Adapting to climate change requires countermeasures that can protect public mental health and community well-
being. Cities and states increasingly incorporate population health promotion into urban planning decisions, yet
the impacts of such decision decisions on mental health outcomes remain largely unstudied. With respect to
climate change cities have significant capacity to help offset the adverse effects of increasing temperatures and
enhance community resilience, through altering the design of natural and built environments. However, such
decisions require empiric evidence on the health effects of both increasing temperature and offsetting designs
to increase shade, particularly given the racial and socioeconomic inequalities in shade access. On a given day,
significant spatial variation in temperature can occur within a city or urban region, mostly driven by local
differences in shade. Temperature and shade exposure have been linked to psychopathology for centuries, with
ample biological plausibility, but few modern studies have provided comprehensive data. We propose to utilize
a cohort study of 3,396 high school students, with substantial diversity in race, income, and neighborhood,
recruited in 9th grade in 2013 in Los Angeles County, and followed up eight times with <1% attrition at each wave,
to innovatively study how intra-city differences in temperature, access to shade, and green space influence the
incidence of internalizing and externalizing symptoms and transdiagnostic psychopathological traits. We will link
geocoded residential, commuter, and school location information to remotely sensed data and local land use to
create high-resolution estimates of neighborhood surface temperatures, tree canopy cover, other built
environment sources of shade, and green space of each of the cohort participants. We will also measure
neighborhood-level factors known or hypothesized to influence psychopathology risk, including air quality,
neighborhood economic conditions, and crime. State-of-the-science confounder control strategies using multi-
dimensional g-formula mediated moderation models will generate robust associations. Through these
assessments we will construct neighborhood typologies of health risk that include social, environmental, and
physical factors. We will: 1) intensively characterize the home and school neighborhoods of >3,000 longitudinally
followed adolescents and identify transdiagnostic psychopathological symptoms and trajectories; 2) determine
the impact of neighborhood surface temperature, shaded areas, and greenspace on internalizing and
externalizing dimensions, transdiagnostic traits; and 3) construct and compare neighborhood typologies of
psychopathological risk incorporating physical and social environmental data and novel latent variable
techniques. Our research team has extensive expertise in spatial and psychiatric epidemiology and experience
in translating science to policy. This work will provide critical missing data on the effects of green infrastructure
on psychopathology among adolescents. Such data are needed to support decision-making around urban
planning, investment, and climate change mitigation to improve population health for local communities.