The Impact of Sleep Timing, Sleep Duration, and Sleep Quality on Depressive Symptoms and Suicidal Ideation amongst Japanese Freshmen: The EQUSITE Study

Abstract

Aim. The aim of this study was to identify the impact of bedtime, wake time, sleep duration, sleep-onset latency, and sleep quality on depressive symptoms and suicidal ideation amongst Japanese freshmen. Methods. This cross-sectional data was derived from the baseline survey of the Enhancement of Q-University Students Intelligence (EQUSITE) study conducted from May to June, 2010. A total of 2,631 participants were recruited and completed the following self-reported questionnaires: the Pittsburgh Sleep Quality Index (PSQI), the Center for Epidemiologic Studies Depression Scale (CES-D), and the original Health Support Questionnaires developed by the EQUSITE study research team. Results. Of 1,992 participants eligible for analysis, 25.5% (n = 507) reported depressive symptoms (CES-D total score ≥ 16), and 5.8% (n = 115) reported suicidal ideation. The present study showed that late bedtime (later than 01:30), sleep-onset latency (≥30 minutes), and poor sleep quality showed a marginally significant association with depressive symptoms. Poor sleep quality was seen to predict suicidal ideation even after adjusting for depressive symptoms. Conclusion. The current study has important implications for the role of bedtime in the prevention of depressive symptoms. Improving sleep quality may prevent the development of depressive symptoms and reduce the likelihood of suicidal ideation.

Sleep quality and body mass index: a co‐twin study

“…Distinct sleep dimensions, other than duration, may more precisely capture influences that drive the association between sleep and obesity (Jarrin et al, 2013). Moreover, sleep quality has shown stronger associations with variables such as depression symptoms (Supartini et al, 2016), which appears to account, at least in part, for the relationship between weight and sleep quality (Sawyer et al, 2015).…”

“…Sleep quality has been frequently used as a single indicator encompassing a collection of sleep measures, such as: total sleep time, sleep-onset latency, degree of fragmentation, total wake time, sleep efficiency, and sometimes sleep-disruptive events such as spontaneous arousals or apnea (Krystal and Edinger, 2008). Self-reported sleep quality is affected by gender and age; women and older people are more likely to report lower sleep quality and a higher number of sleep problems (Madrid-Valero et al, 2017; ª 2017 European Sleep Research Society Ohayon et al, 2004;Uhlig et al, 2014;Zhang and Wing, 2006), and it seems to be more closely associated to psychological distress than duration alone (Supartini et al, 2016). Sleep quality also appears to be related to BMI through an inverse relationship (Hung et al, 2013;Kim, 2015), although the opposite has also been reported (Gildner et al, 2014).…”

Impact of sleep problems on daytime function in school life: a cross-sectional study involving Japanese university students

“…Moreover, early awakening to adapt to their social schedule (e.g., for attending classes early in the morning) consequently brings about insufficient sleep especially in evening-type students. Numerous studies have reported that either insufficient sleep or later chronotype is associated with deterioration of physical health, mental health [3][4][5] and health-related quality of life [6,7] as well as worse academic performance [8][9][10][11][12] in the young population.…”

“…It has been reported that as high as 33-59% of university students have poor sleep quality, which is associated with their worsened health status and academic performance [5,[13][14][15][16][17][18][19]. In these previous studies, sleep quality was defined as "poor" or "good" using the Pittsburg Sleep Quality Index (PSQI), a widely used scale evaluating the following seven components: subjective sleep quality, sleep latency, sleep duration, habitual sleep efficiency, sleep disturbances, use of sleep medication, and daytime dysfunction [20].…”

Prevalence of sleep disturbances in Chinese university students: a comprehensive meta‐analysis

“…Previous studies found variable rates of sleep disturbances in this population. The prevalence of sleep disturbances ranges from 3.0 to 74.2% worldwide, for instance, 3.0% in Thailand (Mohammadbeigi et al ., ), 9.8% in Lebanon (Younes et al ., ), 22.5% in the USA (Gress et al ., ), 33.3% in Japan (Supartini et al ., ), 74.2% in Saudi Arabia (Siddiqui et al ., ), 51.8% in Chile (Velez et al ., ), and 61.7% in Iran (Mohammadbeigi et al ., ). Apart from different sampling methods and geographic locations, the use of different instruments, such as the PSQI (Mohammadbeigi et al ., ), the Insomnia Severity Index (ISI; Gress et al ., ) and non‐quantitative measures (Peltzer and Pengpid, ) could account for such variation in prevalence.…”