Influencia da Qualidade do Sono na Qualidade de Vida no Trabalho de Policais Militares / Influencia de la Calidad del Sueño en la Calidad de Vida en el Trabajo de la Policía Militar / Influence of Sleep Quality on the Quality of Life and Work of Military Police Officers

Resumo Introdução: A profissão policial é considerada de alto risco e exige um vigor físico e mental do trabalhador diante do serviço realizado. De tal modo que uma boa qualidade do sono é importante, pois impacta diretamente em diversos aspectos na saúde desses trabalhadores. Ademais, a falta de uma boa qualidade do sono devido ao trabalho pode influenciar negativamente a qualidade de vida no trabalho. Objetivo: Analisar a influência da qualidade do sono na qualidade de vida no trabalho de policiais militares. Metodologia: Estudo quantitativo, correlacionalde corte transversal, realizado no primeiro semestre de 2019, com policiais de três municípios da Bahia, Brasil. Foram utilizados três instrumentos: sociodemográfico e características laborais; qualidade de vida de vida no trabalho; e qualidade do sono. Foi aplicado o teste do qui quadrado para as variáveis sociodemograficas e ocupacionais. Posteriormente, foi aplicado o teste de correlação de Spearman entre a qualidade do sono com as dimensões da qualidade de vida no trabalho. Resultados: Evidenciou-se entre os 298 policiais que a mediana da idade foi de 40 anos e tempo de serviço ≤ 7 anos, observou-se também que os policiais com pior qualidade do sono apresentaram qualidade de vida no trabalho insatisfatória em todas as dimensões (biológica/fisiológica; psicológica/comportamental; sociológica/relacional; econômica/política, ambiental/organizacional). Conclusão: Os policiais sofrem com a qualidade do sono e consequentemente influencia negativamente a qualidade de vida no trabalho. Assim, há uma necessidade de desenvolver ações no ambiente de trabalho que possam diminuir os afastamentos decorrentes dos problemas de saúde ocasionados pela qualidade do sono.

Resumen Introdución: La formación policial se considera de alto riesgo y requiere vigor físico y mental por parte de la persona trabajadora antes de realizar el servicio. Para esto, la buena calidad de sueño es importante, ya que impacta directamente en la salud de la población trabajadora en varios aspectos. Además, la falta de una buena calidad de sueño debido al trabajo puede influir negativamente en la calidad de vida fuera del trabajo. Objetivo: Analizar la influencia de la calidad del sueño en la calidad de vida en el trabajo de policías militares. Metodología: Estudio cuantitativo, correlacional transversal, realizado en el primer semestre de 2019, con policías de tres municipios de Bahía, Brasil. Se utilizaron tres instrumentos: características sociodemográficas y laborales, calidad de vida en el trabajo y calidad de sueño. Se aplicó la prueba chi cuadrado para las variables sociodemográficas y ocupacionales. Posteriormente, se aplicó la prueba de correlación de Spearman entre la calidad del sueño y las dimensiones de calidad de vida en el trabajo. Resultados: La muestra fue de 298 policías, la mediana de edad fue de 40 años y la antigüedad en el servicio fue ≤ 7 años. También, se observó quienes tuvieron peor calidad de sueño, también tuvieron una calidad de vida en el trabajo insatisfactoria en todos sus dimensiones (biológica/fisiológica; psicológica/conductual; sociológica/relacional; económica/política, ambiental/organizacional). Conclusión: Quienes son agentes de policía sufren de mala calidad de sueño y, en consecuencia, se influye negativamente su calidad de vida en el trabajo. Por lo tanto, existe la necesidad de desarrollar acciones en el lugar de trabajo que pueda reducir los riesgos de problemas de salud causados por la calidad del sueño.

Abstract Background: Police training is considered high risk and demands physical and mental vigor from the worker before preforming the service. Therefore, sleep quality is important as it directly impacts the health of these workers in several aspects. Furthermore, the lack of sleep quality due to work can negatively influence the quality of life outside of work. Aim: To analyze the influence of sleep quality on the quality of life and work of military police officers. Methods: A quantitative, cross-sectional correlational study, conducted in the first half of 2019 with police officers from three municipalities in Bahia, Brazil. Three instruments were used: sociodemographic and work characteristics; quality of life at work; and sleep quality. The chi-square test was applied for sociodemographic and occupational variations. Subsequently, the Spearman correlation test was applied between sleep quality and the quality of life and work dimensions. Results: Among the 298 police officers the median age was 40 years and the length of service was ≤ 7 years. It was also observed that police officers with poorer sleep quality had an unsatisfactory quality of life at work in all its dimensions (biological/physiological; psychological/behavioral; sociological/relational; economic/political, environmental/organizational). Conclusion: Police officers suffer from poor sleep quality and this negatively influence their quality of life and work. Therefore, there is a need to develop actions in the workplace that may reduce the risks of health problems caused by poor sleep quality.

Quality of sleep in individuals with systemic sclerosis and its correlation with functional disability and quality of life: a cross-sectional study.

OBJECTIVE: This study aimed to evaluate the quality of sleep in individuals with systemic sclerosis and its correlation with the quality of life and disability. METHODS: This is a cross-sectional study, carried out in a tertiary service of a university hospital. Inclusion criteria were diagnosis of systemic sclerosis according to the criteria of the American College of Rheumatology/European League Against Rheumatism 2013 or the preliminary criteria of the American College of Rheumatology 1980, age ≥ 18 years; regularly monitored at the outpatient clinic of rheumatology. Clinical and demographic data of the patients were obtained through a structured interview and evaluation of the medical records. Sleep quality was assessed using the Pittsburgh Sleep Quality Index questionnaire, daytime sleepiness using the Epworth Sleepiness Scale, quality of life using 12-item short-form health survey, and disability using the scleroderma health assessment questionnaire. RESULTS: A total of 50 patients with systemic sclerosis were included, with 92% female, mean age 48.9 years, mean disease duration 8.9 years, and 60% limited cutaneous form. Most systemic sclerosis patients (84%) have poor sleep quality and 20% have excessive daytime sleepiness. There was a significant negative correlation between Pittsburgh Sleep Quality Index and the physical and mental components of the 12-item short-form health survey (r=-0.42, p=0.003 and r=-0.43, p=0.002, respectively) and a positive correlation with the scleroderma health assessment questionnaire (r=0.52, p=<0.001). CONCLUSION: This study showed that poor sleep quality is a very common finding among systemic sclerosis patients, and it negatively affects both the quality of life and the degree of disability. Sleep quality is an unmet need in patients with systemic sclerosis Poor sleep quality is very common in patients with systemic sclerosis Poor sleep quality correlated with worse quality of life and greater disability.

The relationship between childhood adversity and sleep quality among rural older adults in China: the mediating role of anxiety and negative coping.

BACKGROUND: Studies have revealed the effects of childhood adversity, anxiety, and negative coping on sleep quality in older adults, but few studies have focused on the association between childhood adversity and sleep quality in rural older adults and the potential mechanisms of this influence. In this study, we aim to evaluate sleep quality in rural older adults, analyze the impact of adverse early experiences on their sleep quality, and explore whether anxiety and negative coping mediate this relationship. METHODS: Data were derived from a large cross-sectional study conducted in Deyang City, China, which recruited 6,318 people aged 65 years and older. After excluding non-agricultural household registration and lack of key information, a total of 3,873 rural older adults were included in the analysis. Structural equation modelling (SEM) was used to analyze the relationship between childhood adversity and sleep quality, and the mediating role of anxiety and negative coping. RESULTS: Approximately 48.15% of rural older adults had poor sleep quality, and older adults who were women, less educated, widowed, or living alone or had chronic illnesses had poorer sleep quality. Through structural equation model fitting, the total effect value of childhood adversity on sleep quality was 0.208 (95% CI: 0.146, 0.270), with a direct effect value of 0.066 (95% CI: 0.006, 0.130), accounting for 31.73% of the total effect; the total indirect effect value was 0.142 (95% CI: 0.119, 0.170), accounting for 68.27% of the total effect. The mediating effects of childhood adversity on sleep quality through anxiety and negative coping were significant, with effect values of 0.096 (95% CI: 0.078, 0.119) and 0.024 (95% CI: 0.014, 0.037), respectively. The chain mediating effect of anxiety and negative coping between childhood adversity and sleep quality was also significant, with an effect value of 0.022 (95% CI: 0.017, 0.028). CONCLUSIONS: Anxiety and negative coping were important mediating factors for rural older adult's childhood adversity and sleep quality. This suggests that managing anxiety and negative coping in older adults may mitigate the negative effects of childhood adversity on sleep quality.

Effort-reward imbalance and sleep quality in railway locomotive stewards: a cross-sectional study.

OBJECTIVE: To assess the correlation between the effort-reward imbalance (ERI) and sleep quality among railway locomotive stewards. DESIGN: Cross-sectional study. SETTING: Lanzhou Bureau Group, China Railway, between July and August 2022. PARTICIPANTS: Railway locomotive stewards. PRIMARY AND SECONDARY OUTCOME MEASURES: Sleep quality was assessed using the Pittsburgh Sleep Quality Index Scale (PSQI), categorising scores of >14 as poor, 8-14 as fair and <8 as good. RESULTS: A total of 5738 valid questionnaires (mean age of 30.85±6.91 years and 5730 males) were included. The response rate was 92.27%. The PSQI score was 11.52±3.95; 2304 (40.15%) respondents had good sleep quality, 1590 (27.71%) had fair sleep quality and 1844 (32.14%) had poor sleep quality. Stepwise multivariable logistic regression analysis showed that, compared with poor sleep quality, Jiayuguan Locomotive Depot workers (OR 0.775, 95% CI 0.587 to 0.971, p=0.028), electric locomotive drivers (OR 0.499, 95% CI 0.316 to 0.786, p=0.003), passenger train locomotive drivers (OR 0.209, 95% CI 1.313 to 3.337, p=0.002), working <40 hours weekly (OR 2.291, 95% CI 1.686 to 3.112, p<0.001), working 40-50 hours weekly (OR 1.602, 95% CI 1.299 to 1.977, p<0.001), senior titles (OR 0.727, 95% CI 0.570 to 0.928, p=0.010), high effort/low reward (OR 2.812, 95% CI 2.218 to 3.564, p<0.001) and low overcommitment (OR 5.848, 95% CI 4.710 to 7.261, p<0.001) were independently associated with fair sleep quality. Electric locomotive drivers (OR 0.535, 95% CI 0.364 to 0.787, p=0.001), diesel locomotive drivers (OR 0.567, 95% CI 0.348 to 0.924, p=0.023), passenger train locomotive drivers (OR 1.471, 95% CI 1.005 to 2.155, p=0.047), working <40 hours weekly (OR 1.549, 95% CI 1.196 to 2.006, p=0.001), working 40-50 hours weekly (OR 1.340, 95% CI 1.141 to 1.574, p<0.001), high school diploma or less (OR 1.448, 95% CI 1.062 to 1.975, p=0.019), high effort/low reward (OR 1.237, 95% CI 1.006 to 1.521, p=0.044), balanced effort-reward (OR 0.653, 95% CI 0.478 to 0.892, p=0.007) and low overcommitment (OR 2.553, 95% CI 2.224 to 2.931, p<0.001) were independently associated with good sleep quality. CONCLUSION: The results revealed an acceptable ERI and poor sleep quality among railway stewards. ERI was correlated with sleep quality. Health education, lifestyle changes and improved work schedules may help boost sleep quality and well-being among railway locomotive stewards.

Exploring workability in an older working population: associations with cognitive functioning, sleep quality, and technostress.

Objective: This observational study investigates workability and its associations with cognitive functioning, sleep quality and technostress among an older working population, also shedding light on potential differences between two occupational categories with different work schedules. Methods: Workers aged over 50, employed in different working sectors (banking/finance, chemical and metal-mechanic industry) were administered a self- report questionnaire including Work Ability Index (WAI), cognitive tests (Stroop Color Task, Corsi Blocks, Digit Span), sleep quality questionnaires (Pittsburgh Sleep Quality Index-PSQI; Insomnia Severity Index-ISI; Ford Insomnia Response to Stress Test-FIRST) and technostress scale. Linear regression models evaluated associations among variables, interaction effects investigated potential moderators. Results: A total of 468 aged workers categorized as white (WCWs; N = 289, 62%) or blue collars (BCWs; N = 179, 38%) were enrolled; most BCWs (N = 104; 58%) were night shift workers. WCWs reported higher workability, cognitive functioning, sleep quality and lower technostress (except for invasion and privacy subscales) than BCWs. Associations between cognitive functioning and workability were statistically significant only for BCWs [slopes equal to 0.2 (0.33), 0.8 (0.34), -0.02 (0.001) for Memory Span Corsi, Block Span Digit and Interference Speed respectively]; additionally, sleep quality significantly moderated this association (p = 0.007). Higher levels of technostress were associated with lower workability, and this relationship was stronger for BCWs. Conclusion: The aging of the workforce has important implications for occupational health and safety. Our findings suggest potential interventions and protective measures to promote older workers' wellbeing; blue-collar workers particularly should benefit from tailored intervention to sustain workability and prevent technostress, considering the role of healthy sleep habits promotion.

Bidirectional Associations Between Loneliness, Emotional Support, and Sleep in Daily Life.

OBJECTIVE: Evidence suggests a link between positive social relationship perceptions and improved sleep (e.g., quality, efficiency) across the life span. Less work has probed the directionality of these relationships. Here, we report findings from the first study to examine bidirectional between- and within-person associations between loneliness and emotional support with daily life measures of sleep. METHODS: Participants were 389 healthy adults aged 40 to 64 years (61% female) who completed hourly surveys assessing loneliness and perceptions of emotional support over the course of 4 days. Measures of actigraphy-assessed sleep and nightly sleep quality were also assessed for 7 to 10 days. RESULTS: Individuals with lower average daily loneliness showed higher sleep quality and efficiency than individuals with higher loneliness (r = -0.19, p < .001; r = -0.14, p = .008, respectively), and greater average emotional support was likewise linked with better sleep quality (r = 0.18, p < .001). Controlling for neuroticism attenuated the effects of average loneliness on sleep. Within-person analyses showed unexpected bidirectional effects. Specifically, days in which people felt relatively lonelier were followed by nights with greater sleep efficiency (γ = 1.08, p = .015), and nights when people reported relatively poorer sleep quality were followed by days with greater emotional support (γ = -0.04, p = .013). These unexpected findings are probed in exploratory analyses. CONCLUSIONS: Individuals with higher loneliness and lower emotional support report poorer sleep quality and efficiency, on average. Day-to-day fluctuations in perceptions of social relationships may affect the following night's sleep, and vice versa.

The Association of Multidimensional Sleep Health With HbA1c and Depressive Symptoms in African American Adults With Type 2 Diabetes.

OBJECTIVE: Sleep is important for diabetes-related health outcomes. Using a multidimensional sleep health framework, we examined the association of individual sleep health dimensions and a composite sleep health score with hemoglobin A1c (HbA1c) and depressive symptoms among African American adults with type 2 diabetes. METHODS: Participants (N = 257; mean age = 62.5 years) were recruited through local churches. Wrist-worn actigraphy and sleep questionnaire data assessed multidimensional sleep health using the RuSATED framework (regularity, satisfaction, alertness, timing, efficiency, duration). Individual sleep dimensions were dichotomized into poor or good sleep health and summed into a composite score. HbA1c was assessed using the DCA Vantage™ Analyzer or A1CNow® Self Check. Depressive symptoms were assessed using the Patient Health Questionnaire (PHQ-9). Regression models examined the association of individual sleep dimensions and composite sleep health with HbA1c and depressive symptoms. RESULTS: Higher composite sleep health scores were associated with a lower likelihood of having greater than minimal depressive symptoms (PHQ-9 ≥ 5) (odds ratio [OR] = 0.578, 95% confidence interval [CI] = 0.461-0.725). Several individual sleep dimensions, including irregularity (OR = 1.013, CI = 1.005-1.021), poor satisfaction (OR = 3.130, CI = 2.095-4.678), and lower alertness (OR = 1.866, CI = 1.230-2.833) were associated with a greater likelihood of having depressive symptoms. Neither composite sleep health scores nor individual sleep dimensions were associated with HbA1c. CONCLUSIONS: Better multidimensional sleep health is associated with lower depressive symptoms among African American adults with type 2 diabetes. Longitudinal research is needed to determine the causal association between multidimensional sleep health and depressive symptoms in this population. TRIAL REGISTRY: ClinicalTrials.gov identifier NCT04282395.

Financial Hardship and Sleep Quality Among Black American Women With and Without Systemic Lupus Erythematosus.

OBJECTIVE: To compare dimensions of financial hardship and self-reported sleep quality among Black women with versus without systemic lupus erythematosus (SLE). METHODS: Participants were 402 Black women (50% with validated diagnosis of SLE) living in Georgia between 2017 and 2020. Black women with SLE were recruited from a population-based cohort established in Atlanta, and Black women without SLE were recruited to be of comparable age and from the same geographic areas as SLE women. Financial hardship was measured using three different scales: financial adjustments, financial setbacks, and financial strain. Sleep was assessed continuously using the Pittsburgh Sleep Quality Index (PSQI) scale. Each dimension of financial hardship was analyzed separately in SLE-stratified multivariable linear regression models and adjusted by sociodemographic and health status factors. RESULTS: Dimensions of financial hardship were similarly distributed across the two groups. Sleep quality was worse in Black women with, versus without, SLE (p < .001). Among Black women with SLE, financial adjustment was positively associated with a 0.40-unit increase in poor sleep quality (95% CI = 0.12-0.67, p = .005). When accounting for cognitive depressive symptoms, financial setbacks and strain were somewhat attenuated for Black women with SLE. Overall, no associations between financial hardships and sleep quality were observed for the women without SLE. CONCLUSIONS: Black women with SLE who experience financial hardships may be more at risk for poor sleep quality than Black women without SLE. Economic interventions targeting this population may help improve their overall health and quality of life.

"The worst thing is lying in bed thinking 'I want a cigarette'" a qualitative exploration of smoker's and ex-smoker's perceptions of sleep during a quit attempt and the use of cognitive behavioural therapy for insomnia to aid cessation.

Smokers report poorer sleep quality than non-smokers and sleep quality deteriorates further during cessation, increasing risk of smoking relapse. Despite the use of cognitive behavioural therapy for insomnia (CBT-I) to aid quit attempts emerging in the area, little is known about smokers and ex smoker's experiences of sleep during a quit attempt or their perceptions of CBT-I. This study addresses this gap by exploring smoker's and ex-smoker's experiences of the link between smoking and sleep and how this may change as a function of smoking/smoking abstinence. It also explores views of traditional CBT-I components (i.e., perceived feasibility, effectiveness, barriers of use). We conducted semi-structured interviews with current and recently quit smokers (n = 17) between January and September 2022. The framework method was used for analysis. Four themes addressing research questions were described. These included: 1) A viscous cycle; poor sleep quality and negative psychological state during cessation; 2) Perceived engagement and effectiveness; the importance of feasibility, experience, value, identity and psychological state in assessing CBT-I as a cessation tool; 3) Striking a balance; tailoring CBT-I to reduce psychological overload in a time of lifestyle transition; and 4) Personalisation and digital delivery helping overcome psychological barriers during cessation. The analysis suggested during quit attempts smokers experienced a range of sleep problems that could increase risk of relapse due to a negative impact on psychological state. It also revealed participants thought that CBT-I is something they would use during a quit attempt but suggested changes and additions that would improve engagement and be better tailored to quitting smokers. Key additions included the integration of smoking-based cognitive restructuring, starting the intervention prior to a quit attempt, and the need for personalisation and tailoring.

Mood and Sleep Quality in Peruvian Medical Students During COVID-19 Pandemic.

INTRODUCTION: The prolongation and consequences of the COVID-19 pandemic have led to an uncertain and devastating panorama in many populations, and the evidence shows a high prevalence of mental health problems in medical students. The objective was to evaluate the association between mood disorders and sleep quality (SQ) in Peruvian medical students during the COVID-19 pandemic. METHODS: A cross-sectional study was conducted on 310 medical students from a private university in Peru. The SQ was measured using the Pittsburgh Sleep Quality Index (PSQI), while mood disorders were evaluated using the Depression Anxiety and Stress Scale-21 (DASS-21). All information was collected by online surveys and then analysed in the R programming language. RESULTS: The SQ results measured by PSQI were poor in 83.9% of the medical students. In the Poison regression analysis, the results of the bivariate analysis in men show that all mood disorders found the prevalence of poor SQ. However, in the multivariate analysis only stress (PRa=1.30; 95% CI, 1.08-1.57; P<0.01) and anxiety (PRa=1.34; 95% CI, 1.09-1.56; P <0.01) increased the prevalence of poor SQ. Women had a similar pattern in bivariate analysis, whereas in multivariate analysis, only severe stress (PRa=1.15; 95% CI, 1.01-1.29; P <0.05) increased the prevalence of poor SQ. CONCLUSIONS: This study allows us to observe the consequences that the COVID-19 pandemic is having on medical students in Peru. It also revealed a population group vulnerable to poor quality of sleep and bad mood, which in the future will impact on health. It is suggested to educate medical students about the importance of proper sleep hygiene and the consequences of poor sleep hygiene practices.

Association Between Sleep Quality and Deep Learning-Based Sleep Onset Latency Distribution Using an Electroencephalogram.

To evaluate sleep quality, it is necessary to monitor overnight sleep duration. However, sleep monitoring typically requires more than 7 hours, which can be inefficient in termxs of data size and analysis. Therefore, we proposed to develop a deep learning-based model using a 30 sec sleep electroencephalogram (EEG) early in the sleep cycle to predict sleep onset latency (SOL) distribution and explore associations with sleep quality (SQ). We propose a deep learning model composed of a structure that decomposes and restores the signal in epoch units and a structure that predicts the SOL distribution. We used the Sleep Heart Health Study public dataset, which includes a large number of study subjects, to estimate and evaluate the proposed model. The proposed model estimated the SOL distribution and divided it into four clusters. The advantage of the proposed model is that it shows the process of falling asleep for individual participants as a probability graph over time. Furthermore, we compared the baseline of good SQ and SOL and showed that less than 10 minutes SOL correlated better with good SQ. Moreover, it was the most suitable sleep feature that could be predicted using early EEG, compared with the total sleep time, sleep efficiency, and actual sleep time. Our study showed the feasibility of estimating SOL distribution using deep learning with an early EEG and showed that SOL distribution within 10 minutes was associated with good SQ.

Self-reported and accelerometry measures of sleep components in adolescents living in Pacific Island countries and territories: Exploring the role of sociocultural background.

OBJECTIVES: The objective of this study is to assess the concordance and its association with sociocultural background of a four-question survey with accelerometry in a multiethnic adolescent population, regarding sleep components. Based on questions from the Pittsburgh Sleep Quality Index and adapted to a school context, the questionnaire focussed on estimating sleep onset time, wake-up time and sleep duration on both weekdays and weekends. This subjective survey was compared with accelerometry data while also considering the influence of sociocultural factors (sex, place of living, ethnic community and socio-economic status). METHODS: Adolescents aged 10.5-16 years (n = 182) in New Caledonia completed the survey and wore an accelerometer for seven consecutive days. Accelerometry was used to determine sleep onset and wake-up time using validated algorithms. Based on response comparison, Bland-Altman plots provided agreement between subjective answers and objective measures. We categorized participants' answers to the survey into underestimated, aligned and overestimated categories based on time discrepancies with accelerometry data. Multinomial regressions highlighted the sociocultural factors associated with discrepancies. RESULTS: Concordance between the accelerometer and self-reported assessments was low particularly during weekends (18%, 26% and 19% aligned for onset sleep time, wake-up time and sleep duration respectively) compared with weekdays (36%, 53% and 31% aligned, respectively). This means that the overall concordance was less than 30%. When considering the sociocultural factors, only place of living was associated with discrepancies in onset sleep time and wake-up time primarily on weekdays. Rural adolescents were more likely to overestimate both onset sleep time (B = -1.97, p < 0.001) and wake-up time (B = -1.69, p = 0.003). CONCLUSIONS: The study found low concordance between self-assessment and accelerometry outputs for sleep components. This was particularly low for weekend days and for participants living in rural areas. While the adapted four-item questionnaire was useful and easy to complete, caution should be taken when making conclusions about sleep habits based solely on this measurement.

Influence of psychometric and sleep quality features on painful mechanical sensitivity and pain modulation in patients with temporomandibular disorders.

Investigating the collective impact of psychometric properties and sleep quality on pain sensitivity in temporomandibular disorder (TMD) patients could improve clinical management strategies. OBJECTIVE: Assessing whether combined psychometric properties and sleep quality impact painful mechanical sensitivity and pain modulation in TMD patients. MATERIALS AND METHODS: A cross-sectional study using secondary data analysis of 77 TMD patients and 101 controls. All participants completed questionnaires characterizing their psychometric profile (anxiety, depression, stress and catastrophizing) and sleep quality, alongside psychophysical tests for painful mechanical sensory (mechanical pain threshold (MPT), pressure pain threshold (PPT), and wind-up ratio (WUR)) and conditioned pain modulation (CPM). Participants were grouped into "High distress" or "Low distress" categories based on psychometric properties and sleep quality using hierarchical cluster and k-means analyses. Multiple linear regression evaluated the influence of TMD, age, and the distress cluster on MPT, WUR, PPT, and CPM in masseter and thenar muscles. Differences were statistically significant when p < 0.05. RESULTS: The presence of TMD was the strongest predictor of mechanical painful sensitivity in the trigeminal region (MPT[F(3,174) = 51.902;p < .001;R2 = .463]; TMD presence (ß = -.682) / PPT[F(3,174) = 15.573;p < .001;R2 = .198] TMD presence (ß = -.452), and extra-trigeminal (MPT[F(3,174) = 35.897;p < .001;R2 = .382] TMD (ß = -.647) / CPM [F(3,174) = 4.106;p < .05;R2 = .050] TMD presence (ß = .197). Furthermore, neither the high distress group nor the low distress group were able to significantly influence the variation of the values of any of the psychophysical variables evaluated (p > .05). CONCLUSIONS: There is not a significant influence of impairment clusters based on psychological variables and sleep quality on painful mechanical sensitivity and pain modulation, regardless of the presence of TMD. CLINICAL RELEVANCE: This outcome suggests that psychosocial factors and sleep quality may not play a decisive role in the sensory-discriminative aspect of pain, particularly concerning painful TMD.

[Association between the clustering of adverse childhood experiences and sleep quality in middle-aged and older Chinese adults].

Objective: To examine the association between the clustering of adverse childhood experiences (ACEs) and sleep quality in middle-aged and older Chinese adults. Methods: Data were from the Life History Survey in 2014 and the third wave follow-up survey in 2015 of China Health and Retirement Longitudinal Study (CHARLS). A total of 10 824 participants aged 45 years and above were included in this study. According to the number of ACEs, the participants were divided into four groups: 0, 1, 2-3 and≥4 ACEs. The multivariate logistic regression model was used to analyze the association of ACEs clustering with inappropriate sleep duration and poor sleep quality in middle-aged and older adults. Results: Among the 10 824 participants with an average age of (60.83±9.06) years, 5 211 (48.14%) were males. About 6 111 participants (56.64%) had inappropriate sleep duration, and 3 640 participants (33.63%) had poor sleep quality. After adjusting for covariates including gender, age, residence, marital status, education, household consumption, BMI, smoking, drinking, and depression in adulthood, compared with the 0 ACE group, the risk of inappropriate sleep duration was significantly increased in the 2-3 ACEs group and≥4 ACEs group, while ORs (95%CIs) were 1.26 (1.12-1.41) and 1.43 (1.23-1.66), respectively. The risk of poor sleep quality in the 2-3 ACEs group and≥4 ACEs group was also significantly higher than that in the 0 ACE group, while ORs (95%CIs) were 1.28 (1.12-1.46) and 1.53 (1.29-1.80), respectively. Conclusion: ACEs clustering in childhood could negatively affect sleep duration and quality in middle-aged and older Chinese adults.

Association between self-perception of the neighborhood environment and sleep problems in older Brazilian adults: findings from ELSI-Brazil.

This study aimed to investigate associations between neighborhood perception and sleep problems in older Brazilian adults. A cross-sectional study was conducted with 5,719 community-dwelling older adults (≥ 60 years) from the Brazilian Longitudinal Study of Aging (ELSI-Brazil, 2019-2021). The outcomes were self-reported sleep problems: poor sleep quality, daytime sleepiness, primary insomnia complaints, difficulty staying asleep, and waking up at dawn. The exposure variables were questions about the perception of participants about the physical and social environment of the neighborhood. Logistic regression was used in data analysis. Garbage, rubbish, or tall grass on the streets and the desire to move were associated with higher odds of poor sleep quality. Concern about falling due to damaged sidewalks, concern about having difficulties taking transportation, and concern about having difficulties crossing the street were associated with higher odds of all sleep problems. Sound/noise of buses and cars was associated with higher odds of some sleep problems. Perceiving the neighborhood as a good place to live was associated with lower odds of daytime sleepiness and primary insomnia complaints. Trusting most people in the neighborhood and perceiving that kids and younger people treat adults with respect were associated with lower odds of daytime sleepiness, primary insomnia complaints, and waking up at dawn. Being a good place for kids to play and raise teenagers was associated with lower odds of daytime sleepiness. These results can assist public administrators in creating urban planning policies aimed at improving neighborhood environments as a means of health promotion.

Sleep initiation patterns and sleep quality among toddlers in the southeast of China: initial study results.

BACKGROUND: A large number of psychological consequences including sleep health emerged during the 2019 Coronavirus disease (COVID-19) pandemic. Sleep patterns in toddlers are vulnerable to negative environmental exposures, however, very few studies on this topic have been published so far. OBJECTIVES: In this paper, we aimed to investigate the sleep patterns and associated factors in toddlers from China confined at home in the context of COVID-19 pandemic. METHODS: From April to November 2021, a convenience sample of 493 parents of young children aged (12-35 months) were surveyed from Fuzhou, Sanming, Quanzhou, Nanping, and Longyan cities in the Fujian Province, China. A cross-sectional survey was conducted via Electronic questionnaires to collect parent and child social-demographic characteristics. The Brief Infant Sleep Questionnaire (BISQ) was used to collect data on sleep practices, sleep duration and patterns, as well as the number of nocturnal awaking . RESULTS: The mean age of toddlers was 2.11 years old, and 52.54% (259/493) were males. Among the 493 toddlers' sleep patterns, 331(67.1%) initiated sleep accompanied by parents, 67(13.6%) slept independently, 59 (12.0%) were breast fed/bottle fed to initiate sleep, 27 (5.5%) were held and 9 (1.8%) rocked. The clear longitudinal association between the duration of night-time sleep, the frequency of nighttime awakenings, and various sleep patterns remains clear (p < 0.05). Multiple linear regression analysis indicated that sleep initiation with bottle-feeding/breast-feeding and rocked significantly increased the frequency of nighttime awakenings and reduced the duration of nighttime sleep (p < 0.05), as held was dramatically only for increasing the number of nighttime awakenings (p < 0.05). Multi-variate logistic regression analysis demonstrated that toddlers with severe sleep difficulties had a higher probability of being rocked to initiate sleep (p < 0.05). Conversely, young children with minor sleep problems were more apt to be in bed alone to initiate sleep (p < 0.05). CONCLUSIONS: During the COVID-19 pandemic, most infants and toddlers initiated sleep accompanied by parents and tend to have electronic media exposure before bedtime. Increased waking at night may be associated with sleep initiation with breast-feeding/bottle-feeding. Therefore, pediatric practitioners in primary community hospitals should pay attention to the education and promotion of sleep hygiene and parenting knowledge of young children to avoid the formation of poor sleep hygiene habits.

Early sleep intervention for improving infant sleep quality: a randomized controlled trial, preliminary result.

BACKGROUND: Healthy sleep issues should provide to family within first 6 months of infant's life. This study aimed to evaluate the effect of early sleep intervention on nighttime sleep quality. METHODS: Eligible infants aged 4 months ± 2 weeks were randomized to receive early sleep intervention or usual care. Data on sleep variables were obtained via parental interview at baseline and 6 months of age. Using logistic regression to analyze the efficacy of early sleep intervention. RESULTS: At baseline, 335 eligible infants were enrolled and randomized. In total, 306 participants were final analyzed: early sleep intervention group (n = 148) and the usual care group (n = 158). The early sleep intervention group had a significantly longer nighttime sleep duration and a shorter night waking duration than the usual care group (585.20 ± 80.38 min vs. 496.14 ± 87.78 min, p < .001 and 61.01 ± 36.38 min vs. 89.72 ± 45.54 min, p < .001). At 6 months of age, the early sleep intervention group had a longer night sleep duration (≥ 4 h/time) than the usual care group (adjusted odds ratio: 2.39, 95% confidence interval: 1.34-4.28). CONCLUSIONS: Early sleep intervention should be recommended to infants at 4 months of age as a part of well childcare to improve infant sleep quality. TRIAL REGISTRATION: Thai Clinical Trials Registry (thaiclinicaltrial.org). Retrospective registered TCTR20230117001 (17/01/2023).

Classification of Sleep Quality and Aging as a Function of Brain Complexity: A Multiband Non-Linear EEG Analysis.

Understanding and classifying brain states as a function of sleep quality and age has important implications for developing lifestyle-based interventions involving sleep hygiene. Current studies use an algorithm that captures non-linear features of brain complexity to differentiate awake electroencephalography (EEG) states, as a function of age and sleep quality. Fifty-eight participants were assessed using the Pittsburgh Sleep Quality Inventory (PSQI) and awake resting state EEG. Groups were formed based on age and sleep quality (younger adults n = 24, mean age = 24.7 years, SD = 3.43, good sleepers n = 11; older adults n = 34, mean age = 72.87; SD = 4.18, good sleepers n = 9). Ten non-linear features were extracted from multiband EEG analysis to feed several classifiers followed by a leave-one-out cross-validation. Brain state complexity accurately predicted (i) age in good sleepers, with 75% mean accuracy (across all channels) for lower frequencies (alpha, theta, and delta) and 95% accuracy at specific channels (temporal, parietal); and (ii) sleep quality in older groups with moderate accuracy (70 and 72%) across sub-bands with some regions showing greater differences. It also differentiated younger good sleepers from older poor sleepers with 85% mean accuracy across all sub-bands, and 92% at specific channels. Lower accuracy levels (<50%) were achieved in predicting sleep quality in younger adults. The algorithm discriminated older vs. younger groups excellently and could be used to explore intragroup differences in older adults to predict sleep intervention efficiency depending on their brain complexity.

Association Between Sleep Quality and Cognitive Symptoms in Patients with Major Depressive Disorder.

Cognitive symptoms and sleep disturbance (SD) are common non-mood-related symptoms of major depressive disorder (MDD). In clinical practice, both cognitive symptoms and SD are related to MDD progression. However, there are only a few studies investigating the connection between cognitive symptoms and SD in patients with MDD, and only preliminary evidence suggests a significant association between cognitive symptoms and SD in patients with mood disorders. This study investigates the relationship between cognitive symptoms and sleep quality in patients with major depressive disorder. Patients (n = 20) with MDD were enrolled; their mean Hamilton Depression Scale-17 score was 21.95 (±2.76). Gold standard polysomnography (PSG) was used to assess sleep quality, and the validated THINC-integrated tool (the cognitive screening tool) was used to evaluate cognitive function in MDD patients. Overall, the results showed significant correlations between the cognitive screening tool's total score and sleep latency, wake-after-sleep onset, and sleep efficiency. These findings indicate that cognitive symptoms are associated with poor sleep quality among patients with MDD.