Same sleep disorder but different sleep patterns: individual differences in sleep health and depressive symptomatology in veterans with obstructive sleep apnea.

PURPOSE: Poor sleep health, a composite measure of key sleep characteristics, may relate to increased depressive symptoms among individuals treated for obstructive sleep apnea. The current investigation examined the association between sleep health and depressive symptomatology. METHODS: In a pilot sample of 13 symptomatic OSA military Veterans with adequate CPAP adherence (mean age = 54.8, 76.9% male, 100% White), empirically validated cutoffs were applied to actigraphy-derived sleep variables: duration, efficiency, timing, and regularity. RESULTS: Participants with zero optimal sleep scores had significantly higher depressive scores (M = 19.0, SD = 3.0) than participants with 1 or 2 (M = 9.8. SD = 4.3, p = .016) and 3 or more optimal sleep scores (M = 11.3, SD = 4.9, p = .038). CONCLUSIONS: These preliminary findings suggest that better sleep health was associated with lower depressive symptomatology. Future work should replicate these preliminary findings in a larger sample.

Poor sleep health predicts the onset of a fear of falling among community-dwelling older adults.

INTRODUCTION: A greater fear of falling predicts disability, falls, and mortality among older adults. Although poor sleep has been identified as a relevant risk factor for fear of falling among older adults, evidence is primarily shown in cross-sectional studies using isolated sleep characteristics. Less is known about whether prior fall experiences change the sleep health-fear of falling link among older adults. We investigated the longitudinal relationship between sleep health and the incidence of fear of falling among community-dwelling older adults and how the association differed between those with or without prior fall experiences. METHODS: Data were from individuals who completed the sleep module in the National Health and Aging Trends Study (2013-2014; n = 686). Fear of falling was assessed with a single item. Multidimensional sleep health was measured with self-reported sleep items based on the SATED model (ie, sleep satisfaction, daytime alertness, timing, efficiency, and duration). Covariates included sociodemographics, assistive device usage, health, risky behavior, and sleep medications. Multiple logistic regression was used to analyze the data. RESULTS: Poor sleep health was associated with the onset of fear of falling at 1-year follow-up (odds ratios=1.20, 95% confidence interval=1.02-1.41). Moreover, poor sleep health increased the odds of having fear of falling among individuals without prior falls experiences and elevated the already heightened risks of developing fear of falling among those who fell at baseline. CONCLUSIONS: Given that fear of falling and experiencing a fall each increase the risk of the other occurring in the future, improving sleep health may prevent older adults from stepping into the vicious cycle of fear of falling and falls.

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.

Associations between sleep health and obesity and weight change in adults: The Daily24 Multisite Cohort Study.

OBJECTIVES: To examine cross-sectional and longitudinal associations of individual sleep domains and multidimensional sleep health with current overweight or obesity and 5-year weight change in adults. METHODS: We estimated sleep regularity, quality, timing, onset latency, sleep interruptions, duration, and napping using validated questionnaires. We calculated multidimensional sleep health using a composite score (total number of "good" sleep health indicators) and sleep phenotypes derived from latent class analysis. Logistic regression was used to examine associations between sleep and overweight or obesity. Multinomial regression was used to examine associations between sleep and weight change (gain, loss, or maintenance) over a median of 1.66 years. RESULTS: The sample included 1016 participants with a median age of 52 (IQR = 37-65), who primarily identified as female (78%), White (79%), and college-educated (74%). We identified 3 phenotypes: good, moderate, and poor sleep. More regularity of sleep, sleep quality, and shorter sleep onset latency were associated with 37%, 38%, and 45% lower odds of overweight or obesity, respectively. The addition of each good sleep health dimension was associated with 16% lower adjusted odds of having overweight or obesity. The adjusted odds of overweight or obesity were similar between sleep phenotypes. Sleep, individual or multidimensional sleep health, was not associated with weight change. CONCLUSIONS: Multidimensional sleep health showed cross-sectional, but not longitudinal, associations with overweight or obesity. Future research should advance our understanding of how to assess multidimensional sleep health to understand the relationship between all aspects of sleep health and weight over time.

Six multidimensional sleep health facets in older adults identified with factor analysis of actigraphy: Results from the Einstein Aging Study.

OBJECTIVES: The concept of multi-dimensional sleep health, originally based on self-report, was recently extended to actigraphy in older adults, yielding five components, but without a hypothesized rhythmicity factor. The current study extends prior work using a sample of older adults with a longer period of actigraphy follow-up, which may facilitate observation of the rhythmicity factor. METHODS: Wrist actigraphy measures of participants (N = 289, Mage = 77.2 years, 67% females; 47% White, 40% Black, 13% Hispanic/Others) over 2 weeks were used in exploratory factor analysis to determine factor structures, followed by confirmatory factor analysis on a different subsample. The utility of this approach was demonstrated by associations with global cognitive performance (Montreal Cognitive Assessment). RESULTS: Exploratory factor analysis identified six factors: Regularity: standard deviations of four sleep measures: midpoint, sleep onset time, night total sleep time (TST), and 24-hour TST; Alertness/Sleepiness (daytime): amplitude, napping (mins and #/day); Timing: sleep onset, midpoint, wake-time (of nighttime sleep); up-mesor, acrophase, down-mesor; Efficiency: sleep maintenance efficiency, wake after sleep onset; Duration: night rest interval(s), night TST, 24-hour rest interval(s), 24-hour TST; Rhythmicity (pattern across days): mesor, alpha, and minimum. Greater sleep efficiency was associated with better Montreal Cognitive Assessment performance (ß [95% confidence interval] = 0.63 [0.19, 1.08]). CONCLUSIONS: Actigraphic records over 2 weeks revealed that Rhythmicity may be an independent factor in sleep health. Facets of sleep health can facilitate dimension reduction, be considered predictors of health outcomes, and be potential targets for sleep interventions.

The association of multidimensional sleep health with adiposity in heart failure with preserved ejection fraction.

BACKGROUND: There are bi-directional relationships between sleep disturbances and obesity, both of which are prevalent in patients with heart failure with preserved ejection fraction (HFpEF). However, little is known about the sleep-obesity association in HFpEF. OBJECTIVES: To determine associations of multidimensional sleep health, night movement, sleep fragmentation, and sleep-disordered breathing (SDB) risk with overall and regional adiposity in HFpEF patients. METHODS: Men and women with HFpEF (n = 49) were assessed via 14-day actigraphy, Pittsburgh Sleep Quality Index, and Epworth Sleepiness Scale to derive multidimensional sleep health. SDB risk was assessed via Berlin Questionnaire. Body composition was measured using anthropometry; MRI quantification of epicardial, abdominal, liver, and thigh adipose tissue was performed in a subsample (n = 22). Spearman correlation (rs) and linear regression analyses (ß coefficient) were used to estimate bivariate and age-adjusted associations. RESULTS: Multidimensional sleep health was inversely associated with BMI (rs = -0.50, p < .001; unadjusted: ß = -4.00, 95%CI: -5.87, -2.13; age-adjusted: ß = -2.48, 95%CI: -4.65, -0.30), thigh subcutaneous adipose tissue (rs = -0.50, p = .018; unadjusted: ß = -36.95, 95%CI: -67.31, -6.59), and thigh intermuscular fat (age-adjusted: ß = -0.24, 95%CI: -0.48, -0.01). Night movement and sleep fragmentation were associated with greater intermuscular thigh and lower liver fat. High SDB risk was associated with a higher visceral-to-subcutaneous ratio of abdominal adiposity and lower thigh adiposity. CONCLUSIONS: Adverse multidimensional sleep health is associated with higher adiposity measures in HFpEF patients. Further studies are needed to determine whether intervening on sleep could ameliorate excess adiposity or whether weight loss could improve sleep quality in HFpEF.

Multidimensional Sleep Health Is Associated with Cardiovascular Disease Prevalence and Cardiometabolic Health in US Adults.

Individual sleep dimensions have been linked to cardiovascular disease (CVD) risk and cardiometabolic health (CMH), but sleep health is multifaceted. We investigated associations of a multidimensional sleep health (MDSH) score, enabling the assessment of sleep health gradients, with CVD and CMH. Participants were 4555 adults aged ≥20 years from the 2017-2018 National Health and Nutrition Examination Survey. A MDSH score, capturing poor, moderate, and ideal sleep was computed from self-reported sleep duration, sleep regularity, difficulty falling asleep, symptoms of sleep disorders, and daytime sleepiness. Survey-weighted multivariable linear and logistic models examined associations of MDSH with CVD and CMH. Ideal and moderate vs. poor MDSH were related to lower odds of hypertension (62% and 41%), obesity (73% and 56%), and central adiposity (68% and 55%), respectively; a statistically significant linear trend was observed across gradients of MDSH (p-trend < 0.001). Ideal vs. moderate/poor MDSH was associated with 32% and 40% lower odds of prevalent CVD and type 2 diabetes, respectively. More favorable MDSH was associated with lower blood pressure, BMI, waist circumference, and fasting glucose. In sex-stratified analyses, ideal vs. moderate/poor MDSH was associated with lower CVD odds and blood pressure in women only. The MDSH framework may be more than just the sum of its parts and could better capture information regarding CVD risk.

Sleep Education for Elders Program (SLEEP): Promising Pilot Results of a Virtual, Health Educator-Led, Community-Delivered Sleep Behavior Change Intervention.

PURPOSE: Sleep problems pose serious public health concerns, and evidence suggests that the problem is worsening. Both sufficient sleep quantity and quality are needed for optimal health, particularly among older adults, but access to sleep care can be difficult. This study examined the efficacy of a six-week sleep behavior change program designed for older adults that was delivered virtually by health educators. PARTICIPANTS AND METHODS: This quasi-experimental pilot study (intervention n = 22; control n = 31) explored the effects of the Sleep Education for Elders Program (SLEEP) on sleep outcomes, which included: 1) sleep quality, measured by the Pittsburgh Sleep Quality Index (PSQI); 2) sleep duration, extracted from the PSQI; 3) insomnia symptoms, measured by the Insomnia Severity Index; 4) sleep hygiene behaviors, obtained from the Sleep Hygiene Index; and 5) excessive daytime sleepiness, measured by the Epworth Sleepiness Scale. RESULTS: After SLEEP, the intervention group experienced significantly improved sleep quality (p < 0.001), a reduction in maladaptive sleep hygiene behaviors (p = 0.007), and reduced daytime sleepiness (p < 0.027) compared to the control group. Effect sizes for all five sleep measures were medium or large. In the intervention group, all changes were judged to be clinically meaningful (≥ 0.5 SD) except for improvements in daytime sleepiness. CONCLUSION: These data support the efficacy of a group-based, virtual behavior change intervention in improving sleep outcomes among older adults.

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

The multidimensional sleep health framework emphasizes that sleep can be characterized across several domains, with implications for developing novel sleep treatments and improved prediction and health screening. However, empirical evidence regarding the domains and representative measures that exist in actigraphy-assessed sleep is lacking. We aimed to establish these domains and representative measures in older adults by examining the factor structure of 28 actigraphy-derived sleep measures from 2,841 older men from the Osteoporotic Fractures in Men Sleep Study and, separately, from 2,719 older women from the Study of Osteoporotic Fractures. Measures included means and standard deviations of actigraphy summary measures and estimates from extended cosine models of the raw actigraphy data. Exploratory factor analyses revealed the same five factors in both sexes: Timing (e.g. mean midpoint from sleep onset to wake-up), Efficiency (e.g. mean sleep efficiency), Duration (e.g. mean minutes from sleep onset to wake-up), Sleepiness/Wakefulness (e.g. mean minutes napping and amplitude of rhythm), and Regularity (e.g. standard deviation of the midpoint). Within each sex, confirmatory factor analyses confirmed the one-factor structure of each factor and the entire five-factor structure (Comparative Fit Index and Tucker-Lewis Index ≥ 0.95; Root Mean Square Error of Approximation 0.08-0.38). Correlation magnitudes among factors ranged from 0.01 to 0.34. These findings demonstrate the validity of conceptualizing actigraphy sleep as multidimensional, provide a framework for selecting sleep health domains and representative measures, and suggest targets for behavioral interventions. Similar analyses should be performed with additional measures of rhythmicity, other age ranges, and more racially/ethnically diverse samples.