Illuminating associations between parent's adverse childhood experiences, children's obesity, and neighborhood environment - SUMMARY
Adverse childhood experiences (ACEs) can increase the risk for obesity both during childhood and later in
adulthood. Emerging evidence suggests a parent's history of ACEs can increase their child's obesity risk,
regardless of whether the child experiences their own ACEs. The association between a parent's ACEs and
their child's obesity is believed to be moderated by via enduring stress-related effects of ACEs on parent's
biology and behavior and family functioning. Research on ACEs-obesity associations rarely focuses on
neighborhood environment, yet neighborhood characteristics are relevant to both ACEs and obesity risk.
Neighborhood characteristics such as greenspace and food access can impact engagement in obesity related
behaviors. Neighborhood factors such as neighborhood poverty and crime can be a source of adversity. Our
previous research documented that adults with a history of ACEs live in less health-promoting neighborhoods
with more obesogenic qualities (e.g., worse supermarket access, less greenspace). However neighborhood's
impact on associations between a parent's ACEs and their child's obesity has not been widely investigated.
Illuminating the role of neighborhood requires advanced spatial analytic methods, because neighborhoods
are complex environments comprised of numerous synergistic characteristics that co-occur within a broader
context of racial and economic segregation. To begin to illuminate neighborhood influences on ACEs-obesity
associations, we validated spatial analytic methods for creating a Neighborhood ACEs Index (NAI). A NAI is
a weighted composite that answers the question “what is the neighborhood environment of individuals who
have experienced ACEs?” It serves as a single-item individual-level proxy for collective neighborhood
environment associated with ACEs. Individuals who live in neighborhoods that have more characteristics
associated with ACEs have a higher NAI score. Using geocoding and spatial methods, a NAI connects
individual-level ACEs data with rich spatial data that includes numerous neighborhood characteristics such as
crime, poverty, and healthcare access. A NAI can be used as an independent variable in analyses to examine
how neighborhood characteristics associated with ACEs influence the relationship of ACEs and obesity. In
addition, a NAI identifies population-specific neighborhood-level targets for interventions and polices.
Neighborhoods whose residents have the highest NAI score can be prioritized for trauma-informed obesity
reduction efforts. Building upon our prior work, this study will create a NAI based upon parent ACEs and
test how that NAI influences associations between a parent's history of ACEs and their child's obesity.
We will harness robust existing data from the H2O study (N=1320) that captured parent ACEs and child
obesity, rich spatial data that captured neighborhood environment, and robust spatial methods. Collectively,
this study is a foundational step towards our long-term goal: informing development of place-based
interventions and policies to reduce obesity for millions of Americans affected by ACEs.
