Starting school time and natural sleep patterns both relate to changes in sleep timing during adolescence

Humans show close-to-24 h (or circadian) rhythms in their behavior and physiology. These fluctuations are endogenous and coordinated by a main circadian clock, located in the superchiasmatic nucleus¹. Even though humans are active during daytime, the expression of the endogenous circadian timing under specific external conditions (i.e. chronotype) shows variability among individuals^2,3. Chronotype has a genetic basis^4–6, but it also depends on other factors, such as age^7–12, light exposure^2,13,14, and cultural and social cues^15–17. Consistently, individuals’ chronotype ranges on a continuum between early and late types and can be assessed by evaluating behavioral^18–20 or physiological rhythms^21–23, as well as by using easy, reliable and standardized questionnaires. The widely used Munich Chronotype Questionnaire (MCTQ)²⁴ assesses several sleep-related variables including a chronotype proxy based on sleep timing: the sleep-corrected midpoint of sleep on free days (MSFsc). This marker highly correlates with other measures, such as the Morning-Eveningness Questionnaire score^25–27, the phase of actigraphy-evaluated sleep-rest activity rhythm^18,19,24, core temperature and other endogenous physiological rhythms^21,22,28,29.

Sleep timing approaches the individuals’ endogenous tendencies only on free days¹⁸, as opposed to weekdays, where sleep timing is usually influenced by working and education schedules³. Accordingly, modern societies are characterized by the prevalence of a misalignment between the biological timing and the social timing (i.e. determined by social cues). This chronic condition is known as social jetlag (SJL)^3,30, which is calculated as the difference between the midpoint of sleep on free days and on weekdays^3,31. It is worth noting that SJL refers to differences on sleep timing but not on sleep duration (SD). Importantly, both SJL and short SD have been associated with negative consequences for physical and mental health, such as obesity^31,32, depression^33,34, higher risk of substance abuse^35,36, higher rates of suicide³⁶, and impaired cognitive performance^37,38.

Although adolescents’ chronotype is particularly late^7–12, secondary school starts very early in the morning all around the world³⁹. This contrast between biological timing and social obligations is proposed to be the main cause of short SD on weekdays (SDw) and high SJL during adolescence^34,35. Consistently, delaying the school start time improves mood, wellbeing and academic performance^40–44, and decreases diurnal somnolence and even the rate of vehicular accidents^{40,41,45–47}. Altogether, these results suggest that a better alignment between adolescents’ internal clock and school schedule might improve both their health and performance.

As a social cue, school start time might potentially modulate adolescents’ chronotype. When comparing different morning school timings, results are not conclusive: a few studies found an association between later school start times and later chronotypes^48–50, while others did not^51,52. However, when more distant school timings were compared (e.g. morning vs. afternoon), later school timings were associated with later chronotypes^53–56. Unfortunately, the lack of random assignment of students to different school timings might confound and/or mask the effect of school timing on chronotype (due to biased assignment based on academic performance, socio-economic status or chronotype preferences). Although it has been well established that chronotypes become progressively delayed until the end of adolescence^7–12, whether and how this developmental effect is modulated by a social cue as school timing needs further investigation.

Recently, we partially addressed this point with a cross-sectional study comparing two well-defined age groups, younger and older adolescents randomly assigned to one of three different school timings at the beginning of secondary school: morning (07:45–12:05), afternoon (12:40–17:00) or evening (17:20–21:40)⁵⁷. Taking advantage of this unusual random assignment, we studied the relationship between school timing, chronotype and age⁵⁵. We found that, despite adolescents’ chronotype was partially aligned with their school timing, students continued to experience high SJL and short SDw. Importantly, school timing modulates these effects: morning-attending students presented the earliest chronotypes, but the highest SJL and the shortest SDw⁵⁷. Our previous results also show an impact of age on chronotype, SJL and SDw, with larger differences between school timings for the oldest adolescents. The conclusions of this previous cross-sectional study regarding how the interaction between age and school timing affects chronotype are compelling, yet limited, because different students were evaluated at different time points during adolescence.

Here we present a follow-up study where the same group of students was evaluated at their 1st (13–14 y.o.) and their 5th (17–18 y.o.) year of secondary school. This longitudinal design allows us to assume that the differences observed between 1st and 5th year are due to age-related changes and not due to interindividual variability. First, we replicate, complement and strengthen the results obtained in our previous cross-sectional study (Hypotheses box H1). However, the novelty and main aim of the present study is to understand using a data-driven approach which factors modulate the developmental change in chronotype that occurs during adolescence (ΔChronotype = MSFsc_5th—MSFsc_1st, i.e. the variation in chronotype that occurs from 1st to 5th year of school. Note that a negative ΔChronotype implies a chronotype advance, i.e. a later chronotype in 1st than in 5th year. In contrast, a positive value implies a chronotype delay). Importantly, the assessment of this aim is only possible with data corresponding to different time points for the same adolescents.

As mentioned before, it has been reported that chronotype is modulated by social cues^15–17 and age^7,8 among other factors^2,54,57,58. However, some recent studies found low-to-moderate stability throughout adolescence in chronotype at individual level^9–11. This result means that even though chronotype delays on average, the developmental change (ΔChronotype) is not necessarily the same for all students. Factors explaining this variability in ΔChronotype are unknown. Here, we propose that this change is not only modulated by school timing, but also it is correlated with baseline chronotype (i.e. the chronotype of each student in 1st year). The relationship between these two factors leads to four possible and alternative scenarios, where the magnitude and/or the direction of ΔChronotype is associated with school timing and/or each adolescent’s baseline chronotype (Hypotheses box H2, Box Fig. 1, Supp. Fig. 1).

Although the four scenarios are possible, we know that: 1- Argentinian adolescents exhibit later chronotypes than adolescents from other countries^{7,8,53,64–66}, and their baseline chronotypes are particularly late; and 2- school timing, as a social cue, has been shown to modulate chronotype^54,57. Consistently, we think that the independent association of both school timing and baseline chronotype will better explain the age-related changes in chronotype (i.e. Hypotheses box H2, scenario c). Importantly, as the interplay of late chronotypes and early school start times is expected to be the cause^39,64 of unwanted sleep-associated conditions (e.g., short SD and high SJL^39,64–69), we hypothesize that changes in social jetlag and sleep duration will be associated with ΔChronotype and influenced by school timing (Hypotheses box H3). Particularly, we predict that a higher ΔChronotype in morning-attending students will be associated with even higher SJL and lower SDw in 5th year, compared with other school timings. In summary, we expect that both school timing and baseline chronotype will be associated with the magnitude and direction of ΔChronotype that, in turn, will be associated with changes in levels of SJL and SDw during adolescence.

Here we achieved three related and complementary aims. First, we reproduced and strengthened our previous cross-sectional results⁵⁷ on how school timing and age affect chronotype and sleep. Second, we showed that the magnitude and the direction of the age-associated change in chronotype is associated with both school timing and baseline chronotype (i.e. chronotype of adolescents in their 1st year of secondary school) consistent with scenario c (Hypotheses box H2, Box Fig. 1c). We proposed a mechanism that is consistent with our results (i.e. the existence of an upper limit), but our data is not sufficient to test which is this limit or if other mechanism is involved. Third, we found that the developmental changes in chronotype are associated with social jetlag and sleep duration age-related changes.

Consistently with our previous data⁵⁷, we found that students’ chronotypes were partially aligned with their school timing. Chronotype depends on both school timing and age, as well as on their interaction: the midpoint of sleep on free days (MSFsc) is later in older adolescents and later school timings, with larger differences between school timings for older adolescents. Social jetlag (SJL) is higher and sleep duration on weekdays (SDw) is shorter when school timing is earlier, especially for older students attending school in the morning. Most results were consistent between both studies, reinforcing our conclusion that school timing, as a social cue, partially modulates adolescents' internal timing.

Importantly, our longitudinal design allowed us to further analyze the low-to-moderate stability of chronotype during adolescence reported in previous longitudinal studies^9–11. We found that ΔChronotype correlates with baseline chronotype. A previous study reported that chronotype development was associated with the interaction between age and circadian preferences⁹ finding similar results. However, baseline chronotype as a factor related to the low stability of chronotype along development has not been previously reported and, thus, our approach and results contribute to understand how chronotype changes during adolescence.

Previous works have studied how chronotype is affected either by school timing^7,8,62 or by age^7–12,60 during adolescence, but here we analyzed these two factors together and longitudinally. Our results are consistent with our prediction that baseline chronotype and school timing are independent and additive associated with adolescents’ chronotype (Supplementary Fig. 1c, Scenario 3): 1- later school timings are related to later chronotypes, with a stronger association in older adolescents, and 2- earlier baseline chronotypes experience a bigger ΔChronotype. According to our model, while a morning-attending student with a baseline chronotype equal to 05:46 (i.e. the mean baseline chronotype for this school timing) practically does not change their chronotype during secondary school, 1-h later baseline chronotypes (i.e. 06:46) would advance their chronotypes 45 min by 5th year. Thus, morning-attending adolescents who have late baseline chronotypes at the beginning of secondary school might experience smaller delays or even advance their chronotype with age. As summarized in Scenario 3, getting older is not necessarily associated with later chronotypes.

Here we propose a mechanism that includes the existence of limits to ΔChronotype during adolescence. Particularly, an upper limit associated with either the developmental stage achieved at the end of secondary school^59,60 or with the entrainment mechanism of the circadian clock⁶² might explain the association of both school timing and baseline chronotype with ΔChronotype. Previous works showed that chronotype variability among adolescents depends on different factors, including genetics, culture, light exposure, schedules and age^{2,4–8,12–17,57}. On the one hand, advanced pubertal stages have been associated with later chronotypes^59,80 students with later baseline chronotypes might be the ones presenting the most advanced pubertal stages at the beginning of secondary school. If this case, they would reach the upper limit before their peers and, consistently, they would have a smaller delay in chronotype between 1st and 5th year than they peers who started secondary school at lower pubertal stages. On the other hand, the upper limit might be associated with the entrainment mechanism. To be entrained to the external 24 h light–dark cycle, humans have to be exposed to light at specific times of the day^2,17,62. Consistently, the interindividual variability exists but has limits and the range of chronotypes does not cover the 24 h (i.e. some theoretically possible chronotypes might not be compatible with entrained rhythms⁶²). Although humans can invert their wake-sleep cycle to be active at night and sleep during the day, as individuals who work night shifts, these subjects do not exhibit stable entrained rhythms^61,63,81. As chronotype is delayed throughout adolescence^7,8,10,11, students with later baseline chronotypes would reach the upper limit of stable entrainment⁸² before their earlier peers. Furthermore, in our setting, this scenario is especially plausible because Argentinian adolescents exhibit particularly late baseline chronotypes^{7,8,53,57,82,83}. Based on our data, we cannot disambiguate whether the upper limit of chronotype exists and depends on the developmental stage and/or on the entrainment mechanisms of the circadian clocks. A possible concern associated with the correlation between the changes observed in MSFsc and its baseline value is that it might be partially/fully explained by the regression towards the mean⁸⁴. This effect occurs because there exists random errors when a variable is assessed within-subjects. Thus, if the initial measurement were an extreme value it is highly probable that the next time we assess the same variable in the same subject the value would be closer to its true mean. This could lead to an artificial association between baseline values and the change observed in the variable. Consistently, the magnitude of the effect depends on the magnitude of within-subject variability and on the precision of the measurement instrument used. Although we acknowledge that this artifact might be influencing our results (especially considering that there is scarce literature validating MCTQ in adolescents), the effect of the regression towards the mean, if present, would only partially affect our results and it does not detract them from its validity. First, MCTQ is a reliable instrument to assess adolescents’ chronotype: similar results (magnitude and direction) associated with age and school timing were obtained using MCTQ^{8,54,57,85,86} and other instruments (e.g. DLMO, actigraphy, MEQ, etc.)^{7,9,10,41,86–88}. Second, MCTQ test–retest reliability is good when assessing adolescents and young adults⁸⁹ and ΔChronotype does not change when adolescents are evaluated and reevaluated with one year difference; furthermore, no differences were found between early and late types⁹⁰. That is, variability within-subjects seems to be low. Moreover, similarly to the results presented here, when the period between test and retest during adolescence is longer, the midpoint of sleep derived from actigraphy showed higher within-subject variability^9,10. Altogether, these findings support the idea that our results are due to a development effect that is built during adolescence and not due to regression towards the mean derived from MCTQ lack of reliability. Finally, we reported a difference of almost 2 h in ΔChronotype when comparing earlier and later chronotypes on different school timings (Fig. 2a). This magnitude is biologically significant and it is highly improbable that it would be observed only because of regression towards the mean, especially when well established effects acting on chronotype during adolescence, such as age and school timing effects, rarely reach this magnitude^{8–10,41,54,57,87}. Future work is needed to fully understand the causes of the association we found between baseline chronotype and ΔChronotype during adolescence.

Importantly, our results show not only that ΔChronotype correlates with baseline chronotype and School timing but also that ΔChronotype is associated with age-related changes in SJL and SDw. As expected, large delays in chronotype were associated with an increase in SJL and this association progressively weakens from morning to evening school timings (Supp. Discussion). In contrast, a delay in chronotype was associated with an increase in SDw in both afternoon and evening school timings, with a steeper association for the latter, and we found no association in the morning (Supp. Discussion). Thus, a better alignment between adolescents’ internal timing and school timing seems to be beneficial in terms of sleep duration for afternoon- and evening-attending adolescents but not for their morning-attending peers. The latter was surprising because, although most adolescents shorten their SDw from 1st to 5th year, the difference on SDw does not depend on their ΔChronotype. A possible explanation for this result is that morning-attending students were already sleep-deprived in their 1st year and, consequently, their SDw might not be further shortened because of homeostatic reasons. Thus, the effect of a delay in Chronotype in morning-attending students is mostly absorbed by an increased in SJL levels and not by a shortening on SDw.

This study has several limitations. First, chronotype and sleep-related variables were self-reported through standardized questionnaires. Consistently, we cannot rule out a bias in students' answers, but they are highly improbable because students were blind to our experimental hypotheses. However, objective assessment of sleep and chronotype, such as actigraphy, could be more suitable. Second, our analyses are based on regressions, which do not allow us to establish causality but only association among variables. Third, we did not have access to other predictors that might modulate chronotype and its developmental change, such as pubertal stage, socioeconomic status, the usage of medications, the presence of illnesses, etc. Fourth, in this longitudinal study we only have data from two time points, one at the first and another at the last year of secondary school. The inclusion of additional time points (e.g. in the middle of secondary school) would be preferable but it was impossible due to operative reasons. Finally, the lack of assessment of chronotype and sleep habits before the beginning of secondary school does not allow us to unequivocally affirm that the initial point was completely balanced between school timings, even considering the random assignation.

This research also has some important strengths. First, the longitudinal design allows us to study the developmental changes during adolescence. Second, the sample size of our study is one of the highest among similar studies^{53,54,56,91,92}. Third, as in our previous study, we worked with three different school schedules, including an evening school timing (17:20 – 21:40). Finally, the random assignation of students to a particular school schedule at the beginning of their secondary school, allowed us to assume no differences in chronotype and sleep habits between school timings before starting secondary school.

Our results have several practical implications. First, we found that an early morning but also the afternoon school timing is associated with unhealthy sleep habits in adolescents. Consistently, a practical implication when thinking about better school start times would be that later morning school starting times might help but may not be enough for adolescents to have healthy sleep. This is especially relevant in populations exhibiting particularly late chronotypes, such as the adolescents from Argentina, Uruguay and Spain^54,93. In these situations, an evening school timing might be at least considered by the educational community and/or policy makers. Many families and even the educational community believed that the morning school timing is 'the most favorable school timing', but our work and several others support the idea that it is not the case: afternoon (or evening) school timing might be a more equitable and even preferable environment where early chronotypes do not present an advantage over late ones^53,55,57. Second, we show that school timing modulates chronotype and sleep habits during adolescence and, then, the undesirable conditions or behaviors associated with eveningness reported in the literature (e.g. depressive feelings or substance use) might be associated with the lack of alignment between chronotype and school timing (previous studies only include students that attend school in the morning^{10,11,94–99}). Thus, future studies should include the effect of school timing. Third, the low-to-moderate stability observed in chronotype during adolescence suggests that chronotype is a malleable target for interventions^{10,11,94–99}: knowing that earlier baseline chronotypes would exhibit larger delays, provides us new insights to help design interventions addressing adolescents sleep health and behavior.

Finally, the association between baseline chronotype and the magnitude and direction of ΔChronotype reported here go against the most parsimonious and intuitive notion that all adolescents would similarly delay their chronotype. Chronotype does not necessarily delay during adolescence and it is associated with baseline chronotype and school timing. These results might modify the previously suggested policies to improve the alignment between school timing and adolescents' internal timing. For example, the assignment of school timing based only on baseline chronotype would not be as beneficial for adolescents' sleep health and academic performance^53–55,57 as expected. Of course, more evidence is needed to shed light on this matter and to understand their practical implications, but this novel finding adds knowledge to the field and opens a new range of possibilities and questions. Exploring the underlying mechanisms of the association of both school timing and baseline chronotype effects with how chronotype changes during adolescence will lead us to a better understanding of how we can help adolescents to reach healthier sleep habits.

We thank our colleagues and the students, staff and authorities of the Escuela Superior de Comercio Carlos Pellegrini for their participation and/or their help, allowing us to conduct this study, especially to G. Braier, D. A. Golombek, E. A. Miglietta, M. Bentura, M. B. Varela, I. Santa Cruz, V. Sarmiento, L. Rodríguez and A. Barral. This research was supported by Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Universidad Nacional de Quilmes, Agencia Nacional de Promoción Científica y Tecnológica. M.S. is sponsored by CONICET and the James S. McDonnell Foundation 21st Century Science Initiative in Understanding Human Cognition Scholar Award. G.R.F., A.P.G. and M.J.L. are sponsored by CONICET. The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript.

Conceptualization: G.R.F, A.P.G., M.S. and M.J.L. Data collection: G.R.F, A.P.G. and M.J.L. Data analysis: G.R.F. and M.J.L. Interpretation: G.R.F, A.P.G., M.S. and M.J.L. Writing: G.R.F, A.P.G. and M.J.L., with revisions from all other authors.

The data and code that support the findings of this study are available from the corresponding author on request.

The authors declare no competing interests.

The online version contains supplementary material available at 10.1038/s41598-022-11928-9.