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Enregistrement W7033010347

Optimization of post-exercise recovery beverages’ composition

2019· article· en· W7033010347 sur OpenAlexaboutno aff

Notice bibliographique

RevueUnicam Scientific Publications (University of Camerino) · 2019
Typearticle
Langueen
DomaineEarth and Planetary Sciences
ThématiqueSubterranean biodiversity and taxonomy
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésDiafiltrationLimitingProtein isoformMyoglobinuria
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

Fluid intake and adequate hydration are essential and critical during and after training sessions and competition events. Reductions in body water content will prejudice performance with exercise performance significantly impaired when 2% or more of body weight is lost through sweat [1-3]. Guidelines states that in the post exercise (within 30 minutes to 1 hour after the end of the physical exercise), effective rehydration requires the intake of a volume of fluid equal to, at least, the 150% of the difference between body weight before and after the training [4] but a lack is still present regarding specific guidelines related to beverage formulations, strategies and volumes.
\nIndeed, in addition to water, sweat contains variable amounts of sodium, with lesser amounts of potassium, calcium, and magnesium so it is important that athletes can benefit from intake of an appropriate amount of a well-formulated drink [5-9]. 
\nOur prevoius studies underlined the potential role of skimmed milk as post recovery drink possibly linked to its specific characteristics [10-12]. In particular, milk has naturally high concentrations of electrolytes, that should aid in fluid recovery following exercise [4, 13].
\nMoreover, it contains casein and whey proteins in a ratio of 3:1 which provides for slower digestion and absorption of these proteins resulting in sustained elevations of blood amino acid concentrations.
\nIn this regard, the aim of this study was to further evaluate the role of milk as post-recovery beverage. In particular, skimmed milk was tested in different volumes (no diluted skimmed milk, skimmed milk diluted 1:2 and 1:3) in order to better evaluate its role and to optimize volume. Moreover, specific nutrients (i.e. Casein, Sodium) and their possible combinations (Casein + Sodium, Whey proteins + Sodium) were taken into account in different concentrations to investigate possible role of specific nutrients. 
\n30 athletes, both male and female, aged between 19 and 47, took part to the study. Each strategy was tested for one week with an intake equal to 500ml of the specific drink with the addiction of an amount of water equal to the volume needed to reach the 150% of loss body weight during the exercise.
\nA specific questionnaire was performed to ask about type of activity performed, the intensity of the activity, the urine colour, the thirst sensation after waking up in the morning; eventual cramps. Anthropometric measurement and Bioimpedence Analysis (both mono-frequency and multi-frequency) were performed to assess body composition and hydration in term of total body water, intra-cellular water and extra-cellular water.
\nFollowing guidelines indications, through the use of 150% of water intake in the post exercise, a variability among subjects were observed with cases also of worsening of hydration status underlining the importance of beverage characteristics as several elements might affect fluid balance: the macronutrient content, the electrolyte (i.e. sodium and potassium) [5-9].
\nAmong the different strategies tested, skimmed milk resulted again the best one, able both to improve total body water in terms of intra-cellular water and body composition more than single milk nutrients. This underlines the importance of further investigate milk as post-exercise recovery beverage in terms not only of nutrients content but also nutrients synergism.
\nEven if data obtained by this study are limited by the restricted number of athletes, obtained results can be considered a step ahead to better evaluate the role of milk as recovery beverages, to define its applicability and to study new hydration protocols in order to improve the present knowledge on athlete’s hydration and recovery. 
\n
\nReferences
\n
\n[1]\tMaughan RJ. Investigating the associations between hydration and exercise performance: methodology and limitations. Nutr Rev. 2012;70(suppl_2):S128-S131.
\n[2]\tMaughan RJ, Shirreffs SM, Leiper JB. Errors in the estimation of hydration status from changes in body mass. J Sports Sci. 2007;25(7):797-804.
\n[3]\tGoulet ED, et al. Pre-exercise hyperhydration delays dehydration and improves endurance capacity during 2 h of cycling in a temperate climate. J Physiol Anthropol. 2008;27(5):263-71.
\n[4]\tShirreffs SM, Watson P, Maughan RJ. Milk as an effective post-exercise rehydration drink. Br J Nutr. 2007; 98(1):173-180.
\n[5]\tThomas DT, Erdman KA, Burke LM. Position of the Academy of Nutrition and Dietetics, Dietitians of Canada, and the American College of Sports Medicine: Nutrition and Athletic Performance. J Acad Nutr Diet. 2016;116(3):501-528.
\n[6]\tBrancaccio P, et al. Supplementation of Acqua Lete(R) (Bicarbonate Calcic Mineral Water) improves hydration status in athletes after short term anaerobic exercise. J Int Soc Sports Nutr. 2012; 9(1):35.
\n[7]\tMaughan RJ, et al. A randomized trial to assess the potential of different beverages to affect hydration status: development of a beverage hydration index. Am J Clin Nutr. 2016;103(3):717-23.
\n[8]\tKalman DS, et al. Comparison of coconut water and a carbohydrate-electrolyte sport drink on measures of hydration and physical performance in exercise-trained men. J Int Soc Sports Nutr. 2012;9(1):1.
\n[9]\tOliver S, et al. Development of a hydration index: a randomized trial to assess the potential of different beverages to affect hydration status. Nutr Hosp. 2015;32 Suppl 2:10264.
\n[10]\tVici G, Albertini F, Quintavalle A, Belli L, Polzonetti V. Milk as recovery drink after exercise: a case study. Alimenti Funzionali e Nutraceutici per la Salute. Camerino, 28th June 2016
\n[11]\tVici G, Camilletti D, Cesanelli L, Belli L, Polzonetti V. Effects of different nutritional strategies in post exercise recovery. Cibo e Nutraceutici: direzione salute. Camerino, 10th July 2018
\n[12]\tVici G, Camilletti D, Mozzoni A, Cesanelli L, Belli L, Polzonetti V. Effects of specific re-hydration protocols after exercise in non-elite and elite athletes. 3rd Sport Nutrition International Conference. Bologna, 30th November 2018
\n[13]\tRoy BD. Milk: the new sports drink? A Review. J Int Soc Sports Nutr. 2008;5:15.

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 distillée sur la base complète

Imitation des enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesCharge utile insuffisante (le modèle a refusé de juger)
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,292
Score d'incertitude au seuil0,990

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,001
Études des sciences et des technologies0,0000,000
Communication savante0,0000,001
Science ouverte0,0010,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0110,000

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.

Tête enseignante Opus0,015
Tête enseignante GPT0,163
Écart entre enseignants0,148 · 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 tête enseignante, pas un consensus.

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
Publié2019
Routes d'admission1
Résumé présentoui

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