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Updated: Sep 10, 2025

Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data
Published on: June 26, 2013
Describing county-level clustering patterns of suicide among Veterans Health Administration patients and all American
A R Cunningham1, V Lebakula1, A G Cosby2
1Oak Ridge National Laboratory, 1 Bethel Valley Rd, Oak Ridge, TN 37830, United States.
Purpose:
Veterans account for 7 % of the adult American population but nearly 14 % of the country's adult suicides. With a distinct geodemographic profile, veterans represent an important subpopulation for spatial analysis, and their access to Veterans Health Administration (VHA) care can make them a uniquely reachable group for policy interventions and research. Better understanding of VHA patterns in context can inform prevention strategies.
Methods:
Hotspot analysis, a type of exploratory spatial data analysis (ESDA), was used to identify county-level clusters with high or low empirical Bayesian smoothed suicide rates among VHA patients in 2018-2019. A parallel analysis was conducted for all American adults. Clusters were then described using county-level characteristics previously linked to suicide prevalence.
Results:
Clusters among VHA patients and the general population often overlapped and shared similar features. Cold spots were associated with lower elevations, higher incomes, and higher education levels, whereas hotspots were associated with higher elevations. All cold spots in the general population and most clusters among VHA patients occurred in metropolitan areas, however VHA hotspots also occurred in metropolitan areas.
Conclusions:
Juxtaposing VHA and general adult ESDA results elucidates patterns of VHA suicides in context, highlighting spatial clusters as targets for interventions and research.
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