key: cord-0943303-2uzai4zx authors: Vitale, Jacopo Antonino; Borghi, Stefano; Codella, Roberto; Lastella, Michele; Nedelec, Mathieu; Banfi, Giuseppe; La Torre, Antonio title: Are elite track and field athletes on track? The impact of COVID-19 outbreak on sleep behavior and training characteristics date: 2021-10-16 journal: Biol Sport DOI: 10.5114/biolsport.2021.109950 sha: 6a25c828e3c1ab58efcd92ea9cefdca76f8ab3e3 doc_id: 943303 cord_uid: 2uzai4zx The Covid-19 outbreak forced many governments to enter a nationwide lockdown. The aim of this study was to evaluate, by means of a survey, changes in sleep parameters and physical activity characteristics of elite track and field athletes in three periods: before the lockdown (T0), during the lockdown (09th March – 03rd May 2020, T1) and the first month after the lockdown (T2). This study was conducted from May 2020 to June 2020 and data were collected using an offline survey with 89 elite track and field athletes (mean age: 24.7 ± 5.4; n = 43 males; n = 46 females). The survey consisted of demographic data and questions on physical activity and sleep behavior at T0, T1 and T2. Athletes reported lower sleep quality scores at T1 compared to T0 and T2 (p < 0.0001) and registered delayed bedtime, wake-up time and longer sleep latency during the lockdown compared to pre-lockdown and post-lockdown whereas no changes in total sleep time were reported. No inter-group differences were detected in sleep characteristics between short- and long-term disciplines and between genders. The weekly training volume decreased from 16.1 ± 5.7 hours at T0 to 10.7 ± 5.7 hours at T1 (p < 0.0001) whereas no significant differences were detected in training volume during the lockdown in relation to the square footage of the house (p = 0.309). Alcohol (p = 0.136) and caffeine intake (p = 0.990) and use of electronic devices (p = 0.317) were similar pre-, during, and post-lockdown. The unprecedented circumstances of the Covid-19 pandemic had negative impacts on the Italian track and field athletes’ sleep and training volumes. In December 2019, a new coronavirus (SARS-CoV-2) emerged in China and the virus outbreak has spread rapidly and widely throughout the world [1] . In January 2020, the World Health Organization declared the outbreak of a new disease, renamed Covid-19, to be a Public Health Emergency of International Concern and, in March 2020, the World Health Organization declared Covid-19 as a pandemic [2] . Italy was the first European country to enter a nationwide lockdown [3] and between the 09 th March 2020 and 3 rd May 2020, the Italian Government adopted severe containment measures to counteract the possible collapse of the Italian health care system and the virus spread [4, 5] . Several activities were temporarily closed, including universities and schools, restaurants, gyms and sports centers and not even outdoor activities were allowed [6] . An inevitable behavior determined by the home confinement was the increase of time spent sitting and engaging in activities that involve low rates of energy expenditure, such as television viewing, use of electronic device, The elite athletes of the Italian Track and Field Federation (FIDAL) are ≈120. Therefore, based on a maximum 120 responses, at least 84 participants would be needed to achieve a statistical precision at 90% confidence intervals with type I error rate of 5%. Participants were Italian elite athletes from the FIDAL, recruited upon invitation by their coaches and physicians. One hundred and twentytwo participants were screened for eligibility using the following inclusion criteria: male or female, all ethnicity, age between 18 and 40 years, elite athletes of FIDAL. The exclusion criteria were as follows: recreational or semi-elite athletes, shift-or part-time workers, injuries that influence the frequency of training, and pregnant women. Participants who met the above inclusion and exclusion criteria were recruited in the study. All athletes received the survey in a printed form, answered to all questions and then returned the document by e-mail to an investigator of the study (J.V.). The subjects completed the survey in June 2020 and the data were manually exported to an Excel file (Microsoft, Edmond, USA) for data analysis. The survey was composed by four sections: 1) demographic data; 2) physical activity and sleep behavior in the last month before the lockdown (T0); 3) during the lockdown (T1); 4) in the first month after the lockdown (T2). Demographics included information on gender, sport discipline (short-term: jumps, throws, 60 m -400 m sprints; long-term: 800 m -marathon/march), training and kind of sports material, home characteristics (e.g. square footage, presence of garden or terrace, type of house) and region of origin. Subjects were classified in athletes resident in the most infected regions of Italy ( Lombardy, Emilia-Romagna, Veneto and Piedmont) or in the less infected regions (all other Italian regions). Primary outcomes of physical activity were hours of training per week, hours of training per day, and number of training sessions per week whereas subjective sleep parameters included wake-up time, bedtime, sleep latency, total sleep time and sleep quality. In detail, we utilized questions 1, 2, 3, 4, and 6 of the Italian version of the Pittsburgh Sleep Quality Index to assess sleep parameters [17, 18] . Data on alcohol and caffeine intake throughout the day and use of electronic devices 1 hour before bedtime were also collected using single selfreport question. Approximately fifteen minutes were required to com- Data are expressed as mean ± SD. Each physical activity and sleep parameter was evaluated three times (T0, T1, and T2) and then checked with the Shapiro-Wilk test. Given a non-normal distribution, in humans [6] . In line with this, data from the Italian population indicate that poor sleep quality and duration were common during lockdown [11] . Cellini and colleagues [11] observed that sleep-wake rhythms change dramatically during home confinement with people going to bed and waking up later and spending more time at bed than usual. However, those behaviors were associated with lower levels of sleep quality. In addition, the decrease in sleep quality was more severe among those with higher levels of stress and anxiety [11] . The world of professional sport experienced an unknown and extreme situation due to the Covid-19 outbreak and all competitions were postponed with any organized training or practice banned or severely limited during the first phase of the virus spread [12] . The health of spectators, athletes and coaches became a priority and the major regional, national and international competitions, such as the Olympic Games in Tokyo, were canceled [1, 12] . International-caliber elite athletes need to preserve an optimal psychophysical condition during the entire competitive season. Nonetheless, the lockdown prevented athletes from training in their habitual settings, causing changes in their physical activity patterns and daily training routine. In addition, home confinement may alter several physical and mental aspects of athletes including physical deconditioning, altered sleep patterns, or feelings of depression and the re-adjustment to normal life and return to sport will undoubtedly be challenging [13] [14] [15] . Therefore, the primary aim of this study was to evaluate, by means of a survey, changes in subjective sleep parameters and physical activity characteristics of Italian elite track and field athletes in three different periods: the month preceding the lockdown (T0), during the lockdown (09 th March -03 rd May 2020, T1) and the first month after the lockdown (T2). Secondary aims were: to assess sleep and physical activity changes between short-and long-term disciplines and between genders; to evaluate the differences in alcohol intake, caffeine intake, and the use of electronic devices before bedtime among T0, T1 and T2. We hypothesized that subjective sleep parameters and physical activity characteristics would be negatively influenced by the home confinement during the lockdown. This was a cross-sectional study conducted at the IRCCS Istituto Ortopedico Galeazzi (Milan, Italy). The study was approved by the Ethical Committee of Vita-Salute San Raffaele University (ref. n.: 95/INT/2020) and all procedures were performed in compliance with laws and regulations governing the use of human subjects (Declaration of Helsinki). The study protocol was registered at clinicaltrials.gov (ClinicalTrials.gov Identifier: NCT04632615). All participants received explanation of purpose, methods of the study and written informed consent was obtained from all subjects. Data were collected using an offline survey and the methodology of this data collection was compliant to the national legislation concerning social distancing during the pandemic. The results of the survey were reported following specific guidelines [16] . Biology of Sport, Vol. 38 No4, 2021 743 Elite athletes' sleep and lockdown the Friedman test followed the by Dunn's multiple comparisons was performed to detect possible differences in physical activity and sleep among T0, T1, and T2. Partial eta-squared (η 2 p ) was used to determine the magnitude of the effect for significant outcomes (α = .05) using the small (< .13), medium (.13-. 25) , and large (> .25) interpretation [19] while effect sizes for pairwise comparison were calculated using Cohen's d and considered to be either trivial (effect size: < 0.20), small (0.21-0.60), moderate (0.61-1.20), large (1.21-2.00), or very large (> 2.00) [20] . The two-way ANOVA was used to test intra-group and inter-group differences for physical activity and sleep parameters in: 1. male vs female athletes and 2. short-term vs long-term disciplines among T0, T1 and T2. A chi-square test (χ2) was used to test the differences between the observed and expected values among T0, T1, and T2 for all categorical variables (sleep quality, alcohol and caffeine intake, and use of electronic devices). The χ2 was also applied to sleep quality for male and female athletes alone and for subjects coming from the most and less infected regions. In addition, to test the differences in hours of training per week during the lockdown (T1) in relation to the square footage of the house (< 50 m 2 , 50-90 m 2 , > 90 m 2 ), a non-parametric Kruskal-Wallis test followed by the Dunn's multiple comparisons was applied. The level of significance was set at p ≤ .05. Statistical analysis was performed using GraphPad Prism (GraphPad Software, San Diego, CA). Note: Data are reported as absolute (and percentages) values. *: the total number of subjects is n = 87 since n = 2 athletes did not perform any training during T1, as specified in "training setting at T1". Abbreviations: SD: Standard Deviation; C.I.: Confidence interval; T1: Lockdown period. the lockdown. Table 2 presents the mean ± SD of physical activity and sleep parameters at T0, T1 and T2. Subjective sleep quality was evaluated as a categorical variable (Table 3 ). The χ2 highlighted differences in sleep quality among T0, T1 and T2 for the entire group of elite athletes (p < 0.0001), for male and female subjects alone (p = 0.048 and p = 0.023 respectively) and for subjects resident in the most infected regions (p = 0.001) and in the least infected regions (p = 0.033) separately. No inter-group differences in sleep quality were observed between the most infected regions vs the least infected regions. Overall, it was observed a decrease in sleep quality at T1 compared to T0 and T2: the answer "very bad" and "not good" increased at T1 (7.8% and 22.5%) compared to T0 (1.1% and 3.4%) whereas the answers "good" or "excellent" decreased at T1 (to 47.2% and 22.5%) compared to T0 (67.4% and 28.1%). Athletes reported significant changes in sleep-wake times Only a significant time effect (intra-group) was detected for all physical activity parameters (p < 0.0001): overall, significantly lower values of weekly and daily physical activity were observed at T1 compared both to T0 and T2 for female and male athletes separately. Similarly, data on bedtime, wake-up time and sleep latency highlighted a significant effect of time (p < 0.0001) but no effect of group and interaction were detected. Specifically, bedtime and wakeup time were delayed and sleep latency was longer at T1 compared to T0 and T2 both for female and male athletes separately. On the contrary, total sleep time did not show any significant inter-and intra-group difference (p = 0.468) ( Figure S1 ). Alcohol and caffeine intake throughout the day and the use of electronic devices before bedtime were assessed as categorical variables and data are presented in Table 4 . The χ2 highlighted no significant Sleep is a biological process having essential physiological functions for recovery and physical performance however, elite athletes do not often reach the recommended levels of night-time sleep duration and quality per night [28, 29] . It has been shown that sleep restriction could negatively impact both sport-specific and athletic performance in different sport disciplines [30] [31] [32] and sleep disturbances in athletes may be explained by their constant exposure to many stressors that impair sleep, such as high-intensity training sessions, long-haul travels or high levels of pre-competition It is common for high-level athletes to experience changes to sleep during competition or during over-reaching or over-training periods [21] . The present study reveals that such sleep disturbances rhythms [24] , may ultimately determine changes in humans' restactivity circadian expression and sleep behavior [23, 25] . In the present study, we observed a ≃45 min delay in bedtimes and wakeup times during the lockdown compared to both pre-and postlockdown period. Further, subjective sleep latency showed a high Note: The data are reported as number of answers and percentage (%). Alcohol intake is reported as mean ± SD of days of consumption per week. *: differences among T0, T1 and T2 are calculated with the Friedman test followed the by Dunn's multiple comparisons. anxiety [33] . Unfortunately, among these variables, it has recently been demonstrated that also the home confinement determined by the Covid-19 pandemic may negatively influence the sleep of elite athletes [34, 35] . To the best of our knowledge, only two studies examined the impact of Covid-19 pandemic on sleep and training in athletes [13, 36] . Pillay et al [13] Further, there was a 25% increase in sleep latency during lockdown which was strongly associated with the time spent on electronic devices before bed [36] . In contrast, we did not detect any significant increase in the use of electronic devices before bedtime and in alcohol or caffeine intake throughout the day during the lockdown ( Table 4 ). It is known that alcohol intake may negatively impact sleep quality by increasing the amount of stage N1 sleep and reducing slow wave sleep [41] and that the consumption of caffeine delays sleep onset latency and decreases slow wave sleep [42] . Our results are in contrast with previous studies highlighting a negative impact of home confinement on alcohol consumption: Stanton and colleagues [9] evaluated the associations between psychological distress and changes in health behaviors since the onset of Covid-19 in Australian adults and they observed that 25% of the sample had an increase in alcohol consumption, 40% had sleep problems and both these negative behavioral changes were associated with higher depression, anxiety and stress symptoms [9] . Similar results were observed in athletes by Håkansson and colleagues [43] as the 16% of the surveyed athletes reported drinking more alcohol during the pandemic and the authors showed that increased alcohol intake was associated with concerns over about one's future in sports but not with other covariates (i.e., anxiety, depression or gambling) [43] (cit). In our study, elite athletes were possibly resilient to the negative effects of lockdown on alcohol and caffeine intake. Therefore, one of the possible explanation for the worsening of sleep behavior in elite athletes may be related to the outdoor light exposure. Exposure to daylight was inevitably reduced during the home confinement and this reduction during wakefulness has been shown to negatively impact subsequent sleep [44] . Lastly, no differences in sleep behavior were observed between athletes resident in the "most-infected" versus "less-infected "regions; this might be explained by ubiquitous containment measures that led athletes to experience identical lockdown circumstances. In regard to physical activity levels, the Covid-19 lockdown impacted on athletes following a J-shaped curve at the mirror, i.e. a bimodal one with two bumps. In fact, the national restrictions imposed a drastic reduction of overall athletes' activities (T0 > T1 [13] observed that South-African athletes decreased both duration and intensity of training during the lockdown highlighting the negative impact of Covid-19 on physical and mental health. Physical exercise is an essential component of professional athletes' life and a reduction of training volume is inevitably linked to detraining and therefore represents a big issue for their performance and health too [45] . It has been ascertained that the levels of physical activity significantly affect sleep behaviors and the quality of sleep and that changes in societal-and work-schedules lead to alterations in sleep [46, 47] . Considering that physical activity constitutes the core of the job for elite athletes, one can understand the adjunctive and summing effect of the described conditions. Irremediably, the training volume of the athletes was decreased in the timebetween and has to be re-shaped and "re-thought" under such unprecedented situation. A significant change in the critical variables of the training sessions (frequency, duration, and timing) confirms the need for such an extraordinary flexibility of the athletes. The no inter-group differences were detected in sleep characteristics between short-and long-term disciplines and between genders and no differences in training volume were detected during the lockdown in relation to the square footage of the house. Alcohol and caffeine intake and use of electronic devices were similar pre-, during, and post-lockdown. With continuous spikes in Covid-19 cases in Italy and with the government reinstituting local/regional lockdowns, these results provide important insights to better manage sleep and training in a population for whom optimal performance is essential. Future studies should assess mental health and cognitive performances in athletes during home confinement. Under lockdown circumstances athletes and their coaching staff should enhance sleep hygiene strategies to maintain the correct sleep-wake patterns [52, 53] and plan a priori training sessions. The ultimate aim would be to avoid training load fluctuations potentially increasing the injury risk factors [54] . In addition, to assist elite athletes in case of further lockdowns, strength coaches should encourage setting goals during training periods. In fact, goal setting has proved to be effective in increasing motivation and reducing anxiety in sport [52, 54] . In conclusion, given the previous experience with the 2011 lockdown in the NFL where athletes were exposed to a greater injury risk [55] , a sport-specific stepwise return to training is advised. psychosocial mechanisms behind these athletes' responses can be quite similar to those delineated for the general population [8] . Given the companion involvement of other psychosocial and mood moderators (anxiety, depression, stress), it stands obvious for athletes, as we have already demonstrated for the general population [8] , that the key element for coping with such a situation is the autonomous motivation. In fact, when individuals whose motivation to enact physical activity is self-determined have positive attitudes toward exercise. Conversely, when motivation is external, athletes are less supported and would have worst attitudes. Some limitations of this study should be acknowledged. First, we only collected self-reported data such that objective information on sleep and physical activity parameters, such as heart rate variability, wrist actigraphy, and hormone profiles (e.g., cortisol, serotonin, melatonin) are lacking. Second, we used five selected questions of the PSQI to assess sleep parameters and no validated questionnaires were used to evaluate alcohol and caffeine intake; Third, since it was not possible to foresee the Covid-19 pandemic, we had to collect data about the pre-lockdown period by retrospective self-report which could be subjected to recall bias; nevertheless, our study procedures are similar to other works that evaluated sleep with surveys during the Covid-19 pandemic in athletes [13, 36] . Fourth, athletes' napping behavior was not evaluated; recent studies reported an increased napping frequency and duration in the general population during the lockdown [48] and it is known that a diurnal nap is an advantageous intervention to enhance recovery process and counteract the negative effect of partial sleep deprivation on physical and cognitive performance in athletes [49] [50] [51] . In summary, the Covid-19 lockdown measures determined a significant decrease in training volume and frequency along with a worsening in sleep quality, sleep latency, and a delay in bedtimes and wake-up times in elite Italian track and field athletes. Nevertheless, FIG. S1. Histograms report means with 95% CI of physical activity and sleep parameters for females (red) and males (blue) athletes. *: p < 0.05; **: p < 0.01; ***: p < 0.0001. 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