Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/38746
Title: The impact of black carbon (BC) on mode-specific galvanic skin response (GSR) as a measure of stress in urban environments
Authors: Yang , Xiuleng
Orjuela, Juan Pablo
McCoy, Emma
Vich, Guillem
Anaya-Boig, Esther
Avila-Palencia, Ione
Brand, Christian
Carrasco-Turigas, Gloria
DONS, Evi 
Gerike, Regine
Gotschi, Thomas
Nieuwenhuijsen, Mark
INT PANIS, Luc 
Standaert, Arnout
de Nazelle, Audrey
Issue Date: 2022
Publisher: ACADEMIC PRESS INC ELSEVIER SCIENCE
Source: ENVIRONMENTAL RESEARCH, 214 (4) (Art N° 114083)
Abstract: Previous research has shown that walking and cycling could help alleviate stress in cities, however there is poor knowledge on how specific microenvironmental conditions encountered during daily journeys may lead to varying degrees of stress experienced at that moment. We use objectively measured data and a robust causal inference framework to address this gap. Using a Bayesian Doubly Robust (BDR) approach, we find that black carbon exposure statistically significantly increases stress, as measured by Galvanic Skin Response (GSR), while cycling and while walking. Augmented Outcome Regression (AOR) models indicate that greenspace exposure and the presence of walking or cycling infrastructure could reduce stress. None of these effects are statistically significant for people in motorized transport. These findings add to a growing evidence-base on health benefits of policies aimed at decreasing air pollution, improving active travel infrastructure and increasing greenspace in cities.
Notes: de Nazelle, A (corresponding author), Imperial Coll London, Ctr Environm Policy, 16-18 Princes Gardens, London SW7 1NE, England.
anazelle@imperial.ac.uk
Keywords: Built environment;Urban planning;Stress;Air pollution;Active travel;Causal inference
Document URI: http://hdl.handle.net/1942/38746
ISSN: 0013-9351
e-ISSN: 1096-0953
DOI: 10.1016/j.envres.2022.114083
ISI #: 000860225300012
Rights: 2022 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/)
Category: A1
Type: Journal Contribution
Validations: ecoom 2023
Appears in Collections:Research publications

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