Vertical jumping and leg power normative data for English school children aged 10–15 years

Taylor, Matthew J.; Cohen, Daniel D.; Voss, Christine; Sandercock, Gavin

doi:10.1080/02640411003770212

Cited by 70 publications

(94 citation statements)

References 22 publications

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“…The range of PJP values for our healthy control group was between 10.0 and 44.1 W/kg which compares closely with other studies that have looked separately at adults Dionyssiotis et al 2010) and children (Taylor et al 2010;Veilleux and Rauch 2010). In our healthy control group, values for maximum power (unadjusted for body mass) ranged from 210 to 3,402 W with lower values being found in children.…”

Section: Discussionsupporting

confidence: 73%

“…When an individual attempts a vertical jump, the combination of neuromuscular interactions and joint mechanics all contribute to the vertical height achieved which is the basis of peak jump power (PJP) (Bobbert and van Ingen Schenau 1988;Vanezis and Lees 2005). Studies in mobilitycompetent adults ) and children (Taylor et al 2010;Veilleux and Rauch 2010) have shown jump power to be highly reproducible and that declines in jump power are related to sarcopenia in aging adults (Buehring et al 2010). Here we present the first application of jump mechanography in a clinical setting as a quantitative measure of ambulatory ability in patients with neuromuscular, bone, and joint diseases.…”

Section: Introductionmentioning

confidence: 99%

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Peak Jump Power Reflects the Degree of Ambulatory Ability in Patients with Mitochondrial and Other Rare Diseases

et al. 2016

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Metabolic diseases that lead to neuromuscular, bone, and joint involvement can reduce ambulation and quality of life. Using jumping mechanography, we developed a novel assessment, peak jump power (PJP), and related this to ambulatory ability in patients either having a known or suspected underlying rare disease. From adults and children, we recruited 88 healthy controls and 115 patients (61 with mitochondrial disease and 54 with another diagnosis). Patients were categorized as having no complaints of weakness or ambulation (ambulatory competent; AC), weakness but able to ambulate without aids (ambulatory weakness; AW), or not able to ambulate without aids such as a walker, cane, or wheelchair (ambulatory assistance; AA). Subjects were asked to perform five successive jumps from a squat position. Instantaneous power (W; watts) was calculated and the highest result was divided by the body mass (kg) to calculate PJP (W/kg). Between healthy controls and AC patients, there was no difference in mean PJP (20.5 AE 7.0 W/kg vs. 19.0 AE 7.4 W/kg, p ¼ 0.601; mean AE SD). Progressively lower results were found in patients with AW with a mean PJP of 11.7 AE 5.1 W/kg (p < 0.001 versus AC) and further those with AA with a mean PJP of 5.8 AE 3.2 W/kg (p < 0.001 versus AW). A subgroup analysis of subjects showed that those who did not use ambulatory aids all had a PJP above 10 W/kg. Using this threshold, the receiver operating characteristic curve (ROC) analysis showed PJP to be highly sensitive evaluation of ambulatory ability (sensitivity 95.8%, specificity 52.1%). Abbreviations

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Section: Discussionsupporting

confidence: 73%

Section: Introductionmentioning

confidence: 99%

Peak Jump Power Reflects the Degree of Ambulatory Ability in Patients with Mitochondrial and Other Rare Diseases

et al. 2016

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“…If these criteria were not met, the jump was performed again. Two trials were given and the highest value recorded and expressed as a z-score (age-normalised jump height) based on UK reference data (30). Peak power was calculated from body mass and flight time (25), defined as the power exerted during the take-off phase of the jump.…”

Section: Methodsmentioning

confidence: 99%

“…Reference data for handgrip: Cohen et al (5). Reference data for vertical jump: Taylor et al (30) *indicates highest quartile mean value. Values in bold indicate significant difference in group mean compared with highest value.…”

Section: A C C E P T E D a C C E P T E Dmentioning

confidence: 99%

Quantification of the Relative Age Effect in Three Indices of Physical Performance

Sandercock

Taylor

Voss

et al. 2013

Journal of Strength and Conditioning Research

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Abstract.The relative age effect (RAE) describes the relationship between an individual's birth month and their level of attainment in sports. There is a clustering of birth dates just after the cut-off used for selection in age-grouped sports and it is hypothesised that such relatively older sportspeople may enjoy maturational and physical advantages over their younger peers. There is, however, little empirical evidence of any such advantage. This study investigated whether schoolchildren's physical performance differed according to which quarter of the school year they were born in.Mass, stature, BMI, cardiorespiratory fitness, strength and power were measured in n=8550 10-16 year olds (53% male). We expressed test performance as age-and sex-specific z-scores based on reference data with age rounded-down to the nearest whole year and also as units normalised for body mass. We then compared these values between yearly birth quarters There were no significant main effects for differences in anthropometric measures in either sex. Girls born in the first quarter of the school year were significantly stronger than those born at other times when handgrip was expressed as a z-score. As z-scores, all measures were significantly higher in boys born in either the first or second yearly quarters. Relative to body mass, cardiorespiratory fitness was higher in boys born in the first quarter and power higher in those born in the second quarter.The relative age effect does not appear to significantly affect girls' performance test scores when they are expressed as z-score or relative to body mass. Boys born in the first and second quarters of the year had a significant physical advantage over their relatively younger peers. These findings have practical bearing if coaches use fitness tests for talent identification and team selection. Categorising test performance based on rounded-down values of whole-year age may disadvantage children born later in the selection year. These relatively younger children may be less to gain selection for teams or training programmes.

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“…The vertical-jump test is a component of various batteries used to assess physical ability in adults and children (19), as the ability to generate power is a key element to success in a number of sports (6,8,11,12,21). It is also important in terms of occupational tasks and tasks of daily living (11) and useful in talent-identification programs (8); there is also emerging evidence that jumping performance may be related to overweight and obesity risk (2).…”

Section: Introductionmentioning

confidence: 99%

Peak-Power Estimation Equations in 12- to 16-Year-Old Children: Comparing Linear with Allometric Models

Duncan

Hankey

Nevill

2013

Pediatric Exercise Science

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This study examined the efficacy of peak-power estimation equations in children using force platform data and determined whether allometric modeling offers a sounder alternative to estimating peak power in pediatric samples. Ninety one boys and girls aged 12-16 years performed 3 countermovement jumps (CMJ) on a force platform. Estimated peak power (PP est ) was determined using the Harman et al., Sayers SJ, Sayers CMJ, and Canavan and Vescovi equations. All 4 equations were associated with actual peak power (r = 0.893-0.909, all p < .01). There were significant differences between PP est using the Harman et al., Sayers SJ, and Sayers CMJ equations (p < .05) and actual peak power (PP actual ). ANCOVA also indicated sex and age effect for PP actual (p < .01). Following a random two-thirds to one-third split of participants, an additive linear model (p = .0001) predicted PP actual (adjusted R 2 = .866) from body mass and CMJ height in the two-thirds split (n = 60). An allometric model using CMJ height, body mass, and age was then developed with this sample, which predicted 88.8% of the variance in PP actual (p < .0001, adjusted R 2 = .888) . The regression equations were cross-validated using the one-third split sample (n = 31), evidencing a significant positive relationship (r = .910, p = .001) and no significant difference (p = .151) between PP actual and PP est using this equation. The allometric and linear models determined from this study provide accurate models to estimate peak power in children.

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Vertical jumping and leg power normative data for English school children aged 10–15 years

Cited by 70 publications

References 22 publications

Peak Jump Power Reflects the Degree of Ambulatory Ability in Patients with Mitochondrial and Other Rare Diseases

Peak Jump Power Reflects the Degree of Ambulatory Ability in Patients with Mitochondrial and Other Rare Diseases

Quantification of the Relative Age Effect in Three Indices of Physical Performance

Peak-Power Estimation Equations in 12- to 16-Year-Old Children: Comparing Linear with Allometric Models

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