Health and Well-Being of Children in Kinship Care: Patterns and Mechanisms

Caregiving setting plays a critical role in shaping children’s health and development. Due to their distinct family dynamics, children in kinship care (i.e. those living with people other than parents) require special scholarly attention. While some studies have evaluated health outcomes for children in kinship care, the varied circumstances of these arrangements call for more research on the heterogeneity in kinship care settings. Also, it is unclear through which mechanisms nonparental caregiving settings may affect children’s health and well-being.

With data from the National Survey of Children’s Health (2011-2012) and the 2013 National Survey of Children in Nonparental Care, this study will start with a categorization of kinship care based on the level of child welfare system involvement: (1) public kinship care, where child welfare agencies hold legal custody and place children with relatives; (2) voluntary kinship care, where children are placed with relatives by child welfare agencies but legal custody remains with the parent or caregiver and (3) private kinship care, where relatives care for children without child welfare involvement. Then, I will compare the health outcomes of children in each type of kinship care to their counterparts in parent-led families. The outcomes to be assessed include physical, developmental, and emotional conditions, as well as healthcare access. Considering that the probability of being in each type of caregiving setting differs considerably across children, I will use the Generalized Propensity Score method to adjust for potential selection bias. Finally, to identify factors that may explain the health effects of kinship care settings, I will test the mediating effects of two important mechanisms: caregiving behaviors (e.g., emotional support) and caregiving resources (e.g., family resilience, received help coordinating care, etc.). For the categorical health outcomes, I will use a recently developed mediation analysis method that addresses re-scaling issues in non-linear models.