A GPS-Based Methodology to Analyze Environment-Health Associations at the Trip Level : Case-Crossover Analyses of Built Environments and Walking
Chaix, Basile LU ; Kestens, Yan ; Duncan, Dustin T ; Brondeel, Ruben ; Méline, Julie ; El Aarbaoui, Tarik ; Pannier, Bruno and Merlo, Juan LU
(2016)
In American Journal of Epidemiology
184(8).
p.570-578
- Abstract
Environmental health studies have examined associations between context and health with individuals as statistical units. However, investigators have been unable to investigate momentary exposures, and such studies are often vulnerable to confounding from, for example, individual-level preferences. We present a Global Positioning System (GPS)-based methodology for segmenting individuals' observation periods into visits to places and trips, enabling novel life-segment investigations and case-crossover analysis for improved inferences. We analyzed relationships between built environments and walking in trips. Participants were tracked for 7 days with GPS receivers and accelerometers and surveyed with a Web-based mapping application about... (More)
Environmental health studies have examined associations between context and health with individuals as statistical units. However, investigators have been unable to investigate momentary exposures, and such studies are often vulnerable to confounding from, for example, individual-level preferences. We present a Global Positioning System (GPS)-based methodology for segmenting individuals' observation periods into visits to places and trips, enabling novel life-segment investigations and case-crossover analysis for improved inferences. We analyzed relationships between built environments and walking in trips. Participants were tracked for 7 days with GPS receivers and accelerometers and surveyed with a Web-based mapping application about their transport modes during each trip (Residential Environment and Coronary Heart Disease (RECORD) GPS Study, France, 2012-2013; 6,313 trips made by 227 participants). Contextual factors were assessed around residences and the trips' origins and destinations. Conditional logistic regression modeling was used to estimate associations between environmental factors and walking or accelerometry-assessed steps taken in trips. In case-crossover analysis, the probability of walking during a trip was 1.37 (95% confidence interval: 1.23, 1.61) times higher when trip origin was in the fourth (vs. first) quartile of service density and 1.47 (95% confidence interval: 1.23, 1.68) times higher when trip destination was in the fourth (vs. first) quartile of service density. Green spaces at the origin and destination of trips were also associated with within-individual, trip-to-trip variations in walking. Our proposed approach using GPS and Web-based surveys enables novel life-segment epidemiologic investigations.
(Less)
- author
- Chaix, Basile
LU
; Kestens, Yan
; Duncan, Dustin T
; Brondeel, Ruben
; Méline, Julie
; El Aarbaoui, Tarik
; Pannier, Bruno
and Merlo, Juan
LU
- organization
- publishing date
- 2016-10-15
- type
- Contribution to journal
- publication status
- published
- subject
- in
- American Journal of Epidemiology
- volume
- 184
- issue
- 8
- pages
- 570 - 578
- publisher
- Oxford University Press
- external identifiers
-
- wos:000386552900003
- scopus:84993660578
- pmid:27659779
- ISSN
- 0002-9262
- DOI
- 10.1093/aje/kww071
- language
- English
- LU publication?
- yes
- id
- 2f83a015-f20b-4958-aeb8-5549f97d7554
- date added to LUP
- 2016-11-01 08:06:47
- date last changed
- 2024-07-26 20:58:14
@article{2f83a015-f20b-4958-aeb8-5549f97d7554,
abstract = {{<p>Environmental health studies have examined associations between context and health with individuals as statistical units. However, investigators have been unable to investigate momentary exposures, and such studies are often vulnerable to confounding from, for example, individual-level preferences. We present a Global Positioning System (GPS)-based methodology for segmenting individuals' observation periods into visits to places and trips, enabling novel life-segment investigations and case-crossover analysis for improved inferences. We analyzed relationships between built environments and walking in trips. Participants were tracked for 7 days with GPS receivers and accelerometers and surveyed with a Web-based mapping application about their transport modes during each trip (Residential Environment and Coronary Heart Disease (RECORD) GPS Study, France, 2012-2013; 6,313 trips made by 227 participants). Contextual factors were assessed around residences and the trips' origins and destinations. Conditional logistic regression modeling was used to estimate associations between environmental factors and walking or accelerometry-assessed steps taken in trips. In case-crossover analysis, the probability of walking during a trip was 1.37 (95% confidence interval: 1.23, 1.61) times higher when trip origin was in the fourth (vs. first) quartile of service density and 1.47 (95% confidence interval: 1.23, 1.68) times higher when trip destination was in the fourth (vs. first) quartile of service density. Green spaces at the origin and destination of trips were also associated with within-individual, trip-to-trip variations in walking. Our proposed approach using GPS and Web-based surveys enables novel life-segment epidemiologic investigations.</p>}},
author = {{Chaix, Basile and Kestens, Yan and Duncan, Dustin T and Brondeel, Ruben and Méline, Julie and El Aarbaoui, Tarik and Pannier, Bruno and Merlo, Juan}},
issn = {{0002-9262}},
language = {{eng}},
month = {{10}},
number = {{8}},
pages = {{570--578}},
publisher = {{Oxford University Press}},
series = {{American Journal of Epidemiology}},
title = {{A GPS-Based Methodology to Analyze Environment-Health Associations at the Trip Level : Case-Crossover Analyses of Built Environments and Walking}},
url = {{http://dx.doi.org/10.1093/aje/kww071}},
doi = {{10.1093/aje/kww071}},
volume = {{184}},
year = {{2016}},
}