Sleep disorders and non-sleep circadian disorders predict depression: A systematic review and meta-analysis of longitudinal studies

Zhang, Mi-Mi; Ma, Yan; Du, Lan-Ting; Wang, Ke; Li, Zhe; Zhu, Weili; Sun, Yuhui; Lü, Lin; Bao, Yanping; Li, Su-Xia

doi:10.1016/j.neubiorev.2022.104532

Cited by 51 publications

(24 citation statements)

References 89 publications

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“…Sleep onset had the highest BEI among insomnia symptoms, suggesting it shares a close relationship with anxiety and depression symptoms. Our results support several longitudinal studies which found that sleep onset insomnia was a stronger predictor of depression than other insomnia subtypes ( 53 , 54 ). Moreover, the residua of sleep onset insomnia were found to predict major depressive disorder relapse ( 55 ).…”

Section: Discussionsupporting

confidence: 91%

Night shifts, insomnia, anxiety, and depression among Chinese nurses during the COVID-19 pandemic remission period: A network approach

Peng

Liang

Wang

et al. 2022

Front. Public Health

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BackgroundThe outbreak of the COVID-19 pandemic imposed a heavy workload on nurses with more frequent night shifts, which led to higher levels of insomnia, depression, and anxiety among nurses. The study aimed to describe the symptom-symptom interaction of depression, anxiety, and insomnia among nurses and to evaluate the impact of night shifts on mental distress via a network model.MethodsWe recruited 4,188 nurses from six hospitals in December 2020. We used the Insomnia Severity Index, Patient Health Questionnaire-9, and Generalized Anxiety Disorder Scale-7 to assess insomnia, depression, and anxiety, respectively. We used the gaussian graphical model to estimate the network. Index expected influence and bridge expected influence was adapted to identify the central and bridge symptoms within the network. We assessed the impact of night shifts on mental distress and compared the network structure based on COVID-19 frontline experience.ResultsThe prevalence of depression, anxiety, and insomnia was 59, 46, and 55%, respectively. Nurses with night shifts were at a higher risk for the three mental disorders. “Sleep maintenance” was the central symptom. “Fatigue,” “Motor,” “Restlessness,” and “Feeling afraid” were bridge symptoms. Night shifts were strongly associated with sleep onset trouble. COVID-19 frontline experience did not affect the network structure.Conclusion“Sleep maintenance,” “Fatigue,” “Motor,” and “Restlessness” were important in maintaining the symptom network of anxiety, depression, and insomnia in nurses. Further interventions should prioritize these symptoms.

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Section: Discussionsupporting

confidence: 91%

Night shifts, insomnia, anxiety, and depression among Chinese nurses during the COVID-19 pandemic remission period: A network approach

Peng

Liang

Wang

et al. 2022

Front. Public Health

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“…Sleep is a complicated set of brain processes that plays a pivotal role in maintaining mental and physical health. 1 Insufficient sleep can lead to multiple adverse medical consequences, including cardiovascular diseases (CVDs), 2 , 3 metabolic disorders, 4 psychiatric disorders, 5 and impaired cognition. 6 , 7 Sleep duration is an important indicator of nighttime sleep, which can be objectively measured using polysomnography and wrist actigraphy or collected from self‐reported sleep questionnaires.…”

mentioning

confidence: 99%

Association of Objective and Self‐Reported Sleep Duration With All‐Cause and Cardiovascular Disease Mortality: A Community‐Based Study

Zhao

Meng

Jin

et al. 2023

JAHA

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Background Previous studies found an association between self‐reported sleep duration and mortality. This study aimed to compare the effects of objective and self‐reported sleep duration on all‐cause and cardiovascular disease (CVD) mortality. Methods and Results A total of 2341 men and 2686 women (aged 63.9±11.1 years) were selected from the SHHS (Sleep Heart Health Study). Objective sleep duration was acquired using in‐home polysomnography records, and self‐reported sleep duration on weekdays and weekends was based on a sleep habits questionnaire. The sleep duration was categorized as ≤4 hours, 4 to 5 hours, 5 to 6 hours, 6 to 7 hours, 7 to 8 hours, and >8 hours. Multivariable Cox regression analysis was used to investigate the association of objective and self‐reported sleep duration with all‐cause and CVD mortality. During a mean follow‐up period of 11 years, 1172 (23.3%) participants died, including 359 (7.1%) deaths from CVD. All‐cause and CVD mortality rates decreased gradually with increasing objective sleep duration. In multivariable Cox regression analysis, the greatest association for all‐cause and CVD mortality was with an objective sleep duration of 5 hours or shorter. In addition, we found a J‐shaped association of self‐reported sleep duration on both weekdays and weekends with all‐cause and CVD mortality. Self‐reported short (≤4 hours) and long (>8 hours) sleep duration on weekdays and weekends were associated with an increased risk of all‐cause and CVD mortality compared with 7 to 8 hours sleep duration. Furthermore, a weak correlation was observed between objective and self‐reported sleep duration. Conclusions This study showed that both objective and self‐reported sleep duration were associated with all‐cause and CVD mortality, but with different characteristics. Registration URL: https://clinicaltrials.gov/ct2/show/NCT00005275 ; Unique identifier: NCT00005275.

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“…the serotonergic and mesolimbic dopamine systems). Another potential pathway is through a lack of adequate sleep, demonstrated to commonly precede depression (Alvaro et al , 2013; Zhang et al , 2022). Sleep may be disturbed due to an inhibition of melatonin production caused by viewing screens close to sleeping hours (Cain and Gradisar, 2010) as well as auditory and visual disturbances of notifications, with the majority of young adults sleeping within close proximity of their smartphones (Lemola et al , 2015).…”

Section: Introductionmentioning

confidence: 99%

Are smartphone use and nature contact predictive of depression in a UK university population?

Dewar,

Catling

2024

JMHTEP

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Purpose The number of university students exhibiting mental health concerns have surged considerably in the past decade. Amongst a number of potential contributing factors, this study aims to assess the role of a broader societal phenomenon; the shift in emphasis in our interactions from the physical to the virtual environments. Specifically, a decrease in nature contact and a contrasting increase in smartphone use are identified as two pathways in which this shift may impact negatively on mental health. Previous research evidences both facets as consistent correlates of depression, although limited research extends these associations to the student population or attempts to establish an interaction between the two. Design/methodology/approach The current study recruited a sample of 380 first-year undergraduate students, via an online survey, to assess if problematic smartphone use (SAS-SV) and nature contact (NCQ) were significant predictors of depression (PHQ-9). Findings Nature contact frequency and smartphone use were significant predictors of depression. Originality/value This is the first study to concurrently assess the impact of smartphone use and nature contact in a student population.

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Sleep disorders and non-sleep circadian disorders predict depression: A systematic review and meta-analysis of longitudinal studies

Cited by 51 publications

References 89 publications

Night shifts, insomnia, anxiety, and depression among Chinese nurses during the COVID-19 pandemic remission period: A network approach

Night shifts, insomnia, anxiety, and depression among Chinese nurses during the COVID-19 pandemic remission period: A network approach

Association of Objective and Self‐Reported Sleep Duration With All‐Cause and Cardiovascular Disease Mortality: A Community‐Based Study

Are smartphone use and nature contact predictive of depression in a UK university population?

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