Analysing the Effects of Regional Factors on the Regional Variation of Obesity Rates Using the Geographically Weighted Regression.
10.4332/KJHPA.2016.26.4.271
- Author:
Da Yang KIM
1
;
Jin Mi KWAK
;
Eun Won SEO
;
Kwang Soo LEE
Author Information
1. Department of Health Administration, Yonsei University Graduate School, Wonju, Korea.
- Publication Type:Original Article
- Keywords:
Obesity;
Geographically weighted regression;
Regional variation;
Ecological study;
Spatial regression
- MeSH:
Depression;
Drinking;
Health Policy;
Health Resources;
Health Surveys;
Information Services;
Obesity*;
Psychology;
Walking
- From:Health Policy and Management
2016;26(4):271-278
- CountryRepublic of Korea
- Language:Korean
-
Abstract:
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.
