Skip to main content
Key Specialties
Cardiology Diabetology Endocrinology Gastroenterology Geriatrics and Gerontology Gynecology and Obstetrics Hematology Infectious Disease Internal Medicine Nephrology Neurology Oncology Pediatrics Respiratory Medicine Rheumatology Surgery
Congress Coverage
2024 ACC Congress 2023 ESMO Congress 2023 EASD Congress 2023 ERS Congress 2023 ESC Congress
Clinical Collections
Advances in Alzheimer’s

At a glance: The STEP trials

A round-up of the STEP phase 3 clinical trials evaluating semaglutide for weight loss in people with overweight or obesity.
ADVANCED SEARCH
Log in
Top
BMC Public Health
Published in: BMC Public Health 1/2014

Open Access 01-12-2014 | Research article

Active transport between home and school assessed with GPS: a cross-sectional study among Dutch elementary school children

Authors: Dirk Dessing, Sanne I de Vries, Jamie MA Graham, Frank H Pierik

Published in: BMC Public Health | Issue 1/2014

Login to get access

Abstract

Background

Active transport to school is associated with higher levels of physical activity in children. Promotion of active transport has therefore gained attention as a potential target to increase children’s physical activity levels. Recent studies have recognized that the distance between home and school is an important predictor for active travel among children. These studies did not yet use the promising global positioning system (GPS) methods to objectively assess active transport. This study aims to explore active transport to school in relation to the distance between home and school among a sample of Dutch elementary school children, using GPS.

Methods

Seventy-nine children, aged 6-11 years, were recruited in six schools that were located in five cities in the Netherlands. All children were asked to wear a GPS receiver for one week. All measurements were conducted between December 2008 and April 2009. Based on GPS recordings, the distance of the trips between home and school were calculated. In addition, the mode of transport (i.e., walking, cycling, motorized transport) was determined using the average and maximum speed of the GPS tracks. Then, proportion of walking and cycling trips to school was determined in relation to the distance between home and school.

Results

Out of all school trips that were recorded (n = 812), 79.2% were classified as active transport. On average, active commuting trips were of a distance of 422 meters with an average speed of 5.2 km/hour. The proportion of walking trips declined significantly at increased school trip distance, whereas the proportion of cycling trips (β = 1.23, p < 0.01) and motorized transport (β = 3.61, p < 0.01) increased. Almost all GPS tracks less than 300 meters were actively commuted, while of the tracks above 900 meters, more than half was passively commuted.

Conclusions

In the current research setting, active transport between home and school was the most frequently used mode of travel. Increasing distance seems to be associated with higher levels of passive transport. These results are relevant for those involved in decisions on where to site schools and residences, as it may affect healthy behavior among children.
Appendix
Available only for authorised users
Literature
1.
Strong WB, Malina RM, Blimkie CJR, Daniels SR, Dishman RK, Gutin B, Hergenroeder AC, Must A, Nixon PA, Pivarnik JM: Evidence based physical activity for school-age youth. J Pediatr. 2005, 146 (6): 732-737. 10.1016/j.jpeds.2005.01.055.CrossRefPubMed
2.
Janssen I, LeBlanc AG: Systematic review of the health benefits of physical activity and fitness in school-aged children and youth. Int J Behav Nutr Phys Act. 2010, 7: 40-10.1186/1479-5868-7-40.CrossRefPubMedPubMedCentral
3.
World Health Organization: Global recommendations on physical activity for health. 2010, Geneva: WHO Press
4.
Kemper HGC, Ooijendijk WTM, Stiggelbout M: Consensus over de Nederlandse Norm voor Gezond Bewegen. Tijdschr Soc Gezondheidsz. 2000, 78: 180-183.
5.
De Vries SI, Hopman-Rock M, Bakker I, Van Mechelen W: Meeting the 60-min physical activity guideline: effect of operationalization. Med Sci Sports Exerc. 2009, 41 (1): 81-86. 10.1249/MSS.0b013e318184c931.CrossRefPubMed
6.
Ekelund U, Tomkinson G, Armstrong N: What proportion of youth are physically active? Measurement issues, levels and recent time trends. Br J Sports Med. 2011, 45 (11): 859-865. 10.1136/bjsports-2011-090190.CrossRefPubMed
7.
De Vries SI, Chorus AMJ: Bewegen in Nederland: jeugdigen van 4-17 jaar. TNO Trendrapport Bewegen en Gezondheid. Edited by: Hildebrandt VH, Chorus AMJ, Stubbe JH. 2010, Leiden: De Bink, 57-76.
8.
Faulkner GE, Buliung RN, Flora PK, Fusco C: Active school transport, physical activity levels and body weight of children and youth: a systematic review. Prev Med. 2009, 48 (1): 3-8. 10.1016/j.ypmed.2008.10.017.CrossRefPubMed
9.
Lubans DR, Boreham CA, Kelly P, Foster CE: The relationship between active travel to school and health-related fitness in children and adolescents: a systematic review. Int J Behav Nutr Phys Act. 2011, 8: 5-10.1186/1479-5868-8-5.CrossRefPubMedPubMedCentral
10.
van Sluijs EM, Fearne VA, Mattocks C, Riddoch C, Griffin SJ, Ness A: The contribution of active travel to children’s physical activity levels: cross-sectional results from the ALSPAC study. Prev Med. 2009, 48 (6): 519-524. 10.1016/j.ypmed.2009.03.002.CrossRefPubMed
11.
Tudor-Locke C, Ainsworth BE, Popkin BM: Active commuting to school: an overlooked source of childrens’ physical activity?. Sports Med. 2001, 31 (5): 309-313. 10.2165/00007256-200131050-00001.CrossRefPubMed
12.
Cooper AR, Page AS, Wheeler BW, Griew P, Davis L, Hillsdon M, Jago R: Mapping the walk to school using accelerometry combined with a global positioning system. Am J Prev Med. 2010, 38 (2): 178-183. 10.1016/j.amepre.2009.10.036.CrossRefPubMed
13.
Frank LD, Engelke P: Multiple impacts of the built environment on public health: Walkable places and the exposure to air pollution. Int Reg Sci Rev. 2005, 28 (2): 193-216. 10.1177/0160017604273853.CrossRef
14.
Maibach E, Steg L, Anable J: Promoting physical activity and reducing climate change: opportunities to replace short car trips with active transport. Prev Med. 2009, 49 (4): 326-327. 10.1016/j.ypmed.2009.06.028.CrossRefPubMed
15.
McDonald NC: Active transport to school: trends among U.S. schoolchildren, 1969-2001. Am J Prev Med. 2007, 32 (6): 509-516. 10.1016/j.amepre.2007.02.022.CrossRefPubMed
16.
Van der Ploeg HP, Merom D, Corpuz G, Bauman AE: Trends in Australian children traveling to school 1971–2003: burning petrol or carbohydrates?. Prev Med. 2008, 46 (1): 60-62. 10.1016/j.ypmed.2007.06.002.CrossRefPubMed
17.
Grize L, Bringolf-Isler B, Martin E, Braun-Fahrländer C: Trend in active transport to school among Swiss school children and its associated factors: three cross-sectional surveys 1994, 2000 and 2005. Int J Behav Nutr Phys Act. 2010, 7: 28-10.1186/1479-5868-7-28.CrossRefPubMedPubMedCentral
18.
Pucher J, Buehler R: Making cycling irresistible: Lessons from the Netherlands, Denmark and Germany. Transport Rev. 2008, 28 (4): 495-528. 10.1080/01441640701806612.CrossRef
19.
Davison KK, Werder JL, Lawson CT: Children’s active commuting to school: current knowledge and future directions. Prev Chronic Dis. 2008, 5 (3): A100-PubMedPubMedCentral
20.
Panter JR, Jones AP, van Sluijs EM, Griffin SJ: Attitudes, social support and environmental perceptions as predictors of active commuting behaviour in school children. J Epidemiol Community Health. 2010, 64 (1): 41-48. 10.1136/jech.2009.086918.CrossRefPubMedPubMedCentral
21.
Wong BY, Faulkner G, Buliung R: GIS measured environmental correlates of active school transport: a systematic review of 14 studies. Int J Behav Nutr Phys Act. 2011, 8: 39-10.1186/1479-5868-8-39.CrossRefPubMedPubMedCentral
22.
Timperio A, Ball K, Salmon J, Roberts R, Giles-Corti B, Simmons D, Baur LA, Crawford D: Personal, family, social, and environmental correlates of active commuting to school. Am J Prev Med. 2006, 30 (1): 45-51. 10.1016/j.amepre.2005.08.047.CrossRefPubMed
23.
McMillan TE: The relative influence of urban form on a child’s travel mode to school. Transport Res Part A Policy Prac. 2007, 41 (1): 69-79. 10.1016/j.tra.2006.05.011.CrossRef
24.
Pont K, Ziviani J, Wadley D, Bennett S, Abbott R: Environmental correlates of children’s active transport: a systematic literature review. Health Place. 2009, 15 (3): 827-840.CrossRefPubMed
25.
Ziviani J, Scott J, Wadley D: Walking to school: incidental physical activity in the daily occupations of Australian children. Occup Ther Int. 2004, 11 (1): 1-11. 10.1002/oti.193.CrossRefPubMed
26.
McDonald NC: Children’s mode choice for the school trip: the role of distance and school location in walking to school. Transport. 2008, 35 (1): 23-35.CrossRef
27.
Duncan MJ, Mummery WK: GIS or GPS? A comparison of two methods for assessing route taken during active transport. Am J Prev Med. 2007, 33 (1): 51-53. 10.1016/j.amepre.2007.02.042.CrossRefPubMed
28.
Schlossberg M, Greene J, Phillips PP, Johnson B, Parker B: School trips: effects of urban form and distance on travel mode. J Am Planning Association. 2006, 72 (3): 337-346. 10.1080/01944360608976755.CrossRef
29.
de Vries SI, Hopman-Rock M, Bakker I, Hirasing RA, van Mechelen W: Built environmental correlates of walking and cycling in Dutch urban children: results from the SPACE study. Int J Environ Res Public Health. 2010, 7 (5): 2309-2324. 10.3390/ijerph7052309.CrossRefPubMedPubMedCentral
30.
Jones AP, Coombes EG, Griffin SJ, van Sluijs EM: Environmental supportiveness for physical activity in English schoolchildren: a study using Global Positioning Systems. Int J Behav Nutr Phys Act. 2009, 6: 42-10.1186/1479-5868-6-42.CrossRefPubMedPubMedCentral
31.
Quigg R, Gray A, Reeder AI, Holt A, Waters DL: Using accelerometers and GPS units to identify the proportion of daily physical activity located in parks with playgrounds in New Zealand children. Prev Med. 2010, 50 (5–6): 235-240.CrossRefPubMed
32.
Kerr J, Duncan S, Schipperijn J: Using global positioning systems in health research: a practical approach to data collection and processing. Am J Prev Med. 2011, 41 (5): 532-540. 10.1016/j.amepre.2011.07.017.CrossRefPubMed
33.
de Vries SI, Bakker I, van Mechelen W, Hopman-Rock M: Determinants of activity-friendly neighborhoods for children: results from the SPACE study. Am J Health Promot. 2007, 21 (Suppl 4): 312-316.CrossRefPubMed
34.
Cole TJ, Bellizzi MC, Flegal KM, Dietz WH: Establishing a standard definition for child overweight and obesity worldwide: international survey. BMJ. 2000, 320 (7244): 1240-1243. 10.1136/bmj.320.7244.1240.CrossRefPubMedPubMedCentral
35.
36.
Maas J, Sterkenburg RP, de Vries SI, Pierik F: Using GPS to measure the interaction between indiciduals and their neighborhood. Neighbourhood Structure and Health Promotion: An Introduction. Edited by: Stock C, Ellaway A. 2013, US: Springer, 153-176.CrossRef
37.
Bonner MR, Han D, Nie J, Rogerson P, Vena JE, Freudenheim JL: Positional accuracy of geocoded addresses in epidemiologic research. Epidemiology. 2003, 14 (4): 408-412.PubMed
38.
Bohte W, Maat K: Deriving and validating trip purposes and travel modes for multi-day GPS-based travel surveys: a large-scale application in the Netherlands. Transport Res Part C Emerg Technol. 2009, 17 (3): 285-297. 10.1016/j.trc.2008.11.004.CrossRef
39.
Yeung J, Wearing S, Hills AP: Child transport practices and perceived barriers in active commuting to school. Transport Res Part A Policy Prac. 2008, 42 (6): 895-900. 10.1016/j.tra.2007.12.007.CrossRef
40.
Yang Y, Diez Roux AV, Bingham CR: Variability and seasonality of active transport in USA: evidence from the 2001 NHTS. Int J Behav Nutr Phys Act. 2011, 8: 96-10.1186/1479-5868-8-96.CrossRefPubMedPubMedCentral
41.
42.
Mitra R, Buliung RN, Roorda MJ: Built environment and school travel mode choice in Toronto, Canada. Transport Res Rec J Transport Res Board. 2010, 2156: 150-159. 10.3141/2156-17.CrossRef
43.
Ahlport KN, Linnan L, Vaughn A, Evenson KR, Ward DS: Barriers to and facilitators of walking and bicycling to school: formative results from the non-motorized travel study. Health Educ Behav. 2008, 35 (2): 221-244.CrossRefPubMed
44.
Jacobsen PL: Safety in numbers: more walkers and bicyclists, safer walking and bicycling. Injury Prev. 2003, 9 (3): 205-209. 10.1136/ip.9.3.205.CrossRef
45.
Southward EF, Page AS, Wheeler BW, Cooper AR: Contribution of the school journey to daily physical activity in children aged 11-12 years. Am J Prev Med. 2012, 43 (2): 201-204. 10.1016/j.amepre.2012.04.015.CrossRefPubMed
46.
Klinker CD, Schipperijn J, Christian H, Kerr J, Ersbøll AK, Troelsen J: Using accelerometers and global positioning system devices to assess gender and age differences in children’s school, transport, leisure and home based physical activity. Int J Behav Nutr Phys Act. 2014, 11 (1): 8-10.1186/1479-5868-11-8.CrossRefPubMedPubMedCentral
47.
de Vries SI, Garre FG, Engbers LH, Hildebrandt VH, Van Buuren S: Evaluation of neural networks to identify types of activity using accelerometers. Med Sci Sports Exerc. 2011, 43 (1): 101-107. 10.1249/MSS.0b013e3181e5797d.CrossRefPubMed
Metadata
Title
Active transport between home and school assessed with GPS: a cross-sectional study among Dutch elementary school children
Authors
Dirk Dessing
Sanne I de Vries
Jamie MA Graham
Frank H Pierik
Publication date
01-12-2014
Publisher
BioMed Central
Published in
BMC Public Health / Issue 1/2014
Electronic ISSN: 1471-2458
DOI
https://doi.org/10.1186/1471-2458-14-227

Other articles of this Issue 1/2014

BMC Public Health 1/2014 Go to the issue

Study protocol

Rationale and study design of the Japan environment and children’s study (JECS)

Research article

Linking secondary school physical education with community sport and recreation for girls: a process evaluation

Research article

Prevalence and risk factors for cervical neoplasia: a cervical cancer screening program in Beijing

Research article

Neck circumference as a measure of neck fat and abdominal visceral fat in Chinese adults

Research article

An update on the prevalence of metabolic syndrome and its associated factors in rural northeast China

Research article

Determinants of health check attendance in adults: findings from the cross-sectional German Health Update (GEDA) study