Association between Oral Hygiene and Metabolic Syndrome: A Systematic Review and Meta-Analysis.
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ABSTRACT:
SUBMITTER: Santoso CMA
PROVIDER: S-EPMC8269064 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:ObjectiveDental plaque accumulation and inadequate personal oral hygiene (OH) are known major risk factors of periodontitis. Nevertheless, the magnitude of their effects has not yet been the subject of a meta-analysis.Material and methodsThe Medline and Scopus databases were searched up to May 2016. Observational studies were eligible if they assessed associations between OH and periodontitis in adult subjects. A multivariate random-effects meta-analysis was used to pool the effects of fair/poor OH versus good OH on periodontitis across studies. The associations between oral care habits and periodontitis were also assessed.ResultsA total of 50 studies were eligible; 15 were used for pooling the effect of fair OH versus good OH and poor OH versus good OH on periodontitis, with pooled odds ratios (ORs) of 2.04 [95% confidence interval (CI): 1.65-2.53] and 5.01 (95% CI: 3.40-7.39), respectively. Eleven studies examined oral care habits measured according to toothbrushing regularity and dental visit frequency; pooled ORs of 0.66 (95% CI: 0.47-0.94) and 0.68 (95% CI: 0.47-0.98) were obtained, respectively.ConclusionsFair to poor OH increases the risk of periodontitis by two- to five-fold. This risk can be reduced by regular toothbrushing and dental visits.
| S-EPMC5724709 | biostudies-literature
Project description:PurposeSleep duration is thought to play a key role in the development of metabolic syndrome. However, the results have been inconsistent.MethodsWe conducted a systematic review and meta-analysis of cohort studies and searched publications in PubMed, Embase, Cochrane Central Register of Controlled Trials, and Clinicaltrials.gov. The summary relative risks (RRs) were estimated using a random model. The sensitivity analysis was performed by sequentially excluding each study to test the robustness of the pooled estimates.FindingWe included 13 studies involving 300,202 patients in which short sleep and long sleep significantly increased the risk of metabolic syndrome 15% (RR = 1.15, 95%CI = 1.09-1.22, p < 0.001) and 19% (RR = 1.19, 95%CI = 1.05-1.35, p < 0.001). Moreover, the relationship between sleep duration and metabolic syndrome risk presented a U-shaped curve. Short and long sleep increased the risk of obesity by 14% (RR = 1.14, 95%CI = 1.07-1.22, p<0.001) and 15% (RR = 1.15, 95%CI = 1.00-1.30, p = 0.04), and high blood pressure 16% (RR = 1.16, 95%CI = 1.02-1.31, p = 0.03) and 13% (RR = 1.13, 95%CI = 1.04-1.24, p = 0.01), respectively. Short sleep can potentially increase the risk of high blood sugar by 12% (RR = 1.12, 95%CI = 1.00-1.15, P = 0.05).ImplicationsBased on our findings, sleep is a behavior that can be changed and is economical. Clinically doctors and health professionals should be encouraged to increase their efforts to promote healthy sleep for all people.
| S-EPMC8640251 | biostudies-literature
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].
| S-EPMC9751936 | biostudies-literature
Project description:ObjectivePrevious studies have demonstrated an association between anxiety and metabolic syndrome (MetS). However, the association is still controversial. This updated meta-analysis aimed to reanalyze the association between anxiety and MetS.MethodsWe comprehensively searched PubMed, Embase and Web of Science for all related studies published before January 23, 2023. Observational studies that informed effect size with 95% confidence interval (CI) for the association between anxiety and MetS were included. According to heterogeneity between studies, fixed or random effects models were applied to calculate the pooled effect size. Publication bias was examined by funnel plots.ResultsThe research included 24 cross-sectional studies: 20 studies used MetS as the dependent variable with a pooled OR of 1.07 (95% CI: 1.01-1.13) and four studies used anxiety as the dependent variable with a pooled OR of 1.14 (95% CI: 1.07-1.23). Three cohort studies were found: two studies detected the association of baseline anxiety with the risk of MetS, one of the studies demonstrated a significant association, but a similar result was not found in another study; one study showed no significant association between baseline MetS and the risk of anxiety.ConclusionCross-sectional studies indicated an association between anxiety and MetS. The results from cohort studies are still inconsistent and limited. More large-scale prospective studies are needed to further reveal the causal relationship of anxiety with MetS.
| S-EPMC9978147 | biostudies-literature
Project description: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.
| S-EPMC8564065 | biostudies-literature
Project description:This systematic review and meta-analysis aim to provide the best evidence on the association between metabolic syndrome (MetS) and uric acid (UA) by determining the size of the effect of this biomarker on MetS. The review protocol is registered with PROSPERO (CRD42021231124). The search covered the PubMed and Scopus databases. Methodological quality was assessed with the STROBE tool, overall risk of bias with RevMan (Cochrane Collaboration) and quality of evidence with Grade Pro. Initially, 1582 articles were identified. Then, after excluding duplicates and reviewing titles and abstracts, 1529 articles were excluded from applying the eligibility criteria. We included 43 papers (56 groups) comparing UA concentrations between subjects 91,845 with MetS and 259,931 controls. Subjects with MetS had a higher mean UA of 0.57 mg/dl (95% CI 0.54-0.61) (p < 0.00001). Given the heterogeneity of the included studies, the researchers decided to perform subgroups analysis. Men with MetS have a higher UA concentration mg/dl 0.53 (95% CI 0.45-0.62, p < 0.00001) and women with MetS 0.57 (95% CI 0.48-0.66, p < 0.00001) compared to subjects without MetS. Assessment of UA concentration could provide a new avenue for early diagnosis of MetS, as a new biomarker and the possibility of new therapeutic targets.
| S-EPMC9626571 | biostudies-literature
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.
| S-EPMC7566901 | biostudies-literature
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.
| S-EPMC8166542 | biostudies-literature
Project description:Metabolic syndrome (MetS) is a combination of cardiovascular risk factors associated with type 2 diabetes, obesity, and cardiovascular diseases. The circadian clock gene polymorphisms are very likely to participate in metabolic syndrome genesis and development. However, research findings of the association between circadian rhythm gene polymorphisms and MetS and its comorbidities are not consistent. In this study, a review of the association of circadian clock gene polymorphisms with overall MetS risk was performed. In addition, a meta-analysis was performed to clarify the association between circadian clock gene polymorphisms and MetS susceptibility based on available data. The PubMed and Scopus databases were searched for studies reporting the association between circadian rhythm gene polymorphisms (ARNTL, BMAL1, CLOCK, CRY, PER, NPAS2, REV-ERBα, REV-ERBβ, and RORα) and MetS, and its comorbidities diabetes, obesity, and hypertension. Thirteen independent studies were analyzed with 17,381 subjects in total. The results revealed that the BMAL1 rs7950226 polymorphism was associated with an increased risk of MetS in the overall population. In contrast, the CLOCK rs1801260 and rs6850524 polymorphisms were not associated with MetS. This study suggests that some circadian rhythm gene polymorphisms might be associated with MetS in different populations and potentially used as predictive biomarkers for MetS.
| S-EPMC8773381 | biostudies-literature
Project description:The purpose of this systematic review was to examine the association of metabolic syndrome (MS) with measures of benign prostatic hyperplasia (BPH) including prostate growth rate, prostate volume, International Prostate Symptom Score (IPSS), prostate-specific antigen (PSA) level, and maximal flow rate.Medline, Cochrane CENTRAL, EMBASE, CBM, and Google Scholar databases were searched until March 23, 2015 using combinations of the keywords benign prostate hyperplasia/BPH, metabolic syndrome, total prostate volume, prostate growth rate, prostate specific antigen, International Prostate Symptom Score/IPSS, maximal flow rate. Cohort or case-control studies of patients with BPH and MS that reported quantitative outcomes were included. The pooled mean differences of the outcome measures were compared between patients with and without MS.A total of 158 potentially relevant studies were identified, and 8 were included in the meta-analysis. The 8 studies included in the meta-analysis contained a total of 3093 BPH patients, wherein 1241 had MS and 1852 did not have MS. BPH patients with MS had a significantly higher prostate growth rate (pooled mean difference?=?0.67?mL/y, P?<?0.001) and larger prostate volume (pooled mean difference?=?6.8?mL, P?=?0.010) than the BPH patients without MS. There was no significant difference in IPSS score (pooled mean difference?=?1.58, P?=?0.202) or maximal flow rate (pooled mean difference?=?-1.41?mL/s, P?=?.345) between BPH patients with and without MS. A borderline nonsignificant difference in PSA (pooled mean difference?=?0.24?ng/mL, P?=?0.056) was noted between BPH patients with and without MS.The results of this meta-analysis are consistent with literature indicating that BPH patients with MS have a higher prostate growth rate and larger prostate volume than those without MS; however, further study is necessary to determine the association of BPH and metabolic disorder elements and the potential risk of disease progression in BPH patients with MS.
| S-EPMC4902470 | biostudies-literature