Abstract: Childhood Maltreatment, Inflammation, and Depression: Leveraging Structural Equation Modeling to Test the Social Signal Transduction Theory (Society for Social Work and Research 26th Annual Conference - Social Work Science for Racial, Social, and Political Justice)

612P Childhood Maltreatment, Inflammation, and Depression: Leveraging Structural Equation Modeling to Test the Social Signal Transduction Theory

Schedule:
Sunday, January 16, 2022
Marquis BR Salon 6, ML 2 (Marriott Marquis Washington, DC)
* noted as presenting author
Jay D. O'Shields, MSW, Doctoral Student, University of Georgia, Athens, GA
Orion Mowbray, PhD, Associate Professor, University of Georgia, Athens, GA
Background and Purpose: Depression represents a serious challenge for healthcare professionals, with a high annual incidence rate, increased risk for early death, and high frequency of medical comorbidity. A leading theory on the emergence, persistence, and recurrence of depression is Social Signal Transduction Theory, which suggests early social threats can produce immune system inflammation that is associated with increased symptoms of depression. Despite the promise this biological theory of depression has, it has yet to be tested adequately. Thus, the present study utilized a structural equation model approach to establish path-based relationships among early childhood experiences, immune system inflammation, and depression.

Methods: Participants included 1,700 individuals from the Midlife Development in the United States data set. The Center for Epidemiologic Studies Depression Inventory (CES-D) served as the dependent variable. Childhood maltreatment was measured though the childhood trauma questionnaire (CTQ), and inflammation was measured through six biomarkers of inflammation which are supported by theory and current empirical studies, including C-reactive protein, fibrinogen, interlukin-6, tumor necrosis factor alpha, sE-Selectin, and s-ICAM-1. A measurement model examined the factor structure of childhood maltreatment, inflammation, and depression. A latent variable structural model examined the relationship from childhood maltreatment to inflammation, and depression, including the control variables perceived stress, body mass index, age, race/ethnicity, and gender.

Results: The measurement model showed two of the latent variables (childhood maltreatment and depression) were each characterized by a singular factor and factor loading scores among the observed variables were all over 0.40. Inflammation as a latent variable demonstrated inconsistent factor loadings with some loadings below 0.40; however, given their relevance to theory, all biomarkers were retained. The latent variable structural model showed adequate fit (chi-square/df=8.006, RMSEA=0.064, SRMR=0.078). This model showed a significant relationship between childhood maltreatment and inflammation (b = 0.60, p < 0.01), and a significant relationship between inflammation and depression (b = 0.20, p < 0.01). Among the control variables, recent stress (b = 0.60, p < 0.01), body mass index (b = 0.03, p<0.05), and gender (b(female) = -0.06, p<0.05) also showed a significant relationship with depression.

Conclusion and Implications: These results provide provisional support for the Social Signal Transduction Theory of depression. While these results are drawn from a cross-sectional study, future research may improve our understanding of how early childhood experiences influence adult mental health, including depression, through longitudinal research. Furthermore, given the association between inflammation and depression, social work practitioners may benefit from the practical knowledge generated from this research which suggests that individuals with histories of childhood maltreatment may also have an increased risk for multiple health problems, as inflammation is commonly associated with both hypertension and heart disease. Additionally, social work practitioners who provide care for persons with health problems associated with inflammation may also consider adopting assessment tools for depression into their practice to expedite treatment options, which may reduce many of the challenges healthcare professional experience associated with depression.