The effect of sleep quality and quantity on athlete's health and perceived training quality

University athletes are unique because they not only have to cope with the normal psycho-physiological stress of training and playing sport, but they also need to accommodate the stress associated with their academic studies along with considerable stress from their social environment. The ability to manage and adapt to stress ultimately helps improve athletic performance, but when stress becomes too much for the athlete, it can result in maladaptation's including sleep disruption which is associated with performance loss, negative mood changes, and even injury or illness. This research aimed to determine if sleep quantity and quality were associated with maladaptation in university athletes. We examined subjective measures of sleep duration and sleep quality along with measures of mood state, energy levels, academic stress, training quality and quantity, and frequency of illness and injury in 82 young (18–23 years) elite athletes over a 1 year period in 2020. Results indicate sleep duration and quality decreased in the first few weeks of the academic year which coincided with increased training, academic and social stress. Regression analysis indicated increased levels of perceived mood (1.3, 1.1–1.5, Odds Ratio and 95% confidence limits), sleep quality (2.9, 2.5–3.3), energy levels (1.2, 1.0–1.4), training quality (1.3, 1.1–1.5), and improved academic stress (1.1, 1.0–1.3) were associated with ≥8 h sleep. Athletes that slept ≥8 h or had higher sleep quality levels were less likely to suffer injury/illness (0.8, 0.7–0.9, and 0.6, 0.5–0.7 for sleep duration and quality, respectively). In conclusion, university athletes who maintain good sleep habits (sleep duration ≥8 h/night and high sleep quality scores) are less likely to suffer problems associated with elevated stress levels. Educating athletes, coaches, and trainers of the signs and symptoms of excessive stress (including sleep deprivation) may help reduce maladaptation and improve athlete's outcomes

Using neopterin to monitor stress in hypoxic and normoxic repeated sprint training in rugby players

Objectives: Neopterin has been used as a stress marker in team sport athletes, but its use in monitoring stress in hypoxic training requires further investigation. The objective of this study was to determine whether neopterin measures could detect differences between hypoxic and normoxic training stress and whether such levels could predict subsequent performance. Methods: Nineteen amateur club rugby players completed two repeated sprint (cycling) sessions per week for 3 weeks in either hypoxic (RSH, n = 9, FIO2 = 0.145) or normoxic (RSN, n = 10, FIO2 = 0.209) conditions. Repeated sprint ability (RSA, running), and the Yo-Yo Intermittent Recovery Level 1 test (YYIR1) were assessed pre- and post- intervention. Resting neopterin, total neopterin, and the difference between resting and post-exercise neopterin and total neopterin levels (acute change) were monitored during training. Results: Neopterin and total neopterin measurements demonstrated high individual variability in all participants. Neopterin and total neopterin were likely and very likely elevated respectively in RSH vs RSN between weeks 1 and 3 (neopterin, 56.4 %, ± 55.6, p = 0.10; percent change, ± 90% confidence interval, p value; total neopterin, 42.2 %, ± 23.5, p = 0.02). Aside from a moderate correlation between the acute change in total neopterin with YYIR1 (r = -0.38) there were no substantial correlations between neopterin and total neopterin measures and post-intervention performance. Conclusions: Neopterin or total neopterin can distinguish between hypoxic and normoxic training. However, high individual variability and limited predictive ability of subsequent performance may restrict the practical application of this stress marker