Abstract: Examining the Differing Effects of Economic Hardship and Poor Maternal Wellbeing on Cumulative Exposure to Adverse Childhood Experiences (Society for Social Work and Research 23rd Annual Conference - Ending Gender Based, Family and Community Violence)

355P Examining the Differing Effects of Economic Hardship and Poor Maternal Wellbeing on Cumulative Exposure to Adverse Childhood Experiences

Friday, January 18, 2019
Continental Parlors 1-3, Ballroom Level (Hilton San Francisco)
* noted as presenting author
Kiley Liming, M.J., Graduate Research Assistant, Graduate Teaching Assistant, University of Kansas, Lawrence, KS
Background/Purpose: Extensive research supports a strong and cumulative relationship between adverse childhood experiences (ACEs) and risky behaviors, mental health disorders, diseases, and health status across the lifespan. Additional factors, such as poor maternal wellbeing and economic hardship (EH), compound the detrimental health and wellbeing implications associated with exposure to multiple, often co-occurring ACEs. Despite the cumulative risk associated with these complexly interrelated adversities, limited research exists exploring the differentiating impact of EH and maternal wellbeing on a child’s risk of exposure to ACEs. This study sought to examine the separate effects of EH and poor maternal wellbeing on a child’s exposure to eight ACEs. This study hypothesized that maternal wellbeing has a mediating effect on the association between EH and the child’s cumulative ACE exposure.


Methods: A confirmatory factor analysis (CFA) was conducted using a random sub-sample (n=4,000) of the 2011 - 2012 National Survey of Children’s Health (NSCH), a nationally representative, cross-sectional study of children 0 and 17 years. Eleven variables and three latent factors were used to test a CFA measurement model. The variables of interest included the predictor variable, EH, and the mediating variable, maternal wellbeing (measured by self-reported mental and physical health status). The outcome latent variable was cumulative ACE exposure, consisting of eight ACE indicators, including exposure to: parental divorce/separation, death, incarceration, domestic violence (DV), mental illness, and substance abuse (SA); neighborhood violence; and discrimination. The mediation was tested using a bootstrapping approach of 10,000 bootstrap samples.


Results: Results revealed EH and poor maternal wellbeing had significant direct effects on a child’s increased ACE exposure (R=-.205, p=<.001; R=.332, p<.001, respectively). Frequent familial EH significantly predicted poor maternal wellbeing (R=-.198, p<.001). Increased EH had a significant indirect effect on cumulative ACE exposure via poor maternal mental health (R=-0.062 p<.001). Another key finding was that caregiver SA and DV were the two strongest predictors of increased childhood ACE exposure (respectively, λ=.637, λ=.602, p<.001).


Conclusions/Implications: These results reveal that children living in households with more economic instability are also more likely to have maternal caregivers with worse mental and physical health status and are significantly more likely to have higher ACE exposures. A key finding of this study was that poor maternal wellbeing had a stronger influence on ACE exposures than the direct effect of exposure to household EH. Providing evidence that a child’s caregiver has a greater influence on exposure to adversities than environmental conditions, such as EH, and that family intervention efforts should be targeted towards promoting caregiver-child attachment. These findings demonstrate that caregivers and children are reciprocally impacted by frequent EH. Additionally, poor maternal wellbeing mediated the relationship between EH and cumulative ACE exposure. The results emphasize that children who are exposed to multiple ACEs are often exposed to other, compounding adversities such as familial EH and poor maternal wellbeing. Adding to the field, the results support the complex transactional and potentiating relationships between an individual and their environments. Identification of protective and risk factors across domains will help researchers identify the most vulnerable populations.