A Beautiful Day in the Neighborhood: The Longitudinal Effects of Early Environments on Child Health and Behavior.

About This Grant

ABSTRACT: Neighborhood residence profoundly patterns child behavior and health across the life course. Children residing in disadvantaged neighborhoods face disproportionate risks of internalizing and externalizing behavioral problems, which can have lasting implications for their overall health and future opportunities. However, prior research on neighborhoods and child outcomes has often relied on cross-sectional designs that fail to capture the temporal influences of neighborhood change and the mechanisms through which these changes effect children. There is thus an urgent need for causal research to identify how and when neighborhood contexts impact child development. This project aims to meet this need by employing advanced multilevel and marginal structural modeling techniques to explore the causal impacts of neighborhood dynamics on child health and behavior, leveraging rich data from the Future of Families and Child Wellbeing Study (FFCWS). Aim 1 will investigate the intricate mechanisms through which neighborhood socioeconomic and social conditions affect child health outcomes, examining whether improvements in these areas are associated with meaningful reductions in behavioral symptoms. Fixed effects models with robust control for time-varying confounders will be used to provide causal estimates of the within-person effects of neighborhood change, and a causal mediation analysis will be conducted within the fixed effects framework to test whether changes in neighborhood social environments partially explain the benefits of improving neighborhood socioeconomic conditions. Through these robust methodologic approaches, this aim seeks to provide a nuanced understanding of how neighborhoods shape development. Aim 2 will then characterize the cumulative and developmental period-specific impacts of neighborhood collective efficacy on child internalizing and externalizing behaviors using marginal structural modeling techniques to address time-varying confounding. The analysis will provide insights into when neighborhood environments are most salient for children’s behavior development. This research, alongside the proposed training plan, will provide Logan Beyer with invaluable expertise in life course epidemiology, the application of causal inference methods to the study of neighborhoods, and the social determinants of child health. These skills will be instrumental in advancing a career dedicated to promoting health for all children. Logan has assembled an exceptional team of sponsors and collaborators to support her in this work. This team will ensure she has access to the resources and opportunities required to achieve her goals of (1) developing expertise in neighborhood effects and child health; (2) expanding proficiency in multilevel and causal modeling; and (3) cultivating research communication strategies for diverse audiences. The implications of this research also extend beyond academic knowledge; causal evidence in this field will inform the design of effective policies and programs to improve health outcomes for children.