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Louise M. Burke, Bronwen Lundy, Ida L. Fahrenholtz and Anna K. Melin

The human body requires energy for numerous functions including, growth, thermogenesis, reproduction, cellular maintenance, and movement. In sports nutrition, energy availability (EA) is defined as the energy available to support these basic physiological functions and good health once the energy cost of exercise is deducted from energy intake (EI), relative to an athlete’s fat-free mass (FFM). Low EA provides a unifying theory to link numerous disorders seen in both female and male athletes, described by the syndrome Relative Energy Deficiency in Sport, and related to restricted energy intake, excessive exercise or a combination of both. These outcomes are incurred in different dose–response patterns relative to the reduction in EA below a “healthy” level of ∼45 kcal·kg FFM−1·day−1. Although EA estimates are being used to guide and monitor athletic practices, as well as support a diagnosis of Relative Energy Deficiency in Sport, problems associated with the measurement and interpretation of EA in the field should be explored. These include the lack of a universal protocol for the calculation of EA, the resources needed to achieve estimates of each of the components of the equation, and the residual errors in these estimates. The lack of a clear definition of the value for EA that is considered “low” reflects problems around its measurement, as well as differences between individuals and individual components of “normal”/“healthy” function. Finally, further investigation of nutrition and exercise behavior including within- and between-day energy spread and dietary characteristics is warranted since it may directly contribute to low EA or its secondary problems.

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Meaghan Nolan, J. Ross Mitchell and Patricia K. Doyle-Baker

Background:

The popularity of smartphones has led researchers to ask if they can replace traditional tools for assessing free-living physical activity. Our purpose was to establish proof-of-concept that a smartphone could record acceleration during physical activity, and those data could be modeled to predict activity type (walking or running), speed (km·h−1), and energy expenditure (METs).

Methods:

An application to record and e-mail accelerations was developed for the Apple iPhone®/iPod Touch®. Twentyfive healthy adults performed treadmill walking (4.0 km·h−1 to 7.2 km·h1) and running (8.1 km·h−1 to 11.3 km·h−1) wearing the device. Criterion energy expenditure measurements were collected via metabolic cart.

Results:

Activity type was classified with 99% accuracy. Speed was predicted with a bias of 0.02 km·h−1 (SEE: 0.57 km·h−1) for walking, –0.03 km·h−1 (SEE: 1.02 km·h−1) for running. Energy expenditure was predicted with a bias of 0.35 METs (SEE: 0.75 METs) for walking, –0.43 METs (SEE: 1.24 METs) for running.

Conclusion:

Our results suggest that an iPhone/iPod Touch can predict aspects of locomotion with accuracy similar to other accelerometer-based tools. Future studies may leverage this and the additional features of smartphones to improve data collection and compliance.

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Zachary C. Pope, Nan Zeng, Xianxiong Li, Wenfeng Liu and Zan Gao

kilocalories, with the correlations reflective of this metric; *Indicates significant correlation at p  < .05 level; **Indicates significant correlation at p  < 0.01 level. Table 3 Mean Absolute Percent Error for Each Smartwatch’s Energy Expenditure Measurement at Each Physical Activity Intensity Versus

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Whitney A. Welch, Scott J. Strath, Michael Brondino, Renee Walker and Ann M. Swartz

simulate 1 day; however, continuous energy expenditure measurement with indirect calorimetry limited our measurement time. Future work could expand upon these findings by examining additive or sustained effects of LPA throughout a day. Another limitation to this study was the use of a controlled laboratory

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Astrid C.J. Balemans, Han Houdijk, Gilbert R. Koelewijn, Marjolein Piek, Frank Tubbing, Anne Visser-Meily and Olaf Verschuren

tasks and were able to understand and speak Dutch. Patients with stroke were excluded when the prestroke Barthel Index 28 was <19 points. Participant with stroke or CP was excluded when they had pulmonary problems that would interfere with the energy expenditure measurements. Based on clinical

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Denise Rodrigues Bueno, Maria de Fátima Nunes Marucci, Clara Suemi da Costa Rosa, Rômulo Araújo Fernandes, Yeda Aparecida de Oliveira Duarte and Maria Lucia Lebão

– 781 . PubMed doi:10.1097/00005768-199805000-00021 10.1097/00005768-199805000-00021 Garatachea , N. , Luque , G.T. , & Gallego , J.G. ( 2010 ). Physical activity and energy expenditure measurements using accelerometers in older adults . Nutricion Hospitalaria, 25 ( 2 ), 224 – 230 . PubMed

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Sabrine N. Costa, Edgar R. Vieira and Paulo C. B. Bento

energy expenditure measurements using accelerometers in older adults . Nutrici ó n Hospitalaria, 25 ( 2 ), 224 – 230 . PubMed ID: 20449530 doi: 10.3305/nh.2010.25.2.4439 Gill , T.M. , Gahbauer , E.A. , Allore , H. , & Han , L. ( 2006 ). Transitions between frailty states among community

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Kayla J. Nuss, Joseph L. Sanford, Lucas J. Archambault, Ethan J. Schlemer, Sophie Blake, Jimikaye Beck Courtney, Nicholas A. Hulett and Kaigang Li

overtraining . British Journal of Sports Medicine, 28 ( 4 ), 241 – 246 . PubMed ID: 7894955 doi:10.1136/bjsm.28.4.241 10.1136/bjsm.28.4.241 Garatachea , N. , Torres-Luque , G. , & González-Gallego , J. ( 2010 ). Physical activity and energy expenditure measurements using accelerometers in older

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Emma L. J. Eyre, Jason Tallis, Susie Wilson, Lee Wilde, Liam Akhurst, Rildo Wanderleys and Michael J. Duncan

.1080/02640410802334196 Garatachea , N. , Torres Luque , G. , & González Gallego , J. ( 2010 ). Physical activity and energy expenditure measurements using accelerometers in older adults . Nutricion Hospitalaria, 25 ( 2 ), 224 – 30 . PubMed ID: 20449530 Gillen , J.B. , & Gibala , M.J. ( 2013 ). Is high

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higher oestrogen and low progesterone occurs. We conclude that it is reasonable to include females with these characteristics alongside males in studies of this kind without having to control for menstrual cycle phase. Methods of Body Composition and Energy Expenditure Measurement in Male International