Peter James1, Jennifer Weissman2, Jean Wolf3, Karen Mumford4, Cheryl K Contant5, Wei-Ting Hwang6, Lynne Taylor6, Karen Glanz7. 1. Harvard TH Chan School of Public Health, Department of Epidemiology, Boston, MA, USA. pjames@hsph.harvard.edu. 2. Emory University, Rollins School of Public Health, Atlanta, GA, USA. 3. Westat Geostats Services, Atlanta, GA, USA. 4. Watershed Institute for Collaborative Environmental Studies, University of Wisconsin-Eau Claire, Eau Claire, WI, USA. 5. Advancing Your Strengths Consulting, Eau Claire, WI, USA. 6. University of Pennsylvania Perelman School of Medicine, Department of Biostatistics, Philadelphia, PA, USA. 7. University of Pennsylvania Perelman School of Medicine, Department of Biostatistics and Epidemiology, Philadelphia, PA, USA.
Abstract
OBJECTIVES: We explored how objectively measured global positioning system (GPS) and accelerometer data match with travel logs and questionnaires in predicting trip duration and physical activity (PA). METHODS: 99 participants wore GPS devices and accelerometers, and recorded all trips in a log for 5 consecutive days. Participants also completed a self-administered questionnaire on PA and travel behaviors. RESULTS: There was good agreement between GPS and log for assessment of trip duration, although log measures overestimated trip duration (concordance correlation coefficient 0.53 [0.47, 0.59]; Bland-Altman estimate 0.76 [0.16, 3.71] comparing GPS to log). Log measures underestimated light PA and overestimated moderate PA compared to accelerometry when greater than zero moderate PA was reported. CONCLUSIONS: It is often not feasible to deploy accelerometry or GPS devices in population research because these devices are expensive and require technical expertise and data processing. Questionnaires and logs provide inexpensive tools to assess PA and travel with reasonable concordance with objective measures. However, they have shortcomings in evaluating the presence and amount of light and moderate PA. Future questionnaires and logs should be developed to evaluate sensitivity to light and moderate PA.
OBJECTIVES: We explored how objectively measured global positioning system (GPS) and accelerometer data match with travel logs and questionnaires in predicting trip duration and physical activity (PA). METHODS: 99 participants wore GPS devices and accelerometers, and recorded all trips in a log for 5 consecutive days. Participants also completed a self-administered questionnaire on PA and travel behaviors. RESULTS: There was good agreement between GPS and log for assessment of trip duration, although log measures overestimated trip duration (concordance correlation coefficient 0.53 [0.47, 0.59]; Bland-Altman estimate 0.76 [0.16, 3.71] comparing GPS to log). Log measures underestimated light PA and overestimated moderate PA compared to accelerometry when greater than zero moderate PA was reported. CONCLUSIONS: It is often not feasible to deploy accelerometry or GPS devices in population research because these devices are expensive and require technical expertise and data processing. Questionnaires and logs provide inexpensive tools to assess PA and travel with reasonable concordance with objective measures. However, they have shortcomings in evaluating the presence and amount of light and moderate PA. Future questionnaires and logs should be developed to evaluate sensitivity to light and moderate PA.
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