Impact of reduced group size on patient adherence and functional outcomes in cardiac rehabilitation: insights from a COVID-19 pandemic natural experiment

Introduction

Cardiac rehabilitation (CR) adherence and functional outcomes were measured after COVID-19 regulations reduced group sizes to one-on-one, modeling a natural experiment.

Methods

A retrospective analysis using a natural experiment model measured participants in 12 weeks of CR during the 17 months before and after a COVID-19-related closure was conducted. The age, sex, race, ethnicity, and referral diagnoses of the pre-COVID-19 closure and post-COVID-19 closure groups were analyzed using a student's unpaired T-test. Adherence (completion rate of CR) and functional outcomes [change in six-minute walk test (6MWT)] were assessed between the two groups using unpaired two-tailed student T tests in GraphPad Prism and confidence intervals were calculated with the Baptista-Pike method.

Results

There were 204 patients in the pre-COVID-19 group and 51 patients in the post-COVID-19 group, due to the smaller group sizes in the post-COVID-19 group, with no significant differences in baseline characteristics between the groups. The pre-COVID-19 group had a higher patient-to-provider ratio [2.8 patients/provider (SD 0.74)] relative to the post-COVID-19 group [0.4 patients/provider (SD 0.12); p < 0.0001]. The post-COVID-19 group had a higher completion rate than pre-COVID-19 group [75% vs. 21%; OR 10.9 (95% CI, 5.3-21.3, p < 0.0001)]. Among those that completed CR, there was no significant difference between groups in 6MWT improvement [+377.9 ft. (n = 47; SD 275.67 ft.) vs. +346.9 ft. (n = 38; SD 196.27 ft.); p = 0.59].

Discussion

The reduction in group size to one-on-one was associated with 10 times higher odds of CR completion. Among those that completed CR, functional outcomes were not influenced by group size. Thus, pursuit of one-on-one sessions may improve CR adherence.

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.

Photovoice for leveraging traditional, complementary, and integrative medicine amongst black adults to improve sleep health and overall health

Introduction

Average adults are recommended to have 7-8 h of sleep. However insufficient sleep (IS defined as <7 h/nightly) is associated with increased risk of chronic diseases such as cardiovascular disease (CVD) and type 2 diabetes mellitus (T2DM). Traditional, complementary, and integrative medicine (TCIM), a burgeoning area of research and practice, leverages both modern and traditional approaches to improve health. Despite TCIM's recognition as a tool to improve sleep and related outcomes, there is a gap in literature in addressing its impact among black individuals, who experience a disproportionate burden of IS and chronic disease. This qualitative study aimed to increase understanding of TCIM practices to overcome IS and overall health in black communities.

Methods

Using photovoice methodology, a qualitative tool which applies community-engaged principles to produce culturally informed results through interviews and digital media, consented participants were recruited from Miami, Florida and (1) instructed to capture images over one week that communicated their TCIM to improve sleep and overall health on their mobile device; (2) interviewed using individual, semi-structured procedures to add "voice" to the "photos" they captured for ~20 min; and (3) invited to participate in follow-up focus groups for refined discussion and data triangulation for ~1.5 h. Both individual and focus group interviews were conducted over Zoom with recordings transcribed for formal content analysis using Nvivo software.

Results

The sample included N = 25 diverse US black individuals (M = 37, SD = 13, range 21-57). Approximately a quarter of the sample were unemployed (N = 7) and majority were women (N = 21). Results highlighted five themes including: (1) natural wellness (sleep supplements, comfort beverages, aromatherapy, herbalism, outdoors); (2) self-care (self-maintenance, physical activity, spatial comfort); (3) leisure (pet support, play); (4) mental stimulation (mindfulness, reading); and (5) spiritual wellness (faith-based practices). Study results elucidate the heterogeneity of diverse US black individuals regarding sociocultural knowledge, beliefs, and behaviors.

Conclusion

Addressing IS in black communities requires a comprehensive strategy that integrates cultural sensitivity, family and community dynamics, education, mental health support, and informed policymaking. Future studies should consider how sleep health literacy, stress appraisal, and coping strategies may vary by race/ethnicity for tailored intervention.

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 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 3 pivotal areas in sleep medicine that 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.

CITATION

Bandyopadhyay A, Oks M, Sun H, et al. Strengths, weaknesses, opportunities, and threats of using AI-enabled technology in sleep medicine: a commentary. J Clin Sleep Med. 2024;20(7):1183-1191.

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.

Cardiovascular disease risk: it is complicated, but race and ethnicity are key, a Bayesian network analysis

Background

Cardiovascular diseases are the leading cause of morbidity and mortality in the United States. Despite the complexity of cardiovascular disease etiology, we do not fully comprehend the interactions between non-modifiable factors (e.g., age, sex, and race) and modifiable risk factors (e.g., health behaviors and occupational exposures).

Objective

We examined proximal and distal drivers of cardiovascular disease and elucidated the interactions between modifiable and non-modifiable risk factors.

Methods

We used a machine learning approach on four cohorts (2005-2012) of the National Health and Nutrition Examination Survey data to examine the effects of risk factors on cardiovascular risk quantified by the Framingham Risk Score (FRS) and the Pooled Cohort Equations (PCE). We estimated a network of risk factors, computed their strength centrality, closeness, and betweenness centrality, and computed a Bayesian network embodied in a directed acyclic graph.

Results

In addition to traditional factors such as body mass index and physical activity, race and ethnicity and exposure to heavy metals are the most adjacent drivers of PCE. In addition to the factors directly affecting PCE, sleep complaints had an immediate adverse effect on FRS. Exposure to heavy metals is the link between race and ethnicity and FRS.

Conclusion

Heavy metal exposures and race/ethnicity have similar proximal effects on cardiovascular disease risk as traditional clinical and lifestyle risk factors, such as physical activity and body mass. Our findings support the inclusion of diverse racial and ethnic groups in all cardiovascular research and the consideration of the social environment in clinical decision-making.

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.

I am Lifted Above the World: utilizing VR for stress reduction among perinatal women of color

Background

Perinatal mental health conditions affect 800,000 individuals annually in the United States and are a leading cause of complications in pregnancy and childbirth. However, the impact of these conditions varies across racial and ethnic groups. Portable digital solutions, such as mobile apps, have been developed for maternal mental health, but they often do not adequately cater to the needs of women of color. To ensure the effectiveness and equity of these interventions, it is crucial to consider the unique experiences of perinatal women from diverse racial backgrounds. This qualitative study aims to explore the complex aspects of motherhood, maternal mental well-being, and resilience among perinatal women of color. It also investigates the factors that either hinder or facilitate the use of Virtual Reality (VR) for stress management in this specific demographic.

Methods

This research involves two focus groups comprising perinatal women, primarily identifying as Black or Latina, enrolled in the ongoing Nurturing Moms study at the University of Miami Miller School of Medicine. Additionally, feedback is collected from five different participants. The study assesses Nurture VR™, a VR-based program integrating mindfulness techniques, relaxation exercises, and guided imagery for pregnancy and postpartum.

Results

Qualitative analysis uncovers five primary themes and 19 sub-themes, addressing the complexities of motherhood, maternal mental health, attitudes towards VR therapy, postpartum care, and the perception of resilience. Participants share challenges related to household management, caregiving, financial stress, breastfeeding, relaxation, sleep, and the significance of social support. Their preferences and reservations regarding VR therapy are also expressed.

Conclusion

This study sheds light on the diverse struggles and obstacles faced by women of color during and after pregnancy, with potential repercussions for their mental and sleep health. It underscores the need for mental health screening and analysis of maternal stress-related sleep issues, in addition to the facilitation of social support in maternal health programs. Additionally, it highlights the promise of culturally responsive behavioral treatments, including VR interventions, in offering timely and tailored mental health support to perinatal women, taking into account their intersectional identities.

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.

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.

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.

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.

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.

Development and Evaluation of the Clinical Trial HEalth Knowledge and Beliefs Scale (CHEKS)

Patient health literacy is vital to clinical trial engagement. Knowledge and beliefs about clinical trials may contribute to patient literacy of clinical trials, influencing engagement, enrollment and retention. We developed and assessed a survey that measures clinical trial health knowledge and beliefs, known as the Clinical trial HEalth Knowledge and belief Scale (CHEKS). The 31 survey items in CHEKS represent knowledge and beliefs about clinical trial research (n = 409) in 2017. We examined item-scale correlations for the 31 items, eliminated items with item-scale correlations less than 0.30, and then estimated internal consistency reliability for the remaining 25 items. We used the comparative fit index (CFI) and the root mean squared error of approximation (RMSEA) to evaluate model fit. The average age of the sample was 34 (SD = 15.7) and 48% female. We identified 6 of the 31 items that had item-scale correlations (corrected for overlap) lower than 0.30. Coefficient alpha for the remaining 25 items was 0.93 A one-factor categorical confirmatory factor analytic model with 16 correlated errors was not statistically significant (chi-square = 10011.994, df = 300, p < 0.001) but fit the data well (CFI = 0.95 and RMSEA = 0.07). CHEKS can assess clinical trial knowledge and beliefs.

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.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13167-022-00284-3.

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)