Urban Form Laboratory, Department of Urban Design and Planning, University of Washington, Seattle, WA, USA
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Emerging Technologies for Assessing Physical Activity Behaviors in Space and Time
- Published on January 28, 2014
Abstract: Precise measurement of physical activity is important for health research, providing a better understanding of activity location, type, duration, and intensity. This article describes a novel suite of tools to measure and analyze physical activity behaviors in spatial epidemiology research. We use individual-level, high-resolution, objective data collected in a space-time framework to investigate built and social environment influences on activity. First, we collect data with accelerometers, global positioning system units, and smartphone-based digital travel and photo diaries to overcome many limitations inherent in self-reported data. Behaviors are measured continuously over the full spectrum of environmental exposures in daily life, instead of focusing exclusively on the home neighborhood. Second, data streams are integrated using common timestamps into a single data structure, the “LifeLog.” A graphic interface tool, “LifeLog View,” enables simultaneous visualization of all LifeLog data streams. Finally, we use geographic information system SmartMap rasters to measure spatially continuous environmental variables to capture exposures at the same spatial and temporal scale as in the LifeLog. These technologies enable precise measurement of behaviors in their spatial and temporal settings but also generate very large datasets; we discuss current limitations and promising methods for processing and analyzing such large datasets. Finally, we provide applications of these methods in spatially oriented research, including a natural experiment to evaluate the effects of new transportation infrastructure on activity levels, and a study of neighborhood environmental effects on activity using twins as quasi-causal controls to overcome self-selection and reverse causation problems. In summary, the integrative characteristics of large datasets contained in LifeLogs and SmartMaps hold great promise for advancing spatial epidemiologic research to promote healthy behaviors.
- Philip M. Hurvitz 1
- Anne Vernez Moudon 1
- Bumjoon Kang 2
- Brian E. Saelens 3,4
- Glen E. Duncan 5
Department of Urban and Regional Planning, State University of New York, Buffalo, NY, USA
Seattle Children’s Research Institute, Seattle, WA, USA
Department of Pediatrics, University of Washington, Seattle, WA, USA
Nutritional Sciences Program, Department of Epidemiology, University of Washington, Seattle, WA, USA
Frontiers in Public Health