Demographic, physical activity, and route characteristics related to school transportation: An exploratory study

American Journal of Health Promotion

Volumn 28, Issue SUPPL 3, 2014, Pages

  Lee, Chanam ^a   Li, Li ^a  

^a TEXAS A AND M UNIVERSITY   (United States)

Author keywords

Accelerometer; Built environment; Global positioning system; Physical activity; Prevention research; School transportation; Walking; Walking to school

Indexed keywords

ACCELEROMETRY; CHILD; CROSS-SECTIONAL STUDY; DEVICES; FEMALE; GEOGRAPHIC INFORMATION SYSTEM; HUMAN; MALE; PHYSIOLOGIC MONITORING; PROCEDURES; SCHOOL; STATISTICS AND NUMERICAL DATA; TRAFFIC AND TRANSPORT; UNITED STATES; WALKING;

ACCELEROMETRY; CHILD; CROSS-SECTIONAL STUDIES; FEMALE; GEOGRAPHIC INFORMATION SYSTEMS; HUMANS; MALE; MONITORING, PHYSIOLOGIC; SCHOOLS; TEXAS; TRANSPORTATION; WALKING;

EID: 84892514372     PISSN: 08901171     EISSN: None     Source Type: Journal    
DOI: 10.4278/ajhp.130430-QUAN-211     Document Type: Article

References (52)

1. Ogden CL, Carroll MD, Curtin LR, et al. Prevalence of high body mass index in US children and adolescents, 2007-2008. JAMA. 2010;303:242-249.
2. Centers for Disease Control and Prevention. Barriers to children walking to or from school - United States, 2004. MMWR Morb Mortal Wkly Rep. 2005;54: 949-952.
3. McDonald NC. Active transportation to school: trends among US schoolchildren, 1969-2001. Am J Prev Med. 2007;32:509-516.
4. Martin S, Carlson S. Barriers to children walking to or from school-United States, 2004. JAMA. 2005;294: 2160-2162. [reprinted from MMWR. 2005;54:949-952]
5. McDonald NC, Deakin E, Aalborg AE. Influence of the social environment on children's school travel. Prev Med. 2010; 50:S65-S68.
6. Salmon J, Salmon L, Crawford DA, et al. Associations among individual, social, and environmental barriers and children's walking or cycling to school. Am J Health Promot. 2007;22:107-113.
7. Rodríguez A, Vogt CA. Demographic, environmental, access, and attitude factors that influence walking to school by elementary school-aged children. J Sch Health. 2009;79:255-261.
8. Lee C, Zhu X, Yoon J, Varni J. Beyond distance: children's school travel mode choice. Ann Behav Med. 2013;45:55-67.
9. 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;64:41-48.
10. Timperio A, Ball K, Salmon J, et al. Personal, family, social, and environmental correlates of active commuting to school. Am J Prev Med. 2006;30:45-51.
11. McDonald NC. Travel and the social environment: evidence from Alameda County, California. Transp Res D Transp Environ. 2007;12:53-63.
12. McMillan TE. The relative influence of urban form on a child's travel mode to school. Transp Res A Policy Pract. 2007;41: 69-79.
13. McDonald NC, Brown AL, Marchetti LM, Pedroso MS. U.S. school travel, 2009 an assessment of trends. Am J Prev Med. 2011;41:146-151.
14. Cooper AR, Page AS, Wheeler BW, et al. Mapping the walk to school using accelerometry combined with a global positioning system. Am J Prev Med. 2010; 38:178-183.
15. Webber SC, Porter MM. Monitoring mobility in older adults using global positioning system (GPS) watches and accelerometers: a feasibility study. J Aging Phys Act. 2009;17:455-467.
16. Wu J, Jiang C, Liu Z, Houston D, et al. Performances of different global positioning system devices for timelocation tracking in air pollution epidemiological studies. Environ Health Insights. 2010;4:93-108.
17. Wieters KM, Kim JH, Lee C. Assessment of Wearable global positioning system units for physical activity research. J Phys Act Health. 2012;9:913-923.
18. Smith G, Gidlow C, Davey R, Foster C. Research What is my walking neighbourhood? A pilot study of English adults' definitions of their local walking neighbourhoods. Int J Behav Nutr Phys Act. 2010;7:34-41.
19. Cooper AR, Page AS, Wheeler BW, et al. Patterns of GPS measured time outdoors after school and objective physical activity in English children: the PEACH project. Int J Behav Nutr Phys Act. 2010;7: 31-39.
20. Wheeler BW, Cooper AR, Page AS, Jago R. Greenspace and children's physical activity: a GPS/GIS analysis of the PEACH project. Prev Med. 2010;51:148-152.
21. Oreskovic NM, Blossom J, Field AE, et al. Combining global positioning system and accelerometer data to determine the locations of physical activity in children. Geospat Health. 2012;6:263-272.
22. Rodriguez DA, Cho GH, Elder JP, et al. Identifying walking trips from IGPS and accelerometer data in adolescent females. J Phys Act Health. 2012;9:421-431.
23. Hussey J, Bell C, Gormley J. The measurement of physical activity in children. Phys Ther Rev. 2007;12:52-58.
24. Loprinzi PD, Cardinal BJ. Measuring children's physical activity and sedentary behaviors. J Exerc Sci Fitness. 2011;9:15-23.
25. Srinivasan KK, Pradhan GN, Naidu GM. Commute mode choice in a developing country-role of subjective factors and variations in responsiveness across captive, semicaptive, and choice segments. Transp Res Rec. 2007;2038:53-61.
26. Fillone AM, Montalbo CM, Tiglao NC. Assessing urban travel: a structural equations modeling (SEM) approach. Proc East Asia Soc Transp Stud. 2005;5: 1050-1064.
27. Beimborn EA, Greenwald MJ, Jin X. Accessibility, connectivity, and captivity-impacts on transit choice. Transit Plann Dev Manage Perform Mark Fare Policy Intermodal Transf Facil. 2003;1835:1-9.
28. Earl PE, Potts J. Latent demand and the browsing shopper. Managerial Decis Econ. 2000;21:111-122.
29. Williams PW, Basford R. Segmenting downhill skiing's latent demand markets. Am Behav Sci. 1992;36:222-235.
30. Assaker G, Vinzi VE, O'Connor P. Extending a tourism causality network model: a cross-country, multigroup empirical analysis. Tourism Hospitality Res. 2011;11:258-277.
31. Landis BW. Bicycle system performance measures: the interaction hazard and latent demand score models. ITE J. 1996; 66:18-26.
32. Moudon AV, Hess PM, Matlick JM, Pergakes N. Pedestrian location identification tools: identifying suburban areas with potentially high latent demand for pedestrian travel. Transp Res Rec. 2002;1818:94-101.
33. Ettema D. Latent activities: modeling the relationship between travel times and activity participation. Transp Res Rec. 2005;1926:171-180.
34. Cervero R. Induced travel demand: research design, empirical evidence, and normative policies. J Plann Lit. 2002;17: 3-20.
35. Almanza E, Jerrett M, Dunton G, et al. A study of community design, greenness, and physical activity in children using satellite, GPS and accelerometer data. Health Place. 2012;18:46-54.
36. Tudor-Locke C, Camhi SM, Troiano RP. A catalog of rules, variables, and definitions applied to accelerometer data in the National Health and Nutrition Examination Survey, 2003-2006. Prev Chronic Dis. 2012;9:E113.
37. Trost SG, Loprinzi PD, Moore R, Pfeiffer KA. Comparison of accelerometer cut points for predicting activity intensity in youth. Med Sci Sports Exerc. 2011;43:1360-1368.
38. Crouter SE, Horton M, Bassett DR. Use of a two-regression model for estimating energy expenditure in children. Med Sci Sports Exerc. 2012;44:1177-1185.
39. Harrell JS, McMurray RG, Baggett CD, et al. Energy costs of physical activities in children and adolescents. Med Sci Sports Exerc. 2005;37:329-336.
40. Dunton G, Liao Y, Almanza E, Jerrett M, et al. Locations of joint physical activity in parent-child pairs based on accelerometer and GPS monitoring. Ann Behav Med. 2013;45:162-172.
41. Freedson P, Pober D, Janz KF. Calibration of accelerometer output for children. Med Sci Sports Exerc. 2005;37: S523-S530.
42. Strong WB, Malina RM, Blimkie CJR, et al. Evidence based physical activity for school-age youth. J Pediatr. 2005;146: 732-737.
43. Blaes A, Baquet G, Fabre C, et al. Is there any relationship between physical activity level and patterns, and physical performance in children? Int J Behav Nutr Phys Act. 2011;8:122.
44. Loprinzi PD, Lee H, Cardinal BJ, et al. The relationship of Actigraph Accelerometer cut-points for estimating physical activity with selected health outcomes: results from NHANES 2003-06. Res Q Exerc Sport. 2012;83:422-430.
45. Stone MR, Rowlands AV, Middlebrooke AR, et al. The pattern of physical activity in relation to health outcomes in boys. Int J Pediatr Obes. 2009;4:306-315.
46. Gordon-Larsen P, Nelson MC, Page P, Popkin BM. Inequality in the built environment underlies key health disparities in physical activity and obesity. Pediatrics. 2006;117:417-424.
47. Fernandes M, Sturm R. Facility provision in elementary schools: correlates with physical education, recess, and obesity. Prev Med. 2010;50:S30-S35.
48. Schlossberg M, Greene J, Phillips PP, et al. School trips: effects of urban form and distance on travel mode. J Am Plann Assoc. 2006;72:337-346.
49. Zhu X, Lee C, Lu Z, Yu C. Threshold and impacts of walkable distance for active school transportation in different contexts. Paper presented at: Robert Wood Johnson Foundation Active Living Research; 2012; San Diego, Calif.
50. Pont K, Ziviani J, Wadley D, et al. Environmental correlates of children's active transportation: a systematic literature review. Health Place. 2009;15: 849-862.
51. Cooper AR, Page AS, Foster LJ, Qahwaji D. Commuting to school: are children who walk more physically active? Am J Prev Med. 2003;25:273-276.
52. 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;48:3-8.