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Front Public Health. 2014 Mar 11;2:19. doi: 10.3389/fpubh.2014.00019. eCollection 2014.

Using MapMyFitness to Place Physical Activity into Neighborhood Context.

Author information

1
Department of Epidemiology, Center for Social Epidemiology and Population Health, University of Michigan School of Public Health , Ann Arbor, MI , USA.
2
Department of Epidemiology, Harvard School of Public Health , Boston, MA , USA ; Department of Environmental Health, Harvard School of Public Health , Boston, MA , USA.
3
MapMyFitness, Inc. , Austin, TX , USA.
4
Department of Electrical Engineering, Stanford University , Stanford, CA , USA.
5
Department of Epidemiology, University of North Carolina Gillings School of Global Public Health , Chapel Hill, NC , USA.
6
Department of Epidemiology, Harvard School of Public Health , Boston, MA , USA ; Department of Environmental Health, Harvard School of Public Health , Boston, MA , USA ; Department of Medicine, Channing Division of Network Medicine, Brigham and Women's Hospital, Harvard Medical School , Boston, MA , USA.

Abstract

It is difficult to obtain detailed information on the context of physical activity at large geographic scales, such as the entire United States, as well as over long periods of time, such as over years. MapMyFitness is a suite of interactive tools for individuals to track their workouts online or using global positioning system in their phones or other wireless trackers. This method article discusses the use of physical activity data tracked using MapMyFitness to examine patterns over space and time. An overview of MapMyFitness, including data tracked, user information, and geographic scope, is explored. We illustrate the utility of MapMyFitness data using tracked physical activity by users in Winston-Salem, NC, USA between 2006 and 2013. Types of physical activities tracked are described, as well as the percent of activities occurring in parks. Strengths of MapMyFitness data include objective data collection, low participant burden, extensive geographic scale, and longitudinal series. Limitations include generalizability, behavioral change as the result of technology use, and potential ethical considerations. MapMyFitness is a powerful tool to investigate patterns of physical activity across large geographic and temporal scales.

KEYWORDS:

GPS; MapMyFitness; MapMyRun; big data; parks; physical activity; quantified self; recreation

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