Training Schedule and Sleep in Adolescent Swimmers

Sink or Swim? Sleep Patterns in Highly Trained Adolescent Swimmers during the In-Season Phase of Training

Objectives  The aim of this study was to investigate the sleeping patterns of highly-trained adolescent swimmers. Further objectives were to compare subjective and objective measures of sleep and to evaluate the relationship between electronic device use and sleep in this cohort. Methods  Fifteen national-level swimmers (age: 16.4 ± 1.0 years) wore wrist actigraphs while completing sleep diaries over a two-week training period. Types of nights were classified as early morning training (≤7am - EARLY), day training (>7am - DAY), and no training (REST). Information on electronic device use before bed and other sleep behaviors was collected via questionnaires. Results  Total sleep time (TST) was significantly ( p  < 0.05) shorter on nights preceding EARLY (5:53 ± 1:06 hour:min) compared with nights preceding DAY (7:40 ± 1:12 hour:min) and REST (7:59 ± 1:19 hour:min). Participants overestimated subjective TST by ∼54 minutes when compared with objectively measured TST ( p  < 0.05). Discussion  Adolescent athletes obtained a greater amount of sleep prior to later training the next day or before rest days, when compared with early morning swim training the next day. Adolescents also overestimated their sleep duration by ∼1 hour per night. There were no significant relationships between electronic device use at night and measured sleep indices.

The Impact of Multisession Sleep-Hygiene Strategies on Sleep Parameters in Elite Swimmers

PURPOSE

Short sleep duration and poor sleep quality are common in swimmers. Sleep-hygiene strategies demonstrated beneficial effects on several sleep parameters. The present study assessed the impact of a multisession sleep-hygiene training course on sleep in elite swimmers.

METHODS

Twenty-eight elite swimmers (17 [2] y) participated. The sleep-hygiene strategy consisted of 3 interventions. Sleep was measured by actigraphy for 7 days before the beginning of the intervention (baseline), after the first collective intervention (postintervention), after the second collective intervention (postintervention 2), and, finally, after the individual intervention (postintervention 3). The Epworth Sleepiness Scale (ESS) was completed concurrently. Swimmers were classified into 2 groups: nonsomnolent (baseline ESS score ≤ 10, n = 13) and somnolent (baseline ESS score ≥ 11, n = 15).

RESULTS

All swimmers had a total sleep time of <8 hours per night. Sixty percent of swimmers were moderately morning type. Later bedtime, less time in bed, and total sleep time were observed in the somnolent group compared with the nonsomnolent group at baseline. An interaction between training course and group factors was observed for bedtime, with a significant advance in bedtime between baseline, postintervention 2, and postintervention 3 for the somnolent group.

CONCLUSIONS

The present study confirms the importance of implementing sleep-hygiene strategies, particularly in athletes with an ESS score ≥11. A conjunction of individual and collective measures (eg, earlier bedtime, napping, and delaying morning training session) could favor the total sleep time achieved.

PHYSICAL FUNCTION CHARACTERISTICS OF SWIMMERS IN PRE-COMPETITION TRAINING

ABSTRACT Introduction: Swimming is a competitive athletic activity whose fundamental objective is to produce high-performance athletes capable of standing out worldwide. Aerobic balance directly affects the athletic performance of these professionals. Objective: Investigate the changes in the physical composition and functional characteristics of swimmers before the competition. The results can play an important guiding role in the training plan of the Chinese athletics team in the competition. Methods: To explore the relationship between swimmers of different ages, the athletes were trained, and their physiological and chemical changes were monitored before the competition. A statistical, mathematical method was used to analyze the data. Results: After exercise, the swimmers’ hemoglobin, red blood cell count, hematocrit, creatine kinase, blood urea, and other indices had changed. The difference between the two groups was significant (P<0.05). Conclusion: The results showed that the swimmers’ body function was stable before the competition with better exercise load capacity. Level of evidence II; Therapeutic studies - investigation of treatment outcomes.

CHANGES IN VO2MAX CAUSED BY AEROBIC EXERCISE IN SWIMMERS

ABSTRACT Introduction The maximal oxygen consumption rate (VO2max) can directly reflect the body's aerobic metabolism and oxygen delivery system. This is a measure of aerobic capacity used to monitor swimmers’ levels and their strength and speed performance. Objective Verify the changes in VO2max when incorporating aerobic exercise training into swimmers’ regular training. Methods 12 volunteer swimmers were divided into two categories: strength training group and regular training group. Both groups performed a fitness test on the 200-meter track before starting the training. VO2 maximal was measured and worked out statistically to verify the results of this competition. The effects of aerobic exercise on the strength and competitive status of the athletes were investigated according to an updated literature review. Results There was a significant change in the maximal oxygen uptake of the athletes after the experimental protocol. The athletes in the strength training group increased their VO2 max compared to the regular training group. The results showed a significant difference in the VO2max index before and after strength training (P<0.05). This suggests that strength training has a significant effect on maximal oxygen consumption. Conclusion Strength training interventions significantly affect athletes’ maximal oxygen consumption intensity and exercise capacity. The aerobic exercise intervention showed evidence of improving the competitive level of athletes. Level of evidence II; Therapeutic studies -investigation of treatment outcomes.

Contemporary Variables that Impact Sleep and Development in Female Adolescent Swimmers and Gymnasts

The effects of sleep on elite athletes in late adolescence and early adulthood have been well documented in a myriad of sports. However, there is underrepresentation of pre-pubertal and young female adolescent athlete research between the ages of 11-17, and specifically female gymnast and swimmers. Neglecting to understand how high energy demand at a young age relates to sleep and restoration may lead to developmental ramifications for this group, as they display physiological dysfunctions like delayed puberty, amenorrhea and are at risk for the female athlete triad or components of the triad. This review aims to summarize the contemporary variables of blue light emitting screens, social media, and caffeine on quality and quantity of sleep in young athletes while identifying gaps in the literature on how these factors impact the target group of young female swimmers and gymnasts.  The implications of this work include sleep hygiene recommendations for increasing duration and quality of sleep, as well as future research with respect to electronic device usage, social media participation, caffeine consumption, and sport engagement in female early adolescent athletes.

Sleep Quality and Duration in European Adolescents (The AdolesHealth Study): A Cross-Sectional, Quantitative Study

Sleep is a vital element of adolescents' overall health; it influences their body and mind and thus affects their quality of life. Adequate sleep quality and duration are essential for maintaining optimal metabolic health and lowering the risk of developing several medical conditions, such as cardiovascular disease. The current study aimed to assess the perceived sleep quality and duration of 1717 European adolescents from three different European countries (Spain, Iceland and Estonia) aged 13- to 16-years (900 boys, 817 girls) using the Pittsburgh Sleep Quality Index (PSQI). A multivariate analysis of variance (MANOVA) was performed to examine differences between groups and two-factor analysis of variance (ANOVA) was used to analyze city and age differences. The probability of having poor sleep quality and duration was calculated by Odd-Ratio (OR). Our study found poor sleep quality in 44% of the boys and 53% of the girls, whereas 68% and 69%, respectively did not get the recommended hours of sleep (i.e., 8-10 h). No difference was found between adolescents from Estonia, Iceland and Spain regarding sleep duration. In contrast, Spanish and Estonian adolescents reported higher probabilities of having poor sleep quality. Finally, girls had a significantly higher probability of poor sleep quality than boys.

The Relationships Between Training Load, Type of Sport, and Sleep Among High-Level Adolescent Athletes

PURPOSE

To evaluate the effects of sporting activities, training loads, and athletes' characteristics on sleep among high-level adolescent athletes, in a controlled training and academic environment.

METHODS

A total of 128 high-level adolescent athletes (age = 15.2 [2.0] y), across 9 different sports, completed common sleep questionnaires and were monitored daily (7.3 [2.7] d) during a typical in-season training period. Sleep was analyzed using actigraphy and sleep diaries, whereas training load was evaluated using the session rating of perceived exertion, and muscle soreness and general fatigue were reported with the aid of visual analog scales. Separate linear mixed-effects models were fitted, including the athlete as a random effect and the following variables as fixed effects: the sport practiced (categorical predictor), daily training load, age, and sex. Different models were used to compare sleep variables among sports and to assess the influence of training load, age, and sex.

RESULTS

The mean total sleep time was 7.1 (0.7) hours. Swimmers presented increased sleep fragmentation, training loads, perceived muscle soreness, and general fatigue compared with athletes who engaged in other sports. Independent of any sport-specific effects, a higher daily training load induced an earlier bedtime and reduced total sleep time and perceived sleep quality, with higher sleep fragmentation. Moreover, female athletes experienced increased total sleep time and worse sleep quality in response to stress compared with those in males.

CONCLUSION

In a controlled training and academic environment, high-level adolescent athletes did not achieve the recommended sleep duration. Impaired sleep quality and quantity could be partially explained by increased training loads.