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

Abstract

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.

Peak Vertical Jump Power as a Marker of Bone Health in Children

“…The jumps were performed on a contact mat and the measured flight time was used to calculate the height of rise of the center of gravity (cm). An equation to estimate jump power from the same jump technique (countermovement jump without swinging the arms) in a pediatric sample comprising non-athletes was identified in the literature [8]. The equation was derived using a force platform to determine vertical-jump height and peak power from the same jump and was controlled for gender differences.…”

“…The equation was derived using a force platform to determine vertical-jump height and peak power from the same jump and was controlled for gender differences. The equation also controls for age differences and use allometric scaling (instead of a linear additive model) to normalize for body size [8]:…”

“…Peak power (watts), boys = 3.717 × 1.108 × exp (0.054 × age) × body mass 0.829 × CMJ height 0.636 Peak power (watts), girls = 3.717 × exp (0.054 × age) × body mass 0.829 × CMJ height 0.636 CMJ, countermovement jump; height in cm; body mass in kg. Cross-validation was conducted in a subsample of 31 adolescents (total sample: 91 adolescents aged 12-16 years) with no significant difference between actual and the predicted peak power (mean ± SD of peak power was 2 539.4 ± 868.6 W and 2 459.8 ± 832.8 W for actual and predicted peak power respectively; adjusted R 2 = 0.888 for the variance of the actual peak power explained by the predicted peak power) [8].…”

“…The vertical jump test can be performed in laboratory settings using a force platform to measure peak and average power (watts). In field settings, prediction equations are used to estimate peak jump power from jump height and body mass in pediatric ages [1,8,24,27]. The ease and accuracy of field-based assessment support the use of the vertical jump test for mass testing programs.…”

Vertical Jump Test as a Health-Promotion Screening Tool for Predicting Bone Strength in Young Adults

“…Jump height was then used to estimate peak vertical jump power using the equation published by Duncan et al (2013). While the International Society for Clinical Densitometry defines "below the expected range for age" to be an areal BMD Z-score of -2.0 or lower, "below average" BMD was defined in this study as a WBLH BMD Z-score of < -1.0 SD due to the small sample size, and due to the fact that a more conservative cutoff value is often preferable for screening tests, as early detection is the goal of such tools.…”