Does place of residence affect risk of suicide? a spatial epidemiologic investigation in Kentucky from 1999 to 2008

Between 2000 and 2007, there were 256,085 deaths in the United States (US) attributed to suicide. Approximately 32,000 people take their own lives every year in the US [1]. In 2009, suicide was the tenth leading cause of death for all ages, the second leading cause of death among 25-34-year olds, and the third leading cause of death among 15-24-year olds [1]. Firearms, suffocation, and poisoning are the most common methods of suicide; however, men and women differ in the methods used. In the same year, firearms were the most commonly used methods of suicide among males, while poisoning was the most commonly used mechanism in females. Males died by suicide at nearly four times the rate of females and represented 78.8% of all US suicides. During their lifetime though, women attempt suicide about two to three times as often as men [1].

In Kentucky, suicide mortality rates have been steadily increasing since 1999. In 2006, suicides rose to 14.4 per 100,000 persons from the 1999 rate of 11.3 per 100,000 persons, a 27% increase. With an average of 13.4 suicides per 100,000 people annually (2000-2006), Kentucky ranks 16^th highest for suicide in the US [1]. Additionally, medical costs and lost wages associated with suicide also take their toll on communities. In 2005, suicide cost society $26.7 billion in combined medical and work loss costs, while in Kentucky it was estimated to cost $481 million [2].

A combination of demographic, individual, relational, community, and societal factors contribute to the risk of suicide. According to the World Health Organization's (WHO) report on violence and health, demographic factors such as age and sex, psychiatric, biological, social and environmental factors, as well as factors related to an individual's life history might play a role in making people more likely to attempt or commit suicide [3].

Although much is understood about suicide at the individual level, including multiple factors associated with increased risk of suicide [3], little has been done at the ecologic level to identify counties or neighborhoods with the greatest risk of suicide. Just as determining individual-level risk factors for suicide is vital for suicide prevention efforts, identifying high-risk areas and investigating spatial patterns for suicide provides a richer understanding of the determinants of suicide than the individual-level risk factors alone. Thus, identifying high-risk counties using spatial statistics may allow for a better targeting of resources and suicide intervention efforts so as to prevent future suicides.

Several studies have used spatial statistical techniques in assessing the presence of high-risk clusters including a brain cancer cluster study [4], a study on networks of sexually transmitted infection [5], and on breast cancer mortality disparities [6]. Other studies incorporating similar methodologies have assessed high-risk clusters of La Crosse virus in West Virginia [7], clusters of giardiasis in Canada [8], and clustering of lung cancer in Italy [9]. However, spatial studies of suicide clusters have been limited. Exeter and Boyle (2007) found a significant geographical cluster of suicide among young adults in east Glasgow across three time periods (1980 to 1982, 1990 to 1992, and 1999 to 2001), which were attributed to socioeconomic deprivation [10]. Another study investigating suicide clusters in Queensland, Australia, found clusters in low socioeconomic areas [11]. These studies provide some support that regions at high risk for suicide are those with greater socioeconomic deprivation.

Though suicide studies have used spatial statistical techniques in other countries, little has been published in the US. The present study has the potential to bridge the gap between suicide research and targeted prevention. The primary purpose of this study was to identify counties at the highest risk for suicide. Secondarily, this study also tests whether suicides are clustered temporally. Thus, the current study provides an analytical framework, using spatial statistics, to identify and target areas with the highest risk of suicide. Further, identification of counties at a greater risk for suicide is expected to guide resources and assist in policy decision making at the county level.

We investigated the spatial epidemiology of suicides in Kentucky as reported in death certificate data files from the Kentucky Office of Vital Statistics between 1999 and 2008 using scan statistics and descriptive epidemiological methods. The results show evidence of hotspots of suicides across Kentucky counties, and describe the differences in suicide characteristics between genders, and for cases inside and outside high-risk spatial clusters. Further, when the purely spatial cluster analysis, SEB map, and cumulative incidence rates are jointly examined, they bolster the evidence of the existence of a high-risk suicide cluster in western Kentucky. To our knowledge this is the first study to investigate spatial and temporal patterns of suicide mortality at the county level in the US. This study allows for a better understanding of where to target resources and prevention efforts at the county level to reduce the burden of suicide in areas of greatest risk [30, 31].

Moreover, suicide victim characteristics within the two spatial clusters allow for more targeted prevention efforts. For example, there is a moderately older age group of victims in the most likely cluster, and a greater proportion of 40-44 year old suicide victims inside the secondary cluster compared to outside the cluster. In addition, suicide cases inside the secondary cluster are more likely to self-poison than outside the cluster. Although our results reveal that females are more likely to self-poison than males (and this agrees with national data) [1], there were not significantly more female suicides inside the secondary cluster than outside. These divergent characteristics of suicide cases inside versus outside clusters can inform interventions and guide future studies. Suicide risk was also found to be highest in 2006, providing evidence that suicide has been gradually increasing in Kentucky since 1999.

Our study differs from Exeter and Boyle's (2007) Scotland suicide cluster analysis in several ways [10]. Exeter and Boyle's study, which was limited to young adult suicides (15 to 44 years old), found high risk clusters in Glasgow, Scotland, across three time periods with relative risks ranging from 1.53 to 2.41, while our study revealed clusters with relative risks ranging from 1.24 to 1.38. Unlike our study, where 67% of suicides were firearm related (65% for adults 15 to 44 years old), Exeter and Boyle found that 63% of suicides among young adults were from poisonings, hangings, strangulation and suffocation. In addition, Scotland's suicide rate among adults aged 15 to 44 years in 1999 to 2001 was 24.3 per 100,000 persons, which was markedly higher than Kentucky's suicide rate of 13.5 per 100,000 persons among adults aged 15 to 44 years during the same period [1]. This difference in suicide method and rates suggests that suicide may be better explained by other factors-such as low socioeconomic status [3, 10], less access to mental health care [32], sudden unemployment [33], depression [34], and alcoholism [35]-than by firearm access alone [36], given that Scotland's suicide rate is higher than Kentucky's despite there being lower access to firearms in Scotland than Kentucky [37]. Thus, this comparison suggests that firearm availability may not be the sole driving force behind increased regional suicide rates. Both studies reveal that suicide does not occur randomly in space, and that the characteristics of suicide cases inside clusters tend to be different than outside; specifically in Scotland where suicide clusters have been explained by the concentration of socioeconomic deprivation [10].

This study found high-risk clusters of suicide in western Kentucky and demonstrated the usefulness of the combination and complementary nature of spatial statistics, cumulative incidence, relative risk, and SEB smoothed rates in identifying areas at highest risk for suicide. The findings can guide intervention efforts at the county level in Kentucky to reduce suicide in those areas at greatest risk.