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093 Female firearm suicide across the lifespan: a descriptive assessment of cases from the national violent death reporting system
  1. Laura Prater,
  2. Erin Morgan,
  3. Miriam Haviland,
  4. Julian Takagi-Stewart,
  5. Brianna Agnew,
  6. Stephen Mooney
  1. University of Washington, Seattle, USA


Statement of Purpose Suicide is a critical health problem for Americans, and a leading cause of death. Firearm suicide is particularly devastating, and females are often overlooked due to the greater frequency of suicide among older white males. A highly lethal method, firearms are responsible for approximately 50% of suicides. As part of a larger National Collaborative on Gun Violence Research study, we aimed to describe characteristics of females who died from firearm suicide.

Methods/Approach We used the National Violent Death Reporting System (NVDRS) to do a descriptive assessment of demographic and health-related characteristics of female firearm suicides. Data were collected through interviews of survivors as well as extracted from Coroner or Medical Examiner/Law Enforcement (CME/LE) reports from NVDRS-reporting states from 2014–2018.

Results There were 8,318 cases of female firearm suicide available for analysis; 90.6% of females were white (n=7,534), 5.2% (n=428) were Black, 1.5% (n=96) were Asian/Pacific Islander, and 1.2% were American Indian/Alaska Native; 3.6% (n=302) were Hispanic. The average age of decedents was 47.2 (SD = 17.0). A diagnosis of depression was present among 40.4% (n=3,363) and a history of suicidal thoughts was noted for 32.2% (n=2,676).

Conclusion Many female firearm suicide decedents had a known diagnosis of depression and a history of suicidal thoughts. Prior intervention to remove firearms from females exhibiting depression and/or suicidal thoughts may be an effective strategy to prevent mortality from suicide attempt.

Significance This study is one of the first to examine characteristics of females across the lifespan who died by firearm suicide. Future directions include using natural language processing (NLP) to code additional variables specific to females (e.g. postpartum depression). We will also link Washington’s state-based VDRS to an all payer claims database, using this information to better understand interactions with the health care system prior to death.

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