Sleep quality components and mental health: Study with a non-clinical population

João, Karine Alexandra Del Rio; Jesus, Saúl Neves de; Carmo, Cláudia; Pinto, Patrícia

doi:10.1016/j.psychres.2018.08.020

Cited by 16 publications

(10 citation statements)

References 43 publications

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“…Practicing clinicians are well aware of the symbiosis between sleep and mental health. Sleep problems are associated cross-sectionally with poor mental health (Del Rio Joao et al, 2018;Krueger and Friedman, 2009). This relationship is understood to be bi-directional (Roberts and Duong, 2014); however, a systematic review of eight prospective studies reported that childhood sleep problems significantly predicted higher levels of subsequent depression and anxiety, but not vice-versa (Alvaro et al, 2013).…”

Section: Introductionmentioning

confidence: 99%

Prospective relationships of mentally passive sedentary behaviors with depression: Mediation by sleep problems

Hallgren

Vancampfort

Owen

et al. 2020

Journal of Affective Disorders

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Background: As distinct from mentally-active sedentary behaviors (e.g. reading), passive sedentary behaviors (e.g. TV-viewing) have been linked to a higher risk of depression, but the underlying mechanisms are unclear. We examined the potential mediating role of sleep problems in prospective relationships of passive sedentary behaviors with major depressive disorder (MDD). Method: In 1997, 43 863 adults were surveyed and responses linked to clinician diagnoses of MDD until 2010. The questionnaire included items on sedentary behavior and sleep problems (Karolinska Sleep Questionnaire). Cox proportional hazard models and the 'counterfactual approach' were used to identify potential mediating effects of sleep problems in the association of passive sedentary behavior and MDD. Results: Of the total sample, 3,065 (7.6%) were excluded for having indications of depression at baseline. Of 33,116 participants with complete data (mean age = 51.3 years, SD = 15.7, 64% female); 472 (1.4%) incident cases of MDD were identified during the 13-year follow-up. In Cox regression analyses, higher durations of passive sedentary behavior (≥3 h/day versus <3 h/day) were associated with greater hazards of developing MDD (HR = 1.27; 95% CI = 1.01, 1.58). This relationship remained after adjusting for confounders (HR = 1.29; 95% CI = 1.03, 1.63). Adding sleep problems into the analysis significantly attenuated these relationships (HR = 1.25; 95% CI = 0.99, 1.57). The excess MDD relative risk of passive sedentary behaviors due to sleep problems was statistically significant. Limitations: Measures of sedentary behavior, physical activity and sleep were self-reported. Conclusion: Sleep problems appear to mediate detrimental associations of passive sedentary behavior with depression. Findings require further confirmation using objective measures. 2016; Zhai et al., 2014); those with MDD have 50% higher odds of being inactive compared to those without depression (Schuch et al., 2018), and structured exercise is shown to reduce depressive symptoms in psychiatric populations (Barbour et al., 2007; Schuch et al., 2016). Physical activityeven in small 'doses'-is also protective against depression onset (

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Section: Introductionmentioning

confidence: 99%

Prospective relationships of mentally passive sedentary behaviors with depression: Mediation by sleep problems

Hallgren

Vancampfort

Owen

et al. 2020

Journal of Affective Disorders

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“…Sleep is a naturally recurring state of mind and body, in which the body alternates between rapid eye movement (REM) sleep and non-REM (NREM) sleep, and sleep quality [1]- [5] is one of the important factors affecting the human being's health. Sleep scoring is a valuable method to evaluate the quality of sleep, which is benefited from the polysomnographic (PSG) recorded by electroencephalogram (EEG), electrooculogram (EOG), electromyogram (EMG), or electrocardiogram (ECG) during sleep.…”

Section: Introductionmentioning

confidence: 99%

An Accurate Sleep Stages Classification Method Based on State Space Model

Shen

Guez

et al. 2019

IEEE Access

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The classification of sleep stages is the process which helps to evaluate the quality of sleep and detect the sleep related disorders. Through analyzing the electroencephalography, the sleep stages can be discriminated manually by specialists. However, this can be a laboriousness work because of the huge datasets. Until now, several studies have been conducted based on the automatic analysis of electroencephalography. Still, as the development of wearable technology, there is a need for an accurate and single-channel electroencephalography based sleep stages identification system. In this paper, a statespace based sleep stages classification method is proposed using the proposed model based essence features extraction method. This method employed the state-space model to establish the intrinsic models based on the single-channel electroencephalography, from which the features used for further classification can be extracted. For 2-stage to 6-stage classification of sleep states, the verification system can achieve 98.6%, 94.9%, 93.0%, 92.3%, 91.8% accuracy on the Sleep-EDF database, and also reach 94.9%, 87.7%, 82.7%, 80.9%, 78.2% on Dreams Subjects database.

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“…Good quality sleep is vital to both physical and mental health (Fernandez-Mendoza and Vgontzas, 2013 ). Sleep disturbances are associated with mental health disorders and pose a risk for depression, anxiety, and post-traumatic stress disorder (PTSD) (Alvaro et al, 2013 ; Del Rio João et al, 2018 ). Children with persistent sleep disturbances are 16 times more likely than those without sleep problems to develop psychosocial symptoms in a subclinical/clinical population (Simola et al, 2014 ).…”

Section: Introductionmentioning

confidence: 99%

Epidemiology of Sleep Disturbances and Their Effect on Psychological Distress During the COVID-19 Outbreak: A Large National Study in China

et al. 2021

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Background: The purpose of the current study was to assess the prevalence of sleep disturbances among Chinese people during the COVID-19 pandemic in a large national survey, analyze the relationship between sleep disturbances and mental health status, and explore the influencing factors of the relationship between sleep disturbances and mental health status.Methods: An online survey was accessed by 19,740 people throughout China from February 14 to 21, 2020. The survey included the Depression Anxiety Stress Scale-21 (DASS-21) to measure psychological distress and two questions about sleep disturbances. Logistic regression analyses and moderation analysis were performed.Results: (1) Among the 14,505 respondents included in analyses, 3,783 (26.08%) reported sleep disturbances at least 3 days during the past week. (2) Sleep disturbances increased the risk of depression, anxiety, and stress (p < 0.05). (3) Gender, age, education, occupation, frequency of attending to epidemic information, nervousness about supplies, receiving provisions of living necessities from the service department during the outbreak, number of correct responses to questions about the epidemic, and isolation/quarantine affected the risk of mental health problems among participants experiencing sleep disturbances (p < 0.05). (4) A moderation analysis found that sleep problems were more likely to affect depression, anxiety, and stress scores in men than women during the COVID-19 outbreak.Conclusion: During the COVID-19 outbreak, 26.08% people surveyed experienced sleep disturbances, and the presence of sleep disturbances was positively related to depression, anxiety, and stress, especially among front-line anti-epidemic workers, younger people, people living in isolation/quarantine, people with a college or greater education, and males.

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Sleep quality components and mental health: Study with a non-clinical population

Cited by 16 publications

References 43 publications

Prospective relationships of mentally passive sedentary behaviors with depression: Mediation by sleep problems

Prospective relationships of mentally passive sedentary behaviors with depression: Mediation by sleep problems

An Accurate Sleep Stages Classification Method Based on State Space Model

Epidemiology of Sleep Disturbances and Their Effect on Psychological Distress During the COVID-19 Outbreak: A Large National Study in China

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