Abstract
Background
Short-term environmental exposures, including green space, air pollution, and noise, have been suggested to affect health. However, the evidence is limited to aggregated exposure estimates which do not allow the capture of daily spatiotemporal exposure sequences. We aimed to (1) determine individuals’ sequential exposure patterns along their daily mobility paths and (2) examine whether and to what extent these exposure patterns were associated with anxiety symptoms.
Methods
We cross-sectionally tracked 141 participants aged 18–65 using their global positioning system (GPS) enabled smartphones for up to 7 days in the Netherlands. We estimated their location-dependent exposures for green space, fine particulate matter, and noise along their moving trajectories at 10-min intervals. The resulting time-resolved exposure sequences were then partitioned using multivariate time series clustering with dynamic time warping as the similarity measure. Respondents’ anxiety symptoms were assessed with the Generalized Anxiety Disorders-7 questionnaire. We fitted linear regressions to assess the associations between sequential exposure patterns and anxiety symptoms.
Results
We found four distinctive daily sequential exposure patterns across the participants. Exposure patterns differed in terms of exposure levels and daily variations. Regression results revealed that participants with a “moderately health-threatening” exposure pattern were significantly associated with fewer anxiety symptoms than participants with a “strongly health-threatening” exposure pattern.
Conclusions
Our findings support that environmental exposures’ daily sequence and short-term magnitudes may be associated with mental health. We urge more time-resolved mobility-based assessments in future analyses of environmental health effects in daily life.
Short-term environmental exposures, including green space, air pollution, and noise, have been suggested to affect health. However, the evidence is limited to aggregated exposure estimates which do not allow the capture of daily spatiotemporal exposure sequences. We aimed to (1) determine individuals’ sequential exposure patterns along their daily mobility paths and (2) examine whether and to what extent these exposure patterns were associated with anxiety symptoms.
Methods
We cross-sectionally tracked 141 participants aged 18–65 using their global positioning system (GPS) enabled smartphones for up to 7 days in the Netherlands. We estimated their location-dependent exposures for green space, fine particulate matter, and noise along their moving trajectories at 10-min intervals. The resulting time-resolved exposure sequences were then partitioned using multivariate time series clustering with dynamic time warping as the similarity measure. Respondents’ anxiety symptoms were assessed with the Generalized Anxiety Disorders-7 questionnaire. We fitted linear regressions to assess the associations between sequential exposure patterns and anxiety symptoms.
Results
We found four distinctive daily sequential exposure patterns across the participants. Exposure patterns differed in terms of exposure levels and daily variations. Regression results revealed that participants with a “moderately health-threatening” exposure pattern were significantly associated with fewer anxiety symptoms than participants with a “strongly health-threatening” exposure pattern.
Conclusions
Our findings support that environmental exposures’ daily sequence and short-term magnitudes may be associated with mental health. We urge more time-resolved mobility-based assessments in future analyses of environmental health effects in daily life.
| Original language | English |
|---|---|
| Article number | 27 |
| Number of pages | 10 |
| Journal | International Journal of Health Geographics |
| Volume | 22 |
| DOIs | |
| Publication status | Published - 10 Oct 2023 |
Bibliographical note
Funding Information:YL was funded by the the China Scholarship Council (CSC) (No. 201908440272). This study was part of the NEEDS project. The research leading to this paper received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation program (Grant Agreement Number 714993). The funders had no role concerning the study design, data collection and analysis, interpretation, or dissemination.
Publisher Copyright:
© 2023, BioMed Central Ltd., part of Springer Nature.
Keywords
- Air pollution
- Daily mobility
- Exposure sequences
- Global positioning system
- Green space
- Noise
- Time series
