Type 2 diabetes and health-related quality of life among older Medicare beneficiaries: The mediating role of sleep

OBJECTIVE

To examine mediating effects of sleep quality and duration on the association between T2D and QoL among Medicare beneficiaries 65+.

METHODS

Data from the Medicare Health Outcome Survey (2015-2020) were used. The outcome was QoL (physical and mental health component-summary scores [PCS and MCS]) measured by the Veterans-Rand-12. The main predictor was diagnosed T2D. Mediators were sleep duration and sleep quality. The effect modifier was race/ethnicity. Structural Equation Modeling was used to estimate moderated-mediating effects of sleep quality and duration across race/ethnicity.

RESULTS

Of the 746,400 Medicare beneficiaries, 26.7% had T2D, and mean age was 76 years (SD ± 6.9). Mean PCS score was 40 (SD ± 12.2), and mean MCS score was 54.0 (SD ± 10.2). Associations of T2D with PCS and MCS were negative and significant. For all racial/ethnic groups, those with T2D reported lower PCS. For White, Black, Asian, and Hispanic beneficiaries only, those with T2D reported lower MCS. The negative impact of T2D on PCS and MCS was mediated through sleep quality, especially very bad sleep quality.

CONCLUSION

Improving sleep may lead to improvement in QoL in elderly adults with T2D.

Strengths, weaknesses, opportunities and threats of using AI-enabled technology in sleep medicine: a commentary

Over the past few years, artificial intelligence (AI) has emerged as a powerful tool used to efficiently automate several tasks across multiple domains. Sleep medicine is perfectly positioned to leverage this tool due to the wealth of physiological signals obtained through sleep studies or sleep tracking devices and abundance of accessible clinical data through electronic medical records. However, caution must be applied when utilizing AI, due to intrinsic challenges associated with novel technology. The Artificial Intelligence in Sleep Medicine committee of the American Academy of Sleep Medicine (AASM) reviews advancements in AI within the sleep medicine field. In this article, the Artificial Intelligence in Sleep Medicine committee members provide a commentary on the scope of AI technology in sleep medicine. The commentary identifies three pivotal areas in sleep medicine which can benefit from AI technologies: clinical care, lifestyle management and population health management. This article provides a detailed analysis of the strengths, weaknesses, opportunities, and threats associated with using AI enabled technologies in each pivotal area. Finally, the article broadly reviews barriers and challenges associated with using AI enabled technologies and offers possible solutions.

A Comparison of Patients' and Neurologists' Assessments of their Teleneurology Encounter: A Cross-Sectional Analysis

Background and Objectives: To better understand patients' and neurologists' assessments of their experiences regarding effectiveness of teleneurology encounters. Methods: Following an audio-video telehealth visit, neurologists asked patients to participate in a survey-based research study about the encounter, and then, the neurologists also recorded their own evaluations. Data were analyzed using standard quantitative and qualitative techniques for dichotomous and ordered-category survey responses in this cross-sectional analysis. Results: The study included unique encounters between 187 patients and 11 general neurologists. The mean patient age was 49 ± 17.5 years. Two thirds of the patients (66.8%, 125/187) were female. One third (33.2%; 62) were patients new to the NYU Langone Health neurology practices. The most common patient chief complaints were headache (69/187, 36.9%), focal and generalized numbness or tingling (21, 11.2%), memory difficulty (15, 8%), spine-related symptoms (12, 6.4%), and vertigo (11, 5.9%). Most patients (94.7%, 177/187) reported that the teleneurology encounter satisfied their needs. Patients and their neurologists agreed that the experience was effective in 91% (162/178) of encounters, regardless of whether the visit was for a new or established patient visit. Discussion: More than 90% of new and established patients and their neurologists agreed that teleneurology encounters were effective despite some limitations of the examination, the occasional need for patient assistance, and technical difficulties. Our results provide further evidence to justify and to expand the clinical use of teleneurology.

The associations between instructional approach, sleep characteristics and adolescent mental health: Lessons from the COVID-19 pandemic

OBJECTIVES

To test whether adolescents' mental health during the COVID-19 pandemic is associated with the combination of their instructional approach(es) and their sleep patterns.

DESIGN

Cross-sectional.

SETTING

Adolescents were recruited through social media outlets in October and November 2020 to complete an online survey.

PARTICIPANTS

Participants were 4442 geographically and racially diverse, community-dwelling students (grades 6-12, 51% female, 36% non-White, 87% high schoolers).

MEASUREMENTS

Participants completed items from the PROMIS Pediatric Depressive Symptoms and Anxiety scales. Participants reported their instructional approach(es), bedtimes, and wake times for each day in the past week. Participants were categorized into five combined instructional approach groups. Average sleep opportunity was calculated as the average time between bedtime and waketime. Social jetlag was calculated as the difference between the average sleep midpoint preceding non-scheduled and scheduled days.

RESULTS

Emotional distress was elevated in this sample, with a large proportion of adolescents reporting moderate-severe (T-score ≥ 65) levels of depressive symptoms (49%) and anxiety (28%). There were significant differences between instructional approach groups, such that adolescents attending all schooldays in-person reported the lowest depressive symptom and anxiety T-scores (P < .001, ηp2 = .012), but also the shortest sleep opportunity (P < .001, ηp2 = .077) and greatest social jetlag (P < .001, ηp2 = .037) of all groups. Adolescents attending school in person, with sufficient sleep opportunity (≥8-9 hours/night) and limited social jetlag (<2 hours) had significantly lower depressive (ηp2 = .014) and anxiety (ηp2 = .008) T-scores than other adolescents.

CONCLUSIONS

Prioritizing in-person education and promoting healthy sleep patterns (more sleep opportunity, more consistent sleep schedules) may help bolster adolescent mental health.

Precision Recruitment and Engagement of Individuals at Risk for Diabetes and Hypertension in Clinical Trials (PREDHICT): A Randomized Trial for an E-Persuasive Mobile Application to Inform Decision Making about Clinical Trials

The primary objective of this randomized trial was to test the effectiveness of the PREDHiCT digital application, which provides educational and supportive navigation to increase willingness to participate in a future clinical trial. The second objective was to test whether PREDHiCT increased clinical trial literacy or enhanced psychological facilitators of clinical trial participation, such as altruism. To test these two objectives, we conducted a 1-month remote decentralized trial with 100 participants who either have a personal or family history of cardiometabolic health conditions, such as hypertension, diabetes, and obesity. Results indicated significant changes in altruism (mean: -2.94 vs. 0.83; p-value = 0.011) and clinical trial literacy (mean: 0.55 vs. 2.59; p-value = 0.001) from baseline to 1-month follow-up between the control and intervention groups. Additionally, participants exposed to personalized clinical trial navigation had greater clinical trial literacy at the end of the study relative to the individuals in the control arm of the study. Our findings indicate that tailored education, navigation, and access to clinical trials-three unique features of our PREDHiCT app-increased altruism and clinical trial literacy but not willingness to participate in a trial.

Association of Birthplace for Sleep Duration, Sleep Quality, and Sleep Disorder Symptoms, at the US-Mexico Border

OBJECTIVES

The present study investigated the roles birthplace and acculturation play in sleep estimates among Hispanic/Latino population at the US-Mexico border.

MEASURES

Data were collected in 2016, from N = 100 adults of Mexican descent from the city of Nogales, AZ, at the US-Mexico border. Sleep was assessed with the Pittsburgh Sleep Quality Index (PSQI), Insomnia Severity Index categorized as none, mild, moderate, and severe, and Multivariable Apnea Prediction Index (MAP) categorized as never, infrequently, and frequently. Acculturation was measured with the Acculturation Rating Scale for Mexican-Americans II (ARSMA-II).

RESULTS

The sample consisted of majority Mexican-born (66%, vs. born in the USA 38.2%). Being born in the USA was associated with 55 fewer minutes of nighttime sleep (p = .011), and 1.65 greater PSQI score (p = .031). Compared to no symptoms, being born in the USA was associated with greater likelihood of severe difficulty falling asleep (OR = 8.3, p = .030) and severe difficulty staying asleep (OR = 11.2, p = .050), as well as decreased likelihood of breathing pauses during sleep (OR = 0.18, P = .020). These relationships remained significant after Mexican acculturation was entered in these models. However, greater Anglo acculturation appears to mediate one fewer hour of sleep per night, poorer sleep quality, and reporting of severe difficulty falling asleep and staying asleep.

CONCLUSIONS

Among individuals of Mexican descent, being born in the USA (vs Mexico) is associated with about 1 hour less sleep per night, worse sleep quality, more insomnia symptoms, and less mild sleep apnea symptoms. These relationships are influenced by acculturation, primarily the degree of Anglo rather than the degree of Mexican acculturation.

Smart sleep: what to consider when adopting AI-enabled solutions in clinical practice of sleep medicine

Since the publication of its 2020 position statement on artificial intelligence (AI) in sleep medicine by the American Academy of Sleep Medicine, there has been a tremendous expansion of AI-related software and hardware options for sleep clinicians. To help clinicians understand the current state of AI and sleep medicine, and to further enable these solutions to be adopted into clinical practice, a discussion panel was conducted on June 7, 2022, at the Associated Professional Sleep Societies Sleep Conference in Charlotte, North Carolina. The article is a summary of key discussion points from this session, including aspects of considerations for the clinician in evaluating AI-enabled solutions including but not limited to what steps might be taken both by the Food and Drug Administration and clinicians to protect patients, logistical issues, technical challenges, billing and compliance considerations, education and training considerations, and other unique challenges specific to AI-enabled solutions. Our summary of this session is meant to support clinicians in efforts to assist in the clinical care of patients with sleep disorders utilizing AI-enabled solutions.

CITATION

Bandyopadhyay A, Bae C, Cheng H, et al. Smart sleep: what to consider when adopting AI-enabled solutions in clinical practice of sleep medicine. J Clin Sleep Med. 2023;19(10):1823-1833.

Ethical and Policy Implications of Racial and Ethnic Healthcare Disparities in Sleep Health

Despite efforts in recent years, including in policy and research, to address health disparities in the United States, many of those disparities continue to fester in marginalized racial/ethnic populations. Understanding sleep health disparities is critical in understanding the health and wellness of these groups. Using obstructive sleep apnea (OSA) in Black populations as a focus, this paper presents the role of race and ethnicity in the clinical understanding of sleep health-related issues by medical practitioners and the implications of the lack of clear policies or best practices to guide medical practitioners' attempts to meet sleep-related needs of marginalized racial/ethnic populations. Furthermore, the knowledge gap may be further complicated by the poor understanding and integration of existing evidence with the many, complex, sleep-associated co-morbidities. Policymaking in this area ought to be based on the ethical implications of disparate sleep-related health outcomes by race and ethnicity. So, we conclude by offering recommendations for developing ethically sound policies for addressing sleep problems in marginalized racial and ethnic populations.

Strategies to Engage Blacks in Sleep Medicine: Lessons Learned from Three Studies Applying Community-Based Participatory Research Principles

Introduction

Awareness, assessment and treatment of sleep apnea are disproportionately lower among Blacks, compared to other racial/ethnic groups. To address this health disparity gap, communication strategies that connect Blacks to OSA education, detection and treatment adherence interventions are needed. Strategies that engage individuals through communication technologies, community-level social network support, and medical providers in clinical settings are also needed. We present lessons learned from three studies that offer these solutions using a community-engaged research model: The Metabolic Syndrome Outcome Study (MetSO), Peer-enhanced Education to Reduce Sleep Ethnic Disparities (PEERS-ED), and Tailored Approach to Sleep Health Education (TASHE), to capture program effectiveness and lessons learned from project successes and failures.

Methods

The methods of OSA community-based programs included the application of an OSA community-engaged research model. This model served as a strategic guideline for effective interventions to engage communities in research and ensure cultural appropriateness in OSA interventions. Focus groups, in-depth interviews and community steering committee meetings were conducted with various stakeholders. Delphi surveys were used to identify high priority diseases and conditions. Community barriers and needs were identified through iterative combinations of surveys and focus group meetings. Stakeholder groups participated in all aspects of our studies, including the development, dissemination and implementation phases, reflecting a bi-directional decision-making process that ensures the interests of both parties were considered. The MetSO, PEERS-ED and TASHE studies were reviewed to understand the effectiveness of the programs and to evaluate lessons learned.

Results

MetSO, PEERS-ED and TASHE interventions revealed that community-engaged strategies are successful in enrolling Black populations into clinical trials. The study teams reached nearly 3,000 Blacks at risk of OSA and screened about 2,000 people in sleep apnea studies in New York City. Sleep brochures were distributed to over 10,000 people. Lessons learned from MetSO, PEERS-ED and TASHE interventions revealed that building relationships, establishing trust, identifying a study champion, learning to adjust and providing participant incentives are key strategic elements for successful recruitment and retention of Blacks participations in clinical trials.

Conclusion

Strategic application of community-oriented frameworks ensures active community engagement throughout the research process, allowing for greater enrollment of Blacks in clinical studies as well as increased OSA awareness, diagnosis, and treatment.

Exploring the combined effects of sleep apnea and APOE-e4 on biomarkers of Alzheimer's disease

Objective

We determined the interactive associations of apolipoprotein e4 (APOE-e4), and obstructive sleep apnea (OSA) on biomarkers of Alzheimer's disease and examined for racial/ethnic differences of this association.

Methods

We used data from the National Alzheimer's Coordinating Center Uniform Dataset (NACC UDS). All participants undergo annual observations, including demographic survey, battery of neuropsychological tests, blood draw (with genotyping), and a clinical evaluation with medical and cognitive/dementia status assessment, while a subset of participants have cerebrospinal fluid (CSF) biomarkers and neuroimaging data. Biomarkers of AD were characterized as the presence of abnormally low amyloid in CSF, via validated Aβ42 cut off protocols, and total segmented hippocampal volume, and volume of white matter hyper intensities (WMH). While clinical markers (to preview cognitive relationships) were characterized via the Montreal Cognitive Assessment (MOCA).

Results

Biomarker and clinical marker data were derived from 1,387 participants at baseline (mean age = 69.73 ± 8.32; 58.6% female; 13.7% Black/African American), 18.4% of the sample had sleep apnea, and 37.9% were APOE-e4 carriers. Our results confirmed previous reports that OSA and APOE-e4 were independently associated with AD through abnormal levels of amyloid (F (1,306) = 4.27; p = 0.040; F (1,285) = 60.88; p < 0.000, respectively), WMH volume (F (1,306) = 4.27; p = 0.040; F (1,285) = 60.88; p < 0.000, respectively), and MOCA scores (F (1,306) = 4.27; p = 0.040; F (1,285) = 60.88; p < 0.000, respectively). No significant interaction between OSA and APOE-e4 relative to amyloid emerged, however, race stratified analyses indicated the interaction of OSA and APOE-e4 and was significantly associated with WMH and hippocampal volume in Black/African American, but not white participants.

Conclusion

OSA and APOE-e4 are interactively associated with WHM in Black/African Americans. This interaction may partially explicate increased levels of risk in this population.

EXPLORING THE EFFICACY OF MOCA SCORE CORRECTIONS IN REDUCING THE INFLUENCE OF RACE/ETHNICITY

As studies have highlighted significant differences in test score distributions between ethnicities, we chose to examine if the MoCA corrections for education curb racial differences. Therefore, we use data from the NIA Alzheimer's Disease Research Center (ADRC) program to explore the efficacy of score corrections in reducing the influence of race/ethnicity. This study utilized the NACC dataset to analyze data covering UDS visits from September 2005 to February 2021. Participants included in the analyses (n= 11987, 64.9% women, 12.3 % Black/African American, mean age 73□9.460; 16□4.98 years of education) were all cognitively normal. The analyses uses the Montreal Cognitive Assessment (MoCA) with and without correction for education (addition of one point for less than 12 years of education), via cut off score derived cognitive status categories. A 2x3 contingency table revealed a statistically significant association between participants’ race (black vs white) and performance on the uncorrected MoCA, X22,n=5291=188.971, p<.001, and the corrected MoCA X22,n=5282=167.073, p<.001. Additionally, a One-way ANCOVA analysis comparing the correlation of education and uncorrected MoCA score for Black/African American (r=.425, p<.001) and White participants (r=.198, p<.001) shows a significant difference between the two groups F1,5288=167.992, p<.001. Specifically, in Black/African American participants, the correlation is much stronger suggesting that years of education is a greater determinant of cognitive status. These results demonstrate that regardless of controlling for education via adding buffer points significant racial disparities in global cognition scores were still present. Alternative corrections for race and education should be considered for future test adaptations.

Out Like a Light: Feasibility and Acceptability Study of an Audio-Based Sleep Aide for Improving Parent–Child Sleep Health

Our study examines the acceptability and feasibility of Moshi, an audio-based mobile application, among children 3–8 years old using a parent–child dyadic approach. Our 10-day within-subject pre–post study design consisted of five nights of a normal bedtime routine and a subsequent five nights exposed to one story on the Moshi application during the intervention. Each five-night period spanned three weeknights and two weekend nights. The Short-Form Children’s Sleep Habits Questionnaire (SF-CSHQ) was used to measure children’s sleep at baseline and post-intervention. The PROMIS, Epworth Sleepiness Scale and Pittsburgh Sleep Quality Index were used to assess parents’ sleep. Among the 25 child–parent dyads, the mean child age was 4 (SD = 1.23) and 63% were male (n = 15). Mean parent age was 35 (SD = 5.83), 84% were female (n = 21), and 48.0% were Black (n = 12). For child-only comparisons, mean post-SF-CSHQ measures were lower compared to baseline. A trend in parent sleep is reported. This study shows the potential of an audio-based mobile sleep aid to improve sleep health in a racially diverse parent and child dyad sample.

Digital biomarkers and sex impacts in Alzheimer’s disease management — potential utility for innovative 3P medicine approach

Digital biomarkers are defined as objective, quantifiable physiological and behavioral data that are collected and measured by means of digital devices. Their use has revolutionized clinical research by enabling high-frequency, longitudinal, and sensitive measurements. In the field of neurodegenerative diseases, an example of a digital biomarker-based technology is instrumental activities of daily living (iADL) digital medical application, a predictive biomarker of conversion from mild cognitive impairment (MCI) due to Alzheimer’s disease (AD) to dementia due to AD in individuals aged 55 + . Digital biomarkers show promise to transform clinical practice. Nevertheless, their use may be affected by variables such as demographics, genetics, and phenotype. Among these factors, sex is particularly important in Alzheimer’s, where men and women present with different symptoms and progression patterns that impact diagnosis. In this study, we explore sex differences in Altoida’s digital medical application in a sample of 568 subjects consisting of a clinical dataset (MCI and dementia due to AD) and a healthy population. We found that a biological sex-classifier, built on digital biomarker features captured using Altoida’s application, achieved a 75% ROC-AUC (receiver operating characteristic — area under curve) performance in predicting biological sex in healthy individuals, indicating significant differences in neurocognitive performance signatures between males and females. The performance dropped when we applied this classifier to more advanced stages on the AD continuum, including MCI and dementia, suggesting that sex differences might be disease-stage dependent. Our results indicate that neurocognitive performance signatures built on data from digital biomarker features are different between men and women. These results stress the need to integrate traditional approaches to dementia research with digital biomarker technologies and personalized medicine perspectives to achieve more precise predictive diagnostics, targeted prevention, and customized treatment of cognitive decline.

0350 At-home Sample Collection for Measurement of Diurnal Rhythms of Urinary Cortisol and Melatonin

Introduction

Sleep- and stress-related hormones (e.g., melatonin, cortisol) can be measured from dried urine samples collected at-home and sent for laboratory testing. These measures may be used to identify patterns of circadian alignment, peak nocturnal melatonin levels as well as a cortisol awakening response. The purpose of this analysis was to describe diurnal patterns and reference ranges from a 4-timepoint serial assessment of urinary cortisol and melatonin in a large cohort of at-home self collected samples.

Methods

This retrospective analysis evaluated data from 3,966 individuals who used an at-home Sleep and Stress Test (Everlywell, Inc.) between September 28, 2017 and July 14, 2021. Individuals provided four urine samples according to habitual sleep patterns: upon waking (T1), two hours after waking (T2), prior to the evening meal (T3), and at bedtime (T4). Melatonin and cortisol distributions were normalized to creatinine and log transformed to approximate normal distributions to define respective reference ranges (two standard deviations above and below the log transformed mean) and reverted to original units for reporting.

Results

71% (n=2,832) of users were female and mean age was 42.8 (sd=12.0) years. Mean (sd) urinary values were as follows: Cortisol: T1, 29.3 (37.9) ug/g Cr; T2, 47.2 (49.8); T3, 14.9 (36.3); T4. 8.38 (26.9). Melatonin: T1, 745 (3208) ug/g Cr; T2, 169 (1189); T3, 45 (620); T4, 155 (1701). For cortisol, only 4-5% of samples fell outside the defined reference ranges across time points. Melatonin was more variable with 23% and 15% falling outside the reference range at time points T3 and T4, respectively. A majority of individuals’ peak cortisol occurred at T2 (67.4%), and melatonin at T1 (85.2%).

Conclusion

This analysis demonstrates measurable physiological diurnal patterns for cortisol and melatonin using at-home self-collection for dried urine tests. This provides evidence that at-home sample collection kits using dried urine spots are a viable tool for assessing diurnal patterns of sleep and stress. Future controlled studies are needed to evaluate the utility in identifying abnormal patterns associated with shift-work or sleep disorders.

Support (If Any)

 

0621 Overcoming Obstacles to Recruitment and Community Engagement During COVID-19 and Development of a Digital Community Outreach program

Introduction

COVID-19 disrupted traditional research infrastructures and processes most notably in-person community recruitment, especially in underrepresented populations like racial ethnic minorities. To find creative and effective strategies, our group implemented and tested the efficacy of a culturally tailored community outreach plan (COP) developed during the US COVID-19 pandemic.

Methods

In February 2021, we developed an 11 step culturally-tailored community outreach program to support the implementation of three NIH funded community-based sleep studies. The following steps include: (1) description of the situation statement, 2) definition of goals, 3) engagement of audience/stakeholders, 4) tailoring message, 5) defining incentives, 6) choice of outreach methods, 7) identification of spokesperson, 8) choice of tools to assess progress, 9) identification of media outlets, 10) creation of study timeline, and 11) implementation of the plan. The studies leveraged several recruitment channels: 1) community settings (Place of worship, “community recruiter”, health fairs, word of mouth, & healthcare providers/doctors’ clinics), 2) online platforms (Facebook, Twitter, LinkedIn and Research Match), and 3) preexisting datasets in NYC.

Results

All three studies successfully met recruitment goals. ESSENTIAL [n= 224, 69% females, mean age= 36], MOSAIC [n=109, 61% females; mean age= 64] and Latinx/Hispanics: DORMIR[n=260, 61.3% of female; 32.4]. Among the three NYC cohorts, the most common recruitment channels were: preexisting datasets (74%), community settings (19%), & online platform (7%) for ESSENTIAL; preexisting datasets (85%) & community settings (15%) for MOSAIC, and (71.7%) online platform for DORMIR. However, the Miami cohorts came mostly from community settings 90% for Essential and 97% for MOSAIC.

Conclusion

Overall, the TSCS community outreach plan seems to be an effective tool to engage minoritized populations in greater NY and Miami. Our current field experience indicates that recruitment channels must be adapted to age, and community resources. Limited access to technology, particularly among older Blacks seem to be a major barrier for field staff to successfully engage the disenfranchised communities.

Support (If Any)

NIH R01HL142066-04; R01HL152453-01 R01HL142066, R01HL095799, RO1MD004113

0615 Association between Ambient Light Exposure and Sleep Duration among American Adults from Varying Race/Ethnicities: Findings from the National Health and Nutrition Examination Survey

Introduction

One in three American adults are sleep deprived in the United States (US). Racial/ethnic minorities are more likely to experience shorter sleep duration than are whites. Light exposure is associated with sleep duration. However, whether this association is independent of individuals’ race/ethnicity has not been studied in a nationally representative sample of the US adult population. We examined associations between ambient light exposure and sleep duration and between race/ethnicity and sleep duration. We also assessed whether associations between light exposure and sleep duration are independent of participants’ race/ethnicity.

Methods

We used data from the National Health and Nutrition Examination Survey (n=4,277 adults; 2013-2014). Participants (≥ 18 years old) wore an actigraph that collected 24-hour sleep/wake and light data for 7 consecutive days. Objective measurements in our analyses included sleep duration (valid minutes) and light exposure (lux). To determine the associations between light exposure and sleep duration, a weighted mixed-effects linear model was estimated controlling for age, sex, family income to poverty ratio, education, employment, marital status, homeownership status, birthplace, household size, vitamin D, smoking, physical activity, sedentary lifestyle, health status, body mass index, depression, chronic conditions, and time in days. A product term between lux and race/ethnicity was included in a second regression model.

Results

Participants had a mean sleep duration of 468.2 minutes. On average, White adults had the longest sleep duration (mean=478.8), followed by other/multiple races (mean=458.6), Asians (mean=449.1); Blacks (mean=445.0), and Hispanics (mean=444.7). Overall, light exposure was negatively associated with sleep duration (= -0.08 lux; p&lt;0.001). Black slept significantly less than did Whites (= -37.1 p&lt;0.001) followed by Asians ( = -26.5; p&lt;0.01) and Hispanics (= -24.6; p&lt;0.01). The association between light exposure and sleep duration did not significantly differ across all race/ethnic groupings, except for Blacks (= -0.05; p&lt;0.01).

Conclusion

To our knowledge, this is the first study that used national data to assess racial/ethnic disparities in objectively measured light exposure. Future research is needed to shed more light on racial/ethnic disparities in the light-exposure-sleep-duration link.

Support (If Any)

R01HL142066, R01HL095799, RO1MD004113, R01HL152453, R25HL105444

0272 Decreased Risk of 2-Year Incidence of Alzheimer’s Disease Among Older Adults Who Report Sleep Symptoms

Introduction

Those with dementia or Alzheimer’s Disease report an elevated amount of sleep difficulties compared to age-matched controls. Sleep-based interventions may be especially useful for this group, such as cognitive behavioral therapy for insomnia or pharmacological interventions. Therefore, it is important to expand the current understanding of the nature of sleep difficulties in those with Alzheimer’s Disease.

Methods

Data from the 2018 Health and Retirement Survey was collected from 17,146 older adults. Poisson regression analyses were used to explore the relationship between Alzheimer’s Disease as diagnosed by a doctor and sleep difficulties. Individuals who reported no Alzheimer’s Disease in the previous wave (N=16,751) were asked if they had since become diagnosed. N=101 individuals reported incident Alzheimer’s Disease in the 2-year gap between assessments. Sleep difficulties were assessed by asking participants if they had difficulties initiating or maintaining sleep, waking up too early, and how rested they felt upon awakening. All 4 of these symptoms were coded as “never,” “sometimes,” or “often.”

Results

Unexpectedly, there was a significant decreased risk of developing Alzheimer’s Disease among those who reported difficulties maintaining sleep (IRR=0.9962; 95%CI[0.9936,0.9988]; p=0.004), and early morning awakenings (IRR=0.9961; 95%CI[0.9938,0.9984]; p=0.001) “sometimes”. When the model was adjusted for sex, race, ethnicity, age, and depression, a similar finding of decreased risk for Alzheimer’s Disease for those who reported difficulties maintaining sleep (IRR=0.9953; 95%CI[0.9927,0.9980]; p&lt;0.001), and early morning awakenings (IRR=0.9954; 95%CI[0.9930,0.9978]; p=0.001), “sometimes” were maintained.

Conclusion

Although previous studies have shown that poor sleep may lead to increased risk of Alzheimer’s and related dementias, the present study, which examined longitudinal data from a large, national sample of older adults, found that there was no association between frequent sleep disturbances and 2-year incidence of Alzheimer’s Disease, and a small association between more mild symptoms and decreased risk. It is possible that the 2-year observation window was insufficient to detect effects. Also, there is a risk of measurement error in collecting self-reported data on sleep and Alzheimer’s diagnoses.

Support (If Any)

The HRS (Health and Retirement Study) is sponsored by the National Institute on Aging (grant number NIA U01AG009740) and is conducted by the University of Michigan.

0618 Association between Ambient Light Exposure, Race/Ethnicity, and Vitamin D among Adults in the United States: Analysis of the National Health and Nutrition Examination Survey

Introduction

The prevalence of vitamin D deficiency (VitD) in the United States is 41 percent, with the highest rate among Blacks 82 percent. Vitamin D deficiency has been linked to chronic diseases. The extent to which the association between light exposure and vitamin D serum levels can vary by individual’s race/ethnicity of which has not been studied at a national level. We aim to explore the associations of ambient light exposure between race/ethnicity and vitamin D.

Methods

The study used data from the National Health and Nutrition Examination Survey (2013-14). For detection of 25-hydroxyvitamin D3 and 25-hydroxyvitamin D2 nmol/L, ultra-high-performance liquid chromatography-tandem mass spectrometry was performed based on serum samples from adults aged ≥ 18 years. Light levels (lux) data were gathered using 24-hour actigraphic monitoring over /a 7day period. Weighted generalized linear models were fitted examining association between light exposure and VitD adjusting for age, sex, family income/poverty ratio, education, employment, house tenure, marital status, birthplace, number of people in household, smoking, physical activity, and sedentarity. To compare this association across race/ethnicity, a product term between lux and race/ethnicity was included in adjusted models.

Results

Among 4,251 participants, White adults had the highest levels of VitD (mean=76.0; se=1.3), then other/multiple races (mean=65.1; se=2.2), Asians (mean=62.5; se=1.4); Hispanics (mean=57.4 nmol/L; se=1.6), and Blacks (mean=50.1; se=1.4). Regression analysis revealed estimated mean VitD of 64.9 nmol/L and positive association between light exposure and VitD ( 0.020). Blacks had significantly lower VitD levels ( -19.3) followed by Asians (-12.1) and Hispanics (-12.6) (all p-values &lt;0.001). The association between light exposure and VitD depended on participant’s race/ethnicity

Conclusion

To our knowledge, this is the first study showing associations between objectively measured light exposure and VitD serum levels using a large representative sample of the US population. Although the study revealed racial/ethnic disparities in VitD levels, light exposure was associated with VitD even when race/ethnicity was adjusted for in the model. Further research on racial/ethnic differences in VitD is warranted.

Support (If Any)

R01HL142066, R01HL095799, RO1MD004113, R01HL152453, R25HL105444

0379 At-home Sample Collection for Identification of Alterations in HPA-axis Activity and Cortisol Area Under the Curve

Introduction

Sleep problems are associated with alterations in diurnal cortisol patterns, reflective of altered hypothalamic-pituitary-axis (HPA) activity. At-home collection of dried samples for measurement of urinary free cortisol are useful for assessment of diurnal rhythms because they do not impose the stress or sleep disruption associated with inpatient studies. The purpose of this analysis was to assess urinary cortisol responses among a large real-world dataset of at-home collection kit users and the potential for utility in identifying alterations in HPA-axis activity.

Methods

This retrospective analysis evaluated data from 3,966 individuals who used a Sleep and Stress Test (Everlywell, Inc.) between September 2017 and July 2021. Four dried urine spot samples were collected according to habitual sleep patterns: upon waking (T1), two hours after waking (T2), prior to the evening meal (T3), and at bedtime (T4). Urinary free cortisol normalized to creatinine, indicative of HPA-axis activity was assessed (area under the curve (AUC), wake to bedtime diurnal cortisol slope (DCS), mid-morning (T2) and bedtime (T4) cortisol levels). Sample reference ranges were established from two standard deviations above and below the log-transformed mean at each time point, values were reverted to original units for reporting.

Results

The sample was predominantly female (n=2,832, 71%). Mean age was 42.8 (sd=12.0) years. Seventy-eight individuals had mid-morning (T2) cortisol levels that were higher than the sample reference range (7.0-170.7 ug/g Cr), and 88 individuals below. Bedtime (T4) cortisol levels were elevated in 145 individuals (reference range 1.1-25.0 ug/g Cr). Total AUC for cortisol was high in 93 and low in 81 of individuals. The slope of the diurnal cortisol response was flattened in 20.6% (n=816) of the sample.

Conclusion

This real-world study demonstrates that at-home dried urine sample collection can be used to characterize normal and atypical HPA-axis activity. Convenient assessment of alterations in diurnal cortisol patterns are critical in identifying and understanding the mechanisms of HPA-axis activity common in sleep disruptions/disorders. Future studies utilizing this methodology may prove useful in identifying subpopulations with altered HPA-axis activity, sleep issues, and potential relationships to cardiometabolic health.

Support (If Any)

 

0273 Sleep Disorders as a Potential Risk Factor for Dementia in Elderly Adults

Introduction

Sleep disorders such as insomnia are seen in the early onset of Alzheimer’s disease, the most common form of dementia. Simultaneously, sleep disorders may indicate increased risk for the development of dementia. Due to the rate of comorbidity of these two conditions seen in the elderly population, the relationship between dementia and sleep disorders is a topic of interest for researchers. A bidirectional correlation between the two could have important implications in the clinical field exploring factors that lead to dementia

Methods

Data was assessed from 17,146 older adults from the 2018 Health and Retirement Survey. Participants were surveyed using questionnaires regarding both incident dementia or serious memory impairment in the past 2 years and the presence of a sleep disorder, as diagnosed by a doctor or health professional. Those who reported no dementia in the previous wave (N=16,547) were asked if they had been diagnosed since they were last asked. N=185 individuals reported incident dementia in the 2-years between assessments. Responses were coded to either “Yes” or “No”. A Poisson regression analysis was conducted to explore the relationship between incident dementia and sleep disorders.

Results

In a sample of older adults, unadjusted results indicate that having a sleep disorder was associated with a 0.6% increased risk of new onset dementia (PRR=1.006; 95%CI[1.001,1.012]; p=0.026). These results were sustained when adjusted for sex, age, race, ethnicity, and depression (PRR=1.006; 95%CI[1.001,1.012]; p=0.013).

Conclusion

Chronic sleep disturbances may be a factor used to indicate increased risk for dementia and help with early detection of the disease. These results demonstrate the value of sleep disorders screening among those at risk for dementia. Further research is needed to clarify these findings (e.g., explore specific sleep disorders) and expand the follow-up window (i.e., beyond 2 years).

Support (If Any)

The HRS (Health and Retirement Study) is sponsored by the National Institute on Aging (grant number NIA U01AG009740) and is conducted by the University of Michigan.

0622 Influence of Cannabis Use Disorder on Sleep Quality among College Students

Introduction

Poor sleep, which has numerous deleterious effects, is one of the most common health complaints among college students. Both race/ethnicity and sex are associated with poor sleep outcomes, with Black college women potentially having higher risk. The college experience is often associated with an increase in stress, as well as drastic shifts in lifestyle and sleep patterns. Research indicates that college students report cannabis use enables them to cope with life stressors and negative emotions and is often used as a sleep aid. The use of cannabis as a to cope may lead to more chronic cannabis use, and the development of Cannabis Use Disorder (CUD), which is most prevalent in individuals aged 18-25. Therefore, this study examined the influence of CUD symptomatology on sleep among Black female college students.

Methods

Participants included 200 Black/African American women (age range: 18-25 years) attending a Historically Black College/University. Each participant completed an Qualtrics online survey including assessment of DSM-5 CUD criteria, and validated measures of sleep quality (Pittsburgh Sleep Quality Index [PSQI]) and perceived stress (Perceived Stress Scale [PSS]).

Results

11.5% of the sample met criteria for CUD. There were no significant differences between the CUD and non-CUD groups in perceived stress, however, all participants endorsed moderate stress levels (M=19.51, SD=5.33). Additionally, all participant’s PSQI scores met criteria for impaired sleep (score &gt;5). [MOU1] [TAD2] T-test analyses indicate that the CUD subgroup reported poorer sleep quality (M=9.04, SD=3.69 vs M=7.07, SD=3.28), more sleep disturbances (M=1.52, SD=0.59 vs M=1.15, SD=0.74), and longer sleep latency (M=37.70, SD=25.28 vs M=25.92, SD=23.95), than the non-CUD group (all p&lt;.05).

Conclusion

Black/African American female college students who met criteria for CUD reported more sleep disturbances, longer sleep latencies, and poorer overall sleep quality. Given the lack of difference in perceived stress, these results suggest that the use of cannabis as a coping aid may exacerbate poor sleep. Previous research indicates that Black women are not only more likely to report poor sleep, but that they also report exploring non-traditional strategies to address their sleep problems. These findings suggest a need to examine these non-traditional coping strategies for possible paradoxical and deleterious effects.

Support (If Any)

Funding: R01HL142066, R01HL095799, RO1MD004113, R01HL152453, 1R15 DA052886-01A1

0612 Does Coping Strategy Protect Sleep Quality During COVID-19? An Examination of Racial, Ethnic, Cultural Differences

Introduction

Little has been done to examine within/between group predictors and mediators of race/ethnic differences in sleep health outcomes, due to COVID-19 exposure. We evaluated the effect of COVID-19 exposure on sleep quality in a multiracial/ethnic sample of New York residents.

Methods

We conducted a cross-sectional study among adults exposed to COVID-19 across New York State from September to November of 2020. Comparisons of participant characteristics e.g., mean scores by race/ethnicity status were made using one-way ANOVA for continuous variables, and chi-square tests for categorical variables. Associations between social determinants of health (employment, location), Trauma Coping Self-Efficacy (CES-T), and sleep quality (Pittsburgh Sleep Quality Index-PSQI) were examined using multilinear regression analysis stratified by race/ethnicity.

Results

Of the 541 participants, 373 (68.9%) were female; mean age was 40.9 years (SD=15), 198 (36.6%) identified as Whites, 111 (20.5%) as Black, 97 (17.9%) as Hispanics, and 135(25%) identified as either Asians, Native-Americans, Pacific-Islanders. Sex was the strongest predictor [β = 1.335; p < .05] of sleep quality, but only among Whites. Trauma Coping Self-Efficacy was negatively associated with sleep quality among Asian, Native-American, or Pacific-Islander participants [β = -.114; p < .05 ]; Black [β = -.099; p < .05] and White participants [β = -0.79; p < .05] but not among Latinos/as [β = -.058; p = 0.71].

Conclusion

Coping Self-Efficacy moderated the effect of COVID-19 on sleep quality among some, but not all, racial/ethnic groups. While CSE-T scores during the first wave of COVID-19 acted as a protective factor for sleep quality among Asians, Native-Americans, and Pacific-Islanders, White and Black participants, this was not the case for Latinos/as/Hispanics residing in New York. Clinical interventions that are tailored for racial/ethnic, community and cultural needs may help to mitigate sleep problems associated with COVID-19 exposure.

Support (If Any)

T32HL129953; 7R01HL142066-04; 1R01HL152453-01

0728 Physical and Mental Health among Blacks with OSA and Insomnia: a Stakeholder-engaged community study

Introduction

Health consequences of co-occurring obstructive sleep apnea (OSA) and insomnia have been well documented. However, little is known about the mental and physical consequences of co-occurring OSA and insomnia among Blacks. We aimed to investigate the rate of OSA risk and insomnia symptoms and potential associations with physical and mental health in a community sample of Blacks.

Methods

Data were collected from an NIH-funded study ‘Peer-Enhanced Education to Reduce Sleep Ethnic Disparities, designed to navigate blacks at risk of OSA to receive timely diagnosis and treatment using peer-delivered linguistically and culturally tailored sleep health education. Blacks (n=878) were screened for OSA using the Apnea Risk Evaluation System Questionnaire; a score ≥6 denoted high OSA risk. The Sleep Disorders Questionnaire was used to assess insomnia based on three common insomnia symptoms: trouble falling asleep, difficulty staying asleep, and early morning awakening. Physical Health Composite Score (SF-12PCS) and Mental Health Composite Scores (SF-12MCS) were generated based on how the person answered the SF-12 questions. Scores range from 0 to 100, where 0 indicates the lowest level of health and 100, the highest. Logistic regression models were used to assess associations of physical and mental health among Blacks at risk for OSA, reporting insomnia symptoms, and co-occurring OSA risk and insomnia symptoms. All models adjusted for differences in age, sex, and BMI.#8232;

Results

The prevalence of OSA risk, insomnia symptoms, and co-occurring OSA risk and insomnia symptoms was 47.9%, 73.3%, and 40.2%, respectively. Logistic regression analyses showed lower physical score was positively associated with the odds of reporting insomnia symptoms (OR=1.03, p=0.007) and co-occurring OSA risk and insomnia symptoms (OR=1.02, p=0.001). Lower mental score was positively associated with the odds of OSA risk (OR=1.04, p=0.001), insomnia symptoms (OR=1.04, p=0.001), and co-occurring OSA risk and insomnia symptoms (OR=1.04, p=0.001). Individuals with OSA were less likely to report higher physical scores compared with those with co-occurring OSA risk and insomnia symptoms.

Conclusion

Results demonstrate that blacks with insomnia symptoms are more likely to endorse worse physical and mental health. Future research should investigate further the mechanism underlying co-occurring OSA and insomnia in this population using objective measurements.

Support (If Any)

Support: NIH R01MD007716

0620 Is SVI a Risk Factor for Sleep and Cardiometabolic Health Among Blacks?

Introduction

The Social Vulnerability Index (SVI) is a novel metric that incorporates a multitude of population factors to predict the susceptibility of communities to deleterious effects of disaster, natural hazards, and environmental insult. Studies show socioeconomic status (SES), an important component of SVI, is a risk factor for cardiometabolic disease and sleep quality. Objectives: This study examined the effect of SVI on cardiometabolic and sleep health among Blacks.

Methods

We utilized harmonized data extracted from two NIH-funded studies enrolling Blacks (i.e., MetSO and PEERS-ED registries). Participants (N=1,497) included New York residents; 65% were male, with a mean(SD) age of 55(±16.2). Data were collected via self-reports (e.g., ARES questionnaire) for sleep quality/duration and cardiometabolic factors (e.g., weight and diet). SVI components included SES, household composition, minority status, and housing type. Mixed-effect logistic regression models were applied, which assessed the effect of SVI and its many subcomponents on each health-related variable of interest. The model was adjusted for age, sex, and education to account for the effects of these factors overlapping in the SVI subcomponents.

Results

Approximately 81% of the sample population was obese, 37.9% were diabetic, 62.3% had a history of hypertension, and 18.4% with a heart disease. Regarding sleep health, 7.7% suffered from sleep apnea, 66.6% were short sleepers, 6.64% were long sleepers, and 14.2% reported insomnia. They had a mean(SD) sleep time of 5.92(±2.05) hours. “Overall SVI” was associated with hypertension (OR=3.98) and “housing type & transport” was correlated with heart disease (OR=4.44) prior to adjusting the model. Applying the adjusted model, “minority status & language” predicts obesity (OR=5.32). Also, “overall SVI” and “SES” were associated with diabetes (OR=3.26; OR=2.71) and hypertension (OR=4.00; OR=3.95). “Household composition” approaches significance as a predictor for sleep apnea (unadjusted - OR=0.26; adjusted - OR=0.26) despite the relatively low case proportion.

Conclusion

SVI seems to be a good indicator of cardiometabolic health among Blacks. However, it is likely a poor marker for sleep health in that population, although trends were observed suggesting that it might play an important role. Further studies are necessary to elucidate the role of SVI on sleep health among Blacks.

Support (If Any)

R01HL142066, R01HL095799, RO1MD004113, R01HL152453

0617 Association Between Green, Blue, and Open Spaces and Sleep Health in a Black Population: An Analysis of the MetSO Dataset

Introduction

Blacks have a high burden of poor sleep health outcomes. Environmental determinants, such as green space or open environments, represent an underexplored contributor to sleep burden among Blacks. The extent these environmental factors affect sleep health outcomes within this population has not been adequately explored. To fill this gap in the literature, we investigated associations between environmental factors and sleep outcomes among Blacks in a large urban city. Objectives included (1) examine if zip-code derived open spaces (defined as proportion of open space in residential area,) green spaces (defined as open tree coverage of the ground) and blue spaces (proportion of water space) sleep apnea risk, and insomnia symptoms; (2) Examine if open, blue, and green spaces predict sleep outcomes independent of sex, age, and education level.

Methods

Our study used data from the Metabolic Syndrome Cohort Study (2009-2014), a studythat examined behavioral intervention methods to improve sleep apnea outcomes among Blacks. Sleep Apnea was assessed with the ARES (apnea risk) scale and insomnia status was collected through self-report (“Do you have difficulty staying/falling asleep or waking up?”) in a subset of 344 participants. Logistic regression analyses were performed to predict the effect green, blue, and open spaces had on sleep outcomes. To account for within zip-code correlation, mixed effects models (unadjusted and adjusted) account for sex, age, and education were considered.

Results

We found that none of the green, blue, or open space variables predicted sleep outcomes in the unadjusted model. In adjusted models, green space predicted sleep apnea risk scores, (OR=1.03, P&lt;.05), but not insomnia.

Conclusion

Our study examined the extent which green, blue, and open spaces predicted insomnia and sleep apnea in urban blacks. We found that only green spaces were associated with sleep apnea, and none of our environmental variables predicted insomnia. Given the large amount of literature detailing a complex and multifactorial process on how environment affects sleep outcomes, our findings suggest that the link between urban environments, green spaces, and sleep outcomes may not be as definitive as they seem. Further research should explore the differential effect environment has on diverse populations’ sleep outcomes.

Support (If Any)

NIH R01HL142066, R01HL095799, RO1MD004113, R01HL152453

Predicting the number of COVID-19 infections and deaths in USA

Background

Uncertainties surrounding the 2019 novel coronavirus (COVID-19) remain a major global health challenge and requires attention. Researchers and medical experts have made remarkable efforts to reduce the number of cases and prevent future outbreaks through vaccines and other measures. However, there is little evidence on how severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection entropy can be applied in predicting the possible number of infections and deaths. In addition, more studies on how the COVID-19 infection density contributes to the rise in infections are needed. This study demonstrates how the SARS-COV-2 daily infection entropy can be applied in predicting the number of infections within a given period. In addition, the infection density within a given population attributes to an increase in the number of COVID-19 cases and, consequently, the new variants.

Results

Using the COVID-19 initial data reported by Johns Hopkins University, World Health Organization (WHO) and Global Initiative on Sharing All Influenza Data (GISAID), the result shows that the original SAR-COV-2 strain has R₀<1 with an initial infection growth rate entropy of 9.11 bits for the United States (U.S.). At close proximity, the average infection time for an infected individual to infect others within a susceptible population is approximately 7 minutes. Assuming no vaccines were available, in the U.S., the number of infections could range between 41,220,199 and 82,440,398 in late March 2022 with approximately, 1,211,036 deaths. However, with the available vaccines, nearly 48 Million COVID-19 cases and 706, 437 deaths have been prevented.

Conclusion

The proposed technique will contribute to the ongoing investigation of the COVID-19 pandemic and a blueprint to address the uncertainties surrounding the pandemic.

Patterns of Eating Associated with Sleep Characteristics: A Pilot Study among Individuals of Mexican Descent at the US-Mexico Border

Introduction: Previous studies have linked sleep to risk of diabetes and obesity, at least partially via alterations in food intake. Diabetes and obesity are common among Hispanics/Latinos, and studies are needed to better clarify the role of sleep in health among this group. Utilizing the revised TFEQ-R-18, this study will examine whether eating behaviors such as cognitive restraint, emotional eating and uncontrolled eating are related to self-reported sleep experiences. Specifically, we hypothesized that poor eating habits would be associated with (1) more insomnia symptoms, (2) overall worse sleep quality, (3) increased daytime sleepiness, and (4) shorter sleep duration.Methods: Data were collected from N = 100 adults (age 18-60, 47% female) of Mexican descent in the city of Nogales, AZ (34% not born in the US). Surveys were presented in English or Spanish. Eating Patterns were assessed with the Three-Factor Eating Questionnaire (TFEQ), which resulted in a total score and subscales for "cognitive restraint," "uncontrolled eating," and "emotional eating." Insomnia was assessed with the use of the Insomnia Severity Index (ISI), Sleepiness with the use of the Epworth Sleepiness Scale (ESS), Sleep quality with the use of the Pittsburgh Sleep Quality Index (PSQI), and weekday and weekend sleep duration with the use of the Sleep Timing Questionnaire (STQ). Covariates included age, sex, Body Mass Index (BMI), education and immigrant status.Results: Overall TFEQ score (problematic eating) was positively associated with greater insomnia, poorer sleep quality, more sleepiness, and less weekend (but not weekday) sleep. Mean TFEQ score in the sample was 18.7 (range 0-51). In adjusted analyses, every point on the TFEQ was associated with 0.6 ISI points, 0.8 PSQI points, 0.5 ESS points, and 1.1 minutes of less weekend sleep duration. Regarding subscale scores, relationships were generally seenbetween sleep and emotional eating and unrestricted eating, and not cognitive restraint.Conclusions: Greater insomnia, poorer sleep quality, increased daytime sleepiness and decreased weekend sleep duration were associated with eating patterns at the US-Mexico border, particularly in the area of unrestricted eating and emotional eating. This suggests possible mechanisms linking sleep and obesity in Hispanic/Latinos.

Stress and Depression Are Associated With Life's Simple 7 Among African Americans With Hypertension: Findings From the Jackson Heart Study

BACKGROUND

The American Heart Association created the Life's Simple 7 (LS7) metrics to promote cardiovascular health (CVH) by achieving optimal levels of blood pressure, cholesterol, blood sugar, physical activity, diet, weight, and smoking status. The degree to which psychosocial factors such as stress and depression impact one's ability to achieve optimal CVH is unclear, particularly among hypertensive African Americans.

METHODS

Cross-sectional analyses included 1,819 African Americans with hypertension participating in the Jackson Heart Study (2000-2004). Outcomes were LS7 composite and individual component scores (defined as poor, intermediate, ideal). High perceived chronic stress was defined as the top quartile of Weekly Stress Inventory scores. High depressive symptoms were defined as Center for Epidemiologic Studies Depression scale scores of ≥16. We compared 4 groups: high stress alone; high depressive symptoms alone; high stress and high depressive symptoms; low stress and low depressive symptoms (reference) using linear regression for total LS7 scores and logistic regression for LS7 components.

RESULTS

Participants with both high stress and depressive symptoms had lower composite LS7 scores (B [95% confidence interval] = -0.34 [-0.65 to -0.02]) than those with low stress and depressive symptoms in unadjusted and age/sex-adjusted models. They also had poorer health status for smoking (odds ratio [95% confidence interval] = 0.52 [0.35-0.78]) and physical activity (odds ratio [95% confidence interval] = 0.71 [0.52-0.95]) after full covariate adjustment.

CONCLUSIONS

The combination of high stress and high depressive symptoms was associated with poorer LS7 metrics in hypertensive African Americans. Psychosocial interventions may increase the likelihood of engaging in behaviors that promote optimal CVH.

The development and psychometric evaluation of the Survey of Obstructive Sleep Apnea Functional Health Literacy

Objective and Objective

Obstructive Sleep Apnea (OSA) is a highly prevalent disorder that disparately affects racial/ethnic minorities. OSA functional health literacy can contribute to health disparities. Documenting poor OSA functional health literacy is needed to inform research agendas, policy, and advocacy efforts. The objective of this study is to develop a scale for measuring OSA functional health literacy among diverse audiences and a variety of reading levels and to ascertain its reliability and validity.

Methods

Development of the 18-item Survey of OSA Functional Health Literacy (SOFHL) was guided by literature review and input from experts. A convenience sample of persons enrolled in a clinical trial completed the survey (n=194). The psychometric evaluation was conducted using factor analysis to identify the number of dimensions in the SOFHL and their relationship to other domains that are relevant to OSA functional health literacy.

Results

Internal consistency reliability (alpha) was estimated for the resulting scale and correlations with educational attainment and income completed. All respondents were Black and 29% reported average household income less than $10,000 USD. Confirmatory factor analysis provided support for two dimensions: OSA general knowledge (alpha=0.81) and self-efficacy for OSA self-management (alpha=0.71).

Conclusions

Higher educational attainment and socioeconomic status were associated with better OSA functional health literacy. These results provide preliminary support for the SOFHL, a measure that can be used to assess OSA functional health literacy.

COVID-19 instructional approaches (in-person, online, hybrid), school start times, and sleep in over 5,000 U.S. adolescents

Study Objectives

To examine associations among instructional approaches, school start times, and sleep during the COVID-19 pandemic in a large, nationwide sample of U.S. adolescents.

Methods

Cross-sectional, anonymous self-report survey study of a community-dwelling sample of adolescents (grades 6–12), recruited through social media outlets in October/November 2020. Participants reported on instructional approach (in-person, online/synchronous, online/asynchronous) for each weekday (past week), school start times (in-person or online/synchronous days), and bedtimes (BT) and wake times (WT) for each identified school type and weekends/no school days. Sleep opportunity was calculated as BT-to-WT interval. Night-to-night sleep variability was calculated with mean square successive differences.

Results

Respondents included 5,245 racially and geographically diverse students (~50% female). BT and WT were earliest for in-person instruction; followed by online/synchronous days. Sleep opportunity was longer on individual nights students did not have scheduled instruction (>1.5 h longer for online/asynchronous than in-person). More students obtained sufficient sleep with later school start times. However, even with the same start times, more students with online/synchronous instruction obtained sufficient sleep than in-person instruction. Significantly greater night-to-night variability in sleep-wake patterns was observed for students with in-person hybrid schedules versus students with online/synchronous + asynchronous schedules.

Conclusions

These findings provide important insights regarding the association between instructional approach and school start times on the timing, amount, and variability of sleep in U.S. adolescents. Given the public health consequences of short and variable sleep in adolescents, results may be useful for education and health policy decision-making for post-pandemic secondary schools.

Using a Digital Neuro Signature to measure longitudinal individual-level change in Alzheimer's disease: the Altoida large cohort study

Conventional neuropsychological assessments for Alzheimer's disease are burdensome and inaccurate at detecting mild cognitive impairment and predicting Alzheimer's disease risk. Altoida's Digital Neuro Signature (DNS), a longitudinal cognitive test consisting of two active digital biomarker metrics, alleviates these limitations. By comparison to conventional neuropsychological assessments, DNS results in faster evaluations (10 min vs 45-120 min), and generates higher test-retest in intraindividual assessment, as well as higher accuracy at detecting abnormal cognition. This study comparatively evaluates the performance of Altoida's DNS and conventional neuropsychological assessments in intraindividual assessments of cognition and function by means of two semi-naturalistic observational experiments with 525 participants in laboratory and clinical settings. The results show that DNS is consistently more sensitive than conventional neuropsychological assessments at capturing longitudinal individual-level change, both with respect to intraindividual variability and dispersion (intraindividual variability across multiple tests), across three participant groups: healthy controls, mild cognitive impairment, and Alzheimer's disease. Dispersion differences between DNS and conventional neuropsychological assessments were more pronounced with more advanced disease stages, and DNS-intraindividual variability was able to predict conversion from mild cognitive impairment to Alzheimer's disease. These findings are instrumental for patient monitoring and management, remote clinical trial assessment, and timely interventions, and will hopefully contribute to a better understanding of Alzheimer's disease.

Adolescent Peer Influence on Eating Behaviors via Social Media: Scoping Review

BACKGROUND

The influence of social media among adolescent peer groups can be a powerful change agent.

OBJECTIVE

Our scoping review aimed to elucidate the ways in which social media use among adolescent peers influences eating behaviors.

METHODS

A scoping review of the literature of articles published from journal inception to 2019 was performed by searching PubMed (ie, MEDLINE), Embase, CINAHL, PsycINFO, Web of Science, and other databases. The review was conducted in three steps: (1) identification of the research question and clarification of criteria using the population, intervention, comparison, and outcome (PICO) framework; (2) selection of articles from the literature using the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines; and (3) charting and summarizing information from selected articles. PubMed's Medical Subject Headings (MeSH) and Embase's Emtree subject headings were reviewed along with specific keywords to construct a comprehensive search strategy. Subject headings and keywords were based on adolescent age groups, social media platforms, and eating behaviors. After screening 1387 peer-reviewed articles, 37 articles were assessed for eligibility. Participant age, gender, study location, social media channels utilized, user volume, and content themes related to findings were extracted from the articles.

RESULTS

Six articles met the final inclusion criteria. A final sample size of 1225 adolescents (aged 10 to 19 years) from the United States, the United Kingdom, Sweden, Norway, Denmark, Portugal, Brazil, and Australia were included in controlled and qualitative studies. Instagram and Facebook were among the most popular social media platforms that influenced healthful eating behaviors (ie, fruit and vegetable intake) as well as unhealthful eating behaviors related to fast food advertising. Online forums served as accessible channels for eating disorder relapse prevention among youth. Social media influence converged around four central themes: (1) visual appeal, (2) content dissemination, (3) socialized digital connections, and (4) adolescent marketer influencers.

CONCLUSIONS

Adolescent peer influence in social media environments spans the spectrum of healthy eating (ie, pathological) to eating disorders (ie, nonpathological). Strategic network-driven approaches should be considered for engaging adolescents in the promotion of positive dietary behaviors.

Binge drinking and insomnia in students from health sciences at one university in Rio de Janeiro, Brazil

In spite of the many studies examining alcohol consumption, recent reviews have indicated that binge drinking has not been extensively studied. Furthermore, it is becoming increasingly clear that sleep is associated with many physiological functions and to drug addictions. The present study aimed to evaluate the relationship between alcohol binge drinking and insomnia in college students of health sciences. All first-year health sciences students (n=286) were evaluated in a cross-sectional study. Envelopes containing the Insomnia Severity Index (ISI), the Alcohol, Smoking, and Substance Involvement Screening Test (ASSIST), and questions capturing sociodemographic data were distributed and collected in classes. It was found that most non-drinkers were female (70.6%), although there were no sex-related differences in the number of binge drinkers (more than 5 drinks on each occasion at least once a week), allowing statistical comparison. The Mann-Whitney U test indicated that the ISI scores were significantly greater in female than male binge drinkers (P=0.014). Moderate or severe insomnia was reported by 23% of the sample, with alcohol being the most frequently associated substance. A specialized intervention was suggested by ASSIST: brief for marijuana (19.2%) and tobacco (23.3%) use, and moderate (31.5%) or intensive (1.4%) for alcohol consumers. The data highlighted the need to pay attention to the habits of college students beyond obtaining scientific information. New data suggesting the influence of genetics on insomnia may be of importance when performing additional studies on the sex differences in alcohol binge drinking.

Ambient Stimuli Perpetuate Nighttime Sleep Disturbances in Hospital Patients With TBI

BACKGROUND AND OBJECTIVES

The effect of the ambient environment, sound, light, and movement, on the nighttime rest-activity of patients hospitalized with moderate-severe traumatic brain injury (TBI) is poorly understood. The purpose of this study was to examine how sound, light, and movement in these patients' hospital rooms may contribute to nighttime awakenings.

METHODS

An observational design was used with 18 adult participants on a neuroscience step-down unit diagnosed with moderate-severe TBI. For up to five consecutive nights, actigraphy was used to capture nighttime awakenings while a custom-made multisensory device captured sound, light, and movement exposures in the participant's room.

RESULTS

Participants were awake for 24% (or about 3 hr) of the time during the designated nighttime period of 8 pm to 8 am. Average nighttime exposures of sound was 52 dB, light was nine lumens, and movement, measured as a proportion, was 0.28% or 28%. With each stimuli exposure set at its average, there was a 20% probability of participant nighttime awakenings. Clinically meaningful reductions of movement in and out the participant's room and elevated sound significantly decreases the participant's probability of nighttime awakenings (p < .05), but reductions in light did not.

CONCLUSION

The ambient environment seems to impede restful sleep in immediate post-injury phase of patients with moderate-severe TBI.

201 COVID-19 Pandemic Sleep Disturbances Related to Stress Experiences at the US-Mexico Border

Introduction

The COVID-19 pandemic has impacted many individuals at the vulnerable US-Mexico border region in a variety of ways. Fear, worry, and stress have increased for many, as has poor sleep. The present study evaluated the degree to which worsened sleep due to the pandemic impacted stress experiences.

Methods

Participants were N=155 individuals who completed the Nogales Cardiometabolic Health and Sleep (NOCHES) and were contacted about completing a COVID sub-study (95% Hispanic/Latino). They were asked the degree to which their sleep worsened due to the pandemic. They also reported the degree to which they agreed with statements regarding various pandemic-related stress experiences. These included infection-related stresses, stresses about community impact, personal psychosocial stresses, stresses about consequences of potential infection, media and society-related stresses, feelings of safety, and how the pandemic has impacted home life. Ordinal logistic regressions were used to determine whether changes in sleep were associated with agreement with statements about pandemic-related stress experiences, adjusted for age, sex, financial status, education, and mental health (PHQ4).

Results

Those who perceived that their sleep worsened were more likely to report greater endorsement of beliefs that they were infected (ordinal Odds Ratio [oOR]=2.82,p&lt;0.0005), they could possibly be infected (oOR=1.98,p=0.003), they feared testing (oOR=1.94,p=0.006), COVID-19 would impact their community (oOR=1.75,p=0.017) and would do so for a long time (oOR=1.90,p=0.006), they experience more general (oOR=4.10,p&lt;0.0005), financial (oOR=3.15,p&lt;0.0005), food-related (oOR=2.97,p&lt;0.0005), housing-related (oOR=2.14,p=0.002), family-related (oOR=2.53,p&lt;0.0005) and relationship (oOR=3.37,p&lt;0.0005) stress, their shopping was impacted by scarcity (oOR=1.76,p=0.014), and they are at high risk for COVID (oOR=1.87,p=0.008). Furthermore, media coverage of COVID-19 had increased their stress (oOR=2.46,p&lt;0.0005), there is too much panic about COVID-19 (oOR=1.67,p=0.032), and they themselves are scared of getting COVID-19 (oOR=1.95,p=0.005), worried about the future (oOR=1.71,p=0.022), feel less secure (oOR=0.59,p=0.028), are thriving less (oOR=0.40,p&lt;0.0005), and their mental health is not improving (oOR=0.46,p=0.002).

Conclusion

Worse sleep due to the COVID-19 pandemic was associated with increased reports of stresses across a wide range of domains. Perhaps sleep health interventions could improve social and emotional health in these domains and reduce stress experiences and better cope with the pandemic. Alternatively, mental health interventions should perhaps be targeted to this population.

Support (if any)

R01MD011600, R01DA051321

238 Adolescent Sleep Variability, Social Jetlag, and Mental Health during COVID-19: Findings from a Large Nationwide Study

Introduction

Adolescents are vulnerable to short, insufficient sleep stemming from a combined preference for late bedtimes and early school start times, and also circadian disruptions from frequent shifts in sleep schedules (i.e., social jetlag). These sleep disruptions are associated with poor mental health. The COVID-19 pandemic has impacted education nationwide, including changes in instructional formats and school schedules. With data from the Nationwide Education and Sleep in TEens During COVID (NESTED) study, we examined whether sleep variability and social jetlag (SJL) during the pandemic associate with mental health.

Methods

Analyses included online survey data from 4767 students (grades 6-12, 46% female, 36% non-White, 87% high school). For each weekday, participants identified if they attended school in person (IP), online-scheduled synchronous classes (O/S), online-no scheduled classes (asynchronous, O/A), or no school. Students reported bedtimes (BT) and wake times (WT) for each instructional format and for weekends/no school days. Sleep opportunity (SlpOpp) was calculated from BT and WT. Weekday night-to-night SlpOpp variability was calculated with mean square successive differences. SJL was calculated as the difference between the average sleep midpoint on free days (O/A, no school, weekends) versus scheduled days (IP, O/S). Participants also completed the PROMIS Pediatric Anxiety and Depressive Symptoms Short Form. Data were analyzed with hierarchical linear regressions controlling for average SlpOpp, gender, and school-level (middle vs high school).

Results

Mean reported symptoms of anxiety (60.0 ±9.1; 14%≧70) and depression (63.4 ±10.2; 22%≧70) fell in the at-risk range. Shorter average SlpOpp (mean=8.3±1.2hrs) was correlated with higher anxiety (r=-.10) and depression (r=-.11; p’s<.001) T-scores. Greater SlpOpp variability was associated with higher anxiety (B=.71 [95%CI=.41-1.01, p<.001) and depression (B=.67 [.33-1.00], p<.001) T-scores. Greater SJL (mean=1.8±1.2hrs; 94% showed a delay in midpoint) was associated with higher anxiety (B=.36 [.12-.60], p<.001) and depression (B=.77 [.50-1.03], p<.001) T-scores.

Conclusion

In the context of system-wide education changes during COVID-19, students on average reported at-risk levels of anxiety and depression symptoms which were associated with greater variability in sleep opportunity across school days and greater social jetlag. Our findings suggest educators and policymakers should consider these sleep-mental health associations when developing instructional formats and school schedules during and post-pandemic.

Support (if any)

T32MH019927(P.W.)

694 Insufficient sleep linked with higher COVID-19 infection cases and deaths in the United States

Introduction

Causes of COVID-19 burden in urban, suburban, and rural counties are unclear, as early studies provide mixed results implicating high prevalence of pre-existing health risks and chronic diseases. However, poor sleep health that has been linked to infection-based pandemics may provide additional insight for place-based burden. To address this gap, we investigated the relationship between habitual insufficient sleep (sleep <7 hrs./24 hr. period) and COVID-19 cases and deaths across urban, suburban, and rural counties in the US.

Methods

County-level variables were obtained from the 2014–2018 American community survey five-year estimates and the Center for Disease Control and Prevention. These included percent with insufficient sleep, percent uninsured, percent obese, and social vulnerability index. County level COVID-19 infection and death data through September 12, 2020 were obtained from USA Facts. Cumulative COVID-19 infections and deaths for urban (n=68), suburban (n=740), and rural (n=2331) counties were modeled using separate negative binomial mixed effects regression models with logarithmic link and random state-level intercepts. Zero-inflated models were considered for deaths among suburban and rural counties to account for excess zeros.

Results

Multivariate regression models indicated positive associations between cumulative COVID-19 infection rates and insufficient sleep in urban, suburban and rural counties. The incidence rate ratio (IRR) for urban counties was 1.03 (95% CI: 1.01 – 1.05), 1.04 (95% CI: 1.02 – 1.05) for suburban, and 1.02 (95% CI: 1.00 – 1.03) rural counties.. Similar positive associations were observed with county-level COVID-19 death rates, IRR = 1.11 (95% CI: 1.07 – 1.16) for urban counties, IRR = 1.04 (95% CI: 1.01 – 1.06) for suburban counties, and IRR = 1.03 (95% CI: 1.01 – 1.05) for rural counties. Level of urbanicity moderated the association between insufficient sleep and COVID deaths, but not for the association between insufficient sleep and COVID infection rates.

Conclusion

Insufficient sleep was associated with COVID-19 infection cases and mortality rates in urban, suburban and rural counties. Level of urbanicity only moderated the relationship between insufficient sleep and COVID death rates. Future studies should investigate individual-level analysis to understand the role of sleep mitigating COVID-19 infection and death rates.

Support (if any)

NIH (K07AG052685, R01MD007716, R01HL142066, K01HL135452, R01HL152453

712 COVID-19 Risk Perception, Sleep Health and Peritraumatic Distress Among New Yorkers: The NYU COVID-19 Mental Health Study

Introduction

Long-term exposure to pandemics like COVID-19 may increase psychological distress (e.g., peri-traumatic and post-traumatic distress) and sleep problems. Little is known about the effects of COVID-19 on peritraumatic distress, a well-documented risk factor for post-traumatic stress disorders (PTSD). The aim of this study was to investigate the association between COVID-19 risk perception and peritraumatic distress, and whether this relationship is moderated by sleep quality among individuals located in NY.

Methods

We examined data from 541 individuals (69% were female, mean age (SD) = 40.9 (15.3)] recruited online during summer and fall 2020 in New York for the NYU-COVID-19 Mental Health Study. Data were gathered on sociodemographic, COVID-19 risk perception (yes or no items), peri-traumatic distress measured by Peritraumatic Distress Inventory (PDI), and sleep quality measured by the Pittsburg Sleep Quality Index (PSQI). Descriptive, regression analysis and interaction terms were conducted using SPSS v. 25 to examine associations between COVID-19 risk perception with symptoms of peritraumatic distress and sleep quality.

Results

Of the 541 participants, 311(57.5%) reported they felt at risk for contracting COVID-19. PSQI was positively correlated with PDI (r =.38, p =0.01). An independent sample t student test indicated, on average, that the symptoms of PDI [(mean (SD)=27.3 (7.63), t = 7.07, n =307)] and PSQI [mean(SD)=10.62(3.57), t=4.31 n=311)] of our participants who felt at risk for contracting the COVID-19 significantly exceeded those who did not [(PDI mean(SD)=22.7(7.13), n =228); PSQI (mean(SD) =9.25(3.72), n=229]. Results of multiple linear regression analysis shown that COVID-19 risk perception was the strongest predictor of PDI [B(t) = −.630(12.7); p &lt; .001]. Furthermore, the interaction effect of PSQI scores and COVID-19 risk perception revealed that sleep quality significantly reduced the association between COVID-19 risk perception and PDI [B(t) = .319(5.71); p &lt;.001], such that poorer sleep and feeling at risk of contracting COVID-19 resulted in more severe PDI scores.

Conclusion

COVID-19 risk perception was associated with peritraumatic distress and poorer sleep quality, and sleep quality attenuated this relationship.

Support (if any)

NIH (T32HL129953, K07AG052685, R01MD007716, R01HL142066, K01HL135452, R01HL152453)

202 COVID-19 Pandemic Sleep Disturbances Related To Dietary Behavior at the US-Mexico Border

Introduction

The COVID-19 pandemic has disrupted life at the US-Mexico border in many ways, including sleep and dietary behavior. Given the potential long-term impact of worsening sleep and metabolic health due to the pandemic, the present study examines whether changes to dietary behavior were associated with changes to sleep.

Methods

Participants were 155 individuals who completed the Nogales Cardiometabolic Health and Sleep (NOCHES) Study and were contacted about completing a COVID-19 sub-study (95% Hispanic/Latino). Participants reported the degree to which they experienced pandemic-related changes to sleep, including a more regular schedule, overall improvement, overall worsening, more initial insomnia, more middle-of-the-night insomnia, more daytime sleepiness, and more napping. They were also asked whether as a result of the pandemic they consumed an overall healthier diet, more homecooked meals, more processed meals, more regular meals, whether they enjoyed food more, and degree of overeating. Ordinal regressions with diet change as outcome and sleep change as predictor were adjusted for age, sex, education, and socioeconomics.

Results

Those who reported more regular sleep were more likely to report a healthier overall diet (oOR=3.12,p<0.0005), more homecooked meals (oOR=2.18,p=0.001), more enjoyment of food (oOR=1.71,p=0.028), and less likelihood of overeating (oOR=0.59,p=0.033). Similarly, those who reported more “improved” sleep reported healthier overall diet (oOR=7.42,p<0.0005), more homecooked meals (oOR=2.59,p=0.001), more regular diet (oOR=2.15,p=0.006), more enjoyment of food (oOR=2.92,p<0.0005), less consumption of processed foods (oOR=0.54,p=0.039), and less overeating (0.33,p<0.0005). Those whose sleep worsened reported eating more processed foods (oOR=1.78,p=0.030) and overeating (oOR=3.90,p<0.0005). Those who reported more initial insomnia reported eating more processed foods (oOR=1.93,p=0.016), more regular diet (oOR=1.65,p=0.042), and overeating more often (oOR=4.11,p<0.0005). More middle-of-the-night insomnia was associated with eating more processed foods (oOR=2.45,p=0.001), more regular diet (oOR=1.66,p=0.031), and overeating more often (oOR=3.68, <0.0005). Those with more daytime sleepiness also reported eating more processed foods (oOR=2.36,p=0.003), more regular diet (oOR=1.79, =0.019), and overeating more often (oOR=3.28,p<0.0005). More napping was associated with a more regular diet (oOR=1.90,p=0.011) and more overeating (oOR=3.53,p<0.0005).

Conclusion

Overall, worse sleep led to worse dietary behavior, especially eating more processed food and overeating.

Support (if any)

Supported by T32HL007249, R01MD011600, R01DA051321

200 COVID-19 Pandemic Sleep Changes Related to Social and Financial Impacts at the US-Mexico Border

Introduction

The COVID-19 pandemic has caused major impacts to social and financial status for many people, including those living in the vulnerable US-Mexico border region. This study examined relationships between changes in sleep and perceived impacts to social and financial stability due to the pandemic.

Methods

Participants were 155 individuals who completed the Nogales Cardiometabolic Health and Sleep (NOCHES) and were contacted about completing a COVID sub-study (95% Hispanic/Latino). Participants were asked if the COVID-19 pandemic was causing them to feel more socially isolated, negatively impacting their finances, causing increased worry about finances, affecting their primary job, causing a job loss, and impacting their belief life will one day return to normal. In addition, they were asked to report the degree to which they experienced pandemic-related changes to sleep, including a regularity, overall improvement/worsening, initial and middle-of-the-night insomnia, daytime sleepiness, and napping. Logistic regression analyses were adjusted for age, sex, socioeconomics, and mental health (PHQ4).

Results

Those who kept a more regular schedule had lower odds of endorsing isolation (OR=0.32,p<0.0005) and higher odds of believing things will return to normal (OR=1.67,p=0.041). Those whose sleep improved also had lower odds of feeling isolated (OR=0.40,p=0.005). Those with worsened sleep had increased odds of feeling isolated (OR=2.14,p=0.023), experiencing a financial impact (OR=1.85,p=0.016) and increased financial worry (OR=1.71,p=0.033), and lower odds of believing things will return to normal (OR=0.53,p=0.012). More initial insomnia was associated with isolation (OR=3.62,p=0.001), financial impact, (OR=1.89,p=0.015), financial worry (OR=1.87,p=0.016) and job impact (OR=1.95,p=0.010). More middle-of-the-night insomnia was associated with financial worry (OR=1.82,p=0.016) and job impact (OR=1.93,p=0.009). More sleepiness was associated with job loss (OR=1.84,p=0.043). More napping was associated with financial impact (OR=1.89,p=0.017) and worry (OR=1.88,p=0.017), impact to job (OR=1.89,p=0.016) or lost job (OR=1.81,p=0.041), and decreased likelihood of believing things will return to normal (OR=0.45,p=0.003).

Conclusion

Pandemic-related stress was linked with sleep disturbances. Worse sleep was indicative of increased social isolation, greater financial fears, more job-related impacts and less of a general sense that things would return to normal.

Support (if any)

Supported by T32HL007249, R01MD011600, R01DA051321

685 Sleep Latency, Pre and Peri-COVID-19 Experiences and PTSD Symptoms: Results from the NYU COVID-19 Mental Health Study

Introduction

An effective response to the COVID-19 pandemic has been the decision to subject individuals residing in New York City to quarantine rules in order to reduce the spread of the virus. As might have been expected, restriction of usual daily activities would affect individuals’ sleep-wake patterns. It is also known that exposure to traumatic experiences can also engender sleep disturbances, most notably in their ability to initiate sleep. This study investigated the associations between sleep onset latency (SOL), pre and peri-COVID-19 exposure and symptoms of posttraumatic stress disorder (PTSD) among New Yorkers.

Methods

541 individuals (female = 373(69%); mean age=40.9) were recruited during the summer and fall of 2020 in New York City to participate in the NYU-COVID-19 Mental Health Study. Participants provided sociodemographic data and were also asked to respond to the COVID-19 quarantine experiences, comprised of seven binary questions, the PTSD Checklist-PCL-5, and the Pittsburg Sleep Quality Index. Descriptive and linear regression analysis were performed to explore associations of scores on the COVID-19 quarantine experience with PTSD and sleep data. All analyses were performed using SPSS 25.0

Results

Regression analyses revealed that SOL emerged as the strongest independent predictor of PTSD symptoms [B(t) = −.630(12.7); p < .001]; factors adjusted in the model included pre and peri-covid-19 factors such as age, sex, job type, and quarantine experience. Analyses assessing potential interaction effect revealed that quarantine experience did not affect the relationship between SOL and PTSD [B(t) = .086(.831); p = >.005]. The other sleep factors in the model did not yield significance. sleep duration had a weak correlation with quarantine, it was not found to be a predictor of PTSD.

Conclusion

We observed that SOL was the most important determinant of PTSD symptoms among individuals exposed to COVID-19. This is consistent with other findings suggesting that a sizable proportion of individuals exposed to pandemics are likely to experience sleep disturbances. It is plausible that quarantine might lead to increased daytime naps, which may impact SOL. Further research is needed to better understand the association of SOL and PTSD as a result of Covid-19.

Support (if any)

K07AG052685, R01MD007716, R01HL142066, T32HL129953, K01HL135452, R01HL152453

237 Sleep disturbances, online instruction, and learning during COVID-19: evidence from 4148 adolescents in the NESTED study

Introduction

COVID-19 fundamentally altered education in the United States. A variety of in-person, hybrid, and online instruction formats took hold in Fall 2020 as schools reopened. The Nationwide Education and School in TEens During COVID (NESTED) study assessed how these changes impacted sleep. Here we examined how instruction format was associated with sleep disruption and learning outcomes.

Methods

Data from 4148 grade 6-12 students were included in the current analyses (61% non-male; 34% non-white; 13% middle-school). Each student’s instructional format was categorized as: (i) in-person; (ii) hybrid [≥1 day/week in-person]; (iii) online/synchronous (scheduled classes); (iv) online/asynchronous (unscheduled classes); (v) online-mixed; or (vi) no-school. Sleep disturbances (i.e., difficulty falling/staying asleep) were measured with validated PROMIS t-scores. A bootstrapped structural equation model examined how instructional format and sleep disturbances predict school/learning success (SLS), a latent variable loading onto 3 outcomes: (i) school engagement (ii) likert-rated school stress; and (iii) cognitive function (PROMIS t-scores). The model covaried for gender, race-ethnicity, and school-level

Results

Our model fit well (RMSEA=.041). Examining total effects (direct + indirect), online and hybrid instruction were associated with lower SLS (b’s:-.06 to -.26; p’s<.01). The three online groups had the strongest effects (synchronous: b=-.15; 95%CI: [-.20, -.11]; asynchronous: b=-.17; [-.23, -.11]; mixed: b=-.14; [-.19, -.098]; p’s<.001). Sleep disturbance was also negatively associated with SLS (b=-.02; [-.02, -.02], p<.001). Monte-carlo simulations confirmed sleep disturbance mediated online instruction’s influence on SLS. The strongest effect was found for asynchronous instruction, with sleep disturbance mediating 24% of its effect (b = -.042; [-0.065, -.019]; p<.001). This sleep-mediated influence of asynchronous instruction propagated down to each SLS measure (p’s<.001), including a near 3-point difference on PROMIS cognitive scores (b = -2.86; [-3.73, -2.00]).

Conclusion

These analyses from the NESTED study indicate that sleep disruption may be one mechanism through which online instruction impacted learning during the pandemic. Sleep disturbances were unexpectedly influential for unscheduled instruction (i.e., asynchronous). Future analyses will examine specific sleep parameters (e.g., timing) and whether sleep’s influence differs in teens who self-report learning/behavior problems (e.g., ADHD). These nationwide data further underscore the importance of considering sleep as educators and policy makers determine school schedules.

Support (if any):

232 COVID stress and sleep disturbance among a racially/ethnically diverse sample of adolescents: Analysis from the NESTED study

Introduction

Using data from the Nationwide Education and Sleep in TEens During COVID (NESTED) study (N=6,578), we investigated if race/ethnicity (64.6% were White and 35.4% identified as a racial/ethnic minority, mixed, or “other”) and community social vulnerability affected the association between COVID stress and sleep disturbance.

Methods

Data on sociodemographic factors (age, race, sex, grade, zip code [for neighborhood social vulnerability index, SVI]), COVID-related stress, depression, anxiety, instructional format (online, in-person, or hybrid), and sleep disturbance (PROMIS Pediatric Sleep Disturbance) were captured through an online survey. Descriptive and inferential analyses (Hierarchical Binary Logistic Regression (HBLR), SPSS v. 25) in 4171 adolescents examined associations between sleep disturbance and COVID-related stress, adjusting for race, sex, SVI, grade level, learning format, household density, and mental health factors.

Results

Sleep disturbance was prevalent among adolescents (89% above average, T-score &gt;50); about two-thirds (64.4%) reported greater stress due to the pandemic. Compared to White (88.5%) adolescents, sleep disturbance was more common in Black (91.2%), Hispanic (90.5%), American Indian/Alaska native (95.1%), and Mixed (92.3%) and less common in Asian (83.9%) adolescents. Chi-square analysis indicated that both race/ethnicity (□2 = 14.96, p&lt;.05) and SVI (□2 = 8.34, p&lt;.05) had an effect on sleep disturbance. HBLR analysis indicated that compared to pre-pandemic, adolescents reporting “little stress” (OR=.70, 95% CI= .49-.99, p=.04) or “the “same amount of stress” (OR=.64, 95% CI= .47-.89, p=.007) had lower odds of sleep disturbance. Higher depression (OR=1.06, 95% CI=1.04-1.07, p&lt;.001) and anxiety (OR=1.05, 95% CI=1.04-1.07, p&lt;.001) symptoms increased odds of sleep disturbance, while male gender lowered odds of sleep disturbance (OR=.11, 95% CI=.015-.86, p&lt;.05). Overall, race/ethnicity (p=.44) and SVI (p=.45) did not independently predict sleep disturbance. Race/ethnicity stratified analyses indicated that for Black and Hispanic adolescents, being in grades 11/ 12 and depression predicted sleep disturbance; and for Asian adolescents SVI and anxiety predicted sleep disturbance.

Conclusion

COVID-related stress and symptoms of depression and anxiety are associated with sleep disturbance. We observed differences in sleep disturbance across racial/ethnic groups and neighborhood social vulnerability strata, for specific racial/ethnic groups.

Support (if any)

AS was supported by funding from the NIH (K01HL135452, R01HL152453)

638 Sleep and circadian markers of BMI in a diverse sample of 9-year old children from the Fragile Families Child and Wellbeing Study

Introduction

Hispanic and Black school-age children from low-income communities experience disproportionate rates of obesity (26% Hispanic, 22% Black) compared to their White counterparts (14%). Sleep patterns and circadian regulation of biological markers are associated with BMI status. However, little is known about racial and ethnic disparities in circadian regulation among children of color. These suggest that it is important to investigate biological markers that could help delineate associations between sleep-circadian regulation and obesity among children of color. Serotonin transporter gene, a neurotransmitter associated with circadian rhythm regulation, has emerged as an important biological variable. In this study, we investigated whether this factor could serve as a proxy for studying associations of circadian rhythm regulation with weight status in this diverse sample.

Methods

Statistical analysis included descriptive and linear regression analysis of the wave 5, Year 9 cohort of the Fragile Families Child and Wellbeing Study dataset. Interviews were conducted with the participant child around their ninth birthday for data collection on home routines and other parent relationship and school connectedness variables. Biological variables were derived from saliva samples at Year 9 to assess telomere length and DNA methylation levels and changes. Variables of interest included sleep duration, sleep timing, and biological variables 5httlpr (insomnia and sleep quality), skin 2 (serotonin transporter), telomere length (stress) and rs9939609 (fat mass and obesity), with BMI as the outcome.

Results

The final sample of 466 children comprised 52% male were 9 years old. Participants’ race was: 35% White, 46% Black, 20% Hispanic, 4% Asian and 5% other. Median family income was $42,500. Sleep duration obtained from these children was negatively associated with BMI (β = -0.245 with p=0.022). We found that gk5stin212 (serotonin transporter gene) was positively associated with BMI (β = 0.991, p = 0.009), while no significant associations was found for genetic variable gk5stin210.

Conclusion

Circadian rhythm dysregulation may serve as a biological mechanism driving overweight or obesity among minority children. Lifestyle and behavioral interventions aimed at the family unit may be needed to modify household and environmental factors that affect circadian regulation among children.

Support (if any)

NIH (T32HL129953), K07AG052685, R01MD007716, R01HL142066, K01HL135452, R01HL152453

684 Contribution of Pulmonary Diseases to COVID-19 Mortality in a Diverse Community of New York City

Introduction

New York City has been one of the largest epicenters of the COVID-19 pandemic. This provided a wealth of data to examine the characteristics of COVID-19 patients in this multi-ethnic city, while assessing the contributions of cardio-metabolic burden and pulmonary conditions as potential “at-risk” conditions for COVID-19. We assessed the relative contribution of common upper and lower airway pulmonary diseases in determining the likelihood of COVID-19-related mortality independent of other medical conditions, health risks, and sociodemographic factors.

Methods

We analyzed data from one of the largest US-based case series of patients with COVID-19, captured from an academic health network in NYC. A total of 11,512 hospitalized patients (March 2-May 24, 2020) were tested with 4,446 (38.62%) receiving a positive diagnosis for COVID-19. EHR queries yielded age at time of testing, sex, race/ethnicity aggregated as non-Hispanic black, Asian and Hispanic referenced to non-Hispanic white; cardio-metabolic conditions (hypertension, hyperlipidemia, diabetes, obesity, peripheral artery disease, and coronary artery disease); pulmonary disease (e.g., COPD, sleep apnea, or asthma); autoimmune disease; and cancer. Mortality was based on the patient state (alive or deceased) at the moment of discharge. We included only patients who had been discharged alive or had expired. Anaconda Python 3.7 was used to perform all analyses.

Results

Among patients testing positive, 959 (21.57%) died of COVID-19-related complications at the hospital. Multivariate-adjusted Cox proportional hazards modeling showed mortality risks were strongly associated with greater age (HR=1.05; 95%CI:1.04–1.05), ethnic minority (HR=1.26; 95%CI:1.10–1.44), low household income (HR=1.29; 95%CI:1.11, 1.49), and male sex (HR=0.85; 95%CI:0.74, 0.97). Higher mortality risks were also associated with a history of COPD (HR=1.27; 95%CI:1.02–1.58), obesity (HR=1.19; 95%CI:1.04–1.37) and peripheral artery disease (HR=1.33; 95%CI:1.05–1.69). We observed a significantly higher rate of COVID-19 cases (43.8% vs 39.6%, p<0.05) among patients with sleep apnea (7.72%). However, they did not have a significantly higher mortality rate (13.0% vs 11.8%, NS), although they experienced a longer hospital stay (7.1±7.7 vs 6.1±7.5, p<0.01).

Conclusion

Patients with COPD had the highest odds of COVID-19 mortality. Sociodemographic factors including increased age, male sex, low household income, ethnic minority status were also independently associated with greater mortality risks.

Support (if any)

K07AG052685, R01MD007716, R01HL142066, K01HL135452, R01HL152453

205 Changes in Sleep Due to COVID Pandemic Associated with Changes to Dietary Patterns

Introduction

The COVID-19 pandemic has affected sleep and diet for many people. The present study sought to examine potential associations between changes to sleep and eating habits during the COVID-19 pandemic.

Methods

A sample of N=419 US adults completed online surveys about sleep and COVID-19 experiences. Questions for diet asked, “since quarantine: I’m eating healthier, eating more processed foods, home-cooked meals and more regularly,” “I’m enjoying food in quarantine and I’m struggling with overeating in quarantine.” Sleep questions asked “since quarantine: I have managed to keep a regular sleep-wake schedule, my sleep has improved, I’m struggling to fall asleep, I’m waking up more during the night, I’m more sleepy during the day and I’m taking more naps during the day.” Answers were reported on a 4-point scale ranging from “strongly disagree to strongly agree.” Ordinal logistic regressions were used, adjusted for age and sex and examined each dietary variable as ordinal outcome and each sleep variable as predictor.

Results

Those who report that they kept a more regular schedule were more likely to report eating healthier (oOR=3.13, p=0.007), eating more home-cooked meals (oOR=3.19, p=0.005), and less likely to be eating more processed foods (oOR=0.39, p=0.02), struggle with overeating (oOR=0.39, p=0.02) or undereating (oOR=0.30, p=0.004) or snacking (oOR=0.25, p=0.001). Those reporting more difficulty falling asleep were less likely to be eating healthier (oOR=0.25, p=0.002) and more likely to be eating more processed foods (oOR=3.07, p=0.009) and snacking (oOr=2.36, P=0.04). Those reporting more difficulty with awakenings were less likely to report eating healthier (oOR=0.34, p=0.03) and more likely to report eating more processed foods (oOR=4.52, p=0.001). Those with more sleepiness were less likely to report eating healthier (oOR=0.29, p=0.01) and more homecooked meals (oOR=0.40, p=0.046) and more likely to report eating more processed foods (oOR=6.42, p<0.0005), overeating (oOR=3.63, p=0.01) and snacking (oOR=5.81, p=0.001).

Conclusion

Research studying psychological, behavioral and environmental factors that are contributing to changes in sleep and dietary patterns is especially important during a pandemic that has forced people into changes that they may not have been prepared for and which may result in long-term health outcomes.

Support (if any)

T32HL007249, R01MD011600, R01DA051321

211 Pandemic-Related Sleep Changes Associated with COVID-Related General, Financial, Food, Housing, Family and Relationship Stress

Introduction

The COVID-19 pandemic has caused widespread disruption and stress for people of all ages and circumstances around the world. This study investigates the relationship between general and specific stressors and various dimensions of sleep health.

Methods

A sample of N=419 US adults completed online surveys about sleep and COVID-19 experiences. Participants were asked whether they experienced increased general, financial, food, housing, family and relationship stress due to the COVID-19 pandemic. They were also asked whether they experienced a more regular schedule, improved sleep, worsened sleep, more early insomnia, more middle-of-the-night insomnia, more daytime sleepiness, and more naps due to the COVID-19 pandemic. Ordinal logistic regressions with sleep change as outcome and stress variable as predictor were adjusted for age, sex, and race/ethnicity.

Results

COVID-19-related general, financial, food, housing, family, and relationship stress were all associated with a decreased likelihood of maintaining a more regular schedule (oOR=0.52-0.67, all p&lt;0.001) and improved sleep (oOR=0.56-0.67, all p&lt;0.001). They were also all associated with a greater likelihood of worsened sleep (oOR=1.48-2.41, all p&lt;0.001), early insomnia (oOR=1.63-1.85, all p&lt;0.001), middle-of-the-night insomnia (oOR=1.40-2.00, all p&lt;0.001), and daytime sleepiness (oOR=1.58-2.07, all p&lt;0.001). Increased napping was also associated with more COVID-related financial, food, and housing stress (oOR=1.33-1.55, all p&lt;0.005).

Conclusion

Regular sleep schedules can be disrupted by stressors directly, or by the anxiety that so often accompanies stress. Stressed individuals may experience increased difficulty falling asleep, or more nighttime arousals, or find themselves waking up earlier than usual, all as a result of ruminating thoughts, stress-induced nightmares, or outside disturbances. Disruption to sleep at night often results in increased daytime sleepiness and fatigue, with a higher chance of napping. This study reports the significant association of some of these with COVID-19 pandemic-related stress. More individuals now find themselves working from home with greater flexibility in their schedules, but this has not necessarily led to better sleep. The impact of the pandemic on various health outcomes as a result of stress is still to be revealed.

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