[Focus on the effects of psychological problems and sleep disorders on tinnitus].

The effects of tinnitus on human health are receiving increasing attention, and it is currently believed that the central compensatory response caused by peripheral hearing loss is the main pathogenesis of chronic tinnitus. Tinnitus, psychological problems and sleep disorders affect and worsen each other, and should be taken seriously in treatment strategies. Chronic tinnitus treatment strategy advocates comprehensive treatment based on sound therapy, including reducing tinnitus sound perception and improving patients' negative mood and poor sleep. Whether treating tinnitus alone or treating relevant psychological problems and sleep disorders can break the vicious circle of tinnitus, psychological problems and sleep disorders. Therefore, balancing both psychological and sleep problems, is the direction of tinnitus treatment and research. The clinical study of the treatment of tinnitus should shift from the previous single tinnitus treatment mode and a single tinnitus evaluation index to the comprehensive treatment and comprehensive evaluation indicators that balance both psychotherapy and sleep improvement.

Prevalence and risk factors of sleep disorders in inflammatory bowel disease: a cross-sectional study.

BACKGROUND: Sleep disorders are one of the major public health problems, which can potentially induce inflammation and exacerbate disease activity, resulting in compromised sleep quality. This study aimed to investigate the prevalence and risk factors associated with sleep disorders among patients with inflammatory bowel disease (IBD). METHODS: Between March 2023 and February 2024, the Pittsburgh Sleep Quality Index was employed to assess sleep quality in both IBD patients and healthy control subjects. Univariate and multivariate analysis were performed to identify the risk factors associated with SD in IBD patients. RESULTS: Overall, 208 IBD patients [150 Crohn's disease (CD) and 58 ulcerative colitis (UC)] and 199 healthy individuals were included. Sleep disorders were observed in 59.6% of patients with IBD, with a higher prevalence among females (63.5%) compared to males (56.9%) (P = 0.476). The prevalence of sleep disorders in IBD patients was significantly higher than that found in healthy controls (37.7%) (all P < 0.01). The prevalence of sleep disorders  among CD and UC patients was 58% and 63.8%, respectively (P = 0.291). The multivariate analysis revealed that older age (OR, 1.070; 95% CI: 1.035-1.105, P = 0.000), smoking (OR, 2.698; 95% CI: 1.089-6.685, P = 0.032), and depression (OR, 4.779; 95% CI: 1.915-11.928, P = 0.001) were risk factors for sleep disorders in IBD patients. However, higher body mass index (OR, 0.879; 95% CI: 0.790-0.977, P = 0.017) was identified as a protective factor. CONCLUSION: Sleep disorders are common among IBD patients regardless of activity levels. Smoking and depression are the major risk factors.

Genetically predicted effects of 10 sleep phenotypes on revision of knee arthroplasty: a mendelian randomization study.

BACKGROUND: Accumulating evidence has suggested that sleep disturbances and disorders are common in patients who undergo knee arthroplasty. Revision surgery represents one of the most catastrophic outcomes of knee arthroplasty. However, it remains unclear whether sleep traits are the causes or consequences of knee arthroplasty revision. This study aimed to genetically examine the relationships between sleep traits and knee arthroplasty revision. METHODS: To determine the causal relationship between sleep traits and knee arthroplasty revision, we employed two-sample Mendelian randomization (MR) using summary statistics from the largest publicly available genome-wide association studies (GWASs). The MR design uses genetic variants as instrumental variables to help separate causal relationships from non-causal associations. The main analyses included an inverse variance weighted (IVW) meta-analysis to obtain primary effect estimates. Sensitivity analyses involving the weighted median approach and MR-Egger regression were also conducted to check for potential pleiotropic biases. Numerous complementary sensitivity analyses were also performed to identify statistically significant causal correlations when there were horizontal pleiotropy and heterogeneity across variants. Finally, a reverse MR analysis was performed to evaluate the possibility of reverse causation. RESULTS: In the absence of heterogeneity and horizontal pleiotropy, the IVW method revealed that genetically-predicted short sleep duration short sleep duration (average sleep duration of 24 h is 6 h or less) was positively correlated with the risk of knee arthroplasty revision (odds ratio = 1.03, 95% confidence interval = 1.01-1.05, and P = 0.003), while the association between genetically-predicted long sleep duration and knee arthroplasty was negative. The reverse MR analysis did not yield evidence supporting reverse causality relation between knee arthroplasty revision and sleep phenotypes. CONCLUSION: This research indicated that, of the 10 sleep phenotypes we analyzed, only sleep duration was causally associated with knee arthroplasty revision. These discoveries added to the understanding of the role of sleep traits in the etiology of knee arthroplasty revision, which might further expand our insights into the prevention of knee arthroplasty revision.

Correlation of Co-Morbidities with Symptom Severity of Children with Autism Spectrum Disorder: A Cross-Sectional Survey.

This study aims to identify potential correlations of the severity of symptoms of children with autism spectrum disorder (ASD) with serum nutritional levels, body composition indicators, diet partiality, and sleep disturbances. The cohort of this cross-sectional study included 120 children with ASD and 110 typically developing (TD) children to assess symptoms of ASD, and to measure serum levels of vitamins and minerals and the body composition values. Diet partiality and sleep disturbances were assessed by administering questionnaires. The serum levels of folic acid, copper, and vitamin B were lower in children with ASD than in TD children, while magnesium and homocysteine were higher (p < 0.05). Children with ASD had greater chest circumference, abdominal skinfold thickness, and body mass index (BMI) than TD children (p < 0.05), and higher prevalences of diet partiality and sleep disturbances (p < 0.001). Lower vitamin A levels and higher vitamin D levels were related to social impairment in children with ASD. Moreover, there were significantly positive correlations of BMI, chest circumference, diet partiality, and sleep disturbances with severity of ASD symptoms (p < 0.05). Collectively, rational nutritional supplementation, dietary management, and behavioral interventions are essential for children with ASD.

Association between sleep disturbances and challenging behavior in children and adolescents with Angelman syndrome.

Angelman Syndrome (AS) is a neurodevelopmental disorder with severe symptoms and associated comorbidities. It is caused by the inactivity or lack of the UBE3a gene. Symptoms of the syndrome include intellectual disability and developmental delay. The current study investigated sleep disturbances (SD) in children and adolescents with AS, associations between SD and possible predictors of SD. Variables examined included age, gender, newborn and infancy history, challenging behavior, type of therapy received, genetic type of AS, and seizures. The sample included data from 109 participants with a mean age of 8.21, accessed via the Global Angelman Syndrome Registry. Chi-square tests were carried out to assess the associations between the variables and a logistical regression was carried out to assess the possible predictors of SD. Associations were found between SD and certain repetitive behaviors: slapping walls, focal hand movements, and agitation at new situations. From these associations, a regression formed a predictive model for sleep disturbances. The findings of this research demonstrated the importance of investigating the relationship between sleep disturbances and challenging behavior in children and adolescents with AS and the need for further research in this area.

Machine learning approach to investigate pregnancy and childbirth risk factors of sleep problems in early adolescence: Evidence from two cohort studies.

BACKGROUND: This study aimed to predict early adolescent sleep problems using pregnancy and childbirth risk factors through machine learning algorithms, and to evaluate model performance internally and externally. METHODS: Data from the China Jintan Child Cohort study (CJCC; n=848) for model development and the US Healthy Brain and Behavior Study (HBBS; n=454) for external validation were employed. Maternal pregnancy histories, obstetric data, and adolescent sleep problems were collected. Several machine learning techniques were employed, including least absolute shrinkage and selection operator, logistic regression, random forest, naïve bayes, extreme gradient boosting, decision tree, and neural network. The area under the receiver operating characteristic curve, sensitivity, specificity, accuracy, and root mean square of residuals were used to evaluate model performance. RESULTS: Key predictors for CJCC adolescents' sleep problems include gestational age, birthweight, duration of delivery, and maternal happiness during pregnancy. In HBBS adolescents, the duration of postnatal depressive emotions was the primary perinatal predictor. The prediction models developed in the CJCC had good-to-excellent internal validation performance but poor performance in predicting the sleep problems in HBBS adolescents. CONCLUSION: The identification of specific perinatal risk factors associated with adolescent sleep problems can inform targeted interventions during and after pregnancy to mitigate these risks. Health providers should consider integrating these predictive factors into routine pre- and postnatal assessments to identify at-risk populations. The variability in model performance across different cohorts highlights the need for context-specific models and the cautious application of predictive analytics across diverse populations. Future research should focus on refining predictive models to account for such variations, potentially through the incorporation of additional socio-cultural factors and genetic markers. This study emphasizes the importance of personalized and culturally sensitive approaches in the prediction and management of adolescent sleep problems, leveraging advanced computational methods to enhance maternal and child health outcomes.

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.

Sleep disorder syndromes of post-acute sequelae of SARS-CoV-2 (PASC) / Long Covid.

INTRODUCTION: COVID-19 infection has resulted in a high prevalence of a post-infectious syndrome, known as post-acute sequelae of SARS-CoV-2 (PASC) or "Long COVID". PASC is a heterogeneous disease with a high prevalence of sleep disturbances, varying from an insomnia disorder to excessive daytime sleepiness. METHODS: Patients seen in the Covid Survivorship Program at the Beth Israel Deaconess Medical Center Boston, USA, were screened for sleep disorders as part of a comprehensive multi-system evaluation. Those who screened positive were referred for a comprehensive sleep evaluation in a dedicated COVID-19-Sleep clinic, followed by diagnostic sleep testing and treatment. This report summarizes patients who completed an American Academy of Sleep Medicine (AASM) accredited facility-based diagnostic evaluation. International Classification of Sleep Disorders 3rd Edition-Revised criteria were met for all diagnoses. RESULTS: In 42 patients with PASC, five categories of sleep disorder syndromes were observed following a sleep clinic evaluation, including obstructive sleep apnea, chronic insomnia disorder, primary hypersomnia, REM behavior disorder (RBD), and new onset circadian phase delay. Seven patients met criteria for idiopathic hypersomnia, and two had narcolepsy type 2. RBD patients were infected in three different waves; circadian disturbance patients were all infected in the winter wave of 2020/21, and the primary hypersomnolence group occurred during all waves, predominantly the initial wave of 2020. A peculiar form of insomnia was a persistent loss of sleep regularity. CONCLUSIONS: Specific sleep symptoms/syndromes are reported in this select group of patients with PASC/Long Covid. As new onset sleep complaints are prevalent in PASC, we recommend a complete clinical and investigative sleep evaluation for persistent severe sleep symptoms following COVID-19 infection.

Factors affecting poor sleep quality in last trimester pregnant women: a cross-sectional research from Turkey.

OBJECTIVE: The aim of the study was to determine the factors affecting poor sleep quality in the last trimester pregnant women. METHODS: A cross-sectional study was conducted at a tertiary care maternity hospital in Ankara, Turkey. The research was conducted between May and September 2019 with 570 pregnant women in the last trimester. The data were collected through the Personal Information Form, Pittsburgh Sleep Quality Index, International Physical Activity Questionnaire Short Form, Restless Legs Syndrome Form, Brief Fatigue Inventory, and Perceived Stress Scale. RESULTS: The mean Pittsburgh Sleep Quality Index score of the pregnant women was 5.98±3.31, and 48.9% of them were found to have over five Pittsburgh Sleep Quality Index scores. Hemoglobin levels, income perceptions, smoking habits, attending pregnant schools, experiencing leg pains or cramping, experiencing back, waist, or neck pains, Restless Legs Syndrome, fatigue levels, and perceived stress levels of the pregnant women were found to be important determinants of sleep quality (p<0.05). CONCLUSION: According to the findings, increasing hemogram levels, attending antenatal education programs, and improving the ability of pregnant women to manage stress are opportunities to improve sleep quality during pregnancy. Careful evaluation of pregnant women in terms of insomnia and affecting factors can be suggested during antenatal follow-up.

The association of sedentary time with sleep disturbances among the US population, 2005 to 2014.

BACKGROUND: Sleep problems increase the risk of premature illness and death. We evaluated the association between sedentary time and sleep disturbances. METHODS: A cross-sectional analysis of the US nationally representative data of 21,414 adults (aged > = 18 years) from National Health and Nutrition Examination Survey (NHANES) (2005-2014) was performed. The data of sleep disturbances were assessed using NHANES questionnaire results, which included the question, "{Have you/has sp} ever been told by a doctor or other health professional that {you have/s/he has} a sleep disorder?". All participants were stratified by quartiles of sedentary behavior distribution, which was the explanatory variable (sedentary time quartile cut points: Q1, 0 < = Q1 < 3 h; Q2, 3 < = Q2 < 5 h; Q3, 5 < = Q3 < 8 h; Q4, 8 < = Q4 < 20 h). We used multivariable logistic regression and the restricted cubic splines (RCS) model to assess the relationship between sedentary time and sleep disturbances. RESULTS: In the unadjusted multivariable logistic regression model (crude model), there was a demonstrated tendency for the odds of sleep disturbances to increase with the sedentary time (Q1 as reference, Q2: OR, 1.31 [95% CI 1.09-1.58] P = 0.005; Q3: OR, 1.62 [95% CI 1.39-1.88] P < 0.001; Q4: OR, 1.75 [95% CI 1.48-2.06] P < 0.001; P for trend < 0.001). In the adjusted model 4, adjustment for gender, age, marital type, education type, race, family poverty index ratio, waist circumference, recreational type, smoke status, drink status, diabetes mellitus status, cardiovascular disease status, sleep duration type, body mass index, the OR in Q2 subgroup didn't significantly increase (Q1 as reference. Q2: OR, 1.18 [95% CI 0.96-1.44] P = 0.1). However, the ORs in Q3 and Q4 (Q3: OR, 1.35 [95% CI 1.14-1.59] P < 0.001; Q4: OR, 1.45 [95% CI 1.21-1.75] P < 0.001) both revealed that the risk of sleep disturbances increased with increasing sedentary time, P for trend < 0.001. The unadjusted RCS model revealed that the risk of sleep disturbances increased non-linearly with increasing sedentary time for total participants (P for non-linearity < 0.001). After adjusting for all covariates, the RCS results revealed that the risk of sleep disturbances increased non-linearly with increasing sedentary time for total participants (P for non-linearity = 0.012). CONCLUSIONS: This study suggested that the longer sedentary time was strongly associated with the sleep disturbances. The protective effect of recreational activities on sleep disturbance, has not been significantly demonstrated.

Association between sleep quality and duration during pregnancy and risk of gestational diabetes: A systematic review and meta-analysis.

OBJECTIVE: Gestational diabetes mellitus (GDM) is associated with several adverse maternal and neonatal outcomes. Previous studies reported a link between altered sleep and risk of GDM. This systematic review aims to collate evidence on the association between impaired sleep quality and duration, and the risk of GDM. METHODS: PubMed, Embase, Web of Science, and Scopus databases were searched up to January 20, 2024. Studies reporting the association between impaired sleep quality and duration and risk of GDM were included. Sleep quality was assessed by the Pittsburgh Sleep Quality Index (PSQI). Random-effects meta-analysis was performed, and the results were reported as hazard ratio (HR) with 95% confidence interval (CI). RESULTS: 19 studies were included. Meta-analysis revealed a significant increase in the risk of GDM in pregnant women with poor sleep quality (i.e. <5 PSQI) (HR: 1.50, 95% CI: 1.26 - 1.78, p < .001). Sleep duration of <7 h (HR: 1.56, 95% CI.: 1.20 - 2.01, p < .001), and >8 h (HR: 2.32, 95% CI.: 1.19 - 4.50, p = .01) were also associated with a significantly higher incidence of GDM. CONCLUSION: Sleep quality and duration emerge as critical risk factors of GDM. Healthcare practitioners should consider targeted interventions to improve sleep hygiene as a potential measure for GDM prevention.

The association between epilepsy and sleep disturbance in US adults: the mediating effect of depression.

BACKGROUND: People with epilepsy (PWE) frequently experience sleep disturbances that can severely affect their quality of life. Depression is also a common symptom in the PWE population and can aggravate sleep problems. However, the interplay between epilepsy, depression, and sleep disturbances is not yet fully understood. Our study was designed to investigate the association between epilepsy and sleep disturbances in US adults and to determine whether depressive symptoms play a mediating role in this relationship. METHODS: We examined data from the National Health and Nutrition Examination Survey (NHANES) spanning January 1, 2015, to March 2020, before the pandemic.A total of 10,093 participants aged ≥ 20 years with complete data on epilepsy and sleep disturbance were included. Weighted multiple logistic regression and mediation analysis were used to explore the associations among depression, epilepsy, and sleep disturbance. Interaction effects of epilepsy with various covariates were also investigated. RESULTS: Epilepsy was associated with depression and sleep disturbances. Weighted logistic regression analysis revealed a significant association between epilepsy and sleep disturbances (OR = 3.67, 95% CI = 1.68-8.04). Depression partially mediated this relationship, demonstrating a mediation effect of 23.0% (indirect effect = 0.037, P < 0.001). Subgroup analyses revealed variations in the relationship between epilepsy and sleep disturbances among different groups. Furthermore, interaction analyses revealed significant interactions between epilepsy and age (P = 0.049) and hypertension (P = 0.045). CONCLUSIONS: Our study utilizing NHANES data confirmed that depression partially mediated the association between epilepsy and sleep disturbance. Additionally, we observed differences in this association across demographic groups. Addressing depressive symptoms in PWE may improve their sleep quality, but further research is needed to explore the underlying mechanisms.

Sleep Disturbance and Subsequent Suicidal Behaviors in Preadolescence.

Importance: Suicide is a leading cause of death among adolescents, who demonstrate high rates of sleep disturbance. Poor sleep appears to confer risk for suicide, but longitudinal investigation of suicidal behaviors remains rare, particularly in the transition from childhood to early adolescence. Objective: To evaluate sleep disturbances in preadolescent children (aged 9 and 10 years) in association with longitudinal risk for suicidal ideation and suicide attempts at the 2-year follow-up. Design, Setting, and Participants: This cohort study used data from the Adolescent Brain Cognitive Development Study between June 2016 and January 2021. This dataset included children aged 9 or 10 years at baseline and their parents or caregivers who were recruited at 21 sites across the US. Data were analyzed July 2023 to June 2024. Exposures: The Sleep Disturbance Scale for Children, a 26-item parent-reported inventory, was administered at baseline, generating a total score and 6 subscales. Central covariates included the Child Behavior Checklist Anxiety and Depression subscale and demographic variables. Main Outcomes and Measures: The computerized Kiddie Schedule for Affective Disorders and Schizophrenia (K-SADS-COMP) assessed parent- and youth-reported suicidal behaviors and outcomes (none; passive, active nonspecific, and active specific suicidal ideation; and suicide attempt) at the 2-year follow-up. Sleep disturbance was further grouped by symptom severity (minimal, moderate, elevated, high, and severe). Results: Of the 10 136 youths who reported no baseline suicidal ideation or behavior, 8807 youths (mean [SD] age, 9.9 [0.6] years; 4507 males [51.2%]; 197 Asian individuals [2.2%], 1273 Black individuals [14.5%], and 5775 White individuals [65.6%]) completed the K-SADS-COMP assessment at the 2-year follow-up and were included in the analysis. At the follow-up, 8044 participants (91.3%) had no suicidal behavior, 317 (3.6%) had passive suicidal ideation, 258 (2.9%) had active nonspecific suicidal ideation, 130 (1.5%) had active specific suicidal ideation, and 58 (0.7%) had a first-time suicide attempt. Baseline sleep disturbance was associated with increased incidence risk for suicidal behavior at age 12 years (odds ratio, 2.68; 95% CI, 1.44-4.98; P = .002), adjusting for covariates. Individual subscales or items demonstrating associations with risk included disorders of excessive somnolence and frequency of nightmares. Conclusions and Relevance: Results of this longitudinal cohort study revealed that disturbed sleep at age 10 years was associated with risk for suicidal thoughts and behaviors in the next 2 years. The findings highlight the potential importance of sleep as a visible risk factor and intervention target in the prevention of youth suicide.

Associations between sleep-related disorders and cardiovascular disease risk in hypertensive patients: Insights from the National Health and Nutrition Examination Survey (NHANES): A cross-sectional study.

Both sleep-related disorders (SRD) and hypertension (HTN) are closely related to the occurrence of cardiovascular disease (CVD); however, few studies have explored their combined effect. Based on the National Health and Nutrition Examination Survey (NHANES) database, we comprehensively analyzed the combined effect of SRD and HTN on the occurrence of CVD. The weighted multivariate logistic regression analysis was adopted to explore how SRD and HTN can affect the occurrence of CVD. Specifically, the additive interaction was evaluated by the relative excess risk due to interaction (RERI), attributable proportion (AP), and the synergy index (SI), and the multiplicative interaction was evaluated by the odds ratio (OR) along with 95% confidence interval (CI) from the product term. All the 33,383 participants from the NHANES database were divided into 2 groups, i.e., the CVD (n = 3712) and non-CVD (n = 29,671) groups. The results indicated that SRD (Model 3: OR = 1.90, 95% CI: 1.60-2.25) and HTN (Model 3: OR = 2.28, 95% CI: 1.87-2.79) were both significantly associated with an increased risk of CVD. Additionally, we observed a significant additive interaction (RERI = 0.88, 95% CI: 0.03-0.65; AP = 0.22, 95% CI: 0.01-0.21; SI = 1.15, 95% CI: 1.07-1.33) and a significant multiplicative interaction (OR = 1.07, 95% CI: 1.03-1.10) between SRD and HTN on the occurrence of CVD. While both SRD and HTN are associated with CVD occurrence, their interaction can also contribute to the development of CVD.

Sleep disorders are closely associated with coronary heart disease in US adults (≥20 years): A cross-sectional study.

The purpose of this research was to assess the association between sleep disorders and coronary heart disease (CHD) using data from the National Health and Nutrition Examination Survey (NHANES) database. This cross-sectional study included 9886 eligible participants with valid data on sleep disorders and CHD from the NHANES from 2011 to 2014. The complex NHANES sampling led to use of sample weights in analyses. Various statistical methods and covariates were utilized. Significance was set at P < .05. Receiver operating characteristic curves were used to assess the diagnostic efficacy of sleep disorders in relation to CHD. Sleep disorders were significantly associated with CHD (P < .001). In the model corrected for age, sex, race, hypertension, diabetes, and uric acid as covariates, sleep disorders and CHD remained significantly associated (P < .001, odds ratio = 1.83 [95% confidence interval: 1.31-2.58]). The correlation between sleep disorders and CHD varies by age and gender. Sleep disorders have some predictive value for CHD (0.5 < area under curve ≤ 0.7). Sleep disorders were associated with and predictive of CHD risk, warranting consideration in clinical assessments.

The association between weight-adjusted waist index and sleep disorders in U.S. adults: results from NHANES 2005-2008.

The detrimental effects of obesity on sleep disorders have garnered a lot of interest. The weight-adjusted waist index (WWI) is a newly developed anthropometric index calculated in terms of weight and waist circumference. The body mass index has been employed to evaluate obesity in the majority of studies that connect obesity to sleep disorders. This study seeks to investigate the correlation between WWI and sleep disorders among adults in the United States. This cross-sectional study was part of the National Health and Nutrition Examination Survey and included adults aged >20 from 2005 to 2008. This study investigated the linear relationship between sleep disorders and WWI using weighted binary logistic regression models. Nonlinear relationships were characterized using smooth curve fitting and threshold effects analyses. After that, based on variables like gender, age, marital status, diabetes, hypertension, and smoking, subgroup analyses were performed. Our study included 9869 participants who were at least 20 years old. Higher WWI was linked to greater odds of sleep disorders prevalence, according to weighted binary logistic regression (odds ratio = 1.15; 95% confidence interval, 1.10, 1.20). In subgroup analyses based on age, marital status, diabetes, hypertension, and smoking, this connection remained robust. However, there were notable differences in this connection depending on gender. Furthermore, a nonlinear correlation with inflection points between WWI and sleep disorders was shown using smooth curve fitting. The nonlinear association between WWI and sleep disorders has an inflection point of 8.1 cm/√kg, as indicated by the threshold effect analyses. A higher WWI exposure may elevate the odds of sleep disorder prevalence, underscoring the importance of considering WWI in the prevention and management of sleep disorders.

[Exposure to noise at home, emotional behaviour, and attention deficit hyperactivity disorder in 9-year-old children].

BACKGROUND: The purpose of this study was to assess the relationship between noise disturbance at home, sleep disturbance, and neurodevelopmental problems in 9-year-old children. MATERIAL AND METHODS: Noise exposure (frequency) perceived by 430 9-year-old children from the INMA cohort in Valencia, Spain, were reported by their mothers. The risk of developing attention deficit hyperactivity disorder, as well as internalizing and externalizing problems, were assessed using the Child Behaviour Checklist. RESULTS: The risk of internalizing (18%) and externalizing problems (11.7%) was higher compared to the risk of developing attention deficit hyperactivity disorder (1.4%) and were more prevalent in boys than in girls. The most common and bothersome noise exposures were generated at home (50.8-55.3%) and by neighbours (24.5%). The risk of neurodevelopmental problems was associated with sleep disturbances, particularly in relation with attention deficit hyperactivity disorder (16.1 vs 4%; p<0.001), with no differences observed between sex. Sleep disturbances were significantly more common in children exposed to noise from household or neighbours. High levels of noise exposure from street traffic and neighbours were linked to an increased risk of attention deficit hyperactivity disorder, while noise from other children at home was associated with a higher risk of internalizing and externalizing problems. These effects remained consistent even after adjusting for sleep disturbances. CONCLUSIONS: High levels of noise annoyance from various sources perceived at home are differently associated with the risks of different neurodevelopmental problems in 9-year-old boys and girls, with sleep disturbances not influencing this relationship.

The relationship between mental health problems and risk of infectious diseases: A Mendelian randomization analysis.

The causal effects of mental health problems on the risk of infectious diseases remain vague. Investigating them via observational study is challenging as it presents possible confounding factors. Therefore, the objective of this study was to utilize Mendelian randomization (MR) techniques to evaluate the causal relationship between mental health problems and the risk of infectious diseases. Multivariable MR analyses were performed using genome-wide association data for sleep disorders (N = 216,700), depression (N = 500,199), anxiety (N = 290,361), nervous feelings (N = 450,700), unspecified mental disorder (N = 218,792), pneumonia (N = 486,484), skin and subcutaneous tissue infection (SSTI; N = 218,792), intestinal infectious diseases (IIDs; N = 218,792), urinary tract infection (N = 463,010), and central nervous system (CNS) infections (N = 218,792) among individuals of European ancestry. Independent genetic variants significantly (P < 10-8) associated with each exposure were considered instruments. The primary analysis used an inverse variance-weighted method, followed by a series of sensitivity analyses. Genetically predicted sleep disorders were associated with an increased risk of SSTI (odds ratio [OR], 1.29 [95% confidence interval (CI), 1.05-1.59]; P = .017). Genetically predicted depression was linked with an increased risk of CNS infections (OR, 1.59 [95% CI, 1.00-2.53]; P = .049) and SSTI (1.24 [95% CI, 1.03-1.49]; P = .024). Genetically predicted anxiety was associated with IIDs (OR, 1.19 [95% CI, 1.03-1.37]; P = .017) and SSTI (OR, 1.21 [95% CI, 1.02-1.43]; P = .029). There was no significant causal evidence for genetic prediction of nervous feelings and unspecified mental disorders in IIDs, CNS infections, SSTI, pneumonia, or urinary tract infection. Sensitivity analyses showed that the above causal association estimates were robust. In this MR study, we demonstrated a causal relationship between sleep disorders, depression, anxiety, and the risk of infectious diseases. However, no evidence was found to support causality between nervous feelings, unspecified mental disorders, and the risk of infectious diseases.