Purpose: To determine whether menstrual-cycle symptoms are associated with sleep in elite female athletes. Methods: Sleep was assessed for a minimum of 25 nights (range = 25–31) using activity monitoring and sleep diaries. Menstrual-cycle symptoms were collected over the same duration in 12 elite female professional soccer players. Generalized estimating equations were used to examine the relationship between the day of the menstrual cycle (from day 1) and total menstrual-cycle symptoms on sleep characteristics. Results: There was a significant relationship between sleep duration and the day of the menstrual cycle (P = .042) and total symptoms reported that day (P < .001), with sleep duration increasing by 21 minutes for every symptom reported. There was a negative day × symptom interaction on sleep duration (P = .004), indicating that with increased symptoms, the day of the menstrual cycle had a smaller relationship with sleep duration. Sleep efficiency (P = .950), wake after sleep onset (P = .217), and subjective sleep quality (P = .080) were not related to the day of the menstrual cycle. The total symptoms reported had no relationship with sleep efficiency (P = .220), subjective sleep quality (P = .502), or sleep latency (P = .740) but did significantly relate to wake after sleep onset (P < .001), with a significant day × symptom interaction (P < .001). Conclusions: Sleep duration increased from day 1 of the menstrual cycle and was associated with the number of menstrual-cycle symptoms reported. All other sleep metrics remained unchanged; however, total symptoms reported were related to wake after sleep onset. Monitoring and managing menstrual-cycle symptoms should be encouraged due to a potential relationship with sleep characteristics.
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Menstrual-Cycle Symptoms and Sleep Characteristics in Elite Soccer Players
Shona L. Halson, Rich D. Johnston, Madison Pearson, and Clare Minahan
Optimization of Sprint Training Among European Coaches: Quality Over Quantity
Aarón Agudo-Ortega, Øyvind Sandbakk, Juan J. Salinero, Bjørn Johansen, and José M. González-Rave
Purpose: To describe how high-level European sprint coaches (from 100 to 400 m) work to improve important factors associated with the quality of the holistic training process and the quality of the specific training session. Methods: A descriptive analysis was conducted using questionnaires from 31 European elite sprint coaches (ie, training athletes defined as tiers 3, 4, and 5) who participated voluntarily. Results: The coaches used traditional periodization (45%) with a 10- to 15-day tapering phase (48%) that includes a reduction in volume, maintenance of intensity, and focus on correct technical execution. In the 3 mesophases, coaches prioritized the basic development of strength and sprint work in the first phases of the season and emphasized more sprint-specific work in the competitive phase. Before sessions, adjustments were made based on factors such as psychological (77%), technical (48%), and physical (39%) parameters. In-session load management relies on a combination of objective and subjective measures (55%), in which the dialogue with athletes (65%) was regarded as the main resource. Feedback during and after sessions covers technical (54%), psychological (48%), and physical (35%) aspects. Recovery protocols after sessions mainly involve rest and professional guidance (42%). For performance assessment and testing, coaches utilize countermovement jump (52%), force–velocity profile (45%), and 30-m flying (61%) as main tools. Conclusions: European sprint coaches demonstrated a comprehensive approach to planning and management, shedding light on the multifaceted nature of their training methodologies and the diverse tools employed for athlete testing and monitoring.
The Relationship Between the Moderate–Heavy Boundary and Critical Speed in Running
Ben Hunter, Samuel Meyler, Ed Maunder, Tobias H. Cox, and Daniel Muniz-Pumares
Purpose: Training characteristics such as duration, frequency, and intensity can be manipulated to optimize endurance performance, with an enduring interest in the role of training-intensity distribution to enhance training adaptations. Training intensity is typically separated into 3 zones, which align with the moderate-, heavy-, and severe-intensity domains. While estimates of the heavy- and severe-intensity boundary, that is, the critical speed (CS), can be derived from habitual training, determining the moderate–heavy boundary or first threshold (T1) requires testing, which can be costly and time-consuming. Therefore, the aim of this review was to examine the percentage at which T1 occurs relative to CS. Results: A systematic literature search yielded 26 studies with 527 participants, grouped by mean CS into low (11.5 km·h−1; 95% CI, 11.2–11.8), medium (13.4 km·h−1; 95% CI, 11.2–11.8), and high (16.0 km·h−1; 95% CI, 15.7–16.3) groups. Across all studies, T1 occurred at 82.3% of CS (95% CI, 81.1–83.6). In the medium- and high-CS groups, T1 occurred at a higher fraction of CS (83.2% CS, 95% CI, 81.3–85.1, and 84.2% CS, 95% CI, 82.3–86.1, respectively) relative to the low-CS group (80.6% CS, 95% CI, 78.0–83.2). Conclusions: The study highlights some uncertainty in the fraction of T1 relative to CS, influenced by inconsistent approaches in determining both boundaries. However, our findings serve as a foundation for remote analysis and prescription of exercise intensity, although testing is recommended for more precise applications.
Agreement Between the 2- and 3-Step Methods for Identifying Subtle Menstrual Disturbances
Dionne A. Noordhof, Madison Y. Taylor, Virginia De Martin Topranin, Tina P. Engseth, Øyvind Sandbakk, and John O. Osborne
Recent methodological recommendations suggest the use of the “3-step method,” consisting of calendar-based counting, urinary ovulation testing, and serum blood sampling, for the identification of subtle menstrual disturbances (SMDs). However, the use of the 3-step method is not always feasible, so a less demanding combination of calendar-based counting and urinary ovulation testing, that is, the 2-step method, may be a viable alternative. Purpose: To investigate the agreement between the 2- and 3-step methods for the detection of SMDs. Methods: Menstrual cycles (MCs, 98) of 59 athletes were assessed using the 2- and 3-step methods. Regular-length MCs (ie, ≥21 and ≤35 d) were classified as either having no SMD (luteal phase length ≥10 d, midluteal progesterone concentration ≥16 nmol·L−1, and being ovulatory) or having an SMD (eg, short luteal phase [<10 d], inadequate luteal phase [midluteal progesterone concentration <16 nmol·L−1], or being anovulatory). Method agreement was assessed using the McNemar test and Cohen kappa (κ). Results: Substantial agreement was observed between methods (κ = .72; 95% CI, .53–.91), but the 2-step method did not detect all MCs with an SMD, resulting in evidence of systematic bias (χ 2 = 5.14; P = .023). The 2-step method detected 61.1% of MCs that had an SMD ([51.4, 70.8]), as verified using the 3-step method, and correctly identified 100% of MCs without an SMD. Conclusions: MCs classified as being disturbed using the 2-step method could be considered valid evidence of SMDs. However, MCs classified without SMDs do not definitively confirm their absence, due to the proven underdetection via the 2-step method.
Gender Equity in Sport-Science Academia: We Still Have a Long Way to Go!
Sabrina Skorski and Silvana Bucher-Sandbakk
Hemodynamic Effects of Intermittent Pneumatic Compression on Athletes: A Double-Blinded Randomized Crossover Study
Filipe Maia, Marta V.B. Machado, Gustavo Silva, Fábio Yuzo Nakamura, and João Ribeiro
Purpose: There are multiple postexercise recovery technologies available in the market based on the assumption of blood-flow enhancement. Lower-limb intermittent pneumatic compression (IPC) has been widely used, but the available scientific evidence supporting its effectiveness remains scarce, requiring a deeper investigation into its underlying mechanisms. The aim of this study was to assess the hemodynamic effects caused by the use of IPC at rest. Methods: Twenty-two soccer and track and field athletes underwent two 15-minute IPC protocols (moderate- [80 mm Hg] and high-pressure [200 mm Hg]) in a randomized order. Systolic peak velocity, end-diastolic peak velocity, arterial diameter, and heart rate were measured before, during (at the eighth minute), and 2 minutes after each IPC protocol. Results: Significant effects were observed between before and during (eighth minute) the IPC protocol for measures of systolic (P < .001) and end-diastolic peak velocities (P < .001), with the greater effects observed during the high-pressure protocol. Moreover, 2 minutes after each IPC protocol, hemodynamic variables returned to values close to baseline. Arterial diameter presented significant differences between pressures during the IPC protocols (P < .05), while heart rate remained unaltered. Conclusion: IPC effectively enhances transitory blood flow of athletes, particularly when applying high-pressure protocols.
Kinetics, Kinematics, and Muscle Activity Patterns During Back Squat With Different Contributions of Elastic Resistance
Lin Shi, Mark Lyons, Michael Duncan, Sitong Chen, Dong Han, and Chengbo Yang
Purpose: Performing back squats with elastic bands has been widely used in resistance training. Although research demonstrated greater training effects obtained from adding elastic bands to the back squat, little is known regarding the optimal elastic resistance and how it affects neuromuscular performance. This study aimed to compare the force, velocity, power, and muscle activity during back squats with different contributions of elastic resistance. Methods: Thirteen basketball players performed 3 repetitions of the back squat at 85% of 1-repetition maximum across 4 conditions: (1) total load from free weight and (2) 20%, (3) 30%, and (4) 40% of the total load from elastic band and the remaining load from free weight. The eccentric and concentric phases of the back squat were divided into upper, middle, and bottom phases. Results: In the eccentric phase, mean velocity progressively increased with increasing elastic resistance, and muscle activity of the vastus medialis and rectus femoris significantly increased with the largest elastic resistance in the upper phase (P ≤ .036). In the concentric phase, mean power (P ≤ .021) and rate of force development (P ≤ .002) significantly increased with increasing elastic resistance. Furthermore, muscle activity of the vastus lateralis and vastus medialis significantly improved with the largest elastic resistance in the upper phases (P ≤ .021). Conclusion: Velocity, power, rate of force development, and selective muscle activity increased as the elastic resistance increased in different phases during the back-squat exercise.
How to Equalize High- and Low-Intensity Endurance Exercise Dose
Pekka Matomäki, Olli-Pekka Nuuttila, Olli J. Heinonen, Heikki Kyröläinen, and Ari Nummela
Purpose: Without appropriate standardization of exercise doses, comparing high- (HI) and low-intensity (LI) training outcomes might become a matter of speculation. In athletic preparation, proper quantification ensures an optimized stress-to-recovery ratio. This review aims to compare HI and LI doses by estimating theoretically the conversion ratio, 1:x, between HI and LI: How many minutes, x, of LI are equivalent to 1 minute of HI using various quantification methods? A scrutinized analysis on how the dose increases in relation to duration and intensity was also made. Analysis: An estimation was conducted across 4 categories encompassing 10 different approaches: (1) “arbitrary” methods, (2) physiological and perceptual measurements during exercise, (3) postexercise measurements, and comparison to (4a) acute and (4b) chronic intensity-related maximum dose. The first 2 categories provide the most conservative estimation for the HI:LI ratio (1:1.5–1:10), and the third, slightly higher (1:4–1:11). The category (4a) provides the highest estimation (1:52+) and (4b) suggests 1:10 to 1:20. The exercise dose in the majority of the approaches increase linearly in relation to duration and exponentially in relation to intensity. Conclusions: As dose estimations provide divergent evaluations of the HI:LI ratio, the choice of metric will have a large impact on the research designs, results, and interpretations. Therefore, researchers should familiarize themselves with the foundations and weaknesses of their metrics and justify their choice. Last, the linear relationship between duration and exercise dose is in many cases assumed rather than thoroughly tested, and its use should be subjected to closer scrutiny.
Athletic Performance Decline Over the Life Span: Cross-Sectional and Longitudinal Analyses of Elite and Masters Track-and-Field Data
Brandon Pfeifer, W. Bradley Nelson, and Robert D. Hyldahl
Purpose : Loss of muscle power has a significant impact on mobility in geriatric populations, so this study sought to determine the extent and time course of performance decline in power-centric events throughout the life span via retrospective analyses of masters and elite track-and-field data. Methods : Four track-and-field events were selected based on maximal power output: the 100-m dash, long jump, high jump, and triple jump. Elite and masters athlete data were gathered from the World Masters Outdoor Championships and the International Amateur Athletic Federation World Athletics Championships (17,945 individual results). Data were analyzed by fitting individual and group results to quadratic and linear models. Results : Average age of peak performance in all events was 27.8 (0.8) years for men and 28.3 (0.8) years for women. Athlete performance decline best matched a linear model for the 5 years following peak performance (mean R 2 = .68 [.20]) and for ages 35–60, but best matched a quadratic model for ages 60–90 and 35–90 (mean R 2 = .75 [.12]). The average rate of decline for the masters data ages 35–60 ranged from 0.55% per year for men’s 100-m dash to 1.04% per year for women’s long jump. A significant age × sex interaction existed between men and women, with men declining faster throughout life in all events except the 100-m dash. Conclusions : Performance decline begins in the early 30s and is linear through middle age. This pattern of decline provides a basis for further research on power-decline pathophysiology and preventive measures starting in the 30s.
A Change-Point Method to Detect Meaningful Change in Return-to-Sport Progression in Athletes
Kate K. Yung, Ben Teune, Clare L. Ardern, Fabio R. Serpiello, and Sam Robertson
Purpose: To explore how the change-point method can be used to analyze complex longitudinal data and detect when meaningful changes (change points) have occurred during rehabilitation. Method: This design is a prospective single-case observational study of a football player in a professional club who sustained an acute lower-limb muscle injury during high-speed running in training. The rehabilitation program was entirely completed in the football club under the supervision of the club’s medical team. Four wellness metrics and 5 running-performance metrics were collected before the injury and until the player returned to play. Results: Data were collected over 130 days. In the univariate analysis, the change points for stress, sleep, mood, and soreness were located on days 30, 47, 50, and 50, respectively. The change points for total distance, acceleration, maximum speed, deceleration, and high-speed running were located on days 32, 34, 37, 41, and 41, respectively. The multivariate analysis resulted in a single change point for the wellness metrics and running-performance metrics, on days 50 and 67, respectively. Conclusions: The univariate approach provided information regarding the sequence and time point of the change points. The multivariate approach provided a common change point for multiple metrics, information that would benefit clinicians to have a broad overview of the changes in the rehabilitation process. Clinicians may consider the change-point method to integrate and visualize data from multiple sources to evaluate athletes’ progression along the return-to-sport continuum.
