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. 2020 Oct 2:11:517120.
doi: 10.3389/fneur.2020.517120. eCollection 2020.

Association Between Self-Reported Snoring and Metabolic Syndrome: A Systematic Review and Meta-Analysis

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Association Between Self-Reported Snoring and Metabolic Syndrome: A Systematic Review and Meta-Analysis

Jinsha Ma et al. Front Neurol. .

Abstract

Background: Snoring is a common condition. Previous studies have reported the relationships between snoring and metabolic syndrome (MetS) and/or its five components: hypertension, hyperglycemia, low-high density lipoprotein (low-HDL), high-triglyceride level, and abdominal obesity. However, conclusions have been inconsistent, and there has been no comprehensive summary on this. Therefore, we performed a systematic review on the relationships between snoring and MetS, including each of MetS' components. Methods: A systematic review and a meta-analysis were conducted following the Meta-analysis of Observational Studies in Epidemiology group and Preferred Reporting Items for Systematic Reviews and Meta-analysis guidelines. Electronic databases including PubMed, Embase, and the Cochrane Library were searched for publications from inception to 15 July 2020. The inverse-variance weighted method was used in the meta-analysis to calculate the pooled odds ratios (ORs) and their 95% confidence intervals (CIs) to determine the association between snoring and MetS (and its components) through a fixed or random effect model. A restricted cubic spline regression model and the linear regression model were used in a two-stage dose-response meta-analysis to evaluate the non-linear and the linear trends between snoring frequency and MetS and its components. Results: A total of 40 studies with 966,652 participants were included in this study. The pooled ORs between snoring and MetS and its components, hypertension, hyperglycemia, low-HDL, high-triglyceride level, and abdominal obesity, were 1.61 (95% CI, 1.43-1.78), 1.23 (95% CI, 1.15-1.31), 1.05 (95% CI, 1.04-1.07), 1.09 (95% CI, 1.00-1.18), 1.08 (95% CI, 1.00-1.17), and 1.75 (95% CI, 1.46-2.05), respectively. Non-linear trends were detected in the five associations except for low-HDL. A linear trend was detected in the association of snoring with hypertension, hyperglycemia, low-HDL, or abdominal obesity, with ORs of 1.07 (95% CI, 1.01-1.13), 1.05 (95% CI, 1.02-1.08), 1.03 (95% CI, 1.02-1.04), and 1.17 (95% CI, 1.16-2.89), respectively. Conclusion: Snoring was a risk factor of MetS, and a dose-response relationship existed between the two. Timely intervention in identifying snorers can minimize as much as possible the risk of metabolic syndrome in those who snore.

Keywords: dose-response; meta-analysis; metabolic syndrome; snoring; systematic review.

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Figures

Figure 1
Figure 1
Flow chart.
Figure 2
Figure 2
Forest plots showing the association between snoring frequency and metabolic syndrome.
Figure 3
Figure 3
(A) Funnel plots of association between snoring frequency and metabolic syndrome. (B) Trim and fill analysis for an asymmetric funnel plot.
Figure 4
Figure 4
Association between snoring frequency and metabolic syndrome (MetS) by dose–response meta-analysis. (A) Non-linear trend between snoring frequency and MetS. (B) Linear trend between snoring frequency and MetS.
Figure 5
Figure 5
Forest plots showing the association between snoring frequency and the components of metabolic syndrome. (A) Snoring frequency and blood pressure. (B) Snoring frequency and glucometabolism. (C) Snoring frequency and lipid metabolism. (D) Snoring frequency and abdominal obesity.

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References

    1. Grundy SM, Cleeman JI, Daniels SR, Donato KA, Eckel RH, Franklin BA, et al. Diagnosis and management of the metabolic syndrome: an american heart association/national Heart, lung, and blood institute scientific statement: executive summary. Circulation. (2005) 112:2735–52. 10.1161/CIRCULATIONAHA.105.169404 - DOI - PubMed
    1. Zhao SC, Xia M, Tang JC, Yan Y. Associations between metabolic syndrome and clinical benign prostatic hyperplasia in a northern urban Han Chinese population: a prospective cohort study. Sci Rep. (2016) 2016:33933 10.1038/srep33933 - DOI - PMC - PubMed
    1. Andrea G, Kristi R, Jiang H. Metabolic syndrome and risk of cardiovascular disease: a meta-analysis. Am J Med. (2006) 119:812–9. 10.1016/j.amjmed.2006.02.031 - DOI - PubMed
    1. Apoor SG, Brandi JW, Daniel EH, Patricia JE, Lisa AG, Virend KS, et al. . Metabolic syndrome and risk of incident cardiovascular events and death: a systematic review and meta-analysis of longitudinal studies. J Am Coll Cardiol. (2007) 49:403–14. 10.1016/j.jacc.2006.09.032 - DOI - PubMed
    1. Vidigal Fde C, Ribeiro AQ, Babio N, Salas-Salvadó J, Bressan J. Prevalence of metabolic syndrome and pre-metabolic syndrome in health professionals: LATINMETS Brazil study. Diabetol Metabol Syndr. (2015) 7:6. 10.1186/s13098-015-0003-x - DOI - PMC - PubMed

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