Alternative Metabolic Strategies are Employed by Endurance Runners of Different Body Sizes; Implications for Human Evolution

Objective A suite of adaptations facilitating endurance running (ER) evolved within the hominin lineage. This may have improved our ability to reach scavenging sites before competitors, or to hunt prey over long distances. Running economy (RE) is a key determinant of endurance running performance, and depends largely on the magnitude of force required to support body mass. However, numerous environmental factors influence body mass, thereby significantly affecting RE. This study tested the hypothesis that alternative metabolic strategies may have emerged to enable ER in individuals with larger body mass and poor RE. Methods A cohort of male (n = 25) and female (n = 19) ultra-endurance runners completed submaximal and exhaustive treadmill protocols to determine RE, and V̇O2Max. Results Body mass was positively associated with sub-maximal oxygen consumption at both LT1 (male r=0.66, p<0.001; female LT1 r=0.23, p=0.177) and LT2 (male r=0.59, p=0.001; female r=0.23, p=0.183) and also with V̇O2Max (male r=0.60, p=0.001; female r=0.41, p=0.046). Additionally, sub-maximal oxygen consumption varied positively with V̇O2Max in both male (LT1 r=0.54, p=0.003; LT2 r=0.77, p<0.001) and female athletes (LT1 r=0.88, p<0.001; LT2 r=0.92, p<0.001). Conclusions The results suggest that, while individuals with low mass and good RE can glide economically as they run, larger individuals can compensate for the negative effects their mass has on RE by increasing their capacity to consume oxygen. The elevated energy expenditure of this low-economy high-energy turnover approach to ER may bring costs associated with energy diversion away from other physiological processes, however.

The Impact of ACTN3 Gene Polymorphisms on Susceptibility to Exercise-Induced Muscle Damage and Changes in Running Economy Following Downhill Running

This study aimed to investigate if ACTN3 gene polymorphism impacts the susceptibility to exercise-induced muscle damage (EIMD) and changes in running economy (RE) following downhill running. Thirty-five healthy men were allocated to the two groups based on their ACTN3 gene variants: RR and X allele carriers. Neuromuscular function [knee extensor isometric peak torque (IPT), rate of torque development (RTD), and countermovement, and squat jump height], indirect markers of EIMD [muscle soreness, mid-thigh circumference, knee joint range of motion, and serum creatine kinase (CK) activity], and RE (oxygen uptake, minute ventilation, blood lactate concentration, and perceived exertion) for 5-min of running at a speed equivalent to 80% of individual maximal oxygen uptake speed were assessed before, immediately after, and 1–4 days after a 30-min downhill run (−15%). Neuromuscular function was compromised (P &lt; 0.05) following downhill running with no differences between the groups, except for IPT, which was more affected in the RR individuals compared with the X allele carriers immediately (−24.9 ± 6.9% vs. −16.3 ± 6.5%, respectively) and 4 days (−16.6 ± 14.9% vs. −4.2 ± 9.5%, respectively) post-downhill running. EIMD manifested similarly for both the groups except for serum CK activity, which was greater for RR (398 ± 120 and 452 ± 126 U L–1 at 2 and 4 days following downhill running, respectively) compared with the X allele carriers (273 ± 121 and 352 ± 114 U L–1 at the same time points). RE was compromised following downhill running (16.7 ± 8.3% and 11 ± 7.5% increases in oxygen uptake immediately following downhill running for the RR and X allele carriers, respectively) with no difference between the groups. We conclude that although RR individuals appear to be more susceptible to EIMD following downhill running, this does not extend to the changes in RE.

Runners Employ Different Strategies to Cope With Increased Speeds Based on Their Initial Strike Patterns

In this paper we examined how runners with different initial foot strike pattern (FSP) develop their pattern over increasing speeds. The foot strike index (FSI) of 47 runners [66% initially rearfoot strikers (RFS)] was measured in six speeds (2.5–5.0 ms−1), with the hypotheses that the FSI would increase (i.e., move toward the fore of the foot) in RFS strikers, but remain similar in mid- or forefoot strikers (MFS) runners. The majority of runners (77%) maintained their original FSP by increasing speed. However, we detected a significant (16.8%) decrease in the FSI in the MFS group as a function of running speed, showing changes in the running strategy, despite the absence of a shift from one FSP to another. Further, while both groups showed a decrease in contact times, we found a group by speed interaction (p &lt; 0.001) and specifically that this decrease was lower in the MFS group with increasing running speeds. This could have implications in the metabolic energy consumption for MFS-runners, typically measured at low speeds for the assessment of running economy.

Impact of Long-term Endurance Performance on Muscles Stiffness in Marathon Runners Over 50 Years Old

The aim of this research is to evaluate marathon performance and asses the influence of this long-distance running endurance exercise on the changes of muscle stiffness in recreational runners aged 50 + years. Thirty-one male long-distance runners aged 50–73 years participated in the experiment. The muscle stiffness of quadriceps and calves was measured in two independent sessions: the day before the marathon and 30 min after the completed marathon run using a Myoton device. The 42.195-km run was completed in 4.30,05 h ± 35.12 min, which indicates an intensity of 79.3% ± 7.1% of HRmax. The long-term, low-intensity running exercise (marathon) in older recreational runners, along with the low level of HRmax and VO2max showed no statistically significant changes in muscle stiffness (quadriceps and calves). There was reduced muscle stiffness, but only in the triceps of the calf in the dominant (left) leg. Moreover, in order to optimally evaluate the marathon and adequately prepare for the performance training programme, we need to consider the direct and indirect analyses of the running economy, running technique, and HRmax and VO2max and DOMS variables. These variables significantly affect the marathon exercise.

The Effect of Static and Dynamic Stretching during Warm-Up on Running Economy and Perception of Effort in Recreational Endurance Runners

This randomized crossover counterbalanced study investigated, in recreational runners, the acute effects of pre-exercise stretching on physiological and metabolic responses, endurance performance, and perception of effort. Eight male endurance runners (age 36 ± 11 years) performed three running-until-exhaustion tests, preceded by three warm-ups, including the following different stretching protocols: static (SS), dynamic (DS), and no-stretching (NS). During the SS and DS sessions, the warm-up consisted of 10 min of running plus 5 min of SS or DS, respectively, while during the NS session, the warm-up consisted of 15 min of running. Physiological and metabolic responses, and endurance running performance parameters, were evaluated. The perception of effort was derived from the rating of perceived exertion (RPE). Running economy significantly improved after SS (p < 0.05) and DS (p < 0.01), and RPE values were significantly lower in SS (p < 0.05) and DS (p < 0.01), compared to NS. No differences in physiological and metabolic responses among the sessions were found. This study showed that including SS and DS within the warm-up ameliorated running economy and decreased the perception of effort during a running-until-exhaustion test, highlighting the benefits of stretching on endurance performance. These results should encourage recreational runners to insert stretching during warm-up, to optimize the running energy costs, reducing the perception of effort and making the training sessions more enjoyable.

Exercise in Giraffes

Observation of giraffes reveal that they can run at very high speeds (~60 km h–1) for short periods (~5 minutes) but can also run at lower speeds (40 km h–1) for much longer periods. This combination of these two types of exercise capabilities is unusual. Their short periods of high speed running have the characteristics of anaerobic exercise. Analysis of the fiber types in their gastrocnemius muscle, and estimates of the available anaerobic energy sources support that conclusion. Longer periods depend on aerobic exercise and requires an adequate supply of oxygen to the lungs, adequate delivery of oxygen to muscles, and sufficient mitochondria to use oxygen. Despite the limitations of giraffe airway and lung anatomy the respiratory system of giraffes can supply sufficient oxygen. The volume of mitochondria in giraffe muscles far exceeds the volume required for maximum aerobic exercise. The cardiovascular system has evolved to generate high blood pressure rather than the circulation of high blood volumes, but if the maximum cardiac output is combined with an increase in the number of circulating erythrocytes, then oxygen delivery to muscles can match oxygen demand. Metabolic demand for oxygen can be reduced by an increase in running economy through storage of metabolic energy as elastic energy in tendons, and it is likely that because leg tendons of giraffes are long (~2 m) that the requirement for metabolic energy can be reduced by 30–40%.

Limitations of Foot-Worn Sensors for Assessing Running Power

Running power as measured by foot-worn sensors is considered to be associated with the metabolic cost of running. In this study, we show that running economy needs to be taken into account when deriving metabolic cost from accelerometer data. We administered an experiment in which 32 experienced participants (age = 28 ± 7 years, weekly running distance = 51 ± 24 km) ran at a constant speed with modified spatiotemporal gait characteristics (stride length, ground contact time, use of arms). We recorded both their metabolic costs of transportation, as well as running power, as measured by a Stryd sensor. Purposely varying the running style impacts the running economy and leads to significant differences in the metabolic cost of running (p < 0.01). At the same time, the expected rise in running power does not follow this change, and there is a significant difference in the relation between metabolic cost and power (p < 0.001). These results stand in contrast to the previously reported link between metabolic and mechanical running characteristics estimated by foot-worn sensors. This casts doubt on the feasibility of measuring running power in the field, as well as using it as a training signal.