Efficacy of Interval Training in Improving Body Composition and Adiposity in Apparently Healthy Adults: An Umbrella Review with Meta-Analysis
Notice bibliographique
Résumé
BACKGROUND: Although the efficacy of interval training for improving body composition has been summarized in an increasing number of systematic reviews in recent years, discrepancies in review findings and conclusions have been observed. OBJECTIVE: This study aims to synthesize the available evidence on the efficacy of interval training compared with moderate-intensity continuous training (MICT) and nonexercise control (CON) in reducing body adiposity in apparently healthy adults. METHODS: An umbrella review with meta-analysis was performed. A systematic search was conducted in seven databases (MEDLINE, EMBASE, Cochrane Database, CINAHL, Scopus, SPORTDiscus, and Web of Science) up to October 2023. Systematic reviews with meta-analyses of randomized controlled trials (RCTs) comparing interval training and MICT/CON were included. Literature selection, data extraction, and methodological quality assessment (AMSTAR-2) were conducted independently by two reviewers. Meta-analyses were performed using a random-effects model. Subgroup analyses were conducted based on the type of interval training [high-intensity interval training (HIIT) and sprint interval training (SIT)], intervention duration, body mass index, exercise modality, and volume of HIIT protocols. RESULTS: Sixteen systematic reviews, including 79 RCTs and 2474 unique participants, met the inclusion criteria. Most systematic reviews had a critically low (n = 6) or low (n = 6) AMSTAR-2 score. Interval training demonstrated significantly greater reductions in total body fat percent (BF%) compared with MICT [weighted mean difference (WMD) of - 0.77%; 95% confidence interval (CI) - 1.12 to - 0.32%] and CON (WMD of - 1.50%; 95% CI - 2.40 to - 0.58%). Significant reductions in fat mass, visceral adipose tissue, subcutaneous abdominal fat, and android abdominal fat were also observed following interval training compared to CON. Subgroup analyses indicated that both HIIT and SIT resulted in superior BF% loss than MICT. These benefits appeared to be more prominent in individuals with overweight/obesity and longer duration interventions (≥ 12 weeks), as well as in protocols using cycling as a modality and low-volume HIIT (i.e., < 15 min of high-intensity exercise per session). CONCLUSIONS: This novel umbrella review with large-scale meta-analysis provides an updated synthesis of evidence with implications for physical activity guideline recommendations. The findings support interval training as a viable exercise strategy for reducing adiposity in the general population.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,012 | 0,002 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 tête enseignante, 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 ».