Background: Regular activity breaks positively impact markers of cardiometabolic health when performed in a laboratory. However, identifying compliance to a free-living regular activity breaks intervention is challenging, particularly if intensity is prescribed. Methods: This study had two parts. In Part A, 20 participants performed activity breaks similar to those shown to impart health benefits while wearing an ActiGraph and activPAL accelerometer, and a heart rate monitor. In Part B, the threshold found to identify these activities was used to identify the activity breaks performed by 78 sedentary, university employees wearing an ActiGraph accelerometer for seven days. Results: A cut-point of 1,000 vector magnitude counts per minute accurately identified activity breaks performed in the laboratory. Applying this cut-point to data collected in free living, sedentary participants identified, on average, seven activity breaks were being performed during work-hours. Conclusions: Using a cut-point of 1,000 vector magnitude counts per minute will identify activity breaks of a similar intensity to those found to elicit acute cardiometabolic benefit. Sedentary university employees may benefit from interventions to increase the number of activity breaks performed across their entire day.
Meredith C. Peddie, Matthew Reeves, Millie K. Keown, Tracy L. Perry and C. Murray Skeaff
Kristie Bjornson, Kit Song, Jennifer Lisle, Sarah Robinson, Elizabeth Killien, Terry Barrett and Chuan Zhou
The aim of this study was to describe walking (stride) activity frequency and intensity in 428 children ages 2–15 years with a single accelerometer-based device. With comparison with published pedometer-determined data, the influence of leg length was examined. Decline in stride frequency and intensity throughout childhood increased with adjustment for leg length. The accelerometer-based device documented higher stride counts than published pedometer-based data with the greatest discrepancy in 4–5 year olds. Recommended walking levels for optimal weight throughout childhood should be examined with knowledge of the device measurement differences and the natural history of walking activity changes with age.
Abderrehmane Rahmani, Georges Dalleau, Fabrice Viale, Christophe A. Hautier and Jean-René Lacour
This study determined the validity and reliability of the kinematic device developed by Bosco et al. (1995) by comparing its peak force, peak velocity, and peak power measurements to data obtained simultaneously with a force platform placed under the subject’s feet. Fifteen international downhill skiers performed maximal half-squats on a guided barbell with masses of 60–180 kg. The coefficient of correlation (r) between the two peak forces (r = 0.85–0.95, p < .001), the two peak velocities (r = 0.74–0.91, p < .001), and the two peak powers (r = 0.85–0.95, p < .001) indicated that the kinematic device measurements were valid. The trial-to-trial reliability of half-squat exercises measured by the kinematic device gave an intraclass coefficient of correlation (CR) of: 0.70-0.90 for peak force, 0.62-0.90 for peak velocity, and 0.57-0.91 for peak power. There were no statistical differences between the two trials. The standard error of the means (SEM%) was less than 5% for peak force, less than 4% for peak velocity, and less than 7% for power. The high CR and low SEM% indicate that the kinematic device is reliable. The movement recorded by the kinematic device accurately described the action measured by the force platform.
I-Min Lee, Eric J. Shiroma, Kelly R. Evenson, Masamitsu Kamada, Andrea Z. LaCroix and Julie E. Buring
’Donovan, Lee, Hamer, & Stamatakis, 2017 ). Device measurements can provide more precise classification of this pattern and has recently begun to be used ( Evenson, Herring, & Wen, 2017 ). As endpoints accrue in the continued follow-up of participants in the WHS, we will be able to address such patterns of
John Andrew Badagliacco and Andrew Karduna
performed with the elbow supported in the rotating splint to ensure motion was due to shoulder rotation. The subjects were instructed to keep their backs flat on the testing table, but were otherwise free to rotate as far as possible in either direction within the constraints of the supporting device
James W. Navalta, Jeffrey Montes, Nathaniel G. Bodell, Charli D. Aguilar, Ana Lujan, Gabriela Guzman, Brandi K. Kam, Jacob W. Manning and Mark DeBeliso
the device measurement, and C t represented the criterion measurement. Results Manual Step Count Visual steps determined by two independent counters were determined to be significantly reliable for both the hike as well as the trail run (see Table 1 ). The average of the step counts from the
Berit Steenbock, Marvin N. Wright, Norman Wirsik and Mirko Brandes
per morning, measured one after the other, to avoid interference with lunchtime. A total of 75 min were allocated for the measurement protocol of one child. This included the assessment of anthropometrics, handedness, mounting and demounting the devices, measurement of resting metabolic rate (RMR
Samantha F. Ehrlich, Amanda J. Casteel, Scott E. Crouter, Paul R. Hibbing, Monique M. Hedderson, Susan D. Brown, Maren Galarce, Dawn P. Coe, David R. Bassett and Assiamira Ferrara
.F. ( 2019 ). Reporting of physical activity device measurement and analysis protocols in lifestyle interventions . American Journal of Lifestyle Medicine . Advance online publication. doi:10.1177/1559827619862179 10.1177/1559827619862179 Keadle , S.K. , Shiroma , E.J. , Freedson , P.S. , & Lee , I
Nicholas D. Gilson, Caitlin Hall, Andreas Holtermann, Allard J. van der Beek, Maaike A. Huysmans, Svend Erik Mathiassen and Leon Straker
together where device, measurement, and data analyses were similar (eg, Arias et al 20 and van Dommelen et al 37 ). Accelerometers used included the ActiGraph GT3X (ActiGraph, Pensacola, FL), 20 , 24 – 34 , 37 , 39 the Active Style Pro 21 and the GENEActiv (Activinsights Ltd, Cambridge, United Kingdom
Michael J. LaMonte, I-Min Lee, Eileen Rillamas-Sun, John Bellettiere, Kelly R. Evenson, David M. Buchner, Chongzhi Di, Cora E. Lewis, Dori E. Rosenberg, Marcia L. Stefanick and Andrea Z. LaCroix
( Healy et al., 2011 ; Sallis & Saelens, 2000 ), particularly so in women, in older adults, and in race/ethnic minorities ( Masse et al., 1998 ; van Uffelen, Heesch, Hill, & Brown, 2011 ). There is increasing use of device measurements of PA and SB, which offer the potential for reducing exposure