Adverse Childhood Experiences (ACEs), including child abuse, have been linked with poor health outcomes in adulthood. The mechanisms that explain these relations are less understood. This study assesses whether associations of ACEs and health risks are mediated by adult socioeconomic conditions, and whether these pathways are different for maltreatment than for other types of adversities. Using the Behavioral Risk Factor Surveillance System 2012 survey (N=29,229), we employ structural equation modeling to (1) estimate associations of the number and type of ACEs with five health risks – depression, obesity, tobacco use, binge drinking, and self-reported sub-optimal health; and (2) assess whether adult socioeconomic conditions— marriage, divorce and separation, educational attainment, income and insurance status—mediate those associations. Findings suggest both direct and indirect associations between ACEs and health risks. At high numbers of ACEs, 15–20% of the association between number of ACEs and adult health risks was attributable to socioeconomic conditions. Associations of three ACEs (exposure to domestic violence, parental divorce, and residing with a person who was incarcerated) with health risks were nearly entirely explained by socioeconomic conditions in adulthood. However, child physical, emotional and sexual abuse were significantly associated with several adult health risks, beyond the effects of other adversities, and socioeconomic conditions explained only a small portion of these associations. These findings suggest that the pathways to poor adult health differ by types of ACEs, and that childhood abuse is more likely than other adversities to have a direct impact.
This study estimates the associations of income with both (self-reported) child protective services (CPS) involvement and parenting behaviors that proxy for child abuse and neglect risk among unmarried families. Our primary strategy follows the instrumental variables (IV) approach employed by Dahl and Lochner (2012), which leverages variation between states and over time in the generosity of the total state and federal Earned Income Tax Credit for which a family is eligible to identify exogenous variation in family income. As a robustness check, we also estimate standard OLS regressions (linear probability models), reduced form OLS regressions, and OLS regressions with the inclusion of a control function (each with and without family-specific fixed effects). Our micro-level data are drawn from the Fragile Families and Child Wellbeing Study, a longitudinal birth-cohort of relatively disadvantaged urban children who have been followed from birth to age nine. Results suggest that an exogenous increase in income is associated with reductions in behaviorally-approximated child neglect and CPS involvement, particularly among low-income single-mother families.
Associations between experiencing child maltreatment and adverse developmental outcomes are widely studied, yet conclusions regarding the extent to which effects are bidirectional, and whether they are likely causal, remain elusive. This study uses the Fragile Families and Child Well-Being study, a birth cohort of 4,898 children followed from birth through age 9. Hierarchical linear modeling and structural equation modeling are employed to estimate associations of maltreatment with cognitive and social-emotional well-being. Results suggest that effects of early childhood maltreatment emerge immediately, though developmental outcomes are also affected by newly occurring maltreatment over time. Additionally, findings indicate that children's early developmental scores predict their subsequent probability of experiencing maltreatment, though to a lesser extent than early maltreatment predicts subsequent developmental outcomes.
The current study investigates the role of race and county characteristics in substantiation and outof-home placement decisions in the United States. Using multi-level models, we analyzed data from counties in the United States available through the National Child Abuse and Neglect Data Systems and Adoption and Foster Care Analysis and Reporting System to investigate the interactions between children's race and the context in which they live. Our sample consisted exclusively of children whose cases had been investigated, therefore we were able to focus on the role played by race and county-characteristics in substantiation and out-of-home placement decisions made by CPS, net of the heightened risk factors (or potential biases) that lead to disparate rates of reporting. Adjusting for state and county of investigation, Black, American Indian/Alaskan Native, and multi-racial children were more likely than White (non-Hispanic) children to be substantiated or placed out of home, while Asian children were less likely to be substantiated or placed out of home. Notably, differences across groups are far smaller in magnitude when demographic and geographic differences are taken into account. Higher countylevel poverty, percentages of Black residents, and juvenile arrest rates were associated with lower odds of substantiation and out-of-home placement among investigated children, whereas an elevated percentage of single-headed households was associated with higher odds of both outcomes. We also found that living in a rural county was associated with greater odds of substantiation, but lower odds of out-of-home placement. Important differences by race were found for these associations.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.