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Melissa Bittner

Edited by Michael Horvat, Luke Kelly, Martin Block, and Ron Croce. Published 2019 by Human Kinetics, Champaign, IL. $67.00 , 280 pp., ISBN 978-1-4925-4380-0 Developmental and Adapted Physical Activity Assessment , by Michael Horvat, Luke Kelly, Martin Block, and Ron Croce, now in its second

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Jeanne F. Nichols, Hilary Aralis, Sonia Garcia Merino, Michelle T. Barrack, Lindsay Stalker-Fader, and Mitchell J. Rauh

There is a growing need to accurately assess exercise energy expenditure (EEE) in athletic populations that may be at risk for health disorders because of an imbalance between energy intake and energy expenditure. The Actiheart combines heart rate and uniaxial accelerometry to estimate energy expenditure above rest. The authors’ purpose was to determine the utility of the Actiheart for predicting EEE in female adolescent runners (N = 39, age 15.7 ± 1.1 yr). EEE was measured by indirect calorimetry and predicted by the Actiheart during three 8-min stages of treadmill running at individualized velocities corresponding to each runner’s training, including recovery, tempo, and 5-km-race pace. Repeated-measures ANOVA with Bonferroni post hoc comparisons across the 3 running stages indicated that the Actiheart was sensitive to changes in intensity (p < .01), but accelerometer output tended to plateau at race pace. Pairwise comparisons of the mean difference between Actiheart- and criterion-measured EEE yielded values of 0.0436, 0.0539, and 0.0753 kcal · kg−1 · min−1 during recovery, tempo, and race pace, respectively (p < .0001). Bland–Altman plots indicated that the Actiheart consistently underestimated EEE except in 1 runner’s recovery bout. A linear mixed-model regression analysis with height as a covariate provided an improved EEE prediction model, with the overall standard error of the estimate for the 3 speeds reduced to 0.0101 kcal · kg−1 · min−1. Using the manufacturer’s equation that combines heart rate and uniaxial motion, the Actiheart may have limited use in accurately assessing EEE, and therefore energy availability, in young, female competitive runners.

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Stamatis Agiovlasitis, Robert W. Motl, John T. Foley, and Bo Fernhall

This study examined the relationship between energy expenditure and wrist accelerometer output during walking in persons with and without Down syndrome (DS). Energy expenditure in metabolic equivalent units (METs) and activity-count rate were respectively measured with portable spirometry and a uniaxial wrist accelerometer in 17 persons with DS (age: 24.7 ± 6.9 years; 9 women) and 21 persons without DS (age: 26.3 ± 5.2 years; 12 women) during six over-ground walking trials. Combined groups regression showed that the relationship between METs and activity-count rate differed between groups (p < .001). Separate models for each group included activity-count rate and squared activity-count rate as significant predictors of METs (p ≤ .005). Prediction of METs appeared accurate based on Bland-Altman plots and the lack of between-group difference in mean absolute prediction error (DS: 17.07%; Non-DS: 18.74%). Although persons with DS show altered METs to activity-count rate relationship during walking, prediction of their energy expenditure from wrist accelerometry appears feasible.

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* Jeanmarie Burke * Jim Lyons * 10 2007 24 4 352 363 10.1123/apaq.24.4.352 Books & Media Developmental and Adapted Physical Activity Assessment Marci Pope 10 2007 24 4 364 366 10.1123/apaq.24.4.364 Digest Digest Rebecca Woodard Scott J. Pedersen Kevin M. Casebolt Suzanna Rocco Dillon Louisa S

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Tiffanye M. Vargas, Robbi Beyer, and Margaret M. Flores

). Developmental and adapted physical activity assessment . Champaign, IL : Human Kinetics . Jeffery-Tonsoni , J.S. , Eys , M.A. , Schinke , R.J. , & Lewko , J. ( 2011 ). The effect of youth sport status on physical activity and sport participation . Journal of Sport Behavior, 34 , 150 – 159 . King

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Yang Liu and Senlin Chen

composition ) with girls performing better than boys in all PDs, who outscored in nearly all PDs except PD#5 ( knowledge of fitness standards ). The largest gender-based difference was with PD#4 ( knowledge about physical activity assessment ). At the high school level, students’ knowledge scores ranged from

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Yang Liu, Senlin Chen, and Xiangli Gu

differences in the performances. Second, students’ active living behaviors, including physical activity and sedentary behavior, like other performance indicators (e.g., attitude toward PE), were measured by a self-reported questionnaire—YAP. Self-reported tools for physical activity assessment are less valid

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* Katie Cederberg * Kerri A. Vanderbom * C. Scott Bickel * James H. Rimmer * Robert W. Motl * 1 10 2018 35 4 476 497 10.1123/apaq.2017-0109 apaq.2017-0109 BOOKS & MEDIA Developmental and Adapted Physical Activity Assessment, 2nd Edition Melissa Bittner 1 10 2018 35 4 498 500 10.1123/apaq.2018

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Eric Tsz-Chun Poon, John O’Reilly, Sinead Sheridan, Michelle Mingjing Cai, and Stephen Heung-Sang Wong

.M. ( 1987 ). Selection of the optimal skeletal site for fracture risk prediction . Clinical Orthopaedics and Related Research, 216 , 262 – 269 . PubMed Weeks , B.K. , & Beck , B.R. ( 2008 ). The BPAQ: A bone-specific physical activity assessment instrument . Osteoporosis International, 19 ( 11