Chronotype change in university students in the health area with excessive daytime sleepiness

Introduction: Excessive daytime sleepiness (EDS) is characterized by an increased likelihood of initiating sleep at inappropriate times through involuntary naps and it negatively impacts performance in studies, work, family, and social relationships and increases the risk of accidents. Objective: This study evaluated the schedule and prevalence of EDS and its associated factors in medical students (using the PBL method), comparing it with students from other health courses (using the Traditional method). Methods: A cross-sectional study was carried out with 1152 university students who were attending courses in the health area. The presence of EDS was defined when scores >10 in the Epworth Sleepiness Scale (ESS) and the chronotype was assessed by means of the MorningnessEveningness Questionnaire (MEQ). Using Stata 13.0 software, descriptive statistics, bivariate and multivariate analyses were performed, including interactions to fit the model. Results: The prevalence of EDS was 56.5% (95% CI, 53.6-59.4), and the mean ESS score was 11.1 (95% CI, 10.8-11.3). This value was lower among those who had morning chronotypes and was higher among medical students. 10.3% (n=119) of the students had a chronotype that was incompatible with the period of the course. The associated and independent factors for EDS were: female gender (PR, 1.14, 95% CI, 1.01-1.29), age between 16 and 19 years (PR, 1.20, 95% CI, 1.04-1.39), studying late at night and using cell phones before falling asleep (PR, 1.56, 95% CI, 1.02-2.38), not doing weekly physical activity (PR, 1.13, 95% CI, 1.02-1.25), and morning chronotype (PR, 0.87, 95% CI, 0.76-0.99). Not using cell phones before bedtime reduced the prevalence of EDS by 14%. Conclusions: This study demonstrated that the morning chronotype behaved as an independent protective factor for disorders of the circadian cycle. Performing weekly physical activity reduces EDS among students with intermediate and evening chronotypes.


INTRODUCTION
Although sleep is a modulator of neuroendocrine function, psychosocial behavior, and a regulator of metabolism and cell renewal, modern behavior has reduced its quantity and quality 1 . Although the extent of the mechanisms involved in sleep, its induction, and its control remain unknown, the biopsychosocial consequences of not sleeping are well understood, and various aspects of sleep have been deduced 2 . Sleep comprises a part of the circadian rhythm and is nonproportionally intercalated with a wakefulness period; this rhythm is regulated by the presence or absence of light 3 .
Sleep disorders have a high prevalence and serious negative impacts; however, few patients with sleep disorders receive treatment, which is usually only pharmacological and is associated with a risk of complications related to tolerance and dependence 4 . Excessive daytime sleepiness (EDS), or hypersomnia, is characterized by an increased likelihood of initiating sleep at inappropriate times through involuntary naps 5 . EDS negatively impacts performance in studies, work, family, and social relationships and increases the risk of accidents 6 . The estimation of EDS prevalence is influenced by the measurement method, the assessed age range and the geographic region of residence: in South America, prevalence rates of up to 21% are reported in Mexico and in Brazil, it is reported in 17% of the population aged over 17 years 7 . Studies have reported a negative association between the presence of EDS and the quality of life of individuals with cardiac, respiratory or chronic noncommunicable diseases 8,9 . Behaviors associated with higher education routine and its consequent psychosocial effects can promote circadian desynchronization of the individual's physiological chronotype and increase the likelihood of EDS 10 . The migration of the morning chronotype towards the evening chronotype can increase the risk of EDS among university students; therefore, the knowledge of this epidemiological profile is the initial step to promote quality of life 11 .

Study design
This was a cross-sectional epidemiological study that evaluated the prevalence of EDS in university students from a private education institution in the Metropolitan Region of the Cuiabá River Valley, between August 2016 and July 2017.
Considering an estimated population of 7,000 college students, a prevalence of EDS equal to 50%, an acceptable margin of error of 5%, a design effect of 1.5, and clusters equal to 1, the sample size was calculated as 546 college students, who were required for a 95% confidence level, using Epi Info 7 software (CDC, Atlanta, USA). To reduce the probability of typing errors, double data entry was adopted.
The sample comprised undergraduate students in the health area who consented to participate in the study, and the evaluation instruments that were incorrectly filled out were excluded (Figure 1). Medical students were compared to students from other courses in the health area. In this teaching institution, the medical course uses the problem-based learning (PBL) method in comparison with other health courses, which used the traditional teaching method. The questionnaires were applied during the students' routine class schedule and they were invited to participate preferably near the middle of the course semester.

Ethical aspects
The present study was submitted to the Ethics and   The ESS is a questionnaire based on observations related to the nature and occurrence of daytime sleepiness. This selfadministered questionnaire assesses the probability of falling asleep in eight situations that involve daily activities; its overall score ranges from 0 to 24 and, according to its creators, scores above 10 suggest EDS. It is a widely used instrument, easy to understand, quickly completed, and its validation and translation into Portuguese included the young population (18 years or older) 13 .

Statistical analysis
The two-proportion test was used to check prevalence equality. Age was categorized into age groups according to the 25 th , 50 th , and 75 th percentiles. The course was categorized as "Medicine" and "Others from the health area" (Nursing, Speech therapy and Audiology, Pharmacy, Dentistry or Biomedical Sciences).
After using the Shapiro-Wilk test to assess the type of distribution of continuous variables, the unpaired Student's t test or its non-parametric analog, the Mann-Whitney test, was used to evaluate the statistical difference of numerical variables with two categories. ANOVA or its non-parametric analog, Kruskal-Wallis, was used to check the statistical difference in variables with three or more categories.

RESULTS
A total of 1,152 university students were assessed, with a mean age of 23.4 years (95% CI, 23.0-23.8). The prevalence of EDS was 56.5% (95% CI, 53.6-59.4) and the mean ESS score was 11.1 (95% CI, 10.8-11.3). Students with a morning chronotype had statistically lower sleepiness scores than those with evening or intermediate chronotypes ( Figure 2). Medical students had a statistically higher mean ESS scores than university students from other health courses ( Figure 3); however, both mean scores were above the cutoff point that classifies the presence of EDS.  In the bivariate analyses, the variables gender, age, day period, performance of physical activity at least once a week, cell phone use at bedtime, use of stimulants to study, The distribution of students according to their chronotypes and the day period is shown in Figure 4.
The independent factors associated with the prevalence of EDS were: female gender, age <19 years old, studying late at night and using cell phones before falling asleep, not doing weekly physical activity, and having a morning chronotype, with the latter being the only protective factor ( For students who did not use cell phones before falling asleep, the prevalence of EDS decreased by 14% (ARR, 0.14, 95%CI, 0.04-23.4).

DISCUSSION
Population data show that one in five people have EDS, which reduces the individual's ability to maintain an ideal level of wakefulness during the day, negatively impacting their health and quality of life 15 . University students need good quality of attention and concentration for the teachinglearning process to be effective.
Using the same definition as our outcome in this study, a cohort study of Korean adults 16 identified the prevalence of EDS as equal to 12.2% and found that the following factors were associated with EDS: older age, intense physical activity, poor education, habitual snoring, and poor sleep perception.
In Australian adults 17 , the prevalence of EDS is 10.4% among men and 13.6% among women, and its total incidence is 5.1% in the age group of 20-29 years. This age group comprises the majority of those attending college and, in the present study, the  Brazilians identified that depressive disorders showed a 155% higher rate in women than men 19 , and the authors added sleep disorders to those of depressive disorder symptoms. In 2015 in the United States, the prevalence of severe mental disorders in women was almost two-fold that that in men, and the prevalence of any mental disorder was almost 50% higher in women than men 20 . This suggests that men and women have distinct emotional health statuses, which can be reflected by the higher prevalence of EDS in women 21 .
A study that evaluated 172 medical students 11  Individuals with a definite morning chronotype usually go to sleep before 10:00 pm and wake up before 6:00 am. High school students showed brain activity with higher alpha power during morning classes, reducing brain activity throughout the day, suggesting that better cognitive development occurs in the morning 23  In Turkish medical students 24 , EDS was more prevalent in female subjects, in agreement with the observations of the present study. A high prevalence of EDS was detected in precollege students (55.8%) 25 , which shows the origin of the sleep disorder occurred before the start of higher education. Among pre-college individuals, the factors associated with EDS were alcohol intake and smoking, and there was no association with gender, age, and depression.
The evaluation of 217 Colombian medical students 26 found that sleep efficiency of less than 65% increased the occurrence of low academic performance by 323%. In the aforementioned study, the prevalence of EDS was equal to 49.8% and the mean ESS was equal to 8.4, which were lower than those observed in the present study. Another study, in turn, suggests that improved sleep quality is able to reduce students' low academic performance 27 . Although the present study did not assess academic performance, its causal relationship with EDS has been increasingly consolidated.
Not using a cell phone before bed would reduce the prevalence of EDS by 14% among university health students.
A recent study 28 found that medical students who used cell phones for >2 hours daily had their melatonin circadian rhythms From the educational point of view, there is a concern regarding academic performance and the students' sense of well-being when they realize they are progressing towards achieving their professional goals. Poor sleep quality increases the risk of low grades and stress 31 and drowsiness is associated with a higher prevalence of burnout and higher scores of mental exhaustion 32 .
One of the limitations of the epidemiological design used in this study was that it was not possible to infer causality, since exposure and outcomes were measured simultaneously. The results, therefore, reflect an absence of temporal relationship; however, the impossibility for EDS to be the cause of the associated factors identified in this study limits the possibility of a reverse causality bias. Future studies will broaden our understanding of the quality of professional performance in former students with a high prevalence of EDS

ETHICAL APPROVAL
All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Declaration of Helsinki and its later amendments or comparable ethical standards.

AUTHORS' CONTRIBUTION
Suellen Suemi Shimada invited the participants, applied the data collection instrument, digitized the answers into a database and revised the manuscript. Marília Rocha Kintschev invited the participants, applied the data collection instrument, digitized the answers into a database and revised the manuscript.
Maria Olivia da Silva invited the participants, applied the data collection instrument, digitized the answers into a database and revised the manuscript. Yara Viñé de Barros invited the participants, applied the data collection instrument, digitized the answers into a database and revised the manuscript. Hugo Dias Hoffmann-Santos wrote the research project, submitted it to the ethics committee, created the database to store the responses of the collection instruments, analyzed the data and wrote the article.