Sleep Quality in Elite Athletes: Normative Values, Reliability and Understanding Contributors to Poor Sleep.

BACKGROUND: The aims of this retrospective study were to (i) provide a description of sleep quality in elite athletes as measured by the Pittsburgh Sleep Quality Index (PSQI), (ii) provide normative PSQI data, (iii) identify differences across sex and sport, (iv) identify components that contribute to high PSQI scores and (v) assess PSQI test-retest reliability. METHODS: The PSQI was completed by 479 athletes (371 female and 108 male) across 20 Olympic team and individual sports. For ordinal and categorical variables, the Wilcoxon rank sum test and Chi Squared tests were used, respectively. A random forest regression was built to determine the importance of each PSQI component. Test-retest reliability was assessed using two-way mixed effects intraclass correlation coefficients. RESULTS: Fifty-two percent of athletes had a global PSQI score ≥ 5. Team sport athletes reported significantly longer sleep onset latency times but longer sleep durations compared with individual sport athletes. Sleep onset latency and sleep quality made the greatest contribution to the global PSQI scores. The PSQI demonstrated variability over periods of 2 months or more, with a minimal detectable change of 3 arbitrary units (AU). CONCLUSION: Long sleep onset latency and poor perceived sleep quality made the greatest contribution to the high PSQI scores observed in approximately half of elite athletes investigated. The PSQI should be administered at regular intervals due to variability within individuals over periods of 2 months or more. Individual questionnaire items or component scores of the PSQI may be useful for practitioners in guiding decision-making regarding sleep interventions in athletes.

The Utility of the Low Energy Availability in Females Questionnaire to Detect Markers Consistent With Low Energy Availability-Related Conditions in a Mixed-Sport Cohort.

The Low Energy Availability in Females Questionnaire (LEAF-Q) was validated to identify risk of the female athlete triad (triad) in female endurance athletes. This study explored the ability of the LEAF-Q to detect conditions related to low energy availability (LEA) in a mixed sport cohort of female athletes. Data included the LEAF-Q, SCOFF Questionnaire for disordered eating, dual-energy X-ray absorptiometry-derived body composition and bone mineral density, Mini International Neuropsychiatric Interview, blood pressure, and blood metabolic and reproductive hormones. Participants were grouped according to LEAF-Q score (≥8 or <8), and a comparison of means was undertaken. Sensitivity, specificity, and predictive values of the overall score and subscale scores were calculated in relation to the triad and biomarkers relevant to LEA. Fisher's exact test explored differences in prevalence of these conditions between groups. Seventy-five athletes (18-32 years) participated. Mean LEAF-Q score was 8.0 ± 4.2 (55% scored ≥8). Injury and menstrual function subscale scores identified low bone mineral density (100% sensitivity, 95% confidence interval [15.8%, 100%]) and menstrual dysfunction (80.0% sensitivity, 95% confidence interval [28.4%, 99.5%]), respectively. The gastrointestinal subscale did not detect surrogate markers of LEA. LEAF-Q score cannot be used to classify athletes as "high risk" of conditions related to LEA, nor can it be used as a surrogate diagnostic tool for LEA given the low specificity identified. Our study supports its use as a screening tool to rule out risk of LEA-related conditions or to create selective low-risk groups that do not need management as there were generally high negative predictive values (range 76.5-100%) for conditions related to LEA.

The effects of intensified training on resting metabolic rate (RMR), body composition and performance in trained cyclists.

BACKGROUND: Recent research has demonstrated decreases in resting metabolic rate (RMR), body composition and performance following a period of intensified training in elite athletes, however the underlying mechanisms of change remain unclear. Therefore, the aim of the present study was to investigate how an intensified training period, designed to elicit overreaching, affects RMR, body composition, and performance in trained endurance athletes, and to elucidate underlying mechanisms. METHOD: Thirteen (n = 13) trained male cyclists completed a six-week training program consisting of a "Baseline" week (100% of regular training load), a "Build" week (~120% of Baseline load), two "Loading" weeks (~140, 150% of Baseline load, respectively) and two "Recovery" weeks (~80% of Baseline load). Training comprised of a combination of laboratory based interval sessions and on-road cycling. RMR, body composition, energy intake, appetite, heart rate variability (HRV), cycling performance, biochemical markers and mood responses were assessed at multiple time points throughout the six-week period. Data were analysed using a linear mixed modeling approach. RESULTS: The intensified training period elicited significant decreases in RMR (F(5,123.36) = 12.0947, p = <0.001), body mass (F(2,19.242) = 4.3362, p = 0.03), fat mass (F(2,20.35) = 56.2494, p = <0.001) and HRV (F(2,22.608) = 6.5212, p = 0.005); all of which improved following a period of recovery. A state of overreaching was induced, as identified by a reduction in anaerobic performance (F(5,121.87) = 8.2622, p = <0.001), aerobic performance (F(5,118.26) = 2.766, p = 0.02) and increase in total mood disturbance (F(5, 110.61) = 8.1159, p = <0.001). CONCLUSION: Intensified training periods elicit greater energy demands in trained cyclists, which, if not sufficiently compensated with increased dietary intake, appears to provoke a cascade of metabolic, hormonal and neural responses in an attempt to restore homeostasis and conserve energy. The proactive monitoring of energy intake, power output, mood state, body mass and HRV during intensified training periods may alleviate fatigue and attenuate the observed decrease in RMR, providing more optimal conditions for a positive training adaptation.