The prevalence of menstrual cycle symptoms and their association with mental health and sleep in German exercising women and athletes

OBJECTIVES

Menstrual cycle symptoms are very common in female athletes. However, more evidence about the association between menstrual cycle characteristics and symptoms with sleep and mental health in athletes needs to be gathered. This study aimed to examine this association in German exercising women and athletes.

DESIGN

322 women (mean age: 23.13 ± 4.36) participated in a cross-sectional study. The survey included the Menstrual Symptom index (MSi), the Depression Anxiety Stress Scales (DASS-21), the Pittsburgh Sleep Quality Index (PSQI), and the Athletes Sleep Behavior Questionnaire (ASBQ). Additionally, demographic, sport-specific data and further menstrual cycle characteristics were examined. Multiple regression models were used for the statistical analyses.

RESULTS

The MSi score demonstrated a highly significant (p < 0.001) positive association with Depression, Anxiety, Stress, PSQI, and ASBQ. The most prevalent menstrual cycle symptoms were cravings/increased appetite, mood changes/anxiety, and tiredness/fatigue. A difference between individual and team sport athletes could not be found. Moreover, there was no association between the constructs and menses length, irregularity, or heaviness of bleeding.

CONCLUSIONS

Menstrual cycle symptoms occur very frequently in female athletes. In this study, they were related to mental health, sleep quality, and sleep behavior, regardless of the cycle phase. This evidence demonstrates the relevance of considering the menstrual cycle and menstrual symptoms in future studies with female athletes and in sport practice.

Monitoring the recovery-stress states of athletes: Psychometric properties of the acute recovery and stress scale and short recovery stress scale among Dutch and Flemish athletes

The Acute Recovery and Stress Scale (ARSS) and the Short Recovery and Stress Scale (SRSS) are recently-introduced instruments to monitor recovery and stress processes in athletes. In this study, our aims were to replicate and extend previous psychometric assessments of the instruments, by incorporating recovery and stress dimensions into one model. Therefore, we conducted five confirmatory factor analyses (CFA) and determined structural validity, internal consistency, and construct validity. Dutch and Flemish athletes (N = 385, 213 females, 170 males, 2 others, 21.03 ± 5.44 years) completed the translated ARSS and SRSS, the Recovery Stress Questionnaire for Athletes (RESTQ-Sport-76), the Rating of Perceived Exertion (RPE) and the Total Quality of Recovery (TQR). There was a good model fit for the replicated CFA, sub-optimal model fit for the models that incorporated recovery and stress into one model, and satisfactory internal consistency (α=.75 - .87). The correlations within and between the ARSS and SRSS, as well as between the ARSS/SRSS and the RESTQ-Sport-76 (r = .31 - -.77 for the ARSS, r = .28 - -.63 for the SRSS), the RPE (r = .19 - -.23), and the TQR (r = .63 - -.63) also supported construct validity. The combined findings support the use of the ARSS and SRSS to assess stress and recovery in sports-related research and practice.

Macronutrient intake as a prospective predictor of depressive symptom severity: An exploratory study with adolescent elite athletes

BACKGROUND

Appropriate availability of macro- and micronutrients has an important impact on cognitive performance, mood and mental health. Although the critical role of nutrition for elite athletes' performance was recognized early on, little is known about whether consumption of specific macronutrients (carbohydrates, proteins, fat) predict the development of future depressive symptoms in adolescent elite athletes.

METHODS

Participants were recruited from three Swiss Olympic Partner Schools (SOPS) in the Northwestern German speaking part of Switzerland. A total of 97 adolescent elite athletes (38% girls, Mage = 16.35 ± 1.19) participated in the study. Depressive symptoms (PHQ9) were assessed at baseline and after 10 months follow-up. A 3-day food recall was completed three months after the baseline assessment. Linear regression analyses were used to examine whether macronutrients predict depression symptom severity after controlling for covariates and baseline depressive symptoms.

RESULTS

Higher protein consumption in athletes was a prospective predictor of lower depressive symptom severity at follow-up (β = -35, p < .05). Several deviations from recommended nutritional standards were observed in elite athletes.

CONCLUSIONS

The findings of this exploratory study support the notion that dietary behaviour may be prospectively associated with athletes' mental health. However, more research is required with larger samples and more in-depth assessment techniques. Future research should also examine whether nutrition education and dietary modification can be used to prevent depressive symptoms among adolescent elite athletes.

Sleep in German female youth national ice hockey athletes

Background

Adequate sleep is of great importance in recovering from and preparing for training and competition.

Objective

This study aimed to investigate subjective sleep quality and daytime sleepiness of the German women’s junior national ice hockey team before and after a training camp immediately preceding the World Championship Division IA tournament.

Materials and methods

Twenty athletes (16.40 ± 0.68 years) completed German paper–pencil versions of the Pittsburgh Sleep Quality Index (PSQI) and the Epworth Sleepiness Scale (ESS) before the training camp (T1, day 1) and on the final day of the training camp (T2, day 7).

Results

Paired t-tests indicated a significant decrease in PSQI global scores from pre- to post-training camp assessments (t = 2.33, p = 0.031, df = 19), with a medium effect size (d = 0.52). Regarding ESS global scores, results of the paired t-test indicated no significant pre- to post-training camp differences (t = 0.67, p = 0.510, df = 19) and the effect size was trivial (d = 0.15). Mean scores were reduced for both PSQI (T1 = 5.90 ± 2.36, T2 = 4.65 ± 2.18) and ESS (T1 = 9.00 ± 3.58, T2 = 8.60 ± 4.04) after the training camp. When analyzed according to the position of the players, no statistically significant intergroup differences were found.

Conclusion

This study underlines the need for monitoring and screening youth athletes’ sleep before special sports events in order to identify a potential need for intervention as early as possible, to prevent serious consequences for athletes’ performance capability and well-being.

Sleep behavior and training load in adolescent elite basketball players during COVID-19 pandemic development

The COVID-19 pandemic caused strong restrictions in organized sports. Specifically, adolescent athletes, whose daily routine is usually determined by school and practice schedules, experienced a sudden lifestyle change. The aim of this study was to examine sleep and training patterns of German elite adolescent basketball players (N = 115, 15.70 ± 1.22 years, female = 32.17%) during different phases of the 2021 lockdown. Sleep and training behavior were documented by a subjective monitoring over 10 days at three different lockdown phases in February, April, and June/July. A linear mixed model approach was conducted for the statistical analyses. Sleep duration and time in bed decreased between phase 1 (prohibition of organized sports) and phase 3 (normal training conditions), while sleep efficiency and quality increased. There was no change in training duration over time, but in training intensity, which peaked in the third phase. This study contains meaningful evidence to analyze the lockdown-related return to practice process. Athletes were able to maintain training duration with alternative protocols during pandemic conditions. Interestingly, athletes slept less under non-lockdown conditions, but reported a better sleep quality. It is recommended to consider athletes' individual preferences when planning training and recovery schedules.

Validierung des Fragebogens zum Schlafverhalten von Sportlerinnen und Sportlern (FSVS)

Zusammenfassung. Der Athlete Sleep Behavior Questionnaire ist ein englischsprachiger Fragebogen zur Erhebung des individuellen Schlafverhaltens von Sportler_innen. Ziel dieser Studie war die Übersetzung des Athlete Sleep Behavior Questionnaire ins Deutsche sowie die wissenschaftliche Validierung dieser deutschen 18-Item-Version, dem Fragebogen zum Schlafverhalten von Sportlerinnen und Sportlern (FSVS). Die Validierungsstichprobe umfasste 450 Teilnehmende. Mittels eines dichotomen Items zur regelmäßigen Wettkampfteilnahme (ja/nein) wurde in Wettkampfsportler_innen ( n = 209) und Kontrollgruppe ( n = 241) unterteilt. Cronbach-α des FSVS-Gesamtwerts ergab .66. Die Pearson-Produkt-Moment-Korrelationsanalysen ergaben moderate Korrelationen zwischen FSVS-Gesamtwert, der Epworth-Sleepiness-Scale ( r = .33) und dem Pittsburgh-Sleep-Quality-Index ( r = .30). Es wurden signifikante Gruppenunterschiede für den FSVS-Gesamtwert gefunden, t‍(448) = 4.47, p < .001, d = 0.42, bei deskriptiv höheren Werten der Gruppe der Wettkampfsportler_innen. In einer separaten Stichprobe, die 13 Ruderer_innen der deutschen Junioren-Nationalmannschaft umfasste, wurden die Fragebogenwerte anschließend mit objektiven Schlafparametern korreliert. Dabei ließ sich eine hohe Korrelation zwischen FSVS-Gesamtwert und Einschlaflatenz ( rs = .68, p = .011) erkennen. Zusammenfassend ist der FSVS ein schnelles und valides Werkzeug, um dysfunktionale Schlafverhaltensweisen bei Wettkampfsportler_innen zu identifizieren. In Anlehnung an die Originalversion wird die Ableitung von Interventionen anhand einzelner Items empfohlen.

Potential Prevalence, Pattern, and Risk Factors of Insomnia Symptoms in Adolescent Elite Athletes

Abstract. Sleep disorders are an important issue among elite athletes. In this study, we used data from two studies to examine the prevalence, pattern, and risk factors of insomnia symptoms among adolescent elite athletes. We assessed insomnia symptoms using the Insomnia Severity Index. The prevalence of moderate-to-severe insomnia varied between 5 – 11 %, with 36 – 54 % of the athletes reporting subthreshold insomnia and 61 – 73 % perceiving at least one insomnia symptom. Female participants were more prone to report insomnia symptoms. Dysfunctional sleep-related cognitions were the most critical risk factor. We identified three groups with distinct insomnia symptom patterns via latent class analyses: 43 % of the participants were characterized as healthy sleepers, 45 % reported medium sleep without heightened concerned about sleep problems, and 12 % reported poor sleep and were substantially worried/distressed about their impaired sleep. More information is needed on how dysfunctional sleep-related cognitions can be influenced to improve athletes’ sleep and to foster their well-being.

Effects of sleep self-monitoring via app on subjective sleep markers in student athletes

As sleep problems are highly prevalent among university students and competitive athletes, and the application of commercial sleep technologies may be either useful or harmful, this study investigated the effects of a 2-week sleep self-monitoring on the sleep of physically active university students (n = 98, 21 ± 1.7 years). Two intervention groups used a free sleep app (Sleep Score; SleepScore Labs™, Carlsbad, CA, USA: n = 20 or Sleep Cycle; Sleep Cycle AB, Gothenburg, Sweden: n = 24) while answering online sleep diaries. They used the app analysis function in week 1 and the 'smart alarm' additionally in week 2. As controls, one group answered the online sleep diary without intervention (n = 21) and another the pre-post questionnaires only (n = 33). Facets of subjective sleep behaviour and the role of bedtime procrastination were analysed. Multilevel models did not show significant interactions, indicating intervention effects equal for both app groups. Sleep Cycle users showed trends toward negative changes in sleep behaviour, while the online sleep diary group showed more, tendentially positive, developments. Bedtime procrastination was a significant predictor of several variables of sleep behaviour and quality. The results indicate neither benefits nor negative effects of app-based sleep self-tracking. Thus, student athletes do not seem to be as susceptible to non-validated sleep technologies as expected. However, bedtime procrastination was correlated with poor sleep quality and should be addressed in sleep intervention programmes.

The First-Night Effect in Elite Sports: An Initial Glance on Polysomnography in Home-Based Settings

Self-applied portable polysomnography is considered a promising tool to assess sleep architecture in field studies. However, no findings have been published regarding the appearance of a first-night effect within a sport-specific setting. Its absence, however, would allow for a single night sleep monitoring and hence minimize the burden on athletes while still obtaining the most important variables. For this reason, the aim of the study was to assess whether the effect appears in home-based sleep monitoring of elite athletes. The study sample included eight male and 12 female German elite athletes from five different sports. Participants slept with a portable polysomnography for two nights, which they self-applied at night before going to bed. Time in bed and wake-up time in the morning were freely chosen by each individual athlete without any restrictions regarding time or sleeping environment. Participants were asked to keep the same location and time frame during the two days of monitoring and stick to their usual sleeping schedules. Sleep stages were manually scored using 30-s epochs. Sleep parameters and stages were later compared with the help of linear mixed models to investigate the factor time. Significant differences between the two nights were found for percentage of Non-REM sleep [T(19) = -2,10, p < 0.05, d = -0.47, 95%-CI (-7.23, -0.01)] with small effect size, Total Wake Time [T(19) = 2.30, p = 0.03, d = 0.51, 95%-CI (1.66, 35.17)], Sleep Efficiency [T(19) = -2.48, p = 0.02, d = -0.55, 95%-CI (-7.43, -0.63)], and Wake percentage [T(19) = 2.47, p = 0.02, d = 0.55, 95%-CI (0.61, 7.43)] with moderate effect sizes, and N3 Sleep Onset Latency [T(19) = 3.37, p < 0.01, d = 0.75, 95%-CI (7.15, 30.54)] with large effect size. Confidence Intervals for all other indices range from negative to positive values and hence specify, that parameters were not systematically negatively affected in the first night. Findings suggest that some individuals are more affected by the first-night effect than others. Yet, in order to keep the measurement uncertainties to a minimum, a more conservative approach with at least two monitoring nights should be used whenever possible, if no other supporting information on the athletes says otherwise.