Differences between 9–11 year old British Pakistani and White British girls in physical activity and behavior during school recess

Background: School recess provides an important opportunity for children to engage in physical activity. Previous studies indicate that children and adults of South Asian origin are less active than other ethnic groups in the United Kingdom, but have not investigated whether activity differs within the shared school environment. The aim of this study was to test the hypothesis that British Pakistani girls aged 9–11 years are less active during recess than White British girls. Methods: In Study One, the proportion of recess spent by 137 White British (N = 70) and British Pakistani (N = 67) girls in sedentary behavior, moderate-to-vigorous activity (MVPA) and vigorous activity (VPA) was determined using accelerometry. In Study Two, 86 White British (N = 48) and British Pakistani (N = 38) girls were observed on the playground using the System for Observing Children’s Activity and Relationships during Play (SOCARP). Accelerometry data were collected during observations to allow identification of activities contributing to objectively measured physical activity. Results: Accelerometry data indicated that British Pakistani girls spent 2.2% (95% CI: 0.2, 4.3) less of their total recess time in MVPA and 1.3% (95% CI: 0.2, 2.4) less in VPA than White British girls. Direct observation showed that British Pakistani girls spent 12.0% (95% CI: 2.9, 21.1) less playground time being very active, and 12.3% (95% CI: 1.7, 23.0) less time playing games. Time spent being very active according to direct observation data correlated significantly with accelerometer-assessed time spent in MVPA and VPA, and time spent playing games correlated significantly with accelerometer-assessed time spent in VPA, suggesting that differences in behavior observed in Study Two may have contributed to the differences in time spent in MVPA and VPA in Study One. Conclusions: British Pakistani girls were less active than White British girls during school recess. Recess has been identified as a potentially important target for the delivery of physical activity interventions; such interventions should consider ways in which the activity levels of British Pakistani girls could be increased

Fundamental Movement Skills in relation to weekday and weekend physical activity in preschool children

OBJECTIVES: To examine associations between fundamental movement skills and weekday and weekend physical activity among preschool children living in deprived communities. DESIGN: Cross-sectional observation study. METHODS: Six locomotor skills and 6 object-control skills were video-assessed using The Children's Activity and Movement in Preschool Study Motor Skills Protocol. Physical activity was measured via hip-mounted accelerometry. A total of 99 children (53% boys) aged 3-5 years (M 4.6, SD 0.5) completed all assessments. Multilevel mixed regression models were used to examine associations between fundamental movement skills and physical activity. Models were adjusted for clustering, age, sex, standardised body mass index and accelerometer wear time. RESULTS: Boys were more active than girls and had higher object-control skill competency. Total skill score was positively associated with weekend moderate-to-vigorous physical activity (p=0.034) but not weekday physical activity categories (p>0.05). When subdomains of skills were examined, object-control skills was positively associated with light physical activity on weekdays (p=0.008) and with light (p=0.033), moderate-to-vigorous (p=0.028) and light- and moderate-to-vigorous (p=0.008) physical activity at weekends. Locomotor skill competency was positively associated with moderate-to-vigorous physical activity on weekdays (p=0.016) and light physical activity during the weekend (p=0.035). CONCLUSIONS: The findings suggest that developing competence in both locomotor and object-control skills may be an important element in promoting an active lifestyle in young children during weekdays and at weekends

Proton radiography in background magnetic fields

Proton radiography has proved increasingly successful as a diagnostic for electric and magnetic fields in high-energy-density physics experiments. Most experiments use target-normal sheath acceleration sources with a wide energy range in the proton beam, since the velocity spread can help differentiate between electric and magnetic fields and provide time histories in a single shot. However, in magnetized plasma experiments with strong background fields, the broadband proton spectrum leads to velocity-spread-dependent displacement of the beam and significant blurring of the radiograph. We describe the origins of this blurring and show how it can be removed from experimental measurements, and we outline the conditions under which such deconvolutions are successful. As an example, we apply this method to a magnetized plasma experiment that used a background magnetic field of 3 T and in which the strong displacement and energy spread of the proton beam reduced the spatial resolution from tens of micrometers to a few millimeters. Application of the deconvolution procedure accurately recovers radiographs with resolutions better than 100 µm, enabling the recovery of more accurate estimates of the path-integrated magnetic field. This work extends accurate proton radiography to a class of experiments with significant background magnetic fields, particularly those experiments with an applied external magnetic field

Quantum Radiation Reaction in Laser-Electron-Beam Collisions

It is possible using current high intensity laser facilities to reach the quantum radiation reaction regime for energetic electrons. An experiment using a wakefield accelerator to drive GeV electrons into a counterpropagating laser pulse would demonstrate the increase in the yield of high energy photons caused by the stochastic nature of quantum synchrotron emission: we show that a beam of $10^9$ 1 GeV electrons colliding with a 30 fs laser pulse of intensity $10^{22}~\text{Wcm}^{-2}$ will emit 6300 photons with energy greater than 700 MeV, $60\times$ the number predicted by classical theory

A Data Science and Machine Learning Approach to Measure and Monitor Physical Activity in Children

Physical Activity is a fundamental component for the maintenance of a healthy lifestyle. Recommendations for physical activity levels are issued by most governments as part of public health measures. Therefore, it is vital for regulatory purposes, that there are reliable measurements of physical activity. However, the techniques and protocols used in existing physical activity research, including laboratory-based measurement, have received increasingly critical scrutiny in recent times. Consequently, physical activity researchers have begun to explore the use of wearable sensing technology to capture large amounts of data and the use of machine learning techniques, specifically artificial neural networks, to produce classifications for specific physical activity events. This paper explores this idea further and presents a supervised machine learning approach that utilises data obtained from accelerometer sensors worn by children in free-living environments. The paper posits a rigorous data science approach that presents a set of activities and features suitable for measuring physical activity in children in free-living environments. A Multilayer Perceptron neural network is used to classify physical activities by activity type, using ecologically valid data from body worn accelerometer sensors. A rigorous reproducible data science methodology is presented for subsequent use in physical activity research. Our results show that it was possible to obtain an overall accuracy of 92% using the initial data set, and 99.8% using interpolated cases