Sleep quality and its associated factors among university students in Malawi

Sleep quality and its associated factors among university students in Malawi | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Sleep quality and its associated factors among university students in Malawi Thokozani Mzumara, Owen Banda, George Munthali, Lazarus Obed Livingstone Banda, and 6 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5401765/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background Mental, physical, and social well-being have an impact on sleep quality. University students are vulnerable to sleep problems due to academic pressure coupled with psychosocial problems. Aim This study aimed to investigate sleep quality and identify its associated factors among university students in Malawi. Method A cross-sectional study was conducted using data collected from 984 students across 13 academic institutions (private and public) in Malawi. A standardized questionnaire was administered via Google Forms, assessing demographic sleep quality and its associated factor variables. Descriptive statistics, Chi-square tests, and logistic regression analyses were used to explore and examine possible associations between poor sleep quality and various demographic factors. Results The study revealed that 28.9% of students experienced poor sleep quality. Gender (p=0.039) and suicidal thoughts (p<0.001) were significantly associated with poor sleep. The results of regression analysis showed that, suicidal thoughts significantly influence bad sleep (p0.05). Conclusion The findings suggest that mental health concerns, particularly suicidal thoughts, are strongly linked to poor sleep quality among university students in Malawi. The results highlight the need for targeted interventions to address sleep-related issues and promote mental well-being among students. sleep quality mental health suicidal thoughts university students Malawi INTRODUCTION Buysse defines sleep health as a complex pattern of sleep-wakefulness tailored to the specific needs of individuals, society, and the environment, enhancing both physical and mental vitality. It is a term that includes components of sleep that are social, behavioral, environmental, and psychobiological. It is primarily defined by three factors: quantity, quality, and problems (Sosoo et al., 2023). Sleep issues, and more especially, major changes in sleep, are now classified among the top 10 warning indicators of suicide by the Substance Abuse and Mental Health Services Administration (SAMSHA) (Bernet & Joiner, 2007). Sleep is a basic biological requirement for both physical and mental health. Sleep is essential for more than just replenishing our bodies; it also helps with mood control, cognitive processing, and memory consolidation (Romeo et al., 2024). However, over the last seventy-five years, the quality of sleep has been declining (Mamun et al., 2020). Hence, poor sleep quality is an emerging public health threat worldwide, where university students are among the most vulnerable populations to sleep disruptions. Hence, the atmosphere of a university campus might be unclean and unhealthy for promoting restful sleep (Mamun et al., 2020). Poor sleep quality at universities can impair students' ability to study and negatively influence their psychological and physical well-being (Liu et al., 2021). As such, the ability to address the factors associated with poor sleep and implementing routine screenings are essential to lessening the burden on students. According to Wang & Biro (2021), mental health, social, and physical factors all have a significant impact on sleep quality. Furthermore, daily cumulative mobile phone use and use with the lights off before sleep are associated with poorer sleep quality (Weng et al., 2021; ). Similarly, another study reported that being stressed in the second year, using electronic devices at bedtime, and having chronic illness were factors associated with poor sleep quality (Nakie et al., 2024). Sleep disorders may be a sign of many mental health conditions, including suicidal thoughts, as well as a risk factor for them. Hence, an avoidable risk factor for suicidal ideas and actions is poor sleep (Littlewood et al. 2019). This bidirectional relationship between sleep and mental health means that while poor sleep can contribute to suicidal thoughts, pre-existing mental health issues can also lead to sleep disturbances, creating a vicious cycle that is difficult to break (Bernert et al., 2015). The prevalence of poor sleep quality among university students is high in Africa (Nekie et al., 2024). Poor sleep quality may be linked to unhealthy lifestyle habits related to psychological health and nutrition in the region. A recent study conducted using secondary data highlighted that there is a high level of academic stress among students in Malawi as coupled with high levels of suicide ideation (Mzumara, 2024). Different studies have been conducted across the world to assess poor sleep and associated factors among university students. Such sleep problems eventually result in irritability and affect lifestyle and interpersonal relationships (Giri et al., 2013). The existing previous research findings have shown that poor quality sleep is modally experienced by university students in many geographic areas including low-and-middle-income countries (LMICs), making the current problem globally rampant. In LMICs such as Malawi, the higher education sector continues to struggle to achieve excellence (Banda et al., 2022). Moreover, the country faces enormous socio-economic challenges such as unemployment (Wu et al., 2022). However, scholarly work on sleep quality analysis among university students in Malawi remains scanty. This study, therefore, sought to address this gap by investigating the prevalence of poor sleep and its associated factors within this population. The current findings can inform health education measures for improving lifestyle habits and sleep quality (Hashim et al., 2022). Moreover, knowledge generated from this study is integral to the development of sleep hygiene programs and lays a foundation for further work in this area. LITERATURE REVIEW Prevalence of sleep problems According to Vasconcelos et al. (2024), carried out in Brazil, 76 percent of respondents reported poor sleep quality with the most aspects affected being sleep latency, delayed sleep, sleep dysfunction in the day, and sleep disturbances. In a similar way, a large-scale study conducted by Nakie et al. (2023) found the total accumulative prevalence to be equal to 63. 31% for sleep quality deficiency among African university students. The scientists attributed the above issue to stress, overuse of electronic gadgets before bedtime, and various diseases. A study conducted by Van Der Heijde et al. (2019) in Europe established that the majority of the students in Dutch higher learning institutions had poor sleep quality, with only 41% of the students having good quality sleep. This tendency is further supported by a study that was done in Latin America by Gómez-Chiappe et al (2020). Furthermore, about 9% of university students in Bogotá, Colombia. According to the results of a cross-sectional study conducted by Hammouda and ElRafey (2024) in the Middle East on a sample of 291 fourth-year medical students at a University in Egypt, 5% suffer from insomnia or insufficient sleep quality. Such study findings show that this problem is prevalent in many cases of education and culture in various countries. Yu et al. (2023) also observed that low sleep quality is experienced commonly by Chinese medical students, but failed to provide certain percentages for it. The differences in the prevalence of poor quality sleep across studies could be in part explained by different methodologies such as the use of standardized questionnaires such as the Pittsburgh Sleep Quality Index (PSQI) (Li et al., 2020). Collectively, our studies emphasize that poor sleep quality is a prevalent problem among university students, which calls for specific strategies to fight this significant problem across the world. Factors associated with sleep quality Research in the present scenario has specifically discussed details about the lack of sufficient sleep among university students and various psychological, social, environmental, and lifestyle factors have been explored. As indicated by Nakie et al. (2023) and Silveira and Véras (2022), stress as a factor played a major role in the poor sleep quality of pupils. These indicators include; stress, electronic device usage during night, and chronic health conditions as revealed by the study done by Nakie et al. (2023). In a broader perspective, Silveira and Véras (2022) have identified worry, tension and technological device use as the leading factors in sleep interruptions among university students. However, according to the study conducted by Felisia et al.(2022), it was found that most of the students had poor sleep due to the following stress factors; academic-related stress was the most dominant stress affected by poor sleep among medical students of Udayana University. Moreover, in their study, they found that irregular sleep patterns and coffee consumption led to reduced quality of sleep, as poor sleep quality was observed with decreased sleep duration. The above-stated finding underscores the need to target academic needs as well as exercise and diet changes to enhance sleep. Meng et al. (2019) and Johnson et al. (2018) have stressed that environmental factors influence sleep quality in China. In their systematic review, Meng et al. (2019) paid due attention to examining the impact of noise from fellow occupants of the rooms and occupancy density per room on college students’ sleep quality. These variables were found to be the main disruptions to sleep. Building on such research findings, Johnson et al. (2018) studied the profound impacts of environmental conditions including noise and temperature on sleep thus stressing the importance of creating the right sleeping environment. It is an extra important issue that social support networks are important which affect the quality of sleep. Vasconcelos et al. (2024) conducted a study to understand the impact of consistent physical exercise in students, recently they concluded that students who exercise physically improve their sleep quality which is why they have stressed the need for students to take preferably healthy lifestyles. In the study of Schmickler et al. (2023), the social factors regarding sleep quality were explored and it was identified that poor social support widely affects anxiety and melancholy which in turn aggravates sleep disorders. This problem was reported to be more so with female students, who complain of poor sleep quality resulting from both academic demands and lack of social interaction. Hossain and Rahman (2020) study conducted in Bangladesh also revealed a strong positive relationship between poor quality of sleep and psychological stress, anxiety, and depression among university students. Following Silveira and Véras (2022) it can be concluded that mental health problems should be addressed to enhance the quality of sleep. Altogether, these many perceptions received from several contexts reveal the complexity of the characteristics of the factors that affect the sleep quality of university students. Such an integration underlines the requirement of employing holistic intervention approaches that consider the psychological, social environmental, and lifestyle factors. Numerous studies confirm significant disparities between female and male participants in concerns to quantity and quality of sleep and episodes of sleep disturbances. Prevailing empirical studies on some demographics have also universally revealed that women are more vulnerable to developing sleep disorders than men. Alosta et al. (2024) revealed that Jordanian women had higher rates of insomnia, nightly wakefulness, and other nuisances including recurrent nightmares, pain, and temperature regulation disturbance. In addition, La et al., (2020) identified a higher prevalence of insomnia among women than men in Korea. Schmickler et al. (2023) observed that female university students in Germany had poor sleep quality as compared to male students. Those differences were defined to be related to several specifics – perceived stress, academic performance, etc. Furthermore, Cha and Eun (2014) corroborate these findings by pointing out the fact that Korean women suffer from sleep disorders more so than men, this may be as a result of their working and caregiving responsibilities. In addition, Decker et al. (2022) established that women undergo more night disturbances than men, and the given sleep disruption is most usually experienced during early to middle adulthood as men and women care for their children. Besides, in a study conducted by Gharaibeh et al. (2022), it was found that female heart failure patients had poor sleep quality when compared to that of their male counterparts. Additionally, the authors have noticed that individuals of the female sex who had COVID-19 have more significant disturbances in the night’s sleep than the male patients (Abuhammad et al., 2023). Several reasons have been advocated to explain differences in sleep quality based on the gender factor. Sex differences are observed with hormonal changes including menstrual cycle, pregnancy, and menopause (Oh et al., 2023; Decker et al., 2022). In this case, a considerable percentage of the roles that are both professional and domestic are supposed to be filled by women and this makes them stressed, therefore they sleep less (Cha & Eun, 2014). Moreover, the societal roles and caregiving roles make these disparities worse as women are more vulnerable to experiencing sleeping disorders than men because of parental responsibilities (Cha & Eun, 2014). Furthermore, life attitudes including lower subjective social standing and other health behaviors including smoking are known to reduce the quality and amounts of sleep attained especially among female students (Schmickler et al., 2023). It is yet imperative to consider gender as one of the key factors that define the susceptibility of heart failure patients to have deficient sleep quality for there was slightly higher susceptibility in women than in men as presented by Gharaibeh et al. in a clinical setup (2022). Thus, the dichotomy of sleep health that has been established between men and women can be attributed to both, biological and environmental or social and psychosocial factors. METHODS Study design and data collection This was a cross-sectional study that collected data ( https://data.mendeley.com/drafts/xbfbcy5bhv ) using online Google forms from students nationwide. Students from thirteen academic institutions participated in the study, namely Chancellor College and Domasi College of Education (Eastern part of the country); Malawi Institute of Management, Nalikule College of Education, Daeyang University, Natural Resources College, and Lilongwe University of Agriculture and Natural Resources (Central part of the country); Mzuzu University (Northern part of the country). Included in the list of sampled institutions were the College of Medicine, Malawi Polytechnic, Malawi University of Science & Technology, the National College of Information Technology, Malawi College of Accountancy, and the Catholic University of Malawi (Southern part of the country). The data was gathered between May and July 2018 (Manda et al., 2021). The online data collection tool was designed to extract variables such as year of study (year 1, year 2, year 3, year 4), age (15–24, 25–34, 35 and above), gender (male, female, and prefer not to say) and level of study (post-graduate, undergraduate). Additionally, the study included the binomial variable “In the past two weeks, did you feel like ending your own life?(Yes or No)” to capture the potential side effect of poor quality sleep. However, the dependent variable was captured using the (Yes/No) question “In the past two weeks, have you experienced bad sleep?”. Any potential missing values were replaced by the mode. Data handling and analysis The online retrieved data was downloaded in a Microsoft Excel sheet and imported to SPSS version 27 for analysis. Descriptive statistics (univariate analysis), including percentages and frequency, presented using graphs and tables were used for illustrating the data. Bivariate analysis using the Chi-square test of association was conducted to assess the strength of the relationship between the dependent variable and explanatory variables. However, to identify factors associated with sleep quality, we employed the logistic regression model (multivariate analysis). All the analysis was statistically tested against alpha = 0.05. Ethical consideration Due to the nature of the current study, ethical approval was waived. However, the initial cross-sectional study (Manda et al., 2019) was ethically approved and adhered to the Declaration of Helsinki. We maintained privacy and confidentiality by keeping all participants anonymous. RESULTS Demographic characteristics of study participants The study comprised 984 students. According to gender, most participants were males, n = 636 (64.6%). The study found that n = 284 (28.9%) of the study participants reported bad sleep. According to the level of study, the majority were undergraduate students (n = 939, 95.6%) (Fig. 2). Based on a year of study, the majority of participants were in their first year (436, 44.3%) (. Based on age, the majority of study participants were aged between 15 and 24, n = 760 (77.2%). About 147 (13.9%) of participants have had suicidal thoughts in the previous two weeks. (Table 1 ) Table 1 Demographic Characteristics of Participants Characteristics Frequency (n = 25626) Percentage (%) Had suicide thought Yes 137 13.9 No 847 86.1 Gender Female 341 34.7 Male 636 64.6 Prefer not to say 7 0.7 Do you sleep badly Yes 15584 60.8 No 3967 15.5 Year of study Year 1 436 44.3 Year 2 Year 3 Year 4 222 201 125 22.6 20.4 12.7 Age 15–24 760 77.2 25–34 35+ Level of study Postgraduate Undergraduate 195 29 45 939 19.8 2.9 4.6 95.4 DEMOGRAPHIC FACTORS ASSOCIATED WITH BAD SLEEP The chi-square test showed that gender is significantly associated with bad sleep (p = 0.039). more males 172 (60.6%) had bad sleep compared to females. The chi-square test found that the association between having bad sleep and the level of study was not statistically significant (p = 0.177). Nonetheless, 6% ( 17 ) of postgraduate students had bad sleep compared to 94 (267) of undergraduate students. The chi-square test indicated that there was no significant association between bad sleep and the year of study (p = 0.096). The chi-square test showed that there was no association between age and having bad sleep among study participants. On the other hand, the chi-square test found that there is a significant association between poor sleep quality and suicidal thoughts (p < 0.001) (Table 2 ). Table 2 Cross tabulations of bad sleep and study variables Bad sleep No bad sleep Variable Category Frequency Percent Frequency Percent P value Gender Female Male Prefer Not to say 112 172 0 39.4 60.6 0.0 229 464 7 32.7 66.3 1.0 0.039 Age 15–24 25–34 35+ 229 51 4 80.6 18.0 1.4 531 144 25 759 20.6 3.6 0.105 Level of study Post graduate Undergraduate 17 267 6.0 94.0 28 672 4.0 96.0 0.177 Had Suicide thoughts Yes No 66 218 23.2 76.8 71 629 10.1 89.9 < 0.001 Year of study Year 1 Year 2 Year 3 Year 4 131 68 44 41 46.1 23.9 15.5 14.4 305 154 157 84 43.6 22.0 22.4 12.0 0.096 FACTORS INFLUENCING BAD SLEEP A logistic regression was run to ascertain the impact of gender and suicidal thoughts on bad sleep on the risk of having bad sleep. Statistical significance was seen in the model: x ( 9 ) = 49.977, p < 0.01. Seven percent (Nagelkerke R square) of the variation in bad sleep was explained by the model. The model has a sensitivity of 96.6% and a specificity of 8.8%, correctly predicting 71.4% of the cases. Participants with suicidal thoughts were two times more likely to have bad sleep (OR = 2.763, 95% CI = 1.897–4.025). According to the model, gender, level of study, year of study, and age do not significantly influence bad sleep. 95% CI for Exp (B) Independent variables P value Exp (B) Lower Upper Suicidal thought 0.000 2.763 1.860 4.025 Gender 0.413 Gender 1 Gender 2 Age Age 1 Age 2 Year of study Year of study 1 Year of study 2 Year of study 3 Level of study 1 Constant 0.9184 0.999 0.049 0.130 0.034 0.083 0.662 0.106 0.162 0.052 0.032 1.223 779553469.589 1.351 3.312 0.921 1.400 0.726 2.015 0.430 0.909 0.000 0.915 1.091 0.636 0.931 0.464 0.993 1.646 1.996 10.052 1.333 2.106 1.137 4.085 DISCUSSION This study found that a lower proportion of participants experienced poor sleep In contrast to a study conducted in Jilin Province, China, found a higher proportion of students with bad sleep (Li et al., 2020). However, a study conducted among Bangladesh students found a lower prevalence of subjective bad sleep quality (Mamun et al., 2020). We attribute the differences to variations in methodology. Our study did not use any tool to assess sleep, whereas the study in China used the Pittsburgh Sleep Quality Index (PSQI), a self-administered questionnaire, to assess sleep for one month. Research has shown that the prevalence of sleep quality varies widely depending on the definition and method used. The current review found no association between age and poor sleep quality. However, Schimickler et al. (2019) reported that older age was a risk factor for poor sleep quality among German university students, though the effect size was small. The observed differences may be due to variations in data analysis and sample size, as Schimickler's study used multiple regression analysis and had a much larger sample size of 1,684 compared to the present study. According to research, people's sleep architecture changes with age, resulting in shorter sleep durations, more awakenings, and trouble staying asleep. These changes may cause people to have lower-quality sleep (Ohayon et al., 2004). The results of this research, however, point out that, at least for the group under study, these age-related sleep alterations may not always result in less quality sleep. The results of this study imply that, rather than age per se, age-related sleep problems may be more closely associated with environmental variables, lifestyle choices, and health status (Zavecz et al., 2023). A study conducted with a focus on middle-aged persons discovered that lifestyle factors—such as physical exercise, stress levels, and social support—had a greater influence on the quality of sleep than age (Mengelers et al.2023). However, the participants in our study were mostly in the middle age range but lifestyle variables were not collected in the data. The current study identified a link between gender and poor sleep quality, with more males being affected compared to females. However, Fatima et al. (2016) reported a higher prevalence of poor sleep quality among females than males in a large Australian population study. In contrast, no statistically significant association between gender and sleep quality was found among students from two tertiary institutions in Northern Malaysia (Lai & Say, 2013) or among Chinese 2 (Chen et al., 2020). These discrepancies across studies may be attributed to variations in sample size, methodology, and geographic location. Additionally, cultural, socio-economic, and academic differences could have influenced these findings (Jeon et al., 2021). This finding adds to the growing body of research that explores gender differences in sleep patterns and their impact on overall health. Numerous studies have historically indicated that women are more prone than men to experience sleep problems, such as insomnia, and poor-quality sleep, which are frequently linked to hormonal changes, stress, and caring for others (Zhang & Wing, 2006), new studies are starting to paint a more complex picture, suggesting that men may also have serious sleep difficulties, particularly in certain populations like college students. Lifestyle variables may be a contributing factor to the increased incidence of poor sleep quality among the male participants in the research. According to Tavernier and Willoughby (2014), men may be more likely to partake in sleep-disturbing activities such as late-night electronic device use, caffeine or alcohol use, and irregular sleep regimens. Furthermore, social pressures and expectations, including stress related to school or work, may result in increased anxiety and stress among males, which can negatively impact sleep. The current research found a significant association between suicidal thoughts and poor sleep. This is consistent with a previous study (Pigeon et al., 2012). Furthermore, suicidal thoughts and poor sleep patterns were also found among undergraduate students at a large public university in the southeastern United States (Nadorff et al., 2011). The findings of our study can be explained by the role of serotonin, which affects both sleep regulation and suicide, suggesting a common neurobiological basis (Bertnet & Joiner, 2007). The association between suicidal thoughts and poor sleep quality among university students underscores the complex interplay of mental health and sleep disturbances. Research has demonstrated that sleep problems, such as insomnia, poor sleep quality, and disrupted sleep patterns, are closely linked with an increased risk of suicidal ideation and behaviors. One critical factor is the role of sleep in emotional regulation. Sleep deprivation or poor sleep quality can impair the brain's ability to manage emotions effectively, leading to heightened stress, anxiety, and depression, which are significant risk factors for suicidal thoughts (Walker, 2019). Additionally, sleep disturbances can exacerbate feelings of hopelessness and despair, further contributing to the risk of suicide (Pigeon et al., 2012). University students are particularly vulnerable to sleep disturbances due to the unique stressors they face, including academic pressures, social challenges, and lifestyle changes. The irregular sleep patterns common among students, such as staying up late and varying sleep schedules, can disrupt the body's circadian rhythm, leading to chronic sleep problems (Hershner & Chervin, 2014). This disruption not only affects cognitive functioning and academic performance but also has profound implications for mental health. The association between sleep and suicide may be primarily influenced by aspects related to mood management. For example, sleep may not be able to offer disturbed people an emotional haven (Bernet & Joiner, 2007). Addressing this relationship requires a holistic approach that includes promoting healthy sleep hygiene, providing mental health support, and creating an environment that fosters emotional well-being among students. Thus, this finding is particularly helpful and offers a key therapeutic focus for upcoming suicide prevention initiatives by considering sleep disruptions as a warning indication (Bernert & Joiner, 2007). The current paper revealed no association between the level of study and poor sleep quality. This finding agrees with a study conducted among Chinese medical students (Chen et al., 2020). On the other hand, Li et al. (2020) reported that the level of study was a significant predictor of poor sleep quality among Chinese college students, with students in lower grades having a higher prevalence of poor sleep quality compared to those in higher grades. This could be due to freshmen being more susceptible to the new freedoms of living away from home for the first time and having little experience in dealing with the academic rigor of the curriculum (Liu et al., 2020). Similar results were found among incoming university students in Taiwan (Cheng et al., 2012). Limitations The study is not without drawbacks. The subjective nature of the study design makes it prone to recall bias since the study did not use objective measures of sleep quality, such as polysomnography or actigraphy. Moreover, the study only focused on youths in school, and as such, it cannot be generalized to the entire youth population, such as non-student youth or older adults. Lastly, the study did not account for potential confounding variables such as lifestyle habits (e.g., caffeine or alcohol consumption), academic workload, and environmental factors that could have influenced sleep quality. Conclusion This study provides valuable information on the prevalence and associated factors of poor sleep quality among university students in Malawi. The findings reveal that a significant proportion of students experience poor sleep, with suicidal thoughts and gender being significant associated factors. While the study did not find significant associations between poor sleep quality and other demographic factors like age, level of study, and year of study, the identified link between mental health concerns and sleep disturbances underscores the importance of addressing mental health-related issues and improving sleep quality among students. 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Psychol Med 49(3):403–411. 10.1017/S0033291718001009 Romero K, Caballero I, José M, Romero R (2024) Exploring suicide ideation in university students: Sleep quality, social media, self-esteem, and barriers to seeking psychological help. Front Psychiatry 15:1352889. https://doi.org/10.3389/fpsyt.2024.1352889 Mzumara T (2024) Excessive internet use as a risk factor for suicide ideation among university students in Malawi: A cross-sectional study. Health Sci Rep 7(6):e2194. https://doi.org/10.1002/hsr2.2194 Bernert RA, Joiner TE (2007) Sleep disturbances and suicide risk: A review of the literature. Neuropsychiatr Dis Treat 3(6):735–743. https://doi.org/10.2147/ndt.s1248 Abuhammad S, Alzoubi KH, Khabour OF, Hamaideh S, Khasawneh B (2023) Sleep quality and sleep patterns among recovered individuals during post-COVID-19 among Jordanian: A cross-sectional national study. Medicine 102(3):e32737. https://doi.org/10.1097/MD.0000000000032737 Alosta MR, Oweidat I, Alsadi M, Alsaraireh MM, Oleimat B, Othman EH (2024) Predictors and disturbances of sleep quality between men and women: results from a cross-sectional study in Jordan. BMC Psychiatry 24(200). https://doi.org/10.1186/s12888-024-05662-x Cha S-E, Eun K-S (2014) Gender difference in sleep problems: Focused on time use in daily life of Korea. Soc Indic Res 119(3):1447–1465. https://doi.org/10.1007/s11205-013-0550-1 Chandran P, Kiran R, Kurian NM (2023) The relationship between sleep quality and academic performance among undergraduate medical students: A cross-sectional study. Int J Acad Med Pharm 5(5):1151–1155 Decker AN, Fischer AR, Gunn HE (2022) Socio-ecological context of sleep: Gender differences and couples’ relationships as exemplars. Curr Psychiatry Rep 24:831–840. https://doi.org/10.1007/s11920-022-01393-6 Gharaibeh B, Al-Absi I, Abuhammad S, Gharaibeh M (2022) Dimensions of sleep characteristics and predictors of sleep quality among heart failure patients: A STROBE compliant cross-sectional study in Jordan. Medicine 101(52):e32585. https://doi.org/10.1097/MD.0000000000032585 Gómez-Chiappe N, Lara-Monsalve PA, Gómez AM, González JC, González L, Gutiérrez-Prieto JE, Jaimes-Reyes MA, Castillo JS (2020) Poor sleep quality and associated factors in university students in Bogotá D.C., Colombia. Sleep Sci 13(2):125–130. https://doi.org/10.5935/1984-0063.20190141 Hammouda MAA, ElRafey DSM (2024) Sleep quality and its effect on academic performance among fourth-year medical students at Zagazig University. Zagazig Univ Med J 30(11):76–82. https://doi.org/10.21608/zumj.2021.56954.2071 La YK, Choi YH, Chu MK, Nam JM, Choi Y-C, Kim W-J (2020) Gender differences influence over insomnia in Korean population: A cross-sectional study. PLoS ONE 15(1):e0227190. https://doi.org/10.1371/journal.pone.0227190 Nakie NM, Obodai J, Ahortor MY (2023) Sleep quality among African university students: A systematic review and meta-analysis. Afr J Health Stud 9(2):124–138 Oh J, Kim E, Huh I (2023) Associations between weekend catch-up sleep and health-related quality of life with a focus on gender differences. Sci Rep 13:20280. https://doi.org/10.1038/s41598-023-47244-z Schmickler JM, Blaschke S, Robbins R, Mess F (2023) Determinants of Sleep Quality: A Cross-Sectional Study in University Students. International Journal of Environmental Research and Public Health, 20 (2019). https://doi.org/10.3390/ijerph20032019 Van Der Heijde C, Van Weeren M, Vonk P (2019) Sleep problems among Dutch higher educational students, working towards solutions. Student Health Service, University of Amsterdam Vasconcelos D, de Santos S, Viana KVS, Diniz DCL, Silva IT, Borges ICO, M. C. S. T., de Ferreira LG (2024) F. Sleep patterns and quality in university students: Characteristics and associated factors. Manual Therapy, Posturology & Rehabilitation Journal , 22(1364). https://doi.org/10.17784/mtprehabjournal.2024.22.1364 Yu L, Wu Y, Guo C, Qiao Q, Wang X, Zang S (2023) Latent profile analysis for health-related quality of life, sleep quality, morning and evening type, and internet addiction among medical students. Sci Rep 13:11247. https://doi.org/10.1038/s41598-023-38302-7 Manda TD, Jamu ES, Mwakilama EP, Maliwichi-Senganimalunje L (2019) Internet Addiction and Mental Health among College Students in Malawi. In G. Kayange, Y. Ndasauka (Eds.), Addiction in South and East Africa. Palgrave Macmillan. https://doi.org/10.1007/978-3-030-13593-5_16 Additional Declarations The authors declare no competing interests. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5401765","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":374777676,"identity":"94bc642e-aa18-4355-bc41-26af838eda10","order_by":0,"name":"Thokozani 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10:11:59","currentVersionCode":1,"declarations":{"humanSubjects":true,"vertebrateSubjects":false,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":true,"humanSubjectConsent":true,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":false},"doi":"10.21203/rs.3.rs-5401765/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5401765/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":68476175,"identity":"ecf867d5-2253-40b1-9018-6443ce383ed7","added_by":"auto","created_at":"2024-11-07 16:04:55","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":521433,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5401765/v1/f3ec3830-a515-4ff2-8561-47fce0e15417.pdf"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003e\u003cstrong\u003eSleep quality and its associated factors among university students in Malawi\u003c/strong\u003e\u003c/p\u003e","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eBuysse defines sleep health as a complex pattern of sleep-wakefulness tailored to the specific needs of individuals, society, and the environment, enhancing both physical and mental vitality. It is a term that includes components of sleep that are social, behavioral, environmental, and psychobiological. It is primarily defined by three factors: quantity, quality, and problems (Sosoo et al., 2023). Sleep issues, and more especially, major changes in sleep, are now classified among the top 10 warning indicators of suicide by the Substance Abuse and Mental Health Services Administration (SAMSHA) (Bernet \u0026amp; Joiner, 2007). Sleep is a basic biological requirement for both physical and mental health. Sleep is essential for more than just replenishing our bodies; it also helps with mood control, cognitive processing, and memory consolidation (Romeo et al., 2024).\u003c/p\u003e \u003cp\u003eHowever, over the last seventy-five years, the quality of sleep has been declining (Mamun et al., 2020). Hence, poor sleep quality is an emerging public health threat worldwide, where university students are among the most vulnerable populations to sleep disruptions. Hence, the atmosphere of a university campus might be unclean and unhealthy for promoting restful sleep (Mamun et al., 2020). Poor sleep quality at universities can impair students' ability to study and negatively influence their psychological and physical well-being (Liu et al., 2021). As such, the ability to address the factors associated with poor sleep and implementing routine screenings are essential to lessening the burden on students.\u003c/p\u003e \u003cp\u003eAccording to Wang \u0026amp; Biro (2021), mental health, social, and physical factors all have a significant impact on sleep quality. Furthermore, daily cumulative mobile phone use and use with the lights off before sleep are associated with poorer sleep quality (Weng et al., 2021; ). Similarly, another study reported that being stressed in the second year, using electronic devices at bedtime, and having chronic illness were factors associated with poor sleep quality (Nakie et al., 2024). Sleep disorders may be a sign of many mental health conditions, including suicidal thoughts, as well as a risk factor for them. Hence, an avoidable risk factor for suicidal ideas and actions is poor sleep (Littlewood et al. 2019). This bidirectional relationship between sleep and mental health means that while poor sleep can contribute to suicidal thoughts, pre-existing mental health issues can also lead to sleep disturbances, creating a vicious cycle that is difficult to break (Bernert et al., 2015).\u003c/p\u003e \u003cp\u003eThe prevalence of poor sleep quality among university students is high in Africa (Nekie et al., 2024). Poor sleep quality may be linked to unhealthy lifestyle habits related to psychological health and nutrition in the region. A recent study conducted using secondary data highlighted that there is a high level of academic stress among students in Malawi as coupled with high levels of suicide ideation (Mzumara, 2024). Different studies have been conducted across the world to assess poor sleep and associated factors among university students. Such sleep problems eventually result in irritability and affect lifestyle and interpersonal relationships (Giri et al., 2013).\u003c/p\u003e \u003cp\u003eThe existing previous research findings have shown that poor quality sleep is modally experienced by university students in many geographic areas including low-and-middle-income countries (LMICs), making the current problem globally rampant. In LMICs such as Malawi, the higher education sector continues to struggle to achieve excellence (Banda et al., 2022). Moreover, the country faces enormous socio-economic challenges such as unemployment (Wu et al., 2022). However, scholarly work on sleep quality analysis among university students in Malawi remains scanty. This study, therefore, sought to address this gap by investigating the prevalence of poor sleep and its associated factors within this population. The current findings can inform health education measures for improving lifestyle habits and sleep quality (Hashim et al., 2022). Moreover, knowledge generated from this study is integral to the development of sleep hygiene programs and lays a foundation for further work in this area.\u003c/p\u003e\n\n\n\n "},{"header":"LITERATURE REVIEW","content":"\u003ch2\u003ePrevalence of sleep problems\u003c/h2\u003e\u003cp\u003eAccording to Vasconcelos et al. (2024), carried out in Brazil, 76 percent of respondents reported poor sleep quality with the most aspects affected being sleep latency, delayed sleep, sleep dysfunction in the day, and sleep disturbances. In a similar way, a large-scale study conducted by Nakie et al. (2023) found the total accumulative prevalence to be equal to 63. 31% for sleep quality deficiency among African university students. The scientists attributed the above issue to stress, overuse of electronic gadgets before bedtime, and various diseases. A study conducted by Van Der Heijde et al. (2019) in Europe established that the majority of the students in Dutch higher learning institutions had poor sleep quality, with only 41% of the students having good quality sleep. This tendency is further supported by a study that was done in Latin America by Gómez-Chiappe et al (2020). Furthermore, about 9% of university students in Bogotá, Colombia. According to the results of a cross-sectional study conducted by Hammouda and ElRafey (2024) in the Middle East on a sample of 291 fourth-year medical students at a University in Egypt, 5% suffer from insomnia or insufficient sleep quality. Such study findings show that this problem is prevalent in many cases of education and culture in various countries. Yu et al. (2023) also observed that low sleep quality is experienced commonly by Chinese medical students, but failed to provide certain percentages for it. The differences in the prevalence of poor quality sleep across studies could be in part explained by different methodologies such as the use of standardized questionnaires such as the Pittsburgh Sleep Quality Index (PSQI) (Li et al., 2020). Collectively, our studies emphasize that poor sleep quality is a prevalent problem among university students, which calls for specific strategies to fight this significant problem across the world.\u003c/p\u003e\u003ch3\u003eFactors associated with sleep quality\u003c/h3\u003e\u003cp\u003eResearch in the present scenario has specifically discussed details about the lack of sufficient sleep among university students and various psychological, social, environmental, and lifestyle factors have been explored. As indicated by Nakie et al. (2023) and Silveira and Véras (2022), stress as a factor played a major role in the poor sleep quality of pupils. These indicators include; stress, electronic device usage during night, and chronic health conditions as revealed by the study done by Nakie et al. (2023). In a broader perspective, Silveira and Véras (2022) have identified worry, tension and technological device use as the leading factors in sleep interruptions among university students. However, according to the study conducted by Felisia et al.(2022), it was found that most of the students had poor sleep due to the following stress factors; academic-related stress was the most dominant stress affected by poor sleep among medical students of Udayana University. Moreover, in their study, they found that irregular sleep patterns and coffee consumption led to reduced quality of sleep, as poor sleep quality was observed with decreased sleep duration. The above-stated finding underscores the need to target academic needs as well as exercise and diet changes to enhance sleep. Meng et al. (2019) and Johnson et al. (2018) have stressed that environmental factors influence sleep quality in China. In their systematic review, Meng et al. (2019) paid due attention to examining the impact of noise from fellow occupants of the rooms and occupancy density per room on college students’ sleep quality. These variables were found to be the main disruptions to sleep. Building on such research findings, Johnson et al. (2018) studied the profound impacts of environmental conditions including noise and temperature on sleep thus stressing the importance of creating the right sleeping environment.\u003c/p\u003e\u003cp\u003eIt is an extra important issue that social support networks are important which affect the quality of sleep. Vasconcelos et al. (2024) conducted a study to understand the impact of consistent physical exercise in students, recently they concluded that students who exercise physically improve their sleep quality which is why they have stressed the need for students to take preferably healthy lifestyles. In the study of Schmickler et al. (2023), the social factors regarding sleep quality were explored and it was identified that poor social support widely affects anxiety and melancholy which in turn aggravates sleep disorders. This problem was reported to be more so with female students, who complain of poor sleep quality resulting from both academic demands and lack of social interaction.\u003c/p\u003e\u003cp\u003eHossain and Rahman (2020) study conducted in Bangladesh also revealed a strong positive relationship between poor quality of sleep and psychological stress, anxiety, and depression among university students. Following Silveira and Véras (2022) it can be concluded that mental health problems should be addressed to enhance the quality of sleep. Altogether, these many perceptions received from several contexts reveal the complexity of the characteristics of the factors that affect the sleep quality of university students. Such an integration underlines the requirement of employing holistic intervention approaches that consider the psychological, social environmental, and lifestyle factors.\u003c/p\u003e\u003cp\u003eNumerous studies confirm significant disparities between female and male participants in concerns to quantity and quality of sleep and episodes of sleep disturbances. Prevailing empirical studies on some demographics have also universally revealed that women are more vulnerable to developing sleep disorders than men. Alosta et al. (2024) revealed that Jordanian women had higher rates of insomnia, nightly wakefulness, and other nuisances including recurrent nightmares, pain, and temperature regulation disturbance. In addition, La et al., (2020) identified a higher prevalence of insomnia among women than men in Korea. Schmickler et al. (2023) observed that female university students in Germany had poor sleep quality as compared to male students. Those differences were defined to be related to several specifics – perceived stress, academic performance, etc. Furthermore, Cha and Eun (2014) corroborate these findings by pointing out the fact that Korean women suffer from sleep disorders more so than men, this may be as a result of their working and caregiving responsibilities. In addition, Decker et al. (2022) established that women undergo more night disturbances than men, and the given sleep disruption is most usually experienced during early to middle adulthood as men and women care for their children. Besides, in a study conducted by Gharaibeh et al. (2022), it was found that female heart failure patients had poor sleep quality when compared to that of their male counterparts. Additionally, the authors have noticed that individuals of the female sex who had COVID-19 have more significant disturbances in the night’s sleep than the male patients (Abuhammad et al., 2023).\u003c/p\u003e\u003cp\u003eSeveral reasons have been advocated to explain differences in sleep quality based on the gender factor. Sex differences are observed with hormonal changes including menstrual cycle, pregnancy, and menopause (Oh et al., 2023; Decker et al., 2022). In this case, a considerable percentage of the roles that are both professional and domestic are supposed to be filled by women and this makes them stressed, therefore they sleep less (Cha \u0026amp; Eun, 2014). Moreover, the societal roles and caregiving roles make these disparities worse as women are more vulnerable to experiencing sleeping disorders than men because of parental responsibilities (Cha \u0026amp; Eun, 2014). Furthermore, life attitudes including lower subjective social standing and other health behaviors including smoking are known to reduce the quality and amounts of sleep attained especially among female students (Schmickler et al., 2023). It is yet imperative to consider gender as one of the key factors that define the susceptibility of heart failure patients to have deficient sleep quality for there was slightly higher susceptibility in women than in men as presented by Gharaibeh et al. in a clinical setup (2022). Thus, the dichotomy of sleep health that has been established between men and women can be attributed to both, biological and environmental or social and psychosocial factors.\u003c/p\u003e"},{"header":"METHODS","content":"\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eStudy design and data collection\u003c/h2\u003e \u003cp\u003eThis was a cross-sectional study that collected data (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://data.mendeley.com/drafts/xbfbcy5bhv\u003c/span\u003e\u003cspan address=\"https://data.mendeley.com/drafts/xbfbcy5bhv\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e)\u003c/span\u003e using online Google forms from students nationwide. Students from thirteen academic institutions participated in the study, namely Chancellor College and Domasi College of Education (Eastern part of the country); Malawi Institute of Management, Nalikule College of Education, Daeyang University, Natural Resources College, and Lilongwe University of Agriculture and Natural Resources (Central part of the country); Mzuzu University (Northern part of the country). Included in the list of sampled institutions were the College of Medicine, Malawi Polytechnic, Malawi University of Science \u0026amp; Technology, the National College of Information Technology, Malawi College of Accountancy, and the Catholic University of Malawi (Southern part of the country). The data was gathered between May and July 2018 (Manda et al., 2021).\u003c/p\u003e \u003cp\u003eThe online data collection tool was designed to extract variables such as year of study (year 1, year 2, year 3, year 4), age (15\u0026ndash;24, 25\u0026ndash;34, 35 and above), gender (male, female, and prefer not to say) and level of study (post-graduate, undergraduate). Additionally, the study included the binomial variable \u0026ldquo;In the past two weeks, did you feel like ending your own life?(Yes or No)\u0026rdquo; to capture the potential side effect of poor quality sleep. However, the dependent variable was captured using the (Yes/No) question \u0026ldquo;In the past two weeks, have you experienced bad sleep?\u0026rdquo;. Any potential missing values were replaced by the mode.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eData handling and analysis\u003c/h3\u003e\n\u003cp\u003eThe online retrieved data was downloaded in a Microsoft Excel sheet and imported to SPSS version 27 for analysis. Descriptive statistics (univariate analysis), including percentages and frequency, presented using graphs and tables were used for illustrating the data. Bivariate analysis using the Chi-square test of association was conducted to assess the strength of the relationship between the dependent variable and explanatory variables. However, to identify factors associated with sleep quality, we employed the logistic regression model (multivariate analysis). All the analysis was statistically tested against alpha\u0026thinsp;=\u0026thinsp;0.05.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eEthical consideration\u003c/h2\u003e \u003cp\u003e Due to the nature of the current study, ethical approval was waived. However, the initial cross-sectional study (Manda et al., 2019) was ethically approved and adhered to the Declaration of Helsinki. We maintained privacy and confidentiality by keeping all participants anonymous.\u003c/p\u003e \u003c/div\u003e"},{"header":"RESULTS","content":"\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eDemographic characteristics of study participants\u003c/h2\u003e \u003cp\u003eThe study comprised 984 students. According to gender, most participants were males, n\u0026thinsp;=\u0026thinsp;636 (64.6%). The study found that n\u0026thinsp;=\u0026thinsp;284 (28.9%) of the study participants reported bad sleep. According to the level of study, the majority were undergraduate students (n\u0026thinsp;=\u0026thinsp;939, 95.6%) (Fig.\u0026nbsp;2). Based on a year of study, the majority of participants were in their first year (436, 44.3%) (. Based on age, the majority of study participants were aged between 15 and 24, n\u0026thinsp;=\u0026thinsp;760 (77.2%). About 147 (13.9%) of participants have had suicidal thoughts in the previous two weeks. (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e)\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDemographic Characteristics of Participants\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCharacteristics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFrequency (n\u0026thinsp;=\u0026thinsp;25626)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePercentage (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHad suicide thought\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e137\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e13.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e847\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e86.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e341\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e34.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e636\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e64.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrefer not to say\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDo you sleep badly\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e15584\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e60.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3967\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e15.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYear of study\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYear 1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e436\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e44.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYear 2\u003c/p\u003e \u003cp\u003eYear 3\u003c/p\u003e \u003cp\u003eYear 4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e222\u003c/p\u003e \u003cp\u003e201\u003c/p\u003e \u003cp\u003e125\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e22.6\u003c/p\u003e \u003cp\u003e20.4\u003c/p\u003e \u003cp\u003e12.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e15\u0026ndash;24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e760\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e77.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e25\u0026ndash;34\u003c/p\u003e \u003cp\u003e35+\u003c/p\u003e \u003cp\u003eLevel of study\u003c/p\u003e \u003cp\u003ePostgraduate\u003c/p\u003e \u003cp\u003eUndergraduate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e195\u003c/p\u003e \u003cp\u003e29\u003c/p\u003e \u003cp\u003e45\u003c/p\u003e \u003cp\u003e939\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e19.8\u003c/p\u003e \u003cp\u003e2.9\u003c/p\u003e \u003cp\u003e4.6\u003c/p\u003e \u003cp\u003e95.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e\u003c/h2\u003e \u003cdiv id=\"Sec12\" class=\"Section3\"\u003e \u003ch2\u003eDEMOGRAPHIC FACTORS ASSOCIATED WITH BAD SLEEP\u003c/h2\u003e \u003cp\u003eThe chi-square test showed that gender is significantly associated with bad sleep (p\u0026thinsp;=\u0026thinsp;0.039). more males 172 (60.6%) had bad sleep compared to females. The chi-square test found that the association between having bad sleep and the level of study was not statistically significant (p\u0026thinsp;=\u0026thinsp;0.177). Nonetheless, 6% (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e) of postgraduate students had bad sleep compared to 94 (267) of undergraduate students. The chi-square test indicated that there was no significant association between bad sleep and the year of study (p\u0026thinsp;=\u0026thinsp;0.096). The chi-square test showed that there was no association between age and having bad sleep among study participants. On the other hand, the chi-square test found that there is a significant association between poor sleep quality and suicidal thoughts (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Table \u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCross tabulations of bad sleep and study variables\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eBad sleep\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003eNo bad sleep\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCategory\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFrequency\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePercent\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eFrequency\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003ePercent\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eP value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003cp\u003eMale\u003c/p\u003e \u003cp\u003ePrefer Not to say\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e112\u003c/p\u003e \u003cp\u003e172\u003c/p\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e39.4\u003c/p\u003e \u003cp\u003e60.6\u003c/p\u003e \u003cp\u003e0.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e229\u003c/p\u003e \u003cp\u003e464\u003c/p\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e32.7\u003c/p\u003e \u003cp\u003e66.3\u003c/p\u003e \u003cp\u003e1.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.039\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15\u0026ndash;24\u003c/p\u003e \u003cp\u003e25\u0026ndash;34\u003c/p\u003e \u003cp\u003e35+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e229\u003c/p\u003e \u003cp\u003e51\u003c/p\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e80.6\u003c/p\u003e \u003cp\u003e18.0\u003c/p\u003e \u003cp\u003e1.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e531\u003c/p\u003e \u003cp\u003e144\u003c/p\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e759\u003c/p\u003e \u003cp\u003e20.6\u003c/p\u003e \u003cp\u003e3.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.105\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLevel of study\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePost graduate\u003c/p\u003e \u003cp\u003eUndergraduate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e17\u003c/p\u003e \u003cp\u003e267\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.0\u003c/p\u003e \u003cp\u003e94.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e28\u003c/p\u003e \u003cp\u003e672\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.0\u003c/p\u003e \u003cp\u003e96.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.177\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHad Suicide thoughts\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e66\u003c/p\u003e \u003cp\u003e218\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e23.2\u003c/p\u003e \u003cp\u003e76.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e71\u003c/p\u003e \u003cp\u003e629\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e10.1\u003c/p\u003e \u003cp\u003e89.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYear of study\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYear 1\u003c/p\u003e \u003cp\u003eYear 2\u003c/p\u003e \u003cp\u003eYear 3\u003c/p\u003e \u003cp\u003eYear 4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e131\u003c/p\u003e \u003cp\u003e68\u003c/p\u003e \u003cp\u003e44\u003c/p\u003e \u003cp\u003e41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e46.1\u003c/p\u003e \u003cp\u003e23.9\u003c/p\u003e \u003cp\u003e15.5\u003c/p\u003e \u003cp\u003e14.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e305\u003c/p\u003e \u003cp\u003e154\u003c/p\u003e \u003cp\u003e157\u003c/p\u003e \u003cp\u003e84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e43.6\u003c/p\u003e \u003cp\u003e22.0\u003c/p\u003e \u003cp\u003e22.4\u003c/p\u003e \u003cp\u003e12.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.096\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eFACTORS INFLUENCING BAD SLEEP\u003c/h2\u003e \u003cp\u003eA logistic regression was run to ascertain the impact of gender and suicidal thoughts on bad sleep on the risk of having bad sleep. Statistical significance was seen in the model: x (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e)\u0026thinsp;=\u0026thinsp;49.977, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01. Seven percent (Nagelkerke R square) of the variation in bad sleep was explained by the model. The model has a sensitivity of 96.6% and a specificity of 8.8%, correctly predicting 71.4% of the cases. Participants with suicidal thoughts were two times more likely to have bad sleep (OR\u0026thinsp;=\u0026thinsp;2.763, 95% CI\u0026thinsp;=\u0026thinsp;1.897\u0026ndash;4.025). According to the model, gender, level of study, year of study, and age do not significantly influence bad sleep.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Taba\" border=\"1\"\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e95% CI for Exp (B)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIndependent variables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eP value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eExp (B)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLower\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003eUpper\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSuicidal thought\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e0.000\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.763\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.860\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e4.025\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.413\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGender 1\u003c/p\u003e \u003cp\u003eGender 2\u003c/p\u003e \u003cp\u003eAge\u003c/p\u003e \u003cp\u003eAge 1\u003c/p\u003e \u003cp\u003eAge 2\u003c/p\u003e \u003cp\u003eYear of study\u003c/p\u003e \u003cp\u003eYear of study 1\u003c/p\u003e \u003cp\u003eYear of study 2\u003c/p\u003e \u003cp\u003eYear of study 3\u003c/p\u003e \u003cp\u003eLevel of study 1\u003c/p\u003e \u003cp\u003eConstant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.9184\u003c/p\u003e \u003cp\u003e0.999\u003c/p\u003e \u003cp\u003e0.049\u003c/p\u003e \u003cp\u003e0.130\u003c/p\u003e \u003cp\u003e0.034\u003c/p\u003e \u003cp\u003e0.083\u003c/p\u003e \u003cp\u003e0.662\u003c/p\u003e \u003cp\u003e0.106\u003c/p\u003e \u003cp\u003e0.162\u003c/p\u003e \u003cp\u003e0.052\u003c/p\u003e \u003cp\u003e0.032\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.223\u003c/p\u003e \u003cp\u003e779553469.589\u003c/p\u003e \u003cp\u003e1.351\u003c/p\u003e \u003cp\u003e3.312\u003c/p\u003e \u003cp\u003e0.921\u003c/p\u003e \u003cp\u003e1.400\u003c/p\u003e \u003cp\u003e0.726\u003c/p\u003e \u003cp\u003e2.015\u003c/p\u003e \u003cp\u003e0.430\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.909\u003c/p\u003e \u003cp\u003e0.000\u003c/p\u003e \u003cp\u003e0.915\u003c/p\u003e \u003cp\u003e1.091\u003c/p\u003e \u003cp\u003e0.636\u003c/p\u003e \u003cp\u003e0.931\u003c/p\u003e \u003cp\u003e0.464\u003c/p\u003e \u003cp\u003e0.993\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e1.646\u003c/p\u003e \u003cp\u003e1.996\u003c/p\u003e \u003cp\u003e10.052\u003c/p\u003e \u003cp\u003e1.333\u003c/p\u003e \u003cp\u003e2.106\u003c/p\u003e \u003cp\u003e1.137\u003c/p\u003e \u003cp\u003e4.085\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eThis study found that a lower proportion of participants experienced poor sleep In contrast to a study conducted in Jilin Province, China, found a higher proportion of students with bad sleep (Li et al., 2020). However, a study conducted among Bangladesh students found a lower prevalence of subjective bad sleep quality (Mamun et al., 2020). We attribute the differences to variations in methodology. Our study did not use any tool to assess sleep, whereas the study in China used the Pittsburgh Sleep Quality Index (PSQI), a self-administered questionnaire, to assess sleep for one month. Research has shown that the prevalence of sleep quality varies widely depending on the definition and method used.\u003c/p\u003e \u003cp\u003eThe current review found no association between age and poor sleep quality. However, Schimickler et al. (2019) reported that older age was a risk factor for poor sleep quality among German university students, though the effect size was small. The observed differences may be due to variations in data analysis and sample size, as Schimickler's study used multiple regression analysis and had a much larger sample size of 1,684 compared to the present study. According to research, people's sleep architecture changes with age, resulting in shorter sleep durations, more awakenings, and trouble staying asleep. These changes may cause people to have lower-quality sleep (Ohayon et al., 2004). The results of this research, however, point out that, at least for the group under study, these age-related sleep alterations may not always result in less quality sleep. The results of this study imply that, rather than age per se, age-related sleep problems may be more closely associated with environmental variables, lifestyle choices, and health status (Zavecz et al., 2023). A study conducted with a focus on middle-aged persons discovered that lifestyle factors\u0026mdash;such as physical exercise, stress levels, and social support\u0026mdash;had a greater influence on the quality of sleep than age (Mengelers et al.2023). However, the participants in our study were mostly in the middle age range but lifestyle variables were not collected in the data.\u003c/p\u003e \u003cp\u003eThe current study identified a link between gender and poor sleep quality, with more males being affected compared to females. However, Fatima et al. (2016) reported a higher prevalence of poor sleep quality among females than males in a large Australian population study. In contrast, no statistically significant association between gender and sleep quality was found among students from two tertiary institutions in Northern Malaysia (Lai \u0026amp; Say, 2013) or among Chinese 2 (Chen et al., 2020). These discrepancies across studies may be attributed to variations in sample size, methodology, and geographic location. Additionally, cultural, socio-economic, and academic differences could have influenced these findings (Jeon et al., 2021). This finding adds to the growing body of research that explores gender differences in sleep patterns and their impact on overall health. Numerous studies have historically indicated that women are more prone than men to experience sleep problems, such as insomnia, and poor-quality sleep, which are frequently linked to hormonal changes, stress, and caring for others (Zhang \u0026amp; Wing, 2006), new studies are starting to paint a more complex picture, suggesting that men may also have serious sleep difficulties, particularly in certain populations like college students. Lifestyle variables may be a contributing factor to the increased incidence of poor sleep quality among the male participants in the research. According to Tavernier and Willoughby (2014), men may be more likely to partake in sleep-disturbing activities such as late-night electronic device use, caffeine or alcohol use, and irregular sleep regimens. Furthermore, social pressures and expectations, including stress related to school or work, may result in increased anxiety and stress among males, which can negatively impact sleep.\u003c/p\u003e \u003cp\u003eThe current research found a significant association between suicidal thoughts and poor sleep. This is consistent with a previous study (Pigeon et al., 2012). Furthermore, suicidal thoughts and poor sleep patterns were also found among undergraduate students at a large public university in the southeastern United States (Nadorff et al., 2011). The findings of our study can be explained by the role of serotonin, which affects both sleep regulation and suicide, suggesting a common neurobiological basis (Bertnet \u0026amp; Joiner, 2007). The association between suicidal thoughts and poor sleep quality among university students underscores the complex interplay of mental health and sleep disturbances. Research has demonstrated that sleep problems, such as insomnia, poor sleep quality, and disrupted sleep patterns, are closely linked with an increased risk of suicidal ideation and behaviors. One critical factor is the role of sleep in emotional regulation. Sleep deprivation or poor sleep quality can impair the brain's ability to manage emotions effectively, leading to heightened stress, anxiety, and depression, which are significant risk factors for suicidal thoughts (Walker, 2019). Additionally, sleep disturbances can exacerbate feelings of hopelessness and despair, further contributing to the risk of suicide (Pigeon et al., 2012).\u003c/p\u003e \u003cp\u003eUniversity students are particularly vulnerable to sleep disturbances due to the unique stressors they face, including academic pressures, social challenges, and lifestyle changes. The irregular sleep patterns common among students, such as staying up late and varying sleep schedules, can disrupt the body's circadian rhythm, leading to chronic sleep problems (Hershner \u0026amp; Chervin, 2014). This disruption not only affects cognitive functioning and academic performance but also has profound implications for mental health. The association between sleep and suicide may be primarily influenced by aspects related to mood management. For example, sleep may not be able to offer disturbed people an emotional haven (Bernet \u0026amp; Joiner, 2007). Addressing this relationship requires a holistic approach that includes promoting healthy sleep hygiene, providing mental health support, and creating an environment that fosters emotional well-being among students. Thus, this finding is particularly helpful and offers a key therapeutic focus for upcoming suicide prevention initiatives by considering sleep disruptions as a warning indication (Bernert \u0026amp; Joiner, 2007).\u003c/p\u003e \u003cp\u003eThe current paper revealed no association between the level of study and poor sleep quality. This finding agrees with a study conducted among Chinese medical students (Chen et al., 2020). On the other hand, Li et al. (2020) reported that the level of study was a significant predictor of poor sleep quality among Chinese college students, with students in lower grades having a higher prevalence of poor sleep quality compared to those in higher grades. This could be due to freshmen being more susceptible to the new freedoms of living away from home for the first time and having little experience in dealing with the academic rigor of the curriculum (Liu et al., 2020). Similar results were found among incoming university students in Taiwan (Cheng et al., 2012).\u003c/p\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eLimitations\u003c/h2\u003e \u003cp\u003eThe study is not without drawbacks. The subjective nature of the study design makes it prone to recall bias since the study did not use objective measures of sleep quality, such as polysomnography or actigraphy. Moreover, the study only focused on youths in school, and as such, it cannot be generalized to the entire youth population, such as non-student youth or older adults. Lastly, the study did not account for potential confounding variables such as lifestyle habits (e.g., caffeine or alcohol consumption), academic workload, and environmental factors that could have influenced sleep quality.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study provides valuable information on the prevalence and associated factors of poor sleep quality among university students in Malawi. The findings reveal that a significant proportion of students experience poor sleep, with suicidal thoughts and gender being significant associated factors. While the study did not find significant associations between poor sleep quality and other demographic factors like age, level of study, and year of study, the identified link between mental health concerns and sleep disturbances underscores the importance of addressing mental health-related issues and improving sleep quality among students. These results highlight the need for targeted interventions, such as psychosocial counseling, pharmacological support, sensitizing students on the importance of avoiding being on social media for prolonged hours, and sleep hygiene education, to enhance the well-being of university students.\u003c/p\u003e"},{"header":"Declarations","content":" \u003cp\u003e \u003cstrong\u003eConflict of interest\u003c/strong\u003e \u003cp\u003eNone\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eInformed consent\u003c/strong\u003e \u003cp\u003eNot applicable\u003c/p\u003e \u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eBanda LOL, Banda JT, Munthali GNC, Mbughi C, Kayembe H, Ngulube P, Madi R (2022) Where is the Malawian higher education heading? A call to the former glory and a more visible and internationalized higher education system. 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Palgrave Macmillan. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/978-3-030-13593-5_16\u003c/span\u003e\u003cspan address=\"10.1007/978-3-030-13593-5_16\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"sleep quality, mental health, suicidal thoughts, university students, Malawi","lastPublishedDoi":"10.21203/rs.3.rs-5401765/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5401765/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMental, physical, and social well-being have an impact on sleep quality. University students are vulnerable to sleep problems due to academic pressure coupled with psychosocial problems.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAim\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study aimed to investigate sleep quality and identify its associated factors among university students in Malawi.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethod\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA cross-sectional study was conducted using data collected from 984 students across 13 academic institutions (private and public) in Malawi. A standardized questionnaire was administered via Google Forms, assessing demographic sleep quality and its associated factor variables. Descriptive statistics, Chi-square tests, and logistic regression analyses were used to explore and examine possible associations between poor sleep quality and various demographic factors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study revealed that 28.9% of students experienced poor sleep quality. Gender (p=0.039) and suicidal thoughts (p\u0026lt;0.001) were significantly associated with poor sleep. The results of regression analysis showed that, suicidal thoughts significantly influence bad sleep (p\u0026lt;0.001). However, sleep quality was not significantly influenced by age, year of study, level of study, and gender (p\u0026gt;0.05).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe findings suggest that mental health concerns, particularly suicidal thoughts, are strongly linked to poor sleep quality among university students in Malawi. The results highlight the need for targeted interventions to address sleep-related issues and promote mental well-being among students.\u003c/p\u003e","manuscriptTitle":"Sleep quality and its associated factors among university students in Malawi","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-11-07 16:04:48","doi":"10.21203/rs.3.rs-5401765/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"fa6470cb-b808-466b-bc68-090f94228010","owner":[],"postedDate":"November 7th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-11-07T16:04:48+00:00","versionOfRecord":[],"versionCreatedAt":"2024-11-07 16:04:48","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-5401765","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5401765","identity":"rs-5401765","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}