This study investigated the acute effect of exercise on sleep outcomes among healthy older women by comparing days with structured exercise versus days without structured exercise during 4 months of exercise training. Participants (n = 51) in this study had wrist-worn actigraphic sleep data available following at least 3 days with structured exercise and 3 days without structured exercise at mid-intervention and at the end of intervention. The exercise intervention was treadmill walking. Multilevel models were used to examine whether structured exercise impacted sleep outcomes during the corresponding night. Overall, 1,362 nights of data were included in the analyses. In unadjusted and adjusted models, bedtimes were significantly earlier on evenings following an acute bout of structured exercise than on evenings without structured exercise. No other sleep parameters differed between exercise and nonexercise days. Understanding the effects of exercise on sleep in this understudied population may help to improve their overall sleep quality.
Charity B. Breneman, Christopher E. Kline, Delia West, Xuemei Sui and Xuewen Wang
Philip D. Tomporowski, Catherine L. Davis, Kate Lambourne, Mathew Gregoski and Joseph Tkacz
The short-term aftereffects of a bout of moderate aerobic exercise were hypothesized to facilitate children’s executive functioning as measured by a visual task-switching test. Sixty-nine children (mean age = 9.2 years) who were overweight and inactive performed a category-decision task before and immediately following a 23-min bout of treadmill walking and, on another session, before and following a nonexercise period. The acute bout of physical activity did not influence the children’s global switch cost scores or error rates. Age-related differences in global switch cost scores, but not error scores, were obtained. These results, in concert with several studies conducted with adults, fail to confirm that single bouts of moderately intense physical activity influence mental processes involved in task switching.
Melissa N. Galea, Steven R. Bray and Kathleen A. Martin Ginis
This study aimed to identify barriers and facilitators associated with walking for exercise among people who experience intermittent claudication. Fifteen individuals (7 men and 8 women) participated in 3 focus groups that were tape-recorded and content analyzed. A social-cognitive framework was used to categorize barriers and facilitators as those related to the person, to the activity, or to the environment. Variables identified included those specific to intermittent claudication and those common among the general population. Barriers to walking included irregular or graded walking surfaces, uncertainty about the outcome of walking, ambiguity regarding pain, the need to take rest breaks, and the presence of leg pain. Facilitating factors included availability of a resting place, use of cognitive coping strategies, companionship support, and availability of a treadmill-walking program. Findings are interpreted in light of current research on exercise determinants and encourage prospective examinations of the predictive validity of these factors for walking.
Herman-J. Engels and Emily M. Haymes
This study examined the effects of a single dose of caffeine (5 mg:kg−1) on energy metabolism during 60-min treadmill walking at light (30%
James J. McClain, Teresa L. Hart, Renee S. Getz and Catrine Tudor-Locke
This study evaluated the utility of several lower cost physical activity (PA) assessment instruments for detecting PA volume (steps) and intensity (time in MVPA or activity time) using convergent methods of assessment.
Participants included 26 adults (9 male) age 27.3 ± 7.1 years with a BMI of 23.8 ± 2.8 kg/m2. Instruments evaluated included the Omron HJ-151 (OM), New Lifestyles NL-1000 (NL), Walk4Life W4L Pro (W4L), and ActiGraph GT1M (AG). Participants wore all instruments during a laboratory phase, consisting of 10 single minute treadmill walking bouts ranging in speed from 40 to 112 m/min, and immediate following the laboratory phase and during the remainder of their free-living day (11.3 ± 1.5 hours). Previously validated AG MVPA cutpoints were used for comparison with OM, NL, and W4L MVPA or activity time outputs during the laboratory and free-living phase.
OM and NL produced similar MVPA estimates during free-living to commonly used AG walking cutpoints, and W4L activity time estimates were similar to one AG lifestyle cutpoint evaluated.
Current findings indicate that the OM, NL, and W4L, ranging in price from $15 to $49, can provide reasonable estimates of free-living MVPA or activity time in comparison with a range of AG walking and lifestyle cutpoints.
Daniel A. Jacobs and Daniel P. Ferris
Instrumented insoles could benefit locomotion research on healthy and clinical populations by providing data in natural settings outside of the laboratory. We designed a low-cost, instrumented insole with 8 pneumatic bladders to measure localized plantar pressure information. We collected gait data during treadmill walking at 1.0 m/s and 1.5 m/s and for sit-to-stand and stand-tosit tasks for 10 subjects. We estimated a common representation of ground kinetics (3-component force vector, 2-component center of pressure position vector, and a single-component torque vector) from the insole data. We trained an intertask neural network for each component of the kinetic data. For the walking tasks at 1.0 m/s and 1.5 m/s, the normalized root mean square error was between 3.1% and 12.9% and for the sit-to-stand and stand-to-sit tasks, the normalized root mean square error was between 3.3% and 21.3% Our findings suggest that the proposed low-cost, instrumented insoles could provide useful data about movement kinetics during real-world activities.
Yuri Feito, David R. Bassett, Dixie L. Thompson and Brian M. Tyo
Activity monitors are widely used in research, and are currently being used to study physical activity (PA) trends in the US and Canada. The purpose of this study was to determine if body mass index (BMI) affects the step count accuracy of commonly used accelerometer-based activity monitors during treadmill walking.
Participants were classified into BMI categories and instructed to walk on a treadmill at 3 different speeds (40, 67, and 94 m·min−1) while wearing 4 accelerometer-based activity monitors (ActiGraph GT1M, ActiCal, NL-2000, and StepWatch).
There was no significant main effect of BMI on pedometer accuracy. At the slowest speed, all waist-mounted devices significantly underestimated actual steps (P < .001), with the NL-2000 recording the greatest percentage (72%). At the intermediate speed, the ActiGraph was the least accurate, recording only 80% of actual steps. At the fastest speed, all of the activity monitors demonstrated a high level of accuracy.
Our data suggest that BMI does not greatly affect the step-counting accuracy of accelerometer-based activity monitors. However, the accuracy of the ActiGraph, ActiCal, and NL-2000 decreases at slower speeds. The ankle-mounted StepWatch was the most accurate device across a wide range of walking speeds.
Gisela Kobberling, Louis W. Jankowski and Luc Leger
The oxygen consumption (VO2) of 30 (10 females, 20 males) legally blind adolescents and their sighted controls were compared for treadmill walking (3 mph, 4.8 km/h) and running (6 mph, 9.6 km/h). The VO2 of the visually impaired subjects averaged 24.4% and 10.8% higher than those of their same-sex age-matched controls, and 42.8% and 11.2% higher than the American College of Sports Medicine (ACSM) norms for walking (p<.01) and running (p<.05), respectively. The normal association between aerobic capacity and locomotor energy costs was evident among the sighted controls (r= .44, p<.05) but insignificant (r=.35, p>.05) for the visually impaired subjects. The energy costs of both walking and running were highest among the totally blind subjects, and decreased toward normal as a function of residual vision among the legally blind subjects. The energy costs of walking and running for blind adolescents are higher than both those of sighted controls and the ACSM norm values.
Ann F. Maliszewski, Patty S. Freedson, Chris J. Ebbeling, Jill Crussemeyer and Kari B. Kastango
The Caltrac accelerometer functions as either an activity monitor that provides activity counts based on vertical acceleration as the individual moves about, or as a calorie counter in which the acceleration units are used in conjunction with body size, age, and sex to estimate energy expenditure. This study compared VO2 based energy expenditure with Caltrac estimated energy expenditure during three speeds of treadmill walking in children and adults. It also tested the validity of the Caltrac to differentiate between high and low levels of walking activity (activity counts). Ten boys and 10 men completed three randomly assigned walks while oxygen consumption was monitored and Caltrac estimates were obtained. The results indicate that the Caltrac does not accurately predict energy expenditure for boys and men across the three speeds of walking. Although there were no significant differences between actual and predicted energy expenditure values, the standard errors of estimate were high (17-25%) and the only significant correlation was found for men at the fastest walking speed (r=.81). However, the 95% confidence intervals of the activity counts and energy expenditure estimates from the Caltrac support its use as an activity monitor during walking.
Amanda Hickey, Dinesh John, Jeffer E. Sasaki, Marianna Mavilia and Patty Freedson
There is a need to examine step-counting accuracy of activity monitors during different types of movements. The purpose of this study was to compare activity monitor and manually counted steps during treadmill and simulated free-living activities and to compare the activity monitor steps to the StepWatch (SW) in a natural setting.
Fifteen participants performed laboratory-based treadmill (2.4, 4.8, 7.2 and 9.7 km/h) and simulated free-living activities (eg, cleaning room) while wearing an activPAL, Omron HJ720-ITC, Yamax Digi-Walker SW-200, 2 ActiGraph GT3Xs (1 in “low-frequency extension” [AGLFE] and 1 in “normal-frequency” mode), an ActiGraph 7164, and a SW. Participants also wore monitors for 1-day in their free-living environment. Linear mixed models identified differences between activity monitor steps and the criterion in the laboratory/free-living settings.
Most monitors performed poorly during treadmill walking at 2.4 km/h. Cleaning a room had the largest errors of all simulated free-living activities. The accuracy was highest for forward/rhythmic movements for all monitors. In the free-living environment, the AGLFE had the largest discrepancy with the SW.
This study highlights the need to verify step-counting accuracy of activity monitors with activities that include different movement types/directions. This is important to understand the origin of errors in step-counting during free-living conditions.