Poor sleep quality is very common among pregnant women. Gestational diabetes mellitus (GDM) has been related to various adverse maternal and neonatal outcomes. The aim of this systematic review was to examine the association between poor sleep quality and gestational diabetes risk. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines, a systematic search was conducted in five electronic databases from inception to February 2019. Studies that examined the relationship between sleep quality and glucose in pregnant women were screened for eligibility. Pooled odds ratio (OR) with 95% confidence interval (CI) was calculated from aggregate data using a fixed-effect model. Thirteen non-experimental studies (n = 21,194 women) were eligible for inclusion. Poor sleep quality was measured using subjective questionnaires in nine studies and objective methods (actigraphy or polysomnography) in four studies. GDM was typically diagnosed following standard guidelines. Eight studies were included in the meta-analysis for GDM. Overall, self-reported poor sleep quality was a significant risk factor for GDM (pooled OR = 1.43, 95%CI: 1.16,1.77, p = 0.001). Three studies examined the association between objective sleep quality and GDM, but no significant relationship was observed. Subjective poor sleep quality was related to an increased risk for GDM, while objectively measured sleep quality was not. This review was limited by the assessment of sleep quality. Future larger studies are warranted to examine the effects of sleep quality on glucose metabolism in pregnancy. Ideally, these studies should measure sleep quality using both validated questionnaires and objective methods. These will provide further directions for improving sleep during pregnancy and exploring its effects on glucose metabolism.
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http://dx.doi.org/10.1016/j.sleep.2019.11.1246 | DOI Listing |
Discrimination (unfair treatment due to group membership) is relatively common among adolescents and has been linked to poor sleep and physical health. Individual differences in physiological functioning may moderate these associations. A sample of 323 youth (48% boys, 52% girls; 58.
View Article and Find Full Text PDFJ Geriatr Psychiatry Neurol
January 2025
Unit of Psychiatry, Department of Public Health and Medicinal Administration, & Institute of Translational Medicine, Faculty of Health Sciences, University of Macau, Macao SAR, China.
Within the global population, depression and anxiety are common among older adults. Tai Chi is believed to have a positive impact on these disturbances. This study examined the network structures of depression and anxiety among older Tai Chi practitioners vs non-practitioners.
View Article and Find Full Text PDFWound Repair Regen
January 2025
Research Unit for Plastic Surgery, University of Southern Denmark, Odense, Denmark.
The WOUND-Q is a patient-reported outcome measure for individuals with any type of chronic wound. This study aimed to identify patient and wound factors associated with the four WOUND-Q health-related quality of life (HRQL) scales: Life impact, Psychological, Sleep, and Social. Adults with a chronic wound were recruited internationally through clinical settings between August 2018 and May 2020, and through an online platform (i.
View Article and Find Full Text PDFJ Pain Res
December 2024
Department of Pain, The First People's Hospital of Zunyi City, Zunyi, Guizhou Province, 563000, People's Republic of China.
Objective: To compare the application effects of short-term peripheral nerve stimulation (st-PNS) and pulsed radiofrequency (PRF) technology in postherpetic neuralgia (PHN).
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Front Digit Health
December 2024
Faculty of Engineering and Computing, Liwa College, Abu Dhabi, United Arab Emirates.
The evolution of artificial intelligence (AI) has revolutionised numerous aspects of our daily lives, with profound implications across various sectors, including healthcare. Although the concept of AI in healthcare was introduced in the early 1970s, the integration of this technology in healthcare is still in the evolution phase. Despite barriers, the current decade is witnessing an increased utility of AI into diverse specialities of the medical field to enhance precision medicine, predict diagnosis, therapeutic results, and prognosis; this includes respiratory medicine, critical care, and in their allied specialties.
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