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Compared with adult athletes, rather little is known about supplementation behavior in adolescent athletes. This study’s aim was to determine elite adolescent athletes’ supplement use and sources of information relating thereto. A total of 430 (87%) of 496 questioned athletes returned the anonymized questionnaire. Thereof, 84% consumed at least one weekly supplement and 97% indicated some supplement intake during the previous 4 weeks. On average, 13.3 supplement servings were consumed per week. The 25th, 50th, and 75th percentile was 4.5, 10.5, and 20.0 servings per week, with a maximum of 67. The most prevalent supplements in use were multimineral products (41% of all athletes), multivitamins (34%), Vitamin C (34%), and Vitamin D (33%). Male athletes consumed significantly more Vitamin C and D, sports drinks, protein powder, and recovery products compared with female athletes; whereas, women consumed more iron supplements. The three most important motives for supplement use were recovery support (40%), health maintenance (39%), and performance enhancement (30%). The most frequent answers to the question “who recommended that you use supplements” were family/friends (36%), a physician (27%), and a trainer/coach (25%). The main three information sources about the supplements in use were the persons who recommended the supplementation (56%), the internet (25%), and information provided by supplement suppliers (11%). A positive doping attitude was associated with the consumption of performance enhancing supplements (p = .017). In conclusion, this study among elite adolescent Swiss athletes indicates a widespread and large-scale use of dietary supplements, which was associated with a low level of information quality.

The syndrome of Relative Energy Deficiency in Sport (RED-S) includes wide-ranging effects on physiological and psychological functioning, performance, and general health. However, RED-S is understudied among male athletes at the highest performance levels. This cross-sectional study aimed to investigate surrogate RED-S markers prevalence in Norwegian male Olympic-level athletes. Athletes (n = 44) aged 24.7 ± 3.8 years, body mass 81.3 ± 15.9 kg, body fat 13.7% ± 5.8%, and training volume 76.1 ± 22.9 hr/month were included. Assessed parameters included resting metabolic rate (RMR), body composition, and bone mineral density by dual-energy X-ray absorptiometry and venous blood variables (testosterone, free triiodothyronine, cortisol, and lipids). Seven athletes (16%) grouped by the presence of low RMR (RMR_ratio < 0.90) (0.81 ± 0.07 vs. 1.04 ± 0.09, p < .001, effect size 2.6), also showed lower testosterone (12.9 ± 5.3 vs. 19.0 ± 5.3 nmol/L, p = .020) than in normal RMR group. In low RMR_ratio individuals, prevalence of other RED-S markers (—subclinical—low testosterone, low free triiodothyronine, high cortisol, and elevated low-density lipoprotein) was (N/number of markers): 2/0, 2/1, 2/2, 1/3. Low bone mineral density (z-score < −1) was found in 16% of the athletes, all with normal RMR. Subclinical low testosterone and free triiodothyronine levels were found in nine (25%) and two (5%) athletes, respectively. Subclinical high cortisol was found in 23% of athletes while 34% had elevated low-density lipoprotein cholesterol levels. Seven of 12 athletes with two or more RED-S markers had normal RMR. In conclusion, this study found that multiple RED-S markers also exist in male Olympic-level athletes. This highlights the importance of regular screening of male elite athletes, to ensure early detection and treatment of RED-S.

Weight cycling is thought to increase the risk of obesity and cardiometabolic disease in nonathletic and athletic populations. However, the magnitude and frequency of weight cycling is not well characterized in elite athletes. To this end, we quantified the weight cycling practices of a male World Champion professional boxer competing at super middleweight (76.2 kg). Over a 5-year period comprising 11 contests, we assessed changes in body mass (n = 8 contests) and body composition (n = 6 contests) during the training camp preceding each contest. Time taken to make weight was 11 ± 4 weeks (range: 4–16). Absolute and relative weight loss for each contest was 12.4 ± 2.1 kg (range: 9.8–17.0) and 13.9% ± 2.0% (range: 11.3–18.2), respectively. Notably, the athlete commenced each training camp with progressive increases in fat mass (i.e., 12.5 and 16.1 kg for Contests 1 and 11) and reductions in fat-free mass (i.e., 69.8 and 67.5 kg for Contests 1 and 11, respectively). Data suggest that weight cycling may lead to “fat overshooting” and further weight gain in later life. Larger scale studies are now required to characterize the weight cycling practices of elite athletes and robustly assess future cardiometabolic disease risk. From an ethical perspective, practitioners should be aware of the potential health consequences associated with weight cycling.

This study determined the influence of a high- (HI) versus low-intensity (LI) cycling warm-up on blood acid-base responses and exercise capacity following ingestion of sodium bicarbonate (SB; 0.3 g/kg body mass) or a placebo (PLA; maltodextrin) 3 hr prior to warm-up. Twelve men (21 ± 2 years, 79.2 ± 3.6 kg body mass, and maximum power output [W _max] 318 ± 36 W) completed a familiarization and four double-blind trials in a counterbalanced order: HI warm-up with SB, HI warm-up with PLA, LI warm-up with SB, and LI warm-up with PLA. LI warm-up was 15 min at 60% W _max, while the HI warm-up (typical of elites) featured LI followed by 2 × 30 s (3-min break) at W _max, finishing 30 min prior to a cycling capacity test at 110% W _max. Blood bicarbonate and lactate were measured throughout. SB supplementation increased blood bicarbonate (+6.4 mmol/L; 95% confidence interval, CI [5.7, 7.1]) prior to greater reductions with HI warm-up (−3.8 mmol/L; 95% CI [−5.8, −1.8]). However, during the 30-min recovery, blood bicarbonate rebounded and increased in all conditions, with concentrations ∼5.3 mmol/L greater with SB supplementation (p < .001). Blood bicarbonate significantly declined during the cycling capacity test at 110%W _max with greater reductions following SB supplementation (−2.4 mmol/L; 95% CI [−3.8, −0.90]). Aligned with these results, SB supplementation increased total work done during the cycling capacity test at 110% W _max (+8.5 kJ; 95% CI [3.6, 13.4], ∼19% increase) with no significant main effect of warm-up intensity (+0.0 kJ; 95% CI [−5.0, 5.0]). Collectively, the results demonstrate that SB supplementation can improve HI cycling capacity irrespective of prior warm-up intensity, likely due to blood alkalosis.

This study compared the acute and chronic impact of citrulline malate (CM) supplementation on muscle contractile properties and fatigue rate of the quadriceps. Eighteen recreationally trained males consumed both a placebo (PL) and CM treatment for two separate dosing periods. The first experimental testing session for each dosing period was considered the baseline day, the second session the acute day, and the third session the chronic day, which followed seven consecutive days of supplementation. All testing sessions included exercising on a cycle ergometer at 50%–60% of their max power output for 30 min followed by performing the Thorstensson test on an isokinetic dynamometer. A two-way (Supplement × Time) analysis of variance with repeated measures resulted in no significant interactions (p > .05) (PL: baseline day, acute day, chronic day vs. CM: baseline day, acute day, chronic day) for peak power (in watts) (469 ± 81, 490 ± 97, 502 ± 99 vs. 464 ± 85, 480 ± 103, 501 ± 81); peak torque (in newton meters) (150 ± 26, 157 ± 32, 161 ± 31 vs. 149 ± 27, 156 ± 33, 161 ± 26); fatigue rate (in percentage) (57 ± 9, 57 ± 10, 58 ± 9 vs. 57 ± 10, 56 ± 9, 58 ± 9); and heart rate (in beats per minute) (156 ± 17, 146 ± 13, 146 ± 9 vs. 155 ± 11, 146 ± 11, 146 ± 9). The results of this study suggest that neither acute nor chronic supplementation of CM had an effect on recovery or fatigue rate of the quadriceps.

Urine specific gravity (USG) thresholds are used in practice and research to determine hypohydration. However, some limited research has found that body size and body composition may impact USG, suggesting that fixed cutoffs may be insensitive. Cross-sectional data from 3,634 participants of the 2007–2008 National Health and Nutrition Examination Survey were analyzed. Along with USG, body mass index (BMI), estimated lean body mass (LBM), and dietary intake were quantified. Logistic regression models were used to evaluate whether higher quintiles of BMI and LBM were associated with elevated USG (USG ≥ 1.020 and ≥1.025) after accounting for dietary moisture and sodium. The USG (1.018 ± 0.0003 vs. 1.015 ± 0.0004); BMI (28.4 ± 0.2 vs. 28.0 ± 0.2 kg/m²); LBM (60.9 ± 0.3 vs. 42.2 ± 0.2 kg); dietary moisture (3,401 ± 92 vs. 2,759 ± 49 g/day); and dietary sodium (4,171 ± 85 vs. 2,959 ± 50) were greater in men than in women (p < .05). Men and women in the fifth quintiles of BMI or LBM (vs. Quintile 1) had greater odds (2.00–3.68, p < .05) of elevated USG. (The only exception was for the association between BMI and USG ≥ 1.025 in men.) Being in Quintile 4 of LBM or BMI (vs. Quintile 1) also tended to be associated with higher odds of elevated of USG, though this pattern was more consistent when using USG ≥ 1.020 than USG ≥ 1.025. In summary, BMI and LBM are associated with USG at the population level. These results affirm that USG depends on body size and composition and raise questions about using fixed USG thresholds for determining hypohydration, particularly for people in the upper quintiles of BMI and LBM.

Supplementing postexercise carbohydrate (CHO) intake with protein has been suggested to enhance recovery from endurance exercise. The aim of this study was to investigate whether adding protein to the recovery drink can improve 24-hr recovery when CHO intake is suboptimal. In a double-blind crossover design, 12 trained men performed three 2-day trials consisting of constant-load exercise to reduce glycogen on Day 1, followed by ingestion of a CHO drink (1.2 g·kg⁻¹·2 hr⁻¹) either without or with added whey protein concentrate (CHO + PRO) or whey protein hydrolysate (CHO + PROH) (0.3 g·kg⁻¹·2 hr⁻¹). Arterialized blood glucose and insulin responses were analyzed for 2 hr postingestion. Time-trial performance was measured the next day after another bout of glycogen-reducing exercise. The 30-min time-trial performance did not differ between the three trials (M ± SD, 401 ± 75, 411 ± 80, 404 ± 58 kJ in CHO, CHO + PRO, and CHO + PROH, respectively, p = .83). No significant differences were found in glucose disposal (area under the curve [AUC]) between the postexercise conditions (364 ± 107, 341 ± 76, and 330 ± 147, mmol·L⁻¹·2 hr⁻¹, respectively). Insulin AUC was lower in CHO (18.1 ± 7.7 nmol·L⁻¹·2 hr⁻¹) compared with CHO + PRO and CHO + PROH (24.6 ± 12.4 vs. 24.5 ± 10.6, p = .036 and .015). No difference in insulin AUC was found between CHO + PRO and CHO + PROH. Despite a higher acute insulin response, adding protein to a CHO-based recovery drink after a prolonged, high-intensity exercise bout did not change next-day exercise capacity when overall 24-hr macronutrient and caloric intake was controlled.