Cardiorespiratory Fitness and Performance Adaptations to High-Intensity Interval Training: Are There Differences Between Men and Women? A Systematic Review with Meta-Analyses
Notice bibliographique
Résumé
Abstract Background It is important to consider biological sex as a variable that might influence exercise adaptation in order to optimize exercise prescription for men and women. Objective The aim of this study was to quantify the impact of biological sex on maximal oxygen uptake ( $$\dot{V}$$ V˙ O2max) and performance outcomes after high-intensity interval training (HIIT). Methods A systematic search and review was conducted by two independent reviewers up to 8 September 2022 using MEDLINE, SPORTDiscus, and Sports Medicine & Education Index in ProQuest. Trials including healthy adults were included if they presented data for or compared male and female $$\dot{V}$$ V˙ O2maxor performance outcomes in response to HIIT. Performance outcomes included measures of exercise performance and concurrently measured physiological adaptations. Where appropriate, a random-effects, pre-post meta-analysis was undertaken. Data were sub-grouped for men and women, baseline training level, mean age, intervention type, and intervention length. Heterogeneity was assessed using Chi2, Cochran’sQ, and HigginsI2and sensitivity analyses, where required. Study quality was assessed using the Newcastle–Ottawa Scale and publication bias was assessed through visual inspection of funnel plots. Results Thirty-three references from 28 trials were included in the review (n = 965; 462 women and 503 men). Meta-analyses included 19 studies for $$\dot{V}$$ V˙ O2max, eight for peak power output from $$\dot{V}$$ V˙ O2maxtesting (PPO), and five for threshold power (powerAT). Meta-analyses revealed similar increases in $$\dot{V}$$ V˙ O2maxin women (g = 0.57; 95% CI 0.44–0.69) and men (g = 0.57; 95% CI 0.42–0.72), and powerATin women (g = 0.38; 95% CI 0.13–0.64) and men (g = 0.38; 95% CI 0.11–0.64). Raw mean differences for change in $$\dot{V}$$ V˙ O2maxwere Δ 0.32 L·min−1and 3.50 mL·kg−1·min−1in men, versus Δ 0.20 L·min−1and 3.34 mL·kg−1·min−1for women. No significant sex differences were present for the primary analysis of any outcome. After sub-grouping, significant differences were present for PPO where the effect size was higher for well-trained women (g = 0.37) compared with well-trained men (g = 0.17), and for $$\dot{V}$$ V˙ O2maxwhere interventions with a duration of 4 weeks or less had significantly smaller effect sizes compared with those longer than 4 weeks (p < 0.001). Unweighted mean percentage change in $$\dot{V}$$ V˙ O2max, PPO, and powerATacross studies was 11.16 ± 7.39%, 11.16 ± 5.99%, and 8.07 ± 6.55% for women, and 10.90 ± 5.75%, 8.22 ± 5.09%, and 7.09 ± 7.17% for men, respectively. Significant heterogeneity was present for both $$\dot{V}$$ V˙ O2maxand PPO (I2, range: 62.06–78.80%). Sub-grouping by baseline training status and intervention length decreased heterogeneity in most groups. A qualitative synthesis of other outcomes indicated similar improvements in fitness and performance for men and women with some evidence suggesting differences in the mechanisms of adaptation. Limitations and Risk of Bias Publication bias is unlikely to have significantly influenced results for $$\dot{V}$$ V˙ O2maxor powerAT, but the meta-analysis of PPO could have benefitted from additional study data to strengthen results. The overlap in age categories and sensitivity of the analysis limits the accuracy of the results of the sub-grouping by age. Conclusions Findings indicated no sex-specific differences for any fitness or performance outcomes. Baseline training status and intervention length accounted for most variability in outcomes. PROSPERO registration number: CRD42021272615.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi 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.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,017 | 0,060 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,002 |
| Méta-épidémiologie (sens large) | 0,021 | 0,031 |
| Bibliométrie | 0,005 | 0,007 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,004 | 0,002 |
| Science ouverte | 0,002 | 0,002 |
| Intégrité de la recherche | 0,003 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,005 | 0,000 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».