Mobile phones have become an integral part of our lives and have notably impacted society; mobile phone penetration rates exceed 100% in most developed countries [1]. One of the problems associated with mobile phones is their impact on sleep and daily rhythms. For example, the National Health and Nutrition Survey in Japan reported that approximately half of respondents in their 20s answered that mobile phone use, texting, and games disturbed their sleep [2]. Furthermore, a recent systematic review and meta-analysis suggested that excessive smartphone use was closely associated with poor self-reported sleep quality, sleep deprivation, and sleep latency prolongation [3]. Another study found that smartphone screen time, mainly mediated by bedtime use, delayed circadian rhythms and reduced total sleep time [4]. In particular, the chronotype, that is, the time orientation of an individual, is known to be the latest in one’s life (becoming the eveningness type [ET]) among young adults around the age of 20 years [5]. As digital devices (e.g., computer screens, mobile devices, and smartphones) are often reported to be related to chronotype (i.e., smartphone use is related to the lateness of the chronotype) in young adults, including university students [6-10], young adults whose chronotype becomes more ET will be more susceptible to a society with an abundance of digital devices.

Most people spend their lives in a morning-oriented society, which forces ET individuals to adopt a morning lifestyle contrary to their time orientation. Therefore, ET individuals experience sleep deficits on weekdays [11] because they are forced to wake up earlier to adapt to a morning-oriented society, even if their bedtime is later. In particular, young adults oversleep on free days (i.e., weekends) to compensate for the sleep deficit accumulated over weekdays because of their late chronotype [12]. Oversleeping on weekends is referred to as weekend catch-up sleep (WeCUS). Furthermore, such differences in sleep between work/school days and free days are assessed by the difference in the midpoint of sleep (MS) (described later) between work/school days (MSW) and free days (MSF) and are called social jet-lag (SJL) [13]. In a society with an abundance of digital devices, a previous study found that having electronic devices in the bedroom and using the internet before going to bed are associated with SJL [14]. Increasing evidence suggests that SJL is a health risk factor (particularly affecting metabolic and circulatory functions). It predisposes patients to diseases later in life [15]. In particular, females may be at a higher risk of developing adverse health symptoms because they have a higher SJL than males [12]. Therefore, issues related to chronotypes and SJL are important in young females.

Additionally, a recent report showed that an increase in SJL was linked to less physical activity (PA) in female students [16]. Lower physical activity levels (PALs) are believed to lead to an imbalance in body composition (lower muscle mass and higher body fat). A more recent study reported that higher body fat and lower muscle mass were significantly associated with chronotype lateness and lower PAL in female university students [17]. A previous study on mobile use among university students reported that smartphone use or dependence may be related to chronotypes [9]. Thus, current digital society requires a simplified assessment of chronotypes in young females, and measures should be taken, especially in the case of ET individuals.

Chronotypes are typically assessed using self-reported questionnaires. For example, the Morningness–Eveningness Questionnaire (MEQ) [18] evaluates chronotypes by calculating a score from answers to 19 questions. Others have used MS to represent the clock time midway between sleep onset (falling asleep) and offset (waking up). The SJL evaluates the difference between the MSW and MSF [13]. Furthermore, the Munich Chronotype Questionnaire (MCTQ) [19] was used to assess 17 simple questions based on the MSF and sleep duration on weekdays and weekends. However, as MSF is assessed using spontaneous sleep, it cannot be evaluated when sleep is affected by external constraints, such as an alarm clock. It is also impossible to evaluate when there is no regular work or school or when there are no regular free days. Therefore, other studies have evaluated the variation in sleep duration over a week and the time at sleep onset and offset using the standard deviation (SD) [20] or the coefficient of variation (CV) [21,22]. In particular, as the SJL or SD of sleep duration cannot evaluate sleep duration itself, the CV of sleep duration is also considered to be able to assess sleep duration as well [21,22]. However, the SD was calculated as a positive (absolute) value. This means that sleeping longer on weekends than on weekdays and sleeping longer on weekdays than on weekends were processed equally. WeCUS is an attempt to catch up on weekday sleep debt on weekends (mostly ET individuals). Conversely, if individuals get enough sleep on weekdays (mainly individuals of the morning type [MT]), their sleep duration may not be prolonged or may be shortened on weekends. If differences in sleep duration were evaluated using SD, they were evaluated equally. A study on college students reported that a few (6%) of them slept less on weekends than on weekdays [23]. Therefore, although one approach is to correct for MSF using average sleep duration across the entire week and oversleeping on weekends, this only applies to individuals who sleep longer on free days than on workdays [24].

Considering these problems, a simple assessment of the differences in sleep duration between weekdays and weekends may be sufficient to evaluate the approximate chronotype. In this case, instead of using several questions or examining the everyday sleep duration, simple questions could be asked, “How long do you sleep on weekdays (school/work days)?” and “How long do you sleep on your weekends (days when you do not have plans)?” are all that is needed. Furthermore, if sleep duration was considered, the ratio of the mean sleep duration on weekdays and weekends (minutes) to the difference in sleep duration on weekdays and weekends (minutes) could be calculated using these two questions. Therefore, this study investigated the association between differences in sleep duration on weekdays and weekends (weekday-to-weekend sleep duration [WWD]) and chronotype, as measured by the MEQ score, as well as the association with PAL in female university students.

Table 1 shows the means and SDs of the measured variables for all participants. Figure 1 shows the frequency distribution of the MEQ scores. The mean was 46, whereas the median was 45, indicating a slightly biased distribution toward lower values.

Figure 2 shows the relationship between Sleep-SD and WWD. A V-shaped linear relationship between Sleep-SD and WWD is shown, with the WWD bordering zero.

Figure 3 shows the relationship between the WWD and sleep duration on weekdays (left) and weekends (right). The WWD was significantly correlated with both sleep durations, with a weak negative relationship with weekday sleep duration and a strong positive relationship with weekend sleep duration. This indicated that individuals with longer sleep durations on weekends compared to weekdays had shorter sleep durations on weekdays and longer sleep durations on weekends. WWD showed no significant correlation with weekday PAL (r=0.12, p=0.08, 95% confidence interval [CI]=-0.02 to 0.26), whereas a significant weak negative correlation with PAL on weekends (r=-0.23, p<0.01, 95% CI=-0.36 to -0.10). This indicates that individuals with longer sleep duration on weekdays compared to weekdays had less PA on weekends.

Figure 4 shows the relationship between MEQ score, WWD, and %WWD. The MEQ score showed a significant moderate relationship with WWD and %WWD (R=-0.40 and -0.41, respectively). Although the regression equations were MEQ score=-0.0345×WWD+51.434 for WWD and MEQ score=-0.1662×%WWD+51.711 for %WWD, the coefficients of determination were only 0.16 and 0.17. This indicates that the MEQ score can be explained by WWD and %WWD.

The average sleep duration of the study participants was 376.2 minutes on weekdays. This was almost the same as the mean value for Japanese females in an international study that investigated the mean sleep duration of university students (6.09 h) [28]. As shown in Figure 2, both SD-Sleep and WWD were calculated using two variables (sleep duration on weekdays and weekends), which resulted in a nearly linear relationship. However, as SD sleep duration had only positive (absolute) values, individuals who slept longer on weekdays than on weekends and vice versa were same SD-Sleep. This is a completely natural result, indicating that when the variation in sleep duration is evaluated by SD, the values of those who sleep longer on weekdays than on weekends are not reflected in the results.

The WWD exhibited a weak negative correlation with weekday sleep duration and a strong positive correlation with weekend sleep duration (Figure 3). This result indicates that WWD is longer for those who sleep shorter on weekdays and longer on weekends. While ET individuals go to bed later, they must adapt their weekday waking time to that of the morning society because of social restrictions. Consequently, they experience sleep deficits on weekdays. Furthermore, previous studies reported that individuals sleep longer on weekends to compensate for sleep deficits [12]. A study of male Japanese students found that the difference in sleep duration between weekdays and weekends was significantly related to MSF [22]. The present study also found that both WWD and %WWD had a significant linear relationship with the MEQ score, and the regression coefficients (R) were almost equal (-0.40 and -0.41), indicating a moderate relationship. These results indicate that individuals with ET sleep for more hours on weekends than on weekdays. Particularly, WWD in this study was weakly related to weekday sleep duration; however, strongly related to weekend sleep duration, suggesting that WWD reflects weekend sleep duration more than weekday sleep duration.

Longer sleep duration on weekends indicates shorter duration of other activities on weekends. This study showed that, although WWD was not significantly related to PAL on weekdays, it was significantly negatively related to PAL on weekends. A previous review indicated that the association between PA and chronotypes among university students was inconsistent [29]. One reason for this inconsistency may be the difference in PA between weekdays and weekends. On weekdays, students go to campus, move from one classroom to another, and engage in after-school activities. This results in a certain amount of PAL regardless of the chronotype or sleep duration. However, on weekends, some students may be active in the morning, whereas others may be inactive. Therefore, the WWD in this study may have been significantly related only to the PAL on weekends. Some reports on female university students have found that PAL is related to body composition, including muscle mass [25], whereas others have found no such relationship [30]. These results suggest that surveys of PALs, especially for university students, should consider the differences between weekdays and weekends.

This study examined whether WWD or %WWD could represent the chronotype, as assessed using the MEQ. A moderately significant linear relationship was found between WWD or %WWD and the MEQ score; however, the coefficient of determination (R2) was approximately 0.16 to 0.17. The WWD in this study was assessed using the self-reported sleep durations of the participants, that is, their approximate sleeping duration on weekdays and weekends. Therefore, several sleep durations in this study were considered different from the actual sleep duration. Therefore, it may not be surprising that the WWD assessed in these studies can only explain the chronotype. However, the MEQ questionnaire survey requires 19 questions to be answered and the total value to be calculated. The SD and CV of sleep duration also require recording in a sleep diary for several consecutive days. Conversely, WWD in this study could be evaluated using only two simple questions: “How long do you sleep on weekdays?” and “How long do you sleep on weekends (free days)?” Surveys on sleep duration are often included in lifestyle questionnaires. In addition, mobile phones are highly prevalent, as indicated in the introduction, and some applications exist for measuring sleep duration on smartphones. This can be used to evaluate WWD automatically. Therefore, the WWD may be useful for assessing approximate chronotypes without any notable burden on participants.

This study had several limitations. First, because the survey was based on a questionnaire, the actual sleep duration needs to be investigated. In addition, activity time should also be assessed objectively using an activity meter. Second, as SJL is a problem in individuals with ET, future studies should include SJL. Furthermore, some individuals take naps to compensate for their sleep debt [31]. Indeed, previous research suggests that napping may be the most adaptive and efficient way to deal with sleep debt [32]. However, this study only assessed sleep duration, and the state of napping is unknown. Therefore, future studies should include the details of napping. Finally, although this study was conducted on female university students as indicated in the Introduction, male students and other generations also need to be examined.

This study investigated the association between differences in sleep duration on weekdays and weekends and chronotype, as measured by the MEQ score, as well as the association with PAL in female university students. The results indicated that difference in sleep duration had a moderate negative relationship with the MEQ score. Moreover, difference in sleep duration exhibited a weak negative correlation with sleep duration on weekdays and a strong positive correlation with sleep duration on weekends. Therefore, ET individuals may compensate for the sleep deficit on weekdays by sleeping longer on weekends, and this was reflected in the difference in sleep duration. Further, since longer sleep on weekends shortens the duration of other activities, a significant negative relationship between difference in sleep duration and PAL on weekends was also observed. These results suggest that WWD can be evaluated with simple questions; “How long do you sleep on weekdays (school days)?” and “How long do you sleep on weekends (have no plans)?” and it may be useful as a means of assessing approximate chronotypes without a significant burden on the participants.