Evidence map›Paper›PMID 40188495›Full record

ArticleJournal of public health (Oxford, England)2025

State-level suicide mortality insights: a comparative study of VHA veterans and the whole US population.

Viswadeep Lebakula, Angela R Cunningham, Arthur G Cosby, Anuj Kapadia, Jodie Trafton, Alina Peluso

Abstract readComparative Study
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of public health (Oxford, England), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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0cells of the map it votes in
1citing papers in PubMed
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1 · What the graph read from it

What it found

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2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Viswadeep LebakulaGeospatial Science and Human Security Division, National Security Sciences Directorate, Oak Ridge National Laboratory, PO Box 2008, Mail Stop 6017, Oak Ridge, TN 37831, USA.
Angela R CunninghamGeospatial Science and Human Security Division, National Security Sciences Directorate, Oak Ridge National Laboratory, PO Box 2008, Mail Stop 6017, Oak Ridge, TN 37831, USA.
Arthur G CosbySocial Science Research Center, Mississippi State University, 1 Research Blvd, Starkville, MS 39762, USA.
Anuj KapadiaComputational Sciences and Engineering Division, Computing and Computational Sciences Directorate, Oak Ridge National Laboratory, PO Box 2008, Mail Stop 6017, Oak Ridge, TN 37831, USA.
Jodie TraftonOffice of Mental Health and Suicide Prevention, Veterans Health Administration, 3801 Miranda Avenue, Palo Alto, CA 94304, USA.
Alina PelusoComputational Sciences and Engineering Division, Computing and Computational Sciences Directorate, Oak Ridge National Laboratory, PO Box 2008, Mail Stop 6017, Oak Ridge, TN 37831, USA.

Funding

Department of Veterans Affairs Office of Health Informatics 36C10B21M0005Department of Veterans Affairs, Office of Mental Health and Suicide PreventionOffice of Science of the US Department of Energy DE-AC05-00OR22725VA-DoD Joint Incentive Fund
6 · The paper itself

Abstract

backgroundSuicide is a leading cause of death in the US Comparative State-level spatial analysis between Veterans Health Administration (VHA veterans) and the whole US population can reveal differences in conditions for targeted interventions and intricate geographical patterns.

methodsThe study population contains 2018 and 2019 suicide deaths of VHA veterans and the whole US population. They were used to calculate state-level rates. States were classified by whether their VHA veteran and whole US population rates were above or below respective mean rates. Local Moran's I was leveraged to examine spatial autocorrelation.

resultsState-level suicide mortality rates and disparities among states were generally higher for VHA veterans (2018: 37.3 ± 7.2; 2019: 46.8 ± 8.3) than for the whole US population (2018: 16.6 ± 4.3; 2019: 16.4 ± 4.4). For both populations, there were statistically significant clusters with high suicide rates. Over one-fourth of states demonstrated inverse relationships, with rates above mean for one group but below for other. VHA veterans are at higher risk with over one-third of states had greater than average veteran suicide risk ratio.

conclusionsVHA veterans are at higher risk than the whole population across all states. Mortality disparities among states and clusters of states with high and low rates suggest targeted interventions and cooperative health strategies may help address these differences.

Indexed as

SuicideVeteransAdultFemaleHumansMaleMiddle AgedUnited StatesUnited States Department of Veterans Affairsclusteringepidemiologyspatial analysissuicideUS veterans

Identifiers

PMID40188495
PMCPMC12123301

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.