Built Environment and Health (BEH) Research Group is an interdisciplinary consortium of researchers who study how neighborhood environments influence health. BEH uses spatial data to examine the impact of the built environments, including urban design, retail environments, land use, public transit, and housing on many aspects of health, including physical activity, diet, obesity, pedestrian injuries, cardiovascular disease and cancer. The BEH Group was founded by Andrew Rundle and Kathryn Neckerman at Columbia University with funding from the Robert Wood Johnson Foundation Health and Society Scholars program. Our faculty team is now at Columbia University, Drexel University, University of Washington and American University, with research staff based at the Department of Epidemiology at the Mailman School of Public Health . The group includes faculty from the fields of public health, urban sociology, and social work. We have published more than 60 peer-reviewed papers. Our work has informed the New York City ‘Active Design Guidelines’, the Mayor’s Food Policy Task Force’s ‘Food Retail Expansion to Support Health’ (FRESH) initiative, and the International WELL Building Institute’s WELL Building and WELL Community Standards. We serve on NIH Scientific Review Panels, frequently speak at national and international conferences, and advise businesses, industry groups, and city, state and federal government agencies. We have developed and validated measures and methods for conducting neighborhood health research and are thought leaders in the area of preserving privacy and confidentiality when using location-based data.
The BEH Group uses geographic information systems (GIS), global positioning systems (GPS), remote sensing technology, large administrative data sets, business and economic data sets, health system data and population health data, an approach we refer to as Urban Health Informatics. Urban Health Informatics is the use of information technology to tap into, organize, cross-link and analyze the massive data effluent produced by urban centers to understand the health of residents. Until recently much of this data stream was either sequestered away and largely inaccessible or was ambient and difficult to tap into. Innovations in information technology, OPEN.GOV initiatives, the availability of online geographic information systems tools, the rise of social-media and the advent of crowd sourcing/Mechanical Turk applications have made these data available to researchers. The Urban Health Informatics approach combines aspects of data science such as machine learning with very large data sets, the use and development of information technology to replace or make traditional field research methods more logistically efficient, the re-purposing of routinely collected administrative data and the curating and linkage of data sets to create new information resources. One goal of this approach is to lower the cost, accelerate the pace, and standardize the methods of research, so that research studies can completed quickly and can be more easily be replicated.
Internationally, the rapid spread of cell and text based communications and of location aware mobile devices in the urban centers of low-to-middle income countries has allowed these cities to leap-frog several generations of telecommunication/data infrastructure and business models experienced in Western industrialized nations. Innovations in mobile technology and the development of mobile lifestyles in these new urban centers have created new models of social, economic and health care interaction. The opportunities for using Urban Health Informatics in these newly emerging global cities to study and intervene on population health are just beginning to be explored.
Over the past several years the we have developed research projects that utilize Urban Health Informatics approaches to studying built environments and population health, including projects to:
- study urban forestry and childhood asthma using LIDAR remote sensing data captured at a resolution of six inches for the entire city of New York,
- develop methods to use Google Street View to study neighborhood disorder and childhood obesity,
- utilize a decade of Department of Health and Mental Hygiene restaurant inspection data to study how neighborhood socioeconomic conditions and changes in City policy on reporting inspection results impact food safety,
- study obesity and physical fitness of ~680,000 public school children using Department of Education records from the NYC FITNESSGRAM program and City wide built environment data.
All of these projects involved the re-purposing and linking of multiple data sets licensed from governmental agencies, commercial sources and health studies. This work has shown the enormous potential for the use of Urban Health Informatics as a tool to study population health.
Contact: Andrew Rundle at email@example.com