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Christopher K. Rhea, Jed A. Diekfuss, Jeffrey T. Fairbrother and Louisa D. Raisbeck

potential age differences in this context is due to sensory integration differences previously observed between younger and older adults ( Redfern, Jennings, Martin, & Furman, 2001 )—indicating that observations for one age group may (or may not) generalize to another age group. Our primary hypothesis was

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Mark De Ste Croix, Abigail Priestley, Rhodri Lloyd and Jon Oliver

Participant characteristics can be seen in Table  1 , which indicates a significant difference between groups for all outcome variables. Table 1 Participant Characteristics by Age Group   U13 U15 U17 Mean ( SD ) Mean ( SD ) Mean ( SD ) Age, y 12.1 (0.5)* 13.9 (0.6) 15.8 (0.5) Stature, m 1.46 (0.06)* 1.59 (0

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Diana Marina Camargo, Paula Camila Ramírez, Vanesa Quiroga, Paola Ríos, Rogério César Férmino and Olga L. Sarmiento

the 3 parks with the highest crime rate) or the app for iPads (iSOPARC) 21 to register the data. SOPARC has been widely used to assess public areas and parks and provides information on the people observed according to age groups (children: 1–12 y old, adolescents: 13–20 y old, adults: 21–59 y old

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Hayley Guiney, Michael Keall and Liana Machado

be achieved via bouts of at least 30 min of activity on 5 days each week ( Government of the Netherlands, 2016 ; Ministry of Health, 2013 ). Despite the well understood benefits of physical activity for all age groups, especially older adults, and clear guidelines on minimum recommended levels of

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Lena Hübner, Solveig Vieluf, Ben Godde and Claudia Voelcker-Rehage

) for all parameters ( SD , T rel , and F rel ). The tests revealed good reliability, as indicated by high Cronbach’s α values (mean ±  SD of all trials per pretest, practice, posttest, and retention block, depicted per parameter and age group); SD : α = .93 ± .02; T rel : α = .82 ± .04; F rel : α

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Elroy J. Aguiar, John M. Schuna Jr., Tiago V. Barreira, Emily F. Mire, Stephanie T. Broyles, Peter T. Katzmarzyk, William D. Johnson and Catrine Tudor-Locke

30-min cadence in older adults, stratified by sex and age groups, from the nationally representative NHANES 2005–2006 PAM data. This tabulation of peak 30-min cadence extends beyond a single central tendency measure of peak 30-min cadence and as such will be useful as normative (reference) data for

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Chanel T. LoJacono, Ryan P. MacPherson, Nikita A. Kuznetsov, Louisa D. Raisbeck, Scott E. Ross and Christopher K. Rhea

statistical tests. Results While preferred waking speed was slower for the older adults ( M  = 0.43, SD  = 0.08 m/s) compared to the younger adults ( M  = 0.96, SD  = 0.18 m/s; t (38) = 2.37, p  = .02), there was no difference in RPE between the age groups at any of the time points ( p  > .05). Pass Rates

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Katherine Reta Devonshire-Gill and Kevin Ian Norton

consistency in determining sufficiency status category. 25 The self-reported responses to the core PA questions provided the data for the study. The sociodemographic variables examined in the study were sex (male/female), age group in years (18–24, 25–34, 35–44, 45–54, 55–64, 65–74, 75+), geographic area of

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Christopher R. Hill, Deborah L. Feltz, Stephen Samendinger and Karin A. Pfeiffer

measuring both PA and BSE. For example, it could be particularly troublesome to ask younger children to recall PA, especially for time periods of up to a week, or decipher what periods of movement equate to PA. Researchers should also take a meticulous approach to considering barriers to PA in young age

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Laura J. McGowan, Rachael Powell and David P. French

Older adults are the least physically active and most sedentary age group ( De Rezende, Rey-López, Matsudo, & do Carmo Luiz, 2014 ), with sedentary behavior being a risk factor for obesity, diabetes, heart disease, ovarian, endometrial and colon cancers, and premature mortality ( Thorp, Owen