohn, Chul 2011, Identification of Spatial Housing Submarkets in the Capital Region Using Self Organizing Map and Chow Test, The Korea Spatial Planning Review, 70:151-166. https://doi.org/10.15793/kspr.2011.70..009
  18. Spielman, S. E.; Thill, Jean-Claude 2008, Social Area Analysis, Data Mining, and GIS, Computers, Environment and Urban Systems 32:110-122. https://doi.org/10.1016/j.compenvurbsys.2007.11.004
  19. Vesanto, Juha; Alhoniemi, Esa 2000, Clustering of the Self-Organizing Map, IEEE Transactions on Neural Networks, 11(3):586-600. https://doi.org/10.1109/72.846731

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  1. 지역사회건강 연구와 근린의 사회경제적 수준 지표로서 주택 가격 수준의 이용 vol.21, pp.6, 2013, https://doi.org/10.12672/ksis.2013.21.6.081