Epidemiology of sleep disorders

Partinen, Markku

doi:10.1016/b978-0-444-52006-7.00018-6

Cited by 67 publications

(17 citation statements)

References 343 publications

(309 reference statements)

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“…The two most common sleep disorders are OSA and insomnia, which each affect approximately 15% of the population (122; 124). OSA is the occurrence of repetitive periods of obstructed breathing during sleep (apneas and hypopneas), associated with drops in oxygen levels, arousals, and mechanical stresses on the heart and lungs.…”

Section: The Public Health Importance Of Sleepmentioning

confidence: 99%

Sleep as a Potential Fundamental Contributor to Disparities in Cardiovascular Health

Jackson

Redline

Emmons

2015

Annu. Rev. Public Health

298

200

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Optimal sleep is integral to health but is commonly not obtained. Despite its wide ranging public health impact, sleep health is under-appreciated by the general public and is only rarely considered by policy makers, employers, schools, and others whose policies and structures can adversely affect sleep. Inadequate sleep duration and quality are prevalent in minority and low-income populations and may play a fundamental role in racial and socioeconomic status (SES) inequities for a wide range of health conditions including cardiovascular disease (CVD).The goal of this review is to examine the relationship between sleep and CVD health disparities. To this end, we describe the overall public health importance of sleep and the role of sleep duration as well as the two most common disorders (sleep apnea and insomnia) as risk factors for a number of chronic diseases. We then focus on the potential link between sleep and CVD disparities. A multilevel model developed for the analysis of population health and health disparities as a part of the National Cancer Institute’s Centers on Population Health and Health Disparities served as our conceptual framework. It is based on the notion that individual behaviors, like sleep, are influenced by complex and dynamic interrelations among the individual and his or her physical and social environments across the lifespan. Using this model, we describe modifiable factors that contribute to insufficient sleep and circadian misalignment, propose potential interventions in various sectors (e.g. neighborhoods, schools, workplaces) that address social structures that contribute to disparities, and conclude by recommending critical areas for future sleep research. We ultimately suggest that integrating sleep into public health research will identify novel approaches for closing the gap in health disparities, such as CVD.

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Section: The Public Health Importance Of Sleepmentioning

confidence: 99%

Sleep as a Potential Fundamental Contributor to Disparities in Cardiovascular Health

Jackson

Redline

Emmons

2015

Annu. Rev. Public Health

298

200

View full text Add to dashboard Cite

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“…Insomnia is a very common health problem that affects 30 to 35% of adults on an episodic basis and 10 to 12% on a chronic basis (AAoS Medicine 1 )( 2 ). One third or more of the population suffers from a sleep disturbance or excessive daytime sleepiness on a daily basis ( 3 ). Insomnia is associated with an increased risk of Alzheimer's disease ( 4 ), Parkinson's disease ( 5 ), hypertension ( 6 ), cardiovascular diseases ( 7 ), depression ( 8 ), obesity ( 9 ), type 2 diabetes ( 10 ), and mortality ( 11 ).…”

Section: Introductionmentioning

confidence: 99%

Abnormal Global Brain Functional Connectivity in Primary Insomnia Patients: A Resting-State Functional MRI Study

et al. 2018

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Background: Resting-state functional magnetic resonance imaging (fMRI) studies have uncovered the disruptions of functional brain networks in primary insomnia (PI) patients. However, the etiology and pathogenesis underlying this disorder remains ambiguous, and the insomnia related symptoms are influenced by a complex network organization in the brain. The purpose of this study was to explore the abnormal intrinsic functional hubs in PI patients using a voxel-wise degree centrality (DC) analysis and seed-based functional connectivity (FC) approach.Methods: A total of 26 PI patients and 28 healthy controls were enrolled, and they underwent resting-state fMRI. Degree centrality was measured across the whole brain, and group differences in DC were compared. The peak points, which significantly altered DC between the two groups, were defined as the seed regions and were further used to calculate FC of the whole brain. Later, correlation analyses were performed between the changes in brain function and clinical features.Results: Primary insomnia patients showed DC values lower than healthy controls in the left inferior frontal gyrus (IFG) and middle temporal gyrus (MTG) and showed a higher DC value in the right precuneus. The seed-based analyses demonstrated decreased FC between the left MTG and the left posterior cingulate cortex (PCC), and decreased FC was observed between the right precuneus and the right lateral occipital cortex. Reduced DC in the left IFG and decreased FC in the left PCC were positively correlated with the Pittsburgh sleep quality index and the insomnia severity index.Conclusions: This study revealed that PI patients exhibited abnormal intrinsic functional hubs in the left IFG, MTG, and the right precuneus, as well as abnormal seed-based FC in these hubs. These results contribute to better understanding of how brain function influences the symptoms of PI.

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“…Compared to wake, tidal volume and minute ventilation is lower in NREM, sleep [26]. REM sleep state has the most irregular breathing whereas NREM has a more 'stable' breathing pattern to maintain minute ventilation [26,44]. The 'stable' breathing in NREM sleep can give some understanding of patterns of individuals [30], so it is hypothesized that there may be groups ( breathing precludes some respiratory events, and it is more common to see respiratory events in REM stage of sleep.…”

Section: Respiration In Sleepmentioning

confidence: 99%

Analysis of airflow indices in paediatric respiratory disorders

Parsley¹

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AimDuchenne Muscular Dystrophy (DMD) and Prader-Willi syndrome (PWS) are complex congenital disorders in which sleep disordered breathing (SDB) typically develop, and this impacts normal growth and neurological development. Due to the slow progression of SDB pathology and the lack of correlation between SDB pathology and daytime clinical symptoms, these patients are often only actively treated after SDB is fully established. This study aims: (1) to determine whether there are changes in breath timing and breath shape (morphology) during sleep in these paediatric respiratory disorders when compared with healthy children; and (2) whether there is an association between physiological markers of disorder progression with these indices of breath timing and shape. MethodsA retrospective cohort of 13 patients with DMD and 11 patients with PWS whom had at least three sequential overnight polysomnograms and 27 healthy controls (2-17 years) were identified from a clinical database. The nasal pressure signal in at least two tenminute segments of stage 2 non-rapid eye movement (NREM) sleep for each patient was extracted from each retrospective polysomnogram. Each breath was automatically segmented into inspiratory and expiratory phase using a customised algorithm, and these were used quantified using three categories of indices: (1) Timing indices including total breath time (Ttot) and fractional inspiratory time (FIT) (mean and standard deviation, SD);(2) Linear shape descriptors (skewness, kurtosis and variance); and (3) Non-linear shape descriptors (line morphology, length -'flatness'and variability). In addition, standard physiological markers of disease progression were extracted from the polysomnogram report: total apnoea-hypopnoea index (AHI), body-mass index (BMI), mean SpO2 and mean CO2. Indices of breath timing and shape were compared between the disorder cohorts and healthy controls; and the changes in indices over years for cohorts were compared to standardphysiological measures to determine if there was any association with disorder progression.

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Epidemiology of sleep disorders

Cited by 67 publications

References 343 publications

Sleep as a Potential Fundamental Contributor to Disparities in Cardiovascular Health

Sleep as a Potential Fundamental Contributor to Disparities in Cardiovascular Health

Abnormal Global Brain Functional Connectivity in Primary Insomnia Patients: A Resting-State Functional MRI Study

Analysis of airflow indices in paediatric respiratory disorders

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