What explains the well-being benefits of physical activity? A mixed-methods analysis of the roles of participation frequency and social identification.

OBJECTIVE: Physical activity in a social setting is said to be associated with well-being because it provides opportunities for participants to form social relationships. However, there are inconsistent findings regarding the well-being benefits of participating in physical activity with others. To address this inconclusive evidence, we draw on the social identity approach to health and well-being to examine whether (a) the frequency of physical activity participation in a social setting and (b) the degree of social identification associated with it, have different relationships with participants' well-being. METHODS: We implemented a two-phase, mixed-methods design with members of women's only fitness clubs in Japan. In Study 1, we collected survey responses about social identification, life satisfaction, and eudaimonic well-being from 1118 members. The survey data were combined with respondents' objective participation data from a membership database. In Study 2, we interviewed a sample of club members to understand how the nature of social relationships differed depending on the degree of their social identification. RESULTS: Study 1 found that social identification with a fitness club, but not the frequency of attending the club for physical activity, was positively associated with members' well-being. Study 2 revealed that members with high social identification experienced more affective relationships with other members than those with medium or low identification. CONCLUSIONS: Our research provides quantitative and qualitative evidence supporting the association between social identification and the well-being benefits of physical activity in a social setting. It confirms the predictions of the social identity approach to health and well-being, demonstrating that people enjoy well-being benefits from physical activity participation when it is internalized as a meaningful definition of self.

Evaluation of Sleep Parameters and Sleep Staging (Slow Wave Sleep) in Athletes by Fitbit Alta HR, a Consumer Sleep Tracking Device.

Purpose: Sleep is an essential factor for athletes, and it is important to intervene in sleep to manage it. We need a device that can evaluate sleep easily and constantly. Consumer wearable devices can be useful tools for athletes. In order to use consumer wearable devices in clinical research, it is essential to conduct a validation study. Thus, we conducted a validation study to assess the Fitbit Alta HRTM (FBA)- a consumer wearable device with an accelerometer and a heart rate monitor to detect sleep stages and quality against electroencephalographic (EEG) studies in athletes. Patients and Methods: Forty college athletes participated in the study. EEG was applied to participants simultaneously while wearing FBA. Results: Regarding sleep parameters, there was a strong correlation between the total sleep time (TST)-EEG and the TST-Fitbit (r = 0.83; p < 0.001). Regarding the sleep stages, there was a modest correlation between the N3 sleep-EEG and the N3 sleep-Fitbit (r = 0.68; p < 0.001). In addition, there was a strong correlation between the percentage of N3 sleep in between sleep onset and initial rapid eye movement sleep-EEG and those on Fitbit (r = 0.73; p < 0.001). Conclusion: These results demonstrate that FBA facilitates sleep monitoring and exhibits acceptable agreement with EEG. Therefore, FBA is a useful tool in athletes' sleep management.

The relationship between body composition and sleep architecture in athletes.

Sleep is essential for athletes to recover physical fitness. It has been suggested that sleep is affected by muscle volume. Compared to female athletes, male athletes with greater muscle volume may have inferior objective sleep quality. This study aimed to assess the relationship between body composition and objective sleep parameters in male and female athletes. The body composition of 17 male and 19 female collegiate athletes were measured, and they underwent overnight home sleep monitoring. Compared with female athletes, male athletes had more muscle mass and less fat mass. Moreover, male athletes had lower sleep efficiency, longer sleep onset latency, higher arousal index, less rapid eye movement (REM) sleep, and lower percentage of slow-wave (N3) sleep in the initial non-REM sleep. Furthermore, the percentage of muscle mass was inversely related, whereas fat mass or percentage of fat mass was directly related to the percentage of N3 sleep in the initial non-REM sleep. Overall, there were no significant association between sex and sleep parameters. However, a significant correlation was found within both subgroups. Objective sleep quality was suggested to be worse in male athletes than in female athletes, implying that sleep architecture may be related to the muscle volume.

Changes in the objective measures of sleep between the initial nights of menses and the nights during the midfollicular phase of the menstrual cycle in collegiate female athletes.

STUDY OBJECTIVES: Sleep is an important recovery period for athletes. Women, including athletes, have reported sleep disturbances around menses. Thus, the aim of this study was to assess the changes in objective sleep parameters in the nights during menses and in the midfollicular phase of the menstrual cycle of young female athletes. METHODS: Female collegiate athletes with regular menstrual cycles were recruited. The participants underwent home electroencephalogram monitoring during the first and second nights after the onset of menses (M1 and M2, respectively) and during one night between the 7th and the 10th night after menses onset (midfollicular phase). RESULTS: Data from 45 athletes were analyzed. The total sleep time was significantly reduced, and sleep onset latency was significantly prolonged in M2 compared with those in the night during the midfollicular phase. Sleep efficiency was significantly reduced in M1 compared with that in the night during the midfollicular phase. Changes in the percentage of deep sleep across menstrual cycles differed among the participants with and without menstrual symptoms or concerns for sanitary products; moreover, such participants spent a lower percentage of time in deep sleep in M1 compared with the other nights. CONCLUSIONS: Collegiate female athletes with regular menstrual cycles are likely to have trouble falling asleep, tend to sleep less, and when concerned about sanitary products, have less deep sleep during menses. Even in young female athletes with regular menstrual cycles, sleep can be disturbed during menses. Interventions to restore or improve sleep should be considered.

Sex differences in factors associated with poor subjective sleep quality in athletes.

BACKGROUND: Sleep is an important recovery period for athletes. In general, women are not satisfied with their sleep quality, which is also true for female soccer players, although the reasons remain to be elucidated. This study aimed to confirm sex difference in sleep quality among athletes from various fields of sport, and to investigate factors related to poor subjective sleep quality in male and female athletes. METHODS: We collected data concerning subjective sleep quality, measured by Pittsburgh Sleep Quality Index (PSQI), from athletes who were 16 to 40 years of age and played various types of sports. Data concerning their sports, lifestyle, and sleep issues and sleep environments, and also menstrual issues for females, were collected. RESULTS: Data from 207 male athletes and 215 female athletes were assessed. Among them, 31.4% of men and 48.8% of women had poor subjective sleep quality (i.e., PSQI≥6). In male athletes, witnessed apnea, episodes of disorientation or confusion during the time of sleep, long time gap between dinner and bedtime, and turning on the heating in the winter, were identified as factors associated with poor sleep quality by multivariate analysis, whereas in female athletes, bathing close to bedtime, habitual drinking, and being annoyed by noises at bedtime were identified. CONCLUSIONS: In both populations, females had poorer subjective sleep quality than males. Sex differences exist in factors associated with poor subjective sleep quality. Thus, different approaches should be considered to improve their sleep quality.

The gender gap in sport performance: equity influences equality.

Sport is recognized as playing a relevant societal role to promote education, health, intercultural dialogue, and the individual development, regardless of an individual's gender, race, age, ability, religion, political affiliation, sexual orientation, and socioeconomic background. Yet, it was not until the 2012 Summer Olympic Games in London that every country's delegation included a female competitor. The gender gap in sport, although closing, remains, due to biological differences affecting performance, but it is also influenced by reduced opportunity and sociopolitical factors that influence full female participation across a range of sports around the world. Until the cultural environment is equitable, scientific discussion related to physiological differences using methods that examine progression in male and female world-record performances is limited. This commentary is intended to provide a forum to discuss issues underlying gender differences in sport performance from a global perspective and acknowledge the influence of cultural and sociopolitical factors that continue to ultimately affect female performance.