ABSTRACT
Disadvantaged neighborhoods are important predictors of internalizing and externalizing behaviors
(INT/EXT) in children, including depression, anxiety, ADHD, and conduct problems. Critically,
however, neighborhoods are neither static nor unidimensional. Rather, they evolve and change over
time, and may do so differentially across built, social, and toxicant domains. What’s more, although
neighborhoods are virtually always considered as endogenous variables, they are themslves active
products of human investment and selection, among other forces. In an effort to address these
complexities, researchers argue for the importance of quantifying the neighborhood ‘exposome’
across multiple sources and types of data (e.g., sensors, geographic information systems, remotely
sensed imagery, and conventional surveys), and to do so taking into account the emergent qualities of
neighborhoods over time as well as their historical antecedents. With this call in mind, we hypothesize
that historical structural racism (i.e., redlining, higway construction, blockbusting) has had cascading
effects on the neighborhood exposome which, in turn, influences modern-day child INT/EXT. To date,
however, virtually no studies have examined the effects of historical structural racism on either the
neighborhood exposome or on child INT/EXT. The proposed R01 aims to fill crucial gaps in our
knowledge base, augmenting two well-characterized and independent datasets with state-of-the-
science geospatial data collections and analytic techniques to evaluate i) historical structural racism’s
legacy for neighborhood trajectories over time, ii) the role of historical structural racism in modern-day
child INT/EXT, with a focus on children of color, and iii) the linkages between historical structural
racism, the neighborhood exposome, and child INT/EXT. Our first sample consists of ~3800 children
identifying as Black or multiracial and residing in (sub)urban areas across Michigan, as well as
roughly 10,000 additional children residing in rural areas and/or identifying as White. Our second
sample consists of ~1,000 intensively assessed child families that were specifically oversampled to
reside in economically disadvantaged neighborhood contexts. As part of the proposed grant, we will
collect geospatial assessments of historical structural racism (1930-1980) and the neighborhood
exposome (2000-2020) in Michigan, and link these data to existing child INT/EXT data in our two
datasets. The core question we will answer is: What are the modern-day consequences of
historical structural racism for neighborhoods and their youngest residents?
