Latent Class Patterns of Adverse Childhood Experiences and Their Relationship to Veteran Status and Sex in the National Epidemiologic Survey of Alcohol and Related Conditions Wave III.

Introduction: Adverse childhood experiences (ACEs) are associated with poor psychosocial and health outcomes in adulthood. Veterans and females experience ACEs disproportionately. A greater understanding of this disparity may be achieved by examining the relationship between distinct ACE patterns an...

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Publicado en:Military Medicine Vol. 187; no. 3/4; pp. 304 - 313
Autores principales: Tynan, Mara, Wooldridge, Jennalee S, Rossi, Fernanda, McLean, Caitlin L, Gasperi, Marianna, Bosch, Jeane, Timko, Christine, Herbert, Matthew, Afari, Niloofar
Formato: research tables/charts Journal Article
Publicado: Oxford University Press / USA Mar/Apr2022
Acceso en línea:Ver este registro en EBSCOhost
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        atl: Latent Class Patterns of Adverse Childhood Experiences and Their Relationship to Veteran Status and Sex in the National Epidemiologic Survey of Alcohol and Related Conditions Wave III.
      aug:
        au:
          Tynan, Mara
          Wooldridge, Jennalee S
          Rossi, Fernanda
          McLean, Caitlin L
          Gasperi, Marianna
          Bosch, Jeane
          Timko, Christine
          Herbert, Matthew
          Afari, Niloofar
        affil: San Diego Joint Doctoral Program in Clinical Psychology, San Diego State University/University of California , San Diego, CA 92120, USA
      sug:
        subj:
          Veterans Psychosocial Factors
          Middle Age
          Family Characteristics
          Female
          Male
          Income
          Adult
          United States
          Human
          Funding Source
          Middle Aged: 45-64 years
          Adult: 19-44 years
          Female
          Male
      ab: Introduction: Adverse childhood experiences (ACEs) are associated with poor psychosocial and health outcomes in adulthood. Veterans and females experience ACEs disproportionately. A greater understanding of this disparity may be achieved by examining the relationship between distinct ACE patterns and these demographic characteristics. Therefore, this study examined distinct ACE patterns and their association with Veteran status, sex, and other demographics in a nationally representative sample of U.S. adults to inform interventions tailored to ACE patterns experienced by specific groups.Materials and Methods: Latent class analysis (LCA) was conducted with data from the National Epidemiologic Survey of Alcohol and Related Conditions-III, a nationally representative structured diagnostic interview conducted from 2012-2013. The target population was the noninstitutionalized adult population living in the USA. The analytic sample was 36,190 (mean age 46.5 years; 48.1% male). Of these participants, 3,111 were Veterans. Data were analyzed between September 2020 and January 2021.Results: Latent class analysis revealed a four-class solution: (1) "Low adversity" (75.3%); (2) "Primarily household dysfunction" (9.0%); (3) "Primarily maltreatment" (10.7%); and (4) "Multiple adversity types" (5.1%). Compared to "Low adversity," members in the other classes were more likely to be Veterans (odds ratio (OR)C2vC1 = 1.33, ORC3vC1 = 1.55, ORC4vC1 = 1.98) and female (ORC2vC1 = 1.58, ORC3vC1 = 1.22, ORC4vC1 = 1.65). While lower education and income were also related to higher adversity class membership, Veteran status and sex were the strongest predictors, even when controlling for education and income.Conclusions: Distinct and meaningful patterns of ACEs identified in this study highlight the need for routine ACE screenings in Veterans and females. As in the current study, operationalizing and clustering ACEs can inform screening measures and trauma-informed interventions in line with personalized medicine. Future work can test if classes are differentially associated with health outcomes.
      pubtype: Academic Journal
      doctype:
        research
        tables/charts
        Journal Article
      ougenre: Article
    language: English
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