Pathways Linking Community-Level Social Determinants of Health to Infant Biological Markers and Early Childhood Psychopathology: A Structural Equation Modeling Approach

Abstract

We aimed to examine associations between multiple community-level social determinants of health and two biological markers: frontal alpha asymmetry (FAA) and telomere length (TL) in early childhood. We also probed pathways from community-level social determinants to biological markers and subsequent psychopathology symptoms. Using a longitudinal design, 211 families were followed during the first 2 years of life. Social determinants were assessed using US Census data, FAA using resting-state electroencephalogram, TL from infant saliva samples, and child psychopathology symptoms using the ITSEA. Statistical analyses included bivariate correlations (unadjusted and with false discovery rate adjustment for multiple comparisons) and SEM. For FAA, higher rates of uninsurance (healthcare) were associated with greater right lateralization at 2 months (r = −0.233, p = 0.028), and higher rates of food insecurity were also associated with greater right lateralization at 9 months (r = −0.250, p = 0.036); however, these associations were not significant after adjustment for multiple comparisons. In our SEM model, we found that both social determinants had paths to FAA (i.e., healthcare uninsurance rates to FAA at 2 months; food insecurity rates to FAA at 9 months), which had paths to child psychopathology symptoms at 2 years. Two community-level social determinants (greater poverty levels/lower home ownership rates) were significantly associated with shorter TL at 9 months (r = −0.395, p = 0.007; r = 0.293, p = 0.048), although only community poverty levels remained significant after adjustment for multiple comparisons. In the SEM model, community poverty levels had paths through TL at 9 months to child psychopathology symptoms at 2 years; home ownership rates only covaried with poverty levels. Distinct social determinant domains may influence markers of biological stress at specific time points. These findings underscore the importance of structural-level policies and early interventions addressing multiple aspects of the environment.