A Cross sectional study design.
All of the participants were recruited from a local school in Oxfordshire. Ethical approval granted by Oxford Brookes University Ethical Advisory Committee. Permission was gained from each school’s head teachers to recruit participants, and opt-out consent was collected from each participant’s parent or legal guardian.
Anthropometric measures were taken which included height (measured using a portable stadiometer, Seca UK), waist circumference (measured mid-way between the lower rib margin and the iliac crest using anthropometry tape), and body weight and composition (measured using a Tanita Body Composition Analyser, model: BC–418 MA, Tanita, UK).
Cardiorespiratory fitness measure
Shuttle run test used for the cardiorespiratory fitness evaluation. Total of 119 participants completed shuttle run test which according to the FITNESSGRAM (PACER), the test consists in running back and forth between two lines 20 meters apart, with running speed determined by audio signals from a pre-recorded music CD.15 The running speed increases at the end of each one-minute stage. The running speed is 8.0 km.h–1 for the first stage, 9.0 km.h–1 for the second stage, and thereafter increases by 0.5 km.h–1 each minute. The test ends when the subjects twice fail to reach the lines at the time indicated by the audio signals, demonstrating an inability to keep the required pace.15
All the participants wore a wrist-band accelerometer during whole shuttle run test. AX3 accelerometer was attached, using a watch strap positioned on the dorsal aspect of participants’ non-dominant hand. The AX3 (axivity, UK) which was used in this study as a measuring device is a continuous logging accelerometer that has been designed to monitor physical activity intensity and duration. It is a triaxial, ±16g acceleration sensor housed in a small (23 x 32.5 x 7.6 mm), light weight (11 g) and encased splash-proof. The sampling frequency of the AX3 ranges from 12.5 Hz to 3200 Hz and the battery can last up to 14 days when recording data at 100 Hz.
Data processing and statistical analyses
There are several methods and equations to estimate VO2max during SR test in adolescents.22One of these methods is Multiple Linear Regression (MLR) model which is a stepwise method.23–26Another method is Artificial Neural Networks (ANN) models which has been validated by Ruiz et al in (2008 and 2009) for VO2max assessment in adolescents.27, 28 Also this method is widely being used in different studies.26, 29–32
Raw 100 Hz triaxial Ax3 data was analysed in a bespoke LabVIEW programme (National Instruments, Newbury, UK) in accordance with the manufacturers analytics (Open movement V22.214.171.124). Below equation used to calculate the signal vector magnitude (gravity-subtracted) (SVMgs), in 1s epochs.33 According to Esliger et al (2011) the unit of the following equation result would be gs.34
[Due to technical limitations the formula could not be displayed here. Please see the supplementary files section to access the formula.]
In addition, a bespoke programme was used to calculated the estimated VO2max for each participant using three different methodologies considering participants’ sex, age, height, weight, body mass index (BMI) and Pacer laps according to Mahar et al 201122, Multiple Linear Regression (MLR) 23–26 and using artificial neural networking (ANN) methodologies27, 28
To achieve the MET values associated with each level of shuttle run, VO2 values were converted to METs using age specific values.The MET values were calculated using the standardized MET formula for adolescents:
1 MET = 5.92 ml kg –1 min–1 (8–12 boys/8–11 girls) and 4.85 ml kg –1 min–1 (13–15 boys/12–14 girls).35
The Shapiro-Wilk test confirmed that all data were normally distributed. Also SVMgs average calculated for each shuttle run level and compared between genders using univariate variance test. In the event of a significant ANOVA result, Bonferroni -corrected post hoc comparisons were undertaken to determine where the significant differences occurred. Differences between the BMI groups were tested using independent t-tests. P < 0.05 was considered significant and all tests were 2-sided. All statistical analyses were performed using SPSS version 25 (IBM SPSS Statistics). Data are displayed as mean (± SD) and mean (95 % CI) in the text and tables.