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Although mindfulness-based interventions may be effective in addressing the common symptom of fatigue, no population-based studies have examined the relationship between mindfulness and fatigue. We determined whether higher levels of dispositional mindfulness were associated with lower levels of fatigue. Cross-sectional data were obtained through the Pennsylvania Head Start Staff Wellness Survey, a 2012 web-based survey in which 2199 of 3375 (65%) eligible staff participated. The analytic sample was restricted to the 2083 female respondents with complete data on dispositional mindfulness (Cognitive and Affective Mindfulness Scale-Revised) and fatigue (Fatigue Severity Scale). We determined the mean covariate-adjusted fatigue scores in each quartile of dispositional mindfulness. This relationship was examined in the overall sample and within subgroups defined by levels of four variables: depressive symptoms, poor sleep quality, childhood adversity, and chronic medical conditions. The sample was 86% non-Hispanic White, and 61% had a bachelor's or more advanced degree. The mean (SD) Fatigue Severity Scale score was 3.3 (1.3). The adjusted mean fatigue score decreased significantly and in a graded manner across higher quartiles of mindfulness, with the adjusted fatigue score 1.4 points lower (95% confidence interval: -1.5, -1.2) among those in the highest quartile of dispositional mindfulness compared to the lowest. This significant graded relationship was present within each subgroup examined, and there was not a statistically significant interaction between dispositional mindfulness and any subgroup variable. Future trials of mindfulness-based interventions should consider assessing the outcome of fatigue in both clinical and non-clinical populations., (Copyright © 2019. Published by Elsevier Inc.)

Objective: To determine whether self-reported drowsy driving was associated with an evening chronotype, a biologically-based difference in circadian sleep-wake timing, and shorter school-night sleep duration in a sample of high school drivers., Study Design: Cross-sectional observational data were obtained from an online survey in spring 2015 of 431 drivers, age 15.5-18.7 years, attending Fairfax County (Virginia) Public schools. Drowsy driving was defined as having ever "driven a car or motor vehicle while feeling drowsy" in the last year. School-night sleep duration was calculated from school-night bedtime and wake time. Those with scores in the lower and upper tertiles of the Morningness-Eveningness Scale for Children were designated as having an evening or morning chronotype, respectively., Results: Among survey respondents, 63.1% drove at least several times a week and 47.6% reported drowsy driving. The covariate-adjusted prevalence of drowsy driving was 13.9% (95% CI 3.0%-24.9%) higher in students who slept <7 hours on school-nights than in those who slept 8 or more hours. Compared with those with a morning chronotype, the adjusted prevalence of drowsy driving was 15.2% (95% CI 4.5%-25.9%) higher among those with an evening chronotype., Conclusion: Among adolescent drivers, both an evening chronotype and shorter school-night sleep duration were associated with more frequent reports of drowsy driving. Interventions to improve the timing and duration of nighttime sleep in adolescents may reduce the occurrence of drowsy driving., (Copyright © 2018 Elsevier Inc. All rights reserved.)

Objective: To determine whether simultaneous school start time changes (delay for some schools; advance for others) impact adolescents' sleep., Design: Quasi-experimental study using cross-sectional surveys before and after changes to school start times in September 2015., Setting: Eight middle (grades 7-8), 3 secondary (grades 7-12), and 8 high (grades 9-12) schools in Fairfax County (Virginia) public schools., Participants: A total of 2017 (6% of ~34,900) students were surveyed before start time changes, and 1180 (3% of ~35,300) were surveyed after., Intervention: A 50-minute delay (7:20 to 8:10 am) in start time for high schools and secondary schools and a 30-minute advance (8:00 to 7:30 am) for middle schools., Measurements: Differences before and after start time changes in self-reported sleep duration and daytime sleepiness., Results: Among respondents, 57.5% were non-Hispanic white, and 10.3% received free or reduced-priced school meals. Before start time changes, high/secondary and middle school students slept a mean (SD) of 7.4 (1.2) and 8.4 (1.0) hours on school nights, respectively, and had a prevalence of daytime sleepiness of 78.4% and 57.2%, respectively. Adjusted for potential confounders, students with a 50-minute delay slept 30.1 minutes longer (95% confidence interval [CI], 24.3-36.0) on school nights and had less daytime sleepiness (-4.8%; 95% CI, -8.5% to -1.1%), whereas students with a 30-minute advance slept 14.8 minutes less (95% CI, -21.6 to -8.0) and had more daytime sleepiness (8.0%; 95% CI, 2.5%-13.5%)., Conclusions: Both advances and delays in school start times are associated with changes in adolescents' school-night sleep duration and daytime sleepiness. Larger changes might occur with later start times., (Copyright © 2017 National Sleep Foundation. Published by Elsevier Inc. All rights reserved.)

Objective: To determine whether shorter school-night sleep duration, greater daytime sleepiness, and greater eveningness chronotype were associated with lower self-regulation among adolescents., Methods: An online survey of 7th- to 12th-grade students in 19 schools in Fairfax County, Virginia Public Schools was conducted in 2015. Self-regulation was measured with the Behavior Rating Inventory of Executive Function, 2nd edition, Screening Self-Report Form. Sleep measures included school night-sleep duration (hours between usual bedtime and wake time), daytime sleepiness (Sleepiness Scale in the Sleep Habits Survey, tertiles), and chronotype (Morningness-Eveningness Scale for Children, continuous score and tertiles). Sociodemographic factors and mental health conditions were analyzed as potential confounders., Results: Among 2017 students surveyed, the mean age was 15.0 years (range, 12.1-18.9 years), and 21.7% slept <7 hours on school nights. In regression models adjusted for confounders, there was a significant independent association between self-regulation and both chronotype (P < .001) and daytime sleepiness (P < .001) but not sleep duration (P = .80). Compared with those in the lowest tertile of daytime sleepiness, those in the highest tertile had lower (0.59 SD units; 95% confidence interval, 0.48-0.71) self-regulation, as did those in the eveningness tertile of chronotype compared with those in the morningness tertile (0.35 SD units lower; 95% confidence interval, 0.24-0.46)., Conclusions: Among adolescents, greater daytime sleepiness and greater eveningness chronotype were independently associated with lower self-regulation, but shorter sleep duration was not. Aspects of sleep other than school-night sleep duration appear to be more strongly associated with self-regulation., (Copyright © 2016 by the American Academy of Pediatrics.)

Objective: To determine whether preschool-aged children with earlier bedtimes have a lower risk for adolescent obesity and whether this risk reduction is modified by maternal sensitivity., Study Design: Data from 977 of 1364 participants in the Study of Early Child Care and Youth Development were analyzed. Healthy singleton-births at 10 US sites in 1991 were eligible for enrollment. In 1995-1996, mothers reported their preschool-aged (mean = 4.7 years) child's typical weekday bedtime, and mother-child interaction was observed to assess maternal sensitivity. At a mean age of 15 years, height and weight were measured and adolescent obesity defined as a sex-specific body-mass-index-for-age ≥95th percentile of the US reference., Results: One-quarter of preschool-aged children had early bedtimes (8:00 p.m. or earlier), one-half had bedtimes after 8:00 p.m. but by 9:00 p.m., and one-quarter had late bedtimes (after 9:00 p.m.). Children's bedtimes were similar regardless of maternal sensitivity (P = .2). The prevalence of adolescent obesity was 10%, 16%, and 23%, respectively, across early to late bedtime groups. The multivariable-adjusted relative risk (95% CI) for adolescent obesity was 0.48 (0.29, 0.82) for preschoolers with early bedtimes compared with preschoolers with late bedtimes. This risk was not modified by maternal sensitivity (P = .99)., Conclusions: Preschool-aged children with early weekday bedtimes were one-half as likely as children with late bedtimes to be obese as adolescents. Bedtimes are a modifiable routine that may help to prevent obesity., Competing Interests: The authors declare no conflicts of interest., (Copyright © 2016 Elsevier Inc. All rights reserved.)

Objective: To determine the association between the prevalence of obesity in preschool-aged children and exposure to 3 household routines: regularly eating the evening meal as a family, obtaining adequate sleep, and limiting screen-viewing time., Methods: We conducted a cross-sectional analysis of a nationally representative sample of approximately 8550 four-year-old US children who were assessed in 2005 in the Early Childhood Longitudinal Study, Birth Cohort. Height and weight were measured. We assessed the association of childhood obesity (BMI > or = 95th percentile) with 3 household routines: regularly eating the evening meal as a family (>5 nights per week); obtaining adequate nighttime sleep on weekdays (> or =10.5 hours per night); and having limited screen-viewing (television, video, digital video disk) time on weekdays (< or =2 hours/day). Analyses were adjusted for the child's race/ethnicity, maternal obesity, maternal education, household income, and living in a single-parent household., Results: Eighteen percent of children were obese, 14.5% were exposed to all 3 routines, and 12.4% were exposed to none of the routines. The prevalence of obesity was 14.3% (95% confidence interval [CI]: 11.3%-17.2%) among children exposed to all 3 routines and 24.5% (95% CI: 20.1%-28.9%) among those exposed to none of the routines. After adjusting for covariates, the odds of obesity associated with exposure to all 3, any 2, or only 1 routine (compared with none) were 0.63 (95% CI: 0.46-0.87), 0.64 (95% CI: 0.47-0.85), and 0.84 (95% CI: 0.63-1.12), respectively., Conclusions: US preschool-aged children exposed to the 3 household routines of regularly eating the evening meal as a family, obtaining adequate nighttime sleep, and having limited screen-viewing time had an approximately 40% lower prevalence of obesity than those exposed to none of these routines. These household routines may be promising targets for obesity-prevention efforts in early childhood.