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Accounting for mobility in air pollution exposure estimates in studies on long-term health effects

Principal Investigator: 

Swiss Tropical and Public Health Institute and Basel University, Switzerland

This study aims to improve our understanding of the contribution of individual mobility in air pollution exposure estimates. The investigators will use location tracking on a mobile phone application for 2,000 individuals in the Netherlands and Switzerland.

Funded under

MOBI-AIR: Accounting for MOBility in AIR pollution exposure estimates in studies on long-term health effects

Kees de Hoogh1,2, Gerard Hoek3, Derek Karssenberg4, Nicole Probst-Hensch1,2, Roel Vermeulen3, Danielle Vienneau1,2

1Swiss Tropical and Public Health Institute; Basel, Switzerland; 2Basel University, Switzerland; 3Institute of Risk Assessment Sciences (IRAS), Utrecht University, the Netherlands; 4Department of Physical Geography (Geo), Utrecht University, the Netherlands

Background: Large scale epidemiological studies investigating long-term health effects of air pollution can typically only consider the residential locations of the participants, thereby ignoring the space-time activity patterns that likely influence total exposure. People are mobile and can be exposed to considerably different levels of air pollution or air pollution mixtures when inside vs. outside, commuting, recreating, or working. Neglecting these mechanisms in exposure assessment may lead to incorrect distributions of exposure over the population which may lead to incorrect exposure health relations in epidemiological studies. The main aim of this study is to assess whether more sophisticated estimates of individual exposure, considering population mobility, decreases the bias in health studies.

Methods: Conducted in Switzerland and the Netherlands, this study will include purpose-designed tracking campaigns in both countries to capture mobility data for 2000 individuals using a freely-available mobile phone App. This information will be used to calibrate agent-based models (ABM) to simulate mobility and commuting tracks for the participants in several included cohort studies. This study draws from our extensive collection of existing air pollution exposure models, and will include these traffic-related pollutants: NO2, BC, PM2.5, PM2.5 elemental composition and UFP. These existing models will be enhanced to produce long-term hourly estimates. Combining the ABM tracks with the detailed spatial-temporal air pollution data will enable calculation of “mobility-enhanced” exposure estimates for every individual in the cohorts. More simple exposure metrics, including the traditional (home address only) and a time-weighted (home + work address), will also be derived. A dedicated exposure error evaluation, involving simulations, will also be conducted to understand the added value of the more sophisticated exposure estimates using ABM to incorporate mobility. Finally, the range of exposure estimates will be used to assess associations with select health endpoints in three large cohort studies (SAPALDIA, EPIC-NL and the Swiss National Cohort) and the influence of these changes in exposure will be evaluated.