In order to supplement the literature that describes individual injuries of the shoulder, carpal tunnel, and back in golfers, we administered a survey to demonstrate the incidence of golfers' injuries and describe the most frequent types. A questionnaire was administered to 1,790 members of the New York State Golf Association (amateur) under age 21. Three hundred sixty-eight players responded. Half of those responding had been struck by a golf ball at least on one occasion (47.6%), and 23% of the injuries were to the head or neck. Male golfers were 2.66 times more likely to be struck by a golf ball than females. Women and golfers with a higher handicap were at an increased risk for upper extremity problems, whereas younger and overweight golfers were more likely to have golf-related back problems. We concluded that golf is associated with a significant morbidity. Repetitious trunk and upper limb motions probably contribute to musculoskeletal disorders. However, an unexpectedly high incidence of trauma from projectile golf balls leads to the conclusion that no amount of stretching or muscular exercise is as important as increased alertness by golfers to decrease this hazard.
John J. Nicholas, Margaret Reidy, and Denise M. Oleske
John J. McMahon, Jason P. Lake, Nicholas J. Ripley, and Paul Comfort
The purpose of this study was to determine the usefulness of calculating jump take-off momentum in rugby league (RL) by exploring its relationship with sprint momentum, due to the latter being an important attribute of this sport. Twenty-five male RL players performed 3 maximal-effort countermovement jumps on a force platform and 3 maximal effort 20-m sprints (with split times recorded). Jump take-off momentum and sprint momentum (between 0 and 5, 5 and 10, and 10 and 20 m) were calculated (mass multiplied by velocity) and their relationship determined. There was a very large positive relationship between both jump take-off and 0- to 5-m sprint momentum (r = .781, P < .001) and jump take-off and 5- to 10-m sprint momentum (r = .878, P < .001). There was a nearly perfect positive relationship between jump take-off and 10- to 20-m sprint momentum (r = .920, P < .001). Jump take-off and sprint momentum demonstrated good–excellent reliability and very large–nearly perfect associations (61%–85% common variance) in an RL cohort, enabling prediction equations to be created. Thus, it may be practically useful to calculate jump take-off momentum as part of routine countermovement jump testing of RL players and other collision-sport athletes to enable the indirect monitoring of sprint momentum.
John McDaniel, N. Scott Behjani, Steven J. Elmer, Nicholas A.T. Brown, and James C. Martin
Previous authors have reported power-pedaling rate relationships for maximal cycling. However, the joint-specific power-pedaling rate relationships that contribute to pedal power have not been reported. We determined absolute and relative contributions of joint-specific powers to pedal power across a range of pedaling rates during maximal cycling. Ten cyclists performed maximal 3 s cycling trials at 60, 90, 120, 150, and 180 rpm. Joint-specific powers were averaged over complete pedal cycles, and extension and flexion actions. Effects of pedaling rate on relative joint-specific power, velocity, and excursion were assessed with regression analyses and repeated-measures ANOVA. Relative ankle plantar flexion power (25 to 8%; P = .01; R 2 = .90) decreased with increasing pedaling rate, whereas relative hip extension power (41 to 59%; P < .01; R 2 = .92) and knee flexion power (34 to 49%; P < .01; R 2 = .94) increased with increasing pedaling rate. Knee extension powers did not differ across pedaling rates. Ankle joint angular excursion decreased with increasing pedaling rate (48 to 20 deg) whereas hip joint excursion increased (42 to 48 deg). These results demonstrate that the often-reported quadratic power-pedaling rate relationship arises from combined effects of dissimilar joint-specific power-pedaling rate relationships. These dissimilar relationships are likely influenced by musculoskeletal constraints (ie, muscle architecture, morphology) and/or motor control strategies.
John H. Hollman, Nicholas J. Beise, Michelle L. Fischer, and Taylor L. Stecklein
Context: Examining the coordinated coupling of muscle recruitment patterns may provide insight into movement variability in sport-related tasks. Objective: The purpose of this study was to examine the relationship between coupled gluteus maximus and medius recruitment patterns and hip-adduction variability during single-limb step-downs. Design: Cross-sectional. Setting: Biomechanics laboratory. Participants: Forty healthy adults, including 26 women and 14 men, mean age 23.8 (1.6) years, mean body mass index 24.2 (3.1) kg/m2, participated. Interventions: Lower-extremity kinematics were acquired during 20 single-limb step-downs from a 19-cm step height. Electromyography (EMG) signals were captured with surface electrodes. Isometric hip-extension strength was obtained. Main Outcome Measures: Hip-adduction variability, measured as the SD of peak hip adduction across 20 repetitions of the step-down task, was measured. The mean amplitudes of gluteus maximus and gluteus medius EMG recruitment were examined. Determinism and entropy of the coupled EMG signals were computed with cross-recurrence quantification analyses. Results: Hip-adduction variability correlated inversely with determinism (r = −.453, P = .018) and positively with entropy (r = .409, P = .034) in coupled gluteus maximus/medius recruitment patterns but not with hip-extensor strength nor with magnitudes of mean gluteus maximus or medius recruitment (r = −.003, .081, and .035; P = .990, .688, and .864, respectively). Conclusion: Hip-adduction variability during single-limb step-downs correlated more strongly with measures of coupled gluteus maximus and medius recruitment patterns than with hip-extensor strength or magnitudes of muscle recruitment. Examining coupled recruitment patterns may provide an alternative understanding of the extent to which hip neuromuscular control modulates lower-extremity kinematics beyond examining muscle strength or EMG recruitment magnitudes.