Faculty Bibliography

Introduction: Social influence is a strong predictor of health behavior in college. This research extends these findings to college students' sleep, exploring how social influence is exerted on their sleep intentions. Exploring social factors that predict uptake of healthful sleep practices in college will illuminate directions for future sleep education programs on college campuses. Methods: Data were collected from a random sample of students at Cornell University (N = 157; mean age = 20 +/- 1.4 years; 78%, female; and 56%, white). Online surveys assessed self-reported sleep behavior, intention, social norm beliefs (e.g., "People important to me would be supportive of me sleeping 7 to 8 hours at night"), and sleep-related conversation (e.g., about healthful sleep practices, "Getting adequate sleep," and unhealthful practices, "Staying up late"). Regression analysis was used to assess relationships between social variables and intentions. Results: Insufficient sleep (< 7hrs) is common on weeknights (48.4% agreed with statement "I sleep 7 to 8 hours on most weeknights"), yet sufficient sleep (7-8hrs) is common on weekends (73.0% agreed with statement "I sleep 7 to 8 hours on most weekend nights"). Students repor ted intention to sleep (M = 1.1, range -3 to +3), and positive nor ms (M = 1.8, same range). Conversations about healthful sleep (M = 6.3, range 1 to 14) were less com mon than un healthfu l sleep (M = 7.2, same range). Regression analysis also showed significant relationships between conversation and social norm beliefs (healthful sleep conversation (b = .43, p < .01, r2 =), unhealthful sleep conversation (b = -.44, p < .01; r2 = .11). Analysis also showed a strong positive relationship between social norm and intention (b = .3, p < .001; r2 = .12). Conclusion: Our findings are consistent with previous research on relationships between social norm and sleep behavior. They extend this literature, documenting negative relationships between unhealthy sleep-related conversation and social norm beliefs. These suggest these undesirable conversations may be important to target in interventions

Introduction: Previous studies have indicated that race/ethnicity predicts insufficient sleep duration and that blacks bear a greater associated burden than individuals of other racial/ethnic group. We hypothesized that this disparity is likely due to greater poverty levels rather than race/ethnicity itself. Methods: Data for the present analysis came from the National Health Interview Survey [2004-2013], (N = 911,773). The survey applies a multi-stage sample survey of the resident civilian non-institutionalized US population. Respondents provided sociodemographic and physician-diagnosed chronic conditions. Self-reported sleep data was used to determine insufficient sleep status (< 6 hours/night) as well as poverty status. Poisson regression and logistic regression analyses were used to analyze the NHIS data. Results: A nalysis showe d that 54.7% of the sample were female; 77.8% were white and 15.6% black, (mean age = 46.68 +/- 17.38) years. Blacks consistently had a significantly higher prevalence of insufficient sleep compared to whites for all years included in the analysis (36.35% (p < .001) versus 27.4% (p < .001). Prevalence estimates of insufficient sleepers living below the poverty level was consistently higher than those living above poverty line (OR = 1.28, 95% CI = 1.25-1.32) (p < .001). After adjusting for race/ethnicity, poverty index was found to be a more significant indicator of likelihood of reporting for insufficient sleep than was race/ethnicity. Conclusion: Results support our hypothesis that poverty level was a stronger indicator of insufficient sleep than was race/ethnicity. Our findings confirm the importance for advocating for mitigation of the negative aspects of poverty such as poor housing and neighborhood quality and food deserts, all of which affecting sleep health, quality of life and eventually chronic disease risks

Introduction: Associations between place of birth and various health outcomes have been explored in recent studies. While sleep disturbance has been related to a number of negative health outcomes, few studies have examined the relationship between place of birth and sleep duration among individuals living in the United States. Methods: We examined data for 416,152 adult participants in the 2000-2013 National Health Interview Survey (NHIS), who provided self-reported hours of sleep and place of birth. NHIS data emanated from face-to-face interviews with trained interviewers from the U.S. Census Bureau. We explored associations between healthy sleep (7-8hrs.), referenced to unhealthy sleep (8 hrs.), and place of birth among US adults using multivariate logistic regression analysis, adjusting for effects of socio-demographic factors, health risks, and physician-diagnosed medical conditions. We used SPSS 20.0 to conduct descriptive and inferential analyses. Results: The mean age of the sample was 47.4 +/- 0.03 years; 56% were female. Of the respondents, 61.5% reported experiencing healthy sleep, 81.5% reported being born in the United States and 18.5% were foreign-born adults. Descriptive statistics revealed that Indian Subcontinent-bor n respondents (71.7%) were more likely to report healthy sleep compared to US-born respondents (OR = 1.53, 95% CI = 1.37-1.71, p < 0.001), whereas African-born respondents (43.5%) were least likely to report healthy sleep (OR = 0.78, 95% CI = 0.70-0.87, p < 0.001). Conclusion: These findings suggest that place of birth should be considered in the assessment of risk factors for unhealthy sleep. They add to the literature on sleep duration among racial and ethnic minorities in the U.S. This is useful when attempting to elucidate differences in sleep based on race/ethnicity and immigrant status

Introduction: Although obstructive sleep apnea (OSA) is known to occur more frequently among patients with metabolic syndrome (MS), the functional relationship between OSA and MS remains unclear. Therefore, we aimed to traverse the genetic-association between OSA and MS using A systems biology approach. Methods: Candidate genes for OSA and MS were extracted from Comparative Toxicogenomics Database (https://urldefense.proofpoint.com/v2/url?u=http- 3A__ctdbase.org_help_goDisease&d=CwIBAg&c=j5oPpO0eBH1iio48DtsedbOBGmuw5jHLjgvtN2r4ehE&r =KRXeNoRy5_8lkSwAJG5vjS1yT0aFSItfe494dmkdSVs&m=m3yKLpCYD6gzdb_fMnv9VyavoXGgk7duRWkr5 hBqb7Q&s=H-qi2fTXsbHCwk-LkFNxgIHjRhCo1YrIWyRu87IlMYs&e= ). Overlapping genes associated with OSA and MS were then assembled by Functional Enrichment analysis tool (FunRich), and their biological functions were identified using the Gene Ontology (GO) approach with the Protein ANalysis THrough Evolutionary Relationships (PANTHER) tool. GO uses structured controlled vocabularies (ontologies) to describe key characteristics of a gene product, including: (1) molecular function/activity, (2) biological processes it is involved in, and (3) cellular components where it is located. Results: Of the genes associated OSA (6,586) and MS (15,228), 5,322 (81%) OSA genes) overlapped between the conditions. GO analyses revealed that these genes were often associated with metabolic diseases (25.3%), inflammation/oxidative stress (13.6%), neurotransmitter regulation (12.8%), behavior/cognitive function (8.9%), and neurodegenerative diseases (4.8%). The remaining 34.7% were associated with other biological functions (i.e., cellular processes, homeostasis and reproduction, etc.). Conclusion: The vast majority of OSA-related genes were also associated with MS, supporting the practice of screening for OSA among individuals with MS. Future lifestyle intervention programs for chronic care management should also focus on sleep as an interventional component to attain maximum benefits

INTRODUCTION: Resistant hypertension (RHTN) is an important condition affecting 29% of the hypertensive population in the U.S., especially among blacks. Sleep disturbances, like obstructive sleep apnea, insomnia, and short sleep duration, are increasingly recognized as underlying modifiable factors for RHTN. We evaluated associations of RHTN with short sleep duration among blacks with metabolic syndrome. METHODS: Data from the Metabolic Syndrome Outcome Study (MetSO), a NIH-funded cohort study characterizing metabolic syndrome (MetS) among blacks were analyzed. MetS was defined according to criteria from the Adult Treatment Panel (ATP III). RHTN was defined according to guidelines from the American Heart Association. Short sleep was defined as self-reported sleep duration <7 hrs experienced during a 24-hour period. RESULTS: Analysis was based on 1,035 patients (mean age: 62+/-14years; female: 69.2%). Of the sample, 90.4% were overweight /obese; 61.4% had diabetes; 74.8% had dyslipidemia; 30.2% had a history of heart disease; and 48% were at high risk for obstructive sleep apnea. Overall, 92.6% reported physician-diagnosed hypertension (HTN) and 20.8% met criteria for RHTN. Analyses showed those with RHTN were more likely to be short sleepers (26.8% vs. 14.9%, p< 0.001). Based on logistic regression analysis, adjusting for effects of age, sex, and medical comorbidities, patients with metabolic syndrome and RHTN had increased odds of being short sleepers (OR = 1.95, 95% CI: 1.28-2.97, p = 0.002). CONCLUSION: Among blacks with metabolic syndrome, patients meeting criteria for resistant hypertension showed a twofold greater likelihood of being short sleepers, prompting the need for sleep screening in this vulnerable population.

The main characteristics of sleep-disordered breathing (SDB) are airflow limitation, chronic intermittent hypoxia, or apnea; which may lead to tissue hypoperfusion and recurrent arousal from sleep. These episodes of hypoxia or apnea can lead to tissue inflammation, and are causal factors of disturbed sleep in both men and women. Several lines of evidence suggest that sleep patterns differ along the lifespan in both male and female subjects, and this may result from the influence of female gonadotropic hormones on sleep. Compared to men, women have more sleep complaints, as women's sleep is not only influenced by gonadotropins, but also by conditions related to these hormones, such as pregnancy. It is therefore not surprising that sleep disturbances are seen during menopause, too. Factors that may play a role in this type of SDB in women include vasomotor symptoms, changing reproductive hormone levels, circadian rhythm abnormalities, mood disorders, coexistent medical conditions, and lifestyle factors.

The etiology of premenstrual syndrome (PMS) is unknown; it may be due to the normal effect of hormones during the menstrual cycle as it occurs in the late luteal phase of the menstrual cycle.PMS affects women of childbearing age and remits with the onset of menstruation. The menstrual phase is known to influence stage 2 and REM sleep in women, irrespective of premenstrual dysphoric disorder (PMDD). Women with PMDD showed a decreased response to melatonin in their luteal phase as compared to the follicular phase of the menstrual cycle. However, melatonin duration or timing of offset in the morning has not been reported to correlate with the mood. Rather, improvement in mood-related symptoms of PMDD has been found to be influenced by sleep deprivation, be it sleep restrictions in early or late night. Sleep disturbance and decreased melatonin secretions due to hormonal fluctuations during the luteal phase of the menstrual cycle could explain the sleep complaints of PMDD.

INTRODUCTION: Adherence to smoking cessation treatment is generally low, especially among socio-economically disadvantaged groups including individuals experiencing homelessness and those with mental illnesses. Despite the high smoking rates in homeless populations (~70%) no study to date has systematically examined predictors of adherence to nicotine replacement therapy (NRT) in this population. OBJECTIVE: The aim of this secondary analysis was to identify predictors of adherence to NRT in a smoking cessation trial conducted among homeless smokers. METHODS: Secondary analysis of data from a randomized controlled trial enrolling 430 persons who were homeless and current cigarette smokers. Participants were assigned to one of the two study conditions to enhance smoking cessation: Motivational Interviewing (MI; 6 sessions of MI + 8 weeks of NRT) or Standard Care (Brief advice to quit+ 8 weeks of NRT). The primary outcome for the current analysis was adherence to NRT at end of treatment (8 weeks following randomization). Adherence was defined as a total score of zero on a modified Morisky adherence scale). Demographic and baseline psychosocial, tobacco-related, and substance abuse measures were compared between those who did and did not adhere to NRT. RESULTS: After adjusting for confounders, smokers who were depressed at baseline (OR=0.58, 95% CI, 0.38-0.87, p=0.01), had lower confidence to quit (OR=1.10, 95% CI, 1.01-1.19, p=0.04), were less motivated to adhere (OR=1.04, 95% CI, 1.00-1.07, p=0.04), and were less likely to be adherent to NRT. Further, age of initial smoking was positively associated with adherence status (OR= 0.83, 95% CI, 0.69-0.99, p=0.04). CONCLUSION: These results suggest that smoking cessation programs conducted in this population may target increased adherence to NRT by addressing both depression and motivation to quit. TRIAL REGISTRATION: clinicaltrials.gov: NCT00786149.