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Lennart Raudsepp and Eva-Maria Riso


The objective of this study was to examine the prospective relationship and changes in sedentary behavior between adolescent girls, their mothers and best friends over time.


The results are based on 122 girls aged 11–12 years at baseline measurement, their mothers and best friends who completed ecological momentary assessment diary for the assessment of sedentary behavior. All measurements were taken at 3 time points separated by one year. We used structural equation modeling to examine associations among sedentary behavior of adolescent girls, their mothers and best friends.


A linear growth model for adolescent girls’ and their best friends’ sedentary behavior fit the data well, revealing an overall significant increase in sedentary behavior across time. Initial levels of mothers’ and best friends’ sedentary behavior were positively related with sedentary behavior of adolescent girls. The changes of adolescent girls’ and best friends’ sedentary behavior across 3 years were positively related. Cross-lagged panel analysis demonstrated significant reciprocal effects between adolescent girls’ and best friends’ sedentary behavior. Mothers’ sedentary behavior at baseline predicted daughters’ sedentary behavior at 1-year follow-up and vice versa.


From early to midadolescence, changes in adolescent girls’ sedentary behavior were associated with changes in best friends’ sedentary behavior. These findings suggest reciprocal associations between sedentary behavior of adolescent girls and their best friends.

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Kelly R. Laurson, Joey A. Lee and Joey C. Eisenmann


Physical activity (PA), television time (TV), and sleep duration (SLP) are considered individual risk factors for adolescent obesity. Our aim was to investigate the concurrent influence of meeting PA, SLP, and TV recommendations on adolescent obesity utilizing 2011 Youth Risk Behavior Surveillance Survey (YRBSS) data.


Subjects included 9589 (4874 females) high school students. PA, SLP, and TV were categorized utilizing established national recommendations and youth were cross-tabulated into 1 of 8 groups based on meeting or not meeting each recommendation. Logistic models were used to examine the odds of obesity for each group. Results: Youth meeting the PA recommendation were not at increased odds of obesity, regardless of SLP or TV status. However, not meeting any single recommendation, in general, led to increased odds of not meeting the other two. In boys, 11.8% met all recommendations while 14.1% met 0 recommendations. In girls, only 5.0% met all recommendations while 17.8% met none.


Boys and girls not meeting any of the recommendations were 4.0 and 3.8 times more likely to be obese compared with their respective referent groups. Further research considering the simultaneous influence these risk factors may have on obesity and on one another is warranted.

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Evelin Lätt, Jarek Mäestu and Jaak Jürimäe

adults have shown that not only the total amount of daily sedentary time may be unhealthy, but also the pattern of sedentary time accumulation might have adverse health effects. 3 – 5 Therefore, a more detailed analysis of sedentary behavior accumulation and examining associations for cardiometabolic

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Jade L. Morris, Andy Daly-Smith, Margaret A. Defeyter, Jim McKenna, Steve Zwolinsky, Scott Lloyd, Melissa Fothergill and Pamela L. Graham

effects on sedentary time, LPA, and MVPA. Covariates entered in the model were maturity offset, BMI SD scores, gender, and the appropriate preactivity category. Two subgroups were created using initial accelerometry data on MVPA levels; (1) Low Active (eg, achieved <45 min/d MVPA) and (2) High Active (eg

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Anna Pulakka, Eric J. Shiroma, Tamara B. Harris, Jaana Pentti, Jussi Vahtera and Sari Stenholm

sedentary time, but mainly from accelerometers worn on the hip during wake time only ( Evenson & Terry, 2009 ; Keadle et al., 2014 ; Masse et al., 2005 ; Peeters, van Gellecum, Ryde, Farías, & Brown, 2013 ; Winkler et al., 2012 ). In addition, some studies have assessed impact of sleep algorithms on

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Manon L. Dontje, Calum F. Leask, Juliet Harvey, Dawn A. Skelton and Sebastien F.M. Chastin

daily physical activity ( Chau et al., 2013 ; de Rezende, Rey-López, Matsudo, & do Carmo Luiz, 2014 ; Dogra & Stathokostas, 2012 ). Several national and international health guidelines explicitly recommend that older adults should reduce their sedentary time and break prolonged periods of sitting to

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Peng Zhang, Jung Eun Lee, David F. Stodden and Zan Gao

noted PA and sedentary data generally represent cross-sectional data with longitudinal tracking of individual trajectories of PA and sedentary time receiving limited attention. Lai et al 7 conducted a meta-analysis on the impact of PA interventions and reported only 4 out of 14 studies investigated the

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Ronit Aviram, Netta Harries, Anat Shkedy Rabani, Akram Amro, Ibtisam Nammourah, Muhammed Al-Jarrah, Yoav Raanan, Yeshayahu Hutzler and Simona Bar-Haim

encouraged to increase habitual physical activity (HPA) and reduce sedentary behavior ( 29 ). It is also clear that physical activity declines in typically developing (TD) individuals through adolescence with a concurrent increase in sedentary time in many populations that have been sampled ( 5 , 11 , 23

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Sofia W. Manta, Paula F. Sandreschi, Thiago S. Matias, Camila Tomicki and Tânia R.B. Benedetti

consequences for the health of older adults ( Brocklebank, Falconer, Page, Perry, & Cooper, 2015 ). When combined, PA and sedentary time (ST) can form different patterns of behavior, with a synergistic effect, thus highlighting the importance of interventions that stimulate a positive pattern to produce health

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Mynor Rodriguez-Hernandez, Jeffrey S. Martin, David D. Pascoe, Michael D. Roberts and Danielle W. Wadsworth

, and 49% greater risk of all-cause mortality. Although physical inactivity (ie, sedentary time) seems to be highly predictive of metabolic risks, Healy et al 12 recently demonstrated that replacement of sedentary time with even light physical activity markedly decreased risk of metabolic disease in an