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Evaluation of the Sleep Regularity Index (SRI) among First-Year College Students: Association with Alcohol Use, Caffeine Consumption, Academic Load, and.

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Presentation on theme: "Evaluation of the Sleep Regularity Index (SRI) among First-Year College Students: Association with Alcohol Use, Caffeine Consumption, Academic Load, and."— Presentation transcript:

1 Evaluation of the Sleep Regularity Index (SRI) among First-Year College Students: Association with Alcohol Use, Caffeine Consumption, Academic Load, and Negative Mood David H. Barker1, Andrew J. Phillips2,3, Mary A. Carskadon1 1. Sleep for Science Research Lab of Brown University, Providence RI, 2. Brigham and Women’s Hospital, Division of Sleep and Circadian Disorders, Boston MA, 3. Harvard Medical School , Division of Sleep Medicine, Boston MA Figure 1. Example Raster Plots for Different SRI scores Objectives Regularity is a feature of sleep has important associations with domains of young-adult functioning, including mood, weight gain, and academic performance. Quantifying regularity can be challenging. The Sleep Regularity Index (SRI) compares the sleep/wake state across adjacent 24 hour periods. The index ranges from 0 (random) to 100 (perfect regularity) and is sensitive to abrupt changes to sleep schedules common during young adulthood (examples of SRI and associated sleep patterns are depicted in Figure 1). We evaluated the SRI among first-year college students using daily diary records. Methods From 2009 to 2014, 1328 first year college students completed daily diaries during their first semester of college. Diaries included bedtime (BT), wake-time (WT), total sleep time (TST), sleep onset latency, and wake after sleep onset for the previous major sleep episode. They also included naps, number of alcoholic drinks, and number of caffeinated drinks. Longer surveys were completed every two weeks that asked about mood (Kandell and Davies, Arch Gen Psychiatry, 1982) and academic load (i.e., number of tests, quizzes, assignments, presentations). Diary data were aggregated across the two weeks prior to each biweekly survey where at least 50% of the diaries were completed (4275 biweekly periods from 1049 participants; Table 1) Binge episodes were defined as 4 or more drinks for females and 5 or more drinks as males Generalized mixed effect models were used to account for nesting of multiple biweekly intervals within participants. Predictors were z-scored. To account for different rates of daily diary completion, all models for outcomes derived from the daily diaries also included an offset term for the number of diaries completed during each biweekly interval. Four models were run for drinking behavior. 1) any drink during the past 2 weeks, 2) among those who drank the number of drinks, 3) among those who drank, any binge episode, and 4) among those who binged, the number of binge episodes. Results SRI has incremental benefit beyond BT and TST in explaining negative mood and some drinking behaviors (number of drinks and any binge episode). Higher SRI (i.e., greater regularity) was associated with earlier Bedtime, β = -.07 [95% CI = -.11; - .04], and shorter Total Sleep Time, β = -.09 [-.12; -.06] (Figure 2). Distribution of SRI scores is shown in Figure 3 Results from multivariate generalized mixed effect models are reported in Table 2. Conclusions The SRI calculated from daily diary records is related to important domains of young-adult functioning including alcohol use and negative mood. Although the SRI is related to sleep duration and timing across a two-week interval in this population, it provides unique information beyond these two measures. Acknowledgements This work was supported by R00HL & MH079179 Table 1. Demographics Figure 2. Relationship between SRI and Bedtime and Total Sleep Time Female, %(n) 57% (598) Age, (mean, SD)  18.65 (0.50) Bedtime 01:39 (66 min) Total Sleep Time 7.44 (0.75) SRI 74.69 (9.41) Negative Mood Range (10-30) 16.54 (4.28) Drinking Behavior Drank during past 2 weeks 46% (483) # of Drinksa (weekly) 5.87 (5.01) Binged during past 2 weeksa 27% (283 # of Bingesb (weekly) 1.14 (1.19) # Caffeinated Drinks weekly 5.10 (5.95) Academic Load 12.23 (7.69) Predicted Relationship From Linear Mixed Effect Model Predicted Relationship From Linear Mixed Effect Model Table 2. Results from Multivariate Generalized Mixed Effect Models Statistic [95% Confidence Interval] Predictor  Outcome Statistic zBedtime zTotal Sleep Time  zSRI Negative Mood β 0.08 [0.03; 0.12] -0.04 [-0.08;-0.01] -0.05 [-0.09;-0.02] Alcoholic Drinks Any Drink AOR 2.05 [1.63;2.56] 1.36 [1.13; 1.63] 0.98 [0.82;1.16] # of Drinksa ARR 1.19 [1.14; 1.24] 1.06 [1.03; 1.24] 0.97 [0.93; 0.99] Any Binge Episodea 1.55 [1.23; 1.94] 1.31 [1.08; 1.60] 0.82 [0.69;0.99] # of Binge Episodesb 1.04 [0.97; 1.10] 1.05 [0.98; 1.11] 0.97 [0.92; 1.02] Caffeinated Drinks 1.04 [1.01;1.07] 0.96 [0.94; 0.98] 0.98 [0.96;1.00] Academic Load 1.12 [1.10; 1.15] 0.97 [0.96; 0.99] 0.99 [0.97; 1.00] Figure 3. Distribution of Biweekly SRI Scores NOTES: All predictors were z-scored. aAmong those who drank during the previous 2 weeks; bAmong those who binged during the previous 2 weeks; β= standardized regression coefficient, AOR= Adjusted Odds Ratio, ARR= Adjusted Rate Ratio; Red highlight= p<.05


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