Guideline-Based Digital Exercise Interventions for Reducing Body Weight and Fat and Promoting Physical Activity in Adults With Overweight and Obesity: Systematic Review and Meta-Analysis
Notice bibliographique
Résumé
Background Digitally delivered physical exercise interventions are becoming increasingly popular in addressing the obesity epidemic. However, there remains uncertainty on their efficacy regarding the reduction of body weight (BW) and body fat, which may, at least partly, be due to variations in study designs and inconsistent adherence to international physical activity (PA) guidelines. Objective This study aimed to evaluate the effectiveness of digital exercise interventions based on PA guidelines in reducing BW and fat in adults with overweight or obesity, as well as their impact on PA-related factors. Methods This review was conducted following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. Comprehensive searches were performed in October 2024 across PubMed, Cochrane Library, Web of Science, and Ovid MEDLINE databases. Eligible studies included adults (aged ≥18 years) with objectively confirmed overweight or obesity who used digital interventions aligned with international PA guidelines. Risk of bias was evaluated using the Cochrane Risk of Bias (version 2) tool for randomized controlled trials and the Risk of Bias in Nonrandomized Studies of Interventions tool for nonrandomized studies. A random-effects meta-analysis with Hartung-Knapp adjustment was performed using R software. Results Out of 4948 studies identified, 188 (3.8%) were screened in full and 30 (0.6%) met the eligibility criteria. Intervention durations ranged from 8 weeks to 24 months (average 6.4, SD 5.5 months). Meta-analysis showed that guideline-based digital exercise interventions significantly reduced BW compared to controls (mean difference [MD]=−1.17 kg; P=.003; I2=0.0%), with subgroup analysis revealing greater effects in active (nondigital) controls (MD=−1.23 kg; I2=7.5%) compared to passive (waitlist) controls (MD=−0.52 kg; I2=0.0%). A significant reduction in BMI was observed (MD=−0.50 kg/m2; P=.003), although with substantial heterogeneity (I2=70.0%), and subgroup analysis showed greater effects compared to passive controls (MD=−0.70 kg/m2; I2=43.1%) rather than to active controls (MD=−0.45 kg/m2; I2=74.5%). No significant effect was observed for body fat percentage overall (MD=−0.08%; P=.84; I2=7.4%). Qualitative analysis (including findings from noncomparative studies) showed that guideline-based digital exercise interventions led to significant reductions in BW (22/25, 88% studies; range −1.3 to −8.4 kg); BMI (19/23, 83% of studies; range −0.4 to −3.4 kg/m2); waist circumference (15/16, 94% of studies; range −2.1 to −9.2 cm), body fat percentage (9/9, 100% of studies; range −0.3% to −4.1%); and fat mass (7/7, 100% of studies; range −0.4 to −6.5 kg), while findings for waist-to-hip ratio and PA outcomes were inconsistent. Conclusions Guideline-based digital PA and exercise interventions show potential in reducing excess BW in adults with overweight or obesity, with stronger effects when compared to nondigital interventions. However, their superiority over traditional methods is uncertain for BMI and body composition. Substantial variations in study designs present challenges in drawing definitive conclusions on specific characteristics of effective digital exercise tools. Trial Registration PROSPERO CRD42024620020; https://www.crd.york.ac.uk/PROSPERO/view/CRD42024620020
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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 | 0,005 | 0,009 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,008 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| 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 | 0,002 |
| 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 ».