Large epidemiological studies that use accelerometers for physical behavior and sleep assessment differ in the location of the accelerometer attachment and the signal aggregation metric chosen. This study aimed to assess the comparability of acceleration metrics between commonly-used body-attachment locations for 24 hours, waking and sleeping hours, and to test comparability of PA cut points between dominant and non-dominant wrist. Forty-five young adults (23 women, 18–41 years) were included and GT3X + accelerometers (ActiGraph, Pensacola, FL, USA) were placed on their right hip, dominant, and non-dominant wrist for 7 days. We derived Euclidean Norm Minus One g (ENMO), Low-pass filtered ENMO (LFENMO), Mean Amplitude Deviation (MAD) and ActiGraph activity counts over 5-second epochs from the raw accelerations. Metric values were compared using a correlation analysis, and by plotting the differences by time of the day. Cut points for the dominant wrist were derived using Lin’s concordance correlation coefficient optimization in a grid of possible thresholds, using the non-dominant wrist estimates as reference. They were cross-validated in a separate sample (N = 36, 10 women, 22–30 years). Shared variances between pairs of acceleration metrics varied across sites and metric pairs (range in r2: 0.19–0.97, all p < 0.01), suggesting that some sites and metrics are associated, and others are not. We observed higher metric values in dominant vs. non-dominant wrist, thus, we developed cut points for dominant wrist based on ENMO to classify sedentary time (<50 mg), light PA (50–110 mg), moderate PA (110–440 mg) and vigorous PA (≥440 mg). Our findings suggest differences between dominant and non-dominant wrist, and we proposed new cut points to attenuate these differences. ENMO and LFENMO were the most similar metrics, and they showed good comparability with MAD. However, counts were not comparable with ENMO, LFENMO and MAD.

This study aims to analyze whether a 13-week exercise program based on 'movement quality' and 'multi-games' can lead to simultaneous benefits to body posture, fundamental movements and physical fitness of children with overweight/obesity. A total of 64 children (10.9 ± 1.3 years, 25.9 ± 3.8 kg/m2, 38 girls and 26 boys) with overweight/obesity were assigned either to a 13-week exercise-based intervention group (IG) (n=33) or to a control group (CG) (n=31).Participants underwent assessments of basic anthropometry (body mass and height), body posture (two-dimensional photogrammetry), fundamental movements (Functional Movement Screen -FMS-TM) and physical fitness (1 repetition maximum -1RMarm and leg press, and ALPHA test battery). After the exercise program, the IG reduced lower limb angle (high effect size: -0.82 SDs; p = 0.001) and plumb-tragus distance (low effect: -0.43 SDs; p = 0.002) in the sagittal plane and increased lower limb angle in the frontal plane (high effect: 0.82 SDs; p = 0.003) compared with the CG. The IG improved their performance in deep squat (p = 0.004), active straight leg raise (p < 0.001), 1RM arm (low effect: 0.46 SDs; p = 0.002), handgrip strength (medium effect: 0.53 SDs; p < 0.001), and standing long jump (medium effect: 0.59 SDs; p = 0.003), all compared with the CG. In conclusion, children with overweight/obesity who participated in our 13-week exercise program developed a better alignment of the head and lower limb, improved their performance in fundamental movements and experienced global muscular strength gains compared with the peers who continued with their usual lives. Among other potential implications, these improvements could contribute to the prevention of musculoskeletal disorders associated with childhood obesity and could increase adherence by positioning these children in a better physical status to keep practicing exercise.

Objectives(1) To develop reference values for health-related fitness in European children and adolescents aged 6–18 years that are the foundation for the web-based, open-access and multilanguage fitness platform (FitBack); (2) to provide comparisons across European countries.MethodsThis study builds on a previous large fitness reference study in European youth by (1) widening the age demographic, (2) identifying the most recent and representative country-level data and (3) including national data from existing fitness surveillance and monitoring systems. We used the Assessing Levels of PHysical Activity and fitness at population level (ALPHA) test battery as it comprises tests with the highest test–retest reliability, criterion/construct validity and health-related predictive validity: the 20 m shuttle run (cardiorespiratory fitness); handgrip strength and standing long jump (muscular strength); and body height, body mass, body mass index and waist circumference (anthropometry). Percentile values were obtained using the generalised additive models for location, scale and shape method.ResultsA total of 7 966 693 test results from 34 countries (106 datasets) were used to develop sex-specific and age-specific percentile values. In addition, country-level rankings based on mean percentiles are provided for each fitness test, as well as an overall fitness ranking. Finally, an interactive fitness platform, including individual and group reporting and European fitness maps, is provided and freely available online (www.fitbackeurope.eu).ConclusionThis study discusses the major implications of fitness assessment in youth from health, educational and sport perspectives, and how the FitBack reference values and interactive web-based platform contribute to it. Fitness testing can be conducted in school and/or sport settings, and the interpreted results be integrated in the healthcare systems across Europe.