This study evaluated the relative validity of different consumer and research activity monitors during semistructured periods of sedentary activity, aerobic exercise, and resistance exercise. Fifty-two (28 male and 24 female) participants age 18-65 yr performed 20 min of self-selected sedentary activity, 25 min of aerobic exercise, and 25 min of resistance exercise, with 5 min of rest between each activity. Each participant wore five wrist-worn consumer monitors [Fitbit Flex, Jawbone Up24, Misfit Shine (MS), Nike+ Fuelband SE (NFS), and Polar Loop] and two research monitors [ActiGraph GT3X+ on the waist and BodyMedia Core (BMC) on the arm] while being concurrently monitored with Oxycon Mobile (OM), a portable metabolic measuring system. Energy expenditure (EE) on different activity sessions was measured by OM and estimated by all monitors. Mean absolute percent error (MAPE) values for the full 80-min protocol ranged from 15.3% (BMC) to 30.4% (MS). EE estimates from ActiGraph GT3X+ were found to be equivalent to those from OM (± 10% equivalence zone, 285.1-348.5). Correlations between OM and the various monitors were generally high (ranged between 0.71 and 0.90). Three monitors had MAPE values lower than 20% for sedentary activity: BMC (15.7%), MS (18.2%), and NFS (20.0%). Two monitors had MAPE values lower than 20% for aerobic exercise: BMC (17.2%) and NFS (18.5%). None of the monitors had MAPE values lower than 25% for resistance exercise. Overall, the research monitors and Fitbit Flex, Jawbone Up24, and NFS provided reasonably accurate total EE estimates at the individual level. However, larger error was evident for individual activities, especially resistance exercise. Further research is needed to examine these monitors across various activities and intensities as well as under real-world conditions.

Activity monitors are frequently used to assess activity in many settings. But as technology advances, so do the mechanisms used to estimate activity causing a continuous need to validate newly developed monitors. The purpose of this study was to examine the step count validity of the Yamax Digiwalker SW-701 pedometer (YX), Omron HJ-720 T pedometer (OP), Polar Active accelerometer (PAC) and Actigraph gt3x+ accelerometer (AG) under controlled and free-living conditions. Participants completed five stages of treadmill walking (n = 43) and a subset of these completed a 3-day free-living wear period (n = 37). Manually counted (MC) steps provided a criterion measure for treadmill walking, whereas the comparative measure during free-living was the YX. During treadmill walking, the OP was the most accurate monitor across all speeds (±1.1% of MC steps), while the PAC underestimated steps by 6.7–16.0% per stage. During free-living, the OP and AG counted 97.5% and 98.5% of YX steps, respectively. The PAC overestimated steps by 44.0%, or 5,265 steps per day. The Omron pedometer seems to provide the most reliable and valid estimate of steps taken, as it was the best performer under lab-based conditions and provided comparable results to the YX in free-living. Future studies should consider these monitors in additional populations and settings.

This study examined the associations between socioeconomic status (SES) and musculoskeletal (MSF) and cardiorespiratory fitness (CRF) in youth. The sample consisted of boys and girls between 3-15 years. SES was categorized utilizing family-income-to-poverty ratio (FIPR). All analyses were standardized for age and sex. For each test of physical fitness, SES was used to estimate mean fitness test percentile and 95% confidence intervals, controlling for race/ethnicity and physical activity. Odds ratios were calculated for the likelihood of having low fitness by SES category. In general, the high SES group had a better composite MSF, body composition, and CRF profiles than low and moderate SES groups. Statistically significant differences were identified for relative grip strength, plank, body mass index, and cardiovascular endurance time (all p < 0.05). Additionally, the odds of low/poor MSF fitness were 1.7 and 1.6 times higher in the low and moderate SES groups (respectively) compared to the children from high SES families. The moderate SES group had an odds of poor CRF 1.6 times higher than the high SES group as well. Children and adolescents from high SES families tend to have higher mean fitness and were less likely to have low/poor fitness.

Aim. To examine the simultaneous influence of physical activity, screen time, and sleep duration recommendations on the odds of childhood obesity (including overweight). Methods. Physical activity was assessed via pedometer and screen time, and sleep duration were assessed via survey in a cross sectional sample of 674 children (aged 7–12 years) from two Midwestern communities in the fall of 2005. Participants were cross tabulated into four groups depending on how many recommendations were being met (0, 1, 2, or all 3). Linear and logistic regression were used to examine the influence of physical activity, screen time and sleep duration on obesity and interactions among the three variables. Results. Children achieving all three recommendations simultaneously (9.2% of total sample) were the least likely to be obese. Approximately 16% of boys and 9% of girls achieving all recommendations were overweight or obese compared to 53% of boys and 42.5% of girls not achieving any. Conclusions. The odds of obesity increased in a graded manner for each recommendation which was not met. Meeting all three recommendations appears to have a protective effect against obesity. Continued efforts are warranted to promote healthy lifestyle behaviors that include meeting physical activity, screen time, and sleep duration recommendations concurrently.

Background: 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.Methods: 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.Conclusions: 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.