An atlas of suicide mortality: England and Wales, 1988–1994
Introduction
In the recent years there have been marked changes in the age patterning of suicide mortality in Britain (Gunnell et al., 2003) as well as in much of the industrialised world (Cantor, 2000). As the most unfavourable trends have generally occurred in young people, suicide ranks as one of the principal causes of premature mortality (Gunnell, 2000). In their classic work, Morselli (1881) and Durkheim (1952) presented maps of national and sub-national suicide rates across Europe. For over a century now, a striking feature of the epidemiology of suicide has been the wide geographical variation in its occurrence i.e. more than 10-fold differences in rates across Europe (Cantor, 2000). Differences of similar magnitude have been reported within Britain (Bunting and Kelly, 1998) and even across smaller areas within particular cities (Sainsbury, 1955; Gunnell et al., 1995; Congdon, 1996). Since Morselli's and Durkheim's maps were used as an aetiological tool in the 19th century, there have been several quantitative investigations into area-based associations of suicide with indicators of their socio-economic characteristics. However, few studies have used maps to explore and represent the geographical variability and patterning of suicide, either in Britain or elsewhere.
The UK government has recently recognised suicide (and mental health) as an important contributor to area health inequalities (Department of Health, 2001). However, the geography of suicide is still poorly understood. Part of the problem is that standardised mortality ratios (SMRs), commonly presented in maps, are calculated in each area independently and, as such, incorporate no information about the amount of heterogeneity or clustering across the map (Clayton and Kaldor, 1987). Inference from SMR maps is particularly problematic at finer levels of geographical aggregation not only because a large proportion of areas might record no deaths but also because areas with small populations are more likely to produce extreme and unreliable estimates. Yet, exploring these issues at a smaller area level, and across different age/sex groups, is central to the investigation of possible area influences, and their magnitude, upon their residents.
Whether descriptive, or ecological assessments, previous studies have generally: (i) focused on relatively large areas or smaller areas within a defined locality e.g. single city or district and/or (ii) not investigated whether the geography of suicide varies across different age and sex groups—as recent changes in its age patterning might suggest and/or (iii) used simple regression approaches that either treat geographical areas as independent or investigated evidence of heterogeneity but not clustering across the map. In a previous analysis, we documented the geographical distribution of suicide amongst 15–44-year old males living in England and Wales (Middleton et al., 2006). We found high rates of suicide clustered in inner-city and coastal areas. Here, we extend our investigation to examine the geographical distribution of suicide in older males and females of all ages. Using geographically and statistically appropriate methodology, we investigated the magnitude and spatial patterning of suicide mortality across 9265 wards in England and Wales and addressed the extent to which there exists a common geography across different age/sex groups.
Section snippets
Data sources
All suicide and undetermined deaths in the 7-year period 1988–1994 were obtained from the Office for National Statistics, ONS (ICD codes E950.0–E959.9 and E980.0–E989.9 excluding E988.8). The inclusion of undetermined deaths has been common practice in suicide research as there is evidence to suggest that most deaths given an open verdict using legal criteria are suicides (Linsley et al., 2001). Deaths coded E988.8 were excluded from the analysis because this code is used to accelerate death
Results
There were 27,839 adult (aged 15+) male and 10,241 adult female suicides in 1988–1994. Of these, 215 (0.6%) of all deaths with missing or incorrect postcodes were excluded from the analyses since they could not be placed geographically. The number of such deaths was not only small but there also is no reason to believe that the error introduced is not geographically random. Even after excluding the 5% most extreme rates on either side of the distribution, there remained 5-fold differences in
Main findings
We improved upon current evidence and practice to produce an atlas of suicide mortality in England and Wales across different age/sex groups and at a smaller area level than documented previously. With more than 9000 small areas across England and Wales, this is the finest geographical scale ever used to examine the national geography of suicide in Britain or elsewhere. Maps presented here incorporated evidence of heterogeneity and clustering in the estimation procedure and revealed patterning
Conclusion
While there is no prior knowledge as to what geographical scale might be important in assessing common area influences upon a population's suicide experience or mental health, large areas are likely to include smaller localities with large differences in their socio-economic characteristics. Thus, the level of geographical aggregation at which patterns and associations are explored is central to understanding the geography of suicide and possible area influences, and their strength, upon a
Contribution of authors
This study forms part of an original proposal put together by D.G., J.S. and N.M. for N.M.'s Ph.D. funded jointly by the University of Bristol and the Overseas Research Students (ORS) Award Scheme during which D.G. and J.S. were N.M.'s Ph.D. supervisors (2000–2004). D.G. and N.M. collected the data. All analyses were performed by N.M. J.S. provided statistical advice. A series of maps of suicide mortality and residual variation after accounting for socio-economic area characteristics appear in
Competing interest statement
All authors declare that there are no competing interests.
Acknowledgements
We wish to acknowledge the Office for National Statistics, and Claire Griffiths in particular, for providing us with the mortality data. Also, Danny Dorling (University of Sheffield) for all the socio-economic, geographic- and mapping-related data e.g. ward boundaries polygon files and postcode look-up files, and Peter Congdon, Tony Ades, Lesley Wood and Ben Wheeler for helpful discussions.
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