Geography of suicide in Taiwan: Spatial patterning and socioeconomic correlates☆
Introduction
There are striking geographic variations in the incidence of suicide. Across Europe, national suicide rates differ more than 10-fold (Levi et al., 2003). Within the same country, the incidence of suicide also varies between regions and has distinct features in its geographic distribution (Gunnell, 2005). Previous studies have investigated associations of area characteristics with suicide rates within a country or region, particularly differences between rural and urban areas (Hirsch, 2006), but few have examined the spatial patterning of suicide. In a recent study which mapped variation across small areas in England and Wales, higher suicide rates were found in central parts of cities and remote/coastal areas (Middleton et al., 2008). Such spatial variation is associated with area indicators of social fragmentation and deprivation (Congdon, 1996, Middleton et al., 2004, Rezaeian et al., 2005). A recent review, mostly of studies from Western countries, shows that area suicide rates are higher in areas characterised by high levels of poverty, unemployment, low educational achievement and lower occupational social class (Rehkopf and Buka, 2006).
Considerable intra-country variations in suicide rates are also seen in some non-Western countries. For example, in China rural suicide rates are three times unban rates (Phillips et al., 2002). However, few studies have investigated the spatial patterning of suicide and its possible contributors in non-Western settings and most of them have used data for rather large geographic units. Spatial analyses at a fine scale are most useful for investigating the geographic pattern of suicide (Middleton et al., 2008) and its association with area socioeconomic characteristics (Rehkopf and Buka, 2006). Small geographic units have more internal homogeneity than large units and their aggregate socioeconomic characteristics are thus more likely to reflect the nature of social environment where people live. Appropriate statistical approaches such as Bayesian hierarchical models can be used to tackle the problem of uncertainty in estimates in small-area analyses, as well as potential spatial autocorrelation in the data (i.e. rates in geographically close areas are likely to be related) (Besag et al., 1991, Lawson et al., 2000); however, they have only been used in a limited number of studies of suicide (Congdon, 1997, Middleton et al., 2008, Pirkola et al., 2009).
We used Bayesian hierarchical models to investigate the spatial patterning of suicide by sex, age group and suicide method across 358 districts in Taiwan, an East Asian country with a population of 23 million, over the period 1999–2007. We also investigated associations with a range of area socioeconomic characteristics.
Section snippets
Suicide and population data
Suicide data (1999–2007) for people aged 15+ years were extracted from the Taiwanese national mortality data file. In all analyses we included certified suicides (International Classification of Diseases, Ninth Revision [ICD-9] codes E950–959) and deaths in cause-of-death categories previously shown to contain ‘missed’ suicides in Taiwan, including undetermined death (E980–989) and accidental death by pesticide poisoning (E863) and suffocation (E913) (Chang et al., 2010b). For simplicity of
Results
There were 37,326 suicides (males=25,530 [68.4%]) in Taiwan in 1999–2007, including 29,761 (79.7%) certified suicides, 6719 (18.0%) undetermined deaths, 580 (1.6%) deaths classified as accidental pesticide poisoning and 266 (0.7%) deaths classified as accidental suffocation. Amongst male suicides 46.9% were 15–44 years old, 32.0% 45–64 years old and 21.1% 65+ years old; the corresponding figures for female suicides were 44.9%, 29.7% and 25.3%, respectively. Hanging/suffocation accounted for
Main findings
The geographic distribution of suicide in Taiwan showed different spatial patterns from those reported in Western nations. Suicide rates in city centres were not higher than the national average, and the capital Taipei showed a pattern of lower rates in the centre, with increasing rates towards suburban areas. There was clustering of the highest rates in East Taiwan. The greatest spatial variation and clustering in rates was found in young age groups. There were marked differences in geographic
Acknowledgements
The authors thank Professor Ying-Chih Chuang at School of Public Health, Taipei Medical University, Taiwan, for helping data extraction from the 2000 Taiwanese national census. The authors appreciate the assistance of the Center for Survey Research of Academia Sinica, Taiwan, in obtaining the Manpower Survey data. DG is a National Institute for Health Research (NIHR) Senior Investigator.
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Funding: S-SC's Ph.D. study was supported by the Taiwanese government (the Government Funds of the Ministry of Education), the Higher Education Funding Council for England (Overseas Research Scholarship) and University of Bristol (University of Bristol Postgraduate Research Scholarship). S-SC's fellowship is funded by the National Science Council, Taiwan (NSC-98-2917-I-564-162).