Association of Subjective Quality and Quantity of Sleep with Quality of Life among a General Population

Matsui, Kentaro; Yoshiike, Takashi; Nagao, Kentaro; Utsumi, Tomohiro; Tsuru, Ayumi; Otsuki, Rei; Ayabe, Naoko; Hazumi, Megumi; Suzuki, Masahiro; Saitoh, Kaori; Aritake-Okada, Sayaka; Inoue, Yuichi; Kuriyama, Kenichi

doi:10.3390/ijerph182312835

Cited by 49 publications

(43 citation statements)

References 48 publications

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“…Nevertheless, our finding of a link between mental health and OSA is in line with the study of Matsui et al (2021). Using results of the self‐administered Short‐Form 8 (SF‐8) and Pittsburgh Sleep Quality Index (PSQI), they detected a relation between decreased mental life quality and subjective shorter sleep duration and impaired sleep quality (Matsui et al, 2021). It should be noted that differences in age, sex, BMI, presence of comorbidities, as well as the patient's environment or the setting might influence the questionnaire results.…”

Section: Discussionsupporting

confidence: 94%

“…A connection between AHI and the PCS is not verifiable. Studies by Matsui et al (2021) and Asghari et al (2013) indicate otherwise.…”

Section: Discussionmentioning

confidence: 94%

“…Secondly, diverse questionnaires were used to assess QOL: Asghari et al (2013) used the internationally approved and comprehensive WHOQOL‐BREF, Matsui et al (2021) used the brief SF‐8, while we evaluated QOL through SF‐12. The 26‐item WHOQOL‐BREF encompasses more domains than the shorter questionnaires SF‐8 or SF‐12.…”

Section: Discussionmentioning

confidence: 99%

“…Furthermore, collection of sleep data was different between the studies: as in SHIP, Asghari et al (2013) used PSG as the gold‐standard for nocturnal monitoring, whereas participants of Matsui et al (2021) were asked the self‐rating PSQI questionnaire. The 19‐item PSQI subjectively assesses quality and disturbances of sleep within different scores (e.g.…”

Section: Discussionmentioning

confidence: 99%

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Quality of life in patients with obstructive sleep apnea: Results from the study of health in Pomerania

Vogler

Daboul

Obst

et al. 2022

Journal of Sleep Research

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Obstructive sleep apnea is known to be an overall public health problem that, among other things, increases morbidity and mortality. Risk factors as well as symptoms of this multidimensional sleep-related breathing disorder negatively affect quality of life.With our study we aimed to expose the association between obstructive sleep apnea and quality of life in the population of Pomerania, Germany. We utilized data from the population-based Study of Health in Pomerania (SHIP). Information on health status and risk factors about 4420 participants (2275 women) were gathered within the cohort SHIP-TREND, of which 1209 (559 women) underwent an overnight polysomnography and completed sleep questionnaires. The quality of life of the participants was measured using the Short-Form 12 questionnaire. For our study, an ordinal regression analysis with age, sex, body mass index and the Short-Form 12 health survey as predictors for apnea-hypopnea index was computed. The potential factors affecting quality of life are different between physical and mental dimensions of quality of life. Significant effects were found regarding age, sex, body mass index and the Short-Form 12 Mental Component Score, but not the Physical Component Score.

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Section: Discussionsupporting

confidence: 94%

“…A connection between AHI and the PCS is not verifiable. Studies by Matsui et al (2021) and Asghari et al (2013) indicate otherwise.…”

Section: Discussionmentioning

confidence: 94%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

See 2 more Smart Citations

Quality of life in patients with obstructive sleep apnea: Results from the study of health in Pomerania

Vogler

Daboul

Obst

et al. 2022

Journal of Sleep Research

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“…Sleep is a fundamental biological process that has long been considered a key determinant of human health and performance, as well as quality of life [1,2]. Poor sleep quality and sleep disturbances have been associated with the onset and development of several mental disorders [3,4,5], such as depression [6,7,8], schizophrenia [9,10], bipolar disorder [11,12], and suicidal risk increase [13,14,15].…”

Section: Introductionmentioning

confidence: 99%

Sleep Activity Recognition and Characterization from Multi-Source Passively Sensed Data

Martínez-García¹,

Moreno-Pino²,

Olmos³

et al. 2023

Preprint

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Sleep constitutes a key indicator of human health, performance, and quality of life. Sleep deprivation has long been related to the onset, development, and worsening of several mental and metabolic disorders, constituting an essential marker for preventing, evaluating, and treating different health conditions. Sleep Activity Recognition methods can provide indicators to assess, monitor, and characterize subjects' sleep-wake cycles and detect behavioral changes. In this work, we propose a general method that continuously operates on passively sensed data from smartphones to characterize sleep and identify significant sleep episodes. Thanks to their ubiquity, these devices constitute an excellent alternative data source to profile subjects' biorhythms in a continuous, objective, and non-invasive manner, in contrast to traditional sleep assessment methods that usually rely on intrusive and subjective procedures. A Heterogeneous Hidden Markov Model is used to model a discrete latent variable process associated with the Sleep Activity Recognition task in a self-supervised way. We validate our results against sleep metrics reported by tested wearables, proving the effectiveness of the proposed approach and advocating its use to assess sleep without more reliable sources.

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Perceived quality of sleep across the menopausal transition: A retrospective cohort study

Maxwell

Reisinger‐Kindle

Rackett

et al. 2023

Health Science Reports

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Background and Aims To compare sleep quality among naturally and surgically post‐menopausal women, and to identify lifestyle factors that predict sleep quality in pre, peri, and postmenopausal women. Methods This is a retrospective cohort study of data collected from 429 women who participated in Fels Longitudinal Study data. Sleep quality, based on the Pittsburgh Sleep Quality Index and the Epworth Sleepiness Scale, demographics, medical history, depression, quality of life, and physical activity levels were included in the analysis. Results The four study groups did not differ on overall sleep quality with either scale (p = 0.61). Both Post‐M groups were more likely to have a major sleep problem than the Peri‐M and Pre‐M groups (p < 0.001), and to have a history of restless leg syndrome (p = 0.016), but the two Post‐M groups did not differ on these problems. Predictors of sleep quality included depression, bodily pain, vitality, and surgical menopause (p<0.001). Conclusion Menopause is associated with sleep disrupting conditions. This study did not find any significant differences in sleep quality among the three reproductive stages or for natural versus surgical menopause. Women may benefit from addressing other lifestyle factors associated with poor sleep quality including mental health factors.

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Association of Subjective Quality and Quantity of Sleep with Quality of Life among a General Population

Cited by 49 publications

References 48 publications

Quality of life in patients with obstructive sleep apnea: Results from the study of health in Pomerania

Quality of life in patients with obstructive sleep apnea: Results from the study of health in Pomerania

Sleep Activity Recognition and Characterization from Multi-Source Passively Sensed Data

Perceived quality of sleep across the menopausal transition: A retrospective cohort study

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