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Mark G. Davis, Kenneth R. Fox, Afroditi Stathi, Tanya Trayers, Janice L. Thompson and Ashley R. Cooper

The relationship of objectively measured sedentary time (ST), frequency of breaks in ST, and lower extremity function (LEF) was investigated in a diverse sample aged ≥ 70 years (n = 217). Physical activity (PA) was assessed by accelerometry deriving moderate-vigorous PA (MVPA) minutes per registered hour (MVPA min · hr−1), registered ST (ST min · hr−1), and breaks in ST min · hr−1 (breaks · hr−1). LEF was assessed by the Short Physical Performance Battery. Univariate associations with overall LEF were MVPA (r = .523), ST (r = −.499), and breaks (r = .389). Adjusted linear regression including MVPA min · hr−1, ST min · hr−1, and breaks · hr−1 explained 41.5% of LEF variance. Each additional break · hr−1 was associated with 0.58 point increase in LEF. Breaks and MVPA had strongest independent associations with LEF. Promoting regular breaks might be useful in maintaining or increasing LEF and later life independence. This novel finding is important for the design of effective lifestyle interventions targeting older adults.

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Tiago V. Barreira, Stephanie T. Broyles, Catrine Tudor-Locke, Jean-Philippe Chaput, Mikael Fogelholm, Gang Hu, Rebecca Kuriyan, Estelle V. Lambert, Carol A. Maher, José A. Maia, Timothy Olds, Vincent Onywera, Olga L. Sarmiento, Martyn Standage, Mark S. Tremblay, Peter T. Katzmarzyk and for the ISCOLE Research Group

(particularly MVPA) and sedentary time can be associated with household income, and this relationship may differ by a country’s level of human development. Some studies have documented associations between family SES and physical activity among children, 12 but the majority of those studies used questionnaire

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Leigh M. Vanderloo, Natascja A. Di Cristofaro, Nicole A. Proudfoot, Patricia Tucker and Brian W. Timmons

Young children’s activity and sedentary time were simultaneously measured via the Actical method (i.e., Actical accelerometer and specific cut-points) and the ActiGraph method (i.e., ActiGraph accelerometer and specific cut-points) at both 15-s and 60-s epochs to explore possible differences between these 2 measurement approaches. For 7 consecutive days, participants (n = 23) wore both the Actical and ActiGraph side-by-side on an elastic neoprene belt. Device-specific cut-points were applied. Paired sample t tests were conducted to determine the differences in participants’ daily average activity levels and sedentary time (min/h) measured by the 2 devices at 15-s and 60-s time sampling intervals. Bland-Altman plots were used to examine agreement between Actical and ActiGraph accelerometers. Regardless of epoch length, Actical accelerometers reported significantly higher rates of sedentary time (15 s: 42.7 min/h vs 33.5 min/h; 60 s: 39.4 min/h vs 27.1 min/h). ActiGraph accelerometers captured significantly higher rates of moderate-to-vigorous physical activity (15 s: 9.2 min/h vs 2.6 min/h; 60 s: 8.0 min/h vs 1.27 min/h) and total physical activity (15 s: 31.7 min/h vs 22.3 min/h; 60 s: = 39.4 min/h vs 25.2 min/h) in comparison with Actical accelerometers. These results highlight the present accelerometry-related issues with interpretation of datasets derived from different monitors.

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Heather McCracken and Shilpa Dogra

Sedentary time, that is, any activity conducted in a seated or reclined posture that requires low energy expenditure ( Sedentary Behaviour Research Network, 2012 ), is emerging as an important determinant of health among adults ( Owen et al., 2011 ) and older adults ( Dogra & Stathokostas, 2012

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Judith Godin, Joanna M. Blodgett, Kenneth Rockwood and Olga Theou

weight gain, whereas 30 min of brisk walking that replaced slow walking or TV watching was associated with weight loss ( Mekary, Willett, Hu, & Ding, 2009 ). Here, we examined sedentary time as the target behavior to be replaced because of the three activity levels we considered (i.e., sedentary, light

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Jennifer L. Copeland

. Since that time, large-scale epidemiological studies around the world have demonstrated a relationship between sedentary time, estimated in a variety of ways, and the risk of cardiometabolic disease and all-cause mortality ( Healy, Matthews, Dunstan, Winkler, & Owen, 2011 ; Katzmarzyk, Church, Craig

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Koji Yonemoto, Takanori Honda, Hiro Kishimoto, Daigo Yoshida, Jun Hata, Naoko Mukai, Mao Shibata, Yoichiro Hirakawa, Toshiharu Ninomiya and Shuzo Kumagai

Physical inactivity is an established risk factor for noncommunicable diseases and the fourth leading cause of death worldwide. 1 – 3 In recent years, a systematic review and meta-analysis showed that sedentary time is an independent risk factor for type 2 diabetes, cardiovascular disease, and

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Karin Lobenius-Palmér, Birgitta Sjöqvist, Anita Hurtig-Wennlöf and Lars-Olov Lundqvist

sedentary time to ensure good present and future health for youth with disabilities. To design PA interventions for youth with disabilities, it is first necessary to know levels of PA and how PA is influenced by different factors, such as sex, age, and type of disability. This information is important for

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Kelli L. Cain, Edith Bonilla, Terry L. Conway, Jasper Schipperijn, Carrie M. Geremia, Alexandra Mignano, Jacqueline Kerr and James F. Sallis

important to get an accurate assessment of sedentary time. Accelerometers are commonly used to objectively measure sedentary behavior, despite the limitation that accelerometers cannot distinguish sitting from standing ( 26 , 38 ). The definition of nonwear time used in accelerometer data processing

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Kasper Salin, Mikko Huhtiniemi, Anthony Watt, Harto Hakonen and Timo Jaakkola

Research has detailed that insufficient levels of physical activity (PA) and excessive levels of sedentary time (ST) have become a major concern in developed countries. 1 , 2 As a result of insufficient PA and excessive calorie intake, the obesity epidemic among children has become a crucial major