Military Occupation and Deployment: Descriptive Epidemiology of Active Duty U.S. Army Men Evaluated for a Disability Discharge

Background Civilian suicide rates vary by occupation in ways related to occupational stress exposure. Comparable military research finds suicide rates elevated in combat arms occupations. However, no research has evaluated variation in this pattern by deployment history, the indicator of occupation stress widely considered responsible for the recent rise in the military suicide rate. Method The joint associations of Army occupation and deployment history in predicting suicides were analysed in an administrative dataset for the 729 337 male enlisted Regular Army soldiers in the US Army between 2004 and 2009. Results There were 496 suicides over the study period (22.4/100 000 person-years). Only two occupational categories, both in combat arms, had significantly elevated suicide rates: infantrymen (37.2/100 000 person-years) and combat engineers (38.2/100 000 person-years). However, the suicide rates in these two categories were significantly lower when currently deployed (30.6/100 000 person-years) than never deployed or previously deployed (41.2–39.1/100 000 person-years), whereas the suicide rate of other soldiers was significantly higher when currently deployed and previously deployed (20.2–22.4/100 000 person-years) than never deployed (14.5/100 000 person-years), resulting in the adjusted suicide rate of infantrymen and combat engineers being most elevated when never deployed [odds ratio (OR) 2.9, 95% confidence interval (CI) 2.1–4.1], less so when previously deployed (OR 1.6, 95% CI 1.1–2.1), and not at all when currently deployed (OR 1.2, 95% CI 0.8–1.8). Adjustment for a differential ‘healthy warrior effect’ cannot explain this variation in the relative suicide rates of never-deployed infantrymen and combat engineers by deployment status. Conclusions Efforts are needed to elucidate the causal mechanisms underlying this interaction to guide preventive interventions for soldiers at high suicide risk.

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“…2011; Belisle et al . 2013; Gubata et al . 2013), and the predictors of re-enlistment (Garvey Wilson et al .…”

Section: Discussionmentioning

confidence: 99%

“…2006; Niebuhr et al . 2011; Gubata et al . 2013), we distinguished combat arms occupations from combat support (providing operational assistance to combat arms) and combat service support (all other Army occupations) (Kirin & Winkler, 1992; Layne et al .…”

Section: Methodsmentioning

confidence: 99%

Occupational differences in US Army suicide rates

et al. 2015

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“…For one, they could be used as the basis of a cluster analysis 37 of commonly occurring multivariate job profiles that might be treated as predictors of adverse outcomes that have been previously studied in both military and civilian occupations, such as substance use, obesity, hypertension, physical injury, hospitalization, disability discharge, and suicide. 11,12,14,20,36 Another possibility would be to use the 21 scales in nested discretized form as the starting point for regression tree analyses aimed at detecting multivariate job condition profiles associated with high risk of adverse outcomes. 38 This is a particularly attractive option for studying effects of job conditions on health given that much of the theorizing about these effects, most notably the influential demand–control model 5 and its extensions, 39 hypothesize that mismatch between multiple job conditions is centrally involved in the adverse health effects of pathogenic occupations.…”

Section: Discussionmentioning

confidence: 99%

“…Although few comparable studies have been carried out in the military, research has documented significant differences across military occupations in rates of job satisfaction, 10 injury, 11 disability, 12 and suicide. 13,14 A limitation of these military occupational studies is that the denominator population is too small to generate stable outcome estimates for most individual occupations, whereas broadly defined occupational groups, such as two-digit Department of Defense-wide occupation codes, are not designed to define a meaningful dimension in predicting a diverse range of outcomes.…”

Section: Introductionmentioning

confidence: 99%

Classifying U.S. Army Military Occupational Specialties Using the Occupational Information Network

Gadermann¹,

Heeringa²,

Stein³

et al. 2014

Military Medicine

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Objectives To derive job condition scales for future studies of the effects of job conditions on soldier health and job functioning across Army Military Occupation Specialties (MOSs) and Areas of Concentration (AOCs) using Department of Labor (DoL) Occupational Information Network (O*NET) ratings. Methods A consolidated administrative dataset was created for the “Army Study to Assess Risk and Resilience in Servicemembers” (Army STARRS) containing all soldiers on active duty between 2004 and 2009. A crosswalk between civilian occupations and MOS/AOCs (created by DoL and the Defense Manpower Data Center) was augmented to assign scores on all 246 O*NET dimensions to each soldier in the dataset. Principal components analysis was used to summarize these dimensions. Results Three correlated components explained the majority of O*NET dimension variance: “physical demands” (20.9% of variance), “interpersonal complexity” (17.5%), and “substantive complexity” (15.0%). Although broadly consistent with civilian studies, several discrepancies were found with civilian results reflecting potentially important differences in the structure of job conditions in the Army versus the civilian labor force. Conclusions Principal components scores for these scales provide a parsimonious characterization of key job conditions that can be used in future studies of the effects of MOS/AOC job conditions on diverse outcomes.

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“…6 In addition, a study evaluating both deployed and nondeployed individuals found that those with combat arms MOS had significantly greater TBI diagnoses than those in other MOS categories. 26 Additional research is needed to identify what factors related to combat arms occupation (eg, controlled explosions or explosive attacks) are potentially modifiable.…”

Section: Disucssionmentioning

confidence: 99%

Preenlistment and Early Service Risk Factors for Traumatic Brain Injury in the Army and Marine Corps: FY 2002-2010

Elmasry

Boivin

Feng³

et al. 2017

Journal of Head Trauma Rehabilitation

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Military Occupation and Deployment: Descriptive Epidemiology of Active Duty U.S. Army Men Evaluated for a Disability Discharge

Abstract: Combat Arms MOS is a significant risk factor for disability retirement primarily among deployed men. Further research is needed to identify specific military occupations most at risk for disability retirement.

Cited by 28 publications

References 19 publications

Occupational differences in US Army suicide rates

Occupational differences in US Army suicide rates

Classifying U.S. Army Military Occupational Specialties Using the Occupational Information Network

Preenlistment and Early Service Risk Factors for Traumatic Brain Injury in the Army and Marine Corps: FY 2002-2010

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