Psychosomatic Medicine最新文献

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.

Objective: Cancer can be a traumatic experience affecting multidimensional aspects of sleep among patients and caregivers. This study examined the differential associations of cancer-related posttraumatic stress symptoms (PTSS) with various sleep markers in this population.

Methods: Patients newly diagnosed with colorectal cancer ( n = 138, mean age = 56.93 years, 31.88% female, 60.14% Hispanic, 6.53 months after diagnosis) and their sleep-partner caregivers ( n = 138, mean age = 55.32 years, 68.12% female, 57.97% Hispanic) completed questionnaires assessing the four PTSS clusters (intrusion, avoidance, alterations in arousal and reactivity, negative alterations in cognitions and mood). Participants also completed daily sleep diaries for 14 consecutive days, from which sleep onset latency (SOL), wake after sleep onset (WASO), and sleep duration were derived.

Results: Actor-partner interdependence model revealed that caregivers' greater alterations in arousal and reactivity were associated with their own longer SOL ( b = 15.59, p < .001) and their patients' longer sleep duration ( b = 0.61, p = .014), whereas patients' arousal and reactivity were associated with their caregivers' shorter SOL ( b = -8.47, p = .050). Patients' and caregivers' greater negative alterations in cognitions and mood were associated with patients' longer SOL ( b = 9.15, p = .014) and shorter sleep duration ( b = -0.41, p = .050), respectively. Caregivers' greater intrusion was related to their own shorter SOL ( b = -10.14, p = .004).

Conclusions: The four PTSS clusters, particularly arousal and reactivity and negative cognitions and mood, have distinct associations with sleep markers individually and dyadically in patients and caregivers affected by cancer. Investigations of psychosocial and biobehavioral pathways underlying these relations are warranted. Tailored trauma treatments and sleep interventions may improve the well-being of this population.

Objective: To compare dimensions of financial hardship and self-reported sleep quality among Black women with versus without systemic lupus erythematosus (SLE).

Methods: Participants were 402 Black women (50% with validated diagnosis of SLE) living in Georgia between 2017 and 2020. Black women with SLE were recruited from a population-based cohort established in Atlanta, and Black women without SLE were recruited to be of comparable age and from the same geographic areas as SLE women. Financial hardship was measured using three different scales: financial adjustments, financial setbacks, and financial strain. Sleep was assessed continuously using the Pittsburgh Sleep Quality Index (PSQI) scale. Each dimension of financial hardship was analyzed separately in SLE-stratified multivariable linear regression models and adjusted by sociodemographic and health status factors.

Results: Dimensions of financial hardship were similarly distributed across the two groups. Sleep quality was worse in Black women with, versus without, SLE (p < .001). Among Black women with SLE, financial adjustment was positively associated with a 0.40-unit increase in poor sleep quality (95% CI = 0.12-0.67, p = .005). When accounting for cognitive depressive symptoms, financial setbacks and strain were somewhat attenuated for Black women with SLE. Overall, no associations between financial hardships and sleep quality were observed for the women without SLE.

Conclusions: Black women with SLE who experience financial hardships may be more at risk for poor sleep quality than Black women without SLE. Economic interventions targeting this population may help improve their overall health and quality of life.

Objective: Sleep quality and duration are important for biological restoration and promotion of psychological well-being. Optimism may facilitate or result from sufficient sleep, but questions remain as to directionality. The present study tested how optimism is associated with levels of and variability in sleep quantity and quality in a longitudinal burst design.

Methods: Midlife and older women ( N = 199) reported their sleep quantity and quality in online diaries for a 7-day period, every 3 months for 2 years. Optimism was measured at baseline and end-of-study. Multilevel models tested the effects of optimism on sleep. Linear regression models tested the effect of sleep on optimism.

Results: Baseline optimism was associated with higher sleep quality ( γ = 2.13 [1.16 to 3.11], p < .0001) and lower intraindividual variability (IIV; night-to-night and wave-to-wave) in sleep quantity (night-to-night: γ = -0.07 [-0.13 to -0.005], p = .03; wave-to-wave: b = -0.07 [-0.12 to -0.02], p = .003). In turn, higher average sleep quality (but not quantity) was associated with higher optimism at end-of-study ( b = 0.02 [0.007 to 0.03], p = .002). Variability in sleep was unrelated to optimism.

Conclusions: Optimism may play an important role in maintaining sleep quality and consistency in sleep quantity, perhaps by buffering stress. Similarly, sleep quality may play an important role in maintaining optimism. The cycle whereby optimism and sleep enhance one another could improve physical health and psychological well-being among aging adults.

Objective: Evidence suggests a link between positive social relationship perceptions and improved sleep (e.g., quality, efficiency) across the life span. Less work has probed the directionality of these relationships. Here, we report findings from the first study to examine bidirectional between- and within-person associations between loneliness and emotional support with daily life measures of sleep.

Methods: Participants were 389 healthy adults aged 40 to 64 years (61% female) who completed hourly surveys assessing loneliness and perceptions of emotional support over the course of 4 days. Measures of actigraphy-assessed sleep and nightly sleep quality were also assessed for 7 to 10 days.

Results: Individuals with lower average daily loneliness showed higher sleep quality and efficiency than individuals with higher loneliness (r = -0.19, p < .001; r = -0.14, p = .008, respectively), and greater average emotional support was likewise linked with better sleep quality (r = 0.18, p < .001). Controlling for neuroticism attenuated the effects of average loneliness on sleep. Within-person analyses showed unexpected bidirectional effects. Specifically, days in which people felt relatively lonelier were followed by nights with greater sleep efficiency (γ = 1.08, p = .015), and nights when people reported relatively poorer sleep quality were followed by days with greater emotional support (γ = -0.04, p = .013). These unexpected findings are probed in exploratory analyses.

Conclusions: Individuals with higher loneliness and lower emotional support report poorer sleep quality and efficiency, on average. Day-to-day fluctuations in perceptions of social relationships may affect the following night's sleep, and vice versa.

Objective: Sleep disturbance is a "hallmark" symptom of posttraumatic stress disorder (PTSD). Poor sleep (including short sleep) after combat-related trauma can also predict subsequent PTSD. Less is known about the association between sleep duration and PTSD symptoms when PTSD is induced by acute coronary syndrome (ACS). We examined the bidirectional relationship between sleep duration and PTSD symptoms over the year after hospital evaluation for ACS.

Methods: Participants were enrolled in this observational study after emergency department evaluation for ACS. Sleep duration ("During the past month, how many hours of actual sleep did you get at night?") and cardiac event or hospitalization-induced PTSD symptoms (PTSD Checklist) were assessed at 1, 6, and 12 months after hospital discharge. Cross-lagged path analysis was used to model the effects of sleep duration and PTSD symptoms on each other. Covariates included age, sex, race/ethnicity, cardiac severity, baseline depression symptoms, and early acute stress disorder symptoms.

Results: The sample included 1145 participants; 16% screened positive for probable PTSD (PTSD Checklist score ≥33). Mean sleep duration across time points was 6.1 hours. Higher PTSD symptoms predicted shorter sleep duration at the next time point (i.e., 1-6 and 6-12 months; B = -0.14 hours/10-point difference, SE = 0.03, p < .001). Shorter sleep duration was associated with higher PTSD symptoms at the next time point (B = -0.25 points/hour, SE = 0.12, p = .04).

Conclusions: Short sleep duration and PTSD symptoms are mutually reinforcing across the first year after ACS evaluation. Findings suggest that sleep, PTSD symptoms, and their relationship should be considered in the post-ACS period.

Objective: Sleep is important for diabetes-related health outcomes. Using a multidimensional sleep health framework, we examined the association of individual sleep health dimensions and a composite sleep health score with hemoglobin A1c (HbA1c) and depressive symptoms among African American adults with type 2 diabetes.

Methods: Participants (N = 257; mean age = 62.5 years) were recruited through local churches. Wrist-worn actigraphy and sleep questionnaire data assessed multidimensional sleep health using the RuSATED framework (regularity, satisfaction, alertness, timing, efficiency, duration). Individual sleep dimensions were dichotomized into poor or good sleep health and summed into a composite score. HbA1c was assessed using the DCA Vantage™ Analyzer or A1CNow® Self Check. Depressive symptoms were assessed using the Patient Health Questionnaire (PHQ-9). Regression models examined the association of individual sleep dimensions and composite sleep health with HbA1c and depressive symptoms.

Results: Higher composite sleep health scores were associated with a lower likelihood of having greater than minimal depressive symptoms (PHQ-9 ≥ 5) (odds ratio [OR] = 0.578, 95% confidence interval [CI] = 0.461-0.725). Several individual sleep dimensions, including irregularity (OR = 1.013, CI = 1.005-1.021), poor satisfaction (OR = 3.130, CI = 2.095-4.678), and lower alertness (OR = 1.866, CI = 1.230-2.833) were associated with a greater likelihood of having depressive symptoms. Neither composite sleep health scores nor individual sleep dimensions were associated with HbA1c.

Conclusions: Better multidimensional sleep health is associated with lower depressive symptoms among African American adults with type 2 diabetes. Longitudinal research is needed to determine the causal association between multidimensional sleep health and depressive symptoms in this population.

Trial registry: ClinicalTrials.gov identifier NCT04282395.

Objective: Occupational burnout has been associated with an increased risk of coronary heart disease, although the mechanisms involved are elusive. We investigated whether poor global sleep quality is associated with impaired coronary microvascular function in male physicians, a professional group at increased risk of burnout.

Methods: Study participants were 30 male physicians with clinical burnout and 30 controls without burnout defined by the Maslach Burnout Inventory. Global sleep quality was measured with the Pittsburgh Sleep Quality Index (PSQI). Endothelium-dependent (cold pressor test) and endothelium-independent (adenosine challenge) coronary microvascular functions were quantified with myocardial perfusion positron emission tomography. In multivariable analyses, the interaction between burnout and the PSQI global score was regressed on measures of coronary microvascular function, adjusting for age, body mass index, physical activity, alcohol consumption, and main effects of burnout and PSQI score.

Results: The prevalence of poor sleepers (PSQI score >5) was 40% in the burnout group and 10% in the control group. Adjusting for covariates, burnout-by-global PSQI score interactions were observed for myocardial blood flow (MBF) at rest ( r partial = -0.30, p = .025), endothelium-dependent coronary flow reserve ( r partial = -0.26, p = .062), MBF response ( r partial = -0.30, p = .028), and hyperemic MBF ( r partial = -0.34, p = .012). The global PSQI score was inversely associated with these MBF measures in the burnout group relative to the control group. No significant interactions emerged for endothelium-independent MBF.

Conclusions: In male physicians with occupational burnout, poor global sleep quality was associated with reduced endothelium-dependent coronary microvascular function, suggesting a mechanism by which burnout may affect cardiovascular health.

Objective: Sleep quality is an important health-protective factor. Psychosocial factors, including attachment orientation, may be valuable for understanding who is at risk of poor sleep quality and associated adverse health outcomes. High attachment anxiety is reliably associated with adverse health outcomes, whereas high attachment avoidance is associated with adverse health outcomes when co-occurring with poor self-regulatory capacity, indexed by heart rate variability (HRV). We examined the associations between attachment anxiety, attachment avoidance, HRV, and sleep quality.

Methods: Using longitudinal data from a sample of 171 older adults measured four times over 1 year ( M = 66.18 years old; 67.83% women), we separated the between-person variance (which we call "trait") and within-person variance (which we call "state") for attachment anxiety, attachment avoidance, and HRV (via the root mean square of successive differences). Sleep quality was measured with the Pittsburgh Sleep Quality Index.

Results: Higher trait attachment anxiety was associated with poorer global sleep quality ( B = 0.22, p = .005). Higher state attachment avoidance was associated with poorer sleep quality ( B = -0.13, p = .01), except for those with higher trait HRV. Higher state attachment anxiety was associated with poorer sleep quality ( B = -0.15, p = .002), except for those with higher or mean trait HRV. Higher trait attachment anxiety was associated with poorer sleep quality ( B = -0.31, p = .02), except for those with higher trait HRV.

Conclusions: High trait HRV mitigated the adverse effects of attachment insecurity on sleep quality. Our results suggest that people with high trait HRV had greater self-regulation capacity, which may enable them to enact emotion regulation strategies effectively.