Faculty Bibliography

Introduction: Sleep health is associated with many domains of functioning. Yet, changing behaviors linked to improved sleep health is difficult. Beliefs about the health impact of sleep may motivate behavior change. This analysis examined which beliefs about sleep might motivate sleep behavior change.
Method(s): Data were from the Sleep and Healthy Activity, Diet, Environment, and Socialization (SHADES) study, consisting of N=1007 community-dwelling adults age 22-60. Participants were asked, regarding "the single most important thing you personally could do to improve your sleep," whether participants were in the stage of precontemplation (not considered change), contemplation (considered but not decided), preparation (decided but not acting), and action stages of change from the transtheoretical model. They were also asked items from the Sleep Practices and Attitudes Questionnaire (SPAQ) regarding the degree to which they agree with whether "not getting enough sleep" can cause sleepiness, drowsy driving, weight gain, heart disease, high cholesterol, hypertension, moodiness, lower energy, decreased sex drive, missed days at work, decreased performance, memory/concentration problems, diabetes, and/or tiredness. Ordinal logistic regressions evaluated increased likelihood of stage of change, based on degree of agreement with those statements, adjusted for age, sex, race/ethnicity, and education. Post-hoc analyses also examined sleep duration as an additional covariate.
Result(s): In adjusted analyses, stage of change was associated with degree of agreement that insufficient sleep can cause sleepiness (OR=1.17, p=0.035), weight gain (OR=1.20, p<0.0005), heart disease (OR=1.21, p=0.001), cholesterol (OR=1.13, p=0.047), hypertension (OR=1.16, p=0.014), moodiness (OR=1.42, p<0.0005), decreased energy (OR=1.30, p=0.002), absenteeism (OR=1.13, p=0.007), decreased performance (OR=1.20, p=0.003), concentration/ memory problems (OR=1.23, p=0.004), diabetes (OR=1.14, p=0.042), and feeling tired (OR=1.39, p<0.0005). When sleep duration was added to the model, significant relationships remained for weight, heart, hypertension, moodiness, energy, absenteeism, performance, memory, diabetes, and tiredness.
Conclusion(s): Degree of belief that insufficient sleep can cause outcomes such as moodiness, occupational problems, and health problems may impact whether an individual is contemplating/ attempting to improve their sleep. This may guide education/outreach efforts

Introduction: Previous studies have shown that racial/ethnic minorities are more likely to be short and/or long sleepers, which may increase risk for morbidity/mortality. This analysis provides a more recent update from a very large national dataset, including representation of additional groups and examination of the role of poverty.
Method(s): Data from the 2016 Behavioral Risk Factor Surveillance System (BRFSS, collected by the CDC) were used. N=464,671 adults >18yrs from all US states/territories provided data on sleep, demographics, and socioeconomics. Sleep duration was categorized as very short (<=4h), short (5-6h), normal (7-8h as reference), and long (>=9h). Race/ethnicity was self-reported as Non-Hispanic White, Black/ African-American, Hispanic/Latino, American-Indian/Alaskan-Native (AIAN), Native Hawaiian/Pacific-Islander (NHPI), or Multiracial/Other. Covariates included age, sex, relationship status, education, employment, and home ownership. Interactions were explored with poverty (income<$20,000) were explored. Multinomial logistic regressions were weighted using BRFSS-specific weights.
Result(s): A significant race-by-poverty interaction was seen (p<0.0005). Compared to non-poor Non-Hispanic White, increased very short sleep was seen among those who were non-poor Black/African-American (RRR=2.1, p<0.0005), Asian (RRR=1.6, p=0.001), AIAN (RRR=1.4, p=0.001), NHPI (RRR=2.0, p=0.002), and Multiracial/Other (RRR=2.2, p<0.0005), and poor Non-Hispanic White (RRR=1.8, p<0.0005), Black/African-American (RRR=1.8, p<0.0005), AIAN (RRR=1.5, p=0.007), NHPI (RRR=2.4, p=0.005), and Multiracial/Other (RRR=3.4, p<0.0005). Compared to non-poor White, increased short sleep was seen among non-poor Black/African-American (RRR=1.7, p<0.0005), Asian (RRR=1.3, p<0.0005), AIAN (RRR=1.2, p=0.02), NHPI (RRR=1.3, p=0.02), Multiracial/Other (RRR=1.3, p<0.0005), and poor Non-Hispanic White (RRR=1.3, p<0.0005), Black/African-American (RRR=1.4, p<0.0005), Asian (RRR=1.3, p=0.04), and Multiracial/Other (RRR=2.2, p<0.0005). Compared to non-poor Non-Hispanic White, increased long sleep was seen for Non-Poor Black/African-American (RRR=1.4, p<0.0005), Poor Non-Hispanic White (RRR=1.3, p<0.0005), Black/African-American (RRR=1.4, p<0.0005), and AIAN (RRR=1.3, p<0.05).
Conclusion(s): Established racial/ethnic sleep disparities are supported in this large national sample, with additional information on understudied vulnerable groups including AI/AN and NH/PI. Further, the this study as the contribution of poverty status

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: Extant literature has demonstrated that relationship quality is associated with mental and physical health outcomes. However, few studies have assessed how relationship quality is related to sleep. In order to extend this work, the present study examined the relationships between sleep variables and relationship satisfaction.
Method(s): Data were from the Sleep and Healthy Activity, Diet, Environment, and Socialization (SHADES) study. N=998 working-age adults age 22-60 provided complete data. Relationship quality was assessed with the item, "On a scale of 1-100, how would you rate your overall satisfaction with your marriage, current relationship, or relationship status (if not in a relationship)?" Sleep-related outcomes included the Insomnia Severity Index (ISI), Pittsburgh Sleep Quality Index (PSQI), Fatigue Severity Scale (FSS), sleep duration item from the National Health and Nutrition Examination Survey (NHANES), and the Brief Index of Sleep Control (BrISC). Covariates included age, sex, education, race/ethnicity, income, relationship status, and body mass index. Regression analyses examined relationship satisfaction as outcome and sleep variable as predictor. We also tested to see if Perceived Stress Scale (PSS) mediated the association between relationship satisfaction and sleep.
Result(s): After adjustment for age, sex, race/ethnicity, education, income, relationship status, and body mass index, overall relationship quality was associated with a lower ISI score (B=-0.05, p<0.0005), lower PSQI score (B=-0.03, p<0.0005), lower FSS score (B=-0.06, p<0.0005), longer sleep duration (B=0.40, p<0.0005), and higher BRISC score (B=0.004, p<0.0005). After adding perceived stress to the model, overall relationship quality was associated with decreased ISI score (B=-0.02, p<0.002), decreased PSQI score (B=-0.01,p=0.002), and higher sleep duration (B=0.25, p=0.02).
Conclusion(s): Overall relationship satisfaction was associated with longer sleep duration, better sleep quality, daytime fatigue, and perceived control over sleep. These relationships were attenuated after accounting for general stress level, but relationships with sleep duration and quality remained significant

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

Sleep is a fundamental necessity of life. However, sleep health and sleep disorders are not equitably distributed across racial/ethnic groups. In fact, growing research consistently demonstrates that racial/ethnic minorities are more likely to experience, for instance, shorter sleep durations, less deep sleep, inconsistent sleep timing, and lower sleep continuity in comparison to Whites. However, racial/ethnic disparities in reports of sleepiness and sleep complaints are inconsistent. Racial/ethnic groups have significant heterogeneity, yet within-group analyses are limited. Among the few published within-group analyses, there are differences in sleep between non-US-born and US-born racial/ethnic groups, but the group with the more favorable sleep profile is consistent for non-US-born Latinos compared to US-born Latinos and Whites but unclear for other racial/ethnic minority groups. These sleep health disparities are a significant public health problem that should garner support for more observational, experimental, intervention, and policy/implementation research. In this review, we 1) summarize current evidence related to racial/ethnic disparities in sleep health and within-group differences, focusing on the sleep of the following racial/ethnic minority categories that are defined by the United States Office of Management and Budget as: American Indian/Alaska Native, Asian, African American/Black, Hispanic/Latino, and Native Hawaiian/Pacific Islander; 2) discuss measurement challenges related to investigating sleep health disparities; 3) discuss potential contributors to sleep health disparities; 4) present promising interventions to address sleep health disparities; and 5) discuss future research directions on intersectionality and sleep health.

Minority individuals in the United States (US) have an increased prevalence of obstructive sleep apnea (OSA) compared to their white/Caucasian counterparts. In general, adherence to positive airway pressure (PAP) therapy is poor and some studies suggest that PAP use among minority individuals is inferior to that of whites. However, there has not been a review of the evidence that addresses racial-ethnic disparities for PAP adherence in the treatment of OSA, and no review has systematically examined the contributing factors to poor adherence among minority individuals compared to whites. We searched the literature for studies published between January 1990 to July 2016 that included objective PAP use comparisons between adult US minority individuals and whites. Twenty-two studies met the inclusion criteria. All studies compared the PAP adherence of blacks to whites. Seven studies compared the PAP adherence of additional minority groups to that of whites. Sixteen of the 22 studies (73%) showed worse PAP adherence in blacks compared to whites. Four studies found equivalent PAP use in US Hispanics compared to whites. Little is known about the PAP adherence of other US minority groups. We present a framework and research agenda for understanding PAP use barriers among US minority individuals.