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      Irregular sleep/wake patterns are associated with poorer academic performance and delayed circadian and sleep/wake timing

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          Abstract

          The association of irregular sleep schedules with circadian timing and academic performance has not been systematically examined. We studied 61 undergraduates for 30 days using sleep diaries, and quantified sleep regularity using a novel metric, the sleep regularity index (SRI). In the most and least regular quintiles, circadian phase and light exposure were assessed using salivary dim-light melatonin onset (DLMO) and wrist-worn photometry, respectively. DLMO occurred later (00:08 ± 1:54 vs. 21:32 ± 1:48; p < 0.003); the daily sleep propensity rhythm peaked later (06:33 ± 0:19 vs. 04:45 ± 0:11; p < 0.005); and light rhythms had lower amplitude (102 ± 19 lux vs. 179 ± 29 lux; p < 0.005) in Irregular compared to Regular sleepers. A mathematical model of the circadian pacemaker and its response to light was used to demonstrate that Irregular vs. Regular group differences in circadian timing were likely primarily due to their different patterns of light exposure. A positive correlation (r = 0.37; p < 0.004) between academic performance and SRI was observed. These findings show that irregular sleep and light exposure patterns in college students are associated with delayed circadian rhythms and lower academic performance. Moreover, the modeling results reveal that light-based interventions may be therapeutically effective in improving sleep regularity in this population.

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          The Pittsburgh sleep quality index: A new instrument for psychiatric practice and research

          Despite the prevalence of sleep complaints among psychiatric patients, few questionnaires have been specifically designed to measure sleep quality in clinical populations. The Pittsburgh Sleep Quality Index (PSQI) is a self-rated questionnaire which assesses sleep quality and disturbances over a 1-month time interval. Nineteen individual items generate seven "component" scores: subjective sleep quality, sleep latency, sleep duration, habitual sleep efficiency, sleep disturbances, use of sleeping medication, and daytime dysfunction. The sum of scores for these seven components yields one global score. Clinical and clinimetric properties of the PSQI were assessed over an 18-month period with "good" sleepers (healthy subjects, n = 52) and "poor" sleepers (depressed patients, n = 54; sleep-disorder patients, n = 62). Acceptable measures of internal homogeneity, consistency (test-retest reliability), and validity were obtained. A global PSQI score greater than 5 yielded a diagnostic sensitivity of 89.6% and specificity of 86.5% (kappa = 0.75, p less than 0.001) in distinguishing good and poor sleepers. The clinimetric and clinical properties of the PSQI suggest its utility both in psychiatric clinical practice and research activities.
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            Sleep duration predicts cardiovascular outcomes: a systematic review and meta-analysis of prospective studies.

            Aims To assess the relationship between duration of sleep and morbidity and mortality from coronary heart disease (CHD), stroke, and total cardiovascular disease (CVD). Methods and results We performed a systematic search of publications using MEDLINE (1966-2009), EMBASE (from 1980), the Cochrane Library, and manual searches without language restrictions. Studies were included if they were prospective, follow-up >3 years, had duration of sleep at baseline, and incident cases of CHD, stroke, or CVD. Relative risks (RR) and 95% confidence interval (CI) were pooled using a random-effect model. Overall, 15 studies (24 cohort samples) included 474 684 male and female participants (follow-up 6.9-25 years), and 16 067 events (4169 for CHD, 3478 for stroke, and 8420 for total CVD). Sleep duration was assessed by questionnaire and incident cases through certification and event registers. Short duration of sleep was associated with a greater risk of developing or dying of CHD (RR 1.48, 95% CI 1.22-1.80, P < 0.0001), stroke (1.15, 1.00-1.31, P = 0.047), but not total CVD (1.03, 0.93-1.15, P = 0.52) with no evidence of publication bias (P = 0.95, P = 0.30, and P = 0.46, respectively). Long duration of sleep was also associated with a greater risk of CHD (1.38, 1.15-1.66, P = 0.0005), stroke (1.65, 1.45-1.87, P < 0.0001), and total CVD (1.41, 1.19-1.68, P < 0.0001) with no evidence of publication bias (P = 0.92, P = 0.96, and P = 0.79, respectively). Conclusion Both short and long duration of sleep are predictors, or markers, of cardiovascular outcomes.
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              Social jetlag: misalignment of biological and social time.

              Humans show large differences in the preferred timing of their sleep and activity. This so-called "chronotype" is largely regulated by the circadian clock. Both genetic variations in clock genes and environmental influences contribute to the distribution of chronotypes in a given population, ranging from extreme early types to extreme late types with the majority falling between these extremes. Social (e.g., school and work) schedules interfere considerably with individual sleep preferences in the majority of the population. Late chronotypes show the largest differences in sleep timing between work and free days leading to a considerable sleep debt on work days, for which they compensate on free days. The discrepancy between work and free days, between social and biological time, can be described as 'social jetlag.' Here, we explore how sleep quality and psychological wellbeing are associated with individual chronotype and/or social jetlag. A total of 501 volunteers filled out the Munich ChronoType Questionnaire (MCTQ) as well as additional questionnaires on: (i) sleep quality (SF-A), (ii) current psychological wellbeing (Basler Befindlichkeitsbogen), (iii) retrospective psychological wellbeing over the past week (POMS), and (iv) consumption of stimulants (e.g., caffeine, nicotine, and alcohol). Associations of chronotype, wellbeing, and stimulant consumption are strongest in teenagers and young adults up to age 25 yrs. The most striking correlation exists between chronotype and smoking, which is significantly higher in late chronotypes of all ages (except for those in retirement). We show these correlations are most probably a consequence of social jetlag, i.e., the discrepancies between social and biological timing rather than a simple association to different chronotypes. Our results strongly suggest that work (and school) schedules should be adapted to chronotype whenever possible.
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                Author and article information

                Contributors
                ajphillips@partners.org
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                12 June 2017
                12 June 2017
                2017
                : 7
                : 3216
                Affiliations
                [1 ]ISNI 0000 0004 0378 8294, GRID grid.62560.37, Sleep Health Institute and Division of Sleep and Circadian Disorders, Departments of Medicine and Neurology, , Brigham and Women’s Hospital, ; Boston, MA USA
                [2 ]ISNI 000000041936754X, GRID grid.38142.3c, Division of Sleep Medicine, , Harvard Medical School, ; Boston, MA USA
                [3 ]ISNI 0000 0001 2341 2786, GRID grid.116068.8, Affective Computing Group, Media Lab, , Massachusetts Institute of Technology, ; Cambridge, MA USA
                Article
                3171
                10.1038/s41598-017-03171-4
                5468315
                28607474
                b70bfb0c-b9a6-45e0-8cf0-9b7b4d4e2238
                © The Author(s) 2017

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 7 December 2016
                : 24 April 2017
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