Risk and Resilience in Early Childhood: Differential Impact of Social Determinants of Health By Latent Class Family Profiles

Background/Purpose: Previous studies estimate that socioeconomic and environmental conditions, or social determinants of health (SDOH), explain nearly half of health outcomes. Additionally, the role of social factors outweighs the influence of health behaviors and health care. Reducing and eliminating these health disparities requires addressing social and environmental inequities that have significant effects on health. Systematically screening for SDOH during well-child visits in early life is a promising strategy for universally addressing needs and connecting families to social services in a non-stigmatizing way. Screening for SDFOH engages caregiver voices in care plans, ensuring that unique needs are met and promoting positive health outcomes. This study systematically examines SDOH among families receiving pediatric care, and differential long-term child and family outcomes associated with risk and resilience profiles in infancy.

Methods: Data were collected via survey interviews with families of infants receiving pediatric care in three states (N = 653). Surveys included caregiver report of multiple dimensions of risk and resilience using validated measures. Constructs included: housing insecurity and quality, neighborhood danger and disorder, functional impact of toxic stress, household stressors, resilience, community connection, mastery, and mobilizing resources. We applied latent profile analysis (LPA) to examine classes based on family characteristics of risk and resilience and then applied multilevel modeling, with clinic as a second-level random effects parameter, to examine differential outcomes of health and well-being over time (12-15 months of child age), based on class membership assessed in infancy.

Results: Iterative assessment of the LPA resulted in a 4-class solution based on fit indices, the LMR likelihood ratio test, Entropy, parsimony, interpretability, and theoretical alignment. Classes included: (1) High Exposure to Household and Relational Risk, Moderate Strengths (19%); (2) Complex Risk Exposure, Lower Strengths (5%); (3) Low Exposure to Risk, Higher Strengths (63%); and (4) High Exposure to Neighborhood Risk, Higher Strengths (13%). Multilevel modeling, using class membership as a predictor of later child and family outcomes, and class 3 as a reference class, revealed that classes 1, 2, and 4 demonstrated significantly higher needs (e.g. TANF, SNAP, WIC, housing assistance, Medicaid) than class 3. Class 1 experienced significantly worse child health outcomes, including overall health, illness and injury, and social-emotional development. Class 4 also experienced worse outcomes related to child social-emotional development.

Conclusions/Implications: Pediatric screening in partnership with families uncovers distinct strengths and needs that can alter the trajectory of child and family outcomes across the lifespan. Early identification of these unique factors can be used to inform pediatric service delivery as well as pediatric referral to community services to support healthy child development and family resilience to adversity. However, this type of screening is often seen as outside the scope of pediatric care. To ensure services are appropriately aligned and caregivers are empowered to take up referred services, policy and administrative healthcare practices must provide resources and infrastructure to support practice integrating SDOH into current practice models to promote family-driven pediatric care that meets the unique needs of each family, maximizing positive child and family outcomes.