Los carbohidratos durante el ejercicio: la investigación de los últimos 10 años. Nuevas recomendaciones

Durante los últimos años se han producido cambios significativos en la comprensión del papel que juegan los carbohidratos durante el ejercicio, y esto permite realizar un asesoramiento más específico y más individualizado en cuanto a la ingestión de carbohidratos durante el ejercicio. Las nuevas directrices propuestas tienen en cuenta la duración (y la intensidad) del ejercicio y el asesoramiento no se limita a la cantidad de carbohidratos, sino que también propone el tipo de estos. La ingesta recomendada de carbohidratos se puede lograr consumiendo bebidas, geles con pocas grasas o alimentos sólidos bajos en proteínas y en fibra (barritas) y la elección debe basarse en las preferencias personales. Debe tenerse en cuenta que la mayoría de estudios se basan en descubrimientos realizados con corredores y ciclistas, por lo que es necesario investigar más para establecer los efectos y los mecanismos subyacentes de la ingestión de carbohidratos en los componentes de habilidad de deportes intermitentes de equipo.Durante los últimos años se han producido cambios significativos en la comprensión del papel que juegan los carbohidratos durante el ejercicio, y esto permite realizar un asesoramiento más específico y más individualizado en cuanto a la ingestión de carbohidratos durante el ejercicio. Las nuevas directrices propuestas tienen en cuenta la duración (y la intensidad) del ejercicio y el asesoramiento no se limita a la cantidad de carbohidratos, sino que también propone el tipo de estos. La ingesta recomendada de carbohidratos se puede lograr consumiendo bebidas, geles con pocas grasas o alimentos sólidos bajos en proteínas y en fibra (barritas) y la elección debe basarse en las preferencias personales. Debe tenerse en cuenta que la mayoría de estudios se basan en descubrimientos realizados con corredores y ciclistas, por lo que es necesario investigar más para establecer los efectos y los mecanismos subyacentes de la ingestión de carbohidratos en los componentes de habilidad de deportes intermitentes de equipo

Els carbohidrats durant l’exercici: la recerca dels darrers 10 anys. Noves recomanacions

Durant els darrers anys s’han produït canvis significatius en la manera d’entendre el paper que juguen els carbohidrats durant l’exercici, i això permet realitzar un assessorament més específic i més individualitzat pel que fa a la ingestió de carbohidrats durant l’exercici. Les noves directrius proposades tenen en compte la durada (i la intensitat) de l’exercici i l’assessorament no es limita a la quantitat de carbohidrats, sinó que també en proposa el tipus. La ingesta recomanada de carbohidrats es pot assolir consumint begudes, gels amb pocs greixos o aliments sòlids baixos en proteïnes i en fibra (barretes) i l’elecció s’ha de basar en les preferències personals. Cal tenir en compte que la majoria d’estudis es basen en descobriments realitzats amb corredors i ciclistes, per la qual cosa cal investigar més per establir els efectes i els mecanismes subjacents de la ingestió de carbohidrats en els components d’habilitat d’esports intermitents d’equip

Gender and the construction of identities in Indian elementary education

EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Contemporary Nutrition Strategies to Optimize Performance in Distance Runners and Race Walkers

Distance events in Athletics include cross country, 10,000-m track race, half-marathon and marathon road races, and 20- and 50-km race walking events over different terrain and environmental conditions. Race times for elite performers span ∼26 min to >4 hr, with key factors for success being a high aerobic power, the ability to exercise at a large fraction of this power, and high running/walking economy. Nutrition-related contributors include body mass and anthropometry, capacity to use fuels, particularly carbohydrate (CHO) to produce adenosine triphosphate economically over the duration of the event, and maintenance of reasonable hydration status in the face of sweat losses induced by exercise intensity and the environment. Race nutrition strategies include CHO-rich eating in the hours per days prior to the event to store glycogen in amounts sufficient for event fuel needs, and in some cases, in-race consumption of CHO and fluid to offset event losses. Beneficial CHO intakes range from small amounts, including mouth rinsing, in the case of shorter events to high rates of intake (75–90 g/hr) in the longest races. A personalized and practiced race nutrition plan should balance the benefits of fluid and CHO consumed within practical opportunities, against the time, cost, and risk of gut discomfort. In hot environments, prerace hyperhydration or cooling strategies may provide a small but useful offset to the accrued thermal challenge and fluid deficit. Sports foods (drinks, gels, etc.) may assist in meeting training/race nutrition plans, with caffeine, and, perhaps nitrate being used as evidence-based performance supplements

Effect of beverage glucose and sodium content on fluid delivery

<p>Abstract</p> <p>Background</p> <p>Rapid fluid delivery from ingested beverages is the goal of oral rehydration solutions (ORS) and sports drinks.</p> <p>Objective</p> <p>The aim of the present study was to investigate the effects of increasing carbohydrate and sodium content upon fluid delivery using a deuterium oxide (D₂O) tracer.</p> <p>Design</p> <p>Twenty healthy male subjects were divided into two groups of 10, the first group was a carbohydrate group (CHO) and the second a sodium group (Na). The CHO group ingested four different drinks with a stepped increase of 3% glucose from 0% to 9% while sodium concentration was 20 mmol/L. The Na group ingested four drinks with a stepped increase of 20 mmol/L from 0 mmol/L to 60 mmol/l while glucose concentration was 6%. All beverages contained 3 g of D₂O. Subjects remained seated for two hours after ingestion of the experimental beverage, with blood taken every 5 min in the first hour and every 10 min in the second hour.</p> <p>Results</p> <p>Including 3% glucose in the beverage led to a significantly greater AUC 60 min (19640 ± 1252 δ‰ vs. VSMOW.60 min) than all trials. No carbohydrate (18381 ± 1198 δ‰ vs. VSMOW.60 min) had a greater AUC 60 min than a 6% (16088 ± 1359 δ‰ vs. VSMOW.60 min) and 9% beverage (13134 ± 1115 δ‰ vs. VSMOW.60 min); the 6% beverage had a significantly greater AUC 60 min than the 9% beverage. There was no difference in fluid delivery between the different sodium beverages.</p> <p>Conclusion</p> <p>In conclusion the present study showed that when carbohydrate concentration in an ingested beverage was increased above 6% fluid delivery was compromised. However, increasing the amount of sodium (0–60 mmol/L) in a 6% glucose beverage did not lead to increases in fluid delivery.</p

Beneficial Effects of Resistance Exercise on Glycemic Control Are Not Further Improved by Protein Ingestion

Purpose: To investigate the mechanisms underpinning modifications in glucose homeostasis and insulin sensitivity 24 h after a bout of resistance exercise (RE) with or without protein ingestion. Methods: Twenty-four healthy males were assigned to a control (CON; n = 8), exercise (EX; n = 8) or exercise plus protein condition (EX+PRO; n = 8). Muscle biopsy and blood samples were obtained at rest for all groups and immediately post-RE (75% 1RM, 8&times;10 repetitions of leg-press and extension exercise) for EX and EX+PRO only. At 24 h post-RE (or post-resting biopsy for CON), a further muscle biopsy was obtained. Participants then consumed an oral glucose load (OGTT) containing 2 g of [U-13C] glucose during an infusion of 6, 6-[2H2] glucose. Blood samples were obtained every 10 min for 2 h to determine glucose kinetics. EX+PRO ingested an additional 25 g of intact whey protein with the OGTT. A final biopsy sample was obtained at the end of the OGTT. Results: Fasted plasma glucose and insulin were similar for all groups and were not different immediately post- and 24 h post-RE. Following RE, muscle glycogen was 26&plusmn;8 and 19&plusmn;6% lower in EX and EX+PRO, respectively. During OGTT, plasma glucose AUC was lower for EX and EX+PRO (75.1&plusmn;2.7 and 75.3&plusmn;2.8 mmol&middot;L-1:120 min, respectively) compared with CON (90.6&plusmn;4.1 mmol&middot;L-1:120 min). Plasma insulin response was 13&plusmn;2 and 21&plusmn;4% lower for EX and CON, respectively, compared with EX+PRO. Glucose disappearance from the circulation was ~12% greater in EX and EX+PRO compared with CON. Basal 24 h post-RE and insulin-stimulated PAS-AS160/TBC1D4 phosphorylation was greater for EX and EX+PRO. Conclusions: Prior RE improves glycemic control and insulin sensitivity through an increase in the rate at which glucose is disposed from the circulation. However, co-ingesting protein during a high-glucose load does not augment this response at 24 h post-exercise in healthy, insulin-sensitive individuals

Validity and relative validity of a novel digital approach for 24-h dietary recall in athletes

BACKGROUND: We developed a digital dietary analysis tool for athletes (DATA) using a modified 24-h recall method and an integrated, customized nutrient database. The purpose of this study was to assess DATA’s validity and relative validity by measuring its agreement with registered dietitians’ (RDs) direct observations (OBSERVATION) and 24-h dietary recall interviews using the USDA 5-step multiple-pass method (INTERVIEW), respectively. METHODS: Fifty-six athletes (14–20 y) completed DATA and INTERVIEW in randomized counter-balanced order. OBSERVATION (n = 26) consisted of RDs recording participants’ food/drink intake in a 24-h period and were completed the day prior to DATA and INTERVIEW. Agreement among methods was estimated using a repeated measures t-test and Bland-Altman analysis. RESULTS: The paired differences (with 95% confidence intervals) between DATA and OBSERVATION were not significant for carbohydrate (10.1%, -1.2–22.7%) and protein (14.1%, -3.2–34.5%) but was significant for energy (14.4%, 1.2–29.3%). There were no differences between DATA and INTERVIEW for energy (-1.1%, -9.1–7.7%), carbohydrate (0.2%, -7.1–8.0%) or protein (-2.7%, -11.3–6.7%). Bland-Altman analysis indicated significant positive correlations between absolute values of the differences and the means for OBSERVATION vs. DATA (r = 0.40 and r = 0.47 for energy and carbohydrate, respectively) and INTERVIEW vs. DATA (r = 0.52, r = 0.29, and r = 0.61 for energy, carbohydrate, and protein, respectively). There were also wide 95% limits of agreement (LOA) for most method comparisons. The mean bias ratio (with 95% LOA) for OBSERVATION vs. DATA was 0.874 (0.551-1.385) for energy, 0.906 (0.522-1.575) for carbohydrate, and 0.895(0.395-2.031) for protein. The mean bias ratio (with 95% LOA) for INTERVIEW vs. DATA was 1.016 (0.538-1.919) for energy, 0.995 (0.563-1.757) for carbohydrate, and 1.031 (0.514-2.068) for protein. CONCLUSION: DATA has good relative validity for group-level comparisons in athletes. However, there are large variations in the relative validity of individuals’ dietary intake estimates from DATA, particularly in athletes with higher energy and nutrient intakes. DATA can be a useful athlete-specific, digital alternative to conventional 24-h dietary recall methods at the group level. Further development and testing is needed to improve DATA’s validity for estimations of individual dietary intakes

Training with low muscle glycogen enhances fat metabolism in well-trained cyclists

Purpose: To determine the effects of training with low muscle glycogen on exercise performance, substrate metabolism, and skeletal muscle adaptation. Methods: Fourteen well-trained cyclists were pair-matched and randomly assigned to HIGH-or LOW-glycogen training groups. Subjects performed nine aerobic training (AT; 90 min at 70% (V) over dotO(2max)) and nine high-intensity interval training sessions (HIT; 8 x 5-min efforts, 1-min recovery) during a 3-wk period. HIGH trained once daily, alternating between AT on day 1 and HIT the following day, whereas LOW trained twice every second day, first performing AT and then, 1 h later, performing HIT. Pretraining and posttraining measures were a resting muscle biopsy, metabolic measures during steady-state cycling, and a time trial. Results: Power output during HIT was 297 +/- 8 W in LOW compared with 323 +/- 9 W in HIGH (P < 0.05); however, time trial performance improved by similar to 10% in both groups (P < 0.05). Fat oxidation during steady-state cycling increased after training in LOW (from 26 +/- 2 to 34 +/- 2 mu mol.kg(-1).min(-1), P < 0.01). Plasma free fatty acid oxidation was similar before and after training in both groups, but muscle-derived triacylglycerol oxidation increased after training in LOW (from 16 +/- 1 to 23 +/- 1 mu mol.kg(-1).min(-1), P < 0.05). Training with low muscle glycogen also increased beta-hydroxyacyl-CoA-dehydrogenase protein content (P < 0.01). Conclusions: Training with low muscle glycogen reduced training intensity and, in performance, was no more effective than training with high muscle glycogen. However, fat oxidation was increased after training with low muscle glycogen, which may have been due to the enhanced metabolic adaptations in skeletal muscle

Effect of Intensive Training on Mood With No Effect on Brain-Derived Neurotrophic Factor

Purpose Monitoring mood state is a useful tool for avoiding non-functional overreaching (NFOR). Brain derived neurotrophic factor (BDNF) is implicated in stress-related mood disorders. The purpose of the present study was to investigate the impact of intensified training-induced mood disturbance on plasma BDNF concentrations at rest and in response to exercise.&nbsp; Methods Eight cyclists performed 1 week of normal (NT), 1 week of intensified (INT) and 1 week of recovery (REC) training. Fasted blood samples were collected before and after exercise, on day 7 of each training week and were analyzed for plasma BDNF and cortisol concentrations. A 24-item Profile Of Mood State questionnaire was administered on day 7 of each training week and global mood score (GMS) was calculated. Results Time trial performance was impaired during INT (p=0.01) and REC (p=0.02) compared with NT. Basal plasma cortisol (NT=153&plusmn;16 ng/ml, INT=130&plusmn;11 ng/ml, REC=150&plusmn;14 ng/ml) and BDNF (NT=484&plusmn;122 pg/ml, INT=488&plusmn;122 pg/ml, REC=383&plusmn;56 pg/ml) concentrations were similar between training conditions. Likewise, similar exercise-induced increases in cortisol and BDNF concentrations were observed between training conditions. GMS was 32% greater during INTvs.NT (P&lt;0.001). Conclusion Consistent with a state of functional overreaching (FOR), impairments in performance and mood state with INT were restored after one week of REC. These results support evidence that mood changes before plasma BDNF concentrations as a biochemical marker of FOR and that cortisol is not a useful marker for predicting FOR