Pre-COVID-19 Short Sleep Duration and Eveningness Chronotype are Associated with Incident Suicide Ideation During COVID-19 Pandemic in Medical Students: A Retrospective Cohort Study

Pre-COVID-19 Short Sleep Duration and Eveningness Chronotype are Associated with Incident Suicide Ideation During COVID-19 Pandemic in Medical Students: A Retrospective Cohort Study | 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 Pre-COVID-19 Short Sleep Duration and Eveningness Chronotype are Associated with Incident Suicide Ideation During COVID-19 Pandemic in Medical Students: A Retrospective Cohort Study Dandan Zheng, Qingsong Qin, Yingyin Peng, Hao Zhong, Yerui Huang, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3360616/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: Cross-sectional evidence suggests that sleep problems increased the risk of suicide during the 2019 coronavirus disease (COVID-19) pandemic. However, a lack of longitudinal studies examined the relationship between pre-COVID-19 sleep duration, chronotype and incident suicide during the COVID-19 pandemic. Thus, we examined these associations in a longitudinal study of medical students. Methods: From the Shantou College Student Sleep Cohort, a total of 333 first and second grade medical students (age 19.41±0.82 years, female 61.26%), without suicidal ideation (SI) at pre-COVID-19 period, were followed up during the COVID-19 pandemic. Incident SI was defined by their response to the 9 th question from the Beck Depression Inventory. Short sleep duration was defined as less than 7 hours/night. The Morningness-Eveningness Questionnaire was used to evaluate the participants’ chronotype. Logistic regression with adjusted odds ratios (AOR) and 95% confidence intervals (95% CI) was used to examine the association between sleep and SI. Results: The prevalence rate of incident SI during the COVID-19 pandemic was 5.71%. Logistic regressions showed that both short sleep duration (AOR=4.91, 95%CI=1.16-20.74) and eveningness (AOR=3.80, 95%CI=1.08-13.30) in the pre-COVID-19 period, after adjusting for confounders, were associated with increased risk of incident SI during the COVID-19 outbreak. Conclusions: Pre-COVID-19 short sleep duration and eveningness are predictors for incident SI during the COVID-19 pandemic in medical students. Prolonging sleep duration may help to decrease SI during major public health crises in medical students. short sleep duration chronotype suicidal ideation COVID-19 medical students Figures Figure 1 Figure 2 Figure 3 1. Introduction Suicide is one of the leading causes of death worldwide. Based on the data from the World Health Organization, suicide in adolescents and young people (15–29 years) accounts for around 23% of all suicides globally and it is the fourth leading cause of death in this age group. 1 To identify the risk factors for suicide within this vulnerable age group is critical to its prevention and early intervention. Suicidal ideation (SI) is considered to be a strong predictor of suicide attempts and completed suicide. 2 Growing evidence suggests that short sleep duration is a potentially salient risk factor for SI in adolescents and young adults. 3 For example, recent longitudinal studies consistently found that short sleep duration is associated with a 1.5- to 3-fold increased incidence of SI in adolescents and young adults. 4 , 5 Furthermore, chronotype is usually described as morningness, intermediateness, and eveningness, and can be associated with poorer health outcomes. 6 Studies report that the risk of suicidality, including suicidal thoughts and attempts, is higher in the eveningness chronotype than the other chronotypes among adolescents. 7 However, other studies show that the association between suicidal ideation and insomnia or depressive symptoms is stronger than chronotype. 8 , 9 Moreover, a longitudinal 3-year follow-up study in general adolescents showed that a persistent eveningness chronotype is not associated with an increased risk of suicidal ideation. 10 The 2019 coronavirus disease (COVID-19) started in December 2019 and became a global pandemic one month later. COVID-19 continues to cause death and disrupt millions of lives and commerce, and increased sleep and psychological problems, are all known risk factors for suicide. 11 A recent systematic review suggested that rates of suicide during COVID-19 increased compared to the pre-COVID-19 period, and sleep problems were an independent risk factor for suicide during the pandemic. 12 However, most evidence is based on cross-sectional studies, whereas no study has examined the relationship between pre-COVID-19 sleep and suicide risk during the COVID-19 pandemic in longitudinal studies. To fill this gap, we examined the association between pre-COVID-19 sleep and incident SI in a longitudinal cohort study. We hypothesized that habitual pre-COVID-19 short sleep duration and eveningness chronotype are associated with the increased risk of incident SI during the COVID-19 pandemic in medical students. 2. Methods 2.1 Study population The data presented here were collected from the Shantou College Student Sleep Cohort (STCSSC, ChiCTR2100051755). 13 To determine baseline, 489 Shantou University medical students in the first and the second grades volunteered to complete a series of online questionnaires related to sleep and mood, through an online Questionnaire Star program, in early May and late October of 2019, during the pre-COVID-19 pandemic. Medical students usually begin their psychiatry courses and clinical practical rotations in hospitals in their 3rd academic year in China. Because the professional medical knowledge of psychiatry may affect the response to the questionnaires for assessing depressive and anxiety symptoms, in addition to hospital rotations affecting their sleep pattern, we did not include the junior, senior and fifth-year medical students in this study. Among the included 489 freshmen and sophomores at baseline, 381 were followed up (follow-up rate of 78%) during the COVID-19 pandemic in China between February to March of 2020. During this period, all included students were staying at home with extended winter holiday due to the COVID-19 pandemic. After excluding 48 subjects with SI at baseline, a total of 333 subjects were included in this study. This study was approved by the Research Ethics Board of Shantou University Mental Health Center (SUMHC20190510). All participants signed informed consents online and were informed that their personal information would be confidential. Figure 1 depicts the flow of this study. Because no longitudinal study examined the association between baseline eveningness chronotype and SI, the sample size calculation of the present student population was based on the prevalence of SI (range from 7.60–17.26%) among normal adolescents, 4 , 5 and the odds ratio (OR) for SI according to short sleep duration (OR = 3.78). At the power of 0.9, and a significance level of 0.05, the sample size needed was calculated to be between 114 to 204 subjects. In our study, we included 381 subjects, which had enough power to test our hypothesis. The sample size determination was conducted using the PASS 15.0.5 program. 2.2 Measures 2.2.1 Sleep assessment The Chinese version of the Pittsburgh Sleep Quality Index (PSQI) questionnaire was used to assess the subject habitual sleep quality. Higher PSQI scores indicate worse sleep quality. 14 The habitual total sleep time (TST) was extracted from the PSQI based on the question “During the past month, how many hours of actual sleep did you get each night”. Short sleep duration was defined as a habitual total sleep time of less than 7 hours (the median of total sleep time of the overall sample). Besides, bedtime, wake up time, time in bed (TIB), and sleep onset latency (SOL) were also extracted from the PSQI to assess the sleep habit. Sleep efficiency was calculated based on TST/TIB. The Morningness-Eveningness Questionnaire (MEQ) was used to evaluate the participant chronotype at baseline. 15 In this study, an eveningness chronotype was defined as a score between 16 to 41, an intermediate chronotype was defined as an MEQ score between 42 to 58, and a morningness chronotype was defined as an MEQ score between 59 to 86. 15 2.2.2 Depressive symptoms and suicide ideation The Beck Depression Inventory (BDI) was used to assess depressive symptoms at both baseline and follow-up. Higher total scores of BDI indicate more depressive symptoms. 16 SI was evaluated based on the subject’s response to the 9th item of the BDI. If a subject responds “I don’t have any thoughts of killing myself”, he or she would be classified as without SI; while if a subject responds “I have thoughts of killing myself, but I would not carry them out” or “I would like to kill myself” or “I would kill myself if I had the chance”, he or she would be classified as SI. 2.2.3 Anxiety symptoms The Beck Anxiety Inventory (BAI) was used to assess anxiety symptoms at both baseline and follow-up. Higher BAI scores indicate more anxiety symptoms. 17 2.2.4 Other measurements Sociodemographic characteristics, such as age, sex, self-reported height and weight, satisfaction with the financial situation, physical activity, caffeine consumption and medication use were also collected. Body mass index (BMI) was calculated based on weight/height (kg/m 2 ). Financial status was collected from a self-report question, “Are you satisfied with your financial situation?”. Subjects who answered “yes” would be classified as satisfied with their financial situation. Caffeine consumption was defined as drinking coffee, tea, cola and/or caffeinated energy drinks on most days. Medication use was defined as taking any medication during the past three months. 2.3 Statistical analysis Data are presented as mean ± standard deviation (SD) for continuous variables, and percentage for categorical variables. Kolmogorov–Smirnov test was used for normality testing. Bivariate comparisons between groups were performed using an independent t-test or Mann–Whitney U-test for normally and non-normally distributed continuous variables, respectively, or using the χ2 test for categorical variables. To examine the association between pre-COVID-19 pandemic short sleep duration, eveningness chronotype and incident SI during the COVID-19 pandemic in China, logical regression with pre-COVID-19 short sleep duration and eveningness chronotype as predictors and incident SI during the COVID-19 pandemic in China as an outcome were conducted. In the regression models, we adjusted for age, sex, BMI, and variables with intergroup differences. Considering that levels of depressive and anxiety symptoms at follow-up may also affect the risk of incident SI, we also adjusted the changes of the total scores of BAI and BDI (follow-up score minus baseline score) instead of the corresponding baseline scores in sensitivity analysis. All hypothesis tests were 2-sided. Adjusted odds ratios (AOR) and 95% confidence intervals (95% CI) were presented. A p-value < 0.05 was used to determine statistical significance. All statistical analyses were performed using IBM SPSS 26.0. 3. Results A total of 381 subjects were followed up during the COVID-19 pandemic, a follow-up rate of 78%, and the median follow-up duration was 9 months. There were no significant differences in baseline age, sex and BMI between the total subjects and the subjects who were followed up (all P-value ≥ 0.05). Among the 333 subjects who did not have SI pre-COVID-19 pandemic, 19 subjects (5.71%) reported incident SI during the COVID-19 pandemic. Table 1 presents the demographic, sleep, and mood characteristics of the entire sample pre-COVID-19 and stratified by the presence or absence of incident SI during the COVID-19 pandemic. Table 1. Demographic, Sleep and Mood Characteristics of the Included Subjects Variables Overall (n=333) Incident Suicidal Ideation P-value Yes (n=19) No (n=314) Demographic characteristic Age, years 19.41±0.82 19.59±0.82 19.39±0.82 0.379 BMI, kg/m 2 20.27±2.52 21.61±3.08 20.19±2.46 0.031 Sex (Female) 204 (61.26) 11 (57.89) 193 (61.46) 0.756 Grade (Freshman) 262 (78.68) 13 (68.42) 249 (79.30) 0.403 Satisfied with the financial situation 274 (82.28) 14 (73.68) 260 (82.80) 0.483 Physical activity 201 (60.36) 11 (57.89) 190 (60.51) 0.821 Caffeine consumption 175 (52.55) 9 (47.37) 166 (52.87) 0.641 Medication use 84 (25.23) 4 (21.05) 80 (25.48) 0.873 Sleep characteristics PSQI, points 4.43±2.18 5.58±2.85 4.36±2.12 0.099 Short sleep duration 167 (50.15) 16 (84.21) 151 (48.09) 0.002 Bedtime 23:52±0:34 24:07±0:33 23:51±0:34 0.039 Wake up time 07:06±0:23 07:12±0:18 07:06±0:23 0.268 TIB, hours 7.24±0.66 7.07±0.60 7.25±0.66 0.231 SOL>30 min 29 (8.71) 4 (21.05) 25 (7.96) 0.072 Sleep efficiency 0.91±0.08 0.90±0.08 0.91±0.08 0.388 Chronotype 0.043 Morningness 39 (11.71) 2 (10.53) 37 (11.78) Intermediate 263 (78.98) 12 (63.16) 251 (79.94) Eveningness 31 (9.31) 5 (26.32) 26 (8.28) Mood characteristics BAI, points 5.05±5.49 8.32±4.52 4.85±5.49 <0.001 BDI, points 7.61±6.20 12.21±6.29 7.33±6.09 0.001 Abbreviations: BAI, Beck Anxiety Inventory; BDI, Beck Depression Inventory; BMI, body mass index; PSQI, Pittsburgh Sleep Quality Index; SOL, sleep onset latency; TIB, time in bed. P-values in bold indicate P<0.05. As shown in Table 1 , BMI (21.61±3.08 kg/m 2 vs. 20.19±2.46 kg/m 2 , P=0.031), bedtime (24:07±0:33 kg/m 2 vs. 23:51±0:34 kg/m 2 , P=0.039), the percentage of self-reported short sleep duration (84.21% vs. 48.09%, P=0.002), eveningness chronotype (26.32% vs. 8.28%, P=0.043), and the total scores of BAI (8.32±4.52 points vs. 4.85±5.49 points, P<0.001) as well as BDI (12.21±6.29 points vs. 7.33±6.09 points, P=0.001) were significantly higher in the SI group compared to the non-SI group pre-COVID-19. We found that pre-COVID-19 short sleep duration (AOR=4.91, 95% CI=1.16-20.74, P=0.031) was associated with increased risk of incident SI during the COVID-19 pandemic, after adjusting for age, sex, BMI, bedtime, and baseline BAI and BDI total scores ( Model 1 in Table 2 ). In sensitivity analysis, when we used the changes of BAI and BDI from follow-up to baseline, instead of the total scores of baseline BAI and BDI as covariates in Model 2 ( Table 2 ), the results were similar and significant (AOR=6.79, 95% CI=1.41-32.74, P=0.017). Moreover, we have examined the association between the baseline score of PSQI, instead of short sleep duration, and incident SI. PSQI was not associated with an increased risk of incident SI during the COVID-19 pandemic (AOR=1.07, 95% CI=0.84-1.36, P=0.585). As shown in Figure 2 , students who had incident SI during the COVID-19 pandemic had shorter sleep duration compared to those who did not have incident SI (6.35 hours vs. 6.63 hours, P=0.026). Table 2. The association between baseline short sleep duration, eveningness chronotype and incident SI Variable Model 1 Model 2 A OR ( 95%CI ) P-value A OR ( 95%CI ) P-value Total sleep time ≥ 7 hours ref NA ref NA Total sleep time < 7 hours 4.91 (1.16-20.74) 0.031 6.79(1.41-32.74) 0.017 Intermediate chronotype ref NA ref NA Morningness chronotype 3.28 (0.57-18.787) 0.183 1.18 (0.14-9.73) 0.881 Eveningness chronotype 3.80 (1.08-13.30) 0.037 5.59 (1.43-21.79) 0.013 Model 1 was adjusted for baseline age, bedtime, BMI, sex, total scores of BAI and BDI. Model 2 was adjusted for baseline age, bedtime, BMI, changes of BAI and BDI from follow-up to baseline, and sex. P-values in bold indicate P<0.05. Furthermore, we found that the pre-COVID-19 eveningness chronotype (AOR=3.80, 95% CI=1.08-13.30, P=0.037) was associated with an increased risk of incident SI during the COVID-19 pandemic compared to intermediate chronotype, after adjusting for age, sex, BMI, baseline financial status, total scores of baseline BAI and BDI ( Model 1 in Table 2 ). In sensitivity analysis, when we used the changes of BAI and BDI from follow-up to baseline, instead of the total scores of baseline BAI and BDI as covariates in Model 2 ( Table 2 ), the results were similar and significant (AOR=5.59, 95% CI=1.43-21.79, P=0.013). However, the morningness chronotype was not associated with incident SI (AOR=3.28, 95% CI=0.57-18.79, P=0.183). Figure 3 shows the comparison of the proportion of SI among the three chronotypes (5.13% vs. 4.56% vs. 16.13%, P=0.043). Supplementary Table 1 and Supplementary Table 2 provide the sociodemographic, sleep and mood characteristics between students who slept shorter or longer than 7 hours/night and with different chronotypes. 4. Discussion Suicide is the 4 th leading cause of death among the 15-29 years old group. It has been reported that sleep problems were associated with suicide during the COVID-19 pandemic. However, no longitudinal study examined the relationship between pre-COVID-19 sleep and suicide risk during the COVID-19 pandemic. This is the first study to analyze the association between the pre-COVID-19 sleep duration, eveningness chronotype and incident SI during the COVID-19 pandemic in medical students. Our findings indicate that pre-COVID-19 short sleep duration and eveningness chronotype are significantly associated with an increased risk of incident SI during the COVID-19 pandemic in medical students. Psychological problems associated with COVID-19, including incident SI, have drawn much attention from the public, as well as the medical community. 18 Several cross-sectional studies have suggested that incident SI is associated with short sleep duration during the COVID-19 pandemic in adolescents. 19 However, no longitudinal study has examined the association between pre-COVID-19 sleep duration and incident SI during the COVID-19 period. In the current study, our findings show that medical students who slept less than 7 hours per night had a higher risk of incident SI during the COVID-19 pandemic. Based on our data, students with short sleep might be more associated with a lack of sleep opportunity rather than difficulty getting sleep, which is consistent with a previous study that was conducted in China. 20 First, the rate of SOL more than 30 minutes between the students who reported short sleep (8.98%) or not (8.43%) was comparable (P=0.859) in our study. Second, students with short sleep duration had a later bedtime (24:08±0:32 vs. 23:36±0:28, P<0.001), shorter TIB (6.98±0.66vs. 7.49±0.56, P<0.001), and comparable wake-up time (07:07±0:22 vs. 07:05±0:23, P=0.900) compared with the students with normal sleep duration at baseline. All this evidence suggests that prolonging sleep by increasing sleep opportunity (i.e., advance bedtime or delay school time) might be helpful. Moreover, our finding of short sleep duration associated with incident SI is consistent with previous longitudinal studies that were not conducted during the COVID-19 pandemic. 3 Taken together, it appears that self-reported short sleep duration is a predictor for future SI, no matter whether in common situations or under major health events. The mechanisms for short sleep duration with increased risk of SI remain unclear. First, it might be associated with inflammation. Previous findings have suggested that insufficient sleep is associated with inflammation. 21 Inflammation increases the risk of depression, which is one of the strong predictors of SI. 22 Second, it might be associated with decreased serotonergic activity. It has been reported that short sleep is associated with decreased serotonergic activity. Lower concentrations of serotonin (5-HT) have been reported to be associated with suicide. 23 However, we do not have biological data enabling us to examine the underlying mechanisms for the association of short sleep with a higher risk of SI. Future studies should examine the mechanisms linking the association between short sleep and SI. An individual’s preference for the time of sleeping and being awake is called their chronotype. Those with an eveningness chronotype are likely to go to bed at midnight, wake later, and show high efficiency and activity in the afternoon compared to those with the morningness chronotype. In the current study, we found that students with the eveningness chronotype have a higher risk of incident SI even after adjusting for depression. These findings are consistent with some studies that were conducted in patients with depressive disorder. 24 However, our findings are inconsistent with a previous longitudinal study that was conducted in general adolescents. 10 The inconsistent findings might be because that study investigated individuals with a persistent eveningness chronotype, while our study used baseline eveningness chronotype as a predictor of incident SI. It has been reported that both suicidality and eveningness have genetic variations in the ARNTL and CLOCK genes. 25 It appears that suicidality may share the same genetic variations with eveningness. It needs to be noted that the findings of this study were based on self-reported sleep duration. Self-reported sleep duration estimates are about an hour longer than objective measures. 26 Self-reported sleep duration does not only reflect sleep duration per se, but is also associated with other factors, such as age, sex, socioeconomic status, education, race, sleep quality, physical health problems (i.e., pain and obesity) and mental health problems (i.e., depression and emotional stress). 27 In the current study, when we further controlled the potential confounders that may affect self-reported sleep duration, the results remained similar and significant. 5. Clinical Implications Our findings suggest that pre-COVID-19 short sleep duration and the eveningness chronotype were the risk factors for incident SI during the COVID-19 pandemic. Our findings showed that self-reported short sleep duration was caused by the later bedtime rather than insomnia symptoms. Prolonged sleep has been shown to be associated with decreased risk of SI. 28 Specifically, for medical students, increasing the chances of sleeping (i.e., going to bed earlier and more flexible school time) might be helpful to prolong their sleep duration and decrease SI risk. 20 6. Strengths and Limitations Strengths of this study include the prospective design and careful control for multiple potential confounders that may affect the association between sleep duration, chronotype and SI. Several limitations should be acknowledged and taken into account when interpreting our results. First, given that different majors may affect the understanding of symptoms of depression and anxiety, and be affected differently by the COVID-19 pandemic, 29 we only included medical students. Thus, our results cannot be generalized to other populations. The association of sleep duration, chronotype and risk of SI in the general population needs to be examined in future studies. Second, our findings were based on self-report questionnaires, which may lead to recall bias. However, it has been reported that the BDI 30 and Chinese version of the PSQI 31 are valid and reliable questionnaires for the Chinese population. 7. Conclusions Our findings suggest that pre-COVID-19 self-reported short sleep and eveningness chronotype predict an increased risk of incident SI during the COVID-19 pandemic in medical students. Prolonging sleep duration by earlier bedtime or flexible school time may help to decrease SI during major public health crises. Declarations Ethics approval and consent to participate This study was approved by the Research Ethics Board of Shantou University Mental Health Center (SUMHC20190510). All participants signed informed consents online and were informed that their personal information would be confidential. Consent for publication Not applicable. Availability of data and materials The datasets used and/or analyzed in the current study are available from the corresponding author on reasonable request. Competing interests The authors declare that they have no competing interests. Funding This study was supported by Guangdong University Students Innovation and Entrepreneurship Training Program [201910560138; 202010560040; S202310560139], National Natural Science Foundation of China [No.81970087; No.82270105], Grant for Key Disciplinary Project of Clinical Medicine under the Guangdong High-level University Development Program and Department of Educational of Guangdong Province [2017KTSCX065] and 2020 Li Ka Shing Foundation Cross-Disciplinary Research Grant [2020LKSFG05B]. Author contributions QQ and YL contributed substantially to the conception and design of the study. YP, HZ, YH, HW, QT and DZ were involved in the acquisition and analysis of the data. DZ and YL participated in the interpretation of the data. 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Chan JWY, Lam SP, Li SX, et al. Eveningness and Insomnia: Independent Risk Factors of Nonremission in Major Depressive Disorder. Sleep. 2014;37(5):911–7. 10.5665/sleep.3658 . Pawlak J, Dmitrzak-Weglarz M, Maciukiewicz M, et al. Suicidal behavior in the context of disrupted rhythmicity in bipolar disorder—Data from an association study of suicide attempts with clock genes. Psychiatry Res. 2015;226(2–3):517–20. 10.1016/j.psychres.2015.01.010 . Arora T, Broglia E, Pushpakumar D, Lodhi T, Taheri S. An Investigation into the Strength of the Association and Agreement Levels between Subjective and Objective Sleep Duration in Adolescents. Xia Y, ed. PLoS ONE . 2013;8(8):e72406. 10.1371/journal.pone.0072406 . Vgontzas AN, Basta M, Fernandez-Mendoza J. Subjective short sleep duration: what does it mean? Sleep Med Rev. 2014;18(4):291–2. 10.1016/j.smrv.2014.04.002 . Pigeon WR, Pinquart M, Conner K. Meta-Analysis of Sleep Disturbance and Suicidal Thoughts and Behaviors. J Clin Psychiatry. 2012;73(09):e1160–7. 10.4088/JCP.11r07586 . Wang Y, Jing X, Han W, Jing Y, Xu L. Positive and negative affect of university and college students during COVID-19 outbreak: a network-based survey. Int J Public Health. 2020;65(8):1437–43. 10.1007/s00038-020-01483-3 . Shek DT. Reliability and factorial structure of the Chinese version of the Beck Depression Inventory. J Clin Psychol. 1990;46(1):35–43. 10.1002/1097-4679(199001)46:13.0.co;2-w . Zheng B, Li M, Wang KL, Lv J. Analysis of the reliability and validity of the Chinese version of Pittsburgh sleep quality index among medical college students. Beijing Da Xue Xue Bao Yi Xue Ban. 2016;48(3):424–8. Additional Declarations No competing interests reported. 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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-3360616","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":236555603,"identity":"d93bdcc1-b565-4261-bef6-e82e08044d69","order_by":0,"name":"Dandan Zheng","email":"","orcid":"","institution":"Shantou University Medical College","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Dandan","middleName":"","lastName":"Zheng","suffix":""},{"id":236555604,"identity":"7ca3be13-986b-4415-b92f-9fc22613cc52","order_by":1,"name":"Qingsong Qin","email":"","orcid":"","institution":"Shantou University Medical College","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Qingsong","middleName":"","lastName":"Qin","suffix":""},{"id":236555605,"identity":"39d9f1fe-3e72-4333-81d1-2abb41346fd5","order_by":2,"name":"Yingyin Peng","email":"","orcid":"","institution":"Shantou University Medical College","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Yingyin","middleName":"","lastName":"Peng","suffix":""},{"id":236555606,"identity":"2fef9e18-4162-43fb-8da7-4d404fcbdbf6","order_by":3,"name":"Hao Zhong","email":"","orcid":"","institution":"Shantou University Medical College","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Hao","middleName":"","lastName":"Zhong","suffix":""},{"id":236555607,"identity":"84420ea4-6bb3-41e7-842f-7fc0753677c3","order_by":4,"name":"Yerui Huang","email":"","orcid":"","institution":"Shantou University Medical College","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Yerui","middleName":"","lastName":"Huang","suffix":""},{"id":236555608,"identity":"c8bb16f2-a580-448f-b368-3f39ec33c663","order_by":5,"name":"Hongjie Wang","email":"","orcid":"","institution":"Shantou University Medical College","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Hongjie","middleName":"","lastName":"Wang","suffix":""},{"id":236555609,"identity":"da431037-7962-4705-aa58-c4361f541172","order_by":6,"name":"Qiqing Tan","email":"","orcid":"","institution":"Shantou University Medical College","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Qiqing","middleName":"","lastName":"Tan","suffix":""},{"id":236555610,"identity":"b6879d7c-d7fd-484e-926b-5a554d44fff0","order_by":7,"name":"Yun Li","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAyElEQVRIiWNgGAWjYFAC5oYDQFIOwmEjSgsjWIsxRDWxWkBkYgPRWuQbGBsP87bdSZ8/v8eA4UPZYQb+2Q34tRgcYGwAanmWu+EYjwHjjHOHGSTuHCCghQGs5XDuBjYeA2Ygg8FAIoGgw8Ba0uXbgFr+EqOFAeKwwwkMQIcxMxKjBeSXg3POHTbccCyt4GDPuXQeiRsEHcZ8+MObssPy8s2HNz74UWYtxz+DkMPkHzAw8cAcCcQ8eNQiAOMPopSNglEwCkbBiAUA6DtDPZVZQDsAAAAASUVORK5CYII=","orcid":"","institution":"Shantou University Mental Health Center","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Yun","middleName":"","lastName":"Li","suffix":""}],"badges":[],"createdAt":"2023-09-16 07:29:12","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3360616/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3360616/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":44142788,"identity":"53587059-a040-4802-862d-da73a4b41c56","added_by":"auto","created_at":"2023-10-05 15:05:06","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":158058,"visible":true,"origin":"","legend":"\u003cp\u003eThe flowchart of this study\u003c/p\u003e\n\u003cp\u003eAbbreviations: SI, suicidal ideation; STCSSC, Shantou College Student Sleep Cohort\u003c/p\u003e","description":"","filename":"fig1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3360616/v1/453721b71e8a078420972197.jpg"},{"id":44142785,"identity":"b1731177-4e63-4ca8-b549-ad41fa243a4a","added_by":"auto","created_at":"2023-10-05 15:05:06","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":42362,"visible":true,"origin":"","legend":"\u003cp\u003eTotal sleep time of the sample with or without incident SI\u003c/p\u003e\n\u003cp\u003eAbbreviation: SI, suicidal ideation\u003c/p\u003e","description":"","filename":"fig2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3360616/v1/e396d5c943e7a6a230208b58.jpg"},{"id":44142786,"identity":"21ec9606-5753-4491-b7d7-1eab4bedadea","added_by":"auto","created_at":"2023-10-05 15:05:06","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":60707,"visible":true,"origin":"","legend":"\u003cp\u003eProportion of incident SI in different chronotypes\u003c/p\u003e\n\u003cp\u003eAbbreviation: SI, suicidal ideation\u003c/p\u003e","description":"","filename":"fig3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3360616/v1/6ab4682061926717aeca10e1.jpg"},{"id":47117244,"identity":"aa044761-5e31-4b3b-8759-d9888f9e23aa","added_by":"auto","created_at":"2023-11-27 05:22:38","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":492150,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3360616/v1/f94523d1-0780-410b-9dbe-02cf1e8713d3.pdf"},{"id":44142784,"identity":"8dc993c0-b875-43c2-8ff0-01a7574a2bf2","added_by":"auto","created_at":"2023-10-05 15:05:06","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":30482,"visible":true,"origin":"","legend":"","description":"","filename":"Supplement.docx","url":"https://assets-eu.researchsquare.com/files/rs-3360616/v1/174c41d72b2a17114e7fb36c.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Pre-COVID-19 Short Sleep Duration and Eveningness Chronotype are Associated with Incident Suicide Ideation During COVID-19 Pandemic in Medical Students: A Retrospective Cohort Study","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eSuicide is one of the leading causes of death worldwide. Based on the data from the World Health Organization, suicide in adolescents and young people (15\u0026ndash;29 years) accounts for around 23% of all suicides globally and it is the fourth leading cause of death in this age group.\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e To identify the risk factors for suicide within this vulnerable age group is critical to its prevention and early intervention.\u003c/p\u003e \u003cp\u003eSuicidal ideation (SI) is considered to be a strong predictor of suicide attempts and completed suicide.\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e Growing evidence suggests that short sleep duration is a potentially salient risk factor for SI in adolescents and young adults.\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e For example, recent longitudinal studies consistently found that short sleep duration is associated with a 1.5- to 3-fold increased incidence of SI in adolescents and young adults.\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e,\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e Furthermore, chronotype is usually described as morningness, intermediateness, and eveningness, and can be associated with poorer health outcomes.\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e Studies report that the risk of suicidality, including suicidal thoughts and attempts, is higher in the eveningness chronotype than the other chronotypes among adolescents.\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e However, other studies show that the association between suicidal ideation and insomnia or depressive symptoms is stronger than chronotype.\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e,\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e Moreover, a longitudinal 3-year follow-up study in general adolescents showed that a persistent eveningness chronotype is not associated with an increased risk of suicidal ideation.\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eThe 2019 coronavirus disease (COVID-19) started in December 2019 and became a global pandemic one month later. COVID-19 continues to cause death and disrupt millions of lives and commerce, and increased sleep and psychological problems, are all known risk factors for suicide.\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e A recent systematic review suggested that rates of suicide during COVID-19 increased compared to the pre-COVID-19 period, and sleep problems were an independent risk factor for suicide during the pandemic.\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e However, most evidence is based on cross-sectional studies, whereas no study has examined the relationship between pre-COVID-19 sleep and suicide risk during the COVID-19 pandemic in longitudinal studies.\u003c/p\u003e \u003cp\u003eTo fill this gap, we examined the association between pre-COVID-19 sleep and incident SI in a longitudinal cohort study. We hypothesized that habitual pre-COVID-19 short sleep duration and eveningness chronotype are associated with the increased risk of incident SI during the COVID-19 pandemic in medical students.\u003c/p\u003e"},{"header":"2. Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\n \u003ch2\u003e2.1 Study population\u003c/h2\u003e\n \u003cp\u003eThe data presented here were collected from the Shantou College Student Sleep Cohort (STCSSC, ChiCTR2100051755).\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e To determine baseline, 489 Shantou University medical students in the first and the second grades volunteered to complete a series of online questionnaires related to sleep and mood, through an online Questionnaire Star program, in early May and late October of 2019, during the pre-COVID-19 pandemic. Medical students usually begin their psychiatry courses and clinical practical rotations in hospitals in their 3rd academic year in China. Because the professional medical knowledge of psychiatry may affect the response to the questionnaires for assessing depressive and anxiety symptoms, in addition to hospital rotations affecting their sleep pattern, we did not include the junior, senior and fifth-year medical students in this study. Among the included 489 freshmen and sophomores at baseline, 381 were followed up (follow-up rate of 78%) during the COVID-19 pandemic in China between February to March of 2020. During this period, all included students were staying at home with extended winter holiday due to the COVID-19 pandemic. After excluding 48 subjects with SI at baseline, a total of 333 subjects were included in this study. This study was approved by the Research Ethics Board of Shantou University Mental Health Center (SUMHC20190510). All participants signed informed consents online and were informed that their personal information would be confidential. Figure \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e depicts the flow of this study.\u003c/p\u003e\n \u003cp\u003eBecause no longitudinal study examined the association between baseline eveningness chronotype and SI, the sample size calculation of the present student population was based on the prevalence of SI (range from 7.60\u0026ndash;17.26%) among normal adolescents,\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e4\u003c/span\u003e,\u003cspan class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e and the odds ratio (OR) for SI according to short sleep duration (OR\u0026thinsp;=\u0026thinsp;3.78). At the power of 0.9, and a significance level of 0.05, the sample size needed was calculated to be between 114 to 204 subjects. In our study, we included 381 subjects, which had enough power to test our hypothesis. The sample size determination was conducted using the PASS 15.0.5 program.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\n \u003ch2\u003e2.2 Measures\u003c/h2\u003e\n \u003cdiv id=\"Sec5\" class=\"Section3\"\u003e\n \u003ch2\u003e2.2.1 Sleep assessment\u003c/h2\u003e\n \u003cp\u003eThe Chinese version of the Pittsburgh Sleep Quality Index (PSQI) questionnaire was used to assess the subject habitual sleep quality. Higher PSQI scores indicate worse sleep quality.\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e The habitual total sleep time (TST) was extracted from the PSQI based on the question \u0026ldquo;During the past month, how many hours of actual sleep did you get each night\u0026rdquo;. Short sleep duration was defined as a habitual total sleep time of less than 7 hours (the median of total sleep time of the overall sample). Besides, bedtime, wake up time, time in bed (TIB), and sleep onset latency (SOL) were also extracted from the PSQI to assess the sleep habit. Sleep efficiency was calculated based on TST/TIB. The Morningness-Eveningness Questionnaire (MEQ) was used to evaluate the participant chronotype at baseline.\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e In this study, an eveningness chronotype was defined as a score between 16 to 41, an intermediate chronotype was defined as an MEQ score between 42 to 58, and a morningness chronotype was defined as an MEQ score between 59 to 86.\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\n \u003c/div\u003e\n \u003cdiv id=\"Sec6\" class=\"Section3\"\u003e\n \u003ch2\u003e2.2.2 Depressive symptoms and suicide ideation\u003c/h2\u003e\n \u003cp\u003eThe Beck Depression Inventory (BDI) was used to assess depressive symptoms at both baseline and follow-up. Higher total scores of BDI indicate more depressive symptoms.\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e SI was evaluated based on the subject\u0026rsquo;s response to the 9th item of the BDI. If a subject responds \u0026ldquo;I don\u0026rsquo;t have any thoughts of killing myself\u0026rdquo;, he or she would be classified as without SI; while if a subject responds \u0026ldquo;I have thoughts of killing myself, but I would not carry them out\u0026rdquo; or \u0026ldquo;I would like to kill myself\u0026rdquo; or \u0026ldquo;I would kill myself if I had the chance\u0026rdquo;, he or she would be classified as SI.\u003c/p\u003e\n \u003c/div\u003e\n \u003cdiv id=\"Sec7\" class=\"Section3\"\u003e\n \u003ch2\u003e2.2.3 Anxiety symptoms\u003c/h2\u003e\n \u003cp\u003eThe Beck Anxiety Inventory (BAI) was used to assess anxiety symptoms at both baseline and follow-up. Higher BAI scores indicate more anxiety symptoms.\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\n \u003c/div\u003e\n \u003cdiv id=\"Sec8\" class=\"Section3\"\u003e\n \u003ch2\u003e2.2.4 Other measurements\u003c/h2\u003e\n \u003cp\u003eSociodemographic characteristics, such as age, sex, self-reported height and weight, satisfaction with the financial situation, physical activity, caffeine consumption and medication use were also collected. Body mass index (BMI) was calculated based on weight/height (kg/m\u003csup\u003e2\u003c/sup\u003e). Financial status was collected from a self-report question, \u0026ldquo;Are you satisfied with your financial situation?\u0026rdquo;. Subjects who answered \u0026ldquo;yes\u0026rdquo; would be classified as satisfied with their financial situation. Caffeine consumption was defined as drinking coffee, tea, cola and/or caffeinated energy drinks on most days. Medication use was defined as taking any medication during the past three months.\u003c/p\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\n \u003ch2\u003e2.3 Statistical analysis\u003c/h2\u003e\n \u003cp\u003eData are presented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation (SD) for continuous variables, and percentage for categorical variables. Kolmogorov\u0026ndash;Smirnov test was used for normality testing. Bivariate comparisons between groups were performed using an independent t-test or Mann\u0026ndash;Whitney U-test for normally and non-normally distributed continuous variables, respectively, or using the \u0026chi;2 test for categorical variables. To examine the association between pre-COVID-19 pandemic short sleep duration, eveningness chronotype and incident SI during the COVID-19 pandemic in China, logical regression with pre-COVID-19 short sleep duration and eveningness chronotype as predictors and incident SI during the COVID-19 pandemic in China as an outcome were conducted. In the regression models, we adjusted for age, sex, BMI, and variables with intergroup differences. Considering that levels of depressive and anxiety symptoms at follow-up may also affect the risk of incident SI, we also adjusted the changes of the total scores of BAI and BDI (follow-up score minus baseline score) instead of the corresponding baseline scores in sensitivity analysis. All hypothesis tests were 2-sided. Adjusted odds ratios (AOR) and 95% confidence intervals (95% CI) were presented. A p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was used to determine statistical significance. All statistical analyses were performed using IBM SPSS 26.0.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"3. Results","content":"\u003cp\u003eA total of 381 subjects were followed up during the COVID-19 pandemic, a follow-up rate of 78%, and the median follow-up duration was 9 months. There were no significant differences in baseline age, sex and BMI between the total subjects and the subjects who were followed up (all P-value \u0026ge; 0.05). Among the 333 subjects who did not have SI pre-COVID-19 pandemic, 19 subjects (5.71%) reported incident SI during the COVID-19 pandemic. \u003cstrong\u003e\u003cem\u003eTable 1\u003c/em\u003e\u003c/strong\u003e presents the demographic, sleep, and mood characteristics of the entire sample pre-COVID-19 and stratified by the presence or absence of incident SI during the COVID-19 pandemic.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 1. Demographic, Sleep and Mood Characteristics of the Included Subjects\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"558\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.342908438061045%\" rowspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariables\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.28725314183124%\" rowspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eOverall (n=333)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.52064631956912%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eIncident\u0026nbsp;Suicidal Ideation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.8491921005386%\" rowspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eP-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\"\u003e\n \u003cp\u003e\u003cstrong\u003eYes\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;(n=19)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\"\u003e\n \u003cp\u003e\u003cstrong\u003eNo (n=314)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"5\"\u003e\n \u003cp\u003e\u003cstrong\u003eDemographic characteristic\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.342908438061045%\"\u003e\n \u003cp\u003eAge, years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.28725314183124%\" valign=\"top\"\u003e\n \u003cp\u003e19.41\u0026plusmn;0.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.26032315978456%\" valign=\"top\"\u003e\n \u003cp\u003e19.59\u0026plusmn;0.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.26032315978456%\" valign=\"top\"\u003e\n \u003cp\u003e19.39\u0026plusmn;0.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.8491921005386%\"\u003e\n \u003cp\u003e0.379\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.342908438061045%\"\u003e\n \u003cp\u003eBMI, kg/m\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.28725314183124%\" valign=\"top\"\u003e\n \u003cp\u003e20.27\u0026plusmn;2.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.26032315978456%\" valign=\"top\"\u003e\n \u003cp\u003e21.61\u0026plusmn;3.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.26032315978456%\" valign=\"top\"\u003e\n \u003cp\u003e20.19\u0026plusmn;2.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.8491921005386%\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.031\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.342908438061045%\"\u003e\n \u003cp\u003eSex (Female)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.28725314183124%\"\u003e\n \u003cp\u003e204 (61.26)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.26032315978456%\"\u003e\n \u003cp\u003e11 (57.89)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.26032315978456%\"\u003e\n \u003cp\u003e193 (61.46)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.8491921005386%\"\u003e\n \u003cp\u003e0.756\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.342908438061045%\"\u003e\n \u003cp\u003eGrade (Freshman)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.28725314183124%\"\u003e\n \u003cp\u003e262 (78.68)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.26032315978456%\"\u003e\n \u003cp\u003e13 (68.42)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.26032315978456%\"\u003e\n \u003cp\u003e249 (79.30)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.8491921005386%\"\u003e\n \u003cp\u003e0.403\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.342908438061045%\"\u003e\n \u003cp\u003eSatisfied with the financial situation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.28725314183124%\"\u003e\n \u003cp\u003e274 (82.28)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.26032315978456%\"\u003e\n \u003cp\u003e14 (73.68)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.26032315978456%\"\u003e\n \u003cp\u003e260 (82.80)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.8491921005386%\"\u003e\n \u003cp\u003e0.483\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.342908438061045%\"\u003e\n \u003cp\u003ePhysical activity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.28725314183124%\"\u003e\n \u003cp\u003e201 (60.36)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.26032315978456%\"\u003e\n \u003cp\u003e11 (57.89)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.26032315978456%\"\u003e\n \u003cp\u003e190 (60.51)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.8491921005386%\"\u003e\n \u003cp\u003e0.821\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.342908438061045%\"\u003e\n \u003cp\u003eCaffeine consumption\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.28725314183124%\"\u003e\n \u003cp\u003e175 (52.55)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.26032315978456%\"\u003e\n \u003cp\u003e9 (47.37)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.26032315978456%\"\u003e\n \u003cp\u003e166 (52.87)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.8491921005386%\"\u003e\n \u003cp\u003e0.641\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.342908438061045%\"\u003e\n \u003cp\u003eMedication use\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.28725314183124%\"\u003e\n \u003cp\u003e84 (25.23)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.26032315978456%\"\u003e\n \u003cp\u003e4 (21.05)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.26032315978456%\"\u003e\n \u003cp\u003e80 (25.48)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.8491921005386%\"\u003e\n \u003cp\u003e0.873\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"5\"\u003e\n \u003cp\u003e\u003cstrong\u003eSleep characteristics\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.342908438061045%\"\u003e\n \u003cp\u003ePSQI, points\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.28725314183124%\"\u003e\n \u003cp\u003e4.43\u0026plusmn;2.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.26032315978456%\"\u003e\n \u003cp\u003e5.58\u0026plusmn;2.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.26032315978456%\"\u003e\n \u003cp\u003e4.36\u0026plusmn;2.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.8491921005386%\"\u003e\n \u003cp\u003e0.099\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.342908438061045%\"\u003e\n \u003cp\u003eShort sleep duration\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.28725314183124%\"\u003e\n \u003cp\u003e167 (50.15)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.26032315978456%\"\u003e\n \u003cp\u003e16 (84.21)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.26032315978456%\"\u003e\n \u003cp\u003e151 (48.09)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.8491921005386%\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.002\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.342908438061045%\" valign=\"top\"\u003e\n \u003cp\u003eBedtime\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.28725314183124%\" valign=\"top\"\u003e\n \u003cp\u003e23:52\u0026plusmn;0:34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.26032315978456%\" valign=\"top\"\u003e\n \u003cp\u003e24:07\u0026plusmn;0:33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.26032315978456%\" valign=\"top\"\u003e\n \u003cp\u003e23:51\u0026plusmn;0:34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.8491921005386%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.039\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.342908438061045%\" valign=\"top\"\u003e\n \u003cp\u003eWake up time\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.28725314183124%\" valign=\"top\"\u003e\n \u003cp\u003e07:06\u0026plusmn;0:23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.26032315978456%\" valign=\"top\"\u003e\n \u003cp\u003e07:12\u0026plusmn;0:18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.26032315978456%\" valign=\"top\"\u003e\n \u003cp\u003e07:06\u0026plusmn;0:23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.8491921005386%\" valign=\"top\"\u003e\n \u003cp\u003e0.268\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.342908438061045%\" valign=\"top\"\u003e\n \u003cp\u003eTIB, hours\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.28725314183124%\" valign=\"top\"\u003e\n \u003cp\u003e7.24\u0026plusmn;0.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.26032315978456%\" valign=\"top\"\u003e\n \u003cp\u003e7.07\u0026plusmn;0.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.26032315978456%\" valign=\"top\"\u003e\n \u003cp\u003e7.25\u0026plusmn;0.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.8491921005386%\" valign=\"top\"\u003e\n \u003cp\u003e0.231\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.342908438061045%\" valign=\"top\"\u003e\n \u003cp\u003eSOL\u0026gt;30 min\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.28725314183124%\" valign=\"top\"\u003e\n \u003cp\u003e29 (8.71)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.26032315978456%\" valign=\"top\"\u003e\n \u003cp\u003e4 (21.05)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.26032315978456%\" valign=\"top\"\u003e\n \u003cp\u003e25 (7.96)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.8491921005386%\" valign=\"top\"\u003e\n \u003cp\u003e0.072\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.342908438061045%\" valign=\"top\"\u003e\n \u003cp\u003eSleep efficiency\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.28725314183124%\" valign=\"top\"\u003e\n \u003cp\u003e0.91\u0026plusmn;0.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.26032315978456%\" valign=\"top\"\u003e\n \u003cp\u003e0.90\u0026plusmn;0.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.26032315978456%\" valign=\"top\"\u003e\n \u003cp\u003e0.91\u0026plusmn;0.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.8491921005386%\" valign=\"top\"\u003e\n \u003cp\u003e0.388\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"88.1508078994614%\" colspan=\"4\"\u003e\n \u003cp\u003eChronotype\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.8491921005386%\" rowspan=\"4\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.043\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"42.36252545824847%\"\u003e\n \u003cp\u003eMorningness\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.014256619144604%\"\u003e\n \u003cp\u003e39 (11.71)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.311608961303463%\"\u003e\n \u003cp\u003e2 (10.53)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.311608961303463%\"\u003e\n \u003cp\u003e37 (11.78)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"42.36252545824847%\"\u003e\n \u003cp\u003eIntermediate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.014256619144604%\"\u003e\n \u003cp\u003e263 (78.98)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.311608961303463%\"\u003e\n \u003cp\u003e12 (63.16)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.311608961303463%\"\u003e\n \u003cp\u003e251 (79.94)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"42.36252545824847%\"\u003e\n \u003cp\u003eEveningness\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.014256619144604%\"\u003e\n \u003cp\u003e31 (9.31)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.311608961303463%\"\u003e\n \u003cp\u003e5 (26.32)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.311608961303463%\"\u003e\n \u003cp\u003e26 (8.28)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"5\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eMood characteristics\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.342908438061045%\"\u003e\n \u003cp\u003eBAI,\u0026nbsp;points\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.28725314183124%\" valign=\"top\"\u003e\n \u003cp\u003e5.05\u0026plusmn;5.49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.26032315978456%\" valign=\"top\"\u003e\n \u003cp\u003e8.32\u0026plusmn;4.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.26032315978456%\" valign=\"top\"\u003e\n \u003cp\u003e4.85\u0026plusmn;5.49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.8491921005386%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.342908438061045%\"\u003e\n \u003cp\u003eBDI,\u0026nbsp;points\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.28725314183124%\" valign=\"top\"\u003e\n \u003cp\u003e7.61\u0026plusmn;6.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.26032315978456%\" valign=\"top\"\u003e\n \u003cp\u003e12.21\u0026plusmn;6.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.26032315978456%\" valign=\"top\"\u003e\n \u003cp\u003e7.33\u0026plusmn;6.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.8491921005386%\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eAbbreviations:\u0026nbsp;BAI, Beck Anxiety Inventory; BDI, Beck Depression Inventory; BMI, body mass index; PSQI, Pittsburgh Sleep Quality Index; SOL, sleep onset latency; TIB, time in bed.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eP-values in bold indicate P\u0026lt;0.05.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAs shown in \u003cstrong\u003e\u003cem\u003eTable 1\u003c/em\u003e\u003c/strong\u003e, BMI (21.61\u0026plusmn;3.08 kg/m\u003csup\u003e2\u003c/sup\u003e vs. 20.19\u0026plusmn;2.46 kg/m\u003csup\u003e2\u003c/sup\u003e, P=0.031), bedtime (24:07\u0026plusmn;0:33 kg/m\u003csup\u003e2\u003c/sup\u003e vs. 23:51\u0026plusmn;0:34 kg/m\u003csup\u003e2\u003c/sup\u003e, P=0.039), the percentage of self-reported short sleep duration (84.21% vs. 48.09%, P=0.002), eveningness chronotype (26.32% vs. 8.28%, P=0.043), and the total scores of BAI (8.32\u0026plusmn;4.52 points vs. 4.85\u0026plusmn;5.49 points, P\u0026lt;0.001) as well as BDI (12.21\u0026plusmn;6.29 points vs. 7.33\u0026plusmn;6.09 points, P=0.001) were significantly higher in the SI group compared to the non-SI group pre-COVID-19.\u003c/p\u003e\n\u003cp\u003eWe found that pre-COVID-19 short sleep duration (AOR=4.91, 95% CI=1.16-20.74, P=0.031) was associated with increased risk of incident SI during the COVID-19 pandemic, after adjusting for age, sex, BMI, bedtime, and baseline BAI and BDI total scores (\u003cem\u003eModel 1\u0026nbsp;\u003c/em\u003ein \u003cstrong\u003e\u003cem\u003eTable 2\u003c/em\u003e\u003c/strong\u003e). In sensitivity analysis, when we used the changes of BAI and BDI from follow-up to baseline, instead of the total scores of baseline BAI and BDI as covariates in \u003cem\u003eModel 2\u003c/em\u003e (\u003cstrong\u003e\u003cem\u003eTable 2\u003c/em\u003e\u003c/strong\u003e), the results were similar and significant (AOR=6.79, 95% CI=1.41-32.74, P=0.017). Moreover, we have examined the association between the baseline score of PSQI,\u0026nbsp;instead of short sleep duration, and incident SI.\u0026nbsp;PSQI was not associated with an increased risk of incident SI during the COVID-19 pandemic (AOR=1.07,\u0026nbsp;95% CI=0.84-1.36, P=0.585). As shown in \u003cstrong\u003e\u003cem\u003eFigure 2\u003c/em\u003e\u003c/strong\u003e, students who had incident SI during the COVID-19 pandemic had shorter sleep duration compared to those who did not have incident SI (6.35 hours vs. 6.63 hours, P=0.026).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 2. The association between baseline short sleep duration, eveningness chronotype and incident SI\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"567\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.333333333333336%\" rowspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariable\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"34.92063492063492%\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eModel 1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"31.746031746031747%\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eModel 2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.0132625994695%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eA\u003c/strong\u003e\u003cstrong\u003eOR (\u003cem\u003e95%CI\u003c/em\u003e)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.50663129973475%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eP-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.97347480106101%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eA\u003c/strong\u003e\u003cstrong\u003eOR (\u003cem\u003e95%CI\u003c/em\u003e)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.50663129973475%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eP-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.3922261484099%\" valign=\"top\"\u003e\n \u003cp\u003eTotal sleep time \u0026ge; 7 hours\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.32155477031802%\" valign=\"top\"\u003e\n \u003cp\u003eref\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.66077738515901%\" valign=\"top\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.964664310954063%\" valign=\"top\"\u003e\n \u003cp\u003eref\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.66077738515901%\" valign=\"top\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.3922261484099%\" valign=\"top\"\u003e\n \u003cp\u003eTotal sleep time \u0026lt; 7 hours\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.32155477031802%\"\u003e\n \u003cp\u003e4.91 (1.16-20.74)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.66077738515901%\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.031\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.964664310954063%\"\u003e\n \u003cp\u003e6.79(1.41-32.74)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.66077738515901%\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.017\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.3922261484099%\" valign=\"top\"\u003e\n \u003cp\u003eIntermediate chronotype\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.32155477031802%\"\u003e\n \u003cp\u003eref\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.66077738515901%\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.964664310954063%\"\u003e\n \u003cp\u003eref\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.66077738515901%\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.3922261484099%\" valign=\"top\"\u003e\n \u003cp\u003eMorningness chronotype\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.32155477031802%\"\u003e\n \u003cp\u003e3.28 (0.57-18.787)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.66077738515901%\"\u003e\n \u003cp\u003e0.183\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.964664310954063%\"\u003e\n \u003cp\u003e1.18 (0.14-9.73)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.66077738515901%\"\u003e\n \u003cp\u003e0.881\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.3922261484099%\" valign=\"top\"\u003e\n \u003cp\u003eEveningness chronotype\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.32155477031802%\"\u003e\n \u003cp\u003e3.80 (1.08-13.30)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.66077738515901%\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.037\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.964664310954063%\"\u003e\n \u003cp\u003e5.59 (1.43-21.79)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.66077738515901%\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.013\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eModel 1 was adjusted for baseline age, bedtime, BMI, sex, total scores of BAI and BDI. Model 2 was adjusted for baseline age, bedtime, BMI, changes of BAI and BDI from follow-up to baseline, and sex. P-values in bold indicate P\u0026lt;0.05.\u003c/p\u003e\n\u003cp\u003eFurthermore, we found that the pre-COVID-19 eveningness chronotype (AOR=3.80, 95% CI=1.08-13.30, P=0.037) was associated with an increased risk of incident SI during the COVID-19 pandemic compared to intermediate chronotype, after adjusting for age, sex, BMI, baseline financial status, total scores of baseline BAI and BDI (\u003cem\u003eModel 1\u003c/em\u003e in \u003cstrong\u003e\u003cem\u003eTable 2\u003c/em\u003e\u003c/strong\u003e). In sensitivity analysis, when we used the changes of BAI and BDI from follow-up to baseline, instead of the total scores of baseline BAI and BDI as covariates in \u003cem\u003eModel 2\u003c/em\u003e (\u003cstrong\u003e\u003cem\u003eTable 2\u003c/em\u003e\u003c/strong\u003e), the results were similar and significant (AOR=5.59, 95% CI=1.43-21.79, P=0.013). However, the morningness chronotype was not associated with incident SI (AOR=3.28, 95% CI=0.57-18.79, P=0.183). \u003cstrong\u003e\u003cem\u003eFigure 3\u003c/em\u003e\u003c/strong\u003e shows the comparison of the proportion of SI among the three chronotypes (5.13% vs. 4.56% vs. 16.13%, P=0.043).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eSupplementary Table 1\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;and \u003cem\u003eSupplementary\u003c/em\u003e \u003cem\u003eTable 2\u0026nbsp;\u003c/em\u003e\u003c/strong\u003eprovide the sociodemographic, sleep and mood characteristics between students who slept shorter or longer than 7 hours/night and with different chronotypes.\u0026nbsp;\u003c/p\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eSuicide is the 4\u003csup\u003eth\u003c/sup\u003e leading cause of death among the 15-29 years old group. It has been reported that sleep problems were associated with suicide during the COVID-19 pandemic. However, no longitudinal study examined the relationship between pre-COVID-19 sleep and suicide risk during the COVID-19 pandemic. This is the first study to analyze the association between the pre-COVID-19 sleep duration, eveningness chronotype and incident SI during the COVID-19 pandemic in medical students. Our findings indicate that pre-COVID-19 short sleep duration and eveningness chronotype are significantly associated with an increased risk of incident SI during the COVID-19 pandemic in medical students.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003ePsychological problems associated with COVID-19, including incident SI, have drawn much attention from the public, as well as the medical community.\u003csup\u003e18\u003c/sup\u003e Several cross-sectional studies have suggested that incident SI is associated with short sleep duration during the COVID-19 pandemic in adolescents.\u003csup\u003e19\u003c/sup\u003e However, no longitudinal study has examined the association between pre-COVID-19 sleep duration and incident SI during the COVID-19 period. In the current study, our findings show that medical students who slept less than 7 hours per night had a higher risk of incident SI during the COVID-19 pandemic. Based on our data, students with short sleep might be more associated with a lack of sleep opportunity rather than difficulty getting sleep, which is consistent with a previous study that was conducted in China.\u003csup\u003e20\u003c/sup\u003e First, the rate of SOL more than 30 minutes between the students who reported short sleep (8.98%) or not (8.43%) was comparable (P=0.859) in our study. Second,\u0026nbsp;students with short sleep duration had a later bedtime (24:08±0:32\u0026nbsp;vs.\u0026nbsp;23:36±0:28, P\u0026lt;0.001), shorter TIB (6.98±0.66vs.\u0026nbsp;7.49±0.56, P\u0026lt;0.001), and comparable wake-up time (07:07±0:22\u0026nbsp;vs.\u0026nbsp;07:05±0:23, P=0.900) compared with the students with normal sleep duration\u0026nbsp;at baseline. All this evidence suggests that prolonging sleep by increasing sleep opportunity (i.e., advance bedtime or delay school time) might be helpful. Moreover, our finding of short sleep duration associated with incident SI is consistent with previous longitudinal studies that were not conducted during the COVID-19 pandemic.\u003csup\u003e3\u003c/sup\u003e Taken together, it appears that self-reported short sleep duration is a predictor for future SI, no matter whether in common situations or under major health events.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe mechanisms for short sleep duration with increased risk of SI remain unclear. First, it might be associated with inflammation. Previous findings have suggested that insufficient sleep is associated with inflammation.\u003csup\u003e21\u003c/sup\u003e Inflammation increases the risk of depression, which is one of the strong predictors of SI.\u003csup\u003e22\u003c/sup\u003e Second, it might be associated with decreased serotonergic activity. It has been reported that short sleep is associated with decreased serotonergic activity. Lower concentrations of serotonin (5-HT) have been reported to be associated with suicide.\u003csup\u003e23\u003c/sup\u003e However, we do not have biological data enabling us to examine the underlying mechanisms for the association of short sleep with a higher risk of SI. Future studies should examine the mechanisms linking the association between short sleep and SI.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAn individual’s preference for the time of sleeping and being awake is called their chronotype. Those with an eveningness chronotype are likely to go to bed at midnight, wake later, and show high\u0026nbsp;efficiency\u0026nbsp;and activity in the afternoon compared to those with the morningness chronotype.\u0026nbsp;In the current study, we found that students with the eveningness chronotype have a higher risk of incident SI even after adjusting for depression. These findings are consistent with some studies that were conducted in patients with depressive disorder.\u003csup\u003e24\u003c/sup\u003e However, our findings are inconsistent with a previous longitudinal study that was conducted in general adolescents.\u003csup\u003e10\u003c/sup\u003e The inconsistent findings might be because that study investigated individuals with a persistent eveningness chronotype, while our study used baseline eveningness chronotype as a predictor of incident SI. It has been reported that both suicidality and eveningness have genetic variations in the ARNTL and CLOCK genes.\u003csup\u003e25\u003c/sup\u003e It appears that suicidality may share the same genetic variations with eveningness.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIt needs to be noted that the findings of this\u0026nbsp;study\u0026nbsp;were based on self-reported sleep duration. Self-reported sleep duration estimates are about an hour longer than objective measures.\u003csup\u003e26\u003c/sup\u003e Self-reported sleep duration does not only reflect sleep duration per se, but is also associated with other factors, such as\u0026nbsp;age,\u0026nbsp;sex,\u0026nbsp;socioeconomic status, education, race, sleep quality, physical health problems (i.e., pain and obesity) and mental health\u0026nbsp;problems (i.e., depression and emotional stress).\u003csup\u003e27\u003c/sup\u003e In the current study, when we further controlled the potential confounders that may affect self-reported sleep duration, the results remained similar and significant.\u0026nbsp;\u003c/p\u003e\n\n\n\n"},{"header":"5. Clinical Implications ","content":"\u003cp\u003eOur findings suggest that pre-COVID-19 short sleep duration and the eveningness chronotype were the risk factors for incident SI during the COVID-19 pandemic. Our findings showed that self-reported short sleep duration was caused by the later bedtime rather than insomnia symptoms. Prolonged sleep has been shown to be associated with decreased risk of SI.\u003csup\u003e28\u003c/sup\u003e Specifically, for medical students, increasing the chances of sleeping (i.e., going to bed earlier and more flexible\u0026nbsp;school time)\u0026nbsp;might be helpful to prolong their sleep duration and decrease SI risk.\u003csup\u003e20\u003c/sup\u003e\u0026nbsp;\u003c/p\u003e"},{"header":"6. Strengths and Limitations","content":"\u003cp\u003eStrengths of this study include the prospective design and careful control for multiple potential confounders that may affect the association between sleep duration, chronotype and SI. Several limitations should be acknowledged and taken into account when interpreting our results. First, given that different majors may affect the understanding of symptoms of depression and anxiety, and be affected differently by the COVID-19 pandemic,\u003csup\u003e29\u003c/sup\u003e we only included medical students. Thus, our results cannot be generalized to other populations. The association of sleep duration, chronotype and risk of SI in the general population needs to be examined in future studies. Second, our findings were based on self-report questionnaires, which may lead to recall bias.\u0026nbsp;However, it has been reported that the BDI\u003csup\u003e30\u003c/sup\u003e and Chinese version of the PSQI\u003csup\u003e31\u003c/sup\u003e are valid and reliable questionnaires for the Chinese population.\u003c/p\u003e"},{"header":"7. Conclusions","content":"\u003cp\u003eOur findings suggest that pre-COVID-19 self-reported short sleep and eveningness chronotype predict an increased risk of incident SI during the COVID-19 pandemic in medical students. Prolonging sleep duration by earlier bedtime or flexible school time may help to decrease SI during major public health crises.\u0026nbsp;\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eEthics approval and consent to participate\u003c/p\u003e\n\u003cp\u003eThis study was approved by the Research Ethics Board of Shantou University Mental Health Center (SUMHC20190510). All participants signed informed consents online and were informed that their personal information would be confidential.\u003c/p\u003e\n\u003cp\u003eConsent for publication\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003eAvailability of data and materials\u003c/p\u003e\n\u003cp\u003eThe datasets used and/or analyzed in the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003eCompeting interests\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003eFunding\u003c/p\u003e\n\u003cp\u003eThis study was supported by Guangdong University Students Innovation and Entrepreneurship Training Program [201910560138; 202010560040; S202310560139], National Natural Science Foundation of China [No.81970087; No.82270105], Grant for Key Disciplinary Project of Clinical Medicine under the Guangdong High-level University Development Program and Department of Educational of Guangdong Province [2017KTSCX065] and 2020 Li Ka Shing Foundation Cross-Disciplinary Research Grant [2020LKSFG05B].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAuthor contributions\u003c/p\u003e\n\u003cp\u003eQQ and YL contributed substantially to the conception and design of the study. YP, HZ, YH, HW, QT and DZ were involved in the acquisition and analysis of the data. DZ and YL participated in the interpretation of the data. DZ and YL drafted the paper. All authors critically revised the manuscript and gave final approval for the submission.\u003c/p\u003e\n\u003cp\u003eAcknowledgments\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe authors thank Prof. Stanley Lin, a native English-speaking scientist who proof-read this manuscript before submission. \u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003e\u003cspan\u003e\u003cem\u003eSuicide Worldwide in 2019: Global Health Estimates.\u003c/em\u003e; 2021. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.who.int/publications/i/item/9789240026643\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eCluver L, Orkin M, Boyes ME, Sherr L, Child, Attempts AS. 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Beijing Da Xue Xue Bao Yi Xue Ban. 2016;48(3):424\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"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":"short sleep duration, chronotype, suicidal ideation, COVID-19, medical students","lastPublishedDoi":"10.21203/rs.3.rs-3360616/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3360616/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground:\u003c/strong\u003e Cross-sectional evidence suggests that sleep problems increased the risk of suicide during the 2019 coronavirus disease (COVID-19) pandemic. However, a lack of longitudinal studies examined the relationship between pre-COVID-19 sleep duration, chronotype and incident suicide during the COVID-19 pandemic. Thus, we examined these associations in a longitudinal study of medical students.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods: \u003c/strong\u003eFrom the Shantou College Student Sleep Cohort, a total of 333 first and second grade medical students (age 19.41±0.82 years, female 61.26%), without suicidal ideation (SI) at pre-COVID-19 period, were followed up during the COVID-19 pandemic. Incident SI was defined by their response to the 9\u003csup\u003eth\u003c/sup\u003e question from the Beck Depression Inventory. Short sleep duration was defined as less than 7 hours/night. The Morningness-Eveningness Questionnaire was used to evaluate the participants’ chronotype. Logistic regression with adjusted odds ratios (AOR) and 95% confidence intervals (95% CI) was used to examine the association between sleep and SI.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e The prevalence rate of incident SI during the COVID-19 pandemic was 5.71%. Logistic regressions showed that both short sleep duration (AOR=4.91, 95%CI=1.16-20.74) and eveningness (AOR=3.80, 95%CI=1.08-13.30) in the pre-COVID-19 period, after adjusting for confounders, were associated with increased risk of incident SI during the COVID-19 outbreak.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions:\u003c/strong\u003e Pre-COVID-19 short sleep duration and eveningness are predictors for incident SI during the COVID-19 pandemic in medical students. Prolonging sleep duration may help to decrease SI during major public health crises in medical students.\u003c/p\u003e","manuscriptTitle":"Pre-COVID-19 Short Sleep Duration and Eveningness Chronotype are Associated with Incident Suicide Ideation During COVID-19 Pandemic in Medical Students: A Retrospective Cohort Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2023-10-05 15:05:01","doi":"10.21203/rs.3.rs-3360616/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":"78f817b2-8c4c-40d7-949a-4c5192ed80f1","owner":[],"postedDate":"October 5th, 2023","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2023-11-27T05:14:31+00:00","versionOfRecord":[],"versionCreatedAt":"2023-10-05 15:05:01","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-3360616","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3360616","identity":"rs-3360616","version":["v1"]},"buildId":"cBFmMYwuxLRRLfASyISRj","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}