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Enregistrement W2147979145 · doi:10.1113/jp270351

Short and sweet: cardiovascular and metabolic improvements in just one hour per week

2015· article· en· W2147979145 sur OpenAlexaffabout
Robert F. Bentley, Danielle C. Bentley

Notice bibliographique

RevueThe Journal of Physiology · 2015
Typearticle
Langueen
DomaineMedicine
ThématiqueCardiovascular and exercise physiology
Établissements canadiensUniversity of TorontoQueen's University
Organismes subventionnairesnon disponible
Mots-clésMedicineCardiologyInternal medicineAnimal scienceBiology

Résumé

récupéré en direct d'OpenAlex

Over the past couple of decades there has been a growing appreciation for the positive effects that exercise may elicit on various bodily systems and disease progressions. However, despite the well-known benefits of regular exercise, insufficient time in our fast-paced lives is often cited as the principle hurdle to overcome. Coupled with this time barrier, increased sedentary time has resulted in obesity levels reaching epidemic proportions globally, resulting in an increased risk for various cardiovascular and metabolic diseases (Ladabaum et al. 2014). Using this information as a framework, the utilisation of an accessible, time-efficient exercise regimen among an obese population would improve our efforts to overcome this epidemic and reduce both cardiovascular and metabolic risk factors. In a recent issue of The Journal of Physiology, Cocks et al. (2015) investigated the impact of 4 weeks of traditional endurance training on a cycle ergometer (5 times per week, 40–60 min per session at ∼65% ) against the recently acclaimed sprint interval training (3 times per week, 4–7 constant load intervals at 200% peak wattage for 30 s separated by 120 s of active recovery) on microvascular function, metabolism and cardiovascular health. This investigation compared the effects of these two exercise modalities among obese young men (n = 16) on skeletal muscle capillarisation, insulin resistance, microvascular endothelial nitric oxide synthase (eNOS) expression, microvascular filtration, and arterial stiffness. Briefly, results from Cocks et al. (2015) revealed that both exercise training modalities were effective at increasing , and improving insulin resistance post training. Additionally, skeletal muscle capillarisation and endothelial eNOS content were both increased, while endothelial NAD(P)H oxidase (NOX2) content in microvessels was reduced in both training approaches. Neither exercise training approach had an impact on body mass index, but traditional endurance training did reduce percentage body fat, while sprint interval training did not (Fig. 1). Interestingly, the positive effects of training did not differ between exercise training modalities, suggesting that sprint interval exercise training is an effective, time-efficient means of improving the cardiovascular and metabolic function of young obese men. SIT; sprint interval training, MICT; moderate intensity continuous exercise, eNOS; endothelial nitric oxide synthase, NOX2; endothelial NAD(P)H oxidase, BMI; body mass index. *Significant difference between pre and post training within a condition (P < 0.05). There was no significant difference between SIT and MICT for any outcome variables (P > 0.05). A strong aspect of the present investigation was the application of the two exercise training modalities. Both exercise training approaches can be easily replicated outside the laboratory by the general population. A common research limitation of traditional sprint interval training is the requirement of a specialised cycle ergometer to correctly complete the ‘all out’ nature of the 30 s Wingate sprints. As a result of this limitation, it can be challenging for research participants to complete the sprint training programmes in facilities outside the laboratory (Gibala & McGee, 2008). As an alternative, this investigation utilised a constant load approach equivalent to a specific power output that matched the mean power output of a traditional ‘all out’ Wingate sprint. This was a very intelligent approach as it allows for the results to be easily transferred and applied to the real world. At the same time, Cocks et al. (2015) provided progressive increases in the exercise prescription within each training modality. This means that as the participants’ fitness improves, the exercise being completed is increased to provide a training stimulus constant relative intensity but progressive absolute intensity throughout the training period. Although the experimental design with respect to exercise was well thought out, it does draw attention to the amount of work being completed between training modalities. The authors did not speak to this potential factor when interpreting their results. A quick calculation, based on reported data, reveals that the total work during the sprint interval training is approximately 10% of the total work during the traditional endurance protocol. The authors also state that despite this disparity in total work, both exercise protocols were equally effective within the context of the outcome variables. It would be interesting to see if the results remain similar when controlled for total work completed throughout the training period. The duration and/or intensity of the traditional endurance training could be modified to coincide with the work completed during the sprint interval training. It is commonly cited within the literature that there is reduced nitric oxide (NO) bioavailability with obesity (Williams et al. 2002). One aspect of the present study was investigation into NO constituents following exercise training. The authors utilised a novel staining technique to assess the resistance vasculature (arterioles and capillaries separately). The authors noted increased expression of eNOS with both types of training, and increased expression in terminal arterioles over capillaries. This was coupled with a reduction in the NO scavenging NOX2 at the endothelium, but not at the sarcolemma. While these measures provide an indication of increased NO bioavailability and potential improvements in microvascular perfusion post training, they do not provide an indication of vasodilatory capacity as a result of the potentially increased NO. The authors could have applied a maximum vasodilatory stimulus using a combination of cuff inflation and superimposed ischaemic light exercise and then measured the resulting increase in vascular conductance following cessation of exercise and cuff deflation. This protocol would be similar to that of those used to assess maximum flow mediated dilatation. This additional information would provide functional data on the implications of the NO and the precursors measured in the present study. Similar to previous investigations, Cocks et al. (2015) demonstrated an increase in with both endurance and sprint interval exercise training (Burgomaster et al. 2008). Uniquely, the present investigation determined increases in skeletal muscle capillarisation within the m. vastas lateralis, providing an indication of perfusion characteristics of the active skeletal muscle and an increase in microvascular filtration rate. The results suggest improved microvascular perfusion and therefore oxygen delivery. Although beyond the scope of the current study, it would have been interesting to note the contribution of increased capillarisation to the increased observed. With the addition of local blood gas data, the Fick equation, and the calculation of using constituent variables from both pre- and post-training variables, the effect of a given variable on could be quantified (i.e. oxygen extraction vs. muscle blood flow). Throughout the report, Cocks et al. (2015) state that the traditional endurance and sprint interval training protocols resulted in equal outcomes among young, sedentary, obese men. These conclusions are based on the statistical insignificance of differences measured through three-way mixed ANOVA and two-way mixed ANOVA comparisons. The authors also provide detailed information pertaining to their ability to detect between group differences and therefore provide a level of confidence in the observed outcomes. Although not completed in the present study, it would be interesting for future investigators to conduct an equivalency test comparing these two training approaches. With a defined equivalency margin and corresponding analyses, an equivalency test is able to determine if a novel therapy (i.e. the sprint interval training protocol) is statistically equivalent to an established therapy (i.e. the endurance protocol) (Walker & Nowacki, 2011). The importance of larger scale, long-term studies with equivalency designs is acknowledged in previous publications of similar training designs (Cocks et al. 2013). Future research that includes such statistical comparisons would provide foundational results for the equivalency of the two protocols, providing additional support for the use of the time-reduced sprint interval training protocol. In conclusion, the recently published article by Cocks et al. (2015) provides interesting insight into the efficacy of both traditional endurance train-ing (∼5 h week−1) and sprint interval training (∼1 h week−1) as a viable means of training in a young, obese population. Importantly, the sprint interval training implemented in the present investigation can be easily applied to an external laboratory setting. The results from this study not only suggest that these methods of training are safe for an at-risk population, but demonstrate improved cardiovascular and metabolic function in a young obese population with minimal time commitment, which fits in nicely with the timing demands of our fast-paced society. None to declare. R.F.B. is supported by a Natural Sciences and Engineering Council of Canada post-graduate scholarship. D.C.B. is supported by a Canadian Institutes of Health Research doctoral research award. The authors would like to thank Matthew Cocks and the entire research team for this research. We would also like to acknowledge that unfortunately not all pertinent articles in the field could be included in this review due to space constraints.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,002
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,035
Score d'incertitude au seuil0,119

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0010,002
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0010,001
Études des sciences et des technologies0,0010,001
Communication savante0,0010,002
Science ouverte0,0010,002
Intégrité de la recherche0,0020,002
Charge utile insuffisante (le modèle a refusé de juger)0,0350,007

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,040
Tête enseignante GPT0,272
Écart entre enseignants0,232 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2015
Routes d'admission2
Résumé présentoui

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