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Sociodemographic and career history predictors of suicide mortality in the United States Army 2004–2009

Published online by Cambridge University Press:  19 February 2014

S. E. Gilman
Affiliation:
Departments of Social and Behavioral Sciences, and Epidemiology, Harvard School of Public Health, Boston, MA, USA
E. J. Bromet
Affiliation:
Department of Psychiatry and Behavioral Science, Stony Brook School of Medicine, Stony Brook, NY, USA
K. L. Cox
Affiliation:
US Army Public Health Command, Aberdeen Proving Ground, MD, USA
L. J. Colpe
Affiliation:
Division of Services and Intervention Research, National Institute of Mental Health, Bethesda, MD, USA
C. S. Fullerton
Affiliation:
Center for the Study of Traumatic Stress, Department of Psychiatry, Uniformed Services University School of Medicine, Bethesda, MD, USA
M. J. Gruber
Affiliation:
Department of Health Care Policy, Harvard Medical School, Boston, MA, USA
S. G. Heeringa
Affiliation:
Institute for Social Research, University of Michigan, Ann Arbor, MI, USA
L. Lewandowski-Romps
Affiliation:
Institute for Social Research, University of Michigan, Ann Arbor, MI, USA
A. M. Millikan-Bell
Affiliation:
US Army Public Health Command, Aberdeen Proving Ground, MD, USA
J. A. Naifeh
Affiliation:
Center for the Study of Traumatic Stress, Department of Psychiatry, Uniformed Services University School of Medicine, Bethesda, MD, USA
M. K. Nock
Affiliation:
Department of Psychology, Harvard University, Cambridge, MA, USA
M. V. Petukhova
Affiliation:
Department of Health Care Policy, Harvard Medical School, Boston, MA, USA
N. A. Sampson
Affiliation:
Department of Health Care Policy, Harvard Medical School, Boston, MA, USA
M. Schoenbaum
Affiliation:
Office of Science Policy, Planning and Communications, National Institute of Mental Health, Bethesda, MD, USA
M. B. Stein
Affiliation:
Departments of Psychiatry and Family and Preventive Medicine, University of California San Diego, La Jolla, CA, USA VA San Diego Healthcare System, San Diego, CA, USA
R. J. Ursano
Affiliation:
Center for the Study of Traumatic Stress, Department of Psychiatry, Uniformed Services University School of Medicine, Bethesda, MD, USA
S. Wessely
Affiliation:
King's Centre for Military Health Research, King's College London, London, UK
A. M. Zaslavsky
Affiliation:
Department of Health Care Policy, Harvard Medical School, Boston, MA, USA
R. C. Kessler*
Affiliation:
Department of Health Care Policy, Harvard Medical School, Boston, MA, USA
*
*Address for correspondence: R. C. Kessler, Ph.D., Department of Health Care Policy, Harvard Medical School, Boston, MA, USA. (Email: ncs@hcp.med.harvard.edu)

Abstract

Background

The US Army suicide rate has increased sharply in recent years. Identifying significant predictors of Army suicides in Army and Department of Defense (DoD) administrative records might help focus prevention efforts and guide intervention content. Previous studies of administrative data, although documenting significant predictors, were based on limited samples and models. A career history perspective is used here to develop more textured models.

Method

The analysis was carried out as part of the Historical Administrative Data Study (HADS) of the Army Study to Assess Risk and Resilience in Servicemembers (Army STARRS). De-identified data were combined across numerous Army and DoD administrative data systems for all Regular Army soldiers on active duty in 2004–2009. Multivariate associations of sociodemographics and Army career variables with suicide were examined in subgroups defined by time in service, rank and deployment history.

Results

Several novel results were found that could have intervention implications. The most notable of these were significantly elevated suicide rates (69.6–80.0 suicides per 100 000 person-years compared with 18.5 suicides per 100 000 person-years in the total Army) among enlisted soldiers deployed either during their first year of service or with less than expected (based on time in service) junior enlisted rank; a substantially greater rise in suicide among women than men during deployment; and a protective effect of marriage against suicide only during deployment.

Conclusions

A career history approach produces several actionable insights missed in less textured analyses of administrative data predictors. Expansion of analyses to a richer set of predictors might help refine understanding of intervention implications.

Type
Original Articles
Copyright
Copyright © Cambridge University Press 2014 

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