Introduction. Wrist (Colles') and forearm fractures commonly occur when a person falls on the outstretched forearm and the force exceeds bone strength. There is lack of experimental evidence testing the available force prediction models and assessing factors that determine forearm forces during a fall.<p> Objective. The primary objective was to compare experimentally measured force peaks (F1max-E and F2max-E) to the force peaks that were predicted by an engineering based force prediction model (F1max-M and F2max-M), at heights greater than 5cm. The second objective was to describe the relationships between the experimentally measured peak forces and forearm bone and muscle strength properties, body mass, and stature as a function of fall height.<p> Methods. Using 3D motion tracking, we assessed the first (F1max) and second (F2max) peak forces from 10 young adults (5 male; 5 female) who volunteered to fall from heights up to 25cm onto a foam covered force plate. Peripheral QCT was used to determine the bone strength index (BSIc), strength-strain index (SSIp), and muscle cross sectional area (MCSA) of each participant. Two 2x8 between-within factorial ANOVAs determined the difference between the experimental and model force peaks, with post hoc analyses at all fall heights. Pearson's correlation was used to determine the relationship between the pQCT-derived bone and muscle strength indices and the force peaks.<p> Results. There was no significant differences between F1max-E and F1max-M across all fall heights, but the model significantly over-predicted the F2max-E across all fall heights. After controlling F1max-E and F2max-E for body mass, the force peaks appeared to be weakly related to the anthropometric as well as bone and muscle strength outcomes (r=0.2-0.7, p>0.05). The relationship between bone and muscle strength outcomes appeared to have a tendency to get stronger at higher fall heights.<p> Conclusion. The model predicted experimental F1max, but not experimental F2max. This study presents preliminary pilot results. Larger sample size is needed to confirm whether incorporating bone and muscle strength estimates into fall force prediction models could enhance forearm fracture risk assessments.

Introduction. Wrist (Colles') and forearm fractures commonly occur when a person falls on the outstretched forearm and the force exceeds bone strength. There is lack of experimental evidence testing the available force prediction models and assessing factors that determine forearm forces during a fall.<p> Objective. The primary objective was to compare experimentally measured force peaks (F1max-E and F2max-E) to the force peaks that were predicted by an engineering based force prediction model (F1max-M and F2max-M), at heights greater than 5cm. The second objective was to describe the relationships between the experimentally measured peak forces and forearm bone and muscle strength properties, body mass, and stature as a function of fall height.<p> Methods. Using 3D motion tracking, we assessed the first (F1max) and second (F2max) peak forces from 10 young adults (5 male; 5 female) who volunteered to fall from heights up to 25cm onto a foam covered force plate. Peripheral QCT was used to determine the bone strength index (BSIc), strength-strain index (SSIp), and muscle cross sectional area (MCSA) of each participant. Two 2x8 between-within factorial ANOVAs determined the difference between the experimental and model force peaks, with post hoc analyses at all fall heights. Pearson's correlation was used to determine the relationship between the pQCT-derived bone and muscle strength indices and the force peaks.<p> Results. There was no significant differences between F1max-E and F1max-M across all fall heights, but the model significantly over-predicted the F2max-E across all fall heights. After controlling F1max-E and F2max-E for body mass, the force peaks appeared to be weakly related to the anthropometric as well as bone and muscle strength outcomes (r=0.2-0.7, p>0.05). The relationship between bone and muscle strength outcomes appeared to have a tendency to get stronger at higher fall heights.<p> Conclusion. The model predicted experimental F1max, but not experimental F2max. This study presents preliminary pilot results. Larger sample size is needed to confirm whether incorporating bone and muscle strength estimates into fall force prediction models could enhance forearm fracture risk assessments.

Purpose: To determine if jumping-performance changes during a peaking phase differed among returners and new players on a female collegiate volleyball team and to determine which variables best explained the variation in performance changes. Methods: Fourteen volleyball players were divided into 2 groups—returners (n = 7) and new players (n = 7)—who completed a 5-wk peaking phase prior to conference championships. Players were tested at baseline before the preseason on measures of the vastus lateralis cross-sectional area using ultrasonography, estimated back-squat 1-repetition maximum, countermovement jump height (JH), and relative peak power on a force platform. Jumping performance, rating of perceived exertion training load, and sets played were recorded weekly during the peaking phase. Results: There were moderate to very large (P < .01, Glass Δ = 1.74) and trivial to very large (P = .07, Δ = 1.09) differences in JH and relative peak power changes in favor of returners over new players, respectively, during the peaking phase. Irrespective of group, 7 of 14 players achieved peak JH 2 wk after the initial overreach. The number of sets played (r = .78, P < .01) and the athlete’s preseason relative 1-repetition maximum (r = .54, P = .05) were the strongest correlates of JH changes during the peaking phase. Conclusions: Returners achieved greater improvements in jumping performance during the peaking phase compared with new players, which may be explained by the returners’ greater relative maximal strength, time spent competing, and training experience. Thus, volleyball and strength coaches should consider these factors when prescribing training during a peaking phase to ensure their players are prepared for important competitions.