Abstract
Because of the spatiotemporal variability of people and air pollutants within cities, it is important to account for a person’s movements over time when estimating personal air pollution exposure. This study aimed to examine the feasibility of using smartphones to collect personal-level time–activity data. Using Skyhook Wireless’s hybrid geolocation module, we developed “Apolux” (Air, Pollution, Exposure), an AndroidTM smartphone application designed to track participants’ location in 5-min intervals for 3 months. From 42 participants, we compared Apolux data with contemporaneous data from two self-reported, 24-h time–activity diaries. About three-fourths of measurements were collected within 5 min of each other (mean=74.14%), and 79% of participants reporting constantly powered-on smartphones (n=38) had a daily average data collection frequency of <10 min. Apolux’s degree of temporal resolution varied across manufacturers, mobile networks, and the time of day that data collection occurred. The discrepancy between diary points and corresponding Apolux data was 342.3 m (Euclidian distance) and varied across mobile networks. This study’s high compliance and feasibility for data collection demonstrates the potential for integrating smartphone-based time–activity data into long-term and large-scale air pollution exposure studies.
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Acknowledgements
This study was supported by the National Institute of Environmental Health Sciences (grant no.: 5R21ES017826) and the National Cancer Institute (R25T CA113951). We thank the staff of the Women’s Health Initiative Study in the Department of Epidemiology and Environmental Health, University at Buffalo, The State University of New York.
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Glasgow, M., Rudra, C., Yoo, EH. et al. Using smartphones to collect time–activity data for long-term personal-level air pollution exposure assessment. J Expo Sci Environ Epidemiol 26, 356–364 (2016). https://doi.org/10.1038/jes.2014.78
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DOI: https://doi.org/10.1038/jes.2014.78
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