This proposal represents a vertical advancement in neighborhood effects research, producing for the first time, national neighborhood indicators of the built environment. Thus far, only local studies have been conducted due to the resource-intensive nature of site visits to conduct assessments of community features and also manual annotations of street images. With the recent advancement of computer vision and the emergence of massive sources of image data, we will leverage our team?s abilities to develop a data collection strategy utilizing geographic information systems to assemble a national collection of Google Street View images of all road intersections and street segments in the United States. We will utilize this data bank, and develop informatics algorithms to produce neighborhood summaries of built environment that have been theoretically and empirically identified to be important for health outcomes. After the creation of Neighborhood Looking Glass, we will conduct investigations into the impact of neighborhood environments on health utilizing medical records from hundreds of thousands of patients and accounting for predisposing characteristics in analyses. Our investigative team?comprised of experts in the field of epidemiology, computer vision, bioinformatics, and computer science?is uniquely suited to implement the study aims.
Our Specific Aims are: 1) Develop informatics techniques to produce neighborhood quality indicators; 2) Measure the accuracy of data algorithms and construct an interactive geoportal for neighborhood data visualization and data sharing, 3) Utilize Neighborhood Looking Glass and a large collection of medical records from Intermountain Healthcare to investigate neighborhood influences on the risk of obesity and substance abuse. The epidemic rise in chronic health conditions is recent and as such suggests its cause is social, cultural, and constructed rather than purely biological. Thus, we have the possibility of intervening on the environment to better support health. Recent studies suggest that the current cohort of young adults may face historically high cardiovascular disease risk and chronic disease burden. Our substantive investigation of the impact of neighborhood factors on chronic conditions will contribute further to the understanding of contextual influences on the health of this cohort at the forefront of a chronic disease epidemic. Moreover, the dramatic rise in overdoses, accidental poisonings, and mental health issues contributing to premature mortality warrants further investigation into risk-inducing environmental factors for substance abuse. Neighborhood Looking Glass will be a significant benefit to neighborhood effects researchers, harnessing the largely untapped potential of street image data to capture built environment characteristics. Results can be utilized to inform population-based strategies to reduce health disparities and improve health.

Public Health Relevance

/Relevance to Public Health The epidemic rise in obesity, related chronic diseases, and substance abuse in recent decades signal the importance of structural forces and social processes, but the dearth of data on contextual factors limits the investigation of multilevel effects on health. The development of the Neighborhood Looking Glass will be a significant benefit to neighborhood effects researchers, harnessing the largely untapped potential of street image data to capture built environment characteristics with potential impact on health. Results from our project can be utilized to inform system-wide and local strategies to improve community health.

National Institute of Health (NIH)
National Library of Medicine (NLM)
Research Project (R01)
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Biomedical Library and Informatics Review Committee (BLR)
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Vanbiervliet, Alan
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University of Maryland College Park
Biostatistics & Other Math Sci
Schools of Public Health
College Park
United States
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