Background: The direction of the longitudinal relationship between physical activity (PA) and fundamental motor skills (FMS) remains unclear. We evaluated the bi-directional, prospective relationships between intensity-specific physical activity (PA) and domain-specific fundamental motor skills (FMS) over 2 years in children attending preschool at baseline. Methods: A sample of 230 children (mean age at baseline 4.7 yr, 52% boys) from the 'Sogn og Fjordane Preschool Physical Activity Study' was measured 2 years apart. PA was assessed using ActiGraph accelerometers (GT3X+). FMS were evaluated by a test battery guided by the 'Test of Gross Motor Development 3' and the 'Preschooler Gross Motor Quality Scale'. PA outcomes were total PA (TPA [counts per minute]) and intensity specific PA and sedentary behaviour (SED) (min/day). FMS outcomes were locomotor, object control, and balance skills. Linear mixed model adjusting for potential co-variates was used to evaluate the bi-directional prospective associations between these variables, including the moderating effect of sex and age. Results: Baseline total PA, moderate-to-vigorous PA (MVPA), and vigorous PA predicted higher locomotor, object control, and balance skills at follow-up (standardized regression coefficient (β): 0.17 to 0.26, p = 0.002–0.017). Baseline SED predicted lower locomotor skills at follow-up (β: − 0.27, p = 0.012). Baseline light PA did not predict FMS at follow-up. Baseline FMS were not associated with PA or SED at follow-up. Conclusions: MVPA was positively associated with development of FMS in young children. In contrast, FMS were not related to future PA levels. Our results suggest promotion of MVPA is important for FMS development in young children.

Reliability of the Actigraph GT3X+ accelerometer has not been determined under normal wear time criteria in a large sample of subjects and accelerometer units. The aim of this study was to assess contralateral hip difference and inter-instrument reliability of the Actigraph GT3X+ monitor in adults under long-term free-living conditions. Eighty-seven adult subjects (28 men; mean (standard deviation) age 31.3 (12.2) years; body mass index 23.7 (3.1) kg/m²) concurrently wore two GT3X+ accelerometers (174 units in total) attached to contralateral hips for 21 days. Reliability was assessed using Bland-Altman plots, mixed model regression analyses and absolute measures of agreement for different lengths of data accumulation (single-day-, 7-day- and 21-day periods). There were no significant differences between contralateral hips (effect size ≤0.042; p ≥.213). Inter-instrument reliability increased with increased length of data-accumulation. For a 7-day measurement period (n = 232 weeks), limits of agreement were ±68 cpm (vertical axis) and ±81.3 cpm (vector magnitude) for overall physical activity (PA) level, ±51 min for sedentary time, ±18.2 min for light PA, ±6.3 min for moderate PA, ±3.5 min for vigorous PA, and ±6.7 min for moderate-to-vigorous PA. The Actigraph GT3X+ accelerometer is a reliable tool for measuring PA in adults under free-living conditions using normal data-reduction criteria. Contralateral hip differences are very small. We suggest accelerometers be attached to the right hip and data to be accumulated over several days of measurement.

To investigate the effect of a seven-month, school-based cluster-randomized controlled trial on academic performance in 10-year-old children. In total, 1129 fifth-grade children from 57 elementary schools in Sogn og Fjordane County, Norway, were cluster-randomized by school either to the intervention group or to the control group. The children in the 28 intervention schools participated in a physical activity intervention between November 2014 and June 2015 consisting of three components: 1) 90min/week of physically active educational lessons mainly carried out in the school playground; 2) 5min/day of physical activity breaks during classroom lessons; 3) 10min/day physical activity homework. Academic performance in numeracy, reading and English was measured using standardized Norwegian national tests. Physical activity was measured objectively by accelerometry. We found no effect of the intervention on academic performance in primary analyses (standardized difference 0.01-0.06, p>0.358). Subgroup analyses, however, revealed a favorable intervention effect for those who performed the poorest at baseline (lowest tertile) for numeracy (p=0.005 for the subgroup∗group interaction), compared to controls (standardized difference 0.62, 95% CI 0.19-1.07). This large, rigorously conducted cluster RCT in 10-year-old children supports the notion that there is still inadequate evidence to conclude that increased physical activity in school enhances academic achievement in all children. Still, combining physical activity and learning seems a viable model to stimulate learning in those academically weakest schoolchildren.

The inter-relationship between physical activity, sedentary behaviour and sleep (collectively defined as physical behaviours) is of interest to researchers from different fields. Each of these physical behaviours has been investigated in epidemiological studies, yet their codependency and interactions need to be further explored and accounted for in data analysis. Modern accelerometers capture continuous movement through the day, which presents the challenge of how to best use the richness of these data. In recent years, analytical approaches first applied in other scientific fields have been applied to physical behaviour epidemiology (eg, isotemporal substitution models, compositional data analysis, multivariate pattern analysis, functional data analysis and machine learning). A comprehensive description, discussion, and consensus on the strengths and limitations of these analytical approaches will help researchers decide which approach to use in different situations. In this context, a scientific workshop and meeting were held in Granada to discuss: (1) analytical approaches currently used in the scientific literature on physical behaviour, highlighting strengths and limitations, providing practical recommendations on their use and including a decision tree for assisting researchers’ decision-making; and (2) current gaps and future research directions around the analysis and use of accelerometer data. Advances in analytical approaches to accelerometer-determined physical behaviours in epidemiological studies are expected to influence the interpretation of current and future evidence, and ultimately impact on future physical behaviour guidelines.

In adults, a minimum of 3–5 days of accelerometer monitoring is usually considered appropriate to obtain reliable estimates of physical activity (PA). However, a longer period of measurement might be needed to obtain reliable estimates of sedentary behavior (SED). The aim of this study was to determine the reliability of objectively assessed SED and PA in adults. Eighty-seven adult subjects (28 men; mean (standard deviation) age 31.3 (12.2) years; body mass index 23.7 (3.1) kg/m²) wore the GT3X+ accelerometer for 21 subsequent days, for which the reliability of different wear time criteria (8 to 12 h/day and 3 to 5 d/week) was explored. Variance partitioning along with the Spearman-Brown prophecy formula was used as the basis for determining intraclass-correlation coefficients (ICC) and the number of monitoring days needed (N) to achieve an ICC = 0.80. Week-by-week reliability was reported using ICC, Bland-Altman plots and absolute measures of agreement. Seven-10 days of monitoring was needed to reliably assess overall- (axis 1 and vector magnitude (VM) counts per minute (CPM)) and moderate-to-vigorous PA (MVPA), 3–4 days was needed for light PA (LPA), whereas the number of days needed for SED depended on whether adjustments were made for wear time (6–8 days) or not (13–15 days). The week-by-week ICC was ≥0.70 for all variables, with limits of agreement being ±267.8 cpm for CPM, ±352.3 cpm for VM CPM, ±76.8 min/day for SED, ±57.8 min/day for LPA and ±43.8 min/day for MVPA, equal to 1.0–1.6 standard deviations, when adjustment was made for wear time. For most variables, more than one week of measurement was needed to achieve an ICC = 0.80. Correcting for wear time was crucial to reliably determine SED. Considerable week-by-week variability was found for all variables. Researchers need to be aware of substantial intra-individual variability in accelerometer-measurements.

Physical activity is a cornerstone for promoting good metabolic health in children, but it is heavily debated which intensities (including sedentary time) are most influential. A fundamental limitation to current evidence for this relationship is the reliance on analytic approaches that cannot handle collinear variables. The aim of the present study was to determine the physical activity signature related to metabolic health in children, by investigating the association pattern for the whole spectrum of physical activity intensities using multivariate pattern analysis. We used a sample of 841 children (age 10.2 ± 0.3 years; BMI 18.0 ± 3.0; 50% boys) from the Active Smarter Kids study, who provided valid data on accelerometry (ActiGraph GT3X+) and several indices of metabolic health (aerobic fitness, abdominal fatness, insulin sensitivity, lipid metabolism, blood pressure) that were used to create a composite metabolic health score. We created 16 physical activity variables covering the whole intensity spectrum (from 0–100 to ≥ 8000 counts per minute) and used multivariate pattern analysis to analyze the data. Physical activity intensities in the vigorous range (5000–7000 counts per minute) were most strongly associated with metabolic health. Moderate intensity physical activity was weakly related to health, and sedentary time and light physical activity were not related to health. This study is the first to determine the multivariate physical activity signature related to metabolic health in children across the whole intensity spectrum. This novel approach shows that vigorous physical activity is strongest related to metabolic health. We recommend future studies adapt a multivariate analytic approach to further develop the field of physical activity epidemiology. The study was registered in Clinicaltrials.gov (www.clinicaltrials.gov) 7th of April 2014 with identification number NCT02132494 .