A GPS-Based Methodology to Analyze Environment-Health Associations at the Trip Level: Case-Crossover Analyses of Built Environments and Walking

被引:46
作者
Chaix, Basile [1 ,2 ]
Kestens, Yan [3 ]
Duncan, Dustin T. [4 ]
Brondeel, Ruben [1 ,2 ,5 ]
Meline, Julie [1 ,2 ]
El Aarbaoui, Tarik [1 ,2 ]
Pannier, Bruno [6 ]
Merlo, Juan [7 ]
机构
[1] INSERM, Unite Mixte Rech Sante 1136, Pierre Louis Inst Epidemiol & Publ Hlth, Paris, France
[2] Pierre & Marie Curie Univ Paris 6, Sorbonne Univ, Unite Mixte Rech Sante 1136, Pierre Louis Inst Epidemiol & Publ Hlth, Paris, France
[3] Univ Montreal, Dept Social & Prevent Med, Fac Med, Montreal, PQ, Canada
[4] NYU, Sch Med, Dept Populat Hlth, New York, NY USA
[5] Ecole Hautes Etud Sante Publ, Sch Publ Hlth, Rennes, France
[6] Ctr Invest Prevent & Clin, Paris, France
[7] Lund Univ, Unit Social Epidemiol, Fac Med, Malmo, Sweden
关键词
accelerometry; built environment; global positional system; travel behavior; walking; PHYSICAL-ACTIVITY; RESEARCH AGENDA; RECORD COHORT; RISK-FACTORS; NEIGHBORHOOD; TRANSPORTATION; ACCELEROMETER; MOBILITY; TRAVEL; TIME;
D O I
10.1093/aje/kww071
中图分类号
R1 [预防医学、卫生学];
学科分类号
1004 ; 120402 ;
摘要
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.
引用
收藏
页码:579 / 589
页数:11
相关论文
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