Ten-Year Stability of an Insomnia Sleeper Phenotype and Its Association With Chronic Conditions.

OBJECTIVE: To identify distinct sleep health phenotypes in adults, examine transitions in sleep health phenotypes over time, and subsequently relate these to the risk of chronic conditions. METHODS: A national sample of adults from the Midlife in the United States study ( N = 3683) provided longitudinal data with two time points (T1: 2004-2006, T2: 2013-2017). Participants self-reported on sleep health (regularity, satisfaction, alertness, efficiency, duration) and the number and type of chronic conditions. Covariates included age, sex, race, education, education, partnered status, number of children, work status, smoking, alcohol, and physical activity. RESULTS: Latent transition analysis identified four sleep health phenotypes across both time points: good sleepers, insomnia sleepers, weekend catch-up sleepers, and nappers. Between T1 and T2, the majority (77%) maintained their phenotype, with the nappers and insomnia sleepers being the most stable. In fully adjusted models with good sleepers at both time points as the reference, being an insomnia sleeper at either time point was related to having an increased number of total chronic conditions by 28%-81% at T2, adjusting for T1 conditions. Insomnia sleepers at both time points were at 72%-188% higher risk for cardiovascular disease, diabetes, depression, and frailty. Being a napper at any time point related to increased risks for diabetes, cancer, and frailty. Being a weekend catch-up sleeper was not associated with chronic conditions. Those with lower education and unemployed were more likely to be insomnia sleepers; older adults and retirees were more likely to be nappers. CONCLUSION: Findings indicate a heightened risk of chronic conditions involved in suboptimal sleep health phenotypes, mainly insomnia sleepers.

Symptom subtype progression in obstructive sleep apnea over 5 years.

STUDY OBJECTIVES: There is limited knowledge regarding the progression or consistency of symptoms in OSA over time. Our objective was to examine the changes in symptom subtypes and identify predictors over a span of 5 years. METHODS: Data of 2,643 participants of the Sleep Heart Health Study with complete baseline and 5-year follow-up visits were analyzed. Latent Class Analysis on 14 symptoms at baseline and follow-up determined symptom subtypes. Individuals without OSA (AHI<5) were incorporated as a known class at each time point. Multinomial logistic regression assessed the effect of age, sex, body mass index (BMI) and AHI on specific class transitions. RESULTS: The sample consisted of 1,408 women (53.8%) and mean (SD) age 62.4 (10.5) years. We identified four OSA symptom subtypes at both baseline and follow-up visits: minimally symptomatic, disturbed sleep, moderately sleepy, and excessively sleepy. Nearly half (44.2%) of the sample transitioned to a different subtype; transitions to moderately sleepy were the most common (77% of all transitions). A five-year older age was associated with a 50% increase in odds to transit from excessively sleepy to moderately sleepy [OR (95% CI: 1.52 (1.17, 1.97)]. Women had 1.97 times higher odds (95% CI: 1.21, 3.18) to transition from moderately sleepy to minimal symptoms. A 5-unit increase in BMI was associated with 2.39 greater odds (95% CI: 1.30, 4.40) to transition from minimal symptoms to excessively sleepy. Changes in AHI did not significantly predict any transitions. CONCLUSIONS: The symptoms of OSA may fluctuate or remain stable over time. Knowledge of symptom progression in OSA may support clinicians with treatment decisions.

An adapted transdiagnostic sleep and circadian intervention for adults with excess weight and suboptimal sleep health: pilot study results.

Study Objectives: This single-arm, mixed-methods, pilot study examined the feasibility and preliminary efficacy of an adapted version of the transdiagnostic intervention for sleep and circadian dysfunction (TranS-C) on multidimensional sleep health (MDSH) in a sample of adults with excess weight and suboptimal sleep health. Methods: Participants received up to eight, weekly, remotely delivered, tailored TranS-C sessions. At pre- and post-intervention, the Pittsburgh Sleep Quality Index, Epworth Sleepiness Scale, and 7 days of Fitbit data were used to evaluate changes in sleep dimensions (regularity, alertness, timing, satisfaction, duration, and efficiency) and the composite MDSH score. Study feasibility examined recruitment, data collection, and intervention engagement (completion of core TranS-C sessions). Acceptability of the intervention was assessed with semi-structured interviews, which were analyzed using thematic analysis. Results: From 85 referrals, 11 individuals were eligible, and 10 completed the study. All intervention participants completed the measures needed to calculate their composite MDSH score and completed the core intervention sessions. Themes from interviews support the intervention's remote delivery approach, applicability of the information provided, and impact on self-reported health. The intervention resulted in a large improvement in the mean composite MDSH score (Cohen's d = 1.17). Small-to-large effects were also observed for individual sleep health dimensions except for timing. Conclusions: Adapted TranS-C is acceptable for adults with excess weight and suboptimal sleep health and may be effective at improving short-term MDSH. With changes to recruitment methods, a larger study is feasible. Limitations include the small sample size and the lack of a control condition.

Shorter total sleep time is associated with lower CD4+/CD8+ T cell ratios in virally suppressed men with HIV.

Study Objectives: Although poor sleep quality is associated with lower CD4+ T cell counts among people living with HIV (PLWH), the association between objective sleep metrics and T lymphocyte subset counts is unknown. We evaluated the association between polysomnography (PSG) derived sleep metrics and T lymphocyte subpopulations in a cohort of men living with HIV. Methods: Virally suppressed men living with HIV participating in the Multicenter AIDS Cohort Study underwent home overnight PSG. We assessed the association of PSG parameters with CD4+ and CD8+ T cell counts and the CD4+/CD8+ T cell ratio. Results: Overall, 289 men with mean (±SD) age 55.3 ±â€…11.3 years and mean CD4+ T cell count 730 ±â€…308 cells/mm3 were evaluated. Total sleep time (TST) was significantly associated with CD8+ but not CD4+ T cell counts. After adjusting for age, race, depressive symptoms, antidepressant use, and non-nucleoside reverse transcriptase inhibitors use, every hour of shorter TST was associated with an additional 33 circulating CD8+ T cells/mm3 (p = 0.05) and a 5.6% (p = 0.0007) decline in CD4+/CD8+ T cell ratio. In adjusted models, every hour of shorter rapid eye movement (REM) sleep was associated with an additional 113 CD8+ T cells/mm3 (p = 0.02) and a 15.1% lower CD4+/CD8+ T cell ratio (p = 0.006). In contrast, measures of sleep efficiency and sleep-disordered breathing were not associated with differences in T lymphocyte subpopulations. Conclusions: Our findings suggest that shorter TST and REM sleep durations are associated with differences in T lymphocyte subpopulations among men living with HIV. Addressing sleep may reflect a novel opportunity to improve immune function in PLWH.

Sleep-wake behavioral characteristics associated with depression symptoms: findings from the Multi-Ethnic Study of Atherosclerosis.

STUDY OBJECTIVES: To help prioritize target/groups for experimental intervention studies, we characterized cross-sectional associations between 24-hour sleep-wake measures and depression symptoms, and evaluated if similar sleep-wake-depression relationships existed in people with and without higher insomnia severity. METHODS: Participants had ≥3 days of actigraphy data (n = 1884; mean age = 68.6/SD = 9.1; 54.1% female). We extracted 18 sleep, activity, timing, rhythmicity, and fragmentation measures from actigraphy. We used individual and multivariable regressions with the outcome of clinically significant depression symptoms (Center for Epidemiologic Studies Depression Scale ≥ 16). We conducted sensitivity analyses in people with higher insomnia severity (top quartile of the Women's Health Initiative Insomnia Rating Scale total score). RESULTS: From separate models in the overall sample, the odds of having depression symptoms were higher with: later timing (e.g. activity onset time odds ratio [OR]/1 SD = 1.32; 95% confidence interval [CI]: 1.16 to 1.50), lower rhythmicity (e.g. pseudo-F OR/1 SD = 0.75; 95% CI: 0.66 to 0.85), less activity (e.g. amplitude OR/1 SD = 0.83; 95% CI: 0.72 to 0.95), and worse insomnia (OR/1 SD = 1.48, 95% CI: 1.31 to 1.68). In multivariable models conducted among people with lower insomnia severity, later timing, lower rhythmicity, and higher insomnia severity were independent correlates of depression. In people with higher insomnia symptom severity, measures of later timing were most strongly associated with depression symptoms. CONCLUSIONS: These correlative observations suggest that experimental studies are warranted to test if: broadly promoting 24-hour sleep-wake functioning reduces depression even in people without severe insomnia, and if advancing timing leads to depression symptom reductions in people with insomnia.

Influence of Impaired Diffusing Capacity and Sleep-disordered Breathing on Nocturnal Hypoxemia and Health Outcomes in Men with and without Human Immunodeficiency Virus.

Rationale: Nocturnal hypoxemia is common in sleep-disordered breathing (SDB) and is associated with increased morbidity and mortality. Although impaired diffusing capacity of the lung for carbon monoxide (DlCO) is associated with daytime hypoxemia, its influence on SDB-related nocturnal hypoxemia is not known. Objectives: To characterize the effects of DlCO impairment on SDB-related nocturnal hypoxemia and associated health outcomes. Methods: Data from a multicenter cohort of men with and without human immunodeficiency virus (HIV) infection, with concomitant measures of DlCO and home-based polysomnography (n = 544), were analyzed. Multivariable quantile regression models characterized associations between DlCO and several measures of SDB-related hypoxemia (e.g., total sleep time with oxygen saturation as measured by pulse oximetry [SpO2] < 90% [T90]). Structural equation models were used to assess associations of impaired DlCO and SDB-related hypoxemia measures with prevalent hypertension and type 2 diabetes. Results: DlCO impairment (<80% predicted) was associated with sleep-related hypoxemia. Participants with severe SDB (apnea-hypopnea index ⩾ 30 events/h) and impaired DlCO had higher T90 (median difference, 15.0% [95% confidence interval (CI), 10.3% to 19.7%]) and average SDB-related desaturation (median difference, 1.0 [95% CI, 0.5 to 1.5]) and lower nadir SpO2 (median difference, -8.2% [95% CI, -11.4% to -4.9%]) and average SpO2 during sleep (median difference, -1.1% [95% CI, -2.1% to -0.01%]) than those with severe SDB and preserved DlCO. Higher T90 was associated with higher adjusted odds of prevalent hypertension (odds ratio, 1.39 [95% CI, 1.14 to 1.70]) and type 2 diabetes (odds ratio, 1.25 [95% CI, 1.07 to 1.46]). Conclusions: DlCO impairment in severe SDB was associated with sleep-related hypoxemia, prevalent hypertension, and type 2 diabetes. Assessment of SDB should be considered in those with impaired DlCO to guide testing and risk stratification strategies.

Sleep-wake behaviors associated with cognitive performance in middle-aged participants of the Hispanic Community Health Study/Study of Latinos.

OBJECTIVES: Many sleep-wake behaviors have been associated with cognition. We examined a panel of sleep-wake/activity characteristics to determine which are most robustly related to having low cognitive performance in midlife. Secondarily, we evaluate the predictive utility of sleep-wake measures to screen for low cognitive performance. METHODS: The outcome was low cognitive performance defined as being >1 standard deviation below average age/sex/education internally normalized composite cognitive performance levels assessed in the Hispanic Community Health Study/Study of Latinos. Analyses included 1006 individuals who had sufficient sleep-wake measurements about 2years later (mean age=54.9, standard deviation= 5.1; 68.82% female). We evaluated associations of 31 sleep-wake variables with low cognitive performance using separate logistic regressions. RESULTS: In individual models, the strongest sleep-wake correlates of low cognitive performance were measures of weaker and unstable 24-hour rhythms; greater 24-hour fragmentation; longer time-in-bed; and lower rhythm amplitude. One standard deviation worse on these sleep-wake factors was associated with ∼20%-30% greater odds of having low cognitive performance. In an internally cross-validated prediction model, the independent correlates of low cognitive performance were: lower Sleep Regularity Index scores; lower pseudo-F statistics (modellability of 24-hour rhythms); lower activity rhythm amplitude; and greater time in bed. Area under the curve was low/moderate (64%) indicating poor predictive utility. CONCLUSION: The strongest sleep-wake behavioral correlates of low cognitive performance were measures of longer time-in-bed and irregular/weak rhythms. These sleep-wake assessments were not useful to identify previous low cognitive performance. Given their potential modifiability, experimental trials could test if targeting midlife time-in-bed and/or irregular rhythms influences cognition.