Biomechanics of Marathon Running

Stöggl, Thomas; Wunsch, Tobias

doi:10.1007/978-3-319-29728-6_2

Cited by 10 publications

(12 citation statements)

References 151 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This was most evident in runners and cyclists, but not as prominent in swimmers, which is likely due to the large disparity in cyclic movement frequencies between different distance events in running and cycling disciplines when compared to swimming. Indeed, there is a much lower discrepancy between the typical stroke rate of swimmers competing in different distance events (i.e., mean freestyle stroke rate range: ~44 to 58 cycles•min -1 from sprint-to longdistance events) 18,19 , when compared to different distance events within both cycling (i.e., mean cadence range: ~70 to 150 rev•min -1 ) 20,21 and running (i.e., mean stride rate range: ~90 -280 strides•min -1 ) 22,23 . It is also worth highlighting that the typical mean stroke rate of sprint swimmers (~58 cycles•min -1 ) 18 is substantially lower than the cycling stroke rate equivalent (i.e., mean cadence) of track sprint cyclists (~150 revolutions•min -1 ) 20 and the mean stride rate of track sprint runners (~280 strides•min -1 ) 22 , respectively.…”

Section: Discussionmentioning

confidence: 99%

The Muscle Typology of Elite and World-Class Swimmers

Bellinger

Lievens

Kennedy³

et al. 2022

International Journal of Sports Physiology and Performance

View full text Add to dashboard Cite

Purpose: To examine whether the muscle typology of elite and world-class swimmers could discriminate between their best distance event, swimming stroke style, or performance level. Methodology: The muscle carnosine content of 43 male (860 [76] FINA [Fédération Internationale de Natation] points) and 30 female (881 [63] FINA points) swimmers was measured in the soleus and gastrocnemius by proton magnetic resonance spectroscopy and expressed as a carnosine aggregate Z score (CAZ score) to estimate muscle typology. A higher CAZ score is associated with a higher estimated proportion of type II fibers. Swimmers were categorized by their best stroke, distance category (sprinters, 50–100 m; middle distance, 200–400 m; or long distance, 800 m–open water), and performance level (world-class, world top 10, or elite and world top 100 swimmers outside of the world top 10). Results: There was no significant difference in the CAZ score of sprint- (−0.08 [0.55]), middle- (−0.17 [0.70]), or long-distance swimmers (−0.30 [0.75], P = .693). World-class sprint swimmers (all strokes included) had a significantly higher CAZ score (0.37 [0.70]) when compared to elite sprint swimmers (−0.25 [0.61], P = .024, d = 0.94). Breaststroke swimmers (0.69 [0.73]) had a significantly higher CAZ score compared to freestyle (−0.24 [0.54], P < .001, d = 1.46), backstroke (−0.16 [0.47], P = .006, d = 1.42), and butterfly swimmers (−0.39 [0.53], P < .001, d = 1.70). Furthermore, within the cohort of breaststroke swimmers, there was a significant positive correlation between FINA points and CAZ score (r = .728, P = .011); however, this association was not evident in other strokes. Conclusion: While there was no clear association between muscle typology and event distance specialization, world-class sprint swimmers possess a greater estimated proportion of type II fibers compared to elite sprint swimmers, as well as breaststroke swimmers compared to freestyle, backstroke, and butterfly swimmers.

show abstract

Section: Discussionmentioning

confidence: 99%

The Muscle Typology of Elite and World-Class Swimmers

Bellinger

Lievens

Kennedy³

et al. 2022

International Journal of Sports Physiology and Performance

View full text Add to dashboard Cite

show abstract

“…This might also be related to the fact that people over 45 are in a less exploratory phase of their lives, and thus do not perceive reasons to seek for different types of sports to practice [ 50 ]. Another explanation might be that these ‘older’ runners are more experienced and therefore, more aware of their bodies and potential injuries [ 30 , 51 ]. This is in line with a previous study, indicating that the most experienced runners included most runners being older than 45 [ 41 ].…”

Section: Discussionmentioning

confidence: 99%

“…Running experience influenced both social and individual reasons to quit negatively, where runners who run for more than 5 years perceive less (social and individual) reasons to quit as compared to runners running for less than a year. We can hypothesize that runners who already have been running for more than 5 years have already been able to overcome obstacles and barriers (e.g., injuries or motivational loss) throughout the years and kept pursuing running [ 30 , 51 ]. On the other hand, participants running for less than a year might have a lower self-efficacy, i.e., confidence in one’s ability to overcome potential obstacles [ 52 ].…”

Section: Discussionmentioning

confidence: 99%

Runner’s Perceptions of Reasons to Quit Running: Influence of Gender, Age and Running-Related Characteristics

Menheere

Janssen

Funk

et al. 2020

IJERPH

View full text Add to dashboard Cite

Physical inactivity has become a major public health concern and, consequently, the awareness of striving for a healthy lifestyle has increased. As a result, the popularity of recreational sports, such as running, has increased. Running is known for its low threshold to start and its attractiveness for a heterogeneous group of people. Yet, one can still observe high drop-out rates among (novice) runners. To understand the reasons for drop-out as perceived by runners, we investigate potential reasons to quit running among short distance runners (5 km and 10 km) (n = 898). Data used in this study were drawn from the standardized online Eindhoven Running Survey 2016 (ERS16). Binary logistic regressions were used to investigate the relation between reasons to quit running and different variables like socio-demographic variables, running habits and attitudes, interests, and opinions (AIOs) on running. Our results indicate that, not only people of different gender and age show significant differences in perceived reasons to quit running, also running habits, (e.g., running context and frequency) and AIOs are related to perceived reasons to quit running too. With insights into these related variables, potential drop-out reasons could help health professionals in understanding and lowering drop-out rates among recreational runners.

show abstract

“…Running on a positive slope is associated with an increase in total muscle volume activated in the lower extremity (Sloniger et al, 1997), with a tendency to mid/forefoot strike, higher stride frequency and decreased stride length when compared to level running, resulting in an increased internal mechanical work, shorter aerial phase duration, longer time spent in stance (Padulo et al, 2013; Vernillo et al, 2017). Up to around 90% maximum velocity, speed increments are mainly met by increased stride length, resulting in more time spent on the swing phase (Dugan & Bhat, 2005; Mann & Hagy, 1980; Novacheck, 1998; Stöggl & Wunsch, 2016). Increased stride frequency will be more significant in attaining higher speeds only when velocity approaches maximum.…”

Section: Introductionmentioning

confidence: 99%

Steeper or Faster? Impacts of Similar-intensity Running Conditions on Heart Rate Variability

ElDash,

Marques

et al. 2024

Preprint

View full text Add to dashboard Cite

Increases in speed or slope promote different adjustments in the locomotor system and lead to a higher heart rate (HR). Because heart rate variability (HRV) is known to respond to exercise intensity and to biomechanical stimuli, we aimed to answer whether HRV would be sensitive to changes in speed and/or slope under similar HR. We hypothesize that HRV would depend solely on HR. To test this hypothesis, 6 healthy male runners (age 30 ± 7.5 yrs.) were recruited and a velocity V, with similar HR/HRmax was selected per volunteer. Changes in HR were referred to these particular velocities V, resulting in comparable exercise intensities. HRV was estimated through standard deviation (sdt) and root mean square of successive RR intervals (rmst), normalized per volunteer. Four running conditions were compared. We found that rmst decreased with speed and slope, with significant interaction between the independent variables. The run {0.7 V, 0%} was different from the remaining 3 conditions, which, in turn, were no different from one another. Thus, this estimator did not show a distinct sensitivity to variations in speed or slope. On the other hand, sdt decreased with both speed and slope, with no significant interactions. The runs performed at {0.7 V, 0%} and {0.7 V, 6%} were different from those at {1 V, 0%} and {1 V, 6%}. Therefore, sdt presented different values under similar HR. This finding leads us to conclude that cardiac control operates sensitively due to the mode of the changes imposed on the metabolic demand.

show abstract

Biomechanics of Marathon Running

Cited by 10 publications

References 151 publications

The Muscle Typology of Elite and World-Class Swimmers

The Muscle Typology of Elite and World-Class Swimmers

Runner’s Perceptions of Reasons to Quit Running: Influence of Gender, Age and Running-Related Characteristics

Steeper or Faster? Impacts of Similar-intensity Running Conditions on Heart Rate Variability

Contact Info

Product

Resources

About