| Summary: | 碩士 === 國立臺灣大學 === 健康政策與管理研究所 === 100 === Objectives: The premimary purpose of this study is to investigate and compare the geographical variations of violent and nonviolent suicide rates in three different periods, by mapping across 350 townships in Taiwan. Secondary purpose, this study applies a multilevel logistic regression analysis to access the individual socioeconomic characteristics, township-level variables, and cross-level effects of suicidal deaths that use violent or nonviolent method and the people aged 20-64 during 1999 to 2007(n=27,970).
Methods: Data files for suicides and undetermined deaths were provided by the Department of Health, from 1999-2007. To find out the changes in spatial patterning over three time periods, Moran’s I statistic and Local Spatial Autocorrelation (LISA) were used to test the spatial clustering/autocorrelation of violent and nonviolent suicide age-standardized rates. Multilevel logistic models including random coefficient model, intercept-as-outcome and slopes-as-outcome model were employed to access the relationship between township-level variables and the individual’s choice of violent/nonviolent suicide methods. Individual-level variables included gender, age, marital, employment status and suicidal periods. Township-level variables included high socio-economic and familial vulnerability hot/cold spots, and data were derived from the 2000 census of population and housing (Directorate-General of Budget Accounting and Statistics), Ministry of Finance (Financial Data Center), Ministry of the Interior (Department of Statistics), and Department of Health.
Results: Both violent and nonviolent suicide rates demonstrated a significant spatial clustering characteristic for the periods 1999-2001, 2002-2004, and 2005-2007. High clusters (hot spots) of suicide rates were more frequently detected in part of rural Hualien, Taitung and Pingtung areas. Furthermore, the spatial clustering of high violent and nonviolent suicide rates was located at different towns during three periods. In addition, results from multilevel logistic models indicated that individual’s gender, age, marital and employment status and suicidal periods were associated to the choice of violent/nonviolent suicide methods. Moreover, after controlling for individual-level variables, suicidal person who lived in a high socio-economic cluster (hot spot) was more likely to commit suicide by violent suicide method. Additionally, person who lived in a low socio-economic cluster (cold spot) tended to use nonviolent method.
Conclusions: As age increases, male, unemployed and suicides occured in the spring and summer had a significantly higher likelihood of commiting suicide by violent method. Additionally, compared to low socio-economic, suicidal person who lived in a high cluster of socio-economic also had a significantly higher risk to choose violent suicide method. Furthermore, cross-level interaction effect was observed in multilevel logistic models. The results demonstrate that, besides individual characteristics, suicide prevention strategies should also consider the socio-economic difference between urban and rural areas.
|
|---|
