Irregular sleep/wake patterns are associated with poorer academic performance and delayed circadian and sleep/wake timing
- PMID: 28607474
- PMCID: PMC5468315
- DOI: 10.1038/s41598-017-03171-4
Irregular sleep/wake patterns are associated with poorer academic performance and delayed circadian and sleep/wake timing
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.
Conflict of interest statement
L.K.B. has previously received research support from Cephalon, NFL charities, Sysco and San Francisco Bar Pilots. She has received consulting/lecture fees or served as a board member for Alertness Solution, Ceridian, Davis Joint Unified School Board, San Jose State University Foundation, Pugot Sound Pilots, Sygma and Torvec. RWP is a co-founder of and shareholder in Empatica Inc and Affectiva Inc and serves on the board of Empatica. She is inventor or co-inventor on over two dozen patents, mostly in the field of affective computing and physiological measurement. She has received royalty payments from MIT for patents licensed to Affectiva, consulting and honorarium payments from Merck, Samsung, Analog Devices, and fees for serving as an expert witness in cases involving wearable sensors from Apple and Intel. Her research is funded in part by a consortium that includes over 70 companies who fund the MIT Media Lab (up to date list is kept online at
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