A Whey Protein‐Based, Multi‐Ingredient Supplement Independently Stimulates Gains in Lean Body Mass and Strength, and Enhances Exercise‐Induced Adaptations in Older Men
Notice bibliographique
Résumé
Reductions in muscle mass and strength with age (sarcopenia) increase the risk for falls, metabolic disorders, and the need for assisted living. Nutrition and exercise interventions are effective in combating sarcopenia. A number of nutrition supplements have been shown to be ‘anti‐sarcopenic’ in their action as isolated compounds but they have never been combined. The objective of this double‐blind randomized controlled study was to evaluate whether daily consumption of a protein‐based, multi‐ingredient nutritional supplement would result in (i) gains in strength and lean body mass independent of exercise; and (ii) enhance exercise‐mediated improvements in these outcomes in a group of healthy older men. Forty‐nine men (age: 73 ± 1 years; BMI: 28.5 ± 0.7 kg/m 2 ) were randomized to 20 weeks of nutrition supplementation (SUPP n=25; whey protein, creatine, vitamin D, calcium, and fish oil twice daily) or placebo (PLB n=24; carbohydrate twice daily). Following 6 weeks of supplementation (Phase 1: SUPP/PLB), subjects undertook a 12‐week progressive exercise training program consisting of resistance exercise and high‐intensity interval training (Phase 2: SUPP/PLB+EX). Dynamic strength (1 repetition maximum [1RM]) for all training exercises and whole body lean mass (WBLM; via dual‐energy x‐ray absorptiometry [DXA]) were evaluated at weeks 0 (baseline), 7 (Phase 1: SUPP/PLB only), and 20 (Phase 2: SUPP/PLB+EX). Data were analyzed using a linear mixed model with treatment and time as factors. Results are presented as mean ± SEM. Unless otherwise stated, p‐values refer to changes over time within each treatment group. Between weeks 0–7 (Phase 1: SUPP/PLB only), subjects in the SUPP group demonstrated substantial gains in strength (Δ ∑1RM: +14 ± 4 kg, p=0.001) and lean mass (Δ WBLM: +1.2 ± 0.3 kg, p=0.001), whereas no change in either outcome was observed in the PLB group (Δ ∑1RM: +3 ± 2 kg, p=1.000; Δ WBLM: −0.1 ± 0.2 kg, p=1.000). With the addition of exercise training (Phase 2: SUPP/PLB+EX), upper body strength increased to a greater degree in the SUPP group (Δ ∑ upper body 1RM: +13 ± 2 kg, p<0.001) compared to the PLB group (Δ ∑ upper body 1RM: +9 ± 2 kg, p<0.001). At baseline and week 7, we observed no difference in strength between SUPP and PLB. However, upon completion of the exercise training program upper body strength was greater in the SUPP group when compared to the PLB group (∑ upper body 1RM at week 20: 119 ± 4 vs. 109 ± 5 kg, p=0.039). Exercise training did not induce further improvements in lean mass in either group (SUPP Δ WBLM: +0.5 ± 0.2 kg, p=0.576; PLB, Δ WBLM: +0.3 ± 0.3 kg, p=0.982). We conclude that the multi‐ingredient nutritional supplement was effective in stimulating gains in strength, as well as gains in lean mass comparable to those observed following longer‐term, intensive resistance exercise training regimens in older men. This proof‐of‐principle study demonstrates that a multi‐pronged nutritional approach, combined with an exercise training program that targets both strength and body composition, is advantageous in attenuating the effects of sarcopenia in aging. Support or Funding Information This work was supported by the Labarge Optimal Aging Initiative.
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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 | 0,001 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 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 ».