Identify the characteristics related to the suicide rates in rural and urban areas of Korea and discover the factors that influence the suicide rate of the rural and urban areas.
Using the data on causes of death from 2006 to 2008, the suicide rates were calculated and compared after age-standardization based on gender, age group and urbanicity. And, in order to understand the factors that influence suicide rate, total 10 local characteristics in four domains - public service, social integration, residential environment, and economic status - were selected for multiple regression analysis.
The suicide rates were higher in men than women, in rural areas than urban, and in older people than the younger. Generally, although there were variations according to age group and urbanicity, suicide rates were significantly related to residential environment and regional economic status but not related to regional welfare spending and social integration. In addition, the population over the age of 65 years, only regional economic status has significantly influence on their suicide rates.
The influence of characteristics of regions on suicide rate is various by age-group, gender, and urbanicity. Therefore, in order to lower suicide rate and reduce the gap between regions, various approaches must be adopted by taking into account the socioeconomic characteristics of the regions.
Citations
Busan is reported to have the highest mortality rate among 16 provinces in Korea, as well as considerable health inequality across its districts. This study sought to examine overall and cause-specific mortality and deprivation at the town level in Busan, thereby identifying towns and causes of deaths to be targeted for improving overall health and alleviating health inequality.
Standardized mortality ratios (SMRs) for all-cause and four specific leading causes of death were calculated at the town level in Busan for the years 2005 through 2008. To construct a deprivation index, principal components and factor analysis were adopted, using 10% sample data from the 2005 census. Geographic information system (GIS) mapping techniques were applied to compare spatial distributions between the deprivation index and SMRs. We fitted the Gaussian conditional autoregressive model (CAR) to estimate the relative risks of mortality by deprivation level, controlling for both the heterogeneity effect and spatial autocorrelation.
The SMRs of towns in Busan averaged 100.3, ranging from 70.7 to 139.8. In old inner cities and towns reclaimed for replaced households, the deprivation index and SMRs were relatively high. CAR modeling showed that gaps in SMRs for heart disease, cerebrovascular disease, and physical injury were particularly high.
Our findings indicate that more deprived towns are likely to have higher mortality, in particular from cardiovascular disease and physical injury. To improve overall health status and address health inequality, such deprived towns should be targeted.
Citations