You are here

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
Status: 
Ongoing
Abstract

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

Kees de Hoogh1,2, Nicole Probst-Hensch1,2,Danielle Vienneau1,2, Ayoung Jeoung1,2, Benjamin Fluekiger1,2,Gerard Hoek3, Roel Vermeulen3, Kalliopi Kyriakou3, Derek Karssenberg4, Meng Li4, Oliver Schmitz4

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 includes tracking campaigns in both countries capturing mobility data for 2000 individuals with a hybrid approach using a bespoke mobile phone App and a purpose-designed tracker device.  The mobility data is used to calibrate agent-based models (ABM) simulating mobility and commuting tracks for several included cohort studies. Existing air pollution exposure models of the traffic-related pollutants NO2, BC, PM2.5, PM2.5 elemental composition and UFP will be enhanced producing long-term hourly estimates. Combining the ABM tracks with the detailed spatial-temporal air pollution data enables 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), are also derived. A dedicated exposure error evaluation, involving simulations, will 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.

Results. We evaluated the tracking capability of the App and the tracker device in both Switzerland and the Netherlands and prepared input databases for the ABM consisting of road network, travel survey data and long-term hourly air pollution surfaces in both countries. We tested the ABM statistical modelling framework on a small subset of the Dutch population creating simulations of personal daily activity schedules for agents, including varying activity duration as well as different activity types and means of transport.

Conclusions. Our initial testing of the tracker devices has demonstrated the feasibility of a hybrid approach in our tracking campaign. Next, the small-scale ABM simulations will be up-scaled to our total study populations.