Search Results

Effects of protein versus mixed macronutrient supplementation on total energy intake (TEI) and protein intake during an ad libitum diet were examined. Trained males undertook two, 2-week dietary interventions which were randomized, double blinded, and separated by 2 weeks. These were high-protein supplementation (HP: 1034.5 kJ energy, 29.6 g protein, 8.7 g fat and 12.3 g CHO) and standard meal supplementation (SM: 1039 kJ energy, 9.9 g protein, 9.5 g fat, and 29.4 g CHO) consumed daily following a week of baseline measures. Eighteen participants finished both interventions and one only completed HP. TEI (mean ± SD) was not different between baseline (11148 ± 3347 kJ) and HP (10705 ± 3143 kJ) nor between baseline and SM (12381 ± 3877 kJ), however, TEI was greater with SM than HP (923 ± 4015 kJ p = .043). Protein intake (%TEI) was greater with HP (22.4 ±6.2%) than baseline (19.4 ± 5.4%; p = .008) but not SM (20.0 ± 5.0%). No differences in absolute daily protein intake were found. Absolute CHO intake was greater with SM than HP (52.0 ± 89.5 g, p = .006). No differences in fat intake were found. Body mass did not change between baseline (82.7 ± 11.2 kg) and either HP (83.1 ± 11.7 kg) or SM (82.9 ± 11.0 kg). Protein supplementation increases the relative proportion of protein in the diet, but doesn’t increase the absolute amount of total protein or energy consumed. Thus some compensation by a reduction in other foods occurs. This is in contrast to a mixed nutrient supplement, which does not alter the proportion of protein consumed but does increase TEI.

Effects of feeding glucose on substrate metabolism during cycling were studied. Trained (60.0 ± 1.9 mL · kg⁻¹ · min⁻¹) males (N = 5) completed two 75 min, 80% VO_2max trials: 125 g ¹³C-glucose (CHO); ¹³C-glucose tracer, 10 g (C). During warm-up (30 min 30% VO_2max) 2 ⋅ 2 g ¹³C-glucose was given as bicarbonate pool primer. Breath samples and blood glucose were analyzed for ¹³C/ ¹²C with IRMS. Protein oxidation was estimated from urine and sweat urea. Indirect calorimetry (protein corrected) and ¹³C/ ¹²C enrichment in expired CO₂ and blood glucose allowed exogenous (G_exo), endogenous (G_endo), muscle (G_muscle), and liver glucose oxidation calculations. During exercise (75 min) in CHO versus C (respectively): protein oxidation was lower (6.8 ± 2.7, 18.8 ± 5.9 g; P = 0.01); G_endo was reduced (71.2 ± 3.8, 80.7 ± 5.7%; P = 0.01); G_muscle was reduced (55.3 ± 6.1, 65.9 ± 6.0%; P = 0.01) compensated by increased G_exo (58.3 ± 2.1, 3.87 ± 0.85 g; P = 0.000002). Glucose ingestion during exercise can spare endogenous protein and carbohydrate, in fed cyclists, without gly-cogen depletion.

Purpose: To examine the movement and physiological demands of rugby union officiating in elite competition. Methods: Movement demands of 9 elite officials across 12 Super Rugby matches were calculated, using global positioning system devices. Total distance (in m), relative distance (in m·min⁻¹), and percentage time spent in various speed zones were calculated across a match. Heart-rate (HR) responses were also recorded throughout each match. Cohen d effect sizes were reported to examine the within-match variations. Results: The total distance covered was 8030 (506) m, with a relative distance of 83 (5) m·min⁻¹ and with no differences observed between halves. Most game time was spent at lower movement speeds (76% [2%]; <2.0 m·s⁻¹), with large effects for time spent >7.0 m·s⁻¹ between halves (d = 2.85). Mean HR was 154 (10) beats·min⁻¹ (83.8 [2.9]%HR_max), with no differences observed between the first and second halves. Most game time was spent between 81%HR_max and 90%HR_max (40.5% [7.5%]) with no observable differences between halves. Distances covered above 5.1 m·s⁻¹ were highest during the first 10 min of a match, while distance at speeds 3.7 to 5 m·s⁻¹ decreased during the final 10 min of play. Conclusions: These findings highlight the highly demanding and intermittent nature of rugby union officiating, with only some minor variations in physical and physiological demands across a match. These results have implications for the physical preparation of professional rugby union referees.

This study examined the relationship between gastrointestinal (GI) symptoms and dietary intake in triathletes. Fifty-five male triathletes (age 31 ±6 yrs) were surveyed regarding the most recently completed half Iron Man triathlon. Questions were asked regarding GI symptoms and dietary intake. Fifty-two percent complained of eructation and 48% of flatulence. Other symptoms were abdominal bloating, vomiting urge, vomiting, nausea, stomachache, intestinal cramps, and diarrhea. More symptoms occurred while running than at other times. All individuals who had eaten within 30 min of the start vomited while swimming. Fat and protein intake was greater in those who vomited or had the urge to vomit than in those without these symptoms. Of the former, 93% had consumed a hypertonic beverage. Forty percent of those who drank a hypertonic beverage and only 11% of those who drank an iso-or hypotonic beverage had severe complaints. Four of five individuals with stomachache had consumed a strongly hypertonic beverage. All subjects with intestinal cramps had eaten fiber-rich foods in the pre race meal; only 10% of those without cramps had done so.

The purpose of this study was to determine whether glycemic index (GI) is influenced by training state. Participants were tested in a randomized order: twice with a reference solution containing 50 g glucose and once each with 2 commercially available snack bars (Griffin’s Fruitli bar and Peak Fuel’s Summit bar) containing 50 g available carbohydrate. Eleven of the participants (6 men and 5 women, M ± SD age 20.8 ± 2.0 yr) were endurance trained (ET; VO_2max 57.5 ± 8.4 ml · kg⁻¹ · min⁻¹), and 9 participants (2 men and 7 women, M ± SD age 22.4 ± 1.8 yr) were sedentary (SE; VO_2max 43.7 ± 9.1 ml · kg⁻¹ · min⁻¹). After an overnight fast, participants consumed either the glucose solution or snack bar, with blood samples taken before eating and at 15, 30, 45, 60, 90, and 120 min after eating began. The mean incremental area under the curve (IAUC) of the glucose reference was 31% lower (95% CI 3–52%, p = .03), and the Fruitli bar 38% lower (95% CI 0–61%, p = .05) in ET than in SE participants. There was a trend for the IAUC for the Summit bar to be 35% lower in ET than in SE participants (95% CI –7% to 61% p = .09). There was no significant interaction between training state and test food. The GIs of the Fruitli and Summit bars was not significantly different between ET and SE participants (p = .65 and .54, respectively). ET participants had a lower glycemic response than SE participants; however, training state did not influence GI.