Alannah K.A. McKay, Peter Peeling, David B. Pyne, Nicolin Tee, Marijke Welveart, Ida A. Heikura, Avish P. Sharma, Jamie Whitfield, Megan L. Ross, Rachel P.L. van Swelm, Coby M. Laarakkers, and Louise M. Burke
This study implemented a 2-week high carbohydrate (CHO) diet intended to maximize CHO oxidation rates and examined the iron-regulatory response to a 26-km race walking effort. Twenty international-level, male race walkers were assigned to either a novel high CHO diet (MAX = 10 g/kg body mass CHO daily) inclusive of gut-training strategies, or a moderate CHO control diet (CON = 6 g/kg body mass CHO daily) for a 2-week training period. The athletes completed a 26-km race walking test protocol before and after the dietary intervention. Venous blood samples were collected pre-, post-, and 3 hr postexercise and measured for serum ferritin, interleukin-6, and hepcidin-25 concentrations. Similar decreases in serum ferritin (17–23%) occurred postintervention in MAX and CON. At the baseline, CON had a greater postexercise increase in interleukin-6 levels after 26 km of walking (20.1-fold, 95% CI [9.2, 35.7]) compared with MAX (10.2-fold, 95% CI [3.7, 18.7]). A similar finding was evident for hepcidin levels 3 hr postexercise (CON = 10.8-fold, 95% CI [4.8, 21.2]; MAX = 8.8-fold, 95% CI [3.9, 16.4]). Postintervention, there were no substantial differences in the interleukin-6 response (CON = 13.6-fold, 95% CI [9.2, 20.5]; MAX = 11.2-fold, 95% CI [6.5, 21.3]) or hepcidin levels (CON = 7.1-fold, 95% CI [2.1, 15.4]; MAX = 6.3-fold, 95% CI [1.8, 14.6]) between the dietary groups. Higher resting serum ferritin (p = .004) and hotter trial ambient temperatures (p = .014) were associated with greater hepcidin levels 3 hr postexercise. Very high CHO diets employed by endurance athletes to increase CHO oxidation have little impact on iron regulation in elite athletes. It appears that variations in serum ferritin concentration and ambient temperature, rather than dietary CHO, are associated with increased hepcidin concentrations 3 hr postexercise.
S. Sofie Lövdal, Ruud J.R. Den Hartigh, and George Azzopardi
Purpose: Staying injury free is a major factor for success in sports. Although injuries are difficult to forecast, novel technologies and data-science applications could provide important insights. Our purpose was to use machine learning for the prediction of injuries in runners, based on detailed training logs. Methods: Prediction of injuries was evaluated on a new data set of 74 high-level middle- and long-distance runners, over a period of 7 years. Two analytic approaches were applied. First, the training load from the previous 7 days was expressed as a time series, with each day’s training being described by 10 features. These features were a combination of objective data from a global positioning system watch (eg, duration, distance), together with subjective data about the exertion and success of the training. Second, a training week was summarized by 22 aggregate features, and a time window of 3 weeks before the injury was considered. Results: A predictive system based on bagged XGBoost machine-learning models resulted in receiver operating characteristic curves with average areas under the curves of 0.724 and 0.678 for the day and week approaches, respectively. The results of the day approach especially reflect a reasonably high probability that our system makes correct injury predictions. Conclusions: Our machine-learning-based approach predicts a sizable portion of the injuries, in particular when the model is based on training-load data in the days preceding an injury. Overall, these results demonstrate the possible merits of using machine learning to predict injuries and tailor training programs for athletes.
Stephen S. Cheung
Lasse Ishøi, Kasper Krommes, Mathias F. Nielsen, Kasper B. Thornton, Per Hölmich, Per Aagaard, Juan J.J. Penalver, and Kristian Thorborg
Purpose: Increasing age, high quadriceps strength, and low hamstring muscle strength are associated with hamstring strain injury in soccer. The authors investigated the age-related variation in maximal hamstring and quadriceps strength in male elite soccer players from under-13 (U-13) to the senior level. Methods: A total of 125 elite soccer players were included from a Danish professional soccer club and associated youth academy (first tier; U-13, n = 19; U-14, n = 16; U-15, n = 19; U-17, n = 24; U-19, n = 17; and senior, n = 30). Maximal voluntary isometric force was assessed for the hamstrings at 15° knee joint angle and for the quadriceps at 60° knee joint angle (0° = full extension) using an external-fixated handheld dynamometer. Hamstring-to-quadriceps strength (H:Q) ratio and hamstring and quadriceps maximal voluntary isometric force levels were compared across age groups (U-13 to senior). Results: Senior players showed 18% to 26% lower H:Q ratio compared with all younger age groups (P ≤ .026). Specific H:Q ratios (mean [95% confidence interval]) were as follows: senior, 0.45 (0.42–0.48); U-19, 0.61 (0.55–0.66); U-17, 0.56 (0.51–0.60); U-15, 0.59 (0.54–0.64); U-14, 0.54 (0.50–0.59); and U-13, 0.57 (0.51–0.62). Hamstring strength increased from U-13 to U-19 with a significant drop from U-19 to the senior level (P = .048), whereas quadriceps strength increased gradually from U-13 to senior level. Conclusion: Elite senior soccer players demonstrate lower H:Q ratio compared with youth players, which is driven by lower hamstring strength at the senior level compared with the U-19 level combined with a higher quadriceps strength. This discrepancy in hamstring and quadriceps strength capacity may place senior-level players at increased risk of hamstring muscle strain injuries.
Sebastian Kaufmann, Olaf Hoos, Aaron Beck, Fabian Fueller, Richard Latzel, and Ralph Beneke
Purpose: To evaluate the metabolic relevance of type of locomotion in anaerobic testing by analyzing and comparing the metabolic profile of the Bosco Continuous Jumping Test (CJ30) with the corresponding profile of the Wingate Anaerobic Test (WAnT). Methods: A total of 11 well-trained, male team-sport athletes (age = 23.7 [2.2] y, height = 184.1 [2.8] cm, weight = 82.4 [6.4] kg) completed a CJ30 and WAnT each. During the WAnT, power data and revolutions per minute were recorded, and during the CJ30, jump height and jumping frequency were recorded. In addition, oxygen uptake and blood lactate concentration were assessed, and metabolic profiles were determined via the PCr-LA-O2 method. Results: In the CJ30, metabolic energy was lower (109.3 [18.0] vs 143.0 [13.1] kJ, P < .001, d = −2.302), while peak power (24.8 [4.4] vs 11.8 [0.5] W·kg−1, P < .001, d = 3.59) and mean power (20.8 [3.6] vs 9.1 [0.5] W·kg−1, P < .001, d = 4.14) were higher than in the WAnT. The metabolic profiles of the CJ30 (aerobic energy = 20.00% [4.7%], anaerobic alactic energy [W PCr] = 45.6% [4.5%], anaerobic lactic energy = 34.4% [5.2%]) and the WAnT (aerobic energy = 16.0% [3.0%], anaerobic alactic W PCr = 34.5% [5.0%], anaerobic lactic energy = 49.5% [3.3%]) are highly anaerobic. Absolute energy contribution for the CJ30 and WAnT was equal in W PCr (49.9 [11.1] vs 50.2 [11.2] kJ), but anaerobic lactic energy (37.7 [7.7] vs 69.9 [5.3] kJ) and aerobic energy (20.6 [5.7] vs 23.0 [4.0] kJ) were higher in the WAnT. Mechanical efficiency was substantially higher in the CJ30 (37.9% [4.5%] vs 15.6% [1.0%], P < .001, d = 6.86), while the fatigue index was lower (18.5% [3.8%] vs 23.2% [3.1%], P < .001, d = −1.38) than in the WAnT. Conclusions: Although the anaerobic share in both tests is similar and predominant, the CJ30 primarily taxes the W PCr system, while the WAnT more strongly relies on the glycolytic pathway. Thus, the 2 tests should not be used interchangeably, and the type of locomotion seems crucial when choosing an anaerobic test for a specific sport.
Laura Hottenrott, Sascha Ketelhut, Christoph Schneider, Thimo Wiewelhove, and Alexander Ferrauti
Postexercise recovery is a fundamental component for continuous performance enhancement. Due to physiological and morphological changes in aging and alterations in performance capacity, athletes of different ages may recover at different rates from physical exercise. Differences in body composition, physiological function, and exercise performance between men and women may also have a direct influence on restoration processes. Purpose: This brief review examines current research to indicate possible differences in recovery processes between male and female athletes of different age groups. The paper focuses on postexercise recovery following sprint and endurance tests and tries to identify determinants that modulate possible differences in recovery between male and female subjects of different age groups. Results: The literature analysis indicates age- and sex-dependent differences in short- and long-term recovery. Short-term recovery differs among children, adults, and masters. Children have shorter lactate half-life and a faster cardiac and respiratory recovery compared to adults. Additionally, children and masters require shorter recovery periods during interval bouts than trained adults. Trained women show a slower cardiac and respiratory recovery compared to trained men. Long-term recovery is strongly determined by the extent of muscle damage. Trained adults tend to have more extensive muscle damage compared to masters and children. Conclusion: The influence of age and sex on the recovery process varies among the different functional systems and depends on the time of the recovery processes. Irrespective of age and sex, the performance capacity of the individual determines the recovery process after high-intensity and endurance exercise.