The future of sleep health: a data-driven revolution in sleep science and medicine

Perez-Pozuelo, Ignacio; Zhai, Bing; Palotti, João; Mall, Raghvendra; Aupetit, Michaël; García‐Gómez, Juan Miguel; Taheri, Shahrad; Guan, Yu; Fernández-Luque, Luis

doi:10.1038/s41746-020-0244-4

Cited by 173 publications

(115 citation statements)

References 190 publications

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“…Technological advances in wrist-worn sensors provide the opportunity to objectively measure sleep through passive recording, in real time, with minimal expense or user burden 22 , 23 . Therefore, wrist-worn, multisensory consumer sleep tracking devices can now provide estimates of sleep patterns over extensive time durations in individuals under demanding circumstances such as medical training.…”

Section: Introductionmentioning

confidence: 99%

“…Therefore, wrist-worn, multisensory consumer sleep tracking devices can now provide estimates of sleep patterns over extensive time durations in individuals under demanding circumstances such as medical training. Additionally, mobile platforms allow for real-time input of self-report symptoms 22 . Therefore, use of current technology provides the opportunity to more comprehensively characterize sleep, while simultaneously assessing mood, to identify the specific sleep disturbances that contribute to depression.…”

Section: Introductionmentioning

confidence: 99%

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Day-to-day variability in sleep parameters and depression risk: a prospective cohort study of training physicians

et al. 2021

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While 24-h total sleep time (TST) is established as a critical driver of major depression, the relationships between sleep timing and regularity and mental health remain poorly characterized because most studies have relied on either self-report assessments or traditional objective sleep measurements restricted to cross-sectional time frames and small cohorts. To address this gap, we assessed sleep with a wearable device, daily mood with a smartphone application and depression through the 9-item Patient Health Questionnaire (PHQ-9) over the demanding first year of physician training (internship). In 2115 interns, reduced TST (b = −0.11, p < 0.001), later bedtime (b = 0.068, p = 0.015), along with increased variability in TST (b = 0.4, p = 0.0012) and in wake time (b = 0.081, p = 0.005) were associated with more depressive symptoms. Overall, the aggregated impact of sleep variability parameters and of mean sleep parameters on PHQ-9 were similar in magnitude (both r2 = 0.01). Within individuals, increased TST (b = 0.06, p < 0.001), later wake time (b = 0.09, p < 0.001), earlier bedtime (b = − 0.07, p < 0.001), as well as lower day-to-day shifts in TST (b = −0.011, p < 0.001) and in wake time (b = −0.004, p < 0.001) were associated with improved next-day mood. Variability in sleep parameters substantially impacted mood and depression, similar in magnitude to the mean levels of sleep parameters. Interventions that target sleep consistency, along with sleep duration, hold promise to improve mental health.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Day-to-day variability in sleep parameters and depression risk: a prospective cohort study of training physicians

et al. 2021

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“…In 2017, the combined cost of insufficient sleep across Canada, United States, United Kingdom, Germany and Japan was estimated to exceed $600 billion a year 6 . However, despite the global problem of sleep insufficiency and its serious public health implications, it is often inadequately recognised by individuals and health professionals alike 7 , 8 . This has motivated organizations such as the Centers for Disease Control and Prevention to advocate for increased surveillance of sleep problems, and heightened awareness of the health promoting effects of sleep 9 .…”

Section: Introductionmentioning

confidence: 99%

Loneliness and social isolation is associated with sleep problems among older community dwelling women and men with complex needs

McLay

Jamieson

Schlüter

2021

Sci Rep

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Sleep problems, loneliness and social isolation often increase with age, significantly impacting older adults’ health and wellbeing. Yet general population health empirical evidence is surprisingly scant. Using the largest national database to date, cross-sectional and longitudinal analyses was undertaken on 140,423 assessments from 95,045 (women: 61.0%) community living older adults aged ≥ 65 years having standardised home care assessments between 1 July 2012 and 31 May 2018 to establish the prevalence and relationships between insufficient sleep, excessive sleep, loneliness and social isolation. At first assessment, insufficient sleep (women: 12.4%, men: 12.7%) was more commonly reported than excessive sleep (women: 4.7%, men: 7.6%). Overall, 23.6% of women and 18.9% of men reported feeling lonely, while 53.8% women and 33.8% men were living alone. In adjusted longitudinal analyses, those who were lonely and socially isolated were more likely to experience insufficient sleep. Respondents with excessive sleep were more likely to live with others. Both loneliness and social isolation contributed to insufficient sleep, synergistically. Loneliness, social isolation and health-concerns may affect the restorative properties of sleep over and above the effects of ageing. Further research is warranted.

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“…The assessment of sleep duration and quality can be achieved through self-monitoring of sleep and its disorders as well as specific clinical assessments conducted at home or within the sleep laboratory [29]. These can be linked to a range of specific measures to address issues with sleep duration and quality.…”

Section: Introductionmentioning

confidence: 99%

Systematic review of clinical practice guidelines to identify recommendations for sleep in type 2 diabetes mellitus management

Smyth

Jenkins

Dunham

et al. 2020

Diabetes Research and Clinical Practice

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Introduction: Sleep quality, quantity and timing have been shown to impact glycaemic control, with a role in insulin sensitivity, glucose tolerance and HbA1C levels, in both diabetic and non-diabetic populations. The aim of this study was to identify recommendations for sleep assessment and management in international clinical practice guidelines focused on type 2 diabetes mellitus management in adults. Study design: Systematic Review. Methodology: Clinical practice guidelines which focused on the management of type 2 diabetes mellitus in adults were included (n = 35). Two independent reviewers utilised the Appraisal of Guidelines for Research and Evaluation tool (AGREE) II and a third reviewer resolved any disagreements. Included guidelines were assessed for recommendations about sleep in diabetes management (n = 14). Data were extracted on sleep recommendations ,themes were generated from the extracted data and narrative syntheses were created. Results: From 1114 identified papers, 35 guidelines met the inclusion criteria. Fourteen of these guidelines included recommendations pertaining to sleep, which broadly fell into five categories; sleep assessment, sleep as a therapeutic target, sleep and co-morbidities of type 2 diabetes mellitus, shift work and sleep and driving. Recommendations varied across guidelines. Conclusion: Few guidelines provided recommendations relating to assessment and management of sleep in type 2 diabetes care. Most of the recommendations were related to obstructive sleep apnoea. However, few guidelines discussed sleep as a therapeutic intervention for diabetes mellitus or described the potential importance of sleep quality and duration in glycaemic control.

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The future of sleep health: a data-driven revolution in sleep science and medicine

Cited by 173 publications

References 190 publications

Day-to-day variability in sleep parameters and depression risk: a prospective cohort study of training physicians

Day-to-day variability in sleep parameters and depression risk: a prospective cohort study of training physicians

Loneliness and social isolation is associated with sleep problems among older community dwelling women and men with complex needs

Systematic review of clinical practice guidelines to identify recommendations for sleep in type 2 diabetes mellitus management

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