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공간분석을 이용한 지역별 비만율에 영향을 미치는 요인분석

Analysing the Effects of Regional Factors on the Regional Variation of Obesity Rates Using the Geographically Weighted Regression

  • 김다양 (연세대학교 대학원 보건행정학과) ;
  • 곽진미 (연세대학교 대학원 보건행정학과) ;
  • 서은원 (연세대학교 대학원 보건행정학과) ;
  • 이광수 (연세대학교 보건과학대학 보건행정학과)
  • Kim, Da Yang (Department of Health Administration, Yonsei University Graduate School) ;
  • Kwak, Jin-Mi (Department of Health Administration, Yonsei University Graduate School) ;
  • Seo, Eun-Won (Department of Health Administration, Yonsei University Graduate School) ;
  • Lee, Kwang-Soo (Department of Health Administration, Yonsei University College of Health Sciences)
  • 투고 : 2016.05.02
  • 심사 : 2016.10.04
  • 발행 : 2016.12.31

초록

Background: This study purposed to analyze the relationship between regional obesity rates and regional variables. Methods: Data was collected from the Korean Statistical Information Service (KOSIS) and Community Health Survey in 2012. The units of analysis were administrative districts such as city, county, and district. The dependent variable was the age-sex adjusted regional obesity rates. The independent variables were selected to represent four aspects of regions: health behaviour factor, psychological factor, socio-economic factor, and physical environment factor. Along with the traditional ordinary least square (OLS) regression analysis model, this study applied geographically weighted regression (GWR) analysis to calculate the regression coefficients for each region. Results: The OLS results showed that there were significant differences in regional obesity rates in high-risk drinking, walking, depression, and financial independence. The GWR results showed that the size of regression coefficients in independent variables was differed by regions. Conclusion: Our results can help in providing useful information for health policy makers. Regional characteristics should be considered when allocating health resources and developing health-related programs.

키워드

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피인용 문헌

  1. Gender Difference and Spatial Heterogeneity in Local Obesity vol.15, pp.2, 2018, https://doi.org/10.3390/ijerph15020311