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Mary O. Hearst, John R. Sirard, Leslie Lytle, Donald R. Dengel and David Berrigan


The association of physical activity (PA), measured 3 ways, and biomarkers were compared in a sample of adolescents.


PA data were collected on 2 cohorts of adolescents (N = 700) in the Twin Cities, Minnesota, 2007–2008. PA was measured using 2 survey questions [Modified Activity Questionnaire (MAQ)], the 3-Day Physical Activity Recall (3DPAR), and accelerometers. Biomarkers included systolic (SBP) and diastolic blood pressure (DBP), lipids, percent body fat (%BF), and body mass index (BMI) percentile. Bivariate relationships among PA measures and biomarkers were examined followed by generalized estimating equations for multivariate analysis.


The 3 measures were significantly correlated with each other (r = .22–.36, P < .001). Controlling for study, puberty, age, and gender, all 3 PA measures were associated with %BF (MAQ = −1.93, P < .001; 3DPAR = −1.64, P < .001; accelerometer = −1.06, P = .001). The MAQ and accelerometers were negatively associated with BMI percentile. None of the 3 PA measures were significantly associated with SBP or lipids. The percentage of adolescents meeting the national PA recommendations varied by instrument.


All 3 instruments demonstrated consistent findings when estimating associations with %BF, but were different for prevalence estimates. Researchers must carefully consider the intended use of PA data when choosing a measurement instrument.

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Catia Martins, Irina Kazakova, Marit Ludviksen, Ingar Mehus, Ulrik Wisloff, Bard Kulseng, Linda Morgan and Neil King

This study aimed to determine the effects of 12 weeks of isocaloric programs of high-intensity intermittent training (HIIT) or moderate-intensity continuous training (MICT) or a short-duration HIIT (1/2HIIT) inducing only half the energy deficit on a cycle ergometer, on body weight and composition, cardiovascular fitness, resting metabolism rate (RMR), respiratory exchange ratio (RER), nonexercise physical activity (PA) levels and fasting and postprandial insulin response in sedentary obese individuals. Forty-six sedentary obese individuals (30 women), with a mean BMI of 33.3 ± 2.9 kg/m2 and a mean age of 34.4 ± 8.8 years were randomly assigned to one of the three training groups: HIIT (n = 16), MICT (n = 14) or 1/2HIIT (n = 16) and exercise was performed 3 times/week for 12 weeks. Overall, there was a significant reduction in body weight, waist (p < .001) and hip (p < .01) circumference,, trunk and leg fat mass (FM; p < .01) and an increase in trunk and leg fat free mass (FFM; p < .01) and cardiovascular fitness (VO2max in ml/kg/min; p < .001) with exercise. However, no significant differences were observed between groups. There was no significant change in RMR, RER, nonexercise PA levels, fasting insulin or insulin sensitivity with exercise or between groups. There was a tendency for a reduction in AUC insulin with exercise (p = .069), but no differences between groups. These results indicate that isocaloric training protocols of HIIT or MICT (or 1/2HIIT inducing only half the energy deficit) exert similar metabolic and cardiovascular improvements in sedentary obese individuals.

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Andrew O. Agbaje, Eero A. Haapala, Niina Lintu, Anna Viitasalo, Juuso Väistö, Sohaib Khan, Aapo Veijalainen, Tuomo Tompuri, Tomi Laitinen and Timo A. Lakka

augment venous return from peripheral tissues to the heart by their contractions and therefore increases stroke volume and cardiac output ( 39 , 41 ). Moreover, using valid and reproducible measurement, we controlled for maturation and body composition in our statistical analyses ( 27 , 45 ). This study

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Marjan Mosalman Haghighi, Yorgi Mavros and Maria A. Fiatarone Singh

, there was no association between change in PA and change in HbA 1c in these 14 trials of behavioral programs, which reported both outcomes using meta-regression ( r  = −.46, P  = .64). This result was similar with the exclusion of the outlier 22 (data not shown). Body Composition Outcomes Data for

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Carina Bauer, Christine Graf, Anna M. Platschek, Heiko K. Strüder and Nina Ferrari

physical activity affects maternal body composition and metabolism. Women who were physically active during pregnancy had reduced risk of excessive weight gain 39 and offspring obesity. 40 Therefore, women should be encouraged to participate in regular physical activity. Consequently, knowledge about

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Ryan P. Durk, Esperanza Castillo, Leticia Márquez-Magaña, Gregory J. Grosicki, Nicole D. Bolter, C. Matthew Lee and James R. Bagley

gut microbiota composition (F/B) and VO 2 max, body composition, or dietary intake among healthy young adults in a free-living environment. Materials and Methods This study was conducted in accordance with the Declaration of Helsinki and approved by San Francisco State University’s Institutional

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Øyvind Sandbakk, Guro Strøm Solli and Hans-Christer Holmberg

in cross-country skiing, where the sex differences become more pronounced as the contribution from upper-body poling increases. 8 Figure 3 —Sex differences in power output, body composition, and physiological variables in connection with various sports. The values given are the increase in men

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Stephanie A. Hooker, Laura B. Oswald, Kathryn J. Reid and Kelly G. Baron

, and mortality. Evidence suggests that sleep is also associated with body composition, with both short and long sleep duration associated with greater likelihood of obesity. 4 Most of the research targeting these health behaviors focuses on the average engagement in behaviors over time. Although

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Alexei Wong and Arturo Figueroa

predominance ( Pagani et al., 1986 ). We followed the standards for the measurement and interpretation of the HRV ( Task Force, 1996 ). Controlled breathing (12 breaths/min) was maintained following a metronome. Body Composition Height and body weight were measured to the nearest 0.5 cm and 0.1 kg

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Alexei Wong, Arturo Figueroa, Marcos A. Sanchez-Gonzalez, Won-Mok Son, Oksana Chernykh and Song-Young Park

were conducted by the same researcher who was unaware of group assignment. Anthropometry and Body Composition Body composition was assessed using an eight-polar tactile-electrode impedance meter (InBody 720; Biospace, Seoul, Korea), which simultaneously recorded bodyweight, fat mass and fat free mass