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Kieran Dowd, Deidre Harrington, Ailish Hannigan, Helen Purtill, Sarah M. Kelly, Alan P. Macken, Niall Moyna, Clodagh S. O’Gorman and Alan E. Donnelly

Objectives:

This study aims to (1) use the objective activPAL activity monitor to assess physical activity behaviors, including sitting/lying, standing, and both light (LIPA) and moderate-to-vigorous physical activity (MVPA); (2) to develop distinct activity profiles based on time spent in each behavior in a sample of adolescent females; and (3) examine whether levels of adiposity differ across these activity profiles.

Methods:

Female adolescents (n = 195; 14–18 y) had body mass index (median = 21.7 [IQR = 5.2] kg/m2) and 4-site skinfold thickness (median 62.0 mm; IQR = 37.1) measured. Physical activity behaviors were measured using the activPAL. Hierarchical cluster analysis grouped participants into activity profiles based on similar physical activity characteristics. Linear mixed models explored differences in body composition across activity profiles.

Results:

Three activity profiles were identified, a low (n = 35), moderate (n = 110), and a high activity profile (n = 50). Significant differences across activity profiles were observed for skinfold thickness (p = .046), with higher values observed in the low activity profile compared with the high activity profile.

Conclusions:

Profiling free-living activity using behaviors from across the activity intensity continuum may account for more of the variability in energy expenditure then examining specific activity intensities, such as MVPA alone. The use of activity profiles may enable the identification of individuals with unhealthy activity behaviors, leading to the development and implementation of more targeted interventions.

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Patty Freedson

measures for extended, field-based studies, but the direct comparison of the Fitbit to a novel pattern recognition methodology called SIP (Sojourns Including Posture) provided a way to evaluate agreement across a full week of free-living activity in participants. The need for precision depends on the

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Liane S. Lewis, James Hernon, Allan Clark and John M. Saxton

across different lifestyle PA domains) to accelerometer cut-points that were calibrated during treadmill walking ( Freedson, Melanson, & Sirard, 1998 ; Copeland & Esliger, 2009 ). One would expect these thresholds would have higher validity for walking than free-living activities. Accelerometer cut

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Christopher P. Connolly, Jordana Dahmen, Robert D. Catena, Nigel Campbell and Alexander H.K. Montoye

Lifestyles at that pace within trimester. c Significantly different than ActiGraph at that pace within trimester. d Significantly different than Fitbit at that pace within trimester. e Significantly different than StepWatch at that pace within trimester. Free-Living Activity Average steps per day recorded

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

generated cut-points of the RT6 in comparison to other tools. In doing this our work seeks to establish validity of the RT6 in a younger adult sample, and provide novel comparisons based on a range of lab-based activities representing free-living activity and location, including energy expenditure

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Giovanni Mario Pes, Maria Pina Dore, Alessandra Errigo and Michel Poulain

under standardized motor activities and for this reason are not suitable to record daily “free-livingactivities. It has been demonstrated that the quantification of physical activity through diaries is dramatically affected by the subjective judgment of the interviewed ( Aguilar-Farías et al., 2015

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Rachel Massie, James Smallcombe and Keith Tolfrey

components of energy balance, measuring EI, EE, and body composition is necessary to examine potential compensatory behaviors ( 30 ). “Compensation” refers to the behaviors that negate the positive health benefits accrued from increasing PA; for example, an increase in EI or decrease in free-living activity

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Laura D. Ellingson, Paul R. Hibbing, Gregory J. Welk, Dana Dailey, Barbara A. Rakel, Leslie J. Crofford, Kathleen A. Sluka and Laura A. Frey-Law

utility. Further, while the present evaluation involves chronic pain patients who are somewhat less active than the general population, the results are intended to be relevant to any application of wrist-worn monitor processing methods for evaluating free-living activity patterns in a clinical or low

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Sheri J. Hartman, Catherine R. Marinac, Lisa Cadmus-Bertram, Jacqueline Kerr, Loki Natarajan, Suneeta Godbole, Ruth E. Patterson, Brittany Morey and Dorothy D. Sears

, Zderic TW , Schuna JM Jr , Hamilton MT , Tudor-Locke C . Free-living activity counts-derived breaks in sedentary time: are they real transitions from sitting to standing? Gait Posture. 2015 ; 42 ( 1 ): 70 – 72 . PubMed doi:10.1016/j.gaitpost.2015.04.008 25953504 10.1016/j.gaitpost.2015

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Charlotte L. Edwardson, Melanie Davies, Kamlesh Khunti, Thomas Yates and Alex V. Rowlands

examine differences in the number of steps recorded during free-living activities where movement patterns of the ND and D hand vary. Consumer activity trackers enable the user to receive feedback on how many steps they are achieving each day and how this compares to recommended levels. These