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Measuring environmental exposures in people’s activity space: The need to account for travel modes and exposure decay

Journal of Exposure Science & Environmental Epidemiology volume 33, pages 954–962 (2023)Cite this article

Abstract

Background

Accurately quantifying people’s out-of-home environmental exposure is important for identifying disease risk factors. Several activity space-based exposure assessments exist, possibly leading to different exposure estimates, and have neither considered individual travel modes nor exposure-related distance decay effects.

Objective

We aimed (1) to develop an activity space-based exposure assessment approach that included travel modes and exposure-related distance decay effects and (2) to compare the size of such spaces and the exposure estimates derived from them across typically used activity space operationalizations.

Methods

We used 7-day-long global positioning system (GPS)-enabled smartphone-based tracking data of 269 Dutch adults. People’s GPS trajectory points were classified into passive and active travel modes. Exposure-related distance decay effects were modeled through linear, exponential, and Gaussian decay functions. We performed cross-comparisons on these three functional decay models and an unweighted model in conjunction with four activity space models (i.e., home-based buffers, minimum convex polygons, two standard deviational ellipses, and time-weighted GPS-based buffers). We applied non-parametric Kruskal–Wallis tests, pair-wise Wilcoxon signed-rank tests, and Spearman correlations to assess mean differences in the extent of the activity spaces and correlations across exposures to particulate matter (PM2.5), noise, green space, and blue space.

Results

Participants spent, on average, 42% of their daily life out-of-home. We observed that including travel modes into activity space delineation resulted in significantly more compact activity spaces. Exposure estimates for PM2.5 and blue space were significantly (p < 0.05) different between exposure estimates that did or did not account for travel modes, unlike noise and green space, for which differences did not reach significance. While the inclusion of distance decay effects significantly affected noise and green space exposure assessments, the decay functions applied appear not to have had any impact on the results. We found that residential exposure estimates appear appropriate for use as proxy values for the overall amount of PM2.5 exposure in people’s daily lives, while GPS-based assessments are suitable for noise, green space, and blue space.

Significance

For some exposures, the tested activity space definitions, although significantly correlated, exhibited differing exposure estimate results based on inclusion or exclusion of travel modes or distance decay effect. Results only supported using home-based buffer values as proxies for individuals’ daily short-term PM2.5 exposure.

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Fig. 1
Fig. 2: Spatiotemporal density of participants’ GPS trajectory points over 24 h for each tracking day.
Fig. 3: The size of different contextual units.
Fig. 4: Boxplots of environmental exposures across different contextual units.
Fig. 5: Spearman correlation matrices of environmental exposures across different contextual units.

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Data availability

The GPS data used in this analysis cannot be shared with third parties as per the policies of Statistics Netherlands.

Notes

  1. The contextual unit represents the geographical area (in km2) used as an analytical unit when examining the effects of area-based exposures on individual-level outcomes.

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Acknowledgements

We thank the editor-in-chief and the four anonymous reviewers for their suggestions to improve the original draft of the manuscript.

Funding

The study was supported by EXPOSOME-NL, which is funded through the Gravitation program of the Dutch Ministry of Education, Culture, and Science and the Netherlands Organization for Scientific Research (NWO grant number 024.004.017). This work received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation program (grant agreement No. 714993).

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Authors and Affiliations

  1. Department of Human Geography and Spatial Planning, Utrecht University, Utrecht, The Netherlands

    Lai Wei, Mei-Po Kwan & Marco Helbich

  2. Department of Geography and Resource Management and Institute of Space and Earth Information Science, Chinese University of Hong Kong, Hong Kong, China

    Mei-Po Kwan

  3. Institute for Risk Assessment Sciences, Utrecht University, Utrecht, The Netherlands

    Roel Vermeulen

  4. Julius Centre for Health Sciences and Primary Care, University Medical Centre, Utrecht University, Utrecht, The Netherlands

    Roel Vermeulen

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  1. Lai Wei
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LW: conceptualization, methodology, formal analysis, visualization, writing—original manuscript. M-PK: writing—review and editing, funding acquisition. RV: funding acquisition, project administration. MH: conceptualization, data curation, methodology, writing—review and editing, supervision.

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Correspondence to Lai Wei.

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Wei, L., Kwan, MP., Vermeulen, R. et al. Measuring environmental exposures in people’s activity space: The need to account for travel modes and exposure decay. J Expo Sci Environ Epidemiol 33, 954–962 (2023). https://doi.org/10.1038/s41370-023-00527-z

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