Great Problems, Great Minds Seminar Series: Using Google Street View to Examine Associations between Built Environment Characteristics and U.S. Health Outcomes—Census Tract, County, and Individual Levels

Join the Department of Social Sciences for this Great Problems, Great Minds seminar series event featuring guest speaker Quynh Nguyen, associate professor of epidemiology and biostatistics in the School of Public Health at the University of Maryland. She holds a Ph.D. and M.S.P.H. in epidemiology from the University of North Carolina at Chapel Hill, and a bachelor's degree in human biology from Stanford University. She is a social epidemiologist focusing on contextual and economic factors as they relate to health. She has extensive experience using numerous national and international population-based health surveys to examine social and economic predictors of health and to quantify national and international patterns in health disparities. Her current research program focuses on creating and validating neighborhood indicators constructed from nontraditional big data sources such as social media data and Google Street View images. Her research has been funded by the National Library of Medicine and National Institutes of Health. She was the principal investigator of a K01 career development grant through the Big Data to Knowledge Initiative and an R01 grant from the National Library of Medicine to pursue this research program. Nguyen is also currently the principal investigator of another data-science driven R01 grant from the National Institute on Minority Health and Health Disparities to construct an artificial intelligence-powered chatbot to deliver health information to racial/ethnic minority mothers.

The virtual event will take place on March 2 beginning at 12:40 p.m.

Advances in neighborhood research have been constrained by the lack of neighborhood data for many geographical areas. This research utilizes millions of Google Street View images across the United States and leverages convolutional neural networks to automatically label each image. The research implements regression models to estimate associations between built environments and health outcomes at various levels including county, census tract, and individual levels. At these various levels, built environments including walkability, physical disorder, and urban development have significant impacts on health behaviors and health outcomes. Google Street View images represent an underutilized resource for building national data on neighborhoods and in examining the influence of built environments on community health outcomes across the United States

The Using Google Street View to Examine Associations between Built Environment Characteristics and U.S. Health Outcomes: Census Tract, County, and Individual Levels event will take place on Zoom.

The event is part of the Great Problems, Great Minds seminar series that explores the major problems facing humanity as we move into the heart of the twenty-first century.

To see the full schedule and videos from previous events, visit the seminar series page.

For more information, contact Assistant Professor of Social Sciences Hao Huang at hhuang48@iit.edu.

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