ABSTRACT
Background@#This study aims to figure out the gaps in health status by estimating amenable mortality rate by region, reflecting the characteristics of Korea, and estimating the years of life lost (YLL) per capita by disease. @*Methods@#People who died from amenable diseases between 2008 and 2018 were extracted from the cause of death statistics provided by Statistics Korea. The age-standardized amenable mortality rates were estimated to compare the health status of 229 regions. YLL per capita was calculated to compute the burden of diseases caused by treatable deaths by region. The YLL per capita by region was calculated to identify the burden of disease caused by amenable deaths. @*Results@#First, while the annual amenable mortality rate in Korea is on a steady decline, but there is still a considerable gap between urban and rural areas when comparing the mortality rates of 229 areas. Second, YLL per capita due to the amenable deaths is approximately 14 person-years during the analysis period (2008–2018). @*Conclusion@#Although the health status of Koreans has continuously improved, there is still a gap in health status region by region in terms of amenable mortality rates. Amenable death accounts for a loss of life equivalent to 14 person-years per year. Since the amenable mortality rate is an indicator that can measure the performance of the health care system, efforts at each local area are required to lower it.
ABSTRACT
Background@#This study aims to figure out the gaps in health status by estimating amenable mortality rate by region, reflecting the characteristics of Korea, and estimating the years of life lost (YLL) per capita by disease. @*Methods@#People who died from amenable diseases between 2008 and 2018 were extracted from the cause of death statistics provided by Statistics Korea. The age-standardized amenable mortality rates were estimated to compare the health status of 229 regions. YLL per capita was calculated to compute the burden of diseases caused by treatable deaths by region. The YLL per capita by region was calculated to identify the burden of disease caused by amenable deaths. @*Results@#First, while the annual amenable mortality rate in Korea is on a steady decline, but there is still a considerable gap between urban and rural areas when comparing the mortality rates of 229 areas. Second, YLL per capita due to the amenable deaths is approximately 14 person-years during the analysis period (2008–2018). @*Conclusion@#Although the health status of Koreans has continuously improved, there is still a gap in health status region by region in terms of amenable mortality rates. Amenable death accounts for a loss of life equivalent to 14 person-years per year. Since the amenable mortality rate is an indicator that can measure the performance of the health care system, efforts at each local area are required to lower it.
ABSTRACT
Background@#Based on the importance of ceasing smoking programs to control the regional disparity of smoking behavior in Korea, this study aims to reveal the variation of smoke rate and determinants of it for 229 provinces. An evaluation of the relative efficiency of the cease smoking program under the consideration of regional characteristics was followed. @*Methods@#The main sources of data are the Korean Statistical Information Service and a national survey on the expenditure of public health centers. Multivariate regression is performed to figure the determinants of regional variation of smoking rate. Based on the result of the regression model, clustering analysis was conducted to group 229 regions by their characteristics. Three clusters were generated. Using data envelopment analysis (DEA), relative efficiency scores are calculated. Results from the pooled model which put 229 provinces in one model to score relative efficiency were compared with the cluster-separated model of each cluster. @*Results@#First, the maximum variation of the smoking rate was 16.9%p. Second, sex ration, the proportion of the elder, and high risk drinking alcohol behavior have a significant role in the regional variation of smoking. Third, the population and proportion of the elder are the main variables for clustering. Fourth, dissimilarity on the results of relative efficiency was found between the pooled model and cluster-separated model, especially for cluster 2. @*Conclusion@#This study figured regional variation of smoking rate and its determinants on the regional level. Unconformity of the DEA results between different models implies the issues on regional features when the regional evaluation performed especially on the programs of public health centers.