Details

Autor(en) / Beteiligte

• de Nazelle, Audrey
• Seto, Edmund
• Donaire-Gonzalez, David
• Mendez, Michelle
• Matamala, Jaume
• Nieuwenhuijsen, Mark J.
• Jerrett, Michael

Titel

Improving estimates of air pollution exposure through ubiquitous sensing technologies

Ist Teil von

• Environmental pollution (1987), 2013-05, Vol.176, p.92-99

Ort / Verlag

Kidlington: Elsevier Ltd

Erscheinungsjahr

2013

Link zum Volltext

Quelle

MEDLINE

Beschreibungen/Notizen

• Traditional methods of exposure assessment in epidemiological studies often fail to integrate important information on activity patterns, which may lead to bias, loss of statistical power, or both in health effects estimates. Novel sensing technologies integrated with mobile phones offer potential to reduce exposure measurement error. We sought to demonstrate the usability and relevance of the CalFit smartphone technology to track person-level time, geographic location, and physical activity patterns for improved air pollution exposure assessment. We deployed CalFit-equipped smartphones in a free-living population of 36 subjects in Barcelona, Spain. Information obtained on physical activity and geographic location was linked to space-time air pollution mapping. We found that information from CalFit could substantially alter exposure estimates. For instance, on average travel activities accounted for 6% of people's time and 24% of their daily inhaled NO2. Due to the large number of mobile phone users, this technology potentially provides an unobtrusive means of enhancing epidemiologic exposure data at low cost. [Display omitted] ► We track people's movement and physical activity level using smartphone technology. ► We illustrate use of the technology to assess air pollution exposure and inhalation. ► Data from smartphones are integrated with air quality models. ► Smartphones will be connected to air pollution and other sensors in the future. Great potential for exposure assessment is found in Smartphone technology integrating GPS and accelerometry, and more sensors in the future; we illustrate with an application in air pollution.