A data-driven approach to categorizing early life adversity exposure in the ABCD Study

BMC Medical Research Methodology

Research

Natalia Orendain¹  Susan Bookheimer¹  Adriana Galván²  Ariana Anderson³  Paul J. Chung⁴ 

[1] Center for Cognitive Neuroscience, University of California, Los Angeles, CA, USA;Department of Psychiatry and Biobehavioral Sciences, University of California, Los Angeles, CA, USA;David Geffen School of Medicine, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, CA, USA;David Geffen School of Medicine, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, CA, USA;Department of Psychology, University of California, Los Angeles, CA, USA;Department of Psychiatry and Biobehavioral Sciences, University of California, Los Angeles, CA, USA;David Geffen School of Medicine, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, CA, USA;Departments of Pediatrics and Health Policy & Management, University of California, Los Angeles, CA, USA;Department of Health Systems Science, Kaiser Permanente Bernard J. Tyson School of Medicine, Pasadena, CA, USA;

关键词: ACEs;    Early life adversity exposure;    Problematic behaviors;    Factor analysis;    CBCL;   

DOI  :  10.1186/s12874-023-01983-9

 received in 2023-01-03, accepted in 2023-06-22,  发布年份 2023

来源: Springer

【 摘 要 】

BackgroundAdversity occurring during development is associated with detrimental health and quality of life outcomes, not just following exposure but throughout the lifespan. Despite increased research, there exists both overlapping and distinct definitions of early life adversity exposure captured by over 30 different empirically validated tools. A data-driven approach to defining and cataloging exposure is needed to better understand associated outcomes and advance the field.MethodsWe utilized baseline data on 11,566 youth enrolled in the ABCD Study to catalog youth and caregiver-reported early life adversity exposure captured across 14 different measures. We employed an exploratory factor analysis to identify the factor domains of early life adversity exposure and conducted a series of regression analyses to examine its association with problematic behavioral outcomes.ResultsThe exploratory factor analysis yielded a 6-factor solution corresponding to the following distinct domains: 1) physical and sexual violence; 2) parental psychopathology; 3) neighborhood threat; 4) prenatal substance exposure; 5) scarcity; and 6) household dysfunction. The prevalence of exposure among 9-and 10-year-old youth was largely driven by the incidence of parental psychopathology. Sociodemographic characteristics significantly differed between youth with adversity exposure and controls, depicting a higher incidence of exposure among racial and ethnic minoritized youth, and among those identifying with low socioeconomic status. Adversity exposure was significantly associated with greater problematic behaviors and largely driven by the incidence of parental psychopathology, household dysfunction and neighborhood threat. Certain types of early life adversity exposure were more significantly associated with internalizing as opposed to externalizing problematic behaviors.ConclusionsWe recommend a data-driven approach to define and catalog early life adversity exposure and suggest the incorporation of more versus less data to capture the nuances of exposure, e.g., type, age of onset, frequency, duration. The broad categorizations of early life adversity exposure into two domains, such as abuse and neglect, or threat and deprivation, fail to account for the routine co-occurrence of exposures and the duality of some forms of adversity. The development and use of a data-driven definition of early life adversity exposure is a crucial step to lessening barriers to evidence-based treatments and interventions for youth.

【 授权许可】

CC BY   
© The Author(s) 2023

【 图 表 】

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