Dataset Information

Association Between Eating Speed and Metabolic Syndrome: A Systematic Review and Meta-Analysis.

ABSTRACT: Objective: This review aimed to systematically summarize and meta-analyze the association between eating speed and metabolic syndrome (MetS). Methods: Following the Preferred Reporting Items for Systematic Reviews, and Meta Analyses (PRISMA) guidelines, four electronic databases (PubMed, Web of Science, MEDLINE, and EMBASE) were searched until March 2021 to identify eligible articles based on a series of inclusion and exclusion criteria. Heterogeneity was examined using I ² statistics. Using random-effects models, the pooled odds ratios (ORs), and 95% CIs were calculated to evaluate the association between eating speed with MetS and its components, including central obesity, blood pressure (BP), high-density lipoprotein cholesterol (HDL), triglyceride (TG), and fasting plasma glucose (FPG). Results: Of the 8,500 original hits generated by the systematic search, 29 eligible studies with moderate-to-high quality were included, involving 465,155 subjects. The meta-analysis revealed that eating faster was significantly associated with higher risks of MetS (OR = 1.54, 95% CI: 1.27-1.86), central obesity (OR = 1.54, 95% CI: 1.37-1.73), elevated BP (OR = 1.26, 95% CI: 1.13-1.40), low HDL (OR = 1.23, 95% CI: 1.15-1.31), elevated TG (OR = 1.29, 95% CI: 1.18-1.42), and elevated FPG (OR = 1.16, 95% CI: 1.06-1.27) compared to eating slowly. Conclusions: The results of the review indicated that eating speed was significantly associated with MetS and its components. Interventions related to decreasing eating speed may be beneficial for the management of MetS. Systematic Review Registration: https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42021242213, identifier: CRD42021242213.

SUBMITTER: Yuan SQ

PROVIDER: S-EPMC8564065 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Association Between Eating Speed and Metabolic Syndrome: A Systematic Review and Meta-Analysis.

Yuan Shu-Qian SQ Liu Ying-Ming YM Liang Wei W Li Fei-Fei FF Zeng Yuan Y Liu Yin-Yue YY Huang Shu-Zhen SZ He Quan-Yuan QY Quach Binh B Jiao Jiao J Baker Julien S JS Yang Yi-de YD

Frontiers in nutrition 20211020

Objective: This review aimed to systematically summarize and meta-analyze the association between eating speed and metabolic syndrome (MetS). Methods: Following the Preferred Reporting Items for Systematic Reviews, and Meta Analyses (PRISMA) guidelines, four electronic databases (PubMed, Web of Science, MEDLINE, and EMBASE) were searched until March 2021 to identify eligible articles based on a series of inclusion and exclusion criteria. Heterogeneity was examined using I <s ...[more]

PMID: 34746200

Similar Datasets

Project description:BackgroundAlthough muscle strength has been reported to be associated with metabolic syndrome (MetS), the association is still controversial. Therefore, the purpose of this meta-analysis was to identify the association between handgrip strength (HGS) and MetS.MethodsOriginal research studies involving HGS and MetS from database inception to 20 May 2022 were selected from PubMed, Web of Science, Embase, China National Knowledge Infrastructure, Wanfang databases, and Chinese Biomedical Document Service System. The odds ratios (ORs) with 95% confidence intervals (CIs) of MetS for HGS were calculated using a random-effects model. A dose-response analysis was performed. Subgroup analysis and meta-regression were also conducted.ResultsThirty effect sizes (reported in 19 articles) with a total of 43,396 participants were included in this meta-analysis. All studies were considered to be of moderate-to-good quality. An inverse association between HGS (low vs. high) with MetS was shown (OR: 2.59, 95% CI: 2.06-3.25). Subgroup analyses demonstrated the pooled ORs of relative HGS (HGS/weight), relative HGS (HGS/BMI), and absolute HGS were 2.97 (95% CI: 2.37-3.71), 2.47 (95% CI: 1.08-5.63), and 1.34 (95% CI: 1.06-1.68), respectively. Dose-response analysis revealed a significant linear dose-response relationship between relative HGS (HGS/weight) and MetS in observational studies (0.1 HGS/weight: OR, 0.68; 95% CI: 0.62-0.75). Univariate meta-regression analysis indicated that country status, measuring tools of HGS, components of MetS, and diagnosed criteria of MetS explained 16.7%, 26.2%, 30.1%, and 42.3% of the tau-squared in the meta-regression, respectively.ConclusionThe results of the current meta-analysis indicated that lower HGS is associated with a higher risk of MetS. A linear dose-response association between lower relative HGS (HGS/weight) and increased prevalence of MetS was found. Accordingly, a lower HGS is a significant predictor of MetS.Systematic review registration[https://www.crd.york.ac.uk/PROSPERO/], identifier [CRD42021276730].

Project description: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.

Project description:Previous meta-analyses that found an inverse association between coffee consumption and metabolic syndrome pooled data from cross-sectional and longitudinal studies, which could lead to potentially misleading conclusions. Hence, this work aimed to reassess this association by analyzing data from the 2 types of studies separately and including recent studies. Online databases including PubMed, Scopus, Embase, The Cumulative Index to Nursing and Allied Health Literature (CINAHL) Plus, and Science Direct were searched for relevant studies published up to July 2020. Both cross-sectional and longitudinal studies were included if published after 1999, reported both effect estimates and CIs, and presented results adjusted for confounding variables. Data of the highest coffee consumption level in each study, as well as those of medium consumption levels in studies with ≥3 consumption categories, were pooled using random-effect models, with sex-stratified and sex-adjusted results being analyzed separately. Results were obtained based on data from 13 cross-sectional studies involving 280,803 participants and 2 longitudinal studies involving 17,014 participants. The overall sex-adjusted association of the highest consumption level was not significant (n = 9 studies; OR: 0.88; 95% CI: 0.70, 1.10; I2: 91.5%) and the 2 longitudinal studies both yielded no association. Subgroup analysis revealed inverse associations in both males and females, as well as in Caucasians with medium coffee consumption (n = 4 studies, OR: 0.88; 95% CI: 0.84, 0.93; I2: 0%). Although residual confounding could affect the results of this meta-analysis, our findings suggested with a low certainty that coffee consumption may not be associated with metabolic syndrome, a finding that is different from those of previous meta-analyses and could be due to variation in characteristics of study participants. More longitudinal studies are also needed to further assess the temporal association between coffee consumption and metabolic syndrome. This meta-analysis was registered at https://www.crd.york.ac.uk/prospero as CRD42018110650.

Dataset Information

Association Between Eating Speed and Metabolic Syndrome: A Systematic Review and Meta-Analysis.

Publications

Association Between Eating Speed and Metabolic Syndrome: A Systematic Review and Meta-Analysis.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets