BACKGROUND: In 2014, suicide was the eighth leading cause of death in Idaho and tenth nationwide. Limited data are available about characteristics of areas with high suicide rates. We sought to identify and characterize spatial clusters of Idaho suicides.
METHODS: We analyzed Idaho Division of Public Health`s death certificate data on deaths occurring among Idaho residents during 2010–2014 and used International Classification of Diseases, Tenth Revision codes X60.0–X84.9, Y87.0, U03.0, and U03.9 to identify suicides; we geocoded residential addresses to census block groups (CBGs). We obtained population data from the 2010 Census and the 2010–2014 American Community Survey. We used a discrete Poisson model in SaTScan™, with P <0.10 cutoff for programmatic considerations, to identify nonoverlapping, high-rate spatial clusters of suicide. Logistic regression was used to examine associations between suicide clustering and CBG-level population characteristics (comparing highest quartile with lowest 3 quartiles); P <0.05 cutoff for inclusion in multivariable modeling.
RESULTS: During 2010–2014, deaths by suicide occurred in 1,501 Idaho residents. We identified 2 clusters of suicide in distinct regions as follows: a 25-CBGs cluster (age- and sex-adjusted relative risk [aRR] = 1.94) and a 6-CBGs cluster (aRR = 3.61). CBGs within the identified clusters were positively associated with the following CBG-level population characteristics: median age ≤31.1 years (multivariable-adjusted odds ratio [aOR] = 2.41; P = 0.041), >53% female (aOR = 2.69; P = 0.011), >1% American Indian or Alaska Native (aOR = 2.92; P = 0.006), and >30% never married (aOR = 3.43; P = 0.004).
CONCLUSIONS: We identified suicide clustering in Idaho and associations with CBG-level characteristics. Idaho suicide prevention programs should consider using results to target prevention efforts.