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David R. Bassett, Dinesh John, Scott A. Conger, Eugene C. Fitzhugh and Dawn P. Coe

Background:

Increases in childhood and adolescent obesity are a growing concern in the United States (U.S.), and in most countries throughout the world. Declines in physical activity are often postulated to have contributed to the rise in obesity rates during the past 40 years.

Methods:

We searched for studies of trends in physical activity and sedentary behaviors of U.S. youth, using nontraditional data sources. Literature searches were conducted for active commuting, physical education, high-school sports, and outdoor play. In addition, trends in sedentary behaviors were examined.

Results:

Data from the Youth Risk Behavior Surveillance System (YRBSS) and other national surveys, as well as longitudinal studies in the transportation, education, electronic media, and recreation sectors showed evidence of changes in several indicators. Active commuting, high school physical education, and outdoor play (in 3- to 12-year-olds) declined over time, while sports participation in high school girls increased from 1971 to 2012. In addition, electronic entertainment and computer use increased during the first decade of the 21st century.

Conclusions:

Technological and societal changes have impacted the types of physical activities performed by U.S. youth. These data are helpful in understanding the factors associated with the rise in obesity, and in proposing potential solutions.

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Stacy N. Scott, Cary M. Springer, Jennifer F. Oody, Michael S. McClanahan, Brittany D. Wiseman, Tyler J. Kybartas and Dawn P. Coe

Previous progressive aerobic cardiovascular endurance run (PACER) equations were developed to estimate peak oxygen consumption (VO2peak) from data collected during treadmill running. No equation has been developed using VO2peak assessed during the PACER. Purpose: To develop and validate a prediction equation to estimate VO2peak from the PACER in 10- to 15-year-olds. Methods: A sample of 163 youth were recruited to develop (n = 101) and validate (n = 62) a prediction equation. VO2peak was measured using a portable metabolic unit. Regression analysis yielded a prediction equation that included laps, body mass index, and interaction between sex and age. Correlations and repeated-measures analysis of variances were used to compare the measured and estimated VO2peak from the new Scott et al equation and 2 commonly used FitnessGram™ (Mahar et al 2011 and Mahar et al 2018) equations, and the impact of sex on predicted VO2peak. Results: Predicted VO2peak from the Mahar et al 2011 and 2018 equations was significantly lower compared with measured values, and the Scott et al prediction was not different. The Mahar et al 2018 equation tended to overestimate VO2peak in males but worked well for females. The Mahar et al 2011 and Scott et al equations revealed no sex differences. Conclusions: The Scott et al equation resulted in a more accurate estimate of VO2peak, performing equally well for both sexes.

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Samantha F. Ehrlich, Amanda J. Casteel, Scott E. Crouter, Paul R. Hibbing, Monique M. Hedderson, Susan D. Brown, Maren Galarce, Dawn P. Coe, David R. Bassett and Assiamira Ferrara

Background: This study sought to compare three sensor-based wear-time estimation methods to conventional diaries for ActiGraph wGT3X-BT accelerometers worn on the non-dominant wrist in early pregnancy. Methods: Pregnant women (n = 108) wore ActiGraph wGT3X-BT accelerometers for seven days and recorded their device on and off times in a diary (criterion). Average daily wear-time estimates from the Troiano and Choi algorithms and the wGT3X-BT accelerometer wear sensor were compared against the diary. The Hibbing 2-regression model was used to estimate time spent in activity (during periods of device wear) for each method. Wear-time and time spent in activity were compared with multiple repeated measures ANOVAs. Bland Altman plots assessed agreement between methods. Results: Compared to the diary (825.5 minutes [795.1, 856.0]), the Choi (843.0 [95% CI: 812.6, 873.5]) and Troiano (839.1 [808.7, 869.6]) algorithms slightly overestimated wear-time, whereas the sensor (774.4 [743.9, 804.9]) underestimated it, although only the sensor differed significantly from the diary (p < .0001). Upon adjustment for average daily wear-time, there were no statistically significant differences between the wear-time methods in regards to minutes per day of moderate-to-vigorous physical activity (MVPA), vigorous physical activity, and moderate physical activity. Bland Altman plots indicated the Troiano and Choi algorithms were similar to the diary and within ≤0.5% of each other for wear-time and MVPA. Conclusions: The Choi or Troiano algorithms offer a valid and efficient alternative to diaries for the estimation of daily wear-time in larger-scale studies of MVPA during pregnancy, and reduce burden for study participants and research staff.