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183


RECRUITING, TRAINING, AND IMPLEMENTING SLEEP HEALTH EDUCATORS IN COMMUNITY-BASED RESEARCH TO IMPROVE SLEEP HEALTH [Meeting Abstract]

Aird, C.; Seixas, A.; Moore, J.; Nunes, J.; Gyamfi, L.; Garcia, J.; Blanc, J.; Williams, N.; Zizi, F.; Jean-Louis, G.
ISI:000554588501407
ISSN: 0161-8105
CID: 4562532

UTILIZATION OF THE ARES TO PREDICT OSA AMONG BLACKS USING HOME-BASED WATCHPAT RECORDING [Meeting Abstract]

Rogers, A.; Seixas, A.; Moore, J.; Zizi, F.; Williams, S.; Gyamfi, L.; Pichardo, Y.; Jean-Louis, G.
ISI:000554588500621
ISSN: 0161-8105
CID: 4562312

SLEEPFECT TRACKER: A CROSSPLATFORM MOBILE RESEARCHKIT APP FOR SLEEP SELF-MANAGEMENT [Meeting Abstract]

Menon, P.; Seixas, A.; Pathan, Z.; Suhail, M.; Jean-Louis, G.; Ayoub, S.; Naqeeb, B.; Wani, B.; Mishra, S.; Khan, S.
ISI:000554588501431
ISSN: 0161-8105
CID: 4562552

Increased Metabolic Burden Among Blacks: A Putative Mechanism for  Disparate COVID-19 Outcomes

Jean-Louis, Girardin; Turner, Arlener D; Jin, Peng; Liu, Mengling; Boutin-Foster, Carla; McFarlane, Samy I; Seixas, Azizi
Mounting evidence shows a disproportionate COVID-19 burden among Blacks. Early findings indicate pre-existing metabolic burden (eg, obesity, hypertension and diabetes) as key drivers of COVID-19 severity. Since Blacks exhibit higher prevalence of metabolic burden, we examined the influence of metabolic syndrome on disparate COVID-19 burden. We analyzed data from a NIH-funded study to characterize metabolic burden among Blacks in New York (Metabolic Syndrome Outcome Study). Patients (n=1035) were recruited from outpatient clinics, where clinical and self-report data were obtained. The vast majority of the sample was overweight/obese (90%); diagnosed with hypertension (93%); dyslipidemia (72%); diabetes (61%); and nearly half of them were at risk for sleep apnea (48%). Older Blacks (age≥65 years) were characterized by higher levels of metabolic burden and co-morbidities (eg, heart disease, cancer). In multivariate-adjusted regression analyses, age was a significant (p≤.001) independent predictor of hypertension (OR=1.06; 95% CI: 1.04-1.09), diabetes (OR=1.03; 95% CI: 1.02-1.04), and dyslipidemia (OR=0.98; 95% CI: 0.97-0.99), but not obesity. Our study demonstrates an overwhelmingly high prevalence of the metabolic risk factors related to COVID-19 among Blacks in New York, highlighting disparate metabolic burden among Blacks as a possible mechanism conferring the greater burden of COVID-19 infection and mortality represented in published data.
PMCID:7537835
PMID: 33061507
ISSN: 1178-7007
CID: 4637172

Obstructive Sleep Apnea and Longitudinal Alzheimer's disease biomarker changes

Bubu, Omonigho M; Pirraglia, Elizabeth; Andrade, Andreia G; Sharma, Ram A; Gimenez-Badia, Sandra; Umasabor-Bubu, Ogie Q; Hogan, Megan M; Shim, Amanda M; Mukhtar, Fahad; Sharma, Nidhi; Mbah, Alfred K; Seixas, Azizi A; Kam, Korey; Zizi, Ferdinand; Borenstein, Amy R; Mortimer, James A; Kip, Kevin E; Morgan, David; Rosenzweig, Ivana; Ayappa, Indu; Rapoport, David M; Jean-Louis, Girardin; Varga, Andrew W; Osorio, Ricardo S
STUDY OBJECTIVES/OBJECTIVE:To determine the effect of self-reported clinical diagnosis of Obstructive Sleep Apnea (OSA) on longitudinal changes in brain amyloid-PET and CSF-biomarkers (Aβ42, T-tau and P-tau) in cognitively normal (NL), mild cognitive impairment (MCI) and Alzheimer's Disease (AD) elderly. METHODS:Longitudinal study with mean follow-up time of 2.52±0.51 years. Data was obtained from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. Participants included 516 NL, 798 MCI and 325 AD elderly. Main Outcomes were annual rate-of-change in brain amyloid-burden (i.e. longitudinal increases in florbetapir-PET uptake or decreases in CSF-Aβ42 levels); and tau-protein aggregation (i.e. longitudinal increases in CSF total-tau (T-tau) and phosphorylated-tau (P-tau)). Adjusted multi-level mixed effects linear regression models with randomly varying intercepts and slopes was used to test whether the rate-of-biomarker-change differed between participants with and without OSA. RESULTS:In NL and MCI groups, OSA+ subjects experienced faster annual increase in florbetapir uptake (B=.06, 95% CI .02, .11 and B=.08, 95% CI .05, .12 respectively) and decrease in CSF-Aβ42 levels (B=-2.71, 95% CI -3.11, -2.35 and B=-2.62, 95% CI -3.23, -2.03, respectively); as well as increases in CSF T-tau (B=3.68, 95% CI 3.31, 4.07 and B=2.21, 95% CI 1.58, 2.86, respectively) and P-tau (B=1.221, 95% CI, 1.02, 1.42 and, B=1.74, 95% CI 1.22, 2.27, respectively); compared to OSA- participants. No significant variations in the biomarker changes over time were seen in the AD group. CONCLUSIONS:In both NL and MCI, elderly, clinical interventions aimed to treat OSA are needed to test if OSA treatment may affect the progression of cognitive impairment due to AD.
PMID: 30794315
ISSN: 1550-9109
CID: 3686712

Interactive associations of obstructive sleep apnea and B-amyloid burden among clinically normal and mild cognitive impairment elderly individuals: An examination of conversion risk [Meeting Abstract]

Bubu, O M; Umasabor-Bubu, O Q; Andrade, A; Chung, A; Parekh, A; Kam, K; Mukhtar, F; Seixas, A; Varga, A; Rapoport, D; Ayappa, I; Forester, T; Jean-Louis, G; Osorio, R S
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
EMBASE:627913961
ISSN: 1550-9109
CID: 3926022

Analyzing 4-year estimates of sleep duration and quality among 2 million users of a sleep tracker in New York City [Meeting Abstract]

Seixas, A; Robbins, R; Affouf, M; Beaugris, L; Donley, T; Moore, J; Richards, S; Jean-Louis, G
Introduction: Population estimates for sleep duration and quality are inconsistent because they rely on self-report and smaller samples using objective data. Tracking and wearable devices may provide more accurate estimates of sleep duration and quality. In this study, we investigated estimates of sleep duration and quality among 2 million users of a mobile sleep application in an urban city in the United States (U.S.).
Method(s): We examined sleep duration and quality from 2,194,897 users of SleepCycle, a popular sleep tracking app. over a four-year period (2015 to 2018). In this analysis, we specifically explored differences in sleep duration and quality by demographic factors, including age and sex. We utilized graphical matrix representations of data (heat maps) and geospatial analyses to compare sleep duration (in hours) and sleep quality (based on a composite score amalgamating time in bed, deep-sleep time, sleep consistency, and amount of times fully awake), considering potential effects of day of the week and seasonality.
Result(s): Among SleepCycle users, 45.6% (n=1,001,335) were female. The average age of the sample was 31.0 years. The mean sleep duration of the total sample was 7.11 hours; women slept longer than did men (M=7.27 hours vs. M=7.00 hours, p<.001). Increasing age tended to be associated with longer sleep duration and better sleep quality. Results also showed sleep duration was longer on weekends (M=7.19 hours), compared to weeknights (M=7.09 hours). Sleep duration was longest (M=7.18 hours) during the winter, but shortest during the summer (M=7.11 hours). Sleep quality was highest (M=72.75) during the winter, but lowest during the summer (M=71.99).
Conclusion(s): Our findings from big data are consistent with previously reported estimates of sleep duration and quality. Sleep duration varied by age, sex, day of the week, and season. Future studies should determine whether estimates of sleep duration and quality are affected by environmental factors such as geographic location
EMBASE:627852668
ISSN: 1550-9109
CID: 3926492

Community-based participatory research methods in sleep medicine: Lessons learned [Meeting Abstract]

Chung, A; Williams, N; Robbins, R; Seixas, A; Rogers, A; Chanko, N; Chung, D; Jean-Louis, G
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
EMBASE:627852600
ISSN: 1550-9109
CID: 3925362

Interactive associations of obstructive sleep apnea and hypertension with longitudinal changes in beta-amyloid burden and cognitive decline in clinically normal elderly individuals [Meeting Abstract]

Bubu, O M; Andrade, A; Parekh, A; Kam, K; Mukhtar, F; Donley, T; Seixas, A A; Varga, A; Ayappa, I; Rapoport, D; Forester, T; Jean-Louis, G; Osorio, R S
Introduction: We determined whether the co-occurrence of OSA and hypertension interact synergistically to promote beta-Amyloid burden and cognitive decline in clinically normal older adults Methods: Prospective longitudinal study utilizing NYU cohort of community-dwelling cognitively-normal elderly, with baseline and at least one follow-up of CSF-Abeta42 (measured using ELISA), and neuropsychological visits. OSA was defined using AHI4%. Hypertension diagnosis was according to AHA-guidelines. Cognitive variables assessed included Logic-2, Animal-Fluency [AF], Vegetable-Fluency [VF]), Boston-Naming-Test [BNT], Digit-Symbol-Substitution-Test [DSST], Trails Making Test-A and B [TMT-A and B]). Linear mixed-effects models with random intercept and slope were used to assess associations between OSA, hypertension, and longitudinal changes in CSF-Abeta and cognition, controlling for age-at-baseline, sex, APOE4-status, years-of-education, and their interactions with time.
Result(s): Of the 98 participants, 63 (64.3%) were women. The mean (SD) age was 69.6 (7.3) years and follow-up time was 2.46 (0.64) years. OSA and hypertension were each associated with faster rate-of-change in CSF-Abeta42 (beta = -3.11; 95%CI, -3.71, -2.51; and beta= -2.82, 95% CI -3.29, -2.35, P < .01 for both respectively). The interaction of OSA and hypertension with time was significant (beta= -1.28, 95% CI -1.78 to -0.78, P < .01) suggesting a synergistic effect. No significant associations were seen between annual-changes in CSF-Abeta42 and cognitive-decline. However, faster decline in VF, and DSST were associated with OSA (beta = -0.054; 95%CI, -0.094, -0.013; P = .02; beta = -0.058; 95%CI, -0.084, -0.033; P < .05 for both respectively), and with hypertension (beta = -0.048; 95%CI, -0.079, -0.017; P = .04; beta = -0.078; 95%CI, -0.098, -0.057; P = .002; respectively). The interaction of OSA and hypertension with time was significant for both VF and DSST (beta = -0.033, 95%CI, -0.048, -0.018; P < .001 and beta = -0.040, 95%CI, -0.064, -0.016; P < .001, respectively), suggesting a synergistic effect.
Conclusion(s): In cognitive-normal elderly OSA individuals, vascular risk may complement AD-biomarkers in assessing risk of prospective cognitive-decline in preclinical AD
EMBASE:627852102
ISSN: 1550-9109
CID: 3926462

What makes people want to make changes to their sleep? assessment of perceived risks of insufficient sleep as a predictor of intent to improve sleep [Meeting Abstract]

Khader, W; Fernandez, F; Seixas, A; Knowlden, A; Ellis, J; Williams, N; Hale, L; Perlis, M; Jean-Louis, G; Killgore, W D S; Alfonso-Miller, P; Grandner, M A
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
EMBASE:627914814
ISSN: 1550-9109
CID: 3926042