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

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.

The Effects of Hospital Resources on the Service Uses: Hospital Service Area Approach / 보건행정학회지

BACKGROUND: This study explored the relationship between hospital resources and services uses in outpatient/inpatient-based hospital service area (HSA) in Korea. METHODS: Study hospitals included all acute care hospitals except tertiary hospitals. Inpatient and outpatient hospital claims from the Korean National Health Insurance (NHI) program in 2010 were used to identify the service uses. Hospital resources and the degree of insurance premium in study areas were identified with the NHI corporation data. Study variables were computed by summing the service uses or hospital resources of study hospitals in each HSA. Service uses were represented by the total medical charges and number of visits/inpatient days. Hospital resources were measured by number of beds, number of doctors, and number of computed tomography (CT). The economic status of NHI enrollees in each HSA was controlled by the average monthly premium of NHI program per household in each HSA. The degree of using local hospitals was controlled with the localization index. RESULTS: Analysis results showed that hospital resources such as beds, CT were statistically related to the service uses. And also localization index was found to have positive significant relationships with service uses. CONCLUSION: Hospital resources such as beds, CT had not only positive impacts on inpatient service uses, but also influences on the outpatient setting. Health policy makers will require monitoring and assessing the hospital resources in Korea.

Regional Disparities of Suicide Mortality by Gender / 보건행정학회지

BACKGROUND: Suicide is one of important health problems in Korea. Previous studies showed factors associated with suicide in individual levels. However, suicide was influenced by society that individuals belong to, so it was required to analyze suicide in local levels. The purpose of this study was to analyze the regional disparities of suicide mortality by gender and the association between local characteristics and suicide mortality. METHODS: This study included 229 city.county.district administrative districts in Korea. Age- and sex-standardized suicide mortality and age-standardized suicide mortality (male/female) were used as dependent variables. City.county.district types, socio-demographics (number of divorces per 1,000 population, number of marriages per 1,000 population, and single households), financial variable (financial independence), welfare variable (welfare budget), and health behavior/status (perceived health status scores and EuroQol-5 dimension [EQ-5D]) were used to represent the local characteristics. We used hot-spot analysis to identify the spatial patterns of suicide mortality and negative binomial regression analysis to examine factors affecting suicide mortality. RESULTS: There were differences in distribution of suicide mortality and hot-spot regions of suicide mortality by gender. Negative binomial regression analysis provided that city.county.district types (city), number of divorces per 1,000 population, financial independence, and EQ-5D had significant influences on the age- and sex-standardized suicide mortality per 100,000. Factor influencing suicide mortality was the number of divorces per 1,000 population in both male and female. CONCLUSION: Study results provided evidences that suicide mortality among regions was differed by gender. Health policy makers will need to consider gender and local characteristics when making policies for suicides.