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Diane E. Butterworth, David C. Nieman, Janice V. Butler and Jodi L. Herring

A group of marathon runners (290 males, 54 females, mean age 39.7 ± 0.7 years) who participated in the Los Angeles Marathon recorded their food and fluid intake throughout a 3-day period, with the time of day denoted for each entry. Investigators coded each subject's food intake according to six time periods: 5:OO-8:59 a.m., 9:00-1059 a.m., 11:OO a.m.-1:59 p.m., 2:00-359 p.m., 4:0&7:59 p.m., and 8:00 p.m.459 a.m. The average intake of the runners consisted of 314 ± 6 g (52.3%) carbohydrates, 83.2 + 2.0 g (30.7%) fat, and 99.7 ± 2.3 g (16.5%) protein. Time periods for breakfast (13.7%), lunch (23.8%), and supper (34.0%) accounted for 71.5% of total caloric intake, with snack time periods contributing 28.5%. Breakfast calories were 68.9 ± 0.9% carbohydrate and 20.4 + 0.7% fat in contrast to supper calories, which were 47.7 ± 0.8% and 31.8 ± 0.6%, respectively. A sizable proportion of the daily caloric intake of recreational marathon runners is contributed by snacks and food intake after 4:00 p.m.

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Jennifer M. Sacheck, Helen M. Rasmussen, Meghan M. Hall, Tamar Kafka, Jeffrey B. Blumberg and Christina D. Economos

To investigate the association between pregame snacks varying in macronutrient content and exercise intensity, physiological stress, and fatigue in young soccer players. One hour before a 50-min soccer game, children (n = 79; 9.1 ± 0.8 y) were randomly assigned to consume a raisin-, peanut-butter-, or cereal-based snack. Body mass index, blood glucose, and salivary measures of stress (cortisol and immunoglobulin A-IgA) were measured pre- and post-game. Exercise intensity was measured by accelerometry. Self-administered questionnaires were used to assess diet quality and fatigue. Analysis of covariance was used to examine the relationship between pregame snacks and biochemical outcomes. Postgame glucose and cortisol increased [12.9 ± 21.3 mg/dL (p < .001) and 0.04 ± 0.10 μg/dL (p < .05), respectively] and IgA decreased −2.3 ± 9.6 μg/mL; p < .001) from pregame values. The pregame snack was not associated with exercise intensity or post-game outcome; however, children consuming the cereal-based (high-sugar and high-glycemic index (GI)) snack exercised more intensely than the 2 lower-GI snack groups (p < .05). Children who consumed the high-sugar, high-GI snack also reported more symptoms of fatigue (p < .05). A high-sugar, high-GI pregame snack was associated with exercise intensity and fatigue but not changes in blood sugar or stress biomarkers following a soccer game in children.

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Kelly Anne Erdman, Jasmine Tunnicliffe, Victor M. Lun and Raylene A. Reimer

The purpose of this study was to determine the meal- and snack-eating frequency and the nutritional composition of each eating occasion of Canadian high-performance athletes during training. Athletes from 8 Canadian Sport Centres prospectively completed 3-d dietary records including all food, fluid, and supplements consumed. The time of consumption and whether the consumption was a meal or snack were also identified. The dietary records were analyzed for energy (kcal) and macronutrient intake (carbohydrate, protein, and fat) and compared based on gender, age, meal vs. snack, and training vs. rest days. Three hundred twenty-four athletic subjects (64% female and 36% male) completed the study. On average, the athletes ate 4.8 ± 0.8 times daily. Nearly all athletes consumed 3 daily meals of breakfast (98.9%), lunch (97.9%), and dinner (98.7%), with few having snacks: 57%, 71.6%, and 58.1% of athletes consumed an a.m., p.m., and evening snack, respectively. Training-day meal frequency did not differ from that during rest days; however, fewer snacks were consumed on rest days. A.m. and p.m. snacks were consumed significantly more often on training days than rest days. Overall, snacks contributed 24.3% of total daily energy intake. Few dietary variations were discovered between genders, while the youngest athletes (<18 yr) ate less often, especially their morning snack, than the older athletes. In conclusion, Canadian high-performance athletes self-adjusted their energy intakes on training vs. rest days primarily by snacking less and reducing their carbohydrate and protein intakes on rest days, yet they consistently ate regular meals.

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Heidi K. Byrne, Yeonsoo Kim, Steven R. Hertzler, Celia A. Watt and Craig O. Mattern


To compare serum glucose and insulin responses to 3 preexercise snacks before, during, and after exercise in individuals with impaired fasting glucose (IFG) and healthy (H) men. In addition, in an IFG population, the authors sought to determine whether a natural fruit snack (i.e., raisins) yields more desirable glucose and insulin concentrations than an energy bar or a glucose solution.


The IFG (n = 11, age = 54.5 ± 1.3 yr, fasting blood glucose [BG] = 6.3 ± 0.1 mmol/L) and H groups (n = 9, age = 48.0 ± 3.1 yr, fasting BG = 4.9 ± 0.1 mmol/L) cycled at 50% of VO2peak for 45 min on 4 occasions after consuming water or 50 g of carbohydrate from raisins (R), an energy bar (EB), or a glucose beverage (GLU). Metabolic markers were measured before, during, and after exercise.


In all nutritional conditions, glucose concentrations of the IFG group were consistently higher than in the H group. Differences between IFG and H groups in insulin concentrations were sporadic and isolated. In the IFG group, preexercise glucose concentration was lower in the R condition than in GLU. Ten and 20 min into exercise, glucose concentrations in the R and EB conditions were lower than in GLU. Insulin concentrations were lower in the R condition than in EB and GLU immediately before exercise and at Minute 10 but at 20 min R remained lower than only GLU.


Glucose concentrations were higher in the IFG group regardless of preexercise snack. Compared with the glucose solution, raisins lowered both the postprandial glycemic and insulinemic responses, whereas the energy bar reduced glycemia but not insulinemia.

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Willeke Trompers, Tracy L Perry, Meredith C Rose and Nancy J. Rehrer

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; VO2max 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; VO2max 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.

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Kim Beals, Katherine A. Perlsweig, John E. Haubenstriker, Mita Lovalekar, Chris P. Beck, Darcie L. Yount, Matthew E. Darnell, Katelyn Allison and Bradley C. Nindl

macronutrient intake and potentially impaired performance and recovery. Further research is warranted to investigate the unique physiological demands and nutritional requirements, including meal/snack timing associated with specific military training operations in challenging environmental conditions. The

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Eric Kyle O’Neal, Samantha Louise Johnson, Brett Alan Davis, Veronika Pribyslavska and Mary Caitlin Stevenson-Wilcoxson

beverage types were consumed in all studies. Participants ate dinner and an evening snack in all studies, and three studies included light snacks or a modest breakfast. Fifty-eight (44%) samples were collected after breakfast, and the remaining voids ( n  = 74; 56%) were collected upon waking. All fluids

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Guadalupe Garrido, Anthony L Webster and Manuel Chamorro

The article describes a study that evaluated the adequacy of 2 different menu settings in a group of elite adolescent Spanish soccer players. Five-day food intake was assessed on 2 occasions, while athletes were consuming a flexible “buffet-style” diet (B; n = 33) and a fixed “menu-style” diet (M; n = 29). For all principal meals of the day food weighing was performed, and snacks were recorded by self-report. M provided significantly higher total energy and carbohydrate intakes than B. Breakfast and snacks both provided more energy in M. Calories obtained from fat were excessive in both settings. Calcium and vitamin D were below recommendations in B but not in M. Fiber, magnesium, folate, vitamin A, and vitamin E intake fell below recommended values in both settings. M provided significantly greater quantities of magnesium and vitamins D and E. Both feeding options were far from optimal in satisfying current scientifically based recommendations for active adolescents.

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Ellen Weissinger, Terry J. Housh and Glen O. Johnson

High school wrestling coaches (N=161) were surveyed concerning their perceptions of weight loss in wrestlers. Results indicated that a majority of coaches thought that wrestlers lose too much weight, and that only four weight loss methods (increased exercise, skipping snacks, eating smaller meals, counting calories) were endorsed as both effective and safe. However, the coaches also reported that they knew wrestlers engaged in unsafe weight loss methods, and a majority let the wrestler himself make decisions about minimal wrestling weight. The data were interpreted as reinforcing the need for responsible adult supervision of wrestling programs.

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Karen Reid

Flatwater kayaking requires upper-body muscle strength and a lean body composition. This case study describes a nutrition intervention with a 19-year-old male elite sprint kayaker to increase muscle mass and improve recovery posttraining. Before the intervention, average daily energy intake was 13.6 ± 2.5 MJ (M ± SD; protein, 1.8 g/kg; carbohydrate, 3.6 g/kg), and the athlete was unable to eat sufficient food to meet the energy demands of training. During the 18-month intervention period, the athlete’s daily energy intake increased to 22.1 ± 3.8 MJ (protein, 3.2 g/kg; carbohydrate, 7.7 g/kg) by including milk-based drinks pre- and posttraining and before bed and an additional carbohydrate-based snack midmorning. This simple dietary intervention, along with a structured strength and conditioning program, resulted in an increase of 10 kg body mass with minimal change in body fat percentage. Adequate vitamin D status was maintained without the need for supplementation during the intervention period. In addition, the athlete reported the milk-based drinks and carbohydrate snacks were easy to consume, and no adverse side effects were experienced. This was the first time the athlete was able to maintain weight during intensive phases of the training cycle.