Adverse childhood experiences and adult outcomes using a causal framework perspective: Challenges and opportunities.

Autor: Jaen J; Mexican School of Public Health, National Institute of Public Health, Cuernavaca, Morelos, Mexico., Lovett SM; Department of Epidemiology, Boston University School of Public Health, Boston, MA, United States., Lajous M; Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, MA, United States; Center for Research on Population Health, National Institute of Public Health, Cuernavaca, Morelos, Mexico., Keyes KM; Columbia University Mailman School of Public Health, NY, NY, United States., Stern D; CONAHCyT - Center for Research on Population Health, National Institute of Public Health, Cuernavaca, Morelos, Mexico. Electronic address: dalia.stern@insp.mx.
Jazyk: angličtina
Zdroj: Child abuse & neglect [Child Abuse Negl] 2023 Sep; Vol. 143, pp. 106328. Date of Electronic Publication: 2023 Jun 26.
DOI: 10.1016/j.chiabu.2023.106328
Abstrakt: Background: Research on the effect of adverse childhood experiences (ACEs) on adult outcomes has typically relied on retrospective assessment of ACEs and cumulative scores. However, this approach raises methodological challenges that can limit the validity of findings.
Objective: The aims of this paper are 1) to present the value of directed acyclic graphs (DAGs) to identify and mitigate potential problems related to confounding and selection bias, and 2) to question the meaning of a cumulative ACE score.
Results: Adjusting for variables that post-date childhood could block mediated pathways that are part of the total causal effect while conditioning on adult variables, which often serve as proxies for childhood variables, can create collider stratification bias. Because exposure to ACEs can affect the likelihood of reaching adulthood or study entry, selection bias could be introduced via restricting selection on a variable affected by ACEs in the presence of unmeasured confounding. In addition to challenges regarding causal structure, using a cumulative score of ACEs assumes that each type of adversity will have the same effect on a given outcome, which is unlikely considering differing risk across adverse experiences.
Conclusions: DAGs provide a transparent approach of the researchers' assumed causal relationships and can be used to overcome issues related to confounding and selection bias. Researchers should be explicit about their operationalization of ACEs and how it is to be interpreted in the context of the research question they are trying to answer.
Competing Interests: Conflicts of interest The authors have no conflicts of interest to disclose.
(Copyright © 2023 Elsevier Ltd. All rights reserved.)
Databáze: MEDLINE
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