Multidimensional sleep health domains in older men and women: an actigraphy factor analysis

Associations Between Repetitive Negative Thinking and Objective and Subjective Sleep Health in Cognitively Healthy Older Adults

Objective

Poor sleep and high levels of repetitive negative thinking (RNT), including future-directed (ie, worry) and past-directed (ie, brooding) negative thoughts, have been associated with markers of dementia risk. The relationship between RNT and sleep health in older adults is unknown. This study aimed to investigate this association and its specificities including multiple dimensions of objective and subjective sleep.

Methods

This study used a cross sectional quantitative design with baseline data from 127 cognitively healthy older adults (mean age 69.4 ± 3.8 years; 63% female) who took part in the Age-Well clinical trial, France. RNT (ie, worry and brooding) levels were measured using the Penn State Worry Questionnaire and the Rumination Response Scale (brooding subscale). Polysomnography was used to assess sleep objectively, and the Pittsburgh Sleep Quality Index and the St. Mary's Hospital Sleep Questionnaire were used to measure sleep subjectively. In primary analyses the associations between RNT and sleep (ie, objective sleep duration, fragmentation and efficiency and subjective sleep disturbance) were assessed via adjusted regressions.

Results

Higher levels of RNT were associated with poorer objective sleep efficiency (worry: β=-0.32, p<0.001; brooding: β=-0.26, p=0.002), but not objective sleep duration, fragmentation, or subjective sleep disturbance. Additional analyses, however, revealed differences in levels of worry between those with short, compared with typical and long objective sleep durations (p < 0.05).

Conclusion

In cognitively healthy older adults, RNT was associated with sleep characteristics that have been implicated in increased dementia risk. It will take additional research to ascertain the causal link between RNT and sleep characteristics and how they ultimately relate to the risk of developing dementia.

Effects of sleep on breakfast behaviors in recently unemployed adults

OBJECTIVES

Skipping meals is linked to negative cardiometabolic health outcomes. Few studies have examined the effects of breakfast skipping after disruptive life events, like job loss. The present analyses examine whether sleep timing, duration, and continuity are associated with breakfast eating among 186 adults who recently (past 90 days) experienced involuntary unemployment from the Assessing Daily Activity Patterns Through Occupational Transitions (ADAPT) study.

METHODS

We conducted both cross-sectional and 18-month longitudinal analyses to assess the relationship between actigraphic sleep after job loss and breakfast eating.

RESULTS

Later sleep timing was associated with a lower percentage of days breakfast was eaten at baseline (B = -0.09, SE = 0.02, P < .001) and longitudinally over 18 months (estimate = -0.04; SE = 0.02; P < .05). No other sleep indices were associated with breakfast consumption cross-sectionally or prospectively.

CONCLUSIONS

Unemployed adults with a delay in sleep timing are more likely to skip breakfast than adults with an advancement in sleep timing. Future studies are necessary to test chronobiological mechanisms by which sleep timing might impact breakfast eating. With the understanding that sleep timing is linked to breakfast eating, the advancement of sleep timing may provide a pathway for the promotion of breakfast eating, ultimately preventing cardiometabolic disease.

Sleep deficiency among people living with human immunodeficiency virus: A growing challenge

PURPOSE OF REVIEW

The purpose of this narrative review is to consolidate and summarize the existing literature on sleep deficiency among people living with human immunodeficiency virus (HIV; PLWH), to discuss the potential impact of antiretroviral therapy on sleep deficiency and to identify priorities for future research in this area.

RECENT FINDINGS

Three important domains of sleep deficiency include alterations in sleep quality (including sleep disorders), duration and timing. The existing HIV and sleep deficiency literature, which is robust for sleep quality but sparser for sleep duration or sleep timing, has identified epidemiological correlates and outcomes associated with sleep deficiency including sociodemographic factors, HIV-specific factors, aspects of physical and mental health and cognition.

SUMMARY

Sleep deficiency is a common problem among PLWH and is likely underdiagnosed, although more high-quality research is needed in this area. Sleep quality has received the most attention in the literature via methodologies that assess subjective/self-reported sleep quality, objective sleep quality or both. There is significantly less research on sleep duration and minimal research on sleep timing. Use of certain antiretroviral therapy drugs may be associated with sleep deficiency for some individuals. Future research should utilize larger, longitudinal studies with consistent, comprehensive and validated methods to assess both subjective and objective measures of sleep deficiency to better understand the prevalence, correlates and clinical implications of sleep deficiency in PLWH.

Race and sex differences in the longitudinal changes in multidimensional self-reported sleep health characteristics in aging older adults

OBJECTIVES

We examined within-individual changes in self-reported sleep health as community-dwelling older adults age as well as potential differences in these changes by self-reported sex and racial identity.

METHODS

Participants were from the United States and enrolled in the Rush Memory and Aging Project, Minority Aging Research Study, or Religious Orders Study (N = 3539, 20% Black, 75% female, mean 78years [range 65-103]), and they received annual, in-person clinical evaluations (median 5 visits [range 1-27]). A sleep health composite score measured the number of poor sleep characteristics among satisfaction, daytime sleepiness, efficiency, and duration. Mixed effects models estimated associations of age, race, sex, and their interactions on the composite and individual sleep measures, accounting for key confounders.

RESULTS

As they aged, Black participants shifted from reporting two poor sleep characteristics to one poor sleep characteristic, while White participants shifted from one poor characteristic to two. Regardless of age, sex, and race, participants reported that they "often" felt satisfied with their sleep and "sometimes" had trouble staying asleep. Females over age 85 and males of all ages reported the most daytime sleepiness, and older White participants (>age 90) reported the most difficulty falling asleep.

CONCLUSIONS

Although self-reported sleep characteristics were typically stable across age, identifying race and sex differences in self-reported sleep health can help guide future research to understand the mechanisms that underlie these differences.

The association between different sleep health dimensions and sex, age, education, circadian preference, and chronic insomnia: a representative population-based study

Objectives

The aims were to explore multidimensional sleep health and the different dimensions of sleep health in the adult Norwegian population in relation to sex, age, education, circadian preference, and chronic insomnia.

Methods

A representative sample of 1028 Norwegians, aged 18 + years completed a cross-sectional web-based survey. Sleep health was measured with the multidimensional RU_SATED scale, which assesses the dimensions of regularity, satisfaction, alertness, timing, efficiency, and duration. Insomnia was assessed with the Bergen Insomnia Scale. Data were analyzed with chi-square tests, t-tests, one-way ANOVAs, and regression analyses, as appropriate. Response rate was 33.5%.

Results

Sleep health was better in males, with increasing age, and with higher educational level, and was poorer in participants with evening preference and chronic insomnia, compared to their respective counterparts. When investigating the different sleep health dimensions, males scored better than females on satisfaction (adjusted odds ratio [aOR] = 0.69, 95% CI = 0.51 to 0.93), timing (aOR = 0.66, 95% CI = 0.49 to 0.88), and efficiency (aOR = 0.68, 95% CI = 0.52 to 0.89). Older age was associated with better scores on regularity and satisfaction, whereas young age was associated with better scores on alertness and duration. High educational level was associated with better scores on alertness, timing, and duration. Evening types scored worse than morning types on regularity (aOR = 0.27, 95% CI = 0.18 to 0.41), satisfaction (aOR = 0.37, 95% CI = 0.26 to 0.53), and timing (aOR = 0.36, 95% CI = 0.26 to 0.51). Participants with chronic insomnia scored worse than participants without insomnia on all six sleep health dimensions.

Conclusions

Sleep health differed significantly in relation to sex, age, education, circadian preference, and chronic insomnia. However, specific group differences were not equally evident in all sleep health dimensions.

Detection of Medication Taking Using a Wrist-Worn Commercially Available Wearable Device

PURPOSE

Medication nonadherence is a persistent and costly problem across health care. Measures of medication adherence are ineffective. Methods such as self-report, prescription claims data, or smart pill bottles have been used to monitor medication adherence, but these are subject to recall bias, lack real-time feedback, and are often expensive.

METHODS

We proposed a method for monitoring medication adherence using a commercially available wearable device. Passively collected motion data were analyzed on the basis of the Movelet algorithm, a dictionary learning framework that builds person-specific chapters of movements from short frames of elemental activities within the movements. We adapted and extended the Movelet method to construct a within-patient prediction model that identifies medication-taking behaviors.

RESULTS

Using 15 activity features recorded from wrist-worn wearable devices of 10 patients with breast cancer on endocrine therapy, we demonstrated that medication-taking behavior can be predicted in a controlled clinical environment with a median accuracy of 85%.

CONCLUSION

These results in a patient-specific population are exemplar of the potential to measure real-time medication adherence using a wrist-worn commercially available wearable device.

The association between multidimensional sleep health and gestational weight gain

BACKGROUND

Although poor sleep health is associated with weight gain and obesity in the non-pregnant population, research on the impact of sleep health on weight change among pregnant people using a multidimensional sleep health framework is needed.

OBJECTIVES

This secondary data analysis of the Nulliparous Pregnancy Outcome Study: Monitoring Mothers-to-be Sleep Duration and Continuity Study (n = 745) examined associations between mid-pregnancy sleep health indicators, multidimensional sleep health and gestational weight gain (GWG).

METHODS

Sleep domains (i.e. regularity, nap duration, timing, efficiency and duration) were assessed via actigraphy between 16 and 21 weeks of gestation. We defined 'healthy' sleep in each domain with empirical thresholds. Multidimensional sleep health was based on sleep profiles derived from latent class analysis and composite score defined as the sum of healthy sleep domains. Total GWG, the difference between self-reported pre-pregnancy weight and the last measured weight before delivery, was converted to z-scores using gestational age- and BMI-specific charts. GWG was defined as low (<-1 SD), moderate (-1 or +1 SD) and high (>+1 SD).

RESULTS

Nearly 50% of the participants had a healthy sleep profile (i.e. healthy sleep in most domains), whereas others had a sleep profile defined as having varying degrees of unhealthy sleep in each domain. The individual sleep domains were associated with a 20%-30% lower risk of low or high GWG. Each additional healthy sleep indicator was associated with a 10% lower risk of low (vs. moderate), but not high, GWG. Participants with late timing, long duration and low efficiency (vs. healthy) profiles had the strongest risk of low GWG (relative risk 1.5, 95% confidence interval 0.9, 2.4). Probabilistic bias analysis suggested that most associations between individual sleep health indicators, sleep health profiles and GWG were biased towards the null.

CONCLUSIONS

Future research should determine whether sleep health is an intervention target for healthy GWG.

Dawn of a New Dawn: Advances in Sleep Health to Optimize Performance

Optimal sleep health is a critical component to high-level performance. In populations such as the military, public service (eg, firefighters), and health care, achieving optimal sleep health is difficult and subsequently deficiencies in sleep health may lead to performance decrements. However, advances in sleep monitoring technologies and mitigation strategies for poor sleep health show promise for further ecological scientific investigation within these populations. The current review briefly outlines the relationship between sleep health and performance as well as current advances in behavioral and technological approaches to improving sleep health for performance.

Sleep Health at the Genomic Level: Six Distinct Factors and Their Relationships With Psychopathology

Background

Poor sleep is associated with many negative health outcomes, including multiple dimensions of psychopathology. In the past decade, sleep researchers have advocated for focusing on the concept of sleep health as a modifiable health behavior to mitigate or prevent these outcomes. Sleep health dimensions often include sleep efficiency, duration, satisfaction, regularity, timing, and daytime alertness. However, there is no consensus on how to best operationalize sleep health at the phenotypic and genetic levels. In some studies, specific sleep health domains were examined individually, while in others, sleep health domains were examined together (e.g., with an aggregate sleep health score).

Methods

Here, we compared alternative sleep health factor models using genomic structural equation modeling on summary statistics from previously published genome-wide association studies of self-reported and actigraphic sleep measures with effective sample sizes up to 452,633.

Results

Our best-fitting sleep health model had 6 correlated genetic factors pertaining to 6 sleep health domains: circadian preference, efficiency, alertness, duration, noninsomnia, and regularity. All sleep health factors were significantly correlated (|rgs| = 0.11-0.51), except for the circadian preference factor with duration and noninsomnia. Better sleep health was generally significantly associated with lower genetic liability for psychopathology (|rgs| = 0.05-0.48), yet the 6 sleep health factors showed divergent patterns of associations with different psychopathology factors, especially when controlling for covariance among the sleep health factors.

Conclusions

These results provide evidence for genetic separability of sleep health constructs and their differentiation with respect to associations with mental health.

The Good Sleeper Scale-15 items: a questionnaire for the standardised assessment of good sleepers

Research with 'good sleepers' is ubiquitous, yet there are no standardised criteria to identify a 'good sleeper'. The present study aimed to create and validate a questionnaire for identifying good sleepers for use in research studies known as the Good Sleeper Scale-15 items (GSS-15). Data were derived from a population-based survey of Australian adults (n = 2,044). A total of 23 items were chosen for possible inclusion. An exploratory factor analysis (EFA) was conducted on ~10% of the survey dataset (n = 191) for factor identification and item reduction. A confirmatory factor analysis (CFA) was conducted on the remaining data (n = 1,853) to test model fit. Receiver operating characteristic curves and correlations were conducted to derive cut-off scores and test associations with sleep, daytime functioning, health, and quality-of-life. The EFA identified six factors: 'Sleep Difficulties', 'Timing', 'Duration', 'Regularity', 'Adequacy', and 'Perceived Sleep Problem'. The CFA showed that model fit was high and comparable to other sleep instruments, χ² (63) = 378.22, p < 0.001, root mean square error of approximation = 0.05, with acceptable internal consistency (α = 0.76). Strong correlations were consistently found between GSS-15 global scores and outcomes, including 'a good night's sleep' (r = 0.7), 'feeling un-refreshed' (r = -0.59), and 'experienced sleepiness' (r = -0.51), p < 0.001. Cut-off scores were derived to categorise individuals likely to be a good sleeper (GSS-15 score ≥40) and those very likely to be a good sleeper (GSS-15 score ≥45). The GSS-15 is a freely available, robust questionnaire that will assist in identifying good sleepers for the purpose of sleep research. Future work will test relationships with other sleep measures in community and clinical samples.

Discrimination and Education Quality Moderate the Association of Sleep With Cognitive Function in Older Black Adults: Results From the Einstein Aging Study

OBJECTIVES

Heterogeneity among Black adults' experiences of discrimination and education quality independently influence cognitive function and sleep, and may also influence the extent to which sleep is related to cognitive function. We investigated the effect of discrimination on the relationship between objective sleep characteristics and cognitive function in older Black adults with varying education quality.

METHOD

Cross-sectional analyses include Black participants in the Einstein Aging Study (N = 104, mean age = 77.2 years, 21% males). Sleep measures were calculated from wrist actigraphy (15.4 ± 1.3 days). Mean ambulatory cognitive function (i.e., spatial working memory, processing speed/visual attention, and short-term memory binding) was assessed with validated smartphone-based cognitive tests (6 daily). A modified Williams Everyday Discrimination Scale measured discriminatory experiences. Linear regression, stratified by reading literacy (an indicator of education quality), was conducted to investigate whether discrimination moderated associations between sleep and ambulatory cognitive function for individuals with varying reading literacy levels. Models controlled for age, income, sleep-disordered breathing, and sex assigned at birth.

RESULTS

Higher reading literacy was associated with better cognitive performance. For participants with both lower reading literacy and more discriminatory experiences, longer mean sleep time was associated with slower processing speed, and lower sleep quality was associated with worse working memory. Later sleep midpoint and longer nighttime sleep were associated with worse spatial working memory for participants with low reading literacy, independent of their discriminatory experiences.

DISCUSSION

Sociocultural factors (i.e., discrimination and education quality) can further explain the association between sleep and cognitive functioning and cognitive impairment risk among older Black adults.

Sleep timing, sleep regularity, and psychological health in early late life women: Findings from the Study of Women's Health Across the Nation (SWAN)

OBJECTIVES

To examine the associations of actigraphy-assessed sleep timing and regularity with psychological health in early late life women, whose circadian rhythms may be impacted by aging.

DESIGN

Cross-sectional.

PARTICIPANTS

A racially/ethnically diverse sample of 1197 community-dwelling women (mean age 65 years) enrolled in the Study of Women's Health Across the Nation.

MEASURES

Actigraphy-assessed sleep measures included timing (mean midpoint from sleep onset to wake-up) and regularity (standard deviation of midpoint in hours). Psychological health measures included a composite well-being score, the Center for Epidemiological Studies Depression Scale, and the Generalized Anxiety Disorder-7 Scale. Linear and logistic regression models, adjusted for covariates (including sleep duration), tested associations between sleep and psychological health measures.

RESULTS

After covariate adjustment, a sleep midpoint outside of 2:00-4: 00 AM was significantly associated with depressive symptoms (β = 0.88, 95% CI = 0.06, 1.70) and scoring above the cut-point for clinically significant depressive symptoms (OR = 1.72, 95% CI = 1.15, 2.57). Sleep irregularity was significantly associated with lower psychological well-being (β = -0.18, 95% CI = -0.33, -0.03), depressive (β = 1.36, 95% CI = 0.29, 2.44) and anxiety (β = 0.93, 95% CI = 0.40, 1.46) symptoms, and scoring above the cut-point for clinically significant depressive (OR = 1.68, 95% CI = 1.01, 2.79) and anxiety (OR = 1.62, 95% CI = 1.07, 2.43) symptoms.

CONCLUSION

Above and beyond sleep duration, a sleep midpoint outside of 2:00-4:00 AM was associated with depressive symptoms while sleep irregularity was associated with multiple psychological health domains in late life women.

Emotional Exhaustion, a Proxy for Burnout, Is Associated with Sleep Health in French Healthcare Workers without Anxiety or Depressive Symptoms: A Cross-Sectional Study

Burnout is frequent among healthcare workers, and sleep problems are suspected risk factors. The sleep health framework provides a new approach to the promotion of sleep as a health benefit. The aim of this study was to assess good sleep health in a large sample of healthcare workers and to investigate its relationship with the absence of burnout among healthcare workers while considering anxiety and depressive symptoms. A cross-sectional Internet-based survey of French healthcare workers was conducted in summer 2020, at the end of the first COVID-19 lockdown in France (March to May 2020). Sleep health was assessed using the RU-SATED v2.0 scale (RegUlarity, Satisfaction, Alertness, Timing, Efficiency, Duration). Emotional exhaustion was used as a proxy for overall burnout. Of 1069 participating French healthcare workers, 474 (44.3%) reported good sleep health (RU-SATED > 8) and 143 (13.4%) reported emotional exhaustion. Males and nurses had a lower likelihood of emotional exhaustion than females and physicians, respectively. Good sleep health was associated with a 2.5-fold lower likelihood of emotional exhaustion and associations persisted among healthcare workers without significant anxiety and depressive symptoms. Longitudinal studies are needed to explore the preventive role of sleep health promotion in terms of the reduction in burnout risk.

The association between multidimensional sleep health and gestational weight gain: nuMoM2b Sleep Duration and Continuity Study

Background

Although poor sleep health is associated with weight gain and obesity in the non-pregnant population, research on the impact of sleep health on weight change among pregnant people using a multidimensional sleep-health framework is needed. This study examined associations among mid-pregnancy sleep health indicators, multidimensional sleep health, and gestational weight gain (GWG).

Methods

We conducted a secondary data analysis of the Nulliparous Pregnancy Outcome Study: Monitoring Mothers-to-be Sleep Duration and Continuity Study (n=745). Indicators of individual sleep domains (i.e., regularity, nap duration, timing, efficiency, and duration) were assessed via actigraphy between 16 and 21 weeks of gestation. We defined "healthy" sleep in each domain based on empirical thresholds. Multidimensional sleep health was based on sleep profiles derived from latent class analysis. Total GWG, the difference between self-reported pre-pregnancy weight and the last measured weight before delivery, was converted to z-scores using gestational age- and BMI-specific charts. GWG was defined as low (<-1 SD), moderate (-1 or +1 SD), and high (>+1 SD).

Results

Nearly 50% of the participants had a healthy sleep profile (i.e., healthy sleep in most domains), whereas others had a sleep profile defined as having varying degrees of poor health in each domain. While indicators of individual sleep domains were not associated with GWG, multidimensional sleep health was related to low and high GWG. Participants with a sleep profile characterized as having low efficiency, late timing, and long sleep duration (vs. healthy sleep profile) had a higher risk (RR 1.7; 95% CI 1.0, 3.1) of low GWG a lower risk of high GWG (RR 0.5 95% CI 0.2, 1.1) (vs. moderate GWG).

Conclusions

Multidimensional sleep health was more strongly associated with GWG than individual sleep domains. Future research should determine whether sleep health is a valuable intervention target for optimizing GWG.

Synopsis

Study question: What is the association between mid-pregnancy multidimensional sleep health and gestational weight gain?What's already known?: Sleep is associated with weight and weight gain outside of pregnancyWhat does this study add?: We identified patterns of sleep behaviors associated with an increased risk of low gestational weight gain.

The association between multidimensional sleep health and migraine burden among patients with episodic migraine

STUDY OBJECTIVES

Using the Sleep Regularity, Satisfaction, Alertness, Timing, Satisfaction, and Duration (Ru-SATED) sleep health framework, we examined the association between multidimensional sleep health and headache burden in a cohort of 98 adults with episodic migraine.

METHODS

Participants wore wrist actigraphs and completed twice-daily electronic diaries regarding sleep, headaches, and other health habits for 6 weeks. We calculated separate composite sleep health scores from diary and actigraphy assessed measures using the Ru-SATED framework. We used adjusted multivariable linear regression models to examine the association between composite sleep health scores and headache frequency, duration, and pain intensity.

RESULTS

Among 98 participants (mean age: 35 ± 12 years; 87.8% female), 83 had healthy ranges in ≥ 3 sleep dimensions. In models adjusted for age, sex, menopausal status, physical activity and alcohol intake, good sleep health was associated with fewer headache days/month (actigraphy: 3.1 fewer days; 95% confidence interval: 0.9, 5.7; diary: 4.0 fewer days; 95% confidence interval: 1.1, 6.9). Results did not change substantively with further adjustment for stress and depressive symptoms. We did not observe an association between sleep health and headache duration or intensity, respectively.

CONCLUSIONS

Among patients with episodic migraine, good multidimensional sleep health, but not the majority of singular dimensions of sleep, is associated with approximately 3-4 fewer headache days/month. In addition, there was no association with headache duration or intensity. These findings highlight the importance of assessing multiple dimensions of sleep and suggest that improving sleep health may be a potential clinical strategy to reduce headache frequency.

CITATION

Yoo A, Vgontzas A, Chung J, et al. The association between multidimensional sleep health and migraine burden among patients with episodic migraine. J Clin Sleep Med. 2023;19(2):309-317.

Cross-cultural adaptation and validation of the Chinese version of the Sleep Health Index

OBJECTIVE

To generate the Chinese Sleep Health Index (SHI-C) in Mandarin with cross-cultural adaptations and test its psychometric properties.

METHODS

This study used a cross-sectional design. Health science students were included (N = 271) and a sub-set (n = 74) was invited for the re-test. Cross-cultural adaptation of the SHI-C was performed prior to formal validation. The SHI-C, Pittsburgh Sleep Quality Index (PSQI), Insomnia Severity Index (ISI), Bedtime Procrastination Scale, and Sleep Hygiene Index were used to measure variables of interest. Exploratory factor analysis was used to evaluate the structure validity. Bivariate analyses were used to evaluate the construct validity.

RESULTS

Exploratory factor analysis identified 3 factors (ie, sleep quality, sleep duration, and disordered sleep) accounting for 55.6% of the total variance. The SHI-C total and sleep quality sub-index scores were significantly associated with both PSQI global score (r = -0.132, p < .05; r = -0.182, p < .01, respectively) and ISI score (r = -0.655, p < .05; r = -0.820, p < .05, respectively). SHI-C total, sleep quality sub-index, and sleep duration sub-index scores were significantly associated with Bedtime Procrastination Scale and Sleep Hygiene Index scores (r = -0.238 to -0.368, p < .05). Students with insomnia (ISI > 9) or poor sleep quality (PSQI > 5) had significantly lower SHI-C scores than those without (73.5 vs. 89.0, p < .01; 84.1 vs. 86.7, p < .05, respectively). SHI-C showed good internal consistency (Cronbach's alpha = 0.73) and test-retest reliability (intraclass correlation coefficient = 0.82).

CONCLUSIONS

The SHI-C demonstrated good validity and adequate reliability in a Chinese sample of health science students. It could be used to measure sleep health in future research and practice. Psychometric properties of the SHI-C among other Chinese populations remain to be confirmed.

Preliminary Evidence for the Sequentially Mediated Effect of Racism-Related Stress on Pain Sensitivity Through Sleep Disturbance and Corticolimbic Opioid Receptor Function

Sleep disturbance predicts worse pain outcomes. Because sleep disturbance inequitably impacts Black adults - with racism as the upstream cause - understanding how racism-related stress impacts pain through sleep might help minimize racialized pain inequities. This preliminary study examined sequential mediation of the effect of racism-related stress on experimental pain through sleep disturbance and corticolimbic μOR function in pain-free non-Hispanic Black (NHB) and White (NHW) adults. Participants completed questionnaires, actigraphy, positron emission tomography, and sensory testing. We reproduced findings showing greater sleep disturbance and pain sensitivity among NHB participants; greater sleep disturbance (r = .35) and lower pain tolerance (r=-.37) were significantly associated with greater racism-related stress. In a sequential mediation model, the total effect of racism-related stress on pain tolerance (β=-.38, P = .005) weakened after adding sleep disturbance and ventromedial prefrontal cortex (vmPFC) μOR binding potential (BPND) as mediators (β = -.18, P = .16). The indirect effect was statistically significant [point estimate = -.003, (-.007, -.0003). Findings showed a potential sequentially mediated effect of racism-related stress on pain sensitivity through sleep disturbance and vmPFC μOR BPND. As policy efforts are enacted to eliminate the upstream cause of systemic racism, these results cautiously suggest that sleep interventions within racism-based trauma informed therapy might help prevent downstream effects on pain. PERSPECTIVE: This preliminary study identified the effect of racism-related stress on pain through sleep disturbance and mu-opioid receptor binding potential in the ventromedial prefrontal cortex. Findings cautiously support the application of sleep interventions within racism-based trauma-informed therapy to prevent pain inequities as policy changes function to eliminate all levels of racism.

Sleep and Circadian Disturbance in Cardiovascular Risk

PURPOSE OF REVIEW

We discuss the relationship between sleep and circadian factors with cardiovascular disease (CVD) risk, including physiologic, behavioral, and psychological mechanisms along this pathway.

RECENT FINDINGS

The relationship between short and long sleep duration, as well as insomnia, with CVD risk is well-established. Recent work has highlighted how other sleep factors, such as sleep regularity (i.e., consistency of sleep timing), multidimensional sleep health, and circadian factors like chronotype and social jetlag, relate to CVD risk. Sleep-focused interventions (e.g., cognitive behavioral therapy for insomnia and sleep extension) may be effective to reduce CVD risk and disease burden. Sleep is increasingly recognized as an integral component of cardiovascular health. This was underscored by the recent inclusion of sleep duration as a health behavior in the American Heart Association's Life's Essential 8 for defining optimal cardiovascular health.

Redefining Cardiovascular Health to Include Sleep: Prospective Associations With Cardiovascular Disease in the MESA Sleep Study

Background Although sufficient and healthy sleep is inversely associated with cardiovascular disease (CVD) and its risk factors, the American Heart Association's Life's Simple 7 (LS7), as a measure of cardiovascular health (CVH), did not include sleep. We evaluated an expanded measure of CVH that includes sleep as an eighth metric in relation to CVD risk. Methods and Results The analytic sample consisted of MESA (Multi-Ethnic Study of Atherosclerosis) Sleep Study participants who had complete data on sleep characteristics from overnight polysomnography, 7-day wrist actigraphy, validated questionnaires, and the outcome. We computed the LS7 score and 4 iterations of a new CVH score: score 1 included sleep duration, score 2 included sleep characteristics linked to CVD in the literature (sleep duration, insomnia, daytime sleepiness, and obstructive sleep apnea), scores 3 and 4 included sleep characteristics associated with CVD in MESA (score 3: sleep duration and efficiency, daytime sleepiness, and obstructive sleep apnea; score 4: score 3+sleep regularity). Multivariable-adjusted logistic and Cox proportional hazards models evaluated associations of the LS7 and CVH scores 1 to 4 with CVD prevalence and incidence. Among 1920 participants (mean age: 69±9 years; 54% female), there were 95 prevalent CVD events and 93 incident cases (mean follow-up, 4.4 years). Those in the highest versus lowest tertile of the LS7 score and CVH scores 1 to 4 had up to 80% lower odds of prevalent CVD. The LS7 score was not significantly associated with CVD incidence (hazard ratio, 0.62 [95% CI, 0.37-1.04]). Those in the highest versus lowest tertile of CVH score 1, which included sleep duration, and CVH score 4, which included multidimensional sleep health, had 43% and 47% lower incident CVD risk (hazard ratio, 0.57 [95% CI, 0.33-0.97]; and hazard ratio, 0.53 [95% CI, 0.32-0.89]), respectively. Conclusions CVH scores that include sleep health predicted CVD risk in older US adults. The incorporation of sleep as a CVH metric, akin to other health behaviors, may enhance CVD primordial and primary prevention efforts. Findings warrant confirmation in larger cohorts over longer follow-up.

Sleep Deficiency in the Elderly

With aging, there are normative changes to sleep physiology and circadian rhythmicity that may predispose older adults to sleep deficiency, whereas many health-related and psychosocial/behavioral factors may precipitate sleep deficiency. In this article, we describe age-related changes to sleep and describe how the health-related and psychosocial/behavioral factors typical of aging may converge in older adults to increase the risk for sleep deficiency. Next, we review the consequences of sleep deficiency in older adults, focusing specifically on important age-related outcomes, including mortality, cognition, depression, and physical function. Finally, we review treatments for sleep deficiency, highlighting safe and effective nonpharmacologic interventions.

Association of Poor Sleep Burden in Middle Age and Older Adults With Risk for Delirium During Hospitalization

BACKGROUND

Delirium is a distressing neurocognitive disorder recently linked to sleep disturbances. However, the longitudinal relationship between sleep and delirium remains unclear. This study assessed the associations of poor sleep burden, and its trajectory, with delirium risk during hospitalization.

METHODS

About 321 818 participants from the UK Biobank (mean age 58 ± 8 years [SD]; range 37-74 years) reported (2006-2010) sleep traits (sleep duration, excessive daytime sleepiness, insomnia-type complaints, napping, and chronotype-a closely related circadian measure for sleep timing), aggregated into a sleep burden score (0-9). New-onset delirium (n = 4 775) was obtained from hospitalization records during a 12-year median follow-up. About 42 291 (mean age 64 ± 8 years; range 44-83 years) had repeat sleep assessment on average 8 years after their first.

RESULTS

In the baseline cohort, Cox proportional hazards models showed that moderate (aggregate scores = 4-5) and severe (scores = 6-9) poor sleep burden groups were 18% (hazard ratio = 1.18 [95% confidence interval: 1.08-1.28], p < .001) and 57% (1.57 [1.38-1.80], p < .001), more likely to develop delirium, respectively. The latter risk magnitude is equivalent to 2 additional cardiovascular risks. These findings appeared robust when restricted to postoperative delirium and after exclusion of underlying dementia. Higher sleep burden was also associated with delirium in the follow-up cohort. Worsening sleep burden (score increase ≥2 vs no change) further increased the risk for delirium (1.79 [1.23-2.62], p = .002) independent of their baseline sleep score and time lag. The risk was highest in those younger than 65 years at baseline (p for interaction <.001).

CONCLUSION

Poor sleep burden and worsening trajectory were associated with increased risk for delirium; promotion of sleep health may be important for those at higher risk.

Actigraphy-derived sleep health profiles and mortality in older men and women

STUDY OBJECTIVES

To identify actigraphy sleep health profiles in older men (Osteoporotic Fractures in Men Study; N = 2640) and women (Study of Osteoporotic Fractures; N = 2430), and to determine whether profile predicts mortality.

METHODS

We applied a novel and flexible clustering approach (Multiple Coalesced Generalized Hyperbolic mixture modeling) to identify sleep health profiles based on actigraphy midpoint timing, midpoint variability, sleep interval length, maintenance, and napping/inactivity. Adjusted Cox models were used to determine whether profile predicts time to all-cause mortality.

RESULTS

We identified similar profiles in men and women: High Sleep Propensity [HSP] (20% of women; 39% of men; high napping and high maintenance); Adequate Sleep [AS] (74% of women; 31% of men; typical actigraphy levels); and Inadequate Sleep [IS] (6% of women; 30% of men; low maintenance and late/variable midpoint). In women, IS was associated with increased mortality risk (Hazard Ratio [HR] = 1.59 for IS vs. AS; 1.75 for IS vs. HSP). In men, AS and IS were associated with increased mortality risk (1.19 for IS vs. HSP; 1.22 for AS vs. HSP).

CONCLUSIONS

These findings suggest several considerations for sleep-related interventions in older adults. Low maintenance with late/variable midpoint is associated with increased mortality risk and may constitute a specific target for sleep health interventions. High napping/inactivity co-occurs with high sleep maintenance in some older adults. Although high napping/inactivity is typically considered a risk factor for deleterious health outcomes, our findings suggest that it may not increase risk when it occurs in combination with high sleep maintenance.

Multidimensional sleep health in a diverse, aging adult cohort: Concepts, advances, and implications for research and intervention

PURPOSE

To illustrate 2 frameshifts of multidimensional sleep health: i) use of composite sleep metrics; and ii) the correlations among sleep dimensions.

PARTICIPANTS

735 adults of diverse backgrounds aged <65 years who participated in the Multi-Ethnic Study of Atherosclerosis.

MEASURES

In-home polysomnography, 7-day wrist actigraphy, and validated questionnaires.

METHODS

The Buysse Ru SATED model-sleep regularity, satisfaction, alertness, timing, efficiency, duration-was operationalized, then extended by including additional measures of sleep architecture and sleep apnea from polysomnography and difficulties initiating sleep from questionnaire and sleep onset latency and duration [ir]regularity from actigraphy. We dichotomized sleep variables, operationalizing optimal and nonoptimal ranges as 1 and 0, respectively, summed into a sleep health score, and computed global sleep health scores via principal components analysis.

FINDINGS

Participants showed low prevalence of sleep regularity in timing (<30 minutes standard deviation [SD]; 21.4% favorable) and duration (<60 minutes SD; 36.9%). Although 62.7% of participants demonstrated favorable sleep duration by actigraphy, few met criteria for favorable levels of % N3 (11.4%) or %R (34.1%). The average Sleep Health Score was 5.6 of 13 (higher is better). Sleep variables were variably intercorrelated (r = 0 to r = -0.72). The first principal component for each operationalization of sleep health was interpretable as a "health" score; all summary scores captured variable but systematic shifts towards more favorable sleep in each sleep variable.

CONCLUSIONS

Multidimensional sleep health can be measured by complementary composite scores as well as consideration of multiple individual dimensions.

Identifying diverse forms of (un)healthy sleep: Sleep profiles differentiate adults' psychological and physical well-being

RATIONALE

Sleep health is best described by the co-occurrence of various dimensions (e.g., regularity, daytime alertness, satisfaction, efficiency, duration) but is rarely measured this way. Information is needed regarding common within-person patterns of sleep characteristics among adults and their relative healthiness.

OBJECTIVE

To deepen understanding of healthy and unhealthy sleep, the present study aimed to uncover multidimensional sleep profiles in adults and their associations with a variety of psychological and physical well-being outcomes.

METHODS

Survey data from 4622 adults who participated in the Midlife in the United States (MIDUS) project was used to identify latent sleep profiles across five core sleep dimensions. Adjusting for individual sleep dimensions and sociodemographic covariates, General Linear Models were used to test the associations of sleep profile membership with hedonic and eudemonic well-being and chronic physical conditions.

RESULTS

Four latent sleep profiles were revealed, good sleepers, sufficient but irregular sleepers, nappers, and short, dissatisfied, and inefficient sleepers. The profiles differentially related to well-being outcomes above and beyond individual sleep dimensions and sociodemographic covariates. Good sleepers generally reported the best outcomes, and short, dissatisfied, and inefficient sleepers generally reported the worst outcomes.

CONCLUSION

Four common sleep profiles describe adults' holistic sleep experiences and predict a variety of well-being outcomes beyond other known predictors. In adulthood, healthy sleep may involve sufficient sleep across all dimensions whereas unhealthy sleep may involve insufficient sleep across three key dimensions: duration, satisfaction, and efficiency.

Sleep Valuation Is Associated with Components of Sleep Health and Daytime Functioning in a College Sample: A Survey Study

Sleep valuation, the worth individuals place on sleep, is an understudied construct in the field of sleep medicine. This study introduced a Sleep Valuation Item Bank and explored how sleep valuation is related to sleep health and daytime functioning within a sample of college students. The participants in this study were 247 (85% white, 83% female) undergraduate students who completed an online survey that included questions from a Sleep Valuation Item Bank and questions about sleep and daytime functioning. Correlation and regression analyses were conducted to determine associations between sleep valuation, aspects of sleep health and daytime functioning. Mediation analyses were conducted to determine whether the sleep health variables explained the associations between sleep valuation and daytime functioning. In correlation analyses, sleep valuation was negatively associated with sleepiness and sleep quality. It was also associated with daytime functioning, including general mental and physical health, depression, and anxiety. In the regression analyses, daytime impairments including poorer physical and mental health, anxiety, and depression were associated with higher sleep valuation. Poorer sleep health, including greater sleepiness and lower sleep quality, explained these associations and were associated with higher sleep valuation. Thus, while daytime impairments, such as anxiety and depression, are related to sleep valuation, this relationship may be due in part to the sleep disturbance that often co-occurs with these impairments.

Multidimensional Sleep Health and Physical Functioning in Older Adults

Objective: To examine the association between multidimensional sleep health and objective measures of physical functioning in older adults. Method: We conducted a secondary analysis of 158 adults ≥65 years who participated in Midlife in the United States (MIDUS) 2 and MIDUS Refresher studies. Physical functioning was assessed using gait speed during a 50-foot timed walk, lower extremity strength via chair stand test, and grip strength via hand-held dynamometers. Composite multidimensional sleep health scores were derived from 1 week of sleep diaries and wrist actigraphy. Results: Multiple linear regression was used to examine the associations between multidimensional sleep health and physical functioning measures. In adjusted regression analyses, multidimensional sleep health was significantly positively associated with gait speed but not lower extremity strength or grip strength. Discussion: These findings suggest multidimensional sleep health may contribute to physical functioning in older adults. Longitudinal examinations are needed to determine the value of multidimensional sleep health as a therapeutic target to optimize physical functioning.

Individual and joint associations of daily sleep and stress with daily well-being in hospital nurses: an ecological momentary assessment and actigraphy study

Sleep and stress are predictors of daily physical and emotional well-being, but few studies assess both simultaneously. This study examined individual and joint associations of daily sleep and stress with daily well-being (DWB) in hospital nurses. Nurses (n = 60) participated in a 14-day ecological momentary assessment and actigraphy study. Multilevel modeling revealed associations of stressor severity and poor sleep health with DWB, independent of and coupled with each other, at within- and between-person levels. Greater stressor severity or poorer sleep health, independent of each other, were associated with more physical symptoms, less positive affect (PA), and more negative affect (NA). Joint associations of stress and sleep with DWB were observed: PA was lowest when higher stressor severity was coupled with poorer sleep health; NA was lowest when lower stressor severity was coupled with better sleep health. Findings suggest the importance of considering both sleep and stress for DWB in hospital nurses.