What Role Does Sleep Play in Weight Gain in the First Semester of University?

Abstract

Objectives We hypothesized that shorter sleep durations and greater variability in sleep patterns are associated with weight gain in the first semester of university. Methods Students (N=132) completed daily sleep diaries for 9-weeks, completed the MEQ (chronotype) and CES-D (depressed mood) at week9, and self-reported weight/height (weeks 1&9). Mean and variability scores were calculated for sleep duration (TST,TSTv), bedtime (BT,BTv), and wake time (WT,WTv). Results An initial hierarchical regression evaluated (block1) sex, ethnicity; (block2) depressed mood, chronotype; (block3) TST; (block4) BT, WT; and (block5; R2change=0.09, p=0.005) TSTv, BTv, WTv with weight change. A sex-by-TSTv interaction was found. A final model showed that ethnicity, TST, TSTv, and BTv accounted for 31% of the variance in weight change for males; TSTv was the most significant contributor (R2 change=0.21, p<0.001). Conclusions Daily variability in sleep duration contributes to males’ weight gain. Further investigation needs to examine sex-specific outcomes for sleep and weight.

Validation of the Sleep Regularity Index in Older Adults and Associations with Cardiometabolic Risk

“…Second, this investigation suggests that the SRI, a novel measure designed to detect rapid changes in sleep schedules as well as adequately characterize the sleep/wake patterns of extremely irregular sleepers, is sensitive to capturing sleep/wake irregularity that may confer risk for developing cardiometabolic disease. This finding dovetails with prior studies linking various indices of sleep irregularity – such as social jetlag, bedtime variability, standard deviation of bedtime, standard deviation of mid-sleep time, and standard deviation of sleep duration – to indices of cardiometabolic health 18 – 23 . Although our findings linking the SRI and cardiometabolic risk support the external validity of the measure, the relative sensitivity of the SRI compared to other measures of sleep irregularity in predicting health outcomes remains an open question and should be the focus of future study.…”

“…There is accumulating evidence – largely from studies with individuals engaged in rotating shift work – to suggest associations between irregular sleep/wake patterns and cardiometabolic disease 14 – 17 ; however, it is unclear how generalizable these findings are to the majority of adults, who have more regular work schedules but may still display irregular sleep patterns, or older individuals, who have retired from the workforce. There is also some initial evidence from studies using self-reports, sleep diaries, and/or actigraphy linking sleep/wake irregularity to weight gain, obesity, insulin resistance, and cardiometabolic illness 18 – 23 . However, measures of sleep irregularity used to date may not assess extremely irregular sleep or capture rapid changes in sleep timing, which are believed to have the largest impact on regulation of the circadian system 24 .…”

Starting university with high eating self-regulatory skills protects students against unhealthy dietary intake and substantial weight gain over 6 months

“…Previous studies have shown that ethnicity does not predict weight changes ( Gillen & Lefkowitz, 2011 ; Roane et al, 2015 ), and this was also the case in the present study. However, a significant moderating effect of eating self-regulatory skills on the relationship between ethnicity and weight changes was found.…”

Sleep Quantity and Quality during Acute Concussion: A Pilot Study

“…Additionally, we observed that individuals with a concussion in our sample experienced greater day-to-day variability in nighttime sleep, which may have substantial negative health consequences. Even in typical adults without a concussion, research has linked such variability to poor subjective sleep quality and lower subjective well-being, 49,50 weight gain, 51 depressive symptoms, 52,53 and stress. 54 In older adults, increased sleep duration variability has been associated with higher rates of diabetes, 55,56 cardiovascular disease, 56 and obesity…”