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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.

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author
organization
publishing date
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
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
2017-11-14 09:53:23
@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},
  volume       = {184},
  year         = {2016},
}