Insomnia, poor sleep quality and perinatal suicidal risk: A systematic review and meta-analysis.

Suicidal risk in mothers is a public health priority. Risk factors include biological, psychological and psychosocial factors. Among the biological factors, the role of sleep disturbances as potential contributors to increased suicidal risk during the peripartum period is becoming apparent. To explore this further, we conducted a systematic review following the PRISMA criteria. Currently, 10 studies have examined the role of insomnia and poor sleep quality in suicidal risk during the peripartum period and have involved 807,760 women. The data showed that disturbed sleep and poor sleep quality increase the risk of suicidal ideation in both pregnant women with and without perinatal depression. The results of the meta-analysis indicated that insomnia and poor sleep quality increase the odds of suicidal risk in pregnant women by more than threefold (OR = 3.47; 95% CI: 2.63-4.57). Specifically, the odds ratio (OR) for poor sleep quality was 3.72 (95% CI: 2.58-5.34; p < 0.001), and for insomnia symptoms, after taking into account perinatal depression, was 4.76 (95% CI: 1.83-12.34; p < 0.001). These findings emphasise the importance of assessing and addressing sleep disturbances during the peripartum period to mitigate their adverse effects on peripartum psychopathology and suicidal risk.

SPECT/CT imaging of poor sleep quality in people with epilepsy.

PURPOSE: To analyze the characteristics of cerebral blood flow changes of poor sleep quality in people with epilepsy(PWE). METHODS: 90 PWE treated in The General Hospital of Ningxia Medical University from December 2021 to September 2023 were divided into poor sleep quality group (PSQG) and good sleep quality group (GSQG) according to the Chinese version of the Pittsburgh Sleep Quality Index (CPSQI), to compare the differences in cerebral perfusion between the two groups of patients, so as to summarize the characteristics of cerebral blood flow changes of poor sleep quality in PWE. RESULTS: The positive rate of interictal single-photon emission computed tomography/computed tomography (SPECT/CT) was 76.7 %(69/90), which showed localized cerebral hypoperfusion. There was no statistical difference between the two groups of PSQG (N=29) and GSQG (N=61) in terms of the positive rate of SPECT/CT, the number of hypoperfusion foci, and the range of hypoperfusion foci. In PSQG and GSQG, 9 patients(31.0 %) and 6 patients(9.8 %) showed hypoperfusion in the right parietal lobe, respectively, and the difference between the two groups was statistically significant (P=0.017). There was no statistical difference the rate of the interictal epileptiform discharges (IEDs) and the brain area of IEDs in electroencephalography(EEG) between the two groups. CONCLUSION: SPECT/CT of poor sleep quality in PWE demonstrated hypoperfusion in the right parietal lobe.

The prevalence of poor sleep quality in the general population in China: a meta-analysis of epidemiological studies.

BACKGROUND: The high prevalence of poor sleep quality (PSQ) in the general population leads to negative health outcomes. Since estimates of PSQ prevalence in the Chinese general population vary widely, this meta-analysis aimed to refine these estimates and to identify moderating factors. METHODS: A comprehensive literature search was undertaken in both international (PubMed, PsycINFO, Web of Science, and EMBASE) and Chinese (Wanfang, and the China National Knowledge Infrastructure databases) databases from inception to 23 November 2023. Studies were required to have used standard scales such as the Chinese version of the Pittsburgh Sleep Quality Index (PSQI). The pooled prevalence of PSQ and 95% confidence intervals (CIs) were calculated using a random-effects model. Subgroup and meta-regression analyses were performed to identify sources of heterogeneity. RESULTS: In 32 studies with a combined 376,824 participants, the pooled prevalence of PSQ was 19.0% (95% CI 15.8-22.8%; range 6.6-43.6%). Across 22 studies that reported PSQI data, the pooled mean score was 4.32 (95%CI 3.82-4.81; SD = 0.502). The pooled mean sleep duration across 8 studies was 7.62 (95% CI 7.23-8.00; SD = 0.194) hours. Subgroup analyses showed that lower education (Q = 4.12, P = 0.042), living in less developed regions (Q = 60.28, P < 0.001), and lower PSQI cutoff values (Q = 9.80, P = 0.007) were significantly associated with PSQ. Meta-regression analyses showed that study quality was inversely associated with estimated PSQ prevalence (ß = - 0.442, P = 0.004). LIMITATIONS: Although measures such as subgroup and meta-regression analyses were performed, substantial heterogeneity remained. Information related to sleep quality, such as comorbid physical diseases or psychiatric disorders, substance use, occupational types, and employment status, were not reported in most studies. CONCLUSION: One in five people in the general population of China may have PSQ and people with lower education or living in western regions may be more susceptible.

Sleep quality disparities in different pregnancy trimesters in low- and middle-income countries: a systematic review and meta-analysis.

INTRODUCTION: Sleep is a crucial determinant of maternal and fetal health, significantly impacting the well-being of both the mother and her developing fetus. Poor sleep quality, characterized by difficulties in falling asleep or staying asleep, can cause poor pregnancy outcome. Conversely, studies came with inconsistent result in the prevalence of poor sleep quality in different trimester of pregnancy. Therefore, this systematic review and meta-analysis study aimed to compare the prevalence of poor sleep quality in different trimesters. METHOD: A systematic review and meta-analysis were done on published studies. Electronic data base search was done from PubMed, Hinari, Medline and Google Scholar. Data were extracted with Excel and the analysis were done using STATA version 17. Publication bias was assessed both graphically and statistically. I-square test was used to identify heterogeneity. RESULT: In this meta-analysis, 38 studies that measured poor sleep quality using the Pittsburg Sleep Quality Index (PSQI ≥ 5) were included. The pooled prevalence of poor sleep quality was identified as 37.46% (95% CI: 29.26, 45.67) in the first trimester, 47.62% (95% CI: 42.23, 53.02) in the second trimester, and 60.05% (95% CI: 51.32, 68.78) in the third trimester. CONCLUSION: This study identified a significant discrepancy in the prevalence of poor sleep quality, which increases as gestational age advances. Therefore, this discrepancy should be addressed, and additional support should be provided to pregnant women to help them achieve adequate sleep, especially as gestational age advances.

Poor sleep quality may contribute to dysfunctional illness perception, physical and emotional distress in hospitalised patients: results of a national survey of the Italian Society of Consultation-Liaison Psychiatry.

Distress associated with physical illness is a well-known risk factor for adverse illness course in general hospitals. Understanding the factors contributing to it should be a priority and among them dysfunctional illness perception and poor sleep quality may contribute to it. As poor sleep quality is recognised as a major risk factor for health problems, we aimed to study its association with illness perception and levels of distress during hospitalisation. This cross-sectional study included a consecutive series of 409 individuals who were hospitalised in medical and surgical units of different hospitals located throughout the Italian national territory and required an assessment for psychopathological conditions. Sleep quality was assessed with the Pittsburgh (Sleep Quality Index), emotional and physical distress with the Edmonton Symptom Assessment System (ESAS), and illness perception with the Brief Illness Perception Questionnaire (BIPQ). Differences between groups, correlations and mediations analyses were computed. Patients with poor sleep quality were more frequently females, with psychiatric comorbidity, with higher scores in the ESAS and BIPQ. Poor sleep quality was related to dysfunctional illness perception, and to both emotional and physical distress. In particular, by affecting cognitive components of illness perception, poor sleep quality may, directly and indirectly, predict high levels of distress during hospitalisation. Poor sleep quality may affect >70% of hospitalised patients and may favour dysfunctional illness perception and emotional/physical distress.Assessing and treating sleep problems in hospitalised patients should be included in the routine of hospitalised patients.

Sleep quality in men with androgenetic alopecia.

PURPOSE: Sleep disturbances affect human health and contribute to several comorbidities. In men, androgenetic alopecia (AGA) is a common, non-scarring form of hair loss that affects a patient's self-esteem. There are limited data regarding the association between poor sleep quality and male AGA. We aimed to compare the prevalence of sleep abnormalities between male patients with AGA and controls to identify an association between the two conditions. METHODS: A case-control study on patients with AGA and age-matched controls was conducted. Participants completed a standardized questionnaire that contained self-evaluated sleep measures, including Pittsburgh Sleep Quality Index (PSQI), Epworth Sleepiness Scale, and STOP-BANG questionnaire. Patients with AGA were classified into mild, moderate, and severe subgroups according to the Hamilton-Norwood classification for stratified analyses. Data between groups and among subgroups were compared. RESULTS: Of 446 male participants, 223 (50%) were in the AGA group, and the remainder (50%) were in the control group. Multivariable logistic regression analysis revealed that hypertension (odds ratio [OR] = 1.90, 95% confidence interval [CI] = 1.16-3.11, p = 0.011) and STOP-BANG score ≥ 5 (OR = 2.05, 95%CI = 1.15-3.66, p = 0.015) were associated with AGA. For subgroup analyses, ordinal logistic regression model showed a significant association between severe AGA and three sleep profiles, namely total sleep time ≤ 6 h (OR = 2.16, 95%CI = 1.02-4.57, p = 0.044), PSQI > 5 (OR = 3.72, 95%CI = 1.42-9.72, p = 0.008), and STOP-BANG score ≥ 5 (OR = 3.01, 95%CI = 1.11-8.13, p = 0.030). CONCLUSION: Our findings revealed an association between sleep disturbances and AGA, which may help guide appropriate management in these patients.

Association of obstructive sleep apnea and sleep quality with cognitive function: a study of middle-aged and elderly persons in India.

INTRODUCTION: Symptoms of obstructive sleep apnea (OSA) and poor sleep quality affect around one in ten people in India. We aimed to determine if OSA symptoms and poor sleep quality are independently associated with cognition in middle-aged and elderly urban Indian populations. METHODS: We studied the cross-sectional association between OSA symptoms (by Berlin Questionnaire), poor sleep quality (by Pittsburgh Sleep Quality Index), and cognitive function in adults ≥ 50 years. Using a standard neuropsychological battery for cognitive function, a G-factor was derived as the first rotated principal component assessing domains of information processing, memory, and executive function. The associations of exposures with cognitive measures were modeled using linear regression, adjusted for metabolic risk factors, lifestyle factors, and psychosocial problems, followed by stratified analysis by decadal age group. RESULTS: A total of 7505 adults were enrolled. Excluding those with MMSE < 26 (n 710), of 6795 individuals (49.2% women), mean (SD) age 64.2 (9.0) years, 38.3% had high risk of OSA symptoms, and 15.9% had poor sleep quality. OSA symptoms were negatively associated with cognitive domains of information processing (adjusted beta coefficient of z-score - 0.02, p-value 0.006), memory (- 0.03, 0.014), and G-factor (- 0.11, 0.014) in full-model. Stratified analysis by age group showed significant adverse effects of OSA symptoms on cognition for middle-aged people (50-60 years) (- 0.26, 0.001), but not in later age groups. Poor sleep quality was also associated with lower cognitive scores for G-factor (- 0.48, < 0.001), memory (- 0.08, 0.005), and executive domains (- 0.12, < 0.001), but not with information domain. CONCLUSION: The findings suggest that both symptoms of OSA and poor sleep quality have a direct adverse impact on cognition in an Indian setting. A modest effect of age on the relationship of OSA and cognition was also observed.

Metabolic risk factors and psychosocial problems independently explain poor sleep quality and obstructive sleep apnea symptoms among adults in urban India.

STUDY OBJECTIVES: To determine if metabolic risk factors are associated with poor sleep quality and obstructive sleep apnea-like symptoms (OSA symptoms) independent of psychosocial problems and demographic and lifestyle factors in older Indian adults. METHODOLOGY: We analyzed baseline data from adults (≥ 50 years) from a population-based cohort, the LoCARPoN study, in India. Variables were grouped as (a) demographic and lifestyle factors such as smoking, alcohol use, and physical activity; (b) psychosocial problems including symptoms of depression, anxiety, and perceived stress; and (c) metabolic risk factors including glycated hemoglobin, high-density lipoprotein, low-density lipoprotein, total cholesterol, body mass index, and hypertension. Variables were examined as predictors of poor sleep quality and OSA symptoms. Groups of variables were added stepwise to a logistic regression. Variance explained by nested models was quantified using McFadden's pseudo R2, and change was formally tested with the log-likelihood ratio test. RESULTS: Among 7505 adults, the prevalence of poor sleep quality was 16.9% (95% CI: 16.0, 17.7), and OSA symptoms were present in 7.0% (95% CI: 6.4, 7.6). Psychosocial problems had a strong independent association with both poor sleep quality (pseudo R2 increased from 0.10 to 0.15, p < 0.001) and more OSA symptoms (pseudo R2 increased from 0.08 to 0.10, p < 0.001). Metabolic risk factors had a modest independent association with sleep quality (pseudo R2 increased from 0.14 to 0.15, p < 0.01), but a strong association with OSA symptoms (pseudo R2 increased from 0.08 to 0.10, p < 0.001). CONCLUSION: Psychosocial and metabolic risk factors were independently associated with sleep quality and OSA symptoms. This fact implied that OSA symptoms may affect both mental health and physical health. Our findings have public health implications because the number and proportion of the elderly in India is increasing, while the prevalence of metabolic risk factors and psychosocial problems is high already. These facts have the potential to exacerbate not only the burden of sleep disorders and OSA symptoms but also associated cardiovascular and neurologic sequelae, further stretching the Indian health-care system.

Adverse childhood experiences and depressive symptoms among adolescents during the COVID-19 pandemic: mediating roles of poor sleep quality and psychological inflexibility.

Previous studies have found that adverse childhood experiences can lead to depressive symptoms. But the underlying mechanisms have not been determined. Guided by the 3-P model of insomnia and acceptance and commitment therapy, this study examined the mediating role of poor sleep quality and psychological inflexibility in the relationship between adverse childhood experiences and depressive symptoms during the COVID-19 pandemic. A total of 996 senior high school students in China (Mage = 16.57 years; SD = 1.03) completed the self-report measures of adverse childhood experiences, depressive symptoms, poor sleep quality, and psychological inflexibility. Multiple mediation analysis revealed that adverse childhood experiences were related to depressive symptoms through poor sleep quality and psychological inflexibility, serially. These findings point to potential targets in the prevention of and intervention in adolescent depressive symptoms.

Poor sleep quality and associated factors among HIV-positive pregnant women in Northwest, Ethiopia: a facility-based, cross-sectional study.

BACKGROUND: Poor sleep quality during pregnancy might have an impact on adverse birth outcomes like premature rupture of membrane, preterm birth, lifelong neurocognitive impairment, low birth weight, and increased the risk of neonatal morbidity and mortality. In Ethiopia, the magnitude of poor sleep quality among this group of people is extremely limited. So, this study aims to determine the magnitude of poor sleep quality and its associated factors among HIV-positive pregnant women attending public hospitals in Northwest Ethiopia. METHODS: An institution-based cross-sectional study was done using a simple random sampling technique to recruit 411 HIV-positive pregnant women from January to March; 2021. Sleep quality over the last 1 month was measured using the Pittsburgh Sleep Quality Index (PSQI). General anxiety disorder (GAD-7), Sleep Hygiene Index (SHI), and List of Threatening of Experiences (LTE) instruments were used to identify factors associated with poor sleep quality. Bivariate and multivariable logistic regression with odds ratio and 95% CI were employed to identify determinant factors of poor sleep quality. Statistical significance association was declared at P-value < 0.05. RESULTS: A total of 411 out of 423 HIV-positive pregnant women were interviewed, with a response rate of 97.1%. The overall magnitude of poor sleep quality among HIV-positive pregnant was found to be 39.4% with a 95% of confidence interval (CI) (34.3, 44.3). Stressful life events, [AOR = 3.10, 95% CI (1.60, 6.01)], having comorbid general anxiety symptoms [AOR = 2.46, 95% CI (1.58, 3.81)], unplanned pregnancy [AOR = 2.18, 95% CI (1.20, 3.96)], and poor sleep hygiene practice [AOR = 2.23, 95% CI (1.21, 4.10)] were significantly associated with poor quality of sleep. CONCLUSION: The overall magnitude of poor sleep quality among HIV-positive pregnant women was high. Stressful life events, poor sleep hygiene, unplanned pregnancy, and comorbid general anxiety symptoms were the determinant factors of poor sleep quality that should be taken high consideration for early detection and appropriate intervention for poor sleep quality in HIV-positive pregnant women.

Prevalence and associated factors of poor sleep quality among postpartum women in North West Ethiopia: a community-based study.

INTRODUCTION: Although sleep disturbance is a community problem, there is limited study in Ethiopia. Therefore, this study aimed to identify the prevalence and factors affecting postpartum poor sleep quality in women. METHOD: A community-based cross-sectional study was conducted from July 1st to August 30th, 2021 in Gondar city. The cluster sampling method was used to address 858 study participants. The Pittsburgh Sleep Quality Index (PSQI) 19-item self-report measure of sleep quality over the past month was used to measure maternal sleep quality during the postpartum period and a global PSQI score of 5 or more was used to indicate poor sleep quality. Binary logistic regression was used to identify variable association and 95% confidence level and adjusted Odds Ratio were used to declare association. RESULT: Poor sleep quality prevalence during postpartum period was 24.0% (95%CI: 21.3-26.9). factors significantly associated with poor sleep quality were family size [AOR = 1.76; 95% CI: (1.14-2.73)], unplanned pregnancy [AOR = 2.11; 95%CI: (1.17-3.80)], had a family history of mental illness [AOR = 3.70; 95%CI: (2.15-6.37)], had known medical disorders [AOR = 2.59; 95%CI: (1.51-4.43)], having intimate partner violence [AOR = 2.58; 95%CI: (1.78-3.75)], and women who can read and write and who complete secondary school [AOR = 2.60; 95% CI: (1.20-5.66)] and [AOR = 2.02; 95%CI: (1.16-3.53)] respectively. On the other hand, being housewife, merchant, and government-employed [AOR = 0.32; 95%CI: (0.14-0.73)], [AOR = 0.13; 95%CI: (0.05-0.34)], and [AOR = 0.38; 95%CI: (0.14-0.98)] respectively were identified to be factors significantly associated with poor sleep quality. CONCLUSION: Poor sleep quality prevalence is high in the community of Gondar city. Thus, setting strategies to increase women's educational level, providing health education programs to create awareness on the consequence of intimate partner violence which could reduce the violence; increasing screening for medical disorders before or during maternity period, preventing unplanned pregnancy with effective family planning method, and employing women in a certain organization will have a great role in reducing poor sleep quality.

Zolpidem improves patients' sleep quality after surgical treatment for infective endocarditis: a prospective observational study.

PURPOSE: The objective of this study was to investigate the efficacy of zolpidem for improving post-operative sleep quality among patients with infective endocarditis (IE) and to identify the potential risk factors for impaired sleep quality at 6 months after surgery. METHODS: Patients with IE who underwent surgical treatment were divided into two groups according to zolpidem usage. The Pittsburgh Sleep Quality Index (PSQI) and Epworth Sleepiness Scale (ESS) were used to evaluate patients' sleep quality and daytime sleepiness at baseline, which was the second day after transferal, and at 6 months after surgery. Logistic regression was used to identify potential risk factors. RESULTS: There were 32 patients in the zolpidem group and 42 in the control group. The PSQI and ESS scores at 6 months after surgery were significantly lower than those at baseline in both groups (P = 0.04). Additionally, 9 patients (28%) in the zolpidem group and 22 patients (52%) in the control group suffered poor sleep quality. Multivariate analysis identified age (odds ratio [OR] = 1.26, 95% confidence interval [CI]: 1.12-1.42), baseline PSQI score (OR = 2.66, 95%CI: 1.55-4.65), and no zolpidem usage (OR = 45.48, 95%CI: 3.01-691.23) as independent factors for poor sleep quality. CONCLUSIONS: Poor sleep quality after IE surgery was prevalent among patients even 6 months after IE surgery. Age, baseline PSQI score and no zolpidem usage were independently associated with poor sleep quality. Therefore, zolpidem has the potential to be an effective part of a treatment arsenal for poor sleep quality after surgical treatment for IE.

Associations of poor sleep quality, chronic pain and depressive symptoms with frailty in older patients: is there a sex difference?

BACKGROUND: Sleep disturbance, chronic pain and depressive symptoms later in life are modifiable risk factors and may contribute to frailty. However, much less is known about sex differences in the association between these concurrent symptoms and frailty in older patients. Therefore, we conducted this study to explore the associations of poor sleep quality, chronic pain, and depressive symptoms with frailty in older patients, and the sex-specific associations. METHODS: In an observational population-based study, 540 older hospitalized patients from Zhejiang Hospital in China were enrolled. We collected data on poor sleep quality, pain, depressive symptoms and frailty using the Pittsburgh Sleep Quality Index, the Numerical Rating Scale, the 15-item Geriatric Depression Scale, and the Clinical Frailty Scale. Multivariate logistic regression models were used to explore the total sample and sex-specific associations among symptom burdens, symptom combination patterns and symptom counts, and frailty. RESULTS: After adjusting for the potential covariates, concurrent poor sleep quality and depressive symptoms (OR = 4.02, 95% CI 1.57-10.26), concurrent poor sleep quality and chronic pain (OR = 2.05, 95% CI 1.04-4.05), and having three symptoms (OR = 3.52, 95% CI 1.19-10.44) were associated with a higher likelihood of frailty in older inpatients. In addition, older patients with 2 or 3 symptoms (2 and 3 vs. 0 symptoms) had a higher risk of frailty, and the odds ratios were 2.40 and 3.51, respectively. Interaction analysis and sex-stratified associations exhibited conflicting results. The nonsignificant effect of the interaction of sex and symptoms on frailty, but not the sex-stratified associations, showed that individual symptoms, symptom combination patterns, and symptom counts were associated with elevated risks of frailty in older male patients, but not in older female patients. CONCLUSIONS: Increased symptom burdens were associated with a higher risk of frailty in older inpatients, especially in those with poor sleep quality concurrent with at least one of the other two symptoms. Thus, a multidisciplinary program addressing these common symptoms is required to reduce adverse outcomes.

Evaluation of sleep quality and restless legs syndrome in adult patients with sickle cell anemia.

PURPOSE: To determine the prevalence of poor sleep quality and RLS in adult patients with sickle cell anemia (SCA). The second aim was to identify the risk factors for RLS and impairment of sleep quality in SCA patients. MATERIALS AND METHODS: Patients at least 18 years old, with hemoglobin electrophoresis confirmation of sickle cell disease, were included. Restless legs syndrome was diagnosed according to the International Restless Legs Syndrome Study Group criteria. The sleep quality of the patients was determined using the Pittsburgh Sleep Quality Index (PSQI) scale. The Epworth Sleepiness Scale (ESS) was used to assess excessive daytime sleepiness. RESULTS: Of 72 patients enrolled in the study, the median total PSQI score was 5 (R 1-17). The total PSQI score was significantly associated with increased age and number of acute severe or extremely severe painful crises during the previous year (p < 0.001, r = 0.45; p = 0.013, r = 0.291 respectively). Of 72 patients, 13 (18%) had RLS and 11 (15%) had excessive daytime sleepiness. The presence of RLS was significantly associated with increased age (p = 0.004). The presence of RLS was not associated with fetal hemoglobin, hemoglobin, hematocrit, or ferritin levels (p > 0.05 for all). CONCLUSION: The prevalence of RLS among this sample of adult patients with sickle cell anemia was much higher than that previously reported for the general Turkish population. The presence of RLS was an important cause of sleep disturbance in these adult patients with SCA.

Long-term exposure to ambient PM1 strengthened the association of depression/anxiety symptoms with poor sleep quality: The Henan Rural Cohort study.

Evidence from numerous epidemiological studies for the relationship between mental disorder and sleep quality was inconclusive and few studies assessed the modification effect of exposure to ambient air PM1 (particulate matter with an aerodynamic diameter ≤ 1.0 µm) on this association. In this study, 27,572 participants aged 18-79 years from The Henan Rural Cohort study were included in the final analyses. The Patient Health Questionnaire-2 (PHQ-2) and Generalized Anxiety Disorder-2 (GAD-2) scales were used to estimate the frequency of depression and anxiety symptoms of all participants, respectively. The Pittsburgh Sleep Quality Index (PSQI) scale was used to assess night sleep quality and PSQI global score (GSC) ≥ 6 was classified as poor sleep quality. The three-year average exposure concentration of PM1 before the baseline survey was determined as long-term exposure concentration of ambient PM1. Logistic regression model was conducted to estimate the independent or joint effect of depression/anxiety symptoms and ambient PM1 exposure on poor sleep quality. In the adjusted models, the odds ratios (ORs) and 95% confidence intervals (95% CIs) of poor sleep quality associated with depression and anxiety symptoms were 3.75 (3.37, 4.17) and 3.42 (3.06, 3.81), respectively, and that associated with long-term exposure to PM1 was 1.06 (1.03, 1.09). An interaction effect was observed between anxiety symptoms score and PM1 concentration on poor sleep quality. With the increment of PM1 concentration, the association was strengthened between depression/anxiety symptoms and poor sleep quality. Besides, compared with the reference group, the ORs (95% CIs) of poor sleep quality in those with comorbidity of depression and anxiety symptoms were 4.98 (3.95, 6.29), 5.23 (3.98, 6.87), 5.76 (4.42, 7.49), and 5.58 (3.83, 8.14), respectively, from the first to the fourth quartile level of the PM1 concentration. These findings suggested that long-term exposure to PM1 strengthened the association of depression/anxiety symptoms with poor sleep quality in rural China.

Sleeping is a nightmare: A qualitative study on the experience and management of poor sleep quality in women with fibromyalgia.

AIM: This study aimed to explore the experience and management of poor sleep quality in Spanish women with fibromyalgia (FM). DESIGN: This was a qualitative study based on one-to-one interviews. METHODS: Twenty-one adult women diagnosed with FM were recruited from the community between January and March 2020. Data were collected through in-depth semistructured one-to-one interviews, using an interview guide of open questions about the experience and management of poor sleep quality, and were analyzed with thematic qualitative analysis. The symptom management theory was used as a biopsychosocial conceptual framework. RESULTS: The results were organized into two themes: (a) experience of poor sleep quality and (b) management strategies for poor sleep quality. Poor sleep quality was found to be a severe symptom of FM that negatively impacts pain, fatigue, stiffness, mental health, and quality of life. The participants perceived pharmacological treatment to be the main approach of health care professionals for improving sleep, and most did not want this form of treatment. Self-management strategies lack clear beneficial effects on sleep quality. CONCLUSION: Women with FM recognize that they need to receive more information from nurses and allied professions about sleep in the context of FM and how to effectively manage poor sleep quality. IMPACT: This study contributes to a better understanding of how women with FM experience and manage poor sleep quality. More information about management strategies for poor sleep quality from nurses and other health care professionals is needed in women with FM. The results of this study can be applied by nurses and health care professionals, including sleep educators, in the treatment of this patient group.

The Influencing Factors of Sleep Quality Among Chinese Junior and Senior High School Adolescents During the COVID-19 Pandemic.

BACKGROUND: Since coronavirus disease 2019 (COVID-19) outbreak, its terrible infectiousness has caused great panic, anxiety and poor sleep quality to the vulnerable adolescent populations. METHODS: This cross-sectional online survey recruited 10 569 Chinese junior and senior high school adolescents during 31 January to 9 February 2020. Basic socio-demographic information, Pittsburgh Sleep Quality Index (PSQI), Self-rating Anxiety Scale (SAS) and Fear of negative evaluation (FNE) were included in the survey. The χ2 and logistic regression analyses were used to identify factors correlated with poor sleep quality. RESULTS: The prevalence of poor sleep quality was 18.6% in the Chinese adolescent population. The average score of PSQI was 3.39 (SD = 2.64), which was significantly correlated with scores for anxiety (r = 0.50, p < 0.01), and FNE (r = 0.36, p < 0.01). Adjusted logistic regression indicated that gender (females) and education (senior high school) were associated with poor sleep quality, while living in Hubei Province and time spent on the COVID-19 information were inversely associated with poor sleep quality. Having a family member or friend infected/suspected and spending time on electronics were associated with higher odds of having poor sleep quality. Adolescents with anxiety were 8 times, and those with FNE were three times more likely than ones without anxiety or FNE to have poor sleep quality. In addition, the number of meals, exercise time and diet quality were also significantly associated with sleep quality. (p < 0.05). CONCLUSIONS: Poor sleep quality was common during the COVID-19 pandemic in Chinese adolescents. Understanding several factors associated with the poor sleep quality will offer some important insights into determining potential interventions to improve sleep quality during the COVID-19 pandemic.

Association between household fuel use and sleep quality in the oldest-old: Evidence from a propensity-score matched case-control study in Hainan, China.

STUDY OBJECTIVES: Emerging evidence has documented that poor sleep quality associated with adverse effects with physical, psychological and neurological disorders, which impeded healthy aging. There is limited knowledge regarding the association of household air pollution (HAP) from solid fuel use with sleep quality, particularly among the population at advanced ages. The aim of this study is to investigate this association in oldest-old (≥80 years) populations. METHODS: China Hainan Centenarian Cohort Study was conducted in the 18 cities and counties of Hainan Province from 2015 to 2017. A total of 1725 individuals aged 80 years and older were included in the study. We used the Pittsburgh sleep quality index (PSQI) to measure individuals' sleep quality with a score of PSQI >8 indicating poor sleep quality. Solid fuel users were defined as those who primarily use coal, biomass charcoal, wood or straw for cooking in their daily life. The propensity score matching (PSM) was adopted and logistic regressions were performed based on the matched sample to estimate the association between the two factors. We adjusted for a wide range of covariates, including demographic, socioeconomic, health-related, and environmental factors. RESULTS: After matching, a total of 1616 participants (mean [SD] age, 94.5 [9.5] years; 72.5% women) were included in the final analysis. About 50.9% of the participants used solid fuel for cooking. The average global PSQI score was 8.26 (SD = 3.3), 49.0% of them were detected as poor sleep quality with a global PSQI score >8. We found significantly higher risk of having poor sleep quality among those who were currently solid fuel users than among clean fuel users, with an odds ratio (OR) of 1.43 (95% CI: 1.14-1.80), adjusting for a wide range of confounders. The associations were more pronounced in those who did not use any ventilation (compared to those who used either mechanical or natural cooking ventilation; 1.79 [1.30-2.47] vs. 1.27 [1.01-1.53], P for interaction = 0.016) and in those who were frequent cooking at home (compared to those who never cooked; 1.65 [1.21-2.26] vs. 1.18 [0.93-1.40], P for interaction = 0.025). CONCLUSIONS: Exposure to HAP from solid fuel combustion increases the risk of poor sleep quality at oldest-old ages. Our findings point to the need of reducing HAP from polluted fuel combustion and implementing cooking ventilation as a public health priority for healthy aging initiatives.

Prevalence and associated factors of poor sleep quality among Chinese older adults living in a rural area: a population-based study.

OBJECTIVE: To investigate the prevalence and associated factors of poor sleep quality among community-dwelling elderly population in a rural area of Northern China. METHODS: We conducted a cross-sectional survey in August-December 2014 and recruited 2195 participants who were aged 65 years or older and living in Yanlou Town of Yanggu County in western Shandong Province, China. Data on demographics, health-related behaviors, and clinical conditions were collected through structured interviews. The Pittsburgh Sleep Quality Index (PSQI) was used to assess the sleep quality and patterns. Poor sleep quality was defined as a PSQI score > 7. We employed multiple logistic models to relate poor sleep quality to various factors. RESULTS: The overall prevalence rates of poor sleep quality were 33.8% in the total sample, 39.2% in women and 26.3% in men (P < 0.01). The most common abnormal sleep domains were prolonged sleep latency (39.7%), decreased sleep duration (31.0%), and reduced habitual sleep efficiency (28.8%). Multiple logistic regression analyses revealed that poor sleep quality was significantly associated with female sex (OR = 1.76, 95% CI 1.46-2.12) and clinical comorbidities such as hypertension (OR = 1.28, 95% CI 1.06-1.54), coronary heart disease (OR = 1.60, 95% CI 1.27-2.00), and chronic obstructive pulmonary disease (OR = 1.82, 95% CI 1.34-2.49). CONCLUSIONS: The sleep disorders were highly prevalent among the elderly in rural China. Modifiable risk factors such as cardiometabolic risk factors and disorders were associated with poor sleep quality, which might be potential targets for interventions to improve sleep quality in elderly population.

Poor self-reported sleep quality and health-related quality of life in patients with chronic fatigue syndrome/myalgic encephalomyelitis.

Non-restorative sleep is a hallmark symptom of chronic fatigue syndrome/myalgic encephalomyelitis. However, little is known about self-reported sleep disturbances in these subjects. This study aimed to assess the self-reported sleep quality and its impact on quality of life in a Spanish community-based chronic fatigue syndrome/myalgic encephalomyelitis cohort. A prospective cross-sectional cohort study was conducted in 1,455 Spanish chronic fatigue syndrome/myalgic encephalomyelitis patients. Sleep quality, fatigue, pain, functional capacity impairment, psychopathological status, anxiety/depression and health-related quality of life were assessed using validated subjective measures. The frequencies of muscular, cognitive, neurological, autonomic and immunological symptom clusters were above 80%. High scores were recorded for pain, fatigue, psychopathological status, anxiety/depression, and low scores for functional capacity and quality of life, all of which correlated significantly (all p < 0.01) with quality of sleep as measured by the Pittsburgh Sleep Quality Index. Multivariate regression analysis showed that after adjusting for age and gender, the pain intensity (odds ratio, 1.11; p <0.05), psychopathological status (odds ratio, 1.85; p < 0.001), fibromyalgia (odds ratio, 1.39; p < 0.05), severe autonomic dysfunction (odds ratio, 1.72; p < 0.05), poor functional capacity (odds ratio, 0.98; p < 0.05) and quality of life (odds ratio, 0.96; both p < 0.001) were significantly associated with poor sleep quality. These findings suggest that this large chronic fatigue syndrome/myalgic encephalomyelitis sample presents poor sleep quality, as assessed by the Pittsburgh Sleep Quality Index, and that this poor sleep quality is associated with many aspects of quality of life.