Search Results

You are looking at 11 - 20 of 74 items for :

  • "active travel" x
Clear All
Restricted access

Casey P. Durand, Kelley K. Pettee Gabriel, Deanna M. Hoelscher and Harold W. Kohl III

Background:

The potential for adults to accrue significant physical activity through public transit use is a topic of interest. However, there are no data on analogous questions among children. The goal of this analysis was to quantify patterns of transit use and correlates of transit-related physical activity among children aged 5 to 17 years.

Methods:

Data for this cross-sectional study came from the 2012 California Household Travel Survey. Probit regressions modeled the probability of transit use; negative binomial regressions modeled minutes/day in transit-related active travel.

Results:

Public transit use accounted for 3% of trips in California in 2012. Older Hispanic youth and those residing in areas with greater housing density and county size had a higher probability of transit use. Driver licensure, home ownership, household income, and vehicles in household were negatively correlated with public transit use. Race/ethnicity, income, and transit type were correlated with time spent in active travel to/from transit.

Conclusions:

Given its importance as a source of physical activity for some children, researchers should consider assessment of public transit-related activity in physical activity measurement instruments. Efforts to encourage active travel should consider how to incorporate transit-related activity, both from a measurement perspective and as an intervention strategy.

Restricted access

Melissa Bopp, Christopher Bopp and Megan Schuchert

Background:

Active transportation (AT) has been associated with positive health outcomes, yet limited research has addressed this with college students, a population at-risk for inactivity. The purpose of this study was to examine the relationship between AT behavior and objectively measured fitness outcomes.

Methods:

A volunteer, convenience sample (n = 299) of college students from a large northeastern university completed a survey about their AT habits to and on campus and psychosocial constructs related to AT and participated in a laboratory-based fitness assessment (cardiovascular endurance, muscular strength and endurance, flexibility, body composition).Off-campus students were dichotomized as nonactive (0−1 AT trips/day) or active travelers (> 1 AT trips/day) to campus; t-tests compared nonactive and active travelers for psychosocial and fitness variables.

Results:

Students were 56.3% male, 79.2% non-Hispanic White, and primarily living off-campus (87%). Most students (n = 177, 59.2%) reported active travel between classes. Off-campus students were primarily active travelers (76.1%). Active travelers to campus had greater cardiovascular fitness (P = .005), were more flexible (P = .006) and had lower systolic blood pressure (P = .05) compared with nonactive travelers.

Conclusion:

This study documents a relationship between AT behavior and objectively measured fitness among college students and provides a rationale for targeting this behavior as a method for improving health outcomes.

Restricted access

Ka Man Leung and Pak-Kwong Chung

environments), and policy. A growing body of evidence supports associations between walking and physical environments in older adults. The most up-to-date systematic review and meta-analysis ( Cerin et al., 2017 ) analyzed studies on physical–environmental correlates in active travel among older adults

Restricted access

Elaine M. Murtagh and Marie H. Murphy

The purpose of this study was to (1) determine the physical activity levels of 9–11 year old children, and (2) compare the activity levels of children who commute to school by active and passive modes. 140 children aged 9–11 years (85 boys) were recruited from four urban Irish schools. Mode of commuting was assessed by questionnaire. Step counts were measured for 4 consecutive days. Mean daily step counts for the sample were 14386 ± 5634. Boys were significantly more active than girls (15857 ± 5482 vs. 12113 ± 5127 steps). Eighty-seven children (62.1%) traveled by car, 51 children (36.4%) walked to school, one child traveled by bus and one child cycled. Children who walked or cycled to school had higher daily step counts than those who traveled by passive modes (16118 ± 5757 vs. 13363 ± 5332 steps). Active commuting to school may therefore represent a worthwhile strategy for improving children’s physical activity levels.

Open access

Dawn C. Mackey, Alexander D. Perkins, Kaitlin Hong Tai, Joanie Sims-Gould and Heather A. McKay

those barriers. They were also encouraged to add new destinations to their personal travel plan after 6 weeks. Participants and activity coach jointly signing off on their personal physical activity and active travel plans. c. Transit training: A single 60-min group transit training workshop was led by

Restricted access

Richard Larouche, Joel D. Barnes, Sébastien Blanchette, Guy Faulkner, Negin A. Riazi, François Trudeau and Mark S. Tremblay

go from home to the following places using active modes of travel (such as walking, running, biking)?” Hence, all active travel modes were combined for analysis. The questionnaire was designed to capture trips that started or ended at home ( 21 ). In a pilot study, the total number of trips reported

Restricted access

Melody Oliver, Karl Parker, Karen Witten, Suzanne Mavoa, Hannah M. Badland, Phil Donovan, Moushumi Chaudhury and Robin Kearns

Background:

The study aim was to determine the association between children’s objectively assessed moderate-to-vigorous physical activity (MVPA) and active trips (AT) and independently mobile trips (IM) during out-of-school hours.

Methods:

Children aged 9 to 13 years (n = 254) were recruited from 9 schools in Auckland, New Zealand between 2011 and 2012. Children completed travel diaries and wore accelerometers for 7 days. Parents provided demographic information. Geographic information systems-derived distance to school was calculated. Accelerometer data were extracted for out of school hours only. Percentage of time spent in MVPA (%MVPA), AT, and IM were calculated. Generalized estimating equations were used to determine the relationship between daily %MVPA and AT and between daily %MVPA and IM, accounting for age, sex, ethnicity, distance to school, day of the week, and numeric day of data collection.

Results:

A significant positive relationship was observed between %MVPA and both AT and IM. For every unit increase in the daily percentage of trips made that were AT or IM, we found an average increase of 1.28% (95% CI 0.87%, 1.70%) and 1.15% (95% CI 0.71%, 1.59%) time in MVPA, respectively.

Conclusion:

Children’s AT and IM are associated with increased MVPA during out-of-school hours.

Restricted access

Chelsea Steel, Carolina Bejarano and Jordan A. Carlson

Purpose: To investigate potential time drift between devices when using Global Positioning Systems (GPS) and accelerometers in field-based research. Methods: Six Qstarz BT-Q1000XT GPS trackers, activPAL3 accelerometers, and ActiGraph GT3X+ and GT3X accelerometers were tested over 1–3 waves, each lasting 9–14 days. Once per day an event marker was created on each pair of devices concurrently. The difference in seconds between the time stamps for each event marker were calculated between each pair of GPS and activPAL devices and GPS and ActiGraph devices. Mixed-effects linear regression tested time drift across days and waves and between two rooms/locations (in an inner room vs. on a windowsill in an outer room). Results: The GPS trackers remained within one second of the computer clock across days and waves and between rooms. The activPAL devices drifted an average of 8.38 seconds behind the GPS devices over 14 days (p < .001). The ActiGraph GT3X+ devices drifted an average of 11.67 seconds ahead of the GPS devices over 14 days (p < .001). The ActiGraph GT3X devices drifted an average of 28.83 seconds behind the GPS devices over 9 days (p < .001). Time drift did not differ across waves but did differ between rooms and across devices. Conclusions: Time drift between the GPS and accelerometer models tested was minimal and is unlikely to be problematic when addressing many common research questions. However, studies that require high levels of precision when matching short (e.g., 1-second) time intervals may benefit from consideration of time drift and potential adjustments.

Restricted access

Elisa A. Marques, Andreia Isabel Pizarro, Jorge Mota and Maria Paula Santos

Background:

The exact relation between objectively measured moderate-to-vigorous physical activity (MVPA) and independent mobility in children has yet to be fully defined. The objective of this study was to determine whether independent mobility is associated with level of MVPA.

Methods:

Data were collected from 9 middle schools in Porto (Portugal) area. A total of 636 children in the 6th grade (340 girls and 296 boys) with a mean age of 11.64 years old participated in the study. PA was measured in 636 participants using an accelerometer. Multinomial logistic regression was applied to assess the odds for belonging to quartiles of MVPA.

Results:

After controlling for age, gender, body mass index, meeting PA recommendations, and participation in structured exercise, the odds of having a higher level of MVPA when children have higher independent mobility increase through the MVPA quartiles.

Conclusions:

A positive associations were found between independent mobility and quartiles of physical activity.

Restricted access

Sandra A. Ham, Sarah Martin and Harold W. Kohl III

Background:

This report describes changes in the percentage of US students (age 5 to 18 years) who walked or bicycled to school and in the distance that they lived from or traveled to their school in 1969 and 2001 and travel patterns in 2001.

Methods:

Data were from the 1969 National Personal Transportation Survey report on school travel and the 2001 National Household Transportation Survey.

Results:

A smaller percentage of students lived within 1 mile of school in 2001 than in 1969. The percentage of students who walked or biked any distance decreased from 42.0% to 16.2%. Nearly half of students used more than 1 travel mode or went to an additional destination en route between home and school in 2001.

Conclusion:

Multidisciplinary efforts are needed to increase the percentage of students who walk or bike to school, as well as decrease the distances that students travel.