Cadence in youth long-distance runners is predicted by leg length and running speed

BACKGROUND

Lower cadence has been previously associated with injury in long-distance runners. Variations in cadence may be related to experience, speed, and anthropometric variables. It is unknown what factors, if any, predict cadence in healthy youth long-distance runners.

RESEARCH QUESTION

Are demographic, anthropometric and/or biomechanical variables able to predict cadence in healthy youth long-distance runners.

METHODS

A cohort of 138 uninjured youth long-distance runners (M = 62, F = 76; Mean ± SD; age = 13.7 ± 2.7; mass = 47.9 ± 13.6 kg; height = 157.9 ± 14.5 cm; running volume = 19.2 ± 20.6 km/wk; running experience: males = 3.5 ± 2.1 yrs, females = 3.3 ± 2.0 yrs) were recruited for the study. Multiple linear regression (MLR) models were developed for total sample and for each sex independently that only included variables that were significantly correlated to self-selected cadence. A variance inflation factor (VIF) assessed multicollinearity of variables. If VIF≥ 5, variable(s) were removed and the MLR analysis was conducted again.

RESULTS

For all models, VIF was > 5 between speed and normalized stride length, therefore we removed normalized stride length from all models. Only leg length and speed were significantly correlated (p < .001) with cadence in the regression models for total sample (R² = 51.9 %) and females (R² = 48.2 %). The regression model for all participants was Cadence = -1.251 *Leg Length + 3.665 *Speed + 254.858. The regression model for females was Cadence = -1.190 *Leg Length + 3.705 *Speed + 249.688. For males, leg length, cadence, and running experience were significantly predictive (p < .001) of cadence in the model (R² = 54.7 %). The regression model for males was Cadence = -1.268 *Leg Length + 3.471 *Speed - 1.087 *Running Experience + 261.378.

SIGNIFICANCE

Approximately 50 % of the variance in cadence was explained by the individual's leg length and running speed. Shorter leg lengths and faster running speeds were associated with higher cadence. For males, fewer years of running experience was associated with a higher cadence.

Sprint running: from fundamental mechanics to practice-a review

In this review, we examine the literature in light of the mechanical principles that govern linear accelerated running. While the scientific literature concerning sprint mechanics is comprehensive, these principles of fundamental mechanics present some pitfalls which can (and does) lead to misinterpretations of findings. Various models of sprint mechanics, most of which build on the spring-mass paradigm, are discussed with reference to both the insight they provide and their limitations. Although much research confirms that sprinters to some extent behave like a spring-mass system with regard to gross kinematics (step length, step rate, ground contact time, and lower limb deformation), the laws of motion, supported by empirical evidence, show that applying the spring-mass model for accelerated running has flaws. It is essential to appreciate that models are pre-set interpretations of reality; finding that a model describes the motor behaviour well is not proof of the mechanism behind the model. Recent efforts to relate sprinting mechanics to metabolic demands are promising, but have the same limitation of being model based. Furthermore, a large proportion of recent literature focuses on the interaction between total and horizontal (end-goal) force. We argue that this approach has limitations concerning fundamental sprinting mechanics. Moreover, power analysis based on isolated end-goal force is flawed. In closing, some prominent practical concepts and didactics in sprint running are discussed in light of the mechanical principles presented. Ultimately, whereas the basic principles of sprinting are relatively simple, the way an athlete manages the mechanical constraints and opportunities is far more complex.

Differential effects of speed on two-dimensional foot strike pattern during barefoot and shod running in recreationally active men

The majority of barefoot running studies have not considered speed as an influential factor on foot strike pattern. The aim of this study was to investigate differences in foot strike pattern and spatiotemporal characteristics between barefoot and shod overground running at varying speeds. We first determined maximal running speed (Vm) over 50 m in 15 recreationally active men who self-reported as habitual rearfoot strikers. Participants then completed shod and barefoot running trials at different speeds equivalent to approximately 90%, 80%, 70% and 60% of Vm. Sagittal plane two-dimensional (2D) foot-ground contact angle, ankle plantar-dorsi flexion angle, contact time, flight time, step length and step rate variables for each trial were recorded. A significant interaction effect of running speed and footwear condition (p < 0.05) on foot-ground contact angle, ankle plantar-dorsi flexion angle and contact time was observed. There was a main effect of running speed (p < 0.01) on flight time, step length and step rate. There was a main effect of footwear condition on step length (p < 0.01). Participants were more inclined to plantarflex the ankle and contact the ground with the forefoot at higher percentages of Vm, especially when running barefoot.

Eight weeks gait retraining in minimalist footwear has no effect on running economy

PURPOSE

To evaluate the effects of an eight week combined minimalist footwear (MFW) and gait-retraining intervention on running economy (RE) and kinematics in conventional footwear runners.

METHODS

Twenty-three trained male runners (age: 43 ± 10 years, stature: 177.2 ± 9.2 cm, body mass: 72.8 ± 10.2 kg, V̇O2max: 56.5 ± 7.0 mL min(-1) kg(-1)) were recruited. Participants were assigned to either an intervention group (n = 13) who gradually increased exposure to MFW and also implemented gait-retraining over an eight week period. RE and kinematics were measured in both MFW and conventional running shoes (CRS) at pre-tests and eight weeks, in a random order. In contrast the control group (n = 10) had no MFW exposure or gait retraining and were only tested in CRS.

RESULTS

The MFW and gait re-training intervention had no effect on RE (p < .001). However, RE was significantly better in MFW (mean difference 2.72%; p = .002) at both pre and post-tests compared to CRS. Step frequency increased as a result of the intervention (+5.7 steps per minute [spm]; p < .001), and was also significantly higher in MFW vs. CRS (+7.5 spm; p < .001).

CONCLUSION

Whilst a better RE in MFW was observed when compared to CRS due to shoe mass, familiarization to MFW with gait-retraining was not found to influence RE.