Objective: Poor sleep is associated with higher levels of inflammatory biomarkers. Conventionally, higher average time awake, lower average time asleep, and lower sleep efficiency define poor sleep. Recent research suggests that, in addition to average sleep, sleep inconsistency is an important indicator of sleep dysfunction. The current study sought to extend our knowledge of the relationship between sleep and inflammation through an examination of sleep inconsistency and inflammatory biomarkers. Methods: Secondary analyses of the Survey of Midlife in the United States (MIDUS) sleep study were conducted. Five hundred thirty-three individuals completed nightly sleep diaries, actigraphy, and underwent a blood draw for the inflammatory biomarkers C-reactive protein, interleukin-6, and fibrinogen. Sleep inconsistency was derived from 7 consecutive nights of assessment and was operationalized as nightly fluctuations in the following variables: terminal wakefulness, number of awakenings, time in bed, sleep onset latency, and wake after sleep onset. Structural equation modeling was used to examine the influence of a latent average sleep and a latent sleep inconsistency variable on a latent inflammation variable. Models were subsequently adjusted for age, sex, BMI, health, and medication. Stratified models by sex were also analyzed. Results: The average sleep model would not converge. The sleep inconsistency model fit the data well. A significant positive association between the latent factors sleep inconsistency and inflammation was observed (β = 10.18, SE = 4.40, p = 0.021), suggesting inconsistent sleep is associated with higher levels of inflammatory biomarkers. When stratified by sex, the association between the latent sleep inconsistency factor and inflammation was significant for women (β = 1.93, SE = 0.82, p = 0.018), but not men (β = 0.20, SE = 0.35, p = 0.566). The association between sleep inconsistency and inflammation weakened following multivariate adjustment (β = 6.23, SE = 3.71, p = 0.093). Conclusions: Inconsistent sleep may be an associated feature of inflammatory dysfunction, especially in women. Future studies should build upon this preliminary work and examine these associations longitudinally and through treatment trials.

Background: College students are at increased risk for sleep disorders, including insomnia disorder and obtaining less than 6.5 hr of sleep per night by choice, or behaviorally induced insufficient sleep syndrome (BIISS). These disorders can have deleterious daytime consequences, including depression. This study aims to establish the prevalence of insomnia and BIISS disorders and examine associations of insomnia and BIISS with other sleep characteristics and depression. Methods: A subset of data from Spit for Science, a college risk behaviors and health study (n = 989) was used. Insomnia and BIISS were defined as mutually exclusive disorders, based on diagnostic criteria. Results: A majority (68%) of students were categorized as normal sleepers, followed by insomnia (22%), and BIISS (10%). Sleep duration was comparable between BIISS and insomnia, while daytime sleepiness was significantly higher in BIISS, and sleep latency was longer in insomnia (m = 44 vs. m = 13 min). Insomnia was associated with the highest depression symptoms, followed by BIISS, and normal sleep, controlling for demographics. Insomnia was associated with twice the risk of moderate or higher depression compared to normal sleep (CI: 1.60, 2.70, p < .001). Conclusion: These findings highlight the sleep difficulties endemic to college populations. Further, this study provides the first prevalence estimation of BIISS in college students and the first comparison of insomnia and BIISS on sleep characteristics and depressive symptoms. This study underscores the importance of targeted screening and intervention to improve both sleep and depression in this vulnerable population.

Sleep health, operationalized as a multidimensional construct consisting of sleep regularity, satisfaction, alertness, timing, efficiency, and duration, is an emerging concept in the field of sleep medicine which warrants further investigation. The purpose of the present study was to: (1) compare sleep health across the lifespan, (2) determine lifestyle factors associated with sleep health, and (3) examine whether lifestyle factors associated with sleep health varied between and within age groups. Participants consisted of 3284 individuals (Mean age = 42.70; 45% male) who participated in a cross-sectional online survey of sleep and health. Sleep health was measured using the RU-SATED scale, while demographic and lifestyle factors (e.g., daily social media use, sedentary activity, fast food consumption, etc.) were all self-reported. Sleep health was the highest among older adults (M = 8.09) followed by middle-aged (M = 7.65) and younger adults (M = 7.16). Across age groups, fast-food consumption, daily regularity, and daily TV, social media, or internet use were all negatively correlated with sleep health (ps < 0.05). Few differences in the association between lifestyle factors and sleep health across age groups were found. Overall, these findings may help to inform sleep health promotion efforts by targeting the most pertinent lifestyle factors for promoting sleep health.