Prevalence and impact of sleep disorders and sleep habits in the United States

Ram, Saravanan; Seirawan, Hazem; Kumar, Satish; Clark, Glenn T.

doi:10.1007/s11325-009-0281-3

Cited by 258 publications

(187 citation statements)

References 38 publications

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“…1,5,7,11,17,18 Despite the growing clinical and public health concerns regarding sleep disorders, few studies have examined associations between sleep and race/ethnicity in the United States. A majority of extant racial/ethnic studies compared African Americans with and without sleep disorders, or comparing African and Caucasian Americans on sleep disordered breathing, snoring, sleep architecture, insomnia symptoms, sleep quality, daytime sleepiness, comorbid conditions, and health-related quality of life.…”

Section: S C I E N T I F I C I N V E S T I G a T I O N Smentioning

confidence: 99%

“…S leep research over the past two decades has shown associations between sleep disorders and chronic disease, [1][2][3][4][5][6][7] poorer health-related quality of life, 8,9 increased health and work-related costs, and travel and work-related accidents. 10,11 Prevalence rates for insomnia, the most commonly reported sleep complaint, range from 20% to 40% of the population, depending on the defi ned severity and frequency, 12 and is suggested to have a bidirectional relationship with several chronic conditions including depression and cardiovascular disease.…”

Section: S C I E N T I F I C I N V E S T I G a T I O N Smentioning

confidence: 99%

“…15 Snoring (48%), feeling unrested (26.5%), and insuffi cient sleep (26%) are leading sleep problems identifi ed in a population-based study. 5 These and other sleep disruptions can contribute to excessive daytime sleepiness, 16 making sleep disorders signifi cant contributors to disability, morbidity, and mortality. 1,5,7,11,17,18 participation and were compensated $30 for their time.…”

Section: S C I E N T I F I C I N V E S T I G a T I O N Smentioning

confidence: 99%

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Spanish Translation and Cross-Language Validation of a Sleep Habits Questionnaire for Use in Clinical and Research Settings

Baldwin

Choi

McClain

et al. 2012

Journal of Clinical Sleep Medicine

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Study Objectives: To translate, back-translate and crosslanguage validate (English/Spanish) the Sleep Heart Health Study Sleep Habits Questionnaire for use with Spanish-speakers in clinical and research settings. Methods: Following rigorous translation and back-translation, this cross-sectional cross-language validation study recruited bilingual participants from academic, clinic, and communitybased settings (N = 50; 52% women; mean age 38.8 ± 12 years; 90% of Mexican heritage). Participants completed English and Spanish versions of the Sleep Habits Questionnaire, the Epworth Sleepiness Scale, and the Acculturation Rating Scale for Mexican Americans II one week apart in randomized order. Psychometric properties were assessed, including internal consistency, convergent validity, scale equivalence, language version intercorrelations, and exploratory factor analysis using PASW (Version18) software. Grade level readability of the sleep measure was evaluated. Results: All sleep categories (duration, snoring, apnea, insomnia symptoms, other sleep symptoms, sleep disruptors, restless legs syndrome) showed Cronbach α, SpearmanBrown coeffi cients and intercorrelations ≥ 0.700, suggesting robust internal consistency, correlation, and agreement between language versions. The Epworth correlated signifi cantly with snoring, apnea, sleep symptoms, restless legs, and sleep disruptors) on both versions, supporting convergent validity. Items loaded on 4 factors accounted for 68% and 67% of the variance on the English and Spanish versions, respectively. Conclusions S C I E N T I F I C I N V E S T I g A T I O N SS leep research over the past two decades has shown associations between sleep disorders and chronic disease, 1-7 poorer health-related quality of life, 8,9 increased health and work-related costs, and travel and work-related accidents.10,11 Prevalence rates for insomnia, the most commonly reported sleep complaint, range from 20% to 40% of the population, depending on the defi ned severity and frequency, 12 and is suggested to have a bidirectional relationship with several chronic conditions including depression and cardiovascular disease.13,14 Prevalence rates for obstructive sleep apnea syndrome range from 2% to 4%, 7 and rates for restless legs syndrome range from 5% to 15% in the general population.15 Snoring (48%), feeling unrested (26.5%), and insuffi cient sleep (26%) are leading sleep problems identifi ed in a population-based study.5 These and other sleep disruptions can contribute to excessive daytime sleepiness, 16 making sleep disorders signifi cant contributors to disability, morbidity, and mortality. 1,5,7,11,17,18 Despite the growing clinical and public health concerns regarding sleep disorders, few studies have examined associations between sleep and race/ethnicity in the United States. A majority of extant racial/ethnic studies compared African Americans with and without sleep disorders, or comparing African and Caucasian Americans on sleep disordered breathing, snoring, sleep architecture, insomnia sympt...

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Section: S C I E N T I F I C I N V E S T I G a T I O N Smentioning

confidence: 99%

Section: S C I E N T I F I C I N V E S T I G a T I O N Smentioning

confidence: 99%

Section: S C I E N T I F I C I N V E S T I G a T I O N Smentioning

confidence: 99%

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Spanish Translation and Cross-Language Validation of a Sleep Habits Questionnaire for Use in Clinical and Research Settings

Baldwin

Choi

McClain

et al. 2012

Journal of Clinical Sleep Medicine

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show abstract

“…More than 10% of the people are seriously affected by sleep disorders, such as sleep apnea and insomnia [6]. These disorders can cause daytime sleepiness, irritability, anxiety and depression [7].…”

Section: Introductionmentioning

confidence: 99%

Symbolic Fusion: A Novel Decision Support Algorithm for Sleep Staging Application

Chen¹,

Xue²,

Ugon³

et al. 2015

EAI Endorsed Trans Perv Health Tech

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With the rapid extension of clinical data and knowledge, decision making becomes a complex task for manual sleep staging. In this process, there is a need for integrating and analyzing information from heterogeneous data sources with high accuracy. This paper proposes a novel decision support algorithm-Symbolic Fusion for sleep staging application. The proposed algorithm provides high accuracy by combining data from heterogeneous sources, like EEG, EOG and EMG. This algorithm is developed for implementation in portable embedded systems for automatic sleep staging at low complexity and cost. The proposed algorithm proved to be an efficient design support method and achieved up to 76% overall agreement rate on our database of 12 patients.

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“…6,7 As a result, many sleep disorders are undiagnosed in children and in adults. [8][9][10] Underdiagnosis of sleep disorders has been historically attributed to the limited inclusion of sleep medicine in medical school curricula. A 1978 survey by the American Sleep Disorders Association showed that 46% of medical schools provided no education in sleep medicine.…”

mentioning

confidence: 99%

Assessing Learning Outcomes and Cost Effectiveness of an Online Sleep Curriculum for Medical Students

Bandla

Franco

Simpson

et al. 2012

Journal of Clinical Sleep Medicine

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objective: Sleep disorders are highly prevalent across all age groups but often remain undiagnosed and untreated, resulting in signifi cant health consequences. To overcome an inadequacy of available curricula and learner and instructor time constraints, this study sought to determine if an online sleep medicine curriculum would achieve equivalent learner outcomes when compared with traditional, classroom-based, face-to-face instruction at equivalent costs. Method: Medical students rotating on a required clinical clerkship received instruction in 4 core clinical sleep-medicine competency domains in 1 of 2 delivery formats: a single 2.5-hour face-to-face workshop or 4 asynchronous e-learning modules. Immediate learning outcomes were assessed in a subsequent clerkship using a multiple-choice examination and standardized patient station, with long-term outcomes assessed through analysis of students' patient write-ups for inclusion of sleep complaints and diagnoses before and after the intervention. Instructional costs by delivery format were tracked. Descriptive and inferential statistical analyses compared learning outcomes and costs by instructional delivery method (face-to-face versus e-learning).Results: Face-to-face learners, compared with online learners, were more satisfi ed with instruction. Learning outcomes (i.e., multiple-choice examination, standardized patient encounter, patient write-up), as measured by short-term and long-term assessments, were roughly equivalent. Design, delivery, and learner-assessment costs by format were equivalent at the end of 1 year, due to higher ongoing teaching costs associated with face-to-face learning offsetting online development and delivery costs. Conclusions: Because short-term and long-term learner performance outcomes were roughly equivalent, based on delivery method, the cost effectiveness of online learning is an economically and educationally viable instruction platform for clinical clerkships. Keywords: Learning outcomes, cost effectiveness, on-line sleep curriculum Citation: Bandla H; Franco RA; Simpson D; Brennan K; McKanry J; Bragg D. Assessing learning outcomes and cost effectiveness of an online sleep curriculum for medical students.

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Prevalence and impact of sleep disorders and sleep habits in the United States

Abstract: Our findings suggest that the prevalence of sleep disorders in the USA is much lower than previously reported in the literature suggesting under diagnosis of sleep disorders by primary care physicians.

Cited by 258 publications

References 38 publications

Spanish Translation and Cross-Language Validation of a Sleep Habits Questionnaire for Use in Clinical and Research Settings

Spanish Translation and Cross-Language Validation of a Sleep Habits Questionnaire for Use in Clinical and Research Settings

Symbolic Fusion: A Novel Decision Support Algorithm for Sleep Staging Application

Assessing Learning Outcomes and Cost Effectiveness of an Online Sleep Curriculum for Medical Students

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