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The Global Prevalence of Metabolic Syndrome in Connection with Sleep Duration: A Systematic Review and Meta-Analysis
Aakanksha Pitliya1, Yasitha Kakarlapudi2, Srivatsa Surya Vasudevan3
1Department of General Medicine, Sri Aurobindo Institute of Medical Sciences and PGI, Indore, India.
Abstract:
The duration and quality of sleep are believed to significantly influence the onset of metabolic syndrome (MetS), but existing data lack consistency. The meta-analysis aims to evaluate the prevalence of the MetS in association with sleep duration. We conducted a systematic review according to the Preferred Reporting Items for Systematic Reviews and Meta-analyses 2020 guidelines. A comprehensive search of PubMed, Google Scholar, and Research Gate databases was performed to identify cohort and cross-sectional studies published in English between 2013 and 2023. We included studies that examined the association between sleep duration/quality and MetS, and two independent reviewers assessed study quality and bias using the Newcastle-Ottawa scale. The systematic review included 11 studies with a total of 343,669 participants, including 4 cohort studies and 7 cross-sectional studies. Sample sizes varied widely, ranging from 293 to 162,121 individuals. The studies had different follow-up periods, participant ages ranging from 10 to 80 years, and predominantly male populations. The prevalence of MetS was higher in average sleepers [52%, 95% confidence interval (CI): 40%-64%] compared with short sleepers (13%, 95% CI: 8%-18%) and long sleepers (15%, 95% CI: 9%-24%). Globally, North American countries exhibit the highest prevalence of MetS across short- (25.3%, 95% CI: 4.2%-72.4%) and long-sleeper (22.4%, 95% CI: 2.8%-74.1%) categories, whereas Asian countries experience the highest prevalence among the average sleeper category (58.7%, 95% CI: 44.1%-71.9%). Our meta-analysis indicates an elevated prevalence of MetS in average sleepers. Future research endeavors address delve into the underlying mechanisms and incorporate objective measures to understand the multifaceted connection between sleep patterns and MetS, guiding more effective preventive and management strategies.
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