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Alyssa Evans, Gavin Q. Collins, Parker G. Rosquist, Noelle J. Tuttle, Steven J. Morrin, James B. Tracy, A. Jake Merrell, William F. Christensen, David T. Fullwood, Anton E. Bowden and Matthew K. Seeley

.g., cardiovascular disease, cancer, and diabetes) ( Alves et al., 2016 ; Beavis, Smith, & Fader, 2016 ; Hamasaki, 2016 ). Commercially available wearable devices that can estimate activity-based outcomes (e.g., energy expenditure) in real time have been shown to (a) increase exercise motivation, physical activity levels

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Hideaki Kumahara, Hiroaki Tanaka, Philippe Terrier, Kojiro Ishii, Jean-Michel Oppert, Bernard Guy-Grand and Yves Schutz

Background:

Daily energy expenditure (EE) assessment plays an important role in clinical strategies for lifestyle-related diseases. The purpose of this study was to compare the performance of 2 activity monitors from different manufacturers to estimate total energy expenditure (TEE) and physical activity related-energy expenditure (PAEE) in daily living conditions.

Methods:

Sixteen adults stayed in a respiratory chamber for 24 h. The subjects wore 2 accelerometers based on uniaxial (Lifecorder; UNI) and triaxial accelerometry (Tritrac-R3D; TRI).

Results:

A highly significant correlation was observed between measured TEE and estimated values (r=0.868 in UNI and r=0.819 in TRI; P<0.001). However, TEE and PAEE were significantly underestimated: TEEUNI by -9% and TEETRI by -12%; PAEEUNI by -10% and PAEETRI by -55%.

Conclusions:

The EE of structured activity was adequately estimated by both accelerometers, whereas the EE of the non-structured activities involved much more errors. The results also suggest that the algorithm for EE calculation may be more important than the number of planes used for detecting acceleration.

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Gianluca Vernillo, Aldo Savoldelli, Barbara Pellegrini and Federico Schena

The current study aimed to show the validity of a portable motion sensor, the SenseWear Armband (SWA), for the estimation of energy expenditure during pole walking. Twenty healthy adults (mean ± SD: age 30.1 ± 7.2 year, body mass 66.1 ± 10.6 kg, height 172.4 ± 8.0 cm, BMI 22.1 ± 2.4 kg·m−2) wore the armband during randomized pole walking activities at a constant speed (1.25 m·s−1) and at seven grades (0%, ±5%, ±15% and ±25%). Estimates of total energy expenditure from the armband were compared with values derived from indirect calorimetry methodology (IC) using a 2–way mixed model ANOVA (Device × Slope), correlation analyses and Bland-Altman plots. Results revealed significant main effects for device, and slope (p < .025) as well as a significant interaction (p < .001). Significant differences between IC and SWA were observed for all conditions (p < .05). SWA generally underestimate the EE values during uphill PW by 0.04 kcal·kg−1·min−1 (p < .05). Whereas, a significant overestimation has been detected during flat and downhill PW by 0.01 and 0.03 kcal·kg−1·min−1 (p < .05), respectively. The Bland-Altman plots revealed bias of the armband compared with the indirect calorimetry at any condition examined. The present data suggest that the armband is not accurate to correctly detect and estimate the energy expenditure during pole walking activities. Therefore, the observed over- and under-estimations warrants more work to improve the ability of SWA to accurately measure EE for these activities.

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Gladys Block, Christopher D. Jensen, Torin J. Block, Jean Norris, Tapashi B. Dalvi and Ellen B. Fung

Background:

Understanding and increasing physical activity requires assessment of occupational, home, leisure and sedentary activities.

Methods:

A physical activity questionnaire was developed using data from a large representative U.S. sample; includes occupational, leisure and home-based domains; and produces estimates of energy expenditure, percent body fat, minutes in various domains, and meeting recommendations. It was tested in 396 persons, mean age 44 years. Estimates were evaluated in relation to percent body fat measured by dual-energy x-ray absorptiometry.

Results:

Median energy expenditure was 2,365 kcal (women) and 2,960 kcal (men). Women spent 35.1 minutes/day in moderate household activities, 13.0 minutes in moderate leisure and 4.0 minutes in vigorous activities. Men spent 18.0, 22.5 and 15.6 minutes/day in those activities, respectively. Men and women spent 276.4 and 257.0 minutes/day in sedentary activities. Respondents who met recommendations through vigorous activities had significantly lower percent body fat than those who did not, while meeting recommendations only through moderate activities was not associated with percent body fat. Predicted and observed percent body fat correlated at r = .73 and r = .82 for men and women respectively, P < .0001.

Conclusions:

This questionnaire may be useful for understanding health effects of different components of activity, and for interventions to increase activity levels.

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Berit Steenbock, Marvin N. Wright, Norman Wirsik and Mirko Brandes

 al., 2016 ). PA is defined as any bodily movement produced by skeletal muscles that results in energy expenditure (EE) ( Caspersen, Powell, & Christenson, 1985 ). In order to monitor children’s PA, analyze associations between PA and health outcomes, and evaluate the effectiveness of interventions promoting

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John M. Schuna Jr., Daniel S. Hsia, Catrine Tudor-Locke and Neil M. Johannsen

for office furniture that reduces physical work and consequently energy expenditure (EE). 11 The modern office chair, desk, and desktop computer often represent the realization of such deliberate efforts to decrease physical workloads in the workplace. More recently, there has been growing interest

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Erik A. Willis, Amanda N. Szabo-Reed, Lauren T. Ptomey, Jeffery J. Honas, Felicia L. Steger, Richard A. Washburn and Joseph E. Donnelly

The American College of Sports Medicine recommends at least 150 minutes per week of moderate-intensity or 75 minutes per week of vigorous-intensity aerobic activity (minimum of 1000 kcal/wk of energy expenditure), in order to improve health outcomes 3 , 6 and 225 minutes per week (2000 kcal/wk of

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Sze Yen Tan, Marijka Batterham and Linda Tapsell

Background:

Knowing the total energy expenditure (TEE) of overweight adults is important for prescribing weight loss interventions. However, objective measurements of TEE may not always be readily available and can be expensive. This study aimed to investigate the validity of RT3 accelerometers in predicting the TEE of sedentary overweight adults, and to identify any sensitivity to anthropometric changes.

Methods:

The analysis used data from a 12-week weight loss study. At baseline and 12-week, TEE was predicted using RT3 accelerometers during whole room calorimeter stays. Bias between 2 methods was compared at and between the baseline and 12-week measurement points. Multiple regression analyses of TEE data were conducted.

Results:

Predicted and measured values for TEE were not different at baseline (P = .677) but were significantly different after weight loss (P = .007). However, the mean bias between methods was small (<100 kcal/d) and was not significantly different between 2 time-points. RT3 activity counts explained an additional 2% of the variation in TEE at 12-week but not at baseline.

Conclusion:

RT3 accelerometers are not sensitive to body composition changes and do not explain variation in TEE of overweight and obese individuals in a sedentary environment.

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Jungyun Hwang, I-Min Lee, Austin M. Fernandez, Charles H. Hillman and Amy Shirong Lu

’s energy expenditure and for reducing their sedentary pursuits ( 52 ). In the last decade, studies have increasingly utilized exergames for physical activity and health promotion ( 4 , 51 ). However, the relationship between energy expenditure and bodily movement in children of varying weight status using

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Julia L. Bone and Louise M. Burke

The measurement of basal metabolism, the lowest amount of energy required for the body to function, is of interest to athletes due to its potential as a diagnostic tool to detect low energy availability ( Loucks et al., 2011 ; Mountjoy et al., 2015 ). The terms basal energy expenditure (BEE) and