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      Poor sleep quality is negatively associated with low cognitive performance in general population independent of self-reported sleep disordered breathing

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          Abstract

          Background

          Sleep disordered breathing (SDB) plays a significant role in both sleep quality and cognition and whether it has an impact on the relationship between above two factors remains to be clear. The study aimed to explore the association between sleep quality and cognitive performance in general population by considering influence of sleep disordered breathing (SDB).

          Methods

          In this cross-sectional study, we enrolled subjects aged ≥ 18 years using a multi-stage random sampling method. Cognitive status was assessed using Mini Mental State Examination (MMSE) questionnaire, sleep quality using Pittsburgh Sleep Quality Index (PSQI) and SDB was assessed using No-SAS scale, respectively. Multi-variable logistic regression was applied to examine the association of sleep quality and cognitive performance. Subgroup analyses were performed in different age groups, and in those with and without SDB.

          Results

          Finally, 30,872 participants aged 47.5 ± 13.8 years with 53.5% women were enrolled, of whom 32.4% had poor sleep quality and 18.6% had low cognitive performance. Compared with good sleepers, subjects with poor sleep quality exhibited significantly higher presence of low cognitive performance (23.7% vs 16.2%, P < 0.001). Poor sleepers revealed 1.26 (95%CI: 1.16,1.36), 1.26 (1.08,1.46) and 1.25 (1.14,1.37) fold odds for low cognitive performance in general population and in subjects with and without self-reported SDB respectively. Stratified by age and SDB, the association was observed in young and middle-aged group without SDB (OR = 1.44, 95%CI: 1.30,1.59) and in the elderly group with SDB (OR = 1.30, 95%CI: 1.07,1.58).

          Conclusions

          Sleep quality is in a negative association with cognitive performance in general population independent of SDB, implying improvement of sleep disturbances is a potential objective of intervention strategies for cognitive protection at population level.

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          Most cited references41

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          Definition, diagnosis and classification of diabetes mellitus and its complications. Part 1: diagnosis and classification of diabetes mellitus provisional report of a WHO consultation.

          K.G.M.M. Alberti, P.Z. Zimmet (1998)
          The classification of diabetes mellitus and the tests used for its diagnosis were brought into order by the National Diabetes Data Group of the USA and the second World Health Organization Expert Committee on Diabetes Mellitus in 1979 and 1980. Apart from minor modifications by WHO in 1985, little has been changed since that time. There is however considerable new knowledge regarding the aetiology of different forms of diabetes as well as more information on the predictive value of different blood glucose values for the complications of diabetes. A WHO Consultation has therefore taken place in parallel with a report by an American Diabetes Association Expert Committee to re-examine diagnostic criteria and classification. The present document includes the conclusions of the former and is intended for wide distribution and discussion before final proposals are submitted to WHO for approval. The main changes proposed are as follows. The diagnostic fasting plasma (blood) glucose value has been lowered to > or =7.0 mmol l(-1) (6.1 mmol l(-1)). Impaired Glucose Tolerance (IGT) is changed to allow for the new fasting level. A new category of Impaired Fasting Glycaemia (IFG) is proposed to encompass values which are above normal but below the diagnostic cut-off for diabetes (plasma > or =6.1 to or =5.6 to <6.1 mmol l(-1)). Gestational Diabetes Mellitus (GDM) now includes gestational impaired glucose tolerance as well as the previous GDM. The classification defines both process and stage of the disease. The processes include Type 1, autoimmune and non-autoimmune, with beta-cell destruction; Type 2 with varying degrees of insulin resistance and insulin hyposecretion; Gestational Diabetes Mellitus; and Other Types where the cause is known (e.g. MODY, endocrinopathies). It is anticipated that this group will expand as causes of Type 2 become known. Stages range from normoglycaemia to insulin required for survival. It is hoped that the new classification will allow better classification of individuals and lead to fewer therapeutic misjudgements.
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            Sleep drives metabolite clearance from the adult brain.

            Lulu Xie, Hongyi Kang, Qiwu Xu … (2013)
            The conservation of sleep across all animal species suggests that sleep serves a vital function. We here report that sleep has a critical function in ensuring metabolic homeostasis. Using real-time assessments of tetramethylammonium diffusion and two-photon imaging in live mice, we show that natural sleep or anesthesia are associated with a 60% increase in the interstitial space, resulting in a striking increase in convective exchange of cerebrospinal fluid with interstitial fluid. In turn, convective fluxes of interstitial fluid increased the rate of β-amyloid clearance during sleep. Thus, the restorative function of sleep may be a consequence of the enhanced removal of potentially neurotoxic waste products that accumulate in the awake central nervous system.
            Article 0 comments Cited 930 times – based on 0 reviews     Review now
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              Prevalence of obstructive sleep apnea in the general population: A systematic review.

              Chamara Senaratna, Jennifer Perret, Caroline J. Lodge … (2017)
              With this systematic review we aimed to determine the prevalence of obstructive sleep apnea (OSA) in adults in the general population and how it varied between population sub-groups. Twenty-four studies out of 3807 found by systematically searching PubMed and Embase databases were included in this review. Substantial methodological heterogeneity in population prevalence studies has caused a wide variation in the reported prevalence, which, in general, is high. At ≥5 events/h apnea-hypopnea index (AHI), the overall population prevalence ranged from 9% to 38% and was higher in men. It increased with increasing age and, in some elderly groups, was as high as 90% in men and 78% in women. At ≥15 events/h AHI, the prevalence in the general adult population ranged from 6% to 17%, being as high as 49% in the advanced ages. OSA prevalence was also greater in obese men and women. This systematic review of the overall body of evidence confirms that advancing age, male sex, and higher body-mass index increase OSA prevalence. The need to a) consider OSA as having a continuum in the general population and b) generate consensus on methodology and diagnostic threshold to define OSA so that the prevalence of OSA can be validly compared across regions and countries, and within age-/sex-specific subgroups, is highlighted.
              Article 0 comments Cited 438 times – based on 0 reviews     Review now
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                Author and article information

                Contributors
                Nanfang Li: lnanfang2016@sina.com
                Journal
                Journal ID (nlm-ta): BMC Public Health
                Journal ID (iso-abbrev): BMC Public Health
                Title: BMC Public Health
                Publisher: BioMed Central (London )
                ISSN (Electronic): 1471-2458
                Publication date (Electronic): 3 January 2022
                Publication date PMC-release: 3 January 2022
                Publication date Collection: 2022
                Volume: 22
                Electronic Location Identifier: 3
                Affiliations
                [1 ]Hypertension Center of People’s Hospital of Xinjiang Uygur Autonomous Region, Xinjiang Hypertension Institute National Health Committee Key Laboratory of Hypertension Clinical Research, No. 91, Tianchi Road Urumqi, Xinjiang, 830001 China
                [2 ]Xinjiang Hypertension Institute, Xinjiang, China
                [3 ]National Health Committee Key Laboratory of Hypertension Clinical Research, Xinjiang, China
                [4 ]Key Laboratory of Xinjiang Uygur Autonomous Region “Hypertension Research Laboratory, Xinjiang, China
                [5 ]Xinjiang Clinical Medical Research Center for Hypertension (Cardio-Cerebrovascular) Diseases, Xinjiang, China
                Article
                Publisher ID: 12417
                DOI: 10.1186/s12889-021-12417-w
                PMC ID: 8725333
                PubMed ID: 34980052
                SO-VID: cd4bf83a-01f5-452d-bd01-9ed9b4739411
                Copyright © © The Author(s) 2022
                License:

                Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

                History
                Date received : 20 April 2021
                Date accepted : 9 December 2021
                Categories
                Subject: Research
                Custom metadata
                issue-copyright-statement © The Author(s) 2022

                ScienceOpen disciplines: Public health
                Keywords: sleep quality,sleep disordered breathing,low cognitive performance
                Data availability:
                ScienceOpen disciplines: Public health
                Keywords: sleep quality, sleep disordered breathing, low cognitive performance

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