Citation

Xu Y, Ajdacic-Gross V, Müller M, Buadze A, Seifritz E, Kleim B, von Känel R, Wagner EYN, Strippoli MPF, Castelao E, Preisig M, Vandeleur CL. Compr. Psychiatry 2021; 112: e152282.

Copyright

(Copyright © 2021, Elsevier Publishing)

DOI

10.1016/j.comppsych.2021.152282

PMID

34749059

Abstract

BACKGROUND: Exposure to childhood adversities (CHAD) has been found to be strongly associated with individuals' mental health and social development. Recently, it has been suggested that certain CHAD patterns exist in the population, which are more closely related to individuals' later mental health than the simple summation of adversities. The current study aims 1) to establish CHAD patterns based on self-reported child abuse and family dysfunction and 2) to assess their associations with mental disorders and sociodemographic indicators reported in adulthood.

METHODS: Data used in this cross-sectional study were derived from the representative CoLaus/PsyCoLaus population-based cohort (N = 5111, 35 to 88 years). Latent class analysis was conducted for the identification of CHAD patterns, while their associations with mental disorders and socioeconomic achievements (e. g. education and income) were investigated using correspondence analysis.

RESULTS: Four CHAD patterns emerged. While the majority (70.7%) of the sample showed an overall low adversity pattern (c1), 13.6% had not been raised by both of their biological parents due to divorce or being placed in foster home (c2), 11.0% had been raised by conflictive / dysfunctional / abusive parents (c3), and 4.7% showed high overall adversities (c4). Patterns c3 and c4 were most strongly associated with various mental disorders, especially c3 with internalizing anxiety disorders, while c2 was closely related to lower educational achievement.

CONCLUSIONS: Four CHAD patterns characterised by varying levels of child abuse and family dysfunction existed in this community sample. They yielded distinct associations with mental disorders and socioeconomic indicators.

Language: en

Keywords

Clustering; Domestic violence; Child abuse; Childhood adversity; Correspondence analysis; Family dysfunction; Latent class analysis