94 research outputs found

    The Standard Error/Standard Deviation Mix-Up: Potential Impacts on Meta-Analyses in Sports Medicine.

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    Background A recent review found that 45% of meta-analyses included statistical errors, of which, the most common was the calculation of effect sizes based on standard error (SE) rather than standard deviation (SD) [the SE/SD mix-up]. Objectives The first aim of this study was to assess the impact of the SE/SD mix-up on the results of one highly cited meta-analysis. Our second aim was to identify one potential source of the SE/SD mix-up, by assessing how often SE is reported as a measure of sample variability in randomised controlled trials in sports medicine. Methods We checked for potential SE/SD mix-ups in a 2015 meta-analysis of randomised controlled trials reporting the effects of recreational football interventions on aerobic fitness in adults. We corrected effect sizes affected by SE/SD mix-ups and re-analysed the data according to the original methodology. We compared pooled estimates of effect sizes from our re-analysis of corrected values with those of the original study. To assess how often SE was reported instead of SD as a measure of sample variance, we text mined results of randomised controlled trials from seven sports medicine journals and reported the proportion reporting of SE versus SD. Results We identified potential SE/SD mix-ups in 9/16 effect sizes included in the meta-analysis describing the effects of football-based interventions versus non-exercise control. The published effect size was standardised mean difference (SMD) = 1.46 (95% confidence interval [CI] 0.91, 2.01). After correcting for SE/SD mix-ups, our re-analysis produced a smaller pooled estimate (SMD = 0.54 [95% CI 0.37, 0.71]). The original pooled estimate for trials comparing football versus running interventions was SMD = 0.68 (95% CI 0.06, 1.4). After correcting for SE/SD mix-ups and re-analysis, the effect was no longer statistically significant (SMD = 0.20 [95% CI - 0.10, 0.49)]). We found that 19.3% of randomised controlled trials reported SE rather than SD to describe sample variability. The relative frequency of the practice ranged from 0 to 25% across the seven journals sampled Conclusions We found the SE/SD mix-up had inflated estimates for the effects of football on aerobic fitness. Meta-analysts should be vigilant to avoid miscalculating effect sizes. Authors, reviewers and editors should avoid and discourage (respectively) the practice of reporting SE as a measure of sample variability in sports medicine research

    Cross-cultural comparisons of aerobic and muscular fitness in Tanzanian and English youth: An allometric approach

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    Comparisons of physical fitness measures between children or within group measures over time are potentially confounded by differences in body size. We compared measures of strength (handgrip) and aerobic fitness (running-speed [20m shuttle-run]) of 10.0–15.9 year-olds from Dar es Salaam, Tanzania (n = 977) with schoolchildren from England (n = 1014) matched for age and sex. Differences in fitness were analyzed using general linear models, with allometric scaling for body size (mass and stature) and further adjustments for physical activity. Mean handgrip of Tanzanians was lower than English youth (F = 165.0, P<0.001, ηp2 = .079). The difference became trivial when run-speed was scaled for body size (ηp2 = .008). Running-speed of the English children was higher than in Tanzanians (F = 16.0, P<0.001, ηp2 = .014). Allometric scaling for accentuated this between-county difference in running-speed (ηp2 = .019) but when adjusted for physical activity between-country differences in running-speed were trivial (ηp2 = .008). These data contradict those studies showing poor muscular fitness in African youth and highlight the need for appropriate scaling techniques to avoid confounding by differences in body size. In contrast to those from rural areas, our sample of contemporary urban Tanzanians were less aerobically fit than European youth. Differences were independent of body size. Lower aerobic fitness of urban Tanzanian youth may be due to reported physical activity levels lower than those of English youth and lower still than previously reported in rural Tanzania

    Contribution of Physical Education to the Daily Physical Activity of Schoolchildren in Saudi Arabia

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    The positive contribution of physical education (PE) to daily physical activity (PA) has been documented in past studies. However, little is known about the contribution of PE to inactive and unfit schoolchildren’s PA. Therefore, the purpose of the present study was to examine the contribution of PE to the daily PA of schoolchildren, especially for inactive and unfit schoolchildren. Accelerometers were used to measure the PA of 111 boys (Mage = 13.6 0.8 years) across 7 days. Moderate-to-vigorous PA (MVPA) was measured during PE classes and on school days with and without PE classes. To measure the time that schoolchildren spent on MVPA, the accelerometer count (i.e., 2296 counts/minute) was used. Schoolchildren spent 22% of PE class time in MVPA. Times spent in MVPA were 12.9, 14.7 and 14.8 minutes higher on PE days than on days without PE for all, inactive, and unfit schoolchildren, respectively. Results showed that 40% percent and 24% of the schoolchildren met the recommended levels of PA on PE days and days without PE, respectively. It is concluded that, since PE classes increase daily engagement in MVPA, especially among inactive and unfit schoolchildren, PE classes should be conducted on all school days

    Maturational and social factors contributing to relative age effects in school sports: Data from the London Youth Games

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    Few studies have investigated whether relative age effects (RAEs) exist in school sport. None have sought to test the competing maturational and social‐agent hypotheses proposed to explain the RAE. We aimed to determine the presence of RAEs in multiple school sports and examine the contribution of maturational and social factors in commonplace school sports. We analyzed birth dates of n=10645 competitors (11‐18 years) in the 2013 London Youth Games annual inter‐school multisport competition and calculated odds ratio (OR) for students competing based on their yearly birth quarter (Q1‐Q4). Multivariate logistic regression was used to determine the relative contribution of constituent year (Grade) and relative age in netball and football which used multiyear age groupings. In girls, RAEs were present in the team sports including hockey, netball, rugby union, cricket and volleyball but not football. In boys, RAEs were stronger in common team sports (football, basketball cricket) as well as athletics and rowing. In netball and football teams with players from two constituent years, birth quarter better‐predicted selection than did constituent year. Relatively older players (Q1) from lower constituent years were overrepresented compared with players from Q3 and Q4 of the upper constituent years. RAEs are present in the many sports commonplace in English schools. Selection of relatively older players ahead of chronologically older students born later in the selection year suggests social agents contribute to RAEs in school sports

    Temporal trends in muscular fitness of English 10-year-olds 1998-2014: an allometric approach

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    Objectives To identify temporal trends in muscular fitness of English children using allometric scaling for height and weight to adjust for the influence of body size. Design Repeated cross-sectional study. Methods We measured; height, weight, standing broad-jump, handgrip, sit-ups and bent-arm hang in 10-year-old boys and girls from Chelmsford, England in: 2014 (n = 306), 2008 (n = 304) and 1998 (n = 310). Physical activity was (PAQ-C) was assessed in 2008 and 2014. Muscular fitness was allometrically scaled for height and weight. We assessed temporal trends using General Linear Models (fixed factors: wave and sex) and reported effect sizes using partial eta squared (ηP²). We compared percentage change per year 1998-2008 with 2008-2014. Results Ten-year-olds in 2014 were taller and heavier than in 2008 and 1998 but there were no differences in BMI. Compared with 2008, physical activity was lower in boys (ηP² = 0.012) and girls (ηP² = 0.27) assessed in 2014. There were significant main effects of wave for handgrip (ηP² = 0.060), sit-ups (ηP² = 0.120) and bent-arm hang (ηP² = 0.204). Pairwise comparisons showed muscular fitness of both sexes was significantly lower in 2014 than in 1998. From 2008 to 2014 percent change per year in handgrip (1.6%) and sit-ups (3.9%) were greater than for the preceding decade (handgrip 0.6%, sit-ups 2.6%). Conclusions Downward temporal trends in muscular fitness appear independent of secular changes in body size. We found a decrease in self-reported physical activity concurrent with the accelerated declines in fitness from 2008 to 2014. These findings suggest the declines in children are not engaging in physical activities which support development of muscular fitness

    The influence of compression tights on running economy varies by relative intensity

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    The effect of compression tights on running economy is unclear. The purpose of this investigation was to assess the influence of compression tights on economy. Following an incremental test to exhaustion to determine aerobic capacity (V̇O2max) and peak running speed (vV̇O2max), twenty-six moderately endurance-trained males (28 ± 7 years; 76.1 ± 8.4 kg; V̇O2max = 54.7 ± 4.8 mL·kg−1·min−1) were allocated to either a 60% (n = 8), 62.5% (n = 9) or 65% vV̇O2max group (n = 9) using block randomisation. Participants ran for 15 min at the allocated vV̇O2max with compression tights and a non-compression control condition in a randomised, counter-balanced order, separated by seven days. Oxygen consumption (V̇O2) and expired carbon dioxide (V̇CO2) was measured to determine economy as caloric unit cost. No difference was observed between conditions for the 60% and 62.5% vV̇O2max groups, however economy was improved with compression at 65% vV̇O2max ( P &lt; 0.01). Combined analysis of all participants revealed ΔRE (Δ = control − compression) correlated with relative aerobic capacity (%V̇O2max) ( r = 0.50, P &lt; 0.01) but not running speed ( r = 0.04, P &lt; 0.84). These data suggest that compression tights influence economy at 65% vV̇O2max or at relative exercise intensities of approximately 75–85%V̇O2max. </jats:p

    Who is meeting the strengthening physical activity guidelines by definition: A cross-sectional study of 253 423 English adults?

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    The current UK physical activity guidelines recommend that adults aged 19 to 65 years perform activity to strengthen muscle and bone a minimum of twice weekly. The number of adults meeting strengthening activity guidelines is lower than for aerobic activity, but estimates vary between studies partly due to differences in how muscle-strengthening activity is defined. We aimed to provide estimates for strengthening activity prevalence in English adults based on a nationally representative sample of n = 253,423 18-65-year-olds. We attempted to quantify the variation in estimates attributable to differences in the way strengthening activity is defined. Finally, we aim to provide a brief descriptive epidemiology of the factors associated with strengthening activity. Adults met guidelines for aerobic activity if they reported the activity equivalent to &gt;150 min/week moderate-intensity exercise. Respondents met strengthening guidelines if they reported at least two bouts per week of strengthening activity. We defined strengthening activity, first, according to criteria used in the Health Survey for England (HSE). Second, we counted bouts of strengthening activities for which we could find evidence of health-related benefits (Evidence). Third, we included bouts of strengthening activity as defined in current UK physical activity guidelines (Guideline). Two-thirds (67%) of adults met guidelines for aerobic activity (69% of men, 65% of women). Less than one-third (29% of men and 24% of women) met guidelines for the HSE definition of strengthening activity. Under the Evidence definition, 16% of men and 9% of women met strengthening guidelines. Using the most-stringent definition (Guideline) just 7.3% of men and 4.1% of women achieved the recommendations for strengthening activity. We found females and older adults (50–65 years) were less likely to meet guidelines for aerobic, strengthening, and combined aerobic plus strengthening activity. The prevalence of meeting activity guidelines was lower in adults from more deprived areas (compared with the least deprived); Adults with lower academic qualifications (Level 1) were less likely to meet activity guidelines than those educated to Level 4 (Degree Level) or higher. Having a limiting disability was associated with a lower prevalence of meeting activity guidelines. Associations between socio-demographic measures and the prevalence of adults meeting activity guidelines were stronger for strengthening activity than for aerobic 51(or combined aerobic plus strengthening) activity Compared with aerobic activity, fewer adults engage in strengthening activity regardless of how it is defined. The range in estimates for how many adults meet strengthening activity guidelines can be explained by variations in the definition of ‘strengthening’ that are used and the specific sports or activities identified as strengthening exercise. When strengthening activity is included, the proportion of English adults meeting current physical activity guidelines could be as high as 1 in 3 but possibly as low as just 1 in 20. A harmonized definition of strengthening activity, that is aligned with physical activity guidelines, is required to provide realistic and comparable prevalence estimates
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