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Purpose: Our goal was to quantify if small (1%-3%) changes in running economy quantitatively affect distance-running performance. Based on the linear relationship between metabolic rate and running velocity and on earlier observations that added shoe mass increases metabolic rate by ~1% per 100 g per shoe, we hypothesized that adding 100 and 300 g per shoe would slow 3000-m time-trial performance by 1% and 3%, respectively. Methods: Eighteen male sub-20-min 5-km runners completed treadmill testing, and three 3000-m time trials wearing control shoes and identical shoes with 100 and 300 g of discreetly added mass. We measured rates of oxygen consumption and carbon dioxide production and calculated metabolic rates for the treadmill tests, and we recorded overall running time for the time trials. Results: Adding mass to the shoes significantly increased metabolic rate at 3.5 m⋅s-1 by 1.11% per 100 g per shoe (95% confidence interval = 0.88%-1.35%). While wearing the control shoes, participants ran the 3000-m time trial in 626.1 ± 55.6 s. Times averaged 0.65% ± 1.36% and 2.37% ± 2.09% slower for the +100-g and +300-g shoes, respectively (P < 0.001). On the basis of a linear fit of all the data, 3000-m time increased 0.78% per added 100 g per shoe (95% confidence interval = 0.52%-1.04%). Conclusion: Adding shoe mass predictably degrades running economy and slows 3000-m time-trial performance proportionally. Our data demonstrate that laboratory-based running economy measurements can accurately predict changes in distance-running race performance due to shoe modifications. [ABSTRACT FROM AUTHOR]

Purpose: Runners naturally adopt a stride frequency closely corresponding with the stride frequency that minimizes energy consumption. Although the concept of self-optimization is well recognized, we lack mechanistic insight into the association between stride frequency and energy consumption. Altering stride frequency affects lower extremity joint power; however, these alterations are different between joints, possibly with counteracting effects on the energy consumption during ground contact and swing. Here, we investigated the effects of changing stride frequency from a joint-level perspective. Methods: Seventeen experienced runners performed six running trials at five different stride frequencies (preferred stride frequency (PSF) twice, PSF ± 8%, PSF ± 15%) at 12 km⋅h-1. During each trial, we measured metabolic energy consumption and muscle activation, and collected kinematic and kinetic data, which allowed us to calculate average positive joint power using inverse dynamics. Results: With decreasing stride frequency, average positive ankle and knee power during ground contact increased (P < 0.01), whereas average positive hip power during leg swing decreased (P <0.01). Average soleus muscle activation during ground contact also decreased with increasing stride frequency (P < 0.01). In addition, the relative contribution of positive ankle power to the total positive joint power during ground contact decreased (P = 0.01) with decreasing stride frequency, whereas the relative contribution of the hip during the full stride increased (P < 0.01) with increasing stride frequency. Conclusions: Our results provide evidence for the hypothesis that the optimal stride frequency represents a trade-off between minimizing the energy consumption during ground contact, associated with higher stride frequencies, without excessively increasing the cost of leg swing or reducing the time available to produce the necessary forces. [ABSTRACT FROM AUTHOR]