Faculty Bibliography

BACKGROUND: Biological rhythmicity has been extensively studied in animals for many decades. Although temporal patterns of physical activity have been identified in humans, no large-scale, multi-national study has been published, and no comparison has been attempted of the ubiquity of activity rhythms at different time scales (such as daily, weekly, monthly, and annual). METHODS: Using individually worn actigraphy devices, physical activity of 2,328 individuals from five different countries (adults of African descent from Ghana, South Africa, Jamaica, Seychelles, and the United States) was measured for seven consecutive days at different times of the year. RESULTS: Analysis for rhythmic patterns identified daily rhythmicity of physical activity in all five of the represented nationalities. Weekly rhythmicity was found in some, but not all, of the nationalities. No significant evidence of lunar rhythmicity or seasonal rhythmicity was found in any of the groups. CONCLUSIONS: These findings extend previous small-scale observations of daily rhythmicity to a large cohort of individuals from around the world. The findings also confirm the existence of modest weekly rhythmicity but not lunar or seasonal rhythmicity in human activity. These differences in rhythm strength have implications for the management of health hazards of rhythm misalignment. Key messages Analysis of the pattern of physical activity of 2,328 individuals from five countries revealed strong daily rhythmicity in all five countries, moderate weekly rhythmicity in some countries, and no lunar rhythmicity or seasonal rhythmicity in any of the countries.

BACKGROUND: Increased legalization of marijuana has resulted in renewed interest in its effects on body weight and cardiometabolic risk. Conflicting data exist regarding marijuana effects on body weight, waist circumference as well as lipid profiles, blood pressure and cardiovascular disease. Furthermore, there is a dearth of data available on this effect in the black population. OBJECTIVE: To assess the metabolic profile and cardiovascular risk factors as well as body weight and waist circumference among urban black marijuana users. METHODS: A cross sectional study design involving 100 patients seen in a Family Practice clinic at University hospital of Brooklyn, NY, USA, over a period of 3 months from January 2014 to March 2014. Participants were administered a questionnaire regarding marijuana use, and other associated behaviors. Socio-demographic, laboratory, and clinical data were collected. We report measures of central tendencies, and dispersion for continuous variables and the frequency of distribution for categorical variables. RESULTS: Of the 100 patients surveyed, 57% were females. The mean (+/-SEM) age of the entire cohort was 46.3 years+/-1.5; range, 19-78 years. The mean body mass index (BMI) was 29.6 kg/m2+/-0.73; SBP=128.0 mmHg+/-1.69; DBP=76.1 mmHg+/-1.17. Current marijuana users had the lowest waist circumference compared to former or never users respectively (32.9+/-0.66 vs. 35.9+/-0.88 vs. 33.4+/-0.74), p<0.01. Diastolic blood pressure in mmHg was significantly higher among former marijuana users compared to current or never users, (80.0+/-2.1 vs. 73.3+/-2.3 vs. 73.4+/-1.6), p<0.01. Current marijuana users showed a tendency (not statistically significant) towards lower total cholesterol, Triglycerides (TG), High Density Lipoprotein (HDL)-cholesterol, Low Density Lipoprotein (LDL)-cholesterol, body mass index (BMI) and systolic blood pressure, compared to former users or never users. CONCLUSION: Current marijuana use is associated with significantly lower waist circumference, compared to former users and never users. Except for diastolic BP that was significantly lower among current users, other metabolic parameters showed tendency towards favorable profile. Further studies are needed to characterize the metabolic effects and to elucidate mechanisms of actions of marijuana in view of its rapid rate of utilization in the USA and around the world.

BACKGROUND: Exposure to the natural environment may improve health behaviors and mental health outcomes such as increased levels of physical activity and lower levels of depression associated with sleep quality. Little is known about the relationship between insufficient sleep and the natural environment. PURPOSE: To determine whether exposure to attributes of the natural environment (e.g., greenspace) attenuates the likelihood of reporting insufficient sleep among US adults. METHODS: Multiple logistic regression models were used to explore the association between self-reported days of insufficient sleep (in the past 30days) and access to the natural environment in a multi-ethnic, nationally representative sample (n=255,171) of US adults >/=18years of age enrolled in the 2010 Behavioral Risk Factor Surveillance System. RESULTS: Using 1-to-6days of insufficient sleep as the referent group for all analyses, lower odds of exposure to natural amenities were observed for individuals reporting 21-to-29days (OR=0.843, 95% confidence interval (CI)=0.747, 0.951) of insufficient sleep. In stratified analyses, statistically significant lower odds of exposure to natural amenities were found among men reporting 7-to-13-days (OR=0.911, 95% CI=0.857, 0.968), 21-to-29-days (OR=0.838, 95% CI=0.759, 0.924), and 30-days (OR=0.860, 95% CI=0.784, 0.943) of insufficient sleep. Greenspace access was also protective against insufficient sleep for men and individuals aged 65+. CONCLUSIONS: In a representative sample of US adults, access to the natural environment attenuated the likelihood of reporting insufficient sleep, particularly among men. Additional studies are needed to examine the impact of natural environment exposure on sleep insufficiency across various socio-demographic groups.

Insufficient sleep is associated with cardiometabolic disease and poor health. However, few studies have assessed its determinants in a nationally representative sample. Data from the 2009 behavioral risk factor surveillance system were used (N = 323,047 adults). Insufficient sleep was assessed as insufficient rest/sleep over 30 days. This was evaluated relative to sociodemographics (age, sex, race/ethnicity, marital status, region), socioeconomics (education, income, employment, insurance), health behaviors (diet, exercise, smoking, alcohol), and health/functioning (emotional support, BMI, mental/physical health). Overall, insufficient sleep was associated with being female, White or Black/African-American, unemployed, without health insurance, and not married; decreased age, income, education, physical activity; worse diet and overall health; and increased household size, alcohol, and smoking. These factors should be considered as risk factors for insufficient sleep.

BACKGROUND: Cancer and its treatments can deleteriously affect memory. Cardiac function and insomnia can exacerbate memory problems. OBJECTIVE: To examine the relationships among cardiovascular disease, insomnia, and self-reported memory problems (SRMP) in adult-onset cancer survivors. METHODS: We included data from participants (41-64 year-old) of the 2007-2008 National Health and Nutrition Examination Survey, a nationally representative probability sample of the civilian, non-institutionalized population of the US. We excluded participants with brain cancer/stroke history since these conditions are expected to cause cognitive problems. Using binary logistic regression, we determined the prevalence of SRMP relative to cardiac problems and insomnia by weighting our results proportionally. We adjusted for predictors of memory problems: age, sex, race, education and general health. RESULTS: The sample included 2289 adults (49% females), 9% with a cancer history. The results pertain only to cancer survivors. Those with insomnia were 16 times as likely to have SRMP. Only insomnia symptoms (OR, 15.74; 95% CI, 1.73-143.30; p < 0.01) significantly predicted SRMP, uniquely explaining 12% of the variance. Insomnia accounted for 18.8% of the association between cardiac issues and SRMP, demonstrating mediation (Sobel p < 0.05). The large CI is a consequence of analyzing a sub-group of a subpopulation. Among participants without a cancer history, cardiovascular disease and insomnia were not associated with SRMP (p > 0.05). LIMITATIONS: We could not determine severity and time-related changes in SRMP. CONCLUSION: Likelihood of SRMP was higher in cancer survivors with a history of cardiovascular disease and insomnia symptoms. Future studies are needed to delineate the cardiac-insomnia-memory interrelationships.

Daily rhythmicity in the locomotor activity of laboratory animals has been studied in great detail for many decades, but the daily pattern of locomotor activity has not received as much attention in humans. We collected waist-worn accelerometer data from more than 2000 individuals from five countries differing in socioeconomic development and conducted a detailed analysis of human locomotor activity. Body mass index (BMI) was computed from height and weight. Individual activity records lasting 7 days were subjected to cosinor analysis to determine the parameters of the daily activity rhythm: mesor (mean level), amplitude (half the range of excursion), acrophase (time of the peak) and robustness (rhythm strength). The activity records of all individual participants exhibited statistically significant 24-h rhythmicity, with activity increasing noticeably a few hours after sunrise and dropping off around the time of sunset, with a peak at 1:42 pm on average. The acrophase of the daily rhythm was comparable in men and women in each country but varied by as much as 3 h from country to country. Quantification of the socioeconomic stages of the five countries yielded suggestive evidence that more developed countries have more obese residents, who are less active, and who are active later in the day than residents from less developed countries. These results provide a detailed characterization of the daily activity pattern of individual human beings and reveal similarities and differences among people from five countries differing in socioeconomic development.

This review introduces a conceptual framework for understanding stakeholder management (ShM) in the clinical and community-based research environment. In recent years, an evolution in practice has occurred in many applicants for public and non-governmental funding of public health research in hospital settings. Community health research projects are inherently complex, have sought to involve patients and other stakeholders in the center of the research process. Substantial evidence has now been provided that stakeholder involvement is essential for management effectiveness in clinical research. Feedback from stakeholders has critical value for research managers inasmuch as it alerts them to the social, environmental, and ethical implications of research activities. Additionally, those who are directly affected by program development and clinical research, the patients, their families, and others, almost universally have a strong motivation to be involved in the planning and execution of new program changes. The current overview introduces a conceptual framework for ShM in the clinical research environment and offers practical suggestions for fostering meaningful stakeholder engagement. The fifth edition of PMBOK((R)) of the Project Management Institute, has served as basis for many of the suggested guidelines that are put forward in this article.

Introduction: Previous research has found that long sleep is associated with a myriad of negative outcomes. These studies have been epidemiological, with large samples but without validated measures of sleep-related outcomes. Few studies have examined subjective sleepiness and fatigue levels in the context of long sleep among older adults. The present study examined differences between average and long sleeping older adults on measures of sleepiness and fatigue. We hypothesized that both sleepiness and fatigue would be higher among the long-sleeping compared with the average-sleeping older adults. Methods: Participants were 41 older adults (31 female; mean age 65.0, range 60-77). Exclusion criteria included sleep medication use, excessive napping, severe medical disorders, > 30 mins TIB intentionally awake, TIB < 6 hrs, 7.25-8 hrs, or > 9.25 hrs, and OSA (AHI > 15) as assessed by ambulatory peripheral arterial tonometry. Participants completed two weeks of sleep diaries and actigraphy and were classified as average sleepers (median 2-week TIB: 6-7.25 h, N = 22) or long sleepers (median 2-week TIB: 8-9.25 h, N = 19). Participants then completed the Epworth Sleepiness Scale (ESS) and Multidimensional Fatigue Symptom Inventory Short Form (MFSI-SF). Results: On the ESS, average sleepers indicated greater sleepiness (6.2 +/- 3.4) than long sleepers (3.7 +/- 2.8), p < 0.02, d = 0.80. There were no significant group differences on the MFSI-SF, with average sleepers reporting similar levels of fatigue (14.95 +/- 11.7) as long sleepers (12.26 +/- 13.3), p = 0.46. Conclusion: Lower levels of sleepiness among long sleepers is inconsistent with previous research. That we found a difference in sleepiness, but not in fatigue suggests that this may not simply be due to measurement effects. Since all participants were healthy, longer sleep time may leave these long sleepers better rested. Future research should include larger sample sizes and objective measures of sleepiness to clarify the differences between these groups

Introduction: Previous research suggests that too little or too much sleep time in adults can have negative consequences on mortality, health, mood and cognitive outcomes. Most of these studies have measured sleep subjectively. In the present study we explored how average or long sleep measured objectively with actigraphy in older adults is associated with cognitive function. We hypothesized that long sleepers would have worse cognitive performance than average sleepers. Methods: As part of a larger longitudinal study, we measured total sleep time among 72 healthy older adults (mean age = 65.01, range = 60-77 years old, 63.9% were female) using actigraphy and sleep diaries. They were classified as average (6-7.25 h in bed) or long sleepers (8-9.25 h in bed). At baseline, we measured set shifting, visual attention and inhibition among 69 participants using the Stroop Task and the Trail Making Test. Results: Stroop Task: N = 69 participants completed this task at baseline. Completion time significantly differed (p < 0.05) between average (N = 39, 103.40 +/- 25.90 seconds) and long sleepers (N = 30, 117.61 +/- 30.74 seconds) with a moderate corresponding effect size (Cohen's d = 0.50). We found no significant difference (p > 0.5) between accuracy of average (4.74 +/- 6.63 errors) and long sleepers (3.73 +/- 5.52 errors). Trail Making Test: N = 64 participants completed this task at baseline. We found no significant difference (p > 0.9) in completion time between average (N = 35, 80.25 +/- 39.88 seconds) and long sleepers (N = 29, 79.87 +/- 30.77 seconds) and no significant difference (p > 0.65) between accuracy of average (0.74 +/- 0.98 errors) and long sleepers (0.86 +/- 1.19 errors). Conclusion: We found that longer sleep among older adults was associated with slower completion time on a task that requires inhibition of an automatic response, the Stroop Task, but that there were no significant differences on a task that requires set shifting and visual attention, the Trail Making Test