Faculty Bibliography

Background/UNASSIGNED:Growing evidence suggests that cancer and diabetes may share common risk factors such as age, race/ethnicity, obesity, insulin resistance, sedentary lifestyle, smoking, and alcohol consumption. However, little is known about how habitual sleep duration (a known cardiometabolic risk factor) may affect the relationship between cancer and diabetes. The aim of this study was to investigate whether sleep duration moderated the relationship between history of cancer and diabetes. Methods/UNASSIGNED:Data were extracted from the National Health Interview Survey dataset from 2004 to 2013 containing demographics, chronic diseases, and sleep duration (N=236,406). Data were analyzed to assess the moderating effect of short and long sleep durations on cancer and diabetes mellitus. Results/UNASSIGNED:<0.05). Conclusion/UNASSIGNED:Our findings indicate that for cancer survivors, short sleep was associated with higher self-reported diabetes and long sleep duration may act as a buffer against diabetes mellitus, as the likelihood of self-reported diabetes was lower among cancer survivors who reported long sleep duration. Impact/UNASSIGNED:Findings from the current study have clinical and public health implications. Clinically, comprehensive sleep assessments and sleep interventions to improve sleep are needed for cancer survivors who have comorbid diabetes. Our findings can also spur public health reform to make sleep an important component of standard cancer survivorship care, as it reduces other chronic disease like diabetes.

Introduction: Physical activity (PA) and sleep are associated with cerebrovascular disease and events like stroke. Though the interrelationships between PA, sleep, and other stroke risk factors have been studied, we are unclear about the associations of different types, frequency and duration of PA, sleep behavioral patterns (short, average and long sleep durations), within the context of stroke-related clinical, behavioral, and socio-demographic risk factors. The current study utilized Bayesian Belief Network analysis (BBN), a type of machine learning analysis, to develop profiles of physical activity (duration, intensity, and frequency) and sleep duration associated with or no history of stroke, given the influence of multiple stroke predictors and correlates. Such a model allowed us to develop a predictive classification model of stroke which can be used in post-stroke risk stratification and developing targeted stroke rehabilitation care based on an individual's profile. Method: Analysis was based on the 2004-2013 National Health Interview Survey (n = 288,888). Bayesian BBN was used to model the omnidirectional relationships of sleep duration and physical activity to history of stroke. Demographic, behavioral, health/medical, and psychosocial factors were considered as well as sleep duration [defined as short < 7 h. and long ≥ 9 h, referenced to healthy sleep (7-8 h)], and intensity (moderate and vigorous) and frequency (times/week) of physical activity. Results: Of the sample, 48.1% were ≤ 45 years; 55.7% female; 77.4% were White; 15.9%, Black/African American; and 45.3% reported an annual income < $35 K. Overall, the model had a precision index of 95.84%. We found that adults who reported 31-60 min of vigorous physical activity six times for the week and average sleep duration (7-8 h) had the lowest stroke prevalence. Of the 36 sleep (short, average, and long sleep) and physical activity profiles we tested, 30 profiles had a self-reported stroke prevalence lower than the US national average of approximately 3.07%. Women, compared to men with the same sleep and physical activity profile, appeared to have higher self-reported stroke prevalence. We also report age differences across three groups 18-45, 46-65, and 66+. Conclusion: Our findings indicate that several profiles of sleep duration and physical activity are associated with low prevalence of self-reported stroke and that there may be sex differences. Overall, our findings indicate that more than 10 min of moderate or vigorous physical activity, about 5-6 times per week and 7-8 h of sleep is associated with lower self-reported stroke prevalence. Results from the current study could lead to more tailored and personalized behavioral secondary stroke prevention strategies.

Introduction/UNASSIGNED:Sleep disturbance is a major public health issue and is comorbid with the cluster of conditions associated with metabolic syndrome (MetS). Our study explored the presence of sleep disturbance, including daytime sleepiness, the risk for obstructive sleep apnea (OSA), and insomnia symptoms, in a cohort of adult Black men and women with MetS. Methods/UNASSIGNED:Patients (n=1,013) from the Metabolic Syndrome Outcome Study (MetSO), 2009-2012, met criteria for MetS based on guidelines from the National Cholesterol Education Program's Adult Treatment Panel and provided sociodemographic data and the Apnea Risk Evaluation System (ARES) questionnaire to assess OSA risk, sleep characteristics, and physician-reported diagnosis of a sleep disorder. Results/UNASSIGNED:Prevalence of the components of MetS included: diabetes (60%); obesity (67%); hypertension (94%); and dyslipidemia (74%). Based on the ARES, 49% were at risk for OSA. Of all study patients, slightly more than half (53%) reported feeling sleepy during the day, and 10% reported an insomnia diagnosis. The most common sleep disturbance reported by 46% of the patients was early morning awakenings (EMA). This was closely followed by 42% who reported difficulty staying asleep (DSA) and 38% reporting difficulty falling asleep (DFA). Seventy percent reported short sleep (≤ 6 hours), whereas a minority (19%) reported long sleep (≥ 9 hours). Only 12% used sleep aids. Women, compared with men, reported greater daytime sleepiness, greater DFA, and greater DSA (57% vs 45%; 41% vs 32.4%; 45% vs 37%), respectively. Conclusion/UNASSIGNED:Blacks with MetS reported insomnia symptoms and insomnia disorder, use of sleep aids, feeling sleepy during the day, and inadequate sleep durations. The presence of these sleep characteristics suggests that patients with MetS should be referred for further sleep assessment.

Obesity is a major global health issue, and its prevalence is increasing. Obesity is associated with much comorbidity such as obstructive sleep apnea (OSA), type 2 diabetes mellitus (T2DM), and cardiovascular diseases (CVD). Obesity is also one of the major causative factors of OSA, and OSA itself can promote the onset of after T2DM because hypoxic episodes decrease insulin sensitivity, and activation of the sympathetic pathway leads to the release of inflammatory markers associated with insulin resistance. Continuous Positive Airway Pressure (CPAP) can be used to ameliorate both conditions, as CPAP decreased hypoxia episodes and increases insulin sensitivity and improves glucose metabolism. Weight-loss strategies play an important role in improving OSA, T2DM, and other associated comorbidities. Lifestyle modification of diet and exercise, medications or bariatric surgery should be considered weight loss. The purpose of this review is to describe the relationship between obesity, OSA, and T2DM.

Sleep plays a pivotal role in both physical and mental health. Sleep quality can be affected by many socio demographic factors, such as race and/or ethnicity, as well as socio economic status (SES). Chronic sleep deprivation is associated with unhealthy behaviors such as alcohol abuse and also places individuals at risk for chronic diseases including obesity, cardiovasculardisease (CVD), depression, and/or anxiety. This review explores the common socio demographic factors and SES that can lead to sleep disturbances. Among these factors are shift work, poor dietary habits, smoking and alcohol abuse. Such factors need to be considered by health care providers in the clinical assessment and management plans of patients with sleep disorders.

STUDY OBJECTIVES/OBJECTIVE:Sleep apnea is associated with hypertension, and treatment may improve outcomes. We examine national burden of sleep apnea, rates of sleep apnea treatment, and whether racial/ethnic disparities exist among patients with hypertension. METHODS:Data from the National Ambulatory Medical Care Survey/National Hospital Ambulatory Medical Care Survey (NAMCS/NHAMCS), 2005-2012, were analyzed (N = 417,950). We identified hypertension patient visits where sleep apnea diagnosis or complaint was recorded. Primary outcome measures were sleep study, medication, or behavioral therapy (diet, weight loss, or exercise counseling). We used multivariate logistic regression to examine treatment by demographic/clinical factors. RESULTS:Among patients with hypertension, sleep apnea was identified in 11.2-per-1,000 visits. Overall, patients with hypertension and a sleep disorder were referred for sleep study in 14.4% of visits, prescribed sleep medication in 11.2% of visits, and offered behavioral therapy in 34.8% of visits. Adjusted analyses show behavioral therapy more likely to be provided to obese patients than normal/overweight (OR = 4.96, 95%CI[2.93-8.38]), but less likely to be provided to smokers than nonsmokers (OR = 0.54, 95%CI[0.32-0.93]). Non-Hispanic blacks were less likely to receive medications than non-Hispanic whites (OR = 0.19, 95% CI[0.06-0.65]). CONCLUSIONS:In the U.S., sleep apnea were observed in a small proportion of hypertension visits, a population at high-risk for the disorder. One explanation for the low prevalence of sleep apnea observed in this patient population at high risk for the disorder is under-diagnosis of sleep related breathing disorders. Behavioral therapy was underutilized, and non-Hispanic Blacks were less likely to receive medications than non-Hispanic Whites.

BACKGROUND:Mobile apps hold promise for serving as a lifestyle intervention in public health to promote wellness and attenuate chronic conditions, yet little is known about how individuals with chronic illness use or perceive mobile apps. OBJECTIVE:The objective of this study was to explore behaviors and perceptions about mobile phone-based apps for health among individuals with chronic conditions. METHODS:Data were collected from a national cross-sectional survey of 1604 mobile phone users in the United States that assessed mHealth use, beliefs, and preferences. This study examined health app use, reason for download, and perceived efficacy by chronic condition. RESULTS:Among participants, having between 1 and 5 apps was reported by 38.9% (314/807) of respondents without a condition and by 6.6% (24/364) of respondents with hypertension. Use of health apps was reported 2 times or more per day by 21.3% (172/807) of respondents without a condition, 2.7% (10/364) with hypertension, 13.1% (26/198) with obesity, 12.3% (20/163) with diabetes, 12.0% (32/267) with depression, and 16.6% (53/319) with high cholesterol. Results of the logistic regression did not indicate a significant difference in health app download between individuals with and without chronic conditions (P>.05). Compared with individuals with poor health, health app download was more likely among those with self-reported very good health (odds ratio [OR] 3.80, 95% CI 2.38-6.09, P<.001) and excellent health (OR 4.77, 95% CI 2.70-8.42, P<.001). Similarly, compared with individuals who report never or rarely engaging in physical activity, health app download was more likely among those who report exercise 1 day per week (OR 2.47, 95% CI 1.6-3.83, P<.001), 2 days per week (OR 4.77, 95% CI 3.27-6.94, P<.001), 3 to 4 days per week (OR 5.00, 95% CI 3.52-7.10, P<.001), and 5 to 7 days per week (OR 4.64, 95% CI 3.11-6.92, P<.001). All logistic regression results controlled for age, sex, and race or ethnicity. CONCLUSIONS:Results from this study suggest that individuals with poor self-reported health and low rates of physical activity, arguably those who stand to benefit most from health apps, were least likely to report download and use these health tools.

Previous studies have identified an association between socioeconomic status and sleep health. While some research has studied this association among sexual minority groups, including men who have sex with men (MSM), they exclusively focused on US-based populations. The interplay between the two in shaping sleep health has not been previously examined on populations residing outside the US. This study considers both determinants, by investigating whether financial hardship is associated with sleep health among a sample of MSM in Paris, France. Broadcast advertisements were placed on a popular geosocial-networking smartphone application for MSM to direct users in Paris to a web-based survey measuring financial hardship and five dimensions of sleep health as well as socio-demographic characteristics. Modified Poisson models with robust error variance were computed to estimate risk ratios (RRs) and 95% confidence intervals (CI) for the associations between financial hardship and the following self-reported outcomes: 1) poor sleep quality, 2) short sleep duration; and 3) sleep problems. In total, 580 respondents completed the survey. In this sample, both financial hardship and poor sleep health were common - 45.5% reported that it was extremely, very, or somewhat difficult for them to meet their monthly payments on bills (referred to as "high financial hardship") and 30.1% rated their sleep as fairly bad or very bad (referred to as "poor sleep quality"). Multivariate models revealed that, compared to participants who reported low financial hardship, those who reported high financial hardship were more likely to report poor sleep quality (aRR: 1.35, 95% CI: 1.04, 1.77), to report problems falling asleep (aRR: 1.23, 95% CI: 1.02, 1.49), and to report problems staying awake in the daytime (aRR: 3.12, 95% CI: 1.83, 5.31). Future research should investigate whether this relationship is causal and determine whether interventions to reduce financial hardships could promote sleep health among MSM.

OBJECTIVES: We analysed association between short sleep duration and prevalence of cardiovascular disease (CVD) in a multiethnic population living in the Netherlands, and the contribution of short sleep to the observed ethnic differences in the prevalence of CVD, independent of CVD risk factors. METHODS: 20 730 participants (aged 18-71 years) of the HELIUS (Healthy Life in an Urban Setting) Study were investigated. Self-reported sleep duration was classified as: short (<7 hours/night) and healthy (7-9 hours/night). Prevalence of CVD was assessed using the Rose Questionnaire on angina pectoris, intermittent claudication and possible myocardial infarction. Association of short sleep duration with prevalent CVD and the contribution of short sleep to the observed ethnic differences in the prevalence of CVD were analysed using adjusted prevalence ratio(s) (PRs) with 95% CI. RESULTS: Results indicate that short sleep was associated with CVD among all ethnic groups with PRs ranging from 1.41 (95% CI 1.21 to 1.65) in Moroccans to 1.62 (95% CI 1.20 to 2.18) in Dutch after adjustment for age, sex and conventional CVD risk factors. The independent contributions of short sleep (in percentage) to ethnic differences in CVD compared with Dutch were 10%, 15%, 15%, 5% and 5% in South-Asian Surinamese, African-Surinamese, Ghanaian, Turkish and Moroccan, respectively. CONCLUSION: Short sleep contributed to ethnic differences in CVD independent of well-known CVD risk factors particularly in Surinamese and Ghanaian groups. Reducing sleep deprivation may be a relevant entry point for reducing increased CVD risks among the various ethnic minority groups.