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Intimate partner violence and suicide mortality: a cross-sectional study using machine learning and natural language processing of suicide data from 43 states
  1. Julie M Kafka1,2,3,
  2. Kathryn Elizabeth Moracco1,3,
  3. Brian W Pence3,4,
  4. Pamela J Trangenstein1,5,
  5. Mike Dolan Fliss3,
  6. Luz McNaughton Reyes1,3
  1. 1 Health Behavior, University of North Carolina at Chapel Hill Gillings School of Global Public Health, Chapel Hill, North Carolina, USA
  2. 2 Firearm Injury & Policy Research Program, University of Washington, Seattle, Washington, USA
  3. 3 Injury Prevention Research Center, The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
  4. 4 Department of Epidemiology, The University of North Carolina at Chapel Hill Gillings School of Global Public Health, Chapel Hill, North Carolina, USA
  5. 5 Alcohol Research Group, Public Health Institute, Oakland, California, USA
  1. Correspondence to Dr Julie M Kafka, Health Behavior, University of North Carolina at Chapel Hill Gillings School of Global Public Health, Chapel Hill, NC 27599, USA; jkafka{at}uw.edu

Abstract

Introduction Intimate partner violence (IPV) is associated with suicidal ideation, yet it remains unclear how often IPV precipitates suicide mortality. To overcome limitations with national data, we applied novel methods to: (1) document the prevalence of IPV-related suicide in the USA and (2) identify correlates for IPV-related suicide.

Methods Using National Violent Death Reporting System data (NVDRS, 2015–2019, n=1 30 550), we recorded IPV circumstances (yes/no) by leveraging prior textual reviews of death narratives and applying a validated natural language processing tool. We could not systematically differentiate IPV perpetration versus victimisation given limited details in NVDRS. Logistic regression compared IPV-related suicides with referent group suicides (no evidence of IPV), stratified by sex.

Results 7.1% of suicides were IPV related (n=9210), most were isolated suicide events (82.8%, n=7625; ie, not homicide suicide). There were higher odds of IPV circumstances when the decedent had civil legal problems (aOR for men: 3.6 (3.3 to 3.9), aOR for women: 2.6 (2.2 to 3.2)), criminal legal problems (aOR men: 2.3 (2.2 to 2.5), aOR for women: 1.7 (1.4 to 2.1)), or used a firearm (aOR men: 1.9 (1.8 to 2.0), aOR for women: 1.9 (1.7 to 2.1)). There were lower odds of IPV circumstances when the decedent had a current mental health problem (aOR men: 0.7 (0.7 to 0.8), aOR for women: 0.7 (0.6 to 0.8)).

Conclusions IPV circumstances contribute to a notable proportion of suicides. IPV-related suicides are distinct from other suicide deaths. Targeted suicide screening and intervention in IPV settings may be beneficial for prevention.

  • Violence
  • Surveillance
  • Mortality
  • Suicide/Self?Harm

Data availability statement

Data may be obtained from a third party. The Restricted Access Data (RAD) from the National Violent Death Reporting System (NVDRS) can be obtained through a request to the Centers for Disease Control and Prevention (CDC). The supervised machine learning tool used in this study is available online, along with a tutorial at the following link: https://github.com/jkafka/IPVsuicide.

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Data availability statement

Data may be obtained from a third party. The Restricted Access Data (RAD) from the National Violent Death Reporting System (NVDRS) can be obtained through a request to the Centers for Disease Control and Prevention (CDC). The supervised machine learning tool used in this study is available online, along with a tutorial at the following link: https://github.com/jkafka/IPVsuicide.

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Footnotes

  • Twitter @bethmoracco, @mikedolanfliss

  • Contributors JMK: conceptualisation (lead), data curation, formal analysis, funding acquisition, investigation, methodology (lead), validation, software (lead), writing—original draft, guarantor. KEM: conceptualisation (supporting), data curation (supporting), investigation (supporting), supervision, writing—reviewing and editing (lead). BWP: conceptualisation (supporting), methodology (supporting), writing—reviewing and editing (equal). PJT: conceptualisation (supporting), writing—reviewing and editing. MDF: conceptualisation (supporting), methodology (supporting), writing—reviewing and editing (equal). LMcNR: conceptualisation (supporting), methodology (supporting), writing—reviewing and editing (equal).

  • Funding The first author (JMK) was funded by the National Collaborative on Gun Violence Research to conduct this work in the final year of her dissertation. She was also funded as a research fellow by the University of North Carolina (UNC) Injury Prevention Research Center (IPRC) in previous years, and thus this study was also partially supported by award R49/CE19-003092 from the National Center for Injury Prevention and Control at the Centers for Disease Control and Prevention (CDC). MDF, LMcNR, BWP and KEM were also supported in part through UNC IPRC and thus through CDC award R49/CE19-003092. The first author also received a summer research fellowship from the UNC Graduate School to launch some of the pilot work for this research. The views expressed in this manuscript are the authors’ alone and do not necessarily reflect the view of any funders or NVDRS participating states.

  • Competing interests None declared.

  • Patient and public involvement Patients and/or the public were not involved in the design, or conduct, or reporting, or dissemination plans of this research.

  • Provenance and peer review Not commissioned; externally peer-reviewed.

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