Faculty Bibliography

BACKGROUND:African American youth (aged 8-14 years) do not adhere to national dietary and physical activity guidelines. Nonadherence to these recommendations contributes to disproportionate rates of obesity compared with their white counterparts. Culturally tailored electronic health (eHealth) solutions are needed to communicate nutrition and physical activity messages that resonate with this target population. OBJECTIVE:This study aimed to identify the impact of exposure to a website hosting culturally tailored cartoons to inspire fruit and vegetable uptake and physical activity levels in African American mother-child dyads. METHODS:Statistical analysis included paired sample t tests to evaluate knowledge gains, self-efficacy, and readiness to change. Adapted items from Prochaska's Stages of Change toward the following 4 behaviors were assessed with pre- and posttest surveys: (1) fruit and vegetable selection on my plate, (2) meal preparation, (3) fruit and vegetable selection outside of home, and (4) physical activity. Open-ended comments on videos from mother-child dyads were used to determine user acceptance. Observations of repeated responses during content analysis informed coding and development of key themes. RESULTS:A final sample size of 93 mother-child dyads completed the study. Mothers reported significant improvement from precontemplation or contemplation stages to preparation or action stages for (1) fruit and vegetable selection on her plate (P=.03), (2) meal preparation for her family (P=.01), (3) fruit and vegetable selection outside the home (P<.001), and (4) physical activity (P<.001). Significant improvements were found in knowledge, stage of change, and self-efficacy for the 4 target behaviors of interest (P<.001). Children's open-ended commentary reported vicarious learning and positive character identification with brown-skinned cartoons exhibiting healthful food and exercise behaviors. Mothers commented on the lack of accessible produce in their neighborhoods not depicted in the cartoon videos. CONCLUSIONS:Culturally adapted cartoons that incorporate tailored preferences by African American families, such as race or demography, may help increase adherence to target health behaviors when developing eHealth behavior solutions.

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: 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: 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: 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: Being awake at night is associated with cognitive/affective dysregulation. Recently, it was found that nocturnal wakefulness is also a risk factor for completed suicide (self-harm). The present analysis examines whether nocturnal wakefulness is also a risk factor for violent crime (harm to others).
Method(s): Data were obtained from the National Archive of Criminal Justice Data and included rates of murder, violent sexual assault, robbery, aggravated assault, and simple assault across each hour of the day in 2016. These data were aggregated from law enforcement agencies in 38 states and Washington DC. Data were examined separately for adults (>18) and juveniles (<18). Standardized Incidence Ratios (SIRs) were computed to evaluate the proportion of violent crimes committed at each hour, relative to what would be expected given the proportion of the population awake at each hour (determined from normative values obtained from the American Time Use Survey).
Result(s): Without adjustment for likelihood of being awake, violent crime peaks at 7-10pm in juveniles and 2-4pm among adults. This pattern changed after adjustment, revealing increased likelihood at night. For adults, more violent crime than would be expected by chance was observed at 23:00 (SIR=1.56), 0:00 (SIR=2.44), 1:00 (SIR=2.97), and 2:00 (SIR=2.86), and also 15:00 (SIR=1.43). For juveniles, more violent crime than would be expected by chance was observed at 22:00 (SIR=1.84), 23:00 (SIR=3.14), 0:00 (SIR=5.71), 1:00 (SIR=8.69), 2:00 (SIR=10.33), 3:00 (SIR=8.04), 4:00 (SIR=2.87).
Conclusion(s): For adults, more violent crimes than expected occurred at night, peaking around 1-2am. For juveniles, there was also an elevated likelihood of crimes at night, peaking slightly later (2-3am). This is in contrast to unweighted crime statistics, which show peaks in the early afternoon in adults and early evening for juveniles. These data lend further credibility to the concept that there may be a biological vulnerability to cognitive/affective dysfunction when awake at night

OBJECTIVE:Sleep, which plays an important role in health and well-being, is socially patterned such that certain demographic groups have worse sleep health than others. One possible mechanism driving sleep disparities is social capital. The current study examines the association between social capital and self-reported sleep variables (eg, duration, insomnia symptoms, and daytime sleepiness) among a sample of 1007 participants from the Sleep Health and Activity, Diet and Environment Study (SHADES). METHODS:Logistic regressions were used to estimate whether the sleep variables were associated with social capital measures. All models control for age, sex, race/ethnicity (Non-Hispanic White, Black/African-American, Hispanic/Latino, Asian, and multicultural/other), income, and education (less than high school, high school graduate, some college, and college graduate). RESULTS:Lower likelihood of membership in groups was seen for long sleepers (>9hrs, p-value<0.05) and beliefs that neighbors rarely/never help each other was more likely among short sleepers (5-6hrs, p-value<0.05), relative to 7-8 h sleepers. A decreased sense of belonging was seen among short sleepers (5-6hrs, p-value<0.05). Decreased likelihood of trust was reported by those with moderate-severe insomnia (p-value<0.05). Similarly, neighborhood improvement efforts were less likely among individuals with moderate-to-severe insomnia (p-value<0.05). CONCLUSIONS:Results of our study show that short and long sleep duration, as well as insomnia, were inversely related to measures of social capital, such as group memberships and a sense of neighborhood belonging. Future research may explore the directionality of the relationship between social capital and sleep and perhaps consider future interventions to improve low social capital and/or poor sleep in community samples.

Introduction: We determined whether Obstructive Sleep Apnea (OSA) and beta-Amyloid Burden (Abeta) act additively or synergistically to promote conversion from cognitive normal (CN) to mild cognitive impairment (MCI) and from MCI to AD.
Method(s): In this longitudinal observational study, we examined CN (n=298) and MCI (n=418) older adults from the ADNI database (adni.loni.usc.edu). OSA was self-reported during a clinical interview. Brain Abeta was assessed using Florbetapir-PET imaging. The primary outcome of the analysis was conversion from CN to MCI (CN participants) and from MCI to AD (MCI participants). Participants were required to have a baseline and at least one follow-up clinical visit that identified their cognitive status. Logistic mixed-effects models with random intercept and slope were used to assess associations between OSA, Abeta, and risk of conversion from CN to MCI, and MCI to AD. All models included age at baseline, sex, APOE4 status, years of education, and their interactions with time.
Result(s): Of the 716 participants, 329 (46%) were women. The overall mean (SD) age was 74.7 (5.0) years, and the overall mean (SD) follow-up time was 5.5 (1.7) years (Range: 2.7 - 10.9 years). In CN participants at baseline, conversion to MCI was associated with both OSA (beta = 0.418; 95% CI, 0.133 to 0.703; P < .001) and higher Abeta-burden (beta = 0.554; 95% CI, 0.215 to 0.892; P < .001). The interaction of OSA and Abeta burden with time was significant (beta = 1.169, 95% CI, 0.776 to 1.562; P < .001), suggesting a synergistic effect. In MCI participants at baseline, conversion to AD was associated with both OSA (beta = 0.637; 95% CI, 0.291 to 0.982; P < .001) and higher Abeta-burden (beta = 1.061; 95% CI, 0.625 to 1.497; P < .001). The interaction of OSA and Abeta burden with time was significant (beta = 1.312, 95% CI, 0.952 to 1.671; P < .001), suggesting a synergistic effect.
Conclusion(s): In both CN and MCI elderly, Abeta modified the risk of progression to AD in OSA participants. OSA patients maybe more physiologically susceptible as Abeta load becomes increasingly abnormal

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: 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