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Am J Prev Med. 2016 Nov;51(5):792-800. doi: 10.1016/j.amepre.2016.06.006. Epub 2016 Aug 12.

"Spatial Energetics": Integrating Data From GPS, Accelerometry, and GIS to Address Obesity and Inactivity.

Author information

1
Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts. Electronic address: pjames@hsph.harvard.edu.
2
Calit2, La Jolla, California.
3
Division of Public Health Sciences, Washington University School of Medicine, St. Louis, Missouri.
4
Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts; Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, Massachusetts.
5
Health Behaviors Research Branch, Behavioral Research Program, National Cancer Institute, Bethesda, Maryland.
6
Department of Family Medicine and Public Health, University of California, San Diego, San Diego, California; Psychology Department, Graduate School of Public Health, San Diego State University, San Diego, California.
7
Urban Form Lab, University of Washington, Seattle, Washington.
8
Department of Parks, Recreation, and Tourism Management, North Carolina State University, Raleigh, North Carolina.
9
Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts; Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts; Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, Massachusetts.

Abstract

To address the current obesity and inactivity epidemics, public health researchers have attempted to identify spatial factors that influence physical inactivity and obesity. Technologic and methodologic developments have led to a revolutionary ability to examine dynamic, high-resolution measures of temporally matched location and behavior data through GPS, accelerometry, and GIS. These advances allow the investigation of spatial energetics, high-spatiotemporal resolution data on location and time-matched energetics, to examine how environmental characteristics, space, and time are linked to activity-related health behaviors with far more robust and detailed data than in previous work. Although the transdisciplinary field of spatial energetics demonstrates promise to provide novel insights on how individuals and populations interact with their environment, there remain significant conceptual, technical, analytical, and ethical challenges stemming from the complex data streams that spatial energetics research generates. First, it is essential to better understand what spatial energetics data represent, the relevant spatial context of analysis for these data, and if spatial energetics can establish causality for development of spatially relevant interventions. Second, there are significant technical problems for analysis of voluminous and complex data that may require development of spatially aware scalable computational infrastructures. Third, the field must come to agreement on appropriate statistical methodologies to account for multiple observations per person. Finally, these challenges must be considered within the context of maintaining participant privacy and security. This article describes gaps in current practice and understanding and suggests solutions to move this promising area of research forward.

PMID:
27528538
PMCID:
PMC5067207
DOI:
10.1016/j.amepre.2016.06.006
[Indexed for MEDLINE]
Free PMC Article

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