What are the Benefits and Risks Associated with Changing Foot Strike Pattern During Running? A Systematic Review and Meta-analysis of Injury, Running Economy, and Biomechanics

Anderson, Laura; Bonanno, Daniel R; Hart, Harvi F; Barton, Christian J

doi:10.1007/s40279-019-01238-y

Cited by 67 publications

(45 citation statements)

References 88 publications

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“…Een PubMed-search met de zoektermen 'running' en 'footstrike' [figuur] plus een systematische review (SR)-filter leverde 25 hits op, waaronder 1 relevante SR van Anderson et al 3 Zoeken vanaf de zoekdatum van de SR (21 april 2019) met de 2 zoektermen leverde op 13 april 2020 227 hits op voor title/ abstract screening. Dit resulteerde in 2 artikelen, die we na beoordeling van de volledige tekst excludeerden omdat ze zich alleen richtten op biomechanica en klinische onderzoeksresultaten ontbraken.…”

Section: Zoekstructuur En Resultatenunclassified

“…Bovendien hadden de onderzoekers het gebruikte protocol in een prospectievetrialregister kunnen publiceren, maar daarover is niets in het artikel terug te vinden, noch hebben we het in de grote trialregisters gevonden. [3][4][5][6] CONCLUSIE EN AANBEVELINGEN Op basis van de geïncludeerde onderzoeken kunnen we alleen concluderen dat overschakelen van hakvoet-op voorvoetloop te overwegen is bij renners met milde tot matige PFPS, wan-neer zij geen pijn in de enkels hebben. Bedenk dat dit alleen geldt voor renners die niet op een andere sport willen overstappen en in staat zijn om een trainingsprogramma te volgen bij een gespecialiseerde fysiotherapeut of hardloopcoach.…”

Section: Zoekstructuur En Resultatenunclassified

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Een voetnoot voor hardlopers

Deynoot

Rozbeh

2021

Huisarts Wet

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Section: Zoekstructuur En Resultatenunclassified

Een voetnoot voor hardlopers

Deynoot

Rozbeh

2021

Huisarts Wet

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“…In addition, coaches should not hesitate to make small adjustments based on the observed performance. Moreover, given the day-to-day variation of human performance and the CI of the estimated CS, i.e., about 5% of its value (Table 2), it would be justified to prescribe exercise intensity outside these confidence limits to avoid being in the phase transition between the heavy and severe intensity domains (Anderson et al, 2019). Jones and Vanhatalo (2017) found that CS occurred at 70-90% ofVO 2 max, depending on training status (the higher the training status, the higher the CS in %VO 2 max).…”

Section: Discussionmentioning

confidence: 99%

Effect of Mathematical Modeling and Fitting Procedures on the Assessment of Critical Speed and Its Relationship With Aerobic Fitness Parameters

et al. 2021

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An accurate estimation of critical speed (CS) is important to accurately define the boundary between heavy and severe intensity domains when prescribing exercise. Hence, our aim was to compare CS estimates obtained by statistically appropriate fitting procedures, i.e., regression analyses that correctly consider the dependent variables of the underlying models. A second aim was to determine the correlations between estimated CS and aerobic fitness parameters, i.e., ventilatory threshold, respiratory compensation point, and maximal rate of oxygen uptake. Sixteen male runners performed a maximal incremental aerobic test and four exhaustive runs at 90, 100, 110, and 120% of the peak speed of the incremental test on a treadmill. Then, two mathematically equivalent formulations (time as function of running speed and distance as function of running speed) of three different mathematical models (two-parameter, three-parameter, and three-parameter exponential) were employed to estimate CS, the distance that can be run above CS (d′), and if applicable, the maximal instantaneous running speed (smax). A significant effect of the mathematical model was observed when estimating CS, d′, and smax (P < 0.001), but there was no effect of the fitting procedure (P > 0.77). The three-parameter model had the best fit quality (smallest Akaike information criterion) of the CS estimates but the highest 90% confidence intervals and combined standard error of estimates (%SEE). The 90% CI and %SEE were similar when comparing the two fitting procedures for a given model. High and very high correlations were obtained between CS and aerobic fitness parameters for the three different models (r ≥ 0.77) as well as reasonably small SEE (SEE ≤ 6.8%). However, our results showed no further support for selecting the best mathematical model to estimate critical speed. Nonetheless, we suggest coaches choosing a mathematical model beforehand to define intensity domains and maintaining it over the running seasons.

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“…runners per group would be needed to detect a significant difference (α = 5%) in response to footwear between non-rearfoot and rearfoot strikers with 80% power (β = 20%). The potential for greater benefits of NIKE in rearfoot strikers might be due to the greater compression of the midsole at the heel region [32] where the amount of ZoomX foam is the greatest, as well as the evidenced -albeit limited -greater vertical loading rates and impact peaks of rearfoot strikers [33]. Research specifically examining responses to NIKE footwear based on footstrike pattern is warranted to elucidate the interaction between footstrike characteristics and the performance enhancing effects of footwear.…”

Section: Discussionmentioning

confidence: 99%

“…intensities. Furthermore, one must consider the risks associated with changing biomechanical patterns in uninjured runners [33] and transitioning to novel footwear too quickly [34]. We only recruited male runners because of shoe cost considerations; however, we speculate that recreational female runners would respond similarly given the findings of similar responses to NIKE footwear from elite [10] and Strava [13] cohorts.…”

Section: Practical Applicationsmentioning

confidence: 99%

Evidence of variable performance responses to the Nike 4% shoe: Definitely not a game-changer for all recreational runners

Hébert‐Losier¹,

Finlayson²,

Driller³

et al. 2020

Preprint

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Purpose: We compared running economy (RE) and 3-km time-trial (TT) performances of male recreational runners wearing the Nike Vaporfly 4% (NIKE), lightweight racing flats (FLAT), and their habitual footwear (OWN). Methods: Eighteen male recreational runners [age: 33.5 (11.9) y, V̇O2peak: 55.8 (4.4) mL·kg-1·min-1] attended 4 sessions ~7 days apart. The first session consisted of a V̇O2peak test to inform subsequent RE speeds set at 60, 70, and 80% of the speed eliciting V̇O2peak. In subsequent sessions, treadmill RE and 3-km TT were assessed in the three footwear in a randomised, counterbalanced crossover design. Results: RE was improved in NIKE (3.6 to 4.5%, p ≤ 0.002) and FLAT (2.4 to 4.0%, p ≤ 0.042) versus OWN across intensities, with a trivial difference between NIKE and FLAT (1.0 to 1.6%, p ≥ 0.325). NIKE 3-km TT (11:07.6 ± 0:56.6 mm:ss) was superior to OWN by 16.6 s (2.4%, p = 0.005) and FLAT by 13.0 s (1.8%, , p = 0.032), with similar times between OWN and FLAT (0.5%, , p = 0.747). Only 29% of runners were more economical across intensities and faster in NIKE. Conclusions: Overall, our findings indicate that NIKE could benefit RE in male recreational runners at relative speeds when compared to OWN, but not when compared to FLAT. More runners exhibited better TT performances in NIKE (61%) versus FLAT (22%) and OWN (17%). The high variability in individual RE (-3.1 to 12.1%) and TT (-3.8 to 8.2%) shoe-responses suggests that individualisation of running footwear prescription is warranted.

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What are the Benefits and Risks Associated with Changing Foot Strike Pattern During Running? A Systematic Review and Meta-analysis of Injury, Running Economy, and Biomechanics

Cited by 67 publications

References 88 publications

Een voetnoot voor hardlopers

Een voetnoot voor hardlopers

Effect of Mathematical Modeling and Fitting Procedures on the Assessment of Critical Speed and Its Relationship With Aerobic Fitness Parameters

Evidence of variable performance responses to the Nike 4% shoe: Definitely not a game-changer for all recreational runners

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