Dr Quynh Nguyen
August 6, 2018

Dr. Quynh C. Nguyen, assistant professor of Epidemiology and Biostatistics, has been awarded an R01 grant from the National Institutes of Health (NIH)/National Library of Medicine for her project titled, “Neighborhood Looking Glass: 360 Degree Automated Characterization of the Built Environment for Neighborhood Effects Research.”

The $1.54 million grant will enable Dr. Nguyen to use Google Street View images and computer vision algorithms to assess the relationship between neighborhood features and health outcomes. The grant enables the construction of a national data repository of built environment features that the team will make publicly available.

“This award allows me to continue to do what I love — try to find new ways to characterize neighborhoods and investigate links between place and health,” Dr. Nguyen said. “In addition, funding allows me to continue to work with great students and provide them with stable employment on this project.”

One of the goals of the grant is to devise new ways to characterize neighborhood environments. Researchers have traditionally depended on neighborhood surveys and on-site visits to assess neighborhood environments, but those methods are costly and time-consuming and limit the number of areas that can be examined. Big data presents new opportunities for costs savings, efficiencies and allows for investigations of national patterns.

A team led by Dr. Nguyen will work to develop informatics techniques to produce neighborhood quality indicators. It will measure the accuracy of data algorithms and construct an interactive geoportal for neighborhood data visualization and sharing.

“The award provides the opportunity to work in a trans-disciplinary team with top-notch researchers in the field of computer vision (Tolga Tasdizen), data management (Feifei Li), and clinical outcomes research (Kim Brunisholz),” she said. “We learn from each other and together, we can make advances that would not be possible in our silos.”

The team will utilize Dr. Nguyen’s previous research and a large collection of medical records from Intermountain Healthcare to investigate neighborhood influences on the risk of obesity and substance abuse. The research could allow health providers and advocates predict individuals’ health outcomes from their neighborhood characteristics and give them better information on how to improve these outcomes.

The new study will build on a previous study where Dr. Nguyen and her team examined images from large geographic areas, including Salt Lake City, Utah; Charleston, West Virginia; and Chicago, Illinois.

That study, published in the Journal of Epidemiology and Community Health, found people living in zip codes with the highest proportion of green streets, crosswalks and commercial buildings/apartments were 25-28% less likely to be obese and 12-18% less likely to suffer from diabetes than those in neighborhoods with the least abundance of these features.


Related Links

Using "big data" to understand neighborhood impact on health

HashtagHealth: A Social Media Big Data Resource for Neighborhood Effects Funded by NIH’s Big Data to Knowledge (BD2K) Initiative

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Quynh Nguyen