Not Lower-Limb Joint Strength and Stiffness but Vertical Stiffness and Isometric Force-Time Characteristics Correlate With Running Economy in Recreational Male Runners

The Effect of Strength Training Methods on Middle-Distance and Long-Distance Runners' Athletic Performance: A Systematic Review with Meta-analysis

BACKGROUND

The running performance of middle-distance and long-distance runners is determined by factors such as maximal oxygen uptake (VO2max), velocity at VO2max (vVO2max), maximum metabolic steady state (MMSS), running economy, and sprint capacity. Strength training is a proven strategy for improving running performance in endurance runners. However, the effects of different strength training methods on the determinants of running performance are unclear.

OBJECTIVE

The aim of this systematic review with meta-analysis was to compare the effect of different strength training methods (e.g., high load, submaximal load, plyometric, combined) on performance (i.e., time trial and time until exhaustion) and its determinants (i.e., VO2max, vVO2max, MMSS, sprint capacity) in middle-distance and long-distance runners.

METHODS

A systematic search was conducted across electronic databases (Web of Science, PubMed, SPORTDiscus, SCOPUS). The search included articles indexed up to November 2022, using various keywords combined with Boolean operators. The eligibility criteria were: (1) middle- and long-distance runners, without restriction on sex or training/competitive level; (2) application of a strength training method for ≥ 3 weeks, including high load training (≥ 80% of one repetition maximum), submaximal load training (40-79% of one repetition maximum), plyometric training, and combined training (i.e., two or more methods); (3) endurance running training control group under no strength training or under strength training with low loads (< 40% of one repetition maximum); (4) running performance, VO2max, vVO2max, MMSS and/or sprint capacity measured before and after a strength training intervention program; (5) randomized and non-randomized controlled studies. The certainty of evidence was assessed using the GRADE (Grading of Recommendations Assessment, Development and Evaluation) approach. A random-effects meta-analysis and moderator analysis were performed using Comprehensive meta-analysis (version 3.3.0.70).

RESULTS

The certainty of the evidence was very low to moderate. The studies included 324 moderately trained, 272 well trained, and 298 highly trained athletes. The strength training programs were between 6 and 40 weeks duration, with one to four intervention sessions per week. High load and combined training methods induced moderate (effect size =  - 0.469, p = 0.029) and large effect (effect size =  - 1.035, p = 0.036) on running performance, respectively. While plyometric training was not found to have a significant effect (effect size =  - 0.210, p = 0.064). None of the training methods improved VO2max, vVO2max, MMSS, or sprint capacity (all p > 0.072). Moderators related to subject (i.e., sex, age, body mass, height, VO2max, performance level, and strength training experience) and intervention (i.e., weeks, sessions per week and total sessions) characteristics had no effect on running performance variables or its determinants (all p > 0.166).

CONCLUSIONS

Strength training with high loads can improve performance (i.e., time trial, time to exhaustion) in middle-distance and long-distance runners. A greater improvement may be obtained when two or more strength training methods (i.e., high load training, submaximal load training and/or plyometric training) are combined, although with trivial effects on VO2max, vVO2max, MMSS, or sprint capacity.

The Relationship Between Running Biomechanics and Running Economy: A Systematic Review and Meta-Analysis of Observational Studies

BACKGROUND

Running biomechanics is considered an important determinant of running economy (RE). However, studies examining associations between running biomechanics and RE report inconsistent findings.

OBJECTIVE

The aim of this systematic review was to determine associations between running biomechanics and RE and explore potential causes of inconsistency.

METHODS

Three databases were searched and monitored up to April 2023. Observational studies were included if they (i) examined associations between running biomechanics and RE, or (ii) compared running biomechanics between groups differing in RE, or (iii) compared RE between groups differing in running biomechanics during level, constant-speed, and submaximal running in healthy humans (18-65 years). Risk of bias was assessed using a modified tool for observational studies and considered in the results interpretation using GRADE. Meta-analyses were performed when two or more studies reported on the same outcome. Meta-regressions were used to explore heterogeneity with speed, coefficient of variation of height, mass, and age as continuous outcomes, and standardization of running shoes, oxygen versus energetic cost, and correction for resting oxygen or energy cost as categorical outcomes.

RESULTS

Fifty-one studies (n = 1115 participants) were included. Most spatiotemporal outcomes showed trivial and non-significant associations with RE: contact time r = - 0.02 (95% confidence interval [CI] - 0.15 to 0.12); flight time r = 0.11 (- 0.09 to 0.32); stride time r = 0.01 (- 0.8 to 0.50); duty factor r = - 0.06 (- 0.18 to 0.06); stride length r = 0.12 (- 0.15 to 0.38), and swing time r = 0.12 (- 0.13 to 0.36). A higher cadence showed a small significant association with a lower oxygen/energy cost (r = - 0.20 [- 0.35 to - 0.05]). A smaller vertical displacement and higher vertical and leg stiffness showed significant moderate associations with lower oxygen/energy cost (r = 0.35, - 0.31, - 0.28, respectively). Ankle, knee, and hip angles at initial contact, midstance or toe-off as well as their range of motion, peak vertical ground reaction force, mechanical work variables, and electromyographic activation were not significantly associated with RE, although potentially relevant trends were observed for some outcomes.

CONCLUSIONS

Running biomechanics can explain 4-12% of the between-individual variation in RE when considered in isolation, with this magnitude potentially increasing when combining different variables. Implications for athletes, coaches, wearable technology, and researchers are discussed in the review.

PROTOCOL REGISTRATION

https://doi.org/10.17605/OSF.IO/293 ND (OpenScience Framework).

Effect of Strength Training Programs in Middle- and Long-Distance Runners' Economy at Different Running Speeds: A Systematic Review with Meta-analysis

BACKGROUND

Running economy is defined as the energy demand at submaximal running speed, a key determinant of overall running performance. Strength training can improve running economy, although the magnitude of its effect may depend on factors such as the strength training method and the speed at which running economy is assessed.

AIM

To compare the effect of different strength training methods (e.g., high loads, plyometric, combined methods) on the running economy in middle- and long-distance runners, over different running speeds, through a systematic review with meta-analysis.

METHODS

A systematic search was conducted across several electronic databases including Web of Science, PubMed, SPORTDiscus, and SCOPUS. Using different keywords and Boolean operators for the search, all articles indexed up to November 2022 were considered for inclusion. In addition, the PICOS criteria were applied: Population: middle- and long-distance runners, without restriction on sex or training/competitive level; Intervention: application of a strength training method for ≥ 3 weeks (i.e., high loads (≥ 80% of one repetition maximum); submaximal loads [40-79% of one repetition maximum); plyometric; isometric; combined methods (i.e., two or more methods); Comparator: control group that performed endurance running training but did not receive strength training or received it with low loads (< 40% of one repetition maximum); Outcome: running economy, measured before and after a strength training intervention programme; Study design: randomized and non-randomized controlled studies. Certainty of evidence was assessed with the GRADE approach. A three-level random-effects meta-analysis and moderator analysis were performed using R software (version 4.2.1).

RESULTS

The certainty of the evidence was found to be moderate for high load training, submaximal load training, plyometric training and isometric training methods and low for combined methods. The studies included 195 moderately trained, 272 well trained, and 185 highly trained athletes. The strength training programmes were between 6 and 24 weeks' duration, with one to four sessions executed per week. The high load and combined methods induced small (ES = - 0.266, p = 0.039) and moderate (ES = - 0.426, p = 0.018) improvements in running economy at speeds from 8.64 to 17.85 km/h and 10.00 to 14.45 km/h, respectively. Plyometric training improved running economy at speeds ≤ 12.00 km/h (small effect, ES = - 0.307, p = 0.028, β1 = 0.470, p = 0.017). Compared to control groups, no improvement in running economy (assessed speed: 10.00 to 15.28 and 9.75 to 16.00 km/h, respectively) was noted after either submaximal or isometric strength training (all, p > 0.131). The moderator analyses showed that running speed (β1 = - 0.117, p = 0.027) and VO2max (β1 = - 0.040, p = 0.020) modulated the effect of high load strength training on running economy (i.e., greater improvements at higher speeds and higher VO2max).

CONCLUSIONS

Compared to a control condition, strength training with high loads, plyometric training, and a combination of strength training methods may improve running economy in middle- and long-distance runners. Other methods such as submaximal load training and isometric strength training seem less effective to improve running economy in this population. Of note, the data derived from this systematic review suggest that although both high load training and plyometric training may improve running economy, plyometric training might be effective at lower speeds (i.e., ≤ 12.00 km/h) and high load strength training might be particularly effective in improving running economy (i) in athletes with a high VO2max, and (ii) at high running speeds.

PROTOCOL REGISTRATION

The original protocol was registered ( https://osf.io/gyeku ) at the Open Science Framework.

Foot and Ankle Muscle Isometric Strength in Nonrearfoot Compared With Rearfoot Endurance Runners

Background

Transitioning to a forefoot strike pattern can be used to manage running-related knee injuries. However, adopting a nonrearfoot strike induces a higher load on foot and ankle structures than rearfoot strike. Sufficient foot muscle strength is also necessary to prevent excessive longitudinal arch (LA) deformation when running with nonrearfoot strike. The aim of this study was to investigate the potential differences in foot-ankle muscle strength between RF and NRF runners.

Methods

A cross-sectional study including 40 RF and 40 NRF runners was conducted. The foot posture and the maximal voluntary isometric strength (MVIS) of 6 foot-ankle muscles were measured. The footstrike pattern was determined using a 2-D camera during a self-paced run on a treadmill.

Results

NRF had higher MVIS for ankle plantar flexor (+12.5%, P = .015), ankle dorsiflexor (+17.7%, P = .01), hallux flexor (+11%, P = .04), and lesser toe flexor (+20.8%, P = .0031). We found a small positive correlation between MVIS of ankle plantar flexor with MVIS of hallux flexor (r = 0.26; P = .01) and lesser toe flexor (r = 0.28; P = .01).

Conclusion

In this cross-sectional study, we found that NRF runners on average have a higher MVIS of hallux and lesser toe flexor compared with RF runners. NRF runners also have a higher MVIS of ankle plantar flexor and dorsiflexor than RF runners. We found only a small correlation between ankle plantar flexor and foot muscle strength.

Level of Evidence

Level III, case-control study.

Running economy and lower extremity stiffness in endurance runners: A systematic review and meta-analysis

Background: Lower extremity stiffness simulates the response of the lower extremity to landing in running. However, its relationship with running economy (RE) remains unclear. This study aims to explore the relationship between lower extremity stiffness and RE. Methods: This study utilized articles from the Web of Science, PubMed, and Scopus discussing the relationships between RE and indicators of lower extremity stiffness, namely vertical stiffness, leg stiffness, and joint stiffness. Methodological quality was assessed using the Joanna Australian Centre for Evidence-Based Care (JBI). Pearson correlation coefficients were utilized to summarize effect sizes, and meta-regression analysis was used to assess the extent of this association between speed and participant level. Result: In total, thirteen studies involving 272 runners met the inclusion criteria and were included in this review. The quality of the thirteen studies ranged from moderate to high. The meta-analysis results showed a negative correlation between vertical stiffness (r = -0.520, 95% CI, -0.635 to -0.384, p < 0.001) and leg stiffness (r = -0.568, 95% CI, -0.723 to -0.357, p < 0.001) and RE. Additional, there was a small negative correlation between knee stiffness and RE (r = -0.290, 95% CI, -0.508 to -0.037, p = 0.025). Meta-regression results showed that the extent to which leg stiffness was negatively correlated with RE was influenced by speed (coefficient = -0.409, p = 0.020, r 2 = 0.79) and participant maximal oxygen uptake (coefficient = -0.068, p = 0.010, r 2 = 0.92). Conclusion: The results of this study suggest that vertical, leg and knee stiffness were negatively correlated with RE. In addition, maximum oxygen uptake and speed will determine whether the runner can take full advantage of leg stiffness to minimize energy expenditure.