Combining sensor tracking with a GPS-based mobility survey to better measure physical activity in trips: public transport generates walking
Abstract Background Policymakers need accurate data to develop efficient interventions to promote transport physical activity. Given the imprecise assessment of physical activity in trips, our aim was to illustrate novel advances in the measurement of walking in trips, including in trips incorporati...
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doaj-8d03c940f5154ebcaae445b928648b532020-11-25T03:42:18ZengBMCInternational Journal of Behavioral Nutrition and Physical Activity1479-58682019-10-0116111310.1186/s12966-019-0841-2Combining sensor tracking with a GPS-based mobility survey to better measure physical activity in trips: public transport generates walkingBasile Chaix0Tarik Benmarhnia1Yan Kestens2Ruben Brondeel3Camille Perchoux4Philippe Gerber5Dustin T. Duncan6Sorbonne Université, INSERM, Institut Pierre Louis d’Epidémiologie et de Santé Publique IPLESP, Nemesis team, Faculté de Médecine Saint-AntoineDepartment of Family Medicine and Public Health & Scripps Institution of Oceanography, University of California in San DiegoDepartment of Social and Preventive Medicine, École de Santé Publique de l’Université de Montréal, Centre de recherche du CHUMDepartment of Social and Preventive Medicine, École de Santé Publique de l’Université de Montréal, Centre de recherche du CHUMLuxembourg Institute of Socio-Economic Research, Maison des Sciences HumainesLuxembourg Institute of Socio-Economic Research, Maison des Sciences HumainesSpatial Epidemiology Lab, Department of Population Health, School of Medicine, New York UniversityAbstract Background Policymakers need accurate data to develop efficient interventions to promote transport physical activity. Given the imprecise assessment of physical activity in trips, our aim was to illustrate novel advances in the measurement of walking in trips, including in trips incorporating non-walking modes. Methods We used data of 285 participants (RECORD MultiSensor Study, 2013–2015, Paris region) who carried GPS receivers and accelerometers over 7 days and underwent a phone-administered web mobility survey on the basis of algorithm-processed GPS data. With this mobility survey, we decomposed trips into unimodal trip stages with their start/end times, validated information on travel modes, and manually complemented and cleaned GPS tracks. This strategy enabled to quantify walking in trips with different modes with two alternative metrics: distance walked and accelerometry-derived number of steps taken. Results Compared with GPS-based mobility survey data, algorithm-only processed GPS data indicated that the median distance covered by participants per day was 25.3 km (rather than 23.4 km); correctly identified transport time vs. time at visited places in 72.7% of time; and correctly identified the transport mode in 67% of time (and only in 55% of time for public transport). The 285 participants provided data for 8983 trips (21,163 segments of observation). Participants spent a median of 7.0% of their total time in trips. The median distance walked per trip was 0.40 km for entirely walked trips and 0.85 km for public transport trips (the median number of accelerometer steps were 425 and 1352 in the corresponding trips). Overall, 33.8% of the total distance walked in trips and 37.3% of the accelerometer steps in trips were accumulated during public transport trips. Residents of the far suburbs cumulated a 1.7 times lower distance walked per day and a 1.6 times lower number of steps during trips per 8 h of wear time than residents of the Paris core city. Conclusions Our approach complementing GPS and accelerometer tracking with a GPS-based mobility survey substantially improved transport mode detection. Our findings suggest that promoting public transport use should be one of the cornerstones of policies to promote physical activity.http://link.springer.com/article/10.1186/s12966-019-0841-2AccelerometryGlobal positioning systemPublic transportTransportWalking |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Basile Chaix Tarik Benmarhnia Yan Kestens Ruben Brondeel Camille Perchoux Philippe Gerber Dustin T. Duncan |
spellingShingle |
Basile Chaix Tarik Benmarhnia Yan Kestens Ruben Brondeel Camille Perchoux Philippe Gerber Dustin T. Duncan Combining sensor tracking with a GPS-based mobility survey to better measure physical activity in trips: public transport generates walking International Journal of Behavioral Nutrition and Physical Activity Accelerometry Global positioning system Public transport Transport Walking |
author_facet |
Basile Chaix Tarik Benmarhnia Yan Kestens Ruben Brondeel Camille Perchoux Philippe Gerber Dustin T. Duncan |
author_sort |
Basile Chaix |
title |
Combining sensor tracking with a GPS-based mobility survey to better measure physical activity in trips: public transport generates walking |
title_short |
Combining sensor tracking with a GPS-based mobility survey to better measure physical activity in trips: public transport generates walking |
title_full |
Combining sensor tracking with a GPS-based mobility survey to better measure physical activity in trips: public transport generates walking |
title_fullStr |
Combining sensor tracking with a GPS-based mobility survey to better measure physical activity in trips: public transport generates walking |
title_full_unstemmed |
Combining sensor tracking with a GPS-based mobility survey to better measure physical activity in trips: public transport generates walking |
title_sort |
combining sensor tracking with a gps-based mobility survey to better measure physical activity in trips: public transport generates walking |
publisher |
BMC |
series |
International Journal of Behavioral Nutrition and Physical Activity |
issn |
1479-5868 |
publishDate |
2019-10-01 |
description |
Abstract Background Policymakers need accurate data to develop efficient interventions to promote transport physical activity. Given the imprecise assessment of physical activity in trips, our aim was to illustrate novel advances in the measurement of walking in trips, including in trips incorporating non-walking modes. Methods We used data of 285 participants (RECORD MultiSensor Study, 2013–2015, Paris region) who carried GPS receivers and accelerometers over 7 days and underwent a phone-administered web mobility survey on the basis of algorithm-processed GPS data. With this mobility survey, we decomposed trips into unimodal trip stages with their start/end times, validated information on travel modes, and manually complemented and cleaned GPS tracks. This strategy enabled to quantify walking in trips with different modes with two alternative metrics: distance walked and accelerometry-derived number of steps taken. Results Compared with GPS-based mobility survey data, algorithm-only processed GPS data indicated that the median distance covered by participants per day was 25.3 km (rather than 23.4 km); correctly identified transport time vs. time at visited places in 72.7% of time; and correctly identified the transport mode in 67% of time (and only in 55% of time for public transport). The 285 participants provided data for 8983 trips (21,163 segments of observation). Participants spent a median of 7.0% of their total time in trips. The median distance walked per trip was 0.40 km for entirely walked trips and 0.85 km for public transport trips (the median number of accelerometer steps were 425 and 1352 in the corresponding trips). Overall, 33.8% of the total distance walked in trips and 37.3% of the accelerometer steps in trips were accumulated during public transport trips. Residents of the far suburbs cumulated a 1.7 times lower distance walked per day and a 1.6 times lower number of steps during trips per 8 h of wear time than residents of the Paris core city. Conclusions Our approach complementing GPS and accelerometer tracking with a GPS-based mobility survey substantially improved transport mode detection. Our findings suggest that promoting public transport use should be one of the cornerstones of policies to promote physical activity. |
topic |
Accelerometry Global positioning system Public transport Transport Walking |
url |
http://link.springer.com/article/10.1186/s12966-019-0841-2 |
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