Using latent class analysis to empirically classify maltreatment according to the developmental timing, duration, and co-occurrence of abuse types

Hannah N. Ziobrowski, Stephen L. Buka, S. Bryn Austin, Adam J. Sullivan, Nicholas J. Horton, Melissa Simone, Alison E. Field

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

Background: Individuals can have vastly different maltreatment experiences depending on the types, developmental timing, and duration of abuse. Women and men may be differentially affected by distinct abuse patterns. Objective: To examine whether maltreatment subgroups could be identified based on the types, developmental timing, and duration of abuse, and to determine their prevalence among a large, community-based sample. We also examined sex differences in associations of maltreatment subgroups with adverse health outcomes. Participants and Setting: Data came from 9310 women and men (95 % White) in the United States who responded to the Growing Up Today Study questionnaire in 2007 (aged 19–27 years). Methods: Participants reported on physical, sexual, and emotional abuse occurring in childhood (before age 11 years) and adolescence (ages 11−17 years). We conducted latent class (LC) analyses using indicators for child and adolescent abuse. We examined associations of LCs with health outcomes using sex-stratified log-binomial models with generalized estimated equations. Results: We identified five LCs characterized by: 1) no/low abuse (59 %), 2) child physical abuse (16 %), 3) adolescent emotional abuse (9%), 4) child and adolescent physical and emotional abuse (16 %), and 5) child and adolescent sexual abuse (1%). LCs were uniquely associated adult health outcomes among both women and men. Associations of LCs with eating disorder behaviors appeared stronger for men than women. Conclusions: Individuals experience distinct patterns of maltreatment based on the types, developmental timing, and duration of abuse. These patterns are uniquely associated with adverse health outcomes in adulthood, and can be identified using LCA.

Original languageEnglish (US)
Article number104574
JournalChild Abuse and Neglect
Volume107
DOIs
StatePublished - Sep 2020

Bibliographical note

Funding Information:
Data collection was supported by research grants from the National Institutes of Health, USA ( MH087786 , DK59570 , DK46200 , HL68041 , HD049889 , DA033974 , HD066963 , OH0098003 ). S.B. Austin is supported by the Maternal and Child Health Bureau , Health Resources and Services Administration, USA ( T71MC00009 , T76MC00001 ).

Publisher Copyright:
© 2020 Elsevier Ltd

Copyright:
Copyright 2020 Elsevier B.V., All rights reserved.

Keywords

  • Child abuse
  • Epidemiology
  • Latent class analysis
  • Population-based

PubMed: MeSH publication types

  • Journal Article

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