Abstract
Background
Sleep is a very important physiologic process which is necessary to maintain a state of well-being. Obstructive Sleep Apnea (OSA) is prevalent among all age groups with variations in presentation and severity. It is often underreported, especially among young people in the Low- and Middle-Income Countries LMICs. This study assessed the prevalence and pattern of OSA among undergraduates enrolled at tertiary Institutions in Kwara State, Nigeria using both Epworth and Stop Bang tools.
Methodology
A campus-based study conducted among undergraduate students in Kwara state. Respondents were selected from three tertiary institutions. A total of 1,048 eligible students were selected using a multistage sampling technique. Epworth Sleepiness Scale (ESS) and Stop Bang Questionnaire (SBQ) were adapted and administered. Both descriptive and inferential analyses were conducted. The level of significance was set at a p-value of <0.05 at 95% confidence interval. Ethical approval was obtained.
Results
The mean age of respondents was 21± 2.69. More than half 634 (60.5%) of the 1048 respondents were females, with 20 (1.9%) were married. Abnormal sleepiness was reported in 151 (14.41%) while 897 (85.59%) had normal sleepiness using ESS. With the SBQ, 998 (95.2%) had a low risk while 46 (4.3%) had a moderate to high risk of OSA. Religion, increasing levels of study, and presence of chronic disease, were significantly associated with abnormal sleepiness using ESS, whereas female gender, religion, presence of chronic disease, smoking, use of sedatives and caffeine were significantly associated with OSA using SBQ.
Conclusion
The prevalence and pattern of sleep disorder among the undergraduates showed a moderate prevalence of sleep disorder and associated risks of OSA using the sleep disorder tools. There is a tendency to become a big burden with an increase in age, therefore health promotion interventions are recommended early to students to create awareness of OSA risks.
Keywords: Sleep Apnea, Undergraduate Students, Epworth Sleepiness Scale, Stop Bang Tool
Introduction
Sleep is a physiologic process required to maintain a state of well-being.1 Obstructive sleep apnea (OSA) is a prevalent illness that can occur regardless of the symptoms and is associated with significant neurocognitive and cardiac consequences. A study among business studies students revealed 66.65 with sleep deprivation.1 Sleep pattern varies with age, physiological, and psychosocial characteristics. It is also not only affected by psychiatric and physical illnesses but by occupational demands too.1 Currently, the treatment of patients experiencing obstructive sleep apnoea differs by nation and is determined by the individual's symptoms. Generally, it has been observed that a sizeable proportion of students experience poor-quality sleep, and this may be related to academic stress.2. Irregular sleep schedules, fatigue,3 and co-morbid physical or psychological conditions4 are associated with poor sleep quality. Consequently, poor sleep also predisposes to the use of stimulants, alcohol, and sedatives with attendant consequences.
Numerous attempts have been made in well-equipped areas to identify and treat persons experiencing obstructive sleep apnea, but existing data suggest that the majority of individuals suffering from obstructive sleep apnea stay misdiagnosed and untreated, even in advanced nations5. There is often limited knowledge of obstructive sleep apnea in developing nations, and testing therapy techniques are frequently unavailable or haven't been tailored for areas with limited resources. Obstructive sleep apnea is related to a large financial and societal consequence due to its multifaceted and social repercussions. The cost of identifying and treating obstructive sleep apnea in the United States in 2015 was roughly $124 billion.7
Recognizing OSA among students promotes awareness about sleep problems. This awareness pushes patients to seek diagnosis and treatment, potentially enhancing their general health and well-being. Because of poor sleep quality, undiagnosed OSA can have a severe influence on cognitive function and academic performance. Addressing this issue has the potential to improve students’ educational outcomes. Understanding the prevalence of OSA in this group aids in identifying the lifestyle variables that contribute to it, such as irregular sleep schedules, stress, or lifestyle behaviors, allowing interventions for healthy living. Early detection of OSA helps prevent future consequences, enhancing long-term health and lowering healthcare expenses associated with untreated sleep disorders. A study on OSA prevalence among tertiary students gives significant data to public health research, assisting policymakers and healthcare practitioners in implementing preventive measures and developing targeted therapies.
This study will help to raise awareness of the burden of obstructive sleep apnea in this part of the globe by contributing to the existing scarcity of local data on the prevalence of obstructive sleep apnea, and by providing data to assist in guiding plans and health policies to address this significant health and societal problem among the undergraduates and youths in Nigeria. The objective of this study is therefore to determine the prevalence and pattern of obstructive sleep apnea among tertiary institution students in North Central Nigeria and the associated factors. This is necessary as research on sleep quality among student populations in our environment is scanty and a better understanding of the etiology and risk factors of sleep problems among students is essential to improve the quality of students’ lives. Also, there have been numerous cross-sectional studies, but to the best of our knowledge, there’s been no school-based study specifically for North Central Nigeria.
Methodology
A descriptive, cross-sectional, and analytical campus-based study was carried out over a month among undergraduate students of tertiary institutions in Ilorin, Kwara State. One from each of the categories of tertiary institutions (College of Education/Polytechnics/Universities) in Kwara state was selected by simple random balloting. Respondents were selected from the State College of Education, Kwara State Polytechnic, and University of Ilorin in North Central Nigeria. The respondents were students in the various faculties in the institutions, the total number of students from each faculty was obtained and proportionate allocation was done to determine respondents to interview from each faculty, department, and level of study in the three schools. The respondents were given a brief description of the study and its objectives and informed that their participation in the study is voluntary, and they may decline without negative consequences. Subsequently, all consecutive consenting subjects were recruited for the study.
Ethical approval was obtained from the Ministry of Health Ethical Research Committee, Kwara State ERC/MOH/2023/3/0128, and confidentiality was maintained. Informed consents were obtained. Sample size (1048) was calculated using Fischer’s formula n = z 2pq /d2 and adjusting for a 10% non-response rate. Eligible students were selected using a multistage sampling technique. The instruments were interviewer administered to the students during the session, and participation was voluntary, anonymous, and unpaid. Blood pressure, height, and weight were recorded at baseline with standard instruments. Epworth Sleepiness Scale (ESS) and Stop Bang Questionnaire (SBQ) were adapted validated and administered. Previous studies as shown concurrent use of the ESS and SBQ too to determine OSA. The ESS measures the severity of excessive daytime sleepiness while the SBQ looks at the symptoms, comorbidities, and physical examination. The IBM SPSS was used to analyse collected data. Both descriptive and inferential analyses were conducted. Descriptive data was reported using frequency and percentage while Chi-square was used for the inferential. The prevalence and factors associated with OSA were reported. The level of significance was set at a p-value of <0.05 at a 95% confidence interval.
Instruments used in the study
The ESS & SBQ are effective tools for detecting a wide range of sleep disorders in the general population. The Epworth Sleepiness Scale (ESS) is a scale designed to assess daytime sleepiness using a brief questionnaire. This can aid in the diagnosis of sleep disorders. On a scale of 0 to 3, the respondent is asked to rate his or her likelihood of falling asleep in eight different situations with responses graded as 0 - being no chance of dozing and 3 a high chance of dozing. The summed score of 0-11 is considered normal, while scores of 12-24 indicate that expert medical advice should be sought. The STOP-BANG questionnaire (SBQ) is another tool to assess the risk of sleep disorder using a set of questions on a scale of 0 to 1. The respondent is asked to respond to STOPBANG variables graded as 0 - being “NO” and 1 “YES”. A summed score of 0-2 is considered Low risk, 3-4 is considered Intermediate risk, while scores of 5-8 are considered high risk for sleep disorder.5.8
Results
A total number of 1048 respondents were recruited for the study. The mean age of respondents was 21± 2.69 with 999 (95.3%) more than 18 years old. More than half 634 (60.5%) of the respondents were females, 968 (92.4%) were Yorubas while only 20(1.9%) were married. (Table 1)
Table 1:
Socio-demographic Characteristics of Respondents
| Variables | Frequency (N=1048) | Percentage (100%) |
|---|---|---|
| Age | ||
| < 18 | 49 | 4.67 |
| >18 | 999 | 95.3 |
| Mean age | 21± 2.69 | |
| Sex | ||
| Female | 634 | 60.5 |
| Male | 414 | 39.5 |
| Religion | ||
| Christianity | 324 | 30.92 |
| Islam | 722 | 68.89 |
| Others | 2 | 0.19 |
| Tribe | ||
| Fulani/Hausa | 14 | 1.34 |
| Igbo | 14 | 1.34 |
| Yoruba | 968 | 92.37 |
| NUPE | 7 | 0.67 |
| Others | 45 | 4.29 |
| Marital status | ||
| Married | 20 | 1.91 |
| Single | 1028 | 98.09 |
| Campus | ||
| Education and Mini campus | 352 | 33.59 |
| Kwara State Polytechnic | 399 | 38.07 |
| University of Ilorin | 297 | 28.34 |
Epworth Sleepiness Scale (ESS) Result showing the level of dosing off was shown in Table 2.
Table 2:
Epworth Sleepiness Scale (ESS) Result among study participants
| ESS VARIABLES | Level of dosing off (N=1048) | High chance | ||
|---|---|---|---|---|
| Would never | Slight chance | Moderate chance | ||
| Freq. (%) | Freq. (%) | Freq. (%) | Freq. (%) | |
| Sitting and reading/ picking grain/counting rosery | 494(47.14) | 264(25.19) | 178(16.99) | 112(10.69) |
| Watching TV /radio/children play/folklore | 542(51.71) | 205(19.56) | 171(16.31) | 130(12.40) |
| Sitting, active in a public place | 680(64.89) | 187(17.85) | 118(11.26) | 63(6.01) |
| As a passenger in a car for ≥ hour | 566(54.01) | 147(14.03) | 162(15.46) | 173(16.51) |
| Lying down to rest | 368(35.12) | 228(21.75) | 229(21.85) | 223(21.28) |
| Sitting and talking to someone | 970(92.56) | 57(5.44) | 14(1.34) | 7(0.67) |
| Sitting quietly after a meal without alcohol | 642(61.16) | 192(18.32) | 144(13.74) | 70(6.68) |
| In a car, while stopped for a few minutes in traffic | 956(91.22) | 54(5.15) | 32(3.06) | 6(0.57) |
The prevalence and risk of OSA using SBQ was shown in Table 3.
Table 3:
Prevalence and risk of OSA using the STOPBANG questionnaire among participants
| VARIABLES | Stop bang (N=1048) | |
|---|---|---|
| YES (%) | NO (%) | |
| STOP | ||
| SNORE loudly (louder Than talking or loud enough to be heard through | 145 (13.84) | 903 (86.16) |
| often feel TIRED, fatigued or sleepy during the daytime | 499 (47.61) | 549 (52.39) |
| OBSERVED breath stop by others | 26 (2.48) | 1022 (97.52) |
| Being treated for high blood PRESSURE | 6 (0.57) | 1042 (99.43) |
| BANG | ||
| BMI more than 35kg/m2 | 7 (0.67) | 1041 (99.33) |
| AGE over 50 years old | 1 (0.10) | 1047 (99.9) |
| NECK circumference > 16 inches (40cm) | 6 (0.57) | 1042 (99.43) |
| GENDER – Male | 410 (39.12) | 638 (60.88) |
Abnormal sleepiness was reported in 151(14.41%) while 897 (85.59%) had normal sleepiness using ESS. (Table IV)
Table 4:
Prevalence of OSA using ESS & SBQ
| Sleep Disorder Risk | Frequency (N=1048) | Percentage (100%) |
|---|---|---|
| ESS | ||
| Normal sleepiness | 897 | 85.59 |
| Abnormal sleepiness | 151 | 14.41 |
| STOP BANG | ||
| Low risk (0-2) | 998 | 95.23 |
| Intermediate risk (3-4) | 46 | 4.39 |
| High risk (5-8) | 4 | 0.38 |
ESS-Epworth Sleepiness Scale
OSA-Obstructive Sleep Apnea
SBQ-Stop Bang Questionnaire
With the SBQ, 998 (95.2%) had a low risk while 50 (4.8%) had a moderate to high risk of OSA. (Table 4). Almost 1020 (97.3%) of all the students reported not to have smoked before. (Table 5). Only a few 55(5.25%) had sleeping problems prior and 46(4.39%) sought help (Table 6).
Table 5:
Pattern of Substance use among respondents
| VARIABLES | SUBSTANCE USE (N=1048) | |
|---|---|---|
| Yes / % | No/& | |
| Do you smoke | 28 (2.67) | 1020 (97.33) |
| Do you take alcohol | 87 (8.30) | 961 (91.7) |
| Do you take any substance to help you sleep | 15 (1.43) | 1033 (98.57) |
| Do you take caffeine | 360 (34.35) | 688 (65.65) |
| Do you take cannabis | 20 (1.91) | 1028 (98.09) |
| Do you take marijuana | 22 (2.10) | 1026 (97.9) |
| Do you take tobacco | 29 (2.77) | 1019 (97.23) |
| Do you take any form of sedatives | 13 (1.24) | 1035 (98.76) |
Table 6:
Sleep disorder among respondents
| Variables | Frequency (N=1048) | Percentage (100%) |
|---|---|---|
| Have you sought help of any kind for sleeping | ||
| No | 1002 | 95.61 |
| Yes | 46 | 4.39 |
| Do you think you have Problems sleeping | ||
| No | 993 | 94.75 |
| Yes | 55 | 5.25 |
| Where did you seek for help (n=46) | ||
| Hospital | 15 | 27.27 |
| Patent medicine store | 15 | 27.27 |
| Pharmacy store | 17 | 30.91 |
| Traditional | 0 | 0 |
| Others | 8 | 14.55 |
| Do you take any drug to help you sleep (n=1048) | ||
| No | 1007 | 96.09 |
| Yes | 41 | 3.91 |
| Where do you get the drug (n=41) | ||
| Hospital | 4 | 9.76 |
| Patent Medicine | 9 | 21.95 |
| Pharmacy | 27 | 65.85 |
| Others | 1 | 2.44 |
Abnormal sleep pattern across the different class levels was shown with the highest prevalence reported among 600 level students (Fig. 1)
Figure 1:
Prevalence of abnormal sleep pattern
Religion, increasing levels of study, presence of chronic disease, smoking, and caffeine were significantly associated with average and abnormal sleepiness using ESS, (Table 7)
Table 7:
Relationship between sociodemographic factors and sleep apnea using ESS
| Variables | ESS | χ2 | p-value | ||
|---|---|---|---|---|---|
| N. Sleepiness | A.Sleepiness | Total | |||
| 897(85.59) | 151(14.41) | 1048(100) | |||
| Age | 2.862 | 0.09 | |||
| <18 | 46 (93.88) | 3 (6.12) | 49 (4.68) | ||
| >18 | 851 (85.19) | 148 (14.81) | 999 (95.32) | ||
| Sex | 0.700 | 0.40 | |||
| Female | 538 (84.86) | 96 (15.14) | 634 (60.5) | ||
| Male | 356 (86.71) | 58 (13.29) | 414 (39.5) | ||
| Religion | 13.21 | 0.00 | |||
| Christianity | 260 (80.25) | 64 (19.75) | 324 (30.9) | ||
| Islam | 636 (88.09) | 86 (11.91) | 722 (68.89) | ||
| Others | 1 (50.00) | 1 (50.00) | 2 (0.21) | ||
| Tribe | 3.598 | 0.46 | |||
| Fulani | 11 (78.57) | 3 (21.43) | 14 (1.34) | ||
| Hausa | 11 (78.57) | 3 (21.43) | 14 (1.34) | ||
| Igbo | 6 (85.71) | 1 (14.29) | 7 (0.67) | ||
| Yoruba | 834 (86.16) | 134 (13.84) | 968 (92.27) | ||
| Others | 35 (77.78) | 10 (22.22) | 45 (4.29) | ||
| Marital status | 1.855 | 0.17 | |||
| Married | 15 (75.00) | 5 (25.00) | 20 (1.91) | ||
| Single | 882 (85.80) | 146 (14.41) | 1028 (98.1) | ||
| Level | 46.25 | 0.00 | |||
| 100 | 320 (91.95) | 28 (8.05) | 348 (33.2) | ||
| 200 | 269 (89.67) | 31 (10.33) | 300 (28.62) | ||
| 300 | 113 (79.58) | 29 (20.42) | 142 (13.5) | ||
| 400 | 133 (78.70) | 36 (21.30) | 169 (16.13) | ||
| 500 | 23 (76.67) | 7 (23.33) | 30 (2.86) | ||
| 600 | 39 (66.10) | 20 (33.90) | 59 (5.63) |
ESS-Epworth Sleepiness Scale, N-normal, A-abnormal.
whereas female gender, religion, presence of chronic disease, smoking, use of sedatives and caffeine were significantly associated with OSA using SBQ at a p-value <0.005(Table 8)
Table 8:
Relationship between sociodemographic factors and sleep apnea using SBQ
| Variables | Stop bang Risk | χ2 | p-value | |||
|---|---|---|---|---|---|---|
| Low | Intermediate | High | Total | |||
| Age | 1.9263 | 0.38 | ||||
| <18 | 45 (91.84) | 4 (8.16) | 0 (0.00) | 49 (4.68) | ||
| >18 | 953 (95.40) | 42 (4.20) | 4 (0.40) | 999 (95.32) | ||
| Sex | 30.494 | <0.001 | ||||
| Female | 622 (98.11) | 10 (1.58) | 2 (0.32) | 634 (60.5) | ||
| Male | 376 (90.82) | 36 (8.70) | 2 (0.48) | 414 (39.5) | ||
| Religion | 10.617 | 0.03 | ||||
| Christianity | 305 (95.06) | 14 (4.32) | 2 (0.62) | 324 (30.9) | ||
| Islam | 689 (95.43) | 31 (4.29) | 2 (0.28) | 722 (21.29) | ||
| Others | 1 (50.00) | 1 (50.00) | 0.00 | 2 (0.19) | ||
| Tribe | 9.3405 | 0.31 | ||||
| Fulani | 14 (100.00) | 0 (0) | 0 (0) | 14 (1.34) | ||
| Hausa | 14 (100.00) | 0 (0) | 0 (0) | 14 (1.34) | ||
| Igbo | 6 (85.71) | 1 (14.29) | 0 | 7 (0.67) | ||
| Yoruba | 920 (95.04) | 45 (4.65) | 3 (0.31) | 968 (92.37) | ||
| Others | 44 (97.78) | 0 | 1 (2.22) | 45 (4.29) | ||
| Marital status | 1.5987 | 0.45 | ||||
| Married | 18 (90.00) | 2 (10.00) | 0 (0.00) | 20 (1.91) | ||
| Single | 980 (95.33) | 44 (4.28) | 4 (0.39) | 1028 (98.1) | ||
| Class level | 16.806 | 0.08 | ||||
| 100 | 333 (95.69) | 14 (4.02) | 1 (0.29) | 348 (33.2) | ||
| 200 | 282 (94.00) | 18 (6.00) | 0 (0) | 300 (28.6) | ||
| 300 | 135 (95.07) | 7 (4.93) | 0 (0) | 142 (13.5) | ||
| 400 | 161 (95.27) | 6 (3.55) | 2 (1.18) | 169 (16.1) | ||
| 500 | 28 (93.33) | 1 (3.33) | 1 (3.33) | 30 (2.9) | ||
| 600 | 59 (100.00) | 0 (0.00) | 0 (0.00) | 59 (5.6) | ||
SBQ-Stop Bang Questionnaire, χ2 - Chi2 test.
Discussion
The findings showed that respondents were mostly young with a mean age of 21± 2.69 years and slight female predominance. The majority of the participants were single, and almost all had never smoked before. While there was variation in the participants' sleep patterns, most of them reported normal sleep and when evaluated for obstructive sleep apnea (OSA) risk using the SBQ assessment tool, most participants were classified as low risk.
These demographics are consistent with earlier research findings, by Osaigbovo, Ogbolu, and Okeahialam9 which emphasize the young age of university attendees. Another study10 reported a similar tribe and marital distribution in Western Nigeria11. The data showed that most of the respondents had normal sleep patterns, in contrast to earlier studies which reveal that students experienced shorter sleep durations, inconsistent bedtimes, nocturnal snacking, and sleep patterns characterized by snoring11. This disparity could be attributed to useful coping strategies or lesser exposure to stressors. From these findings, the measures responsible for this improvement should be sustained and encouraged among undergraduates.
The majority had normal blood pressure and body mass index (BMI) values, and they were of typical height and weight. This health profile indicates a relatively healthy population, which is consistent with findings from other research involving similar age groups12 –13.
Regarding substance use, results indicated that the majority of the respondents did not engage in smoking, alcohol, and substances to aid sleep. While a sizable percentage of respondents reported using caffeine, a smaller percentage reported using sedatives or other substances like cannabis. This contrasts with other studies that reveal higher rates of cannabis and tobacco use among university students, suggesting a possible gap in substance use education and prevention efforts3. The high percentage of caffeine use is however supported by the results of other studies that prove that caffeine consumption is frequent among university students, and it is used to handle their academic stress and to stay awake14. These findings highlight the effectiveness of current preventive measures in reducing substance use among students but suggest a need for increased focus on caffeine use to prevent overuse. Further health campaigns and understanding the reasons behind substance use can inform prevention programs.
The results have further shown that most of the respondents mainly depend on over-the-counter medications from patent medicine dealers (PMDs) rather than seeking professional medical attention. Relative to other similar studies, these findings depict the general trend in which students prefer purchasing over-the-counter drugs owing to their affordability and accessibility15, but it also runs the risk of resulting in incorrect diagnosis and treatment. More public health education is required to raise awareness of the dangers of self-medication and the value of expert medical consultations.
Results on the Epworth Sleepiness Scale (ESS) demonstrate a high proportion of respondents answered no or very little in the likelihood of dozing during everyday situations. That is, the majority would not fall asleep talking to a person or sitting in a public place. However, a moderate fraction indicated a slight to moderate chance of dozing when lying down during the day or sitting as a passenger for a long period. This aligns with other studies that show university students had low levels of daytime sleepiness, but a greater tendency to fall asleep in bed or as a passenger which may result from sleep deficits accumulated by their busy schedules and the demands of their studies11. There is also a possible cultural factor, as some students are more familiar with taking naps when they have smaller amounts of free time throughout the day- particularly in less structured environments16.
The STOPBANG questionnaire showed only a small number of respondents had characteristics associated with increased risk for Obstructive Sleep Apnea (OSA) on the initial results. A minority reported loud snoring, and daytime tiredness or witnessed apnoeic events. Fewer still had risk factors like obesity (BMI), treatment for hypertension, or large neck circumference. It is noteworthy that most respondents were female and were at higher risk of OSA.
However, previous studies have reported a high prevalence of OSA among respondents who snorted, 16.3% who demonstrated extreme sleepiness, 10.0% who experienced weariness, and 8.0% who encountered drowsy driving 8.
In addition, studies noted that drug use, internet use, and psychological distress are associated with OSA16. There is a strong correlation between smoking and several sleep disorders and a quantitative relationship between the amount of smoking and the likelihood of developing these sleep difficulties17. There is also a strong correlation between caffeine use whose intake rises during stressful academic periods and restful sleep18.
Many students at the Nigerian university exhibited suboptimal knowledge of obstructive sleep apnoea 14, highlighting the necessity of integrating the assessment of sleep disorders into the undergraduate curriculum that primarily aims to facilitate the identification of clinical characteristics associated with prevalent sleep disorders, such as sleep apnoea.19
Conclusion
The sleep disorder tools show a moderate prevalence of sleep disorder and some important associated risks of OSA among undergraduate students. There is a tendency for this to become a big burden with an increase in age, therefore health promotion and prevention interventions are recommended early to students to create awareness of OSA risks and prevent OSA at an older age. Such education should be in the early years and should include the importance of improved sleep to physical and mental health. Optimizing sleep quality will ultimately improve the wellness of the future workforce and subsequently improve the quality of life of the general population in Nigeria and beyond.
Limitations of the study
The study was done among only three tertiary institutions, and it did not consider the youths who were out of school.
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