Mental disorders associated with subpopulations of women affected by violence and abuse

Courtenay E. Cavanaugh, Silvia S. Martins, Hanno Petras, Jacquelyn C. Campbell

Research output: Contribution to journalArticlepeer-review

18 Scopus citations

Abstract

Violence against women is a major public health problem associated with mental disorders. Few studies have examined the heterogeneity of interpersonal violence and abuse (IVA) among women and associated mental health problems. Latent class analysis was used to identify subpopulations of women with similar lifetime histories of IVA victimization and to examine 10 associated past-year mental disorders. Participants were 19,816 adult women who participated in Wave 2 of the National Epidemiologic Study on Alcohol and Related Conditions (NESARC). The 3-class model was best supported by the data. Class 1 (6.7%) had a high probability of witnessing domestic violence as a child. Class 2 (21.8%) had a low probability of all events except lifetime sexual assault. Class 3 (71.5%) had a low probability for all events. Mental disorders were more common among members of Classes 1 and 2 than Class 3. For example, members in Class 1 were approximately 8 and 9 times more likely than members in Class 3 to have had posttraumatic stress disorder or a drug use disorder, respectively, during the past year. Of the 10 mental disorders, 5 were more common among members of Class 1 than of Class 2. Findings suggest the mental health consequences of IVA among women are extensive and interventions should be tailored for distinct subpopulations affected by IVA.

Original languageEnglish (US)
Pages (from-to)459-466
Number of pages8
JournalJournal of traumatic stress
Volume26
Issue number4
DOIs
StatePublished - Aug 2013
Externally publishedYes

ASJC Scopus subject areas

  • Clinical Psychology
  • Psychiatry and Mental health

Fingerprint

Dive into the research topics of 'Mental disorders associated with subpopulations of women affected by violence and abuse'. Together they form a unique fingerprint.

Cite this