Early childhood household instability, adolescent structural neural network architecture, and young adulthood depression: A 21-year longitudinal study

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Abstract

Unstable and unpredictable environments are linked to risk for psychopathology, but the underlying neural mechanisms that explain how instability relate to subsequent mental health concerns remain unclear. In particular, few studies have focused on the association between instability and white matter structures despite white matter playing a crucial role for neural development. In a longitudinal sample recruited from a population-based study (N = 237), household instability (residential moves, changes in household composition, caregiver transitions in the first 5 years) was examined in association with adolescent structural network organization (network integration, segregation, and robustness of white matter connectomes; Mage = 15.87) and young adulthood anxiety and depression (six years later). Results indicate that greater instability related to greater global network efficiency, and this association remained after accounting for other types of adversity (e.g., harsh parenting, neglect, food insecurity). Moreover, instability predicted increased depressive symptoms via increased network efficiency even after controlling for previous levels of symptoms. Exploratory analyses showed that structural connectivity involving the left fronto-lateral and temporal regions were most strongly related to instability. Findings suggest that structural network efficiency relating to household instability may be a neural mechanism of risk for later depression and highlight the ways in which instability modulates neural development.

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Hardi, F. A., Goetschius, L. G., Tillem, S., McLoyd, V., Brooks-Gunn, J., Boone, M., … Monk, C. S. (2023). Early childhood household instability, adolescent structural neural network architecture, and young adulthood depression: A 21-year longitudinal study. Developmental Cognitive Neuroscience, 61. https://doi.org/10.1016/j.dcn.2023.101253

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