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Research Questions

  1. What characteristics explain variability in the Army's suicide rate?
  2. What data sources are available to identify variability in general U.S. suicide rates?
  3. What characteristics explain variability in the general U.S. population suicide rate?
  4. On what factors might the authors aim to match or standardize the general U.S. population to look like that of the Army?
  5. What are the effects and implications of expanding the matching factors to include age, gender, race/ethnicity, time, marital status, and educational attainment?
  6. What is the potential effect of "unmatchable" factors on the comparison of suicide rates between the Army and the general U.S. population?

Over the past 15 years, the suicide rate among members of the U.S. armed forces has doubled, with the greatest increase observed among soldiers in the Army. This increasing rate is paralleled by a smaller increase in the general U.S. population, observed across both genders, in virtually every age group and in nearly every state. An empirical question exists: What is the extent or degree to which the suicide trend in the Army is unique to that service, relative to what is observed in the general U.S. population?

The Army has typically attempted to address this question by standardizing the general population to look like the Army on demographic characteristics. However, given the rise in suicide rates over the past decade, the Army wanted to better understand whether standardization based solely on age and gender is enough. Expanding the characteristics on which the general population is standardized to match the Army could be useful to gain a better understanding of the suicide trends in the Army. However, such a change also brings with it some challenges, including the lack of readily available data in the general U.S. population. In addition, even an expanded set of characteristics still results in having a large number of unmeasured factors that cannot be included in this type of analysis.

In this report, the authors explore how accounting for age, gender, race/ethnicity, time, marital status, and educational attainment affects suicide rate differences between soldiers and a comparable subset of the general U.S. population.

Key Findings

Matchable, comparable factors between the Army and the general U.S. population are needed

  • The authors identified six factors available for comparing the populations: gender, age, race/ethnicity, time, marital status, and educational attainment.
  • Five additional factors could be important for this comparison: geography, parenthood, occupation, mental health, and firearm availability.

Using an expanded set of factors reveals that the expected suicide rate in the general U.S. population is consistently lower than when adjusting for age and gender only

  • Marital status was the key factor driving this shift.

Occupation coding needs to be improved to compare the Army with the general U.S. population

  • As occupation is a known risk factor for suicide in both populations, better-quality data on decedents in the general population would be useful.
  • A soldier's job-related duties and operational tempo are other factors that may distinguish the Army and general U.S. populations, but drawing parallels between job categories in the two populations proved difficult.

Firearm data are lacking

  • Soldiers may differ from their general population counterparts regarding ownership of or access to personally owned firearms.
  • The lack of high-quality data on personally owned firearms among soldiers and the general population impedes the Army's ability to study this potentially important factor.

Mental health diagnoses need to be examined and standardized

  • Mental health conditions are among the strongest risk factors for suicide; however, accounting for mental health diagnoses when comparing the Army and general U.S. population will require identifying data in the U.S. population that link known diagnoses to deaths.

Recommendations

  • When comparing the Army's suicide rate with that of the general U.S. population, comparisons should be adjusted for age, gender, and year, and for the additional matchable factors of race/ethnicity, educational attainment, and marital status.
  • Because the conclusions one can draw from comparing the suicide rates of the Army and the general U.S. population will change depending on which factors are used to match the populations, the preferred comparison should be the one that includes factors that (1) are associated with suicide risk, (2) differ between the military and the general population, and (3) are outside the control of the Army.
  • The Army should collaborate with the U.S. Census Bureau, the Centers for Disease Control and Prevention (CDC), and the U.S. Department of Labor to improve occupation/industry coding for general U.S. population deaths.
  • The Army should collect voluntary data on soldiers who own personal firearms and should encourage the CDC or another federal agency to resume collecting voluntarily provided survey data on gun ownership and use in the general population.
  • Future research should examine the suicide risk among those with mental health diagnoses in the Army relative to similar individuals in the general U.S. population.

Table of Contents

  • Chapter One

    Introduction

  • Chapter Two

    Suicide Risk and Protective Factors

  • Chapter Three

    Army Risk Factors

  • Chapter Four

    General Population Risk Factors

  • Chapter Five

    Matching the Army to a Comparable Subset of General U.S. Population

  • Chapter Six

    Conclusions

  • Appendix A

    Industry and Occupation Coding in the NVDRS

  • Appendix B

    Suicide Modeling Methods

  • Appendix C

    Candidate Data Sources on General Population Suicides

  • Appendix D

    Data Harmonization

  • Appendix E

    Analyses for Location and Deployment History

  • Appendix F

    2015 Army Analysis

Research conducted by

The research described in this report was sponsored by the United States Army and conducted by the Personnel, Training, and Health Program within the RAND Arroyo Center.

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