Relationship between insomnia and depression in a community sample depends on habitual sleep duration

Inequities in atherosclerotic cardiovascular disease prevention

Atherosclerotic cardiovascular (CV) disease (ASCVD) prevention encompasses interventions across the lifecourse: from primordial to primary and secondary prevention. Primordial prevention begins in childhood and involves the promotion of ideal CV health (CVH) via optimizing physical activity, body mass index, blood glucose levels, total cholesterol levels, blood pressure, and sleep while minimizing tobacco use. Primary and secondary prevention of ASCVD thereafter centers around mitigating ASCVD risk factors via medical therapy and lifestyle interventions. Disparities in optimal preventive efforts exist among historically marginalized groups in each of these three prongs of ASCVD prevention. Children and adults with a high burden of social determinants of health also face inequity in preventive measures. Inadequate screening, risk factor management and prescription of preventive therapeutics permeate the care of certain groups, especially women, Black, and Hispanic individuals in the United States. Beyond this, individuals belonging to historically marginalized groups also are much more likely to experience other ASCVD risk-enhancing factors, placing them at higher risk for ASCVD over their lifetime. These disparities translate to worse outcomes, with higher rates of ASCVD and CV mortality among these groups. Possible solutions to promoting equity involve community-based youth lifestyle interventions, improved risk-factor screening, and increasing accessibility to healthcare resources and novel preventive diagnostics and therapeutics.

Association of sleep duration and risk of mental disorder: a systematic review and meta-analysis

BACKGROUND

The effects of sleep duration on the development of mental illness remain controversial. Therefore, it is necessary to identify the effects of long or short sleep duration on psychological disorders, which could reveal new ways for preventing and treating mental health conditions cheaply.

METHODS

Identifying published papers was accomplished by using the following five English databases on March 16, 2022: PubMed, MEDLINE, Embase, Web of Science databases, and Scopus. Cross-sectional and cohort studies were considered if they evaluated the association of sleep duration with all kinds of mental illness in adults. We excluded case reports, editorials, narrative reviews, and studies without detailed information on sleep duration. Summary effect-size estimates were expressed as risk ratios (RRs) or odds ratios (ORs) with 95% confidence intervals and were evaluated using random-effect models. Mantel-Haenszel's random-effects model was used to estimate the inconsistency index (I2) and Tau2 index (measurement of heterogeneity).

RESULTS

A total of 52 studies were included in this analysis, consisting of 14 cohort studies and 38 cross-sectional studies. These studies involved a combined sample size of 1,407,891 participants who met the inclusion criteria. Cohort (adjusted RR = 1.42, 95% CI: 1.26-1.60, P < .001, I2 = 37.6%, Tau2 = 0.014) and cross-sectional studies (adjusted OR = 1.67, 95% CI: 1.57-1.77, P < .001, I2 = 79.7%, Tau2 = 0.060) concluded that short sleep duration increased mental disorder risks. The same conclusions were acquired in the subgroup analysis, especially for depression (adjusted RR = 1.43, 95% CI: 1.24-1.65, P < .001, I2 = 80.4%, Tau2 = 0.082), anxiety (adjusted RR = 1.30, 95% CI: 1.04-1.63, P = .002, I2 = 0.0%, Tau2 = 0.000), and PTSD (adjusted RR = 1.35, 95% CI: 1.04-1.76, P = .022, I2 = 24.1%, Tau2 = 0.013) in cohort studies. The results of subgroup analysis indicated that long sleep duration was not a risk factor for depression (adjusted RR = 1.15, 95% CI: 0.98-1.34, P = .088, I2 = 63.4%, Tau2 = 0.045) and anxiety (adjusted RR = 1.37, 95% CI: 0.93-2.03, P = .114, I2 = 0.0%, Tau2 = 0.000).

CONCLUSIONS

Short sleep duration, not long sleep duration, is an independent predictor of developing mental disorders, particularly anxiety and depression.

Assessment of Lumbar Spinal Stenosis as a Risk Factor for Development of Sleep Disorder: The Locomotive Syndrome and Health Outcome in Aizu Cohort Study (LOHAS)

Purpose

Insomnia has been reported to coexist with various musculoskeletal disorders. Although lumbar spinal stenosis (LSS) is the most frequently operated on spinal disease, the causal relationship between LSS and development of sleep disorders remains unclear due to lack of longitudinal studies. This study aimed to determine whether LSS was a risk factor for developing new sleep disorders, primarily insomnia, using a prospective cohort of community residents.

Patients and Methods

This study was a prospective cohort study. Participants aged ≥65 years from the "Locomotive Syndrome and Health Outcomes in Aizu Cohort Study (LOHAS)" conducted in 2008 formed our study population. LSS was diagnosed using the self-administered, self-reported history questionnaire, a validated diagnostic support tool for LSS. Sleep disorder was investigated using a questionnaire during the 2-year follow-up. The impact of LSS on sleep disorder onset was analyzed after adjusting for potential confounders, such as age, sex, obesity, hypertension, diabetes, depression, and smoking habits, using propensity score matching.

Results

Of the 489 participants who were followed up for two years, 38 (7.8%) had newly developed a sleep disorder in 2010. After adjusting for confounding factors, a comparison of 133 participants each in the control and LSS groups showed significantly higher frequency of new-onset sleep disorders (19 [14.3%] in the LSS group versus 6 [4.5%] in the control group).

Conclusion

LSS was found to be an independent risk factor for sleep disorders.

Development and Initial Validation of the Assessment of Sleep Environment (ASE): Describing and Quantifying the Impact of Subjective Environmental Factors on Sleep

The purpose of this study was to develop and test the reliability and validity of a 13-item self-report Assessment of Sleep Environment (ASE). This study investigates the relationship between subjective experiences of environmental factors (light, temperature, safety, noise, comfort, humidity, and smell) and sleep-related parameters (insomnia symptoms, sleep quality, daytime sleepiness, and control over sleep). The ASE was developed using an iterative process, including literature searches for item generation, qualitative feedback, and pilot testing. It was psychometrically assessed using data from the Sleep and Healthy Activity Diet Environment and Socialization (SHADES) study (N = 1007 individuals ages 22-60). Reliability was determined with an internal consistency and factor analysis. Validity was evaluated by comparing ASE to questionnaires of insomnia severity, sleep quality, daytime sleepiness, sleep control, perceived stress, and neighborhood disorder. The ASE demonstrated high internal consistency and likely reflects a single factor. ASE score was associated with insomnia symptoms (B = 0.09, p < 0.0001), sleep quality (B = 0.07, p < 0.0001), and sleep control (B = -0.01, p < 0.0001), but not daytime sleepiness. The ASE was also associated with perceived stress (B = 0.20, p < 0.0001) and neighborhood disorder (B = -0.01, p < 0.0001). Among sleep environment factors, only smell was not associated with sleep quality; warmth and safety were negatively associated with sleepiness; and of the sleep environment factors, only light/dark, noise/quiet, and temperature (warm/cool) were not associated with insomnia symptoms. The ASE is a reliable and valid measure of sleep environment. Physical environment (light, temperature, safety, noise, comfort, humidity, and smell) was associated with insomnia symptoms and sleep quality but not sleepiness.

Life's Essential 8: Updating and Enhancing the American Heart Association's Construct of Cardiovascular Health: A Presidential Advisory From the American Heart Association

In 2010, the American Heart Association defined a novel construct of cardiovascular health to promote a paradigm shift from a focus solely on disease treatment to one inclusive of positive health promotion and preservation across the life course in populations and individuals. Extensive subsequent evidence has provided insights into strengths and limitations of the original approach to defining and quantifying cardiovascular health. In response, the American Heart Association convened a writing group to recommend enhancements and updates. The definition and quantification of each of the original metrics (Life's Simple 7) were evaluated for responsiveness to interindividual variation and intraindividual change. New metrics were considered, and the age spectrum was expanded to include the entire life course. The foundational contexts of social determinants of health and psychological health were addressed as crucial factors in optimizing and preserving cardiovascular health. This presidential advisory introduces an enhanced approach to assessing cardiovascular health: Life's Essential 8. The components of Life's Essential 8 include diet (updated), physical activity, nicotine exposure (updated), sleep health (new), body mass index, blood lipids (updated), blood glucose (updated), and blood pressure. Each metric has a new scoring algorithm ranging from 0 to 100 points, allowing generation of a new composite cardiovascular health score (the unweighted average of all components) that also varies from 0 to 100 points. Methods for implementing cardiovascular health assessment and longitudinal monitoring are discussed, as are potential data sources and tools to promote widespread adoption in policy, public health, clinical, institutional, and community settings.

[Sleep disorders reduce the therapeutic success of inpatient psychosomatic treatments for depressive disorders]

Sleep disorders reduce the therapeutic success of inpatient psychosomatic treatments for depressive disorders Objective: What influence do difficulties in falling and staying asleep in patients with depressive disorders have on the success of psychosomatic treatment? Method: The Data were collected in a naturalistic, multicenter observational study (STOP-D) at the beginning (T1), the end (T2) and six months later after discharge (T3). The sample consisted of female patients with depressive disorders (N = 487) who were treated for M = 61.7 days (SD = 26.8). An insomnia scale with a total of seven items was created subsequently to T1 from Items of the Beck Depression Inventory (BDI-I), from the Hamilton Depression Scale (HAMD) and from the Global Severe Index (GSI) from the Symptom Checklist 90 (SCL-90-R). Then groups were formed on changes in insomnia symptoms from T1 to T2. These two groups "sleep improver" and "sleep deteriorators" were tested by analysis of variance. Results: The subsequently constructed insomnia scale showed good psychometric characteristics in the performed analyses. Patients who reported an improvement in their sleep disturbances during inpatient psychosomatic treatment had significantly lower depression scores in the self-evaluation inventories (BDI-I und SCL-90-R) than patients without improvements in their sleep patterns. This effect was even more pronounced for the catamnestic period. Discussion: Insomnia symptoms in depressed female patients can be an important indicator of the effect of inpatient psychosomatic treatment and can have negative impact on the sustainability of the therapy success.

Evaluation of Severity Levels of the Athens Insomnia Scale Based on the Criterion of Insomnia Severity Index

The Athens Insomnia Scale (AIS) can be regarded as a highly useful instrument in both clinical and research settings, except for when assessing the severity level. This study aims to determine the severity criteria for AIS by using the Insomnia Severity Index (ISI). A total of 1666 government employees aged 20 years or older were evaluated using the AIS and ISI, the Patient Health Questionnaire for depressive symptoms, the Epworth Sleepiness Scale for daytime sleepiness, and the Short Form Health Survey of the Medical Outcomes Study for health-related quality of life (QoL). A significant positive correlation (r) was found between the AIS and the ISI (r = 0.80, p < 0.001). As a result of describing receiver-operator curves, the severity criteria of the AIS are capable of categorizing insomnia severity as follows: absence of insomnia (0-5), mild insomnia (6-9), moderate insomnia (10-15), and severe insomnia (16-24). In addition, compared to all scales across groups categorized by AIS or ISI, it was revealed that similar results could be obtained (all p < 0.05). Therefore, the identification of the severity of AIS in this study is important in linking the findings of epidemiological studies with those of clinical studies.