Body composition measurements remain one of the best objective ways to analyze tissue distribution in athletes. The purpose of this study was to establish an average body composition profile for professional male ice hockey players, assess the yearly fluctuations of body composition after a single season, and assess body composition changes among different positions. Body composition was measured using dual-energy X-ray absorptiometry in 36 professional male ice hockey players. Descriptive statistics were used to determine average values. A paired samples t-test was applied to determine differences over a one-year period. A one-way analysis of variance was used to determine differences between positions, at both time points. Alpha levels were set a priori at p<0.05. Significant increases were observed in percent body fat across time points for all positions (p=0.019). There were significant differences in percent body fat between positions played (p=0.012) after one year. We demonstrated that there was low variability among the different positions in professional male ice hockey players. Additionally, we observed how a single year minimally influences changes in body composition. More research is required to evaluate body composition in male ice hockey players.

BackgroundExercise is primarily sustained by energy derived from lipids (plasma free fatty acids and intramuscular triglycerides), and glucose (plasma glucose and muscle glycogen). Substrate utilization is the pattern by which these fuel sources are used during activity. There are many factors that influence substrate utilization. We aim to delineate the effect of exercise intensity and body composition on substrate utilization.ObjectiveThe objective of our study was to discern the differences in substrate utilization profiles during a maximal and submaximal graded exercise test, and to determine the extent to which body composition influences substrate utilization during the exercise tests.MethodsA total of 27 male athletes, 32.5 ± 11 years of age, were recruited for this study. Body composition was analyzed using a bioelectrical impedance analyzer. Maximal and submaximal exercise tests were performed on a treadmill. A novel graded submaximal treadmill protocol was used for the submaximal test.ResultsAverage percent body fat (PBF) was 15.8 ± 5%. Average maximal oxygen consumption (VO2max) was 47.6 ± 9 mL/kg/min, while the average exercise intensity (percent VO2max) at which participants were shifting to glucose predominance for energy during the maximal and submaximal tests were 76 ± 8.3% and 58.4 ± 21.1%, respectively. A paired-samples t-test was conducted to compare percent VO2max at crossover point in maximal and submaximal graded exercise tests. There was a significant difference in percent VO2max at the crossover point for maximal (76 ± 8.3%) and submaximal (58 ± 21.1%) tests (t = 4.752, p = 0.001). A linear regression was performed to elucidate the interaction between exercise intensity at the crossover point and body composition during a maximal and submaximal graded exercise test. There was a significant effect of PBF on percent VO2max at crossover point during the maximal graded exercise test [F(1,24) = 9.10, P = 0.006] with an R2 of 0.245. However, there was no significant effect of PBF on percent VO2max at crossover point during the submaximal graded exercise test (P &gt; 0.05).ConclusionSubstrate utilization, represented by the crossover point, is dependent on the rate of increase in exercise intensity. At maximal efforts, the crossover to carbohydrates from fats as the predominant fuel source occurs at a significantly later stage of percent VO2max than at submaximal efforts. Furthermore, body composition represented by PBF is a significant predictor of substrate utilization during maximal efforts. Athletes with a relatively higher PBF are more likely to have increased lipid oxidation during high intensity exercises than those with a lower body fat percentage.

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ObjectiveIn our cross-sectional study, we evaluated micronutrient supplementation intake among Collegiate and Masters Athletes.MethodsWe conducted a cross-sectional study to assess micronutrient supplementation consumption in Collegiate and Masters Athletes, comparing sex and sport classification within each respective group. Micronutrient supplement consumption data were measured using a Food Frequency Questionnaire. A two-way analysis of variance was used to explore the differences among Collegiate and Masters Athletes' supplement intakes of the following vitamins and minerals: vitamins A, B6, B12, C, E, D, and calcium, folate, iron, magnesium niacin, riboflavin, selenium, thiamine, and zinc. When significant differences were found, a Bonferroni post hoc test was performed to identify specific group differences. The significance level was set a priori at p &lt; 0.05.ResultsA total of 198 athletes (105 females and 93 males) were included in the study. Participants were 36.16 ± 12.33 years of age. Collegiate male athletes had significantly greater vitamin A [1,090.51 ± 154.72 vs. 473.93 ± 233.18 mg retinol activity equivalents (RAE)/day] (p &lt; 0.036), folate [337.14 ± 44.79 vs. 148.67 ± 67.50 mcg dietary folate equivalents (DFE)/day] (p &lt; 0.027), and magnesium (65.35 ± 8.28 vs. 31.28 ± 12.48 mg/day) (p &lt; 0.031) intakes compared to Collegiate female athletes. Collegiate CrossFit Athletes (940.71 ± 157.54 mg/day) had a significantly greater vitamin C intake compared to Collegiate General Athletes (156.34 ± 67.79 mg/day) (p &lt; 0.005), Collegiate Triathletes (88.57 ± 148.53 mg/day) (p &lt; 0.027), Collegiate Resistance Training Athletes (74.28 ± 143.81 mg/day) (p &lt; 0.020), and Collegiate Powerlifters (175.71 ± 128.63 mg/day) (p &lt; 0.044). Masters females had significantly greater calcium intakes compared to Masters males (494.09 ± 65.73 vs.187.89 ± 77.23 mg/day, respectively) (p &lt; 0.002). Collegiate Runners (41.35 ± 6.53 mg/day) had a significantly greater iron intake compared to Collegiate Powerlifters (4.50 ± 6.53 mg/day) (p &lt; 0.024). Masters Swimmers (61.43 ± 12.10 mg/day) had significantly greater iron intakes compared to Masters General Athletes (13.97 ± 3.56 mg/day) (p &lt; 0.014), Masters Runners (17.74 ± 2.32 mg/day) (p &lt; 0.03), Masters Triathletes (11.95 ± 3.73 mg/day) (p &lt; 0.008), Masters CrossFit Athletes (15.93 ± 5.36 mg/day) (p &lt; 0.043), Masters Rowers (9.10 ± 3.36 mg/day) (p &lt; 0.003), and Masters Cyclists (1.71 ± 9.88 mg/day) (p &lt; 0.011). Masters Powerlifters (47.14 ± 9.65 mg/day) had significantly greater zinc intakes compared to Masters General Athletes (9.57 ± 2.84 mg/day) (p &lt; 0.015), Masters Runners (10.67 ± 1.85 mg/day) (p &lt; 0.017), Masters Triathletes (10.24 ± 2.98 mg/day) (p &lt; 0.020), Masters Rowers (9.33 ± 2.68 mg/day) (p &lt; 0.013), and Masters Cyclists (1.43 ± 7.88 mg/day) (p &lt; 0.019). There were no other significant differences among the other micronutrient supplement intakes between the sexes or among the sport classification.ConclusionWe reported significant differences among female and male Collegiate and Masters Athletes. Additionally, we reported significant differences among Collegiate and Masters Athletes sport classifications. Further research should examine both dietary and micronutrient supplement intake among Collegiate and Masters Athletes to examine the extent that athletes exceed the Recommended Dietary Allowances (RDA), and the potential effects on health and performance.

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Recommendations for protein intake are based on total body weight; however, these recommendations do not consider lean body mass (LBM). The purpose of the present study was to identify the average protein intake in g/kg LBM in a group of healthy Masters Athletes (≥26 years of age, exercising ≥2 d/week). Data were obtained from a cross-sectional study. Body weight (kg), height (cm) and LBM via dual-energy X-ray absorptiometry were measured. Dietary intake was measured using a 2005 Block Food Frequency Questionnaire. The average energy intake, the percent energy from protein and the average protein intake in g/kg LBM were calculated. Differences between protein intake and the US Recommended Dietary Allowance (US RDA) (0⋅8 g/kg body weight) were determined. Alpha levels were set a priori to P < 0⋅05. A total of 176 participants (94 women, 82 men; 39 ± 11 years of age; body mass index: 24⋅6 ± 3⋅4 kg/m2) were analysed. The average energy intake, the percent protein energy and the average protein intake were 7996⋅9 ± 110⋅9 kilojoules (kJ)/d (1,910⋅4 ± 26⋅5 kcal), 15⋅5 ± 2⋅6 % and 1⋅43 ± 0⋅53 g/kg LBM, respectively. No differences existed between women and men for protein intake/kg LBM. Both sexes had significantly higher protein intakes than the US RDA (P < 0⋅001). We identified the average protein intake (g/kg LBM) in healthy Masters Athletes that may contribute to evolving perspectives on the determination of protein needs. The present study helps establish the relationship between protein intake and LBM so that we may further increase our accuracy when developing future protein recommendations.