Faculty Bibliography

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: 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: 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 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: While there is epidemiologic evidence that racial/ ethnic minorities report shorter sleep duration and poorer sleep quality than whites, few studies have assessed sleep continuity (SC), variable by variable (e.g., SL, NWAK, WASO, EMA, & TST). The present analysis assesses in a quantitative way whether insomnia symptom severity varies by race/ethnicity.
Method(s): An archival analysis was conducted on an existing database of 4,206 individuals who completed a screening survey on-line at https://urldefense.proofpoint.com/v2/url?u=http- 3A__www.sleeplessinphilly.com&d=DwIBAg&c=j5oPpO0eBH1iio48DtsedeElZfc04rx3ExJHeIIZuCs&r=CY_ mkeBghQnUPnp2mckgsNSbUXISJaiBQUhM-Uz9W58&m=_icVcFoc7ulJmPF3ojT4VQ- keh3a2N4OhtHGRLx7AN4&s=GRc5DD1Hlq9WkqeVHjBH7X9hXNa8mcKsHyVAl9iK8QI&e=. Variables collected included estimates for: sleep latency (SL), number of awakenings (NWAK), wake after sleep onset (WASO), early morning awakenings (EMA) and total sleep time (TST).
Result(s): The sample for the present analysis was comprised of 2,049 whites (63.4%), 1,007 blacks (31.2%), and 175 Hispanics (5.4%). The overall mean age was 39.0+/-14.7, 60.4% of the sample was female, and the average BMI was 28.0+/-7.1. For all SC variables, blacks significantly differed from whites: SL (49.2+/-38.3 vs. 42.8+/-30.5; p<.001); NWAK (2.64+/-1.7 vs. 2.50+/-1.6; p<.001); WASO (47.3+/-43.4 vs. 29.9+/-30.5; p<.000); EMA (63.4+/-41.8 vs. 57.2+/-33.0; p<.000); Hispanics did not significantly differ from whites with respect to the above measures. For self-reported TST, blacks and Hispanics significantly differed from whites (316.4+/-85.1; 356.2+/-73.7; 365.8+/-80.6, respectively; p<0.000).
Conclusion(s): Our results suggest that blacks exhibit marginally worse sleep continuity (statistically significant owing to the large sample sizes) and shorter TSTs. Analysis is ongoing to evaluate Time in Bed [TIB], calculated TST, SE%, sleep period, sleep schedule differences, and percentage of group with Insufficient Sleep Disorder by race, in matched samples

Introduction: Several studies have demonstrated that insomnia symptoms negatively impact adherence to Continuous Positive Airway Pressure (CPAP). Yet, little is known about psychosocial factors that may buffer the associated negative effects. The present study explored the role of resilience, the ability to function in the face of or following adversity, on reducing the negative effects of insomnia on CPAP adherence.
Method(s): The study sample included volunteers from a large sleep center enrolling individuals newly diagnosed with Obstructive Sleep Apnea (OSA). For this analysis, we examined volunteers with complete data (n=45) on insomnia severity (based on the Insomnia Severity Index (ISI)), resilience (based on the Connor Davidson Resiliency Scale (CD-RISC)), and objective median hours of CPAP use over the first 30 days of treatment.
Result(s): The mean age was 55.4 years (SD=15.7); 62.2% male, and 33% black. The mean ISI score was 13.0 (SD=6.3), mean CD-RISC was 30.7 (SD=5.7) and mean CPA use over the first 30 days was 5.9 (SD=1.9). In the linear regression, ISI was positively correlated with increased hours of CPAP use (r=-0.305, p=.047). Resilience was not significantly correlated with CPAP use (r=0.216, p=.163), likely attributable to the sample size. ISI correlated with CPAP use among those with low resilience (r=-0.461, p=.027), but not among those with high resilience (r=-0.039, p=.870). There was a significant interaction (B(SE)=0.22 (0.08); p=.005) between ISI and resilience on median hours of CPAP use, indicating that resilience may moderate the association between ISI and hours of CPAP use.
Conclusion(s): Results of our study indicated that resilience is an important factor and may reduce the negative effects of insomnia on CPAP adherence. Notably, the high resilience score in this sample could signal an important target for tailoring CPAP adherence interventions to address unique characteristics of each subgroup

Introduction: The influence of aging on the symptomatic presentation of obstructive sleep apnea (OSA) is not well-characterized in US veterans. Our aims were to 1) examine age and established predictors of sleepiness and insomnia symptoms in US veterans with OSA and 2) determine if the relationship between predictors and sleepiness and insomnia depended on age.
Method(s): We performed a retrospective analysis of US veterans newly-diagnosed with OSA at the Miami VA in 2015. On diagnostic PSG night (76% attended studies), questionnaires were completed querying demographics, social characteristics, insomnia symptoms (Insomnia severity index [ISI]), sleepiness (Epworth sleepiness scale [ESS]) and self-reported sleep duration. Medical and psychiatric comorbidities were assessed with electronic medical record review. Linear regression modeling was used to explore the association of variables with 1) ESS and 2) ISI. Regression analyses were performed in two steps: 1) all variables were entered simultaneously testing for main effects, 2) the product of age and each variable found to have an association at a significance level of p < 0.10 with the primary outcome was entered separately to test for interaction.
Result(s): The sample consisted of 483 veterans (93% male, age 52 +/- 13 yrs, 41% black, 34% Hispanic) diagnosed with OSA (AHI 36 +/- 28 events/hr of sleep). Having a regular bed partner, higher weighted medical comorbidities, chronic pain diagnosis, and shorter sleep duration were associated with ESS. Age did not moderate the relationship between these variables and the ESS. Younger age, Hispanic ethnicity, higher educational level, shorter sleep duration, mood and pain diagnoses were each associated with the ISI. Furthermore, an age-sleep duration interaction term was associated with the ISI (b = -0.03; p=0.005). For all participants, there was an inverse relationship between sleep duration and ISI scores. However, for any sleep duration, older veterans reported a lower level of insomnia symptoms than younger veterans.
Conclusion(s): Older veterans with OSA may report less sleep complaints. Personalized screening methods for older individuals with OSA may be needed

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