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Internal circadian phase assessment is increasingly acknowledged as a critical clinical tool for the diagnosis, monitoring, and treatment of circadian rhythm sleep-wake disorders and for investigating circadian timing in other medical disorders. The widespread use of in-laboratory circadian phase assessments in routine practice has been limited, most likely because circadian phase assessment is not required by formal diagnostic nosologies, and is not generally covered by insurance. At-home assessment of salivary dim light melatonin onset (DLMO, a validated circadian phase marker) is an increasingly accepted approach to assess circadian phase. This approach may help meet the increased demand for assessments and has the advantages of lower cost and greater patient convenience. We reviewed the literature describing at-home salivary DLMO assessment methods and identified factors deemed to be important to successful implementation. Here, we provide specific protocol recommendations for conducting at-home salivary DLMO assessments to facilitate a standardized approach for clinical and research purposes. Key factors include control of lighting, sampling rate, and timing, and measures of patient compliance. We include findings from implementation of an optimization algorithm to determine the most efficient number and timing of samples in patients with Delayed Sleep-Wake Phase Disorder. We also provide recommendations for assay methods and interpretation. Providing definitive criteria for each factor, along with detailed instructions for protocol implementation, will enable more widespread adoption of at-home circadian phase assessments as a standardized clinical diagnostic, monitoring, and treatment tool.
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Ritmo Circadiano , Melatonina , Saliva , Humanos , Melatonina/análise , Melatonina/metabolismo , Saliva/metabolismo , Saliva/química , Ritmo Circadiano/fisiologiaRESUMO
Sleep difficulties and misuse of drugs/alcohol have been associated with suicidal ideation in young people. Using cross-sectional representative surveys of adolescents in the United States, we conducted adjusted logistic regression modeling to assess the relationships between sleep difficulties, substance use, and suicidal ideation among adolescents with a history of depression (n = 38,418) between 2015 and 2020. Sleep difficulties were associated with thinking about (aOR=1.6,95%CI:1.3-1.9), planning (aOR=1.8,95%CI:1.2-2.6), or attempting (aOR=1.7,95%CI:1.2-2.5) suicide. In those reporting alcohol abuse/dependence, sleep difficulties were associated with attempting suicide (aOR=3.1,95%CI:1.2-8.5). In those reporting illicit drug abuse/dependence, sleep difficulties were associated with thinking about (aOR=2.1,95%CI:1.1-4.1) and attempting (aOR=2.2,95%CI:1.2-4.1) suicide.
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Study Objectives: Insomnia, poor sleep quality and extremes of sleep duration are associated with COVID-19 infection. This study assessed whether these factors are related to Post-Acute Sequelae of SARS-CoV-2 infection (PASC). Methods: Cross-sectional survey of a general population of 24,803 U.S. adults to determine the association of insomnia, poor sleep quality and sleep duration with PASC. Results: Prevalence rates of PASC among previously COVID-19 infected participants for three definitions of PASC were COPE (21.9%), NICE (38.9%) and RECOVER PASC Score (15.3%). PASC was associated with insomnia in all 3 models in fully adjusted models with adjusted odds ratios (aORs) and 95% confidence intervals (CI) ranging from 1.30 (95% CI: 1.11-1.52, p≤0.05, PASC Score) to 1.52 (95% CI: 1.34-1.71, p≤0.001, (NICE). Poor sleep quality was related to PASC in all models with aORs ranging from 1.77 (95% CI: 1.60-1.97, p≤0.001, NICE) to 2.00 (95% CI: 1.77-2.26, p≤0.001, COPE). Sleep <6 hours was associated with PASC with aORs between 1.59 (95% CI: 1.40-1.80, p≤0.001, PASC Score) to 1.70 (95% CI: 1.53-1.89, p≤0.001, COPE). Sleep ≥ 9 hours was not associated with PASC in any model. Although vaccination with COVID-19 booster decreased the likelihood of developing PASC, it did not attenuate associations between insomnia, poor sleep quality and short sleep duration with PASC in any of the models. Conclusions: Insomnia, poor sleep quality and short sleep duration are potential risk factors for PASC. Interventions to improve sleep may decrease the development of PASC.
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OBJECTIVES: To develop and implement a pilot online data collection tool to help local health departments with their COVID-19 pandemic response efforts and inform health department actions. DESIGN: The COVID-19 Outbreak Public Evaluation (COPE) was an online survey and was distributed by participating sites to individuals who recently tested positive for SARS-CoV-2. Surveys recorded participant demographics and assessed recent infection risk behaviors (eg, mask use, air travel), vaccination status, sleep and exercise habits, social behaviors and beliefs, and physical and mental health. SETTING: Seven health departments participated in the initiative, which took place during May 1 to September 30, 2022. Identical items were administered to demographically representative samples of adults nationally in the United States within a similar timeframe. PARTICIPANTS: A total of 38 555 participants completed surveys. Responses from participants with recent SARS-CoV-2 infections were compared with respondents from the national surveys who did not have evidence or awareness of prior SARS-CoV-2 infections. MAIN OUTCOME MEASURE: To implement of a process that allows health departments to receive data from local cases and compare this information to national controls during the COVID-19 pandemic. RESULTS: Fifty-four biweekly reports were provided to public health departments between May and September 2022. Information and comparisons within the reports were updated in response to evolving public health priorities for the pandemic response. The initiative helped to guide public health response efforts during the COVID-19 pandemic. Moreover, the receptiveness by local health departments and participants provides evidence to support this data collection and reporting model as a component of the public health response to future emergencies. CONCLUSION: This project demonstrates the feasibility of a centralized, rapid, and adaptive data collection system for local health departments and provides evidence to advocate for data collection methods to help guide local health departments to respond in a timely and effective manner to future public health emergencies.
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COVID-19 , Coleta de Dados , Pandemias , SARS-CoV-2 , Humanos , COVID-19/epidemiologia , COVID-19/prevenção & controle , Inquéritos e Questionários , Estados Unidos/epidemiologia , Coleta de Dados/métodos , Pandemias/prevenção & controle , Governo Local , Masculino , Adulto , Feminino , Saúde Pública/métodos , Pessoa de Meia-Idade , Surtos de Doenças/prevenção & controle , InternetRESUMO
Previous research has revealed that daily variations in human neurobehavioral functions are driven in part by the endogenous circadian system. The objective of this study was to explore whether there exists a circadian influence on performance regarding a risky decision-making task and to determine whether the performance changes with sleep deprivation (SD). Thirteen participants underwent a 39 h constant routine (CR) protocol, during which they remained awake in constant conditions and performed the BART (balloon analogue risk task) every two hours. The mean pumps (gains) (p < 0.001) and balloons popped (losses) (p = 0.003) exhibited variation during the CR. The reaction time (RT) also showed significant variation across the CR (p < 0.001), with slower mean RTs in the morning hours following SD. A greater risk propensity was observed around midday before SD and a lower risk propensity after 29.5 h of being awake. The sensitivity to punishment varied during the CR, but did not follow a predictable trend. Further research using real monetary incentives and neurophysiological measures is warranted to elucidate these findings.
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Study Objectives: We previously reported that during a 45-day simulated space mission, a dynamic lighting schedule (DLS) improved circadian phase alignment and performance assessed once on selected days. This study aimed to evaluate how DLS affected performance on a 5-minute psychomotor vigilance task (PVT) administered multiple times per day on selected days. Methods: Sixteen crewmembers (37.4â ±â 6.7 years; 5F) underwent six cycles of 2â ×â 8-hour/night followed by 5â ×â 5-hour/night sleep opportunities. During the DLS (nâ =â 8), daytime white light exposure was blue-enriched (~6000 K; Level 1: 1079, Level 2: 76 melanopic equivalent daytime illuminance (melEDI) lux) and blue-depleted (~3000-4000 K; L1: 21, L2: 2 melEDI lux) 3 hours before bed. In the standard lighting schedule (SLS; nâ =â 8), lighting remained constant (~4500K; L1: 284, L2 62 melEDI lux). Effects of lighting condition (DLS/SLS), sleep condition (5/8 hours), time into mission, and their interactions, and time awake on PVT performance were analyzed using generalized linear mixed models. Results: The DLS was associated with fewer attentional lapses (reaction time [RT]â >â 500 milliseconds) compared to SLS. Lapses, mean RT, and 10% fastest/slowest RTs were worse following 5 compared to 8 hours of sleep but not between lighting conditions. There was an effect of time into mission on RTs, likely due to sleep loss. Overall performance differed by time of day, with longer RTs at the beginning and end of the day. There were more lapses and slower RTs in the afternoon in the SLS compared to the DLS condition. Conclusions: Future missions should incorporate DLS to enhance circadian alignment and performance. This paper is part of the Sleep and Circadian Rhythms: Management of Fatigue in Occupational Settings Collection.
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OBJECTIVE: This study assesses whether chronotype is related to COVID-19 infection and whether there is an interaction with shift work. Methods: This study used a cross-sectional survey of 19,821 U.S. adults. Results: COVID-19 infection occurred in 40% of participants, 32.6% morning and 17.2% evening chronotypes. After adjusting for demographic and socioeconomic factors, shift/remote work, sleep duration, and comorbidities, morning chronotype was associated with a higher (adjusted odds ratio [aOR]: 1.15, 95% CI: 1.10-1.21) and evening chronotype with a lower (aOR: 0.82, 95% CI: 0.78-0.87) prevalence of COVID-19 infection in comparison to an intermediate chronotype. Working exclusively night shifts was not associated with higher prevalence of COVID-19. Morning chronotype and working some evening shifts was associated with the highest prevalence of previous COVID-19 infection (aOR: 1.87, 95% CI: 1.28-2.74). Conclusion: Morning chronotype and working a mixture of shifts increase risk of COVID-19 infection.
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COVID-19 , Ritmo Circadiano , SARS-CoV-2 , Jornada de Trabalho em Turnos , Humanos , COVID-19/epidemiologia , Masculino , Feminino , Adulto , Estudos Transversais , Pessoa de Meia-Idade , Jornada de Trabalho em Turnos/estatística & dados numéricos , Estados Unidos/epidemiologia , Prevalência , Fatores de Risco , Adulto Jovem , Tolerância ao Trabalho Programado/fisiologia , Sono , Idoso , Inquéritos e Questionários , CronotipoRESUMO
BACKGROUND: Obstructive sleep apnea is associated with COVID-19 infection. Less clear is whether obstructive sleep apnea is a risk factor for the development of post-acute sequelae of SARS-CoV-2 infection (PASC). STUDY DESIGN: Cross-sectional survey of a general population of 24,803 US adults to determine the association of obstructive sleep apnea with PASC. RESULTS: COVID-19 infection occurred in 10,324 (41.6%) participants. Prevalence of persistent (>3 months post infection) putative PASC-related physical and mental health symptoms ranged from 6.5% (peripheral edema) to 19.6% (nervous/anxious). In logistic regression models, obstructive sleep apnea was associated with all putative PASC-related symptoms with the highest adjusted odds ratios being fever (2.053) and nervous/anxious (1.939). In 4 logistic regression models of overall PASC derived from elastic net regression, obstructive sleep apnea was associated with PASC (range of adjusted odds ratios: 1.934-2.071); this association was mitigated in those with treated obstructive sleep apnea. In the best fitting overall model requiring ≥3 symptoms, PASC prevalence was 21.9%. CONCLUSION: In a general population sample, obstructive sleep apnea is associated with the development of PASC-related symptoms and a global definition of PASC. Treated obstructive sleep apnea mitigates the latter risk. The presence of 3 or more PASC symptoms may be useful in identifying cases and for future research.
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COVID-19 , Síndrome de COVID-19 Pós-Aguda , Apneia Obstrutiva do Sono , Humanos , Apneia Obstrutiva do Sono/epidemiologia , Apneia Obstrutiva do Sono/complicações , COVID-19/complicações , COVID-19/epidemiologia , Masculino , Feminino , Pessoa de Meia-Idade , Estudos Transversais , Adulto , Idoso , Fatores de Risco , Estados Unidos/epidemiologia , SARS-CoV-2 , PrevalênciaRESUMO
Background: Obstructive sleep apnea (OSA) is associated with COVID-19 infection. Fewer investigations have assessed OSA as a possible risk for the development of Post-Acute Sequelae of SARS-CoV-2 infection (PASC). Research Question: In a general population, is OSA associated with increased odds of PASC-related symptoms and with an overall definition of PASC? Study Design: Cross-sectional survey of a general population of 24,803 U.S. adults. Results: COVID-19 infection occurred in 10,324 (41.6%) participants. Prevalence rates for a wide variety of persistent (> 3 months post infection) putative PASC-related physical and mental health symptoms ranged from 6.5% (peripheral edema) to 19.6% (nervous/anxious). In logistic regression models adjusted for demographic, anthropometric, comorbid medical and socioeconomic factors, OSA was associated with all putative PASC-related symptoms with the highest adjusted odds ratios (aOR) being fever (2.053) and nervous/anxious (1.939) respectively. Elastic net regression identified the 13 of 37 symptoms most strongly associated with COVID-19 infection. Four definitions of PASC were developed using these symptoms either weighted equally or proportionally by their regression coefficients. In all 4 logistic regression models using these definitions, OSA was associated with PASC (range of aORs: 1.934-2.071); this association was mitigated in those with treated OSA. In the best fitting overall model requiring ≥3 symptoms, PASC prevalence was 21.9%. Conclusion: In a general population sample, OSA is associated with the development of PASC-related symptoms and a global definition of PASC. A PASC definition requiring the presence of 3 or more symptoms may be useful in identifying cases and for future research.