Emerging technologies for assessing physical activity behaviors in space and time
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 i...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2014-01-01
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| Series: | Frontiers in Public Health |
| Subjects: | |
| Online Access: | http://journal.frontiersin.org/Journal/10.3389/fpubh.2014.00002/full |
| _version_ | 1818484497474125824 |
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| author | Philip M Hurvitz Anne Vernez Moudon Bumjoon eKang Brian E Saelens Glen E Duncan |
| author_facet | Philip M Hurvitz Anne Vernez Moudon Bumjoon eKang Brian E Saelens Glen E Duncan |
| author_sort | Philip M Hurvitz |
| collection | DOAJ |
| description | 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. Next, 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. |
| first_indexed | 2024-12-10T15:56:21Z |
| format | Article |
| id | doaj.art-700d1a4c00e74a6eb6b10086d52d6562 |
| institution | Directory Open Access Journal |
| issn | 2296-2565 |
| language | English |
| last_indexed | 2024-12-10T15:56:21Z |
| publishDate | 2014-01-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Public Health |
| spelling | doaj.art-700d1a4c00e74a6eb6b10086d52d65622022-12-22T01:42:38ZengFrontiers Media S.A.Frontiers in Public Health2296-25652014-01-01210.3389/fpubh.2014.0000275633Emerging technologies for assessing physical activity behaviors in space and timePhilip M Hurvitz0Anne Vernez Moudon1Bumjoon eKang2Brian E Saelens3Glen E Duncan4University of WashingtonUniversity of WashingtonState University of New York at BuffaloSeattle Childrens HospitalUniversity of WashingtonPrecise 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. Next, 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.http://journal.frontiersin.org/Journal/10.3389/fpubh.2014.00002/fullBehaviorphysical activityenvironmentGISGPSaccelerometry |
| spellingShingle | Philip M Hurvitz Anne Vernez Moudon Bumjoon eKang Brian E Saelens Glen E Duncan Emerging technologies for assessing physical activity behaviors in space and time Frontiers in Public Health Behavior physical activity environment GIS GPS accelerometry |
| title | Emerging technologies for assessing physical activity behaviors in space and time |
| title_full | Emerging technologies for assessing physical activity behaviors in space and time |
| title_fullStr | Emerging technologies for assessing physical activity behaviors in space and time |
| title_full_unstemmed | Emerging technologies for assessing physical activity behaviors in space and time |
| title_short | Emerging technologies for assessing physical activity behaviors in space and time |
| title_sort | emerging technologies for assessing physical activity behaviors in space and time |
| topic | Behavior physical activity environment GIS GPS accelerometry |
| url | http://journal.frontiersin.org/Journal/10.3389/fpubh.2014.00002/full |
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