Faculty Bibliography

Introduction: Child fatigue has been associated with behavioral outcomes, including aggression, hyperactivity, and conduct problems, which may affect academic performance. We explored whether fatigue was associated with external behavioral health outcomes in a predominantly Black (Afro-Caribbean and African-American) student population (90%). Ratings of parent and teacher agreement of child fatigue was evaluated. This analysis was part of a larger research program, which included a cluster randomized controlled trial in ten public elementary schools in historically disinvested neighborhoods.
Method(s): A total of 804 first-graders (7+/- 0.6 years old) participated in the study focused on child self-regulation, mental health achievement, parenting and parent involvement. Externalizing behaviors (i.e., conduct problems, aggression, and hyperactivity) were reported by teachers using the Behavior System for Children (BASC-2). A composite score of teacher-perceived child fatigue was created based on ratings of child fatigue, morning alertness, and falling asleep in class. Parent perception of child fatigue was assessed using the Children's Sleep Habits Questionnaire. Regression analysis was conducted to determine the association between teacher's reports of child fatigue and externalizing behavior problems. Cohen's kappa coefficient assessed parent and teacher agreement of child fatigue based on categorical classification of presence of child fatigue.
Result(s): Children who were perceived as fatigued (i.e., tiredness and falling asleep in class) by their teacher were more likely to have a high BASC externalizing composite score (T=60 cut off) (beta = -0.24, p<.001). Cohen's kappa of 0.004 (p<0.05) showed a slight discordance in perception of child fatigue comparing reports from teachers and parents, although results were not significant.
Conclusion(s): Teacher perception of child fatigue was significantly associated with teacher BASC T-score of child externalizing behavior outcomes. Future studies should explore longitudinal relationships between fatigue and mental health

Introduction: Based on principles of community-based participatory research methods (CBPR), a community-oriented framework was applied in three studies that focused on African- Americans/ Blacks (herein referred to as Blacks): The Metabolic Syndrome Outcome Study (MetSO), Tailored Approach to Sleep Health Education (TASHE), and Peer-Based Sleep Health Education and Social Support (PEERS-ED). We describe results of our application of this framework to enroll and study Blacks in these NIHfunded studies of obstructive sleep apnea (OSA).
Method(s): Our community-oriented framework includes strategic guidelines for effective intervention to engage communities in research and ensure cultural and linguistic appropriateness of sleep messages in behavioral interventions. Strategies included: 1) focus groups and in-depth interviews with key stakeholders; 2) establishing a community advisory board; 3) conducting Delphi surveys to identify high-priority diseases and conditions. Community barriers were identified through an iterative process using surveys and focus groups. Stakeholder groups were integral during the development, implementation and dissemination, reflecting a patient-oriented decision-making process with respect to key intervention components.
Result(s): MetSO, TASHE, and PEERS-ED reached nearly 3,000 Blacks at risk of OSA in New York City. Of those, 2,000 were screened for OSA. Sleep brochures were distributed to over 10,000 individuals. The mean age of community participants was 62+/-14 years; 69% were female; 43% had an annual income <$10,000; and 37% had 10); 10% reported an insomnia diagnosis and 12% used sleep medications. Based on WatchPAT data, 24% had moderate OSA and 18%, severe OSA. Compared to blacks receiving standard sleep messages, those exposed to tailored sleep messages in our interventions were nearly 4 times as likely to adhere to OSA care.
Conclusion(s): Community outreach may be an effective strategy in the reach and spread of sleep messages among low-income Blacks at-risk for OSA

Introduction: Using the National Health and Aging Trends Study (NHATS), we examined use of sleeping medication, difficulty falling asleep, and trouble falling back asleep among individuals with and without cognitive impairment.
Method(s): Binomial logistic regression examined sleep medication use and insomnia symptoms (difficulty falling asleep or falling back asleep after awakening) by cognitive impairment (no dementia and possible or probable dementia). Sleep-related variables were collected on frequency scales ranging from 1 (every day) to 5 (never). Of the sample, 71.1% were White (n=3,369), 20.7% were Black (n=982), 5.0% were Hispanic (n=235), and 2.4% other (n=113); 60.4% were female (n=2,662) and 39.6% were male (n=1,875).
Result(s): Respondents were classified as having no dementia (63.7%), possible dementia (8.5%), or probable dementia (12.9%). Of the sample, 10.7% reported medication use every night, 2.5% 5-6 nights/week, 5.7% 2-4 nights/week, 6.6% once/week and 59.4% reported no use. Of the respondents, 8.3% reported difficulty sleeping every night, 8.0% reported 5-6 nights/week, 21.4% reported 2-4 nights/week, 22.9% reported rarely, and 23.5% reported never experiencing difficulty sleeping. Regarding difficulty falling back asleep, 4.9% reported difficulty every night, 7.4% reported 5-6 nights/week, 26.0% reported 2-4 nights/week, 20.4% reported rarely, and 24.3% reported never. Compared to individuals who reported never using sleep medications, those reporting nightly use were significantly more likely to be cognitively impaired (OR=1.44,95%CI: 1.14-1.82). Compared to individuals reporting never having difficulty falling asleep, those reporting difficulty falling asleep nightly were not more likely to have cognitive impairment (OR=0.74 95%CI: 0.67 to 1.19). Compared to individuals reporting never having difficulty falling back asleep after awakening, those frequently reporting difficulty falling back asleep were less likely to be cognitively impaired (OR=0.44,95%CI:0.22 to 0.64).
Conclusion(s): Cognitive impairment was positively associated with sleep medication use in adjusted models, but not with trouble falling asleep or difficulty falling back asleep after awakening. Our findings are consistent with the literature on deleterious consequences of sleep medications

Introduction: We determined whether the co-occurrence of OSA and hypertension interact synergistically to promote beta-Amyloid burden and cognitive decline in clinically normal older adults Methods: Prospective longitudinal study utilizing NYU cohort of community-dwelling cognitively-normal elderly, with baseline and at least one follow-up of CSF-Abeta42 (measured using ELISA), and neuropsychological visits. OSA was defined using AHI4%. Hypertension diagnosis was according to AHA-guidelines. Cognitive variables assessed included Logic-2, Animal-Fluency [AF], Vegetable-Fluency [VF]), Boston-Naming-Test [BNT], Digit-Symbol-Substitution-Test [DSST], Trails Making Test-A and B [TMT-A and B]). Linear mixed-effects models with random intercept and slope were used to assess associations between OSA, hypertension, and longitudinal changes in CSF-Abeta and cognition, controlling for age-at-baseline, sex, APOE4-status, years-of-education, and their interactions with time.
Result(s): Of the 98 participants, 63 (64.3%) were women. The mean (SD) age was 69.6 (7.3) years and follow-up time was 2.46 (0.64) years. OSA and hypertension were each associated with faster rate-of-change in CSF-Abeta42 (beta = -3.11; 95%CI, -3.71, -2.51; and beta= -2.82, 95% CI -3.29, -2.35, P < .01 for both respectively). The interaction of OSA and hypertension with time was significant (beta= -1.28, 95% CI -1.78 to -0.78, P < .01) suggesting a synergistic effect. No significant associations were seen between annual-changes in CSF-Abeta42 and cognitive-decline. However, faster decline in VF, and DSST were associated with OSA (beta = -0.054; 95%CI, -0.094, -0.013; P = .02; beta = -0.058; 95%CI, -0.084, -0.033; P < .05 for both respectively), and with hypertension (beta = -0.048; 95%CI, -0.079, -0.017; P = .04; beta = -0.078; 95%CI, -0.098, -0.057; P = .002; respectively). The interaction of OSA and hypertension with time was significant for both VF and DSST (beta = -0.033, 95%CI, -0.048, -0.018; P < .001 and beta = -0.040, 95%CI, -0.064, -0.016; P < .001, respectively), suggesting a synergistic effect.
Conclusion(s): In cognitive-normal elderly OSA individuals, vascular risk may complement AD-biomarkers in assessing risk of prospective cognitive-decline in preclinical AD

Introduction: Sleep health encompasses a number of concepts, including "satisfaction," timing, efficiency, duration, and absence of disorders, and is related to mental/physical health. This analysis aims to explore the idea of "sleep satisfaction" and how it relates to these concepts.
Method(s): Data were from N=1,003 working-age adults age 22-60 in the Philadelphia area. Participants were asked to rate their satisfaction with sleep on a scale of 0-100 (100=max). Participants also completed the Insomnia Severity Index, Epworth Sleepiness Scale, Fatigue Severity Scale, Brief Inventory of Sleep Control, sleep duration (categorized as <=4h, 5-6h, 7-8h[ref], and >=9h), habitual bedtime, Patient Health Questionnaire (for depression), GAD7 anxiety scale, Perceived Stress Scale, and an overall indicator of health (Excellent, Very Good, Good, Fair, or Poor). Linear regression analyses examined whether each of these individually and/or uniquely contributed variance to sleep satisfaction after adjustment for age, sex, race/ethnicity, education, and income.
Result(s): The following significantly predicted worse sleep satisfaction (in order of decreasing magnitude): insomnia symptoms (B=- 2.99, p<0.0005), sleep duration in the <=4h (B=-38.57, p<0.0005), 5-6h (B=-19.03, p<0.0005), and >=9h (B=-8.15, p=0.032) ranges vs 7-8h, lack of sleep control (B=3.42, p<0.0005), later bedtime (B=-2.83, p<0.0005), sleepiness (-1.82, p<0.0005), fatigue (B=-0.86, p<0.0005), depression (B=-2.38, p<0.0005), anxiety (B=-2.16, p<0.0005), stress (B=-1.32, p<0.0005), and overall health rated as good (B=-15.29, p<0.0005), fair (B=-27.22, p<0.0005), and poor (B=-38.79, p<0.0005), vs excellent. In a model with all variables combined, unique variance was contributed only by insomnia, sleep duration, sleep control, and depression; other variables were non-significant.
Conclusion(s): Sleep satisfaction, as a concept, is related to nighttime sleep experiences, daytime impairment experiences, and overall mental and physical health. However, some of these relationships overlap and a combined model suggests that sleep satisfaction mostly represents a combination of nighttime sleep duration/ quality, perceived control, and daytime mood

Introduction: Population estimates for sleep duration and quality are inconsistent because they rely on self-report and smaller samples using objective data. Tracking and wearable devices may provide more accurate estimates of sleep duration and quality. In this study, we investigated estimates of sleep duration and quality among 2 million users of a mobile sleep application in an urban city in the United States (U.S.).
Method(s): We examined sleep duration and quality from 2,194,897 users of SleepCycle, a popular sleep tracking app. over a four-year period (2015 to 2018). In this analysis, we specifically explored differences in sleep duration and quality by demographic factors, including age and sex. We utilized graphical matrix representations of data (heat maps) and geospatial analyses to compare sleep duration (in hours) and sleep quality (based on a composite score amalgamating time in bed, deep-sleep time, sleep consistency, and amount of times fully awake), considering potential effects of day of the week and seasonality.
Result(s): Among SleepCycle users, 45.6% (n=1,001,335) were female. The average age of the sample was 31.0 years. The mean sleep duration of the total sample was 7.11 hours; women slept longer than did men (M=7.27 hours vs. M=7.00 hours, p<.001). Increasing age tended to be associated with longer sleep duration and better sleep quality. Results also showed sleep duration was longer on weekends (M=7.19 hours), compared to weeknights (M=7.09 hours). Sleep duration was longest (M=7.18 hours) during the winter, but shortest during the summer (M=7.11 hours). Sleep quality was highest (M=72.75) during the winter, but lowest during the summer (M=71.99).
Conclusion(s): Our findings from big data are consistent with previously reported estimates of sleep duration and quality. Sleep duration varied by age, sex, day of the week, and season. Future studies should determine whether estimates of sleep duration and quality are affected by environmental factors such as geographic location

OBJECTIVE/UNASSIGNED:Workplace-based employee health promotion programs often target weight loss or physical activity, yet there is growing attention to sleep as it affects employee health and performance. The goal of this review is to systematically examine workplace-based employee health interventions that measure sleep duration as an outcome. DATA SOURCE/UNASSIGNED:We conducted systematic searches in PubMed, Web of Knowledge, EMBASE, Scopus, and PsycINFO (n = 6177 records). STUDY INCLUSION AND EXCLUSION CRITERIA/UNASSIGNED:To be included in this systematic review, studies must include (1) individuals aged >18 years, (2) a worker health-related intervention, (3) an employee population, and (4) sleep duration as a primary or secondary outcome. RESULTS/UNASSIGNED:Twenty studies met criteria. Mean health promotion program duration was 2.0 months (standard deviation [SD] = 1.3), and mean follow-up was 5.6 months (SD = 6.5). The mean sample size of 395 employees (SD = 700.8) had a mean age of 41.5 years (SD = 5.2). Measures of sleep duration included self-report from a general questionnaire (n = 12, 66.6%), self-report based on Pittsburgh Sleep Quality Index (n = 4, 22.2%), and self-report and actigraphy combined (n = 5, 27.7%). Studies most commonly included sleep hygiene (35.0%), yoga (25.0%), physical activity (10.0%), and cognitive-behavioral therapy for insomnia (10.0%) interventions. Across the interventions, 9 different behavior change techniques (BCTs) were utilized; the majority of interventions used 3 or fewer BCTs, while 1 intervention utilized 4 BCTs. Study quality, on average, was 68.9% (SD = 11.1). Half of the studies found workplace-based health promotion program exposure was associated with a desired increase in mean nightly sleep duration (n = 10, 50.0%). CONCLUSIONS/UNASSIGNED:Our study findings suggest health promotion programs may be helpful for increasing employee sleep duration and subsequent daytime performance.