Literature DB >> 26682132

Are GIS-modelled routes a useful proxy for the actual routes followed by commuters?

Alice M Dalton1, Andrew P Jones1, Jenna Panter2, David Ogilvie2.   

Abstract

Active commuting offers the potential to increase physical activity among adults by being built into daily routines. Characteristics of the route to work may influence propensity to walk or cycle. Geographic information system (GIS) software is often used to explore this by modelling routes between home and work. However, if the validity of modelled routes depends on the mode of travel used, studies of environmental determinants of travel may be biased. We aimed to understand how well modelled routes reflect those actually taken, and what characteristics explain these differences. We compared modelled GIS shortest path routes with actual routes measured using QStarz BT-Q1000X Global Positioning System (GPS) devices in a free-living sample of adults working in Cambridge and using varying travel modes. Predictors of differences, according to length and percentage overlap, between the two route sets were assessed using multilevel regression models and concordance coefficients. The 276 trips, made by 51 participants, were on average 27% further than modelled routes, with an average geographical overlap of 39%. However, predictability of the route depended on travel mode. For route length, there was moderate-to-substantial agreement for journeys made on foot and by bicycle. Route overlap was lowest for trips made by car plus walk (22%). The magnitude of difference depended on other journey characteristics, including travelling via intermediate destinations, distance, and use of busy roads. In conclusion, GIS routes may be acceptable for distance estimation and to explore potential routes, particularly active commuting. However, GPS should be used to obtain accurate estimates of environmental contexts in which commuting behaviour actually occurs. Public health researchers should bear these considerations in mind when studying the geographical determinants and health implications of commuting behaviour, and when recommending policy changes to encourage active travel.

Entities:  

Keywords:  Global Positioning System; active travel; commute environment; geographic information system

Year:  2015        PMID: 26682132      PMCID: PMC4678602          DOI: 10.1016/j.jth.2014.10.001

Source DB:  PubMed          Journal:  J Transp Health        ISSN: 2214-1405


  29 in total

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Journal:  Am J Prev Med       Date:  2002-04       Impact factor: 5.043

Review 2.  Cycling for transport and public health: a systematic review of the effect of the environment on cycling.

Authors:  Simon D S Fraser; Karen Lock
Journal:  Eur J Public Health       Date:  2010-10-06       Impact factor: 3.367

3.  Travel behavior and objectively measured urban design variables: associations for adults traveling to work.

Authors:  Hannah M Badland; Grant M Schofield; Nick Garrett
Journal:  Health Place       Date:  2007-05-18       Impact factor: 4.078

4.  Portable global positioning system receivers: static validity and environmental conditions.

Authors:  Scott Duncan; Tom I Stewart; Melody Oliver; Suzanne Mavoa; Deborah MacRae; Hannah M Badland; Mitch J Duncan
Journal:  Am J Prev Med       Date:  2013-02       Impact factor: 5.043

5.  GPS tracking in neighborhood and health studies: a step forward for environmental exposure assessment, a step backward for causal inference?

Authors:  Basile Chaix; Julie Méline; Scott Duncan; Claire Merrien; Noëlla Karusisi; Camille Perchoux; Antoine Lewin; Karima Labadi; Yan Kestens
Journal:  Health Place       Date:  2013-01-17       Impact factor: 4.078

6.  A concordance correlation coefficient to evaluate reproducibility.

Authors:  L I Lin
Journal:  Biometrics       Date:  1989-03       Impact factor: 2.571

7.  Dynamic Accuracy of GPS Receivers for Use in Health Research: A Novel Method to Assess GPS Accuracy in Real-World Settings.

Authors:  Jasper Schipperijn; Jacqueline Kerr; Scott Duncan; Thomas Madsen; Charlotte Demant Klinker; Jens Troelsen
Journal:  Front Public Health       Date:  2014-03-10

8.  Associations between active commuting, body fat, and body mass index: population based, cross sectional study in the United Kingdom.

Authors:  Ellen Flint; Steven Cummins; Amanda Sacker
Journal:  BMJ       Date:  2014-08-19

9.  Neighborhood, route, and school environments and children's active commuting.

Authors:  Jenna R Panter; Andrew P Jones; Esther M F Van Sluijs; Simon J Griffin
Journal:  Am J Prev Med       Date:  2010-03       Impact factor: 5.043

10.  How well do modelled routes to school record the environments children are exposed to? A cross-sectional comparison of GIS-modelled and GPS-measured routes to school.

Authors:  Flo Harrison; Thomas Burgoine; Kirsten Corder; Esther M F van Sluijs; Andy Jones
Journal:  Int J Health Geogr       Date:  2014-02-14       Impact factor: 3.918

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  5 in total

1.  Effect of the Street Environment on Walking Behavior: A Case Study Using the Route Choice Model in the Chunliu Community of Dalian.

Authors:  Lan Jin; Wei Lu; Peijin Sun
Journal:  Front Public Health       Date:  2022-05-10

Review 2.  Revealed Preference Methods for Studying Bicycle Route Choice-A Systematic Review.

Authors:  Ray Pritchard
Journal:  Int J Environ Res Public Health       Date:  2018-03-07       Impact factor: 3.390

3.  GIS-modelled built-environment exposures reflecting daily mobility for applications in child health research.

Authors:  Amy Mizen; Richard Fry; Sarah Rodgers
Journal:  Int J Health Geogr       Date:  2020-04-10       Impact factor: 3.918

4.  Social Inclusion and Physical Activity in Ciclovía Recreativa Programs in Latin America.

Authors:  Carlos Mejia-Arbelaez; Olga L Sarmiento; Rodrigo Mora Vega; Mónica Flores Castillo; Ricardo Truffello; Lina Martínez; Catalina Medina; Oscar Guaje; José David Pinzón Ortiz; Andres F Useche; David Rojas-Rueda; Xavier Delclòs-Alió
Journal:  Int J Environ Res Public Health       Date:  2021-01-14       Impact factor: 3.390

5.  From motorised to active travel: using GPS data to explore potential physical activity gains among adolescents.

Authors:  Venurs Loh; Shannon Sahlqvist; Jenny Veitch; Lukar Thornton; Jo Salmon; Ester Cerin; Jasper Schipperijn; Anna Timperio
Journal:  BMC Public Health       Date:  2022-08-09       Impact factor: 4.135

  5 in total

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