Abstract
The built environment affects mental health outcomes, but this relationship is less studied and understood. This article proposes a novel multi-level scenario-based predictive analytics framework (MSPAF) to explore the complex relationships between community mental health outcomes and the built environment conditions. The MSPAF combines rigorously validated interpretable machine learning algorithms and scenario-based sensitivity analysis to test various hypotheses on how the built environment impacts community mental health outcomes across the largest metropolitan areas in the US. Among other findings, our results suggest that declining socio-economic conditions of the built environment (e.g., poverty, low income, unemployment, decreased access to public health insurance) are significantly associated with increased reported mental health disorders. Similarly, physical conditions of the built environment (e.g., increased housing vacancies and increased travel costs) are significantly associated with increased reported mental health disorders. However, this positive relationship between the physical conditions of the built environment and mental health outcomes does not hold across all the metropolitan areas, suggesting a mixed effect of the built environment’s physical conditions on community mental health. We conclude by highlighting future opportunities of incorporating other variables and datasets into the MSPAF framework to test additional hypotheses on how the built environment impacts community mental health.
Highlights
The built environment affects mental health outcomes, but this relationship is less studied and understood
This study leveraged a library of supervised interpretable machine learning models to assess the associations between community mental health outcomes and, the built environment’s physical and socio-economic aspects
This study employs a library of supervised interpretable machine learning models and scenario-based sensitivity analyses to explore the relationship between adults’ mental health, and the socio-economic and physical aspects of the built environment in the US largest metropolitan areas
Summary
The built environment affects mental health outcomes, but this relationship is less studied and understood. Our results suggest that declining socio-economic conditions of the built environment (e.g., poverty, low income, unemployment, decreased access to public health insurance) are significantly associated with increased reported mental health disorders. Physical conditions of the built environment (e.g., increased housing vacancies and increased travel costs) are significantly associated with increased reported mental health disorders This positive relationship between the physical conditions of the built environment and mental health outcomes does not hold across all the metropolitan areas, suggesting a mixed effect of the built environment’s physical conditions on community mental health. The physical and socio-economic aspects of the built environment impact population mental health outcomes of a community. In what they delineate as the “neighborhood domain”, the commissioning report on the SDGs and mental health indicates that poorly planned or deteriorating neighborhoods (e.g., housing vacancy and declining quality of housing and community infrastructure) pose mental health challenges on individual-level biological markers[16]
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