Objectives This study seeks to further the work exploring adverse childhood experiences (ACEs) by proposing a novel approach to understanding the impact of ACEs through applying advanced analytical methods to examine whether combinations of ACEs differentially impact child health outcomes. Methods Using National Survey of Children's Health data, we use latent class analysis to estimate associations between classes of ACEs and child health outcomes. Results Class membership predicts child poor health, with differences found for specific ACE combinations. A subgroup of children exposed to poverty and parental mental illness are at higher risk for special healthcare needs than all other groups, including children exposed to 3 or more ACEs. Conclusions Different combinations of ACEs carry different risk for child health. Interventions tailored to specific ACEs and ACE combinations are likely to have a greater effect on improving child health. Our findings suggest children who experience specific ACE combinations (e.g., poverty and parental mental illness) are at particularly high risk for poor health outcomes. Therefore, clinicians should routinely assess for ACEs to identify children exposed to the most problematic ACE combinations; once identified, these children should be given priority for supportive interventions tailored to their specific ACE exposure and needs.
Keywords: Adverse childhood experiences; Child health; Latent class analysis; National Survey of Child Health.