Excessive daytime sleepiness and its pattern among Indian college students

Accepted Manuscript Excessive daytime sleepiness and its pattern among Indian college students Dr. Gurjeet Kaur, Ph.D. (Public Health)., Assistant Professor, Dr. Amarjeet Singh, MD, Professor PII:

S1389-9457(16)30217-9

DOI:

10.1016/j.sleep.2016.08.020

Reference:

SLEEP 3187

To appear in:

Sleep Medicine

Received Date: 3 March 2016 Revised Date:

11 August 2016

Accepted Date: 22 August 2016

Please cite this article as: Kaur G, Singh A, Excessive daytime sleepiness and its pattern among Indian college students, Sleep Medicine (2016), doi: 10.1016/j.sleep.2016.08.020. This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

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Corresponding Author and First Author: Dr. Gurjeet Kaur, Ph.D. (Public Health). Assistant Professor, Department of Public Health and Hospital Administration, Eternal University, Baru Sahib, District Sirmaur, Himachal Pardesh, India. Second Author:

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Order of Authors: Gurjeet Kaur, Ph.D.; Amarjeet Singh, MD

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Dr. Amarjeet Singh, MD, Professor, School of Public Health, Post Graduate Institute of Medical Education and Research, Chandigarh, India.

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Excessive daytime sleepiness and its

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pattern among Indian college students

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Abstract

The objective of this study was to determine the prevalence and pattern of excessive daytime sleepiness (EDTS) in Indian college students. This was a cross-sectional study that was

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conducted among 1215 undergraduate students, using the Epworth Sleep Scale (ESS) and a

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sociodemographic survey. A high proportion (45%) of EDTS was observed, and the problem was significantly greater in professional courses. A probability of association of EDTS with coffee/tea consumption, alcohol consumption and smoking was also observed in the study.

Keywords:

Epworth Sleepiness Scale

Sleep hygiene

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Physical activity

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Sleepiness

Professional streams India

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Excessive daytime sleepiness

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Introduction The burden of detrimental effects of sleep-related disorders is an under-recognized public health

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problem (Colten et al., 2006). There is growing epidemiological evidence that shows the association of sleep deprivation with mortality and morbidity. Consequences of sleep disorders can be broadly classified into long-term effects and short-term or immediate effects. Long-term

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effects of sleep disorders include metabolic disorders, obesity, cardiovascular disorders, hypertension, acute coronary syndrome, stroke, and depressive disorders.

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According to the International Classification of Sleep Disorders, excessive daytime sleepiness (EDTS) is defined as: difficulty in maintaining the alert awake state, usually accompanied by a rapid entrance into sleep when the person is sedentary. Excessive daytime sleepiness (EDTS) is one of the most common sleep problems, and is an indicator of many sleep disorders such as: insufficient sleep, poor sleep quality, insomnia, sleep-related breathing

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disorders, circadian rhythm disorders, and disorders of central hypersomnolence. Chronic sleep loss leads to an accumulation of sleep debt, which leads to fatigue and EDTS. Besides affecting mortality and morbidity, EDTS detrimentally affects quality of life,

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cognitive performance and performance at work (Slater & Steier, 2012). Insufficient sleep and

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sleepiness also affects day-to-day activities. Road accidents, occupational accidents, impaired alertness, and decreased cognitive performance are some of the immediate effects of sleep disorders. Loss of quality of life, and medical and nonmedical cost estimates due to sleep problems are quite high. In a service economy, shift work has changed the sleep pattern of the population (Akerstedt, 2003). Too much exposure to artificial lights and overindulgence in television, Internet and social media have dramatically changed human lifestyles. Deviations in natural sleep patterns and EDTS are a common consequence of this ultramodern lifestyle. 3

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Sleep-related behaviors and patterns are also changing among college students. Moving from school to college is one of the most significant events in life, when there is a transition from adolescence to adulthood. A sense of independence associated with a new environment of a

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college, academic and career stress, increased use of technology, moving from home to hostel, experimentation with smoking and liquor, etc, are some of the common changes in life for

college students. These dynamic and rapid changes also affect the sleep behaviors of college

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students.

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There are many methods for assessing EDTS and sleep quality. Sleep diaries, Multiple Sleep Latency Test (MSLT), Maintenance of Wakefulness Test (MWT), Functional Outcomes of Sleepiness Questionnaire (FOSQ), Medical Outcome Study (MOSl) Sleep Scale, Karolinska Sleepiness Scale (KSS), Stanford Sleepiness Scale (SSS) and Epworth Sleepiness Scale (ESS) are some of the tools that are used to measure EDTS. The ESS is the most widely used self-

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reported questionnaire with which to assess EDTS. It is based on retrospective reports of dozing behavior when engaged in a variety of activities; it sums eight items. The ESS rates chances of

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dozing off in particular situations (Johns 1991, 1992). In India, some efforts have been made to understand the problem of EDTS in different

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populations. But the research carried out on sleep in India has been very limited and sketchy. A few studies have shown high prevalence of EDTS, poor sleep quality and poor sleep hygiene among junior residents (Mastin, Siddalingaiah, Singh, & Lal, 2012), medical students (Giri, Baviskar, & Phalke, 2013), and the general population (Roopa, Deepa, Indulekha, Mohan, 2010). Sleep problems are quite prevalent in India and these studies are just the tip of the iceberg.

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Young Indian college students are one of the most vulnerable population groups that experience sleep problems. Therefore, it was felt that there was an urgent need to research the sleep health of college students. The objective of this research study was to determine the

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prevalence and pattern of EDTS among college students in Chandigarh, India, and to determine the factors associated with differential prevalence of EDTS among the segment of population

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under study.

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Method

This was a cross-sectional study intended to detect EDTS among college students in the city of Chandigarh, India. Chandigarh is a fast developing city and is a capital of two states: Punjab and Haryana.

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A total of 1215 students pursuing graduation – Bachelor of Arts (BA), Bachelor of Commerce (BCom), Bachelor of Science (BSc), Bachelor of Technology (BTech), Bachelor of Dental Surgery (BDS), and Bachelor of Medicine and Bachelor of Surgery (MBBS) – from

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different colleges were included in the study. Ethical clearance was taken from the ethical committee of Punjab University, Chandigarh, India. Data were collected during the time when

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students were free from their classes after receiving permission from college authorities. To invite participants, pamphlets were distributed in the colleges. Posters, inviting

students to participate, were displayed on notice boards and prominent places such as college canteens and common rooms. The announcements to invite participants into the study were made in classrooms. Those who were ill at any time during the last month were excluded from the study, as illness disturbs the natural sleep pattern. Those who were unwilling to participate were

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also excluded from the study. Before participation, informed consent was taken from all participants for this cross-sectional interview-based non-interventional study.

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The sample size was calculated, taking into account α=0.05, β=0.20, p=0.25 (from review of literature) and Q=1 p=0.75. Sample size = 4PQ/ r2 = 4 x 25 x 75/5 x 5 = 300. There were four study groups, each having 300 students.

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Study tools

To understand the pattern and determinants of EDTS, a self-administered questionnaire was used

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to collect sociodemographic information. Information pertaining to age, sex, education stream, year of course, the behavioral risk factors, such as consumption and frequency of coffee/tea, smoking (tobacco), alcohol, physical activity status/habits, history of medical disorders and family’s disorder history was recorded. To calculate body mass index (BMI), participants’

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anthropometric measurements of height and weight were taken. Height was measured to the nearest 0.1 cm and weight was measured to the nearest 0.1 kg. The Epworth Sleep Scale (ESS) is an eight-item scale used to determine prevalence and

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grading of EDTS. The ESS has high internal consistency of Cronbach’s α=0.88 and produces a single factor on factor analysis (John 1992). Many other studies have also reported high internal

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consistency of ESS original and translated versions. ESS scores were graded using two cut-offs to determine prevalence of EDTS. Data were analyzed using an old cut-off of 9 and a new cutoff of 10 (John, 2009).

SPSS statistical package 10.00 was used for statistical analysis. Percentage, mean, SD,

Chi-squared test, t-test, and ANOVA were used for statistical analysis.

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Results Sociodemographic and lifestyle profile of study participants participants

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Data were collected from 1215 participants. The age range was 16–28 years; mean age was

19.50 years. Male participants were 51.40%, and 48.60% were females. As shown in Table 1, 28.30% of study participants were from the Arts and Commerce stream, 33.30% were from

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professional courses and 47.30% were from the Science stream. In the Arts stream, 15.20% of the participants were from BA and 13.10% from BCom; in professional courses, 12.20% were

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from BTech, 6.30% from BDS, and 5.80% were from MBBS. A total of 34.60% participants were from the first year, 32.10% were from the second year, and 33.3% were from the third year of educational courses (Table 1).

Lifestyle profile profile

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The consumption of 0–2 cups of tea/coffee was reported by 65.50% of the study participants. Tobacco smoking was reported by 3.50%. Liquor consumption was reported by 6.80%.

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Of the participants studied, 47.74% were not physically active, 31.60% reported participating in physical activity 1–3 times a week, and 20.66% reported physical activity ≥4

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times a week. The BMI was found to be low in 27.6% of participants and normal in 61.5%; 10.9% were found to be overweight (Table 1).

Prevalence Prevalence of excessive daytime sleepiness Prevalence of EDTS was 44.5% (ESS ≥10); according to the new cut-off (John et al. 2009) it was 32.30% (Table 2). Mean ESS score of study participants was 8.9 ± 3.64 (95% CI 8.77–9.18) (Table 3).

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Sociodemographic and lifestyle determinants of excessive daytime sleepiness Gender

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The prevalence of EDTS was 43.59% in male study participants, and 45.52% in females. There was no significant association of gender with EDTS (Chi-squared test p=0.500, OR=1.081) (Table 4).

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Study stream

The prevalence of (ESS ≥10) (EDTS) was 38.37%, 45.66% and 49.49% in Arts/Commerce,

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Science and professional streams, respectively. There was significant association between study stream and EDTS (Chi-squared test p=0.014*) at p<0.01 (Table 4). Significant difference was observed in mean EDTS scores of different study streams (Table 6). Year of study at college

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The respective prevalence of EDTS was 40.86%, 50.51% and 42.57% in the first, second and third year at college (Table 4).

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Body mass index

The Prevalence of EDTS was 43.28%, 45.44% and 43.18% in low, normal and overweight BMI

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categories, respectively. There was no association between BMI and EDTS (Chi-squared test p=0.757) (Table 4). No significant difference in mean EDTS score was observed in different BMI categories of study participants (Table 6). Physical activity

The prevalence of EDTS (ESS ≥10) was 46.90% in participants who were not performing any physical activity. The prevalence of EDTS was 45.57% in participants who were performing physical activity for 1–3 days per week, and 37.45% in participants who did physical activity for 8

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≥4 days per week. A significant association between frequency of physical activity and prevalence of EDTS was found (Chi-squared test p=0.037) (Table 4).

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Lifestyle variables variables

The prevalence of EDTS was lower between those who did not consume coffee/tea than in those who consumed coffee/tea (38.46% vs 46.18%; p=0.026*) (Table 5). The mean EDTS scores were significantly different in study participants who did not consume coffee/tea and those who

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did (9.03 ± 3.63 vs 8.63 ± 3.69) (t=1.705, p=0.02*) (Table 7). The prevalence of EDTS was

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lower in teetotalers than in alcohol drinkers (43.90% vs 53.04%; p=0.007*) (Table 5). The mean EDTS scores were significantly different in study participants who consumed alcohol as compared with others (9.73 ± 3.15 vs 8.92 ± 3.67) (t=2.260, p=026*) (Table 7). The prevalence of EDTS was lower in nonsmokers than smokers (44.08% vs 57.14%; p=0.03*) (Table 5). The mean EDTS score in smokers was significantly different from nonsmokers (10.19 ± 4.23 vs 8.93

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Discussion

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± 3.62) (t=2.209, p=0.027*) (Table 7).

During time at college, student(s) prepare themselves for fulfilling responsibilities to be

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shouldered during adult life. In the near future, skills and knowledge acquired at college help students to lead a successful personal, professional and social life. It is an established fact that attentiveness during academics in college time is a significant factor that affects the performance of a student. Excessive daytime sleepiness is a serious cause of impaired daytime attentiveness and fatigue. The problem of EDTS was found to be epidemic in college students. In the current study, almost 45% of the study population had a problem with EDTS (ESS ≥10). This indicates that the burden of sleepiness is very high in Indian college students. 9

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Few studies on the problem of sleepiness have been carried out in the Indian population. In a study on Indian medical students, Mastin et al. observed that almost half of the resident physicians had problem with EDTS. In a study of a 20–76 year age group of a south Indian

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population, Roopa et al. observed that 59% (n=358) of the study participants had problems with EDTS. Even if the cut-off score for ESS is increased to 10 (John 2009), one third of study

participants were excessively sleepy (ESS >10). In 2013, Giri et al. reported that 30.6% of Indian

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medical students had a sleepiness problem (ESS >9). However, there is large difference between Giri’s data and the present results. This may suggest that the problem is increasing among Indian

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college students, and this level of prevalence is an alarming situation.

Previous studies among undergraduate college and university students in various countries have shown prevalence of EDTS in a range of 10-45% (Kang & Chen 2009, Lai & Say 2013, Lund, Brian, Whiting, & Prichard, 2010, Robinson et al. 2013, Tran et al. 2014).

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Prevalence observed in the present study is similar to Malaysian (Lai & Say 2013) and Japanese students (Matsushita et al. 2014), whereas it is on the higher side when compared with Taiwanese college students (Kang & Chen 2009), American (Lund et al. 2010), Ethiopian

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(Robinson et al. 2013), Thai (Tran et al. 2014), Mexican (Moo-Estrella, Pe´rez-Benı´tez, Solı´sRodrı´guez, & Arankowsky-Sandoval, 2005), Peruvian (Whittier et al. 2014) and Chilean

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(Concepcion et al. 2013) college students. Sleepiness problem studies in similar age groups of undergraduate nursing, pharmacy,

and medical students in different populations across Asian and Tropical countries also show comparable results. Studies in Brazilian undergraduate medical students (Rique, Filho, Ferreira, Sousa-Mun˜oz, 2014, Hidalgo & Caumo, 2002), Tripoli pharmaceutical college students (Taher, Samud, Ratimy, & Seabe, 2012), Taiwanese nursing students (Huang, Yang, Wu, Liub, & Chen,

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2014) have shown similar prevalence. However, the problem of sleepiness was more severe in Sudanese (Mirghani, Ahmed, & Elbadawi, 2015) and Malaysian undergraduate medical students (Zailinawati et al. 2009) as compared with the present study, which was conducted in an Indian

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city representative of developing India.

Sociodemographic determinants of excessive daytime sleepiness

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Among sociodemographic factors, prevalence of sleepiness was significantly associated with stream of study. The mean EDTS scores and prevalence of EDTS were highest in professional

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course students and lowest in Arts and Commerce students. Studies show that greater academic stress contributes to sleep problems among students (Duarte et al. 2014, Chen et al. 2015). The high prevalence of EDTS in professional and science courses may be due to high academic stress, lack of physical activity due to a busy academic schedule, and maladaptive sleep hygiene

Lifestyle factors factors

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practices.

Excessive daytime sleepiness was significantly associated with stimulant beverages (ie,

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coffee/tea consumption). Mean EDTS scores were significantly higher in smokers and alcohol consumers. Adenosine is an endogenous biochemical sleep promoter in the basal forebrain; it

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inhibits the cholinergic neurons that create arousal, and regulates sleep. Regular daily dietary caffeine intake was associated with daytime sleepiness in a large sample and population-based study (Roehrs & Roth 2008). Caffeine is a blocker of adenosine receptors; thus, caffeine reduces sleep. The consumption of coffee/tea before bedtime is an established poor sleep hygiene practice. It is a common practice in university and college student(s) to take coffee/tea at bedtime.

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Studies in connection with sleep problems of college and university students in other countries have also established an association between sleep problems and caffeine or other stimulant consumption (Ogeil & Philips 2015 , Whittier et al. 2014 , Lund et al. 2010, Kabrita,

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Hajjar-Muça, & Duffy, 2014, Sanchez et al. 2014, Sawah et al. 2015, Tran et al. 2014 ). Smoking is another addiction that affects sleep. Smokers show a high prevalence of EDTS and other sleep disorders (Arber, Bote & Meadows, 2009, Wali & Abaalkhai 2015, Mak et al. 2010). The

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association of EDTS and smoking was also reported in Chilean college students (Concepcion et al. 2013). Alcohol also causes sleep disturbances and sleep problems in healthy adults (Roehrs,

smokers and liquor consumers.

Physical activity

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Papineau, Rosenthal & Roth, 1999). In the present study, mean EDTS scores were higher in

The present study established a significant association between the prevalence of EDTS and

physical activity.

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frequency of physical activity. The prevalence of EDTS decreased with increases in frequency of

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Many studies have established the association of sleep problems with physical inactivity. Physical activity stresses the body, and the brain increases the duration of deep sleep to maintain

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equilibrium. Physical activity increases total sleep time, delays REM sleep onset, and increases slow-wave sleep (Driver & Taylor 2000). Regular exercise has small beneficial effects on total sleep time and sleep efficiency, sleep onset latency, and moderate beneficial effects on sleep quality (Youngstedt, O'Connor, Crabbe, & Dishman, 2000, Kredlow, Capozzoli, Hearon, Calkins, & Otto, 2015, Yang, Ho, Chen & Chien, 2012). Thus, regular physical activity may protect from problems of EDTS and have positive effects on sleep.

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Limitations of the study This cross-sectional study used a self-administered questionnaire, so respondent bias cannot be

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ruled out. A single scale was used, which was also a limitation of the study.

Conclusion

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Problems with EDTS are common in Indian college students. Four out of ten students attending college have EDTS and suffer from problems associated with it. Thus, it is a serious health

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problem in college students. This study observed an association of EDTS with study stream, alcohol, smoking and caffeine/tea intake. Students on professional courses and in science streams seem to be more at the risk.

College students, especially on professional and science courses, should be made aware

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of the possibility of feeling drowsy in cases of sleep disorders and inadequate sleep hygiene; they should also be informed about the direct and indirect consequences of EDTS on health, due to impaired cognitive judgment. The results of this study suggest that there is an urgent need to

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continue research on sleepiness in this population, in order to validate the data on the prevalence

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of the disorder and better clarify its association with lifestyle and sociodemographic factors.

Acknowledgements Acknowledgements

Sincere thanks to all the college students who participated in this study; without their cooperation this work would not have been possible.

Conflict of interest and funding 13

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None. This research was a part of doctorate thesis and received no specific grant from any

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among Thai college students. Journal of Public Health and Epidemiology 2014; 8(6):202–10. doi:10.5897/JPHE2014.0620.

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Wali SO, Abaalkhail BA. Prevalence and predictors of habitual snoring in a sample of Saudi middle-aged adults. Saudi Medical Journal 2015; 36(8):920-7. doi: 10.15537/smj.2015.8.11848. Whittier A, Sanchez S, Castañeda B, Sanchez E, Gelaye B, Yanez D, et al. Eveningness

SC

Chronotype, Daytime sleepiness, caffeine consumption, and use of other stimulants among Peruvian university students. Journal Caffeine Research 2014; 4(1):21-7. doi:

M AN U

10.1089/jcr.2013.0029.

Yang PY, Ho KH, Chen HC, Chien MY. Exercise training improves sleep quality in middle-aged and older adults with sleep problems: a systematic review. Journal Physiotherapy 2012;58(3): 157-63. doi: 10.1016/S1836-9553(12)70106-6.

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Youngstedt SD, O'Connor PJ, Crabbe JB, Dishman RK. The influence of acute exercise on sleep following high caffeine intake. Physiology Behaviors 2000; 68(4):563-70. doi:10.1016/S0031-

EP

9384(99)00213-9.

Zailinawati AH, Teng CL, Chung YC, Teow TL, Lee PN, Jagmohni KS. Daytime sleepiness and

AC C

sleep quality among Malaysian medical students. Medical Journal Malaysia 2009; 64(2):108-10. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/20058567.

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N (%)

Gender

Male

624 (51.4)

Female

591 (48.6)

First

421 (34.6)

Second

390 (32.1)

Third

404 (33.3)

Arts/Commerce

344 (28.3)

Year of study

Study stream

Science Professional Low (<18.5)

Physical activity (in

Physical activity frequency (in

295 (47.4)

335 (27.6)

Normal (18.5–24.99)

746 (61.4)

Overweight >25

132 (10.9)

Yes

635 (52.26)

No

580 (47.74)

0

EP

addition to work)

576 (24.2)

TE D

BMI

1–3 times/week

AC C

addition to work) in

580 (47.74) 384 (31.6)

a week

≥4 times/week

251 (20.66)

Coffee/tea intake

Yes

955 (78.6)

No

260 (27.4)

Yes

83 (7.8)

No

1132 (93.2)

0

1132 (93.2)

Alcohol intake

Amount of Alcohol 1

SC

Category

M AN U

Variable

RI PT

Table 1. Sociodemographic and lifestyle profile of study participants.

64 (1.6)

>2 drinks/week

19 (5.3)

Yes

42 (3.5)

No

1173 (95.5)

AC C

EP

TE D

M AN U

SC

Smoking

1–2 drinks/week

RI PT

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2

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Table 2. Prevalence of EDTS among study participants as per two cut-offs (N=1215).

No

Yes

9

674 (55.5)

541 (44.5)

10

822 (67.7)

393 (32.3)

AC C

EP

TE D

M AN U

SC

Cut-off

RI PT

Excessive daytime sleepiness

3

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Table 3. Item wise score and responses to Epworth Sleepiness Scale by study participants (N=1215).

2

Would never doze

Slight chance of dozing

Moderate chance of dozing

Sitting and reading

126 (10.40)

292 (24.0)

608 (50.0)

Watching TV

431 (35.5)

492 (40.5)

Sitting inactive in a public place (eg, a theater or movie)

729 (60.0)

As a passenger in a car for an hour without a break

278 (22.9)

Lying down to rest in the afternoon when circumstances permit

157 (12.9)

High chance of dozing

(95% CI)

189 (15.6)

1.71± 0.85 (1.66–1.76)

249 (20.5)

43 (3.5)

0.92 ± 0.83 (0.87–0.97)

142 (11.7)

45 (3.7)

0.59 ± 0.84 (0.54–0.64)

265 (21.8)

425 (35.0)

247 (20.3)

1.531 ± 0.06 (1.47–1.59)

311 (25.6)

434 (35.7)

313 (25.8)

1.74 ± 0.981 (0.69–1.80)

TE D

299 (24.6)

908 (74.7)

210 (17.3)

79 (6.5)

18 (1.5)

0.35 ± 0.67 (0.31–0.38)

212 (17.4)

318 (26.2)

392 (32.3)

293 (24.1)

1.631 ± 0.031 (0.57– 1.69)

243 (20.0)

122 (10.0)

43 (3.5)

0.51 ± 0.82 (0.4–0.55)

EP

Sitting quietly after lunch without alcohol

Mean ± SD

In a car while stopped for a few minutes in traffic

807 (66.4)

AC C

Total Mean ± SD (95% CI)

4

SC

1

Sitting and talking with someone

3

M AN U

0 ESS items

Item wise score

RI PT

Chance of dozing

8.9 ± 3.64 (8.77–9.18)

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Table 4. Comparison between EDTS and no EDTS in different sociodemographic categories. Excessive daytime sleepiness p (2ChiNo Yes N (%) N (%) squared tailed) 0.456 0.500 352 (56.41) 272 (43.59)

Category Male

Gender

322 (54.48)

269 (45.52)

First

249 (59.14)

172 (40.86)

Second

193 (49.49)

197 (50.51)

Third

232 (57.43)

172 (42.57)

Arts/Commerce

212 (61.63)

132 (38.37)

M AN U

Science

313 (54.34)

263 (45.66)

149 (50.51)

146 (49.49)

Below normal (<18.5) 190 (56.72)

145 (43.28)

Normal (18.5.0–24.99) 407 (54.56)

296 (45.44)

Study stream

Professional

53 (43.18)

No

308 (53.10)

272 (46.90)

Yes

366 (57.64)

269 (42.36)

0

308 (53.10)

272 (46.90)

1–3 days per week

209 (54.43)

175 (45.57)

≥4 days/week

157 (62.55)

94 (37.45)

AC C

EP

Physical activity frequency (in addition to work) in a week

75 (56.82)

TE D

Overweight (>25.0) Physical activity (in addition to work)

5

0.014*

8.597

SC

Female

Year

BMI

RI PT

Sociodemographic variable

8.519

0.014*

0.757 0.557

2.523

0.112

6.578

0.37*

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Table 5. Prevalence of EDTS as per use of coffee/tea, liquor, alcohol and smoking. Excessive daytime sleepiness Category

No

Yes

N (%)

N (%)

No

160 (61.54) 100 (38.46)

Yes

514 (53.82) 441 (46.18)

No

635 (56.10) 497 (43.90)

Yes

39 (46.99)

4.926

SC

Coffee/tea intake

0 Frequency of liquor

2.597 0.107

635 (56.10) 497 (43.90)

1–2 drinks/week

33 (51.56)

31 (48.44) 4.965

>2 drinks/week

6 (31.58)

13 (68.42)

No Smoking

EP

TE D

Yes

AC C

0.026*

44 (53.01)

M AN U

Liquor

6

χ2

RI PT

Stimulant/addiction

p (2-tailed)

0.084

656 (55.92) 517 (44.08) 18 (42.86)

24 (57.14)

2.803 0.094

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Table 6. Mean EDTS scores as per sociodemographic categories (t/f test). Sociodemographic variable

Excessive daytime sleepiness scores Categories

624 (51.4)

8.86

Female

591(48.6)

9.09

421 (34.6)

8.68

390 (32.1)

9.52

3.59

404 (33.3)

8.75

3.59

Second Third Study Stream

BMI

3.95

Science

576 (24.2)

9.18

3.55

Professional

295 (47.4)

9.38

3.34

335 (27.6)

8.74

3.41

746 (61.4)

9.06

3.68

132 (10.9)

9.12

3.98

635 (52.26)

8.80

3.73

580 (47.74)

9.16

3.54

580 (47.74)

9.16

3.54

384 (31.6)

9.02

3.69

251 (20.66)

8.46

3.78

TE D

EP 0

AC C

Physical Activity frequency (in addition to work) in a week

No

1–3 times/week ≥4 times/week

7

t(1213) = –1.803

0.279

3.69

8.27

Yes Physical activity (in addition to work)

3.44

344 (28.3)

Normal (18.5–24.99) Overweight >25

p (2tailed)

3.83

Arts/Commerce

Low (<18.5)

t/f

RI PT

Male

First

S.D

SC

Year of study

Mean

M AN U

Gender

N

f(2,1212) = 6.475

0.002**

f(2,1212) = 9.379

0.000***

f(2,1210) = 0.986

0.373

t(1213) = –1.739

0.082

f(2,1212) = 3.332

0.036*

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Table 7. Mean EDTS scores as per use of coffee/tea, liquor, alcohol and smoking (t/f test). Excessive daytime sleepiness scores Categories

955 (78.6)

9.06

No

260 (27.4)

8.63

Yes

83 (7.8)

9.73

No

1132 (93.2)

8.92

Yes

Alcohol intake

Amount of alcohol

0 1-2 drinks/week > 2 drinks/week

Smoking

Yes

EP AC C 8

3.69

p (2tailed)

t(1213) = 1.705

0.089

t(99.121) = 2.260

0.026*

f(2,1212) = 4.788

0.008**

f(1213) = 2.209

0.027*

3.15

3.67

3.67

9.22

2.88

19 (5.3)

11.47

3.45

42 (3.5)

10.19

4.23

1173 (95.5)

8.93

3.62

64 (1.6)

t/f

3.63

8.92

TE D

No

1132 (93.2)

S.D

SC

Mean

M AN U

Coffee/tea intake

N

RI PT

Stimulant use

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Highlights

RI PT

SC M AN U TE D

•

EP

•

A high proportion (45%) of the study population had problems with excessive daytime sleepiness (EDTS). Probability of association of EDTS with study stream, alcohol, smoking and caffeine/tea was observed in study. Students of professional course and science streams were more at the risk of EDTS.

AC C

•