Relationship between sleep quality and mental health according to demographics of 850 patients with chronic obstructive pulmonary disease

The Effect of Sleep Impairment, as Assessed by the CASIS Questionnaire, in Patients with Chronic Obstructive Pulmonary Disease on Disease Severity and Physical and Mental Health: A Cross-Sectional Study in Primary Care

The aim of our study was to assess the prevalence of sleep impairment among primary care patients with COPD and explore its impact on disease severity and overall health status. This cross-sectional study included 251 participants > 40 years old from the prospective COCARE COPD study. Data on sociodemographic characteristics, medical history, disease-specific quality of life [COPD Assessment Test (CAT)], COPD severity [Global Initiative for Chronic Obstructive Lung Disease (GOLD) 2023 categorization based on CAT score and exacerbations], fatigue [Fatigue Severity Scale (FSS)], psychological parameters [Patient Health Questionnaire-9 (PHQ-9) and General Anxiety Disorder-7 (GAD-7)], and sleep complaints [COPD and Asthma Sleep Impact Scale (CASIS) and Epworth Sleepiness Scale (ESS)] were collected. Multiple logistic regression analysis was conducted to test for associations of sleep impairment with COPD and overall health status, adjusting for confounders. Sleep impairment, indicated by a CASIS score ≥ 30, increased the risk of worse COPD health status (CAT ≥ 10 OR: 9.7, 95% CI: 5-19, p < 0.001), COPD severity (GOLD B OR: 8.9, 95% CI: 4.5-17.6, p < 0.001 and GOLD E OR: 17.4, 95% CI: 5.1-59.4, p < 0.001), excessive daytime sleepiness (ESS > 10, OR: 3.2, 95% CI: 1.3-8.1, p = 0.012), depressive symptoms (PHQ-9 ≥ 10, OR: 6.4, 95% CI: 2.1-19.1, p = 0.001), anxiety symptoms (GAD-7 ≥ 10, OR: 3.9, 95% CI: 1.6-9.2, p = 0.002), and fatigue (FSS ≥ 36, OR: 5.3, 95% CI: 2.8-9.8, p < 0.001). In conclusion, our findings suggest that sleep impairment, based on the CASIS questionnaire, is associated with worse physical and mental health in patients with COPD. Therefore, through consistent evaluation of sleep and targeted management strategies, healthcare providers could improve the quality of life for these patients.

Postural balance in COPD with obstructive sleep apnoea: a cross-sectional study

Objective

The aim of this study was to assess the postural balance in COPD patients with obstructive sleep apnoea (OSA). Physical activity, anxiety and depression symptoms, mood, and falls were also assessed in this population.

Methods

Moderate to severe COPD patients were assessed for laboratory and clinical postural balance (force platform and mini-balance evaluation systems test (Mini-BESTest)), physical activity (accelerometry), OSA (polysomnography), sleep quality (Pittsburgh Sleep Quality Index), sleepiness (Epworth Sleepiness Scale), anxiety and depression symptoms (Hospital Anxiety and Depression Scale), dyspnoea (modified Medical Research Council), clinical status (COPD Assessment Test) and mood (Brunel Mood Scale). Self-reported falls were recorded for 6 months via phone calls.

Results

COPD patients (n=70) were divided according to the polysomnography findings into the no OSA (n=30), mild OSA (n=25), and moderate to severe OSA (n=15) groups. Compared to patients with no OSA, those with moderate to severe OSA (msOSA group) presented median (interquartile range) increased path length (30.5 (23.9-34.5) cm versus 39.0 (30.6-52.6) cm, anteroposterior displacement (1.89 (1.39-2.31) cm versus 2.54 (2.06-2.83) cm and postural adjustment velocity (1.02 (0.80-1.15) cm·s-1 versus 1.30 (1.02-1.76) cm·s-1) (p<0.05). No differences were observed in the Mini-BESTest scores among the groups. The msOSA group presented a greater number of recurrent fallers in the first follow-up trimester. No association was observed between postural balance and age and pulmonary function.

Conclusion

Individuals with COPD and moderate to severe OSA present changes in postural balance, including broader oscillation, faster postural adjustments and a greater risk of falls than those with no OSA. Physical activity, anxiety and depression symptoms, and mood are similar between COPD patients with and without OSA.

Poor sleep quality, COPD severity and survival according to CASIS and Pittsburgh questionnaires

Poor sleep quality is frequent among COPD patients and it has been related to worse outcomes. The objective of this study was to compare the COPD and Asthma Sleep Impact Scale (CASIS) and the generic Pittsburgh Sleep Quality Index (PSQI) questionnaires as reliable tools for evaluating sleep quality and its relationship with COPD characteristics and survival. Stable COPD patients were prospectively evaluated. Anthropometric, sociodemographic, comorbidity, lung function and treatment data were collected. All patients completed CASIS and PSQI, mMRC dyspnea severity scale, COPD Assessment Test (CAT), sleep apnoea STOP-Bang and Hospital Anxiety and Depression Scale (HADS) questionnaires. Body mass index, airflow Obstruction, Dyspnea and Exacerbations (BODEx) index was calculated. Life status was determined after a mean follow-up of 3.7 (SD 1) years. We included 200 patients, 69.5% male, mean age 65.8 (9) years. Poor sleep was detected in 100 (50%) and 84 patients (42%) according to PSQI and CASIS questionnaires, respectively, with an agreement of 63%. Poor sleep was related to female gender, more severe dyspnea and worse BODEx, HADS and CAT scores according to both questionnaires. PSQI was associated to chronic pain or inferior urinary tract symptoms and CASIS to exacerbations, shorter walked distance in the 6-min walking test and treatment with oral corticosteroids or chronic oxygen. Thirty nine (19.5%) patients died during follow-up. Mortality was not associated to PSQI nor CASIS results. Unlike PSQI, CASIS is more related to COPD severity and its results are not influenced by comorbidities with known impact on sleep quality. In our sample, poor sleep quality was not associated with increased mortality.

Mental health and sleep quality among patients with asthma and COPD

This study aims to compare the mental health of patients with asthma and COPD in terms of anxiety, depression, and sleep quality and to examine the factors that predict sleep disturbance, anxiety, and depressive symptoms.

Methods

This quantitative cross-sectional study employed convenience sampling to enroll 200 patients with asthma and 190 patients with COPD. Data were gathered using a standardized self-administered questionnaire that contained sections on patients' characteristics, the Sleep Quality, Anxiety, and Depression.

Results

The prevalence of poor sleep quality was 17.5 and 32.6% among asthmatic and COPD patients, respectively. The incidence of anxiety and depression was 38 and 49.5% among the patients with asthma, respectively. Their prevalence in patients with COPD was 48.9 and 34.7%, respectively. The multivariate regression analysis showed that marital status (married), BMI, education level (pre-university level), presence of comorbid illness, and depression were significant predictors of PSQI in asthmatic patients. Moreover, age, gender (male), marital status (married), education level (pre-university level), depression, and anxiety were significant predictors of PSQI among COPD participants. According to this study, COPD, and asthma pose serious health risks, including reduced sleep quality, anxiety, and depression.

Association between Sleep Duration and Hand Grip Strength among COPD Patients

This study aimed to evaluate the association between night-time sleep duration and hand grip strength (HGS) among patients with chronic obstructive pulmonary disease (COPD). Participants aged ≥45 years were included in a nationally representative investigation clinical study in 2015. HGS was measured using dynamometers. The data on night-time sleep duration, sociodemographic information, and health-related variables were systematically collected. For analysis, sleep duration was categorized as <5 h, 5-7 h, 7 h, 7-9 h, and >9 h. Multivariable linear regression models were used to determine the possible association between the night-time sleep duration and HGS. Our results indicated that the shortest (<5 h) or the longest sleep duration (>9 h) was relevant to high risk of weaker HGS in females. In males, the shortest (<5 h) sleep duration was correlated to lower HGS. Thus, our findings clearly suggest that health care providers should focus on the potential influence of sleep duration on HGS among COPD patients.

Mediation Effect of the Coping Strategies on the Relation Between Stress and Sleep Quality

OBJECTIVE

Recently data has been accumulated regarding the role of coping strategies in the relationship between stress and sleep quality. Therefore, we set out to identify the mediating effects of coping strategies between stress and sleep quality.

METHODS

A online-based cross-sectional study was performed using the Perceived Stress Scale-10, the Pittsburgh Sleep Quality Index, and a simplification of the 60-item Coping Orientation to Problems Experienced (Brief COPE) inventory in the nonclinical adult sample. The 24 items of Brief COPE were categorized into four factors (social support, problem solving, avoidance, positive thinking). Then, we used the PROCESS macro to conduct the multiple mediation analysis for the four coping styles as potential mediators in the relationship between stress and sleep quality, and an additional subgroup analysis was examined to identify a gender difference for the mediation effect.

RESULTS

As a group, four coping styles mediated significantly the association between perceived stress and poor sleep quality. And avoidance has maintained its significance thought all regression analyses. Finally, this results remained as same in the females.

CONCLUSION

The effect of perceived stress on poor sleep quality was mediated by coping strategies, especially by avoidance. Thus, further research should consider the coping styles of individuals to reduce the influence of stress on sleep quality.

Systematic Review of Physical Activity, Sedentary Behaviour and Sleep Among Adults Living with Chronic Respiratory Disease in Low- and Middle-Income Countries

Abstract

Physical activity (PA), sedentary behaviour (SB) and sleep are important lifestyle behaviours associated with chronic respiratory disease (CRD) morbidity and mortality. These behaviours need to be understood in low- and middle-income countries (LMIC) to develop appropriate interventions.

Purpose

Where and how have free-living PA, SB and sleep data been collected for adults living with CRD in LMIC? What are the free-living PA, SB and sleep levels of adults living with CRD?

Patients and Methods

The literature on free-living PA, SB and sleep of people living with CRD in LMIC was systematically reviewed in five relevant scientific databases. The review included empirical studies conducted in LMIC, reported in any language. Reviewers screened the articles and extracted data on prevalence, levels and measurement approach of PA, SB and sleep using a standardised form. Quality of reporting was assessed using bespoke criteria.

Results

Of 89 articles, most were conducted in Brazil (n=43). PA was the commonest behaviour measured (n=66). Questionnaires (n=52) were more commonly used to measure physical behaviours than device-based (n=37) methods. International Physical Activity Questionnaire was the commonest for measuring PA/SB (n=11). For sleep, most studies used Pittsburgh Sleep Quality Index (n=18). The most common ways of reporting were steps per day (n=21), energy expenditure (n=21), sedentary time (n=16), standing time (n=13), sitting time (n=11), lying time (n=10) and overall sleep quality (n=32). Studies revealed low PA levels [steps per day (range 2669-7490steps/day)], sedentary lifestyles [sitting time (range 283-418min/day); standing time (range 139-270min/day); lying time (range 76-119min/day)] and poor sleep quality (range 33-100%) among adults with CRD in LMIC.

Conclusion

Data support low PA levels, sedentary lifestyles and poor sleep among people in LMIC living with CRDs. More studies are needed in more diverse populations and would benefit from a harmonised approach to data collection for international comparisons.

Interactions between Sleep and Emotions in Humans and Animal Models

Recently, increased interest and efforts were observed in describing the possible interaction between sleep and emotions. Human and animal model studies addressed the implication of both sleep patterns and emotional processing in neurophysiology and neuropathology in suggesting a bidirectional interaction intimately modulated by complex mechanisms and factors. In this context, we aimed to discuss recent evidence and possible mechanisms implicated in this interaction, as provided by both human and animal models in studies. In addition, considering the affective component of brain physiological patterns, we aimed to find reasonable evidence in describing the two-way association between comorbid sleep impairments and psychiatric disorders. The main scientific literature databases (PubMed/Medline, Web of Science) were screened with keyword combinations for relevant content taking into consideration only English written papers and the inclusion and exclusion criteria, according to PRISMA guidelines. We found that a strong modulatory interaction between sleep processes and emotional states resides on the activity of several key brain structures, such as the amygdala, prefrontal cortex, hippocampus, and brainstem nuclei. In addition, evidence suggested that physiologically and behaviorally related mechanisms of sleep are intimately interacting with emotional perception and processing which could advise the key role of sleep in the unconscious character of emotional processes. However, further studies are needed to explain and correlate the functional analysis with causative and protective factors of sleep impairments and negative emotional modulation on neurophysiologic processing, mental health, and clinical contexts.

Components of Pittsburgh Sleep Quality Index in Iranian adult population: an item response theory model

Objective/background

There have been conducted few studies in Iran on the quality of sleep in the general population. This study aimed to use the item response theory (IRT) model to examine the accuracy of the seven components of the Pittsburgh Sleep Quality Index (PSQI) and to provide an appropriate cut-off point for population-based studies.

Methods

This study was performed using the data of the second phase of the Shahroud Eye Cohort Study (ShECS) in 2014. The sleep quality of 4710 participants was measured through PSQI. Using an IRT model, the seven components of the index are considered as indicators and sleep quality as the latent variable in the measurement model. This model supposed that there is only one hidden component to explain the respondent's behavior to a number of items.

Results

Results of analyzing different components of PSQI showed that component 6 (using sleep medication) and 7 (daytime dysfunction disorder) had the lowest values of discrimination parameter and component 4 (habitual sleep efficiency) and 1 (sleep quality) had the highest value of discrimination parameter. Persons with an expected sleep quality score of less than or equal to 6.5 will be defined as good sleep quality pattern.

Conclusions

Since discrimination values for components 6 and 7 are less than the values for other components, the use of the standardized latent scores is emphasized for assessing the quality of sleep in the population.

•

For seven components of PSQI, difficulty and discrimination parameters were estimated using IRT.

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Using an IRT model persons with an expected sleep quality score ≤ 6.5 will be defined as good sleep quality pattern.

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Almost 42.9% and 0.2% had poor and very poor sleep quality.

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Sleep quality, and habitual sleep efficiency components had the highest value of discrimination parameter.

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Component 6 and 7 play the lowest role in assessing sleep quality in the general population.

Poorer sleep quality correlated with mental health problems in college students: A longitudinal observational study among 686 males

OBJECTIVE

Poor sleep quality and mental health problems are common in college students. The objective of this study is to examine whether sleep quality predicts the risk of future mental health problems, and vice versa.

METHODS

The sleep quality and mental health status of 686 male college students were estimated, and 582 of them were followed up a year later. Subjective sleep quality and mental health problems were measured with the Pittsburgh Sleep Quality Index (PSQI) and the Depression Anxiety Stress Scale-21 (DASS-21), respectively.

RESULTS

Either at baseline or during follow-up, the PSQI global score was positively associated with scores for depression, anxiety, and stress on the DASS-21 (p's < 0.001). Longitudinal analyses revealed that DASS-21 total score increased in line with increased of PSQI global score during the year (p < .001). More importantly, the cross-lagged analysis showed that (i) PSQI global score at baseline was positively related to depression (β = 0.261), anxiety (β = 0.321), and stress (β = 0.311) scores a year later (p's < 0.001) and (ii) depression (β = 0.259), stress (β = 0.245) and anxiety (β = 0.292) scores at baseline were related to PSQI global score a year later (p's < 0.001). Finally, we further found that among those without mental health problems at baseline, poorer baseline sleep quality predicted a higher risk of anxiety symptoms a year later (RR 3.07, 95% CI 1.36-6.97, p = .007).

CONCLUSIONS

These data may suggest a bidirectionally relationship between sleep quality and mental health problems.

Do Sleeping Disorders Impair Sexual Function in Married Iranian Women of Reproductive Age? Results from a Cross-Sectional Study

Purpose

This study aimed to evaluate the relationship between sleep quality and sexual function among Iranian women.

Methods

This study was conducted on 277 married women of reproductive age. The inclusion criteria were as follows: married women aged 18–45 years, with at least basic literacy, and women married monogamously for at least one year. The following tools were used for gathering data: a demographic questionnaire; Pittsburgh Sleep Quality Index (PSQI); Insomnia Severity Index (ISI); Epworth Sleepiness Scale (ESS); and Female Sexual Function Index (FSFI). Pearson correlation coefficients, independent t-tests, chi-square tests, and linear regression analyses were used to analyze the data.

Results

There was a significant inverse relation between poor sleep quality (r = −0.13, P = 0.02), daytime sleepiness (r = −0.39, P < 0.001), insomnia (r = −0.35, P < 0.001), and sexual function. Sexual desire was significantly related to sleep quality and insomnia (P < 0.001). Sexual arousal (r = −0.18, r = −0.29, P < 0.001), lubrication (r = −0.21, r = −0.3, −0.12, P < 0.001), orgasms (r = 0.17, r = −0.15, P < 0.001), and sexual satisfaction (r = −0.02, −r = 0.3, r = −0.15, P < 0.001) were significantly related to all types of sleep disorders (poor sleep quality, insomnia, and sleepiness). Pain during intercourse was significantly associated with poor sleep quality and insomnia. With each unit decrease in sleep quality, sexual function decreased by 0.49 (P < 0.001), and with each unit increase in the delay of sleep onset, sexual function decreased by 1.58 (P = 0.04).

Conclusion

Results of this study showed that there was a significant relationship between sleep quality and sexual function in Iranian women of reproductive age. The quality of sleep among reproductive-aged women merits the attention of health care providers and policy makers.

Noninvasive ventilation in stable hypercapnic COPD: what is the evidence?

Long-term noninvasive ventilation (NIV) to treat chronic hypercapnic respiratory failure is still controversial in severe chronic obstructive pulmonary disease (COPD) patients. However, with the introduction of high-intensity NIV, important benefits from this therapy have also been shown in COPD. In this review, the focus will be on the arguments for long-term NIV at home in patients with COPD. The rise of (high-intensity) NIV in COPD and the randomised controlled trials showing positive effects with this mode of ventilation will be discussed. Finally, the challenges that might be encountered (both in clinical practice and in research) in further optimising this therapy, monitoring and following patients, and selecting the patients who might benefit most will be reviewed.