Faculty Bibliography

OBJECTIVES: To evaluate the effect of a practice-based, culturally appropriate patient education intervention on blood pressure (BP) and treatment adherence among patients of African origin with uncontrolled hypertension. METHODS: Cluster randomised trial involving four Dutch primary care centres and 146 patients (intervention n = 75, control n = 71), who met the following inclusion criteria: self-identified Surinamese or Ghanaian; >/=20 years; treated for hypertension; SBP>/=140 mmHg. All patients received usual hypertension care. The intervention-group was also offered three nurse-led, culturally appropriate hypertension education sessions. BP was assessed with Omron 705-IT and treatment adherence with lifestyle- and medication adherence scales. RESULTS: 139 patients (95%) completed the study (intervention n = 71, control n = 68). Baseline characteristics were largely similar for both groups. At six months, we observed a SBP reduction of >/=10 mmHg -primary outcome- in 48% of the intervention group and 43% of the control group. When adjusted for pre-specified covariates age, sex, hypertension duration, education, baseline measurement and clustering effect, the between-group difference was not significant (OR; 0.42; 95% CI: 0.11 to 1.54; P = 0.19). At six months, the mean SBP/DBD had dropped by 10/5.7 (SD 14.3/9.2)mmHg in the intervention group and by 6.3/1.7 (SD 13.4/8.6)mmHg in the control group. After adjustment, between-group differences in SBP and DBP reduction were -1.69 mmHg (95% CI: -6.01 to 2.62, P = 0.44) and -3.01 mmHg (-5.73 to -0.30, P = 0.03) in favour of the intervention group. Mean scores for adherence to lifestyle recommendations increased in the intervention group, but decreased in the control group. Mean medication adherence scores improved slightly in both groups. After adjustment, the between-group difference for adherence to lifestyle recommendations was 0.34 (0.12 to 0.55; P = 0.003). For medication adherence it was -0.09 (-0.65 to 0.46; P = 0.74). CONCLUSION: This intervention led to significant improvements in DBP and adherence to lifestyle recommendations, supporting the need for culturally appropriate hypertension care. TRIAL REGISTRATION: Controlled-Trials.com ISRCTN35675524.

BACKGROUND: Excessive daytime sleepiness (EDS) often occurs as a result of insufficient sleep, sleep apnea, illicit substance use, and other medical and psychiatric conditions. This study tested the hypothesis that blacks exhibiting EDS would have poorer self-reported adherence to hypertensive medication using cross-sectional data from the Counseling African-Americans to Control Hypertension (CAATCH) trial. METHODS: A total of 1,058 hypertensive blacks (average age 57+/-12 years) participated in CAATCH, a randomized controlled trial evaluating the effectiveness of a multilevel intervention for participants who receive care from community health centers in New York City. Data analyzed in this study included baseline sociodemographics, medical history, EDS, and medication adherence. We used the Epworth Sleepiness Scale, with a cutoff score of >/=10, to define EDS. Medication adherence was measured using an abbreviated Morisky Medication Adherence scale, with a score >0 indicating nonadherence. RESULTS: Of the sample, 71% were female, 72% received at least a high school education, 51% reported a history of smoking, and 33% had a history of alcohol consumption. Overall, 27% of the participants exhibited EDS, and 44% of those who exhibited EDS were classified as adherent to prescribed antihypertensive medications. Multivariable logistic regression analysis, adjusting for effects of age, body mass index, sex, education, and smoking and drinking history indicated that participants who exhibited EDS were more than twice as likely to be nonadherent (odds ratio 2.28, 95% confidence interval 1.42-3.67, P<0.001). CONCLUSION: Analysis of the CAATCH data showed a high prevalence of EDS among hypertensive blacks. EDS is a significant predictor of nonadherence to prescribed medications for hypertension. These findings point to a modifiable variable that can be targeted in future interventions focusing on medication adherence.

Introduction: Inadequate sleep duration is an important public health burden in the United States. However, there is a paucity of information on the relationships between psychological health and inadequate sleep. Our study examined the relationships between emotional distress and inadequate sleep. Methods: Data from the 2009 National Health Interview Survey (NHIS), N = 27,731 participants 18 years and older, were analyzed to investigate the associations of emotional distress with inadequate sleep duration, adjusting for socio-demographic factors, health risks, and chronic diseases. We deine inadequate sleep as less than 7 or greater than 8 hours sleep durations; compared to healthy sleep (7-8 hours). We measured emotional distress, based on Kessler's 6 scale, which assesses the frequency of feeling sad, nervous, restless, hopeless, worthless, and burdened over a 30-day period. Responses were used to generate a score ranging from 0 to 24. Scores of > 13 are considered likely to indicate serious mental illness. Results: Of the sample, 52% were female, 80% were white, 12% black, and 8% other; 30% hold a HS diploma and 31% reported a family income below 31K. Analysis also showed that 10.9% reported emotional distress and 37.2% reported inadequate sleep. Results of our logistic regression analysis revealed that individuals with emotional distress had 57% greater odd of reporting inadequate sleep (OR = 1.5795% C.I. 1.54, 1.61, p < 0.001); the model adjusted for age, sex, race/ethnicity, marital status, education, combined family income, body mass index, history of alcohol consumption, smoking status, and chronic diseases including, arthritis, hypertension, diabetes, cancer, coronary heart disease and heart conditions. Conclusion: Our indings showed that emotional distress, an important proxy for psychological health, was the strongest predictor of inadequate sleep. Other factors associated with inadequate sleep include demographic (age, education, sex, race/ethnicity, combined family income), health!

Introduction: Studies have shown that decreased sleep duration and later sleep timing (midpoint of sleep) are associated with an increased body mass index (BMI). However, previous research has not determined which of these two sleep parameters is a better predictor of BMI. This study sought to determine whether sleep timing is a better predictor of the likelihood of being overweight/obese than insuficient sleep. Methods: Volunteers consisted of 459 postmenopausal women (mean age = 67.71 + 7.87 years) participating in the Women's Health Initiative study. Of the sample, 72% were non-Hispanic white; 14% Hispanic; 9% black; and 5% other. Volunteers wore an actigraph (Actillume) (ACT) and kept a seven-day sleep diary (SD) to estimate habitual sleep durations. ACT data were scored using a validated algorithm (Cole-Kripke) provided by the Actillume manufacturer. Subjective and actigraphic data were averaged over a period of 7 days to obtain an index of both objective and subjective sleep duration. Sleep timing was derived by calculating the midpoint of reported bedtimes and rise times. Results: Analysis revealed that 20.6% of the volunteers experienced short sleep (< 6 hours) based on subjective data; 47.7% experienced short sleep based on actigraphic estimates. The average sleep timing occured at 03:08. Of the sample, 62% were categorized as overweight or obese. Multivariate-adjusted linear regression showed that only ACTderived sleep duration was signiicantly associated with being overweight/ obese (OR = 2.46 (95% CI: 1.39-4.35, p < .001). There were no statistically signiicant associations between subjective sleep duration or sleep timing with overweight/obesity. The model adjusted for age, race, physical activity and sleep medications. Conclusion: Results suggest that insuficient sleep as measured by actigraphy is the single most important predictor of the likelihood of being overweight/obese among older women. Unlike previous research, sleep timing was not signiicantly associated with being overw!

Introduction: Many risk factors have been implicated in the pathophysiology of obstructive sleep apnea (OSA). Recent evidence suggests that medical risk factors, such as uncontrolled/high blood pressure (BP), high cholesterol, triglycerides, high body mass index, diabetes, and dyslipidemia (all indicators of metabolic syndrome) are highly comorbid with OSA. However, data on the relationships between these risk factors and OSA among blacks with metabolic syndrome are lacking. Methods: Data for the present study were collected from 340 participants from the Metabolic Syndrome Outcome (MetSO) study, a NIHfunded cohort study of 1,035 blacks with metabolic syndrome (mean age = 62 + 13 years, 69% female, and 43% with annual family income < $10K). During initial interviews, patients provided sociodemographic, health risks, and history of chronic diseases. Patients with a score > 6 on the Apnea Risk Evaluation System (ARES) were considered at high OSA risk. Logistic regression analyses were employed to investigate whether metabolic syndrome indicators, particularly uncontrolled blood pressure, increased the odds of OSA. Results: Of the sample, 77.1% was at risk for OSA and 16.8% had uncontrolled BP. Analysis also showed 60.4% were diabetic, 8.9% had a stroke history, 74.3% had dyslipidemia, 91.1% were either overweight or obese and 30.9% had heart disease. Mean systolic BP was 134.8 + 18.4; diastolic BP was 75.6 + 11.9; LDL cholesterol was 105.6 + 36.9; HDL cholesterol was 48.0 + 17.3; triglycerides was 135.8 + 81.2; glucose was 138.4 + 68.3; and HbA1c was 7.93 + 1.63. Logistic regression analysis showed that uncontrolled BP independently increased the odds of OSA risk (OR = 1.94, 95% CI = 1.12-3.32, p < 0.01). Conclusion: Our indings suggest that uncontrolled BP was associated with a twofold greater risk of OSA in blacks. The clinical implication of this inding is that blacks with metabolic syndrome and who have uncontrolled BP should be screened for the presence of OSA

Introduction: Identiication of risk factors for obstructive sleep apnea (OSA) is important to enable comprehensive intervention to reduce associated cardiovascular (CV) morbidity and mortality. The Metabolic Syndrome Outcome Study provides a unique opportunity to assess the presence of these factors among blacks, a group that is at high risk for adverse CV outcomes. The purpose of this study was to investigate risk of OSA among blacks with metabolic syndrome Methods: The present study utilized data from the Metabolic Syndrome Outcome (MetSO) study, an NIH-funded cohort study of blacks with metabolic syndrome. A total of 1,035 patients provided data for the present analysis. Patients were diagnosed with metabolic syndrome using criteria articulated in the joint interim statement for harmonizing the metabolic syndrome. OSA risks for all patients were assessed with the Apnea Risk Evaluation System (ARES). Those with an ARES score > 6 were considered at high OSA, based on previous validation studies. Data was coded and analyzed by an experienced statistician using SPSS 19.0. Results: The average age of the sample was 62 + 14 years (range: 20- 97); 71% were female. Of the sample, 93% were diagnosed with hypertension; 61%, diabetes; 72%, dyslipidemia; 90% were overweight/ obese; 33% had a history of heart disease and 10% had a stroke. ARES data indicated that 48% were at high OSA risk. Using multivariate logistic regression analysis, adjusting for age and gender, we observed that obesity was the strongest predictor of OSA risk (OR = 1.59, 95%CI = 1.24-2.04, p < 0.0001). This inding remained signiicant even after adjustment for blood pressure, LDL, HDL, and glucose levels (OR = 1.44, 95%CI = 1.11-1.86, p < 0.001). Conclusion: Of all of the markers of the metabolic syndrome, obesity is the most important predictor of increased risk of OSA among blacks. Our inding is consistent with previous research regarding the obesityapnea link

Introduction: Sleep among blacks with metabolic syndrome is not well characterized. Our study examined sleep characteristics of black men and women with a diagnosis of metabolic syndrome. Methods: The present study utilized data from the Metabolic Syndrome Outcome Study (MetSO), an NIH-funded cohort study of blacks with metabolic syndrome (N = 1,035). Patients [mean age = 62 + 14 years; female = 71%] were diagnosed with metabolic syndrome using criteria articulated in the joint interim statement for harmonizing the metabolic syndrome. They provided self-reported data including sleep habits and insomnia symptoms. They were administered the Apnea Risk Evaluation System (ARES) to ascertain risk of obstructive sleep apnea (OSA). Patients with a score of > 6 on the ARES scale were considered at high OSA risk, based on validation studies. Results: Of the sample, 60% were diagnosed with diabetes; stroke, 10%; heart disease, 31%; hypertension, 93%; overweight/obese, 90%. Based on ARES data, 48% were at risk for OSA. Analysis also showed that 53% reported feeling sleepy during the day, and 10% had an insomnia diagnosis. Speciic insomnia symptoms included dificulty falling asleep (38%), dificulty maintaining sleep (42%), early morning awakening (46%); 53% reported daytime naps, and 12% used sleep medication. Prevalence of short sleepers (< 6 hrs) and long sleepers (> 9 hrs), referenced to healthy sleepers (7-8 hrs), was 70% and 19%, respectively. Based on chi-squared analysis, there was signiicant difference between males and females in regard to reported daytime sleepiness (41% vs. 56%; x2 = 7.736, p < 0.05), dificulty falling asleep (34% vs. 41%; x2 = 5.252, p < 0.05), and daytime naps (60% vs. 50%, x2 = 8.338, p < 0.05). No other signiicant gender differences were observed. Conclusion: Our indings suggest that a large number of blacks with metabolic syndrome experience insomnia symptoms, use sleep aids, and are both short and long sleepers. These sleep-related problems are associated with a myriad of !

Introduction: Although the relationship between sleep duration and body mass index (BMI) has been well-characterized, the underlying mechanisms have not. Understanding which factors explain this relationship would provide important insights in developing effective public health interventions to reduce associated cardiometabolic risks. The present study investigated 5 potential mediators of the relationship between sleep duration and BMI. Methods: Data from the 2009 Behavioral Risk Factor Surveillance System (BRFSS) was used in our analysis. BRFSS is a CDC-sponsored project representing the world's largest ongoing, state-speciic, randomized telephone survey that measures behavioral risk factors among U.S. adults [mean age = 56 + 16 years, female = 63%]. Analysis focused on interviews conducted in six representative states, soliciting sociodemographic, medical, sleep, and health-risk data, yielding observations for n = 35,895 respondents. A bootstrapping method was employed to generate conidence intervals (BCCI) ascertaining total and unique mediation across all 5 hypothesized mediators simultaneously (using 1,000 bootstrap samples) of the sleep duration and BMI relationship. The hypothesized mediators included: alcohol use, diet, physical activity, general health status, and life satisfaction. Age and sex were adjusted in all tested models. Results: Analysis showed that for each additional hour of sleep BMI decreases by 0.15 unit. Evidence of unique mediation was noted for: physical activity (BCCI = 0.0017 to 0.0102; SE = 0.0022), diet (BCCI =-0.0138 to-0.0052; SE = 0.0022), and general health status (BCCI =-0.0379 to-0.0079; SE = 0.0423). However, there was no evidence of unique mediation for: alcohol use (BCCI =-0.0013 to 0.0019; SE = 0.0008) or life satisfaction (BCCI =-0.0057 to 0.0057; SE = 0.0028). Conclusion: These indings suggest that the sleep and BMI relationship may be partially mediated by physical activity, diet, and general health. This is consistent with previous hypotheses regard!