Impact of Environmental Airborne Manganese Exposure on Cognitive and Motor Functions in Adults: A Systematic Review and Meta-Analysis
Laura Ruiz-AzconaIgnacio Fernández-OlmoAndrea ExpósitoBohdana MarkivMaría Paz‐ZuluetaPaula Parás‐BravoCarmen Sarabia‐CoboMiguel Santibáñez
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Whether environmental exposure to Manganese (Mn) in adults is associated with poorer results in cognitive and motor function is unclear. We aimed to determine these associations through a meta-analysis of published studies.A systematic review was conducted to identify epidemiological studies on a population ≥18 years old exposed to environmental airborne Mn, and in which results on specific tests to evaluate cognitive or motor functions were reported. We consulted Medline through PubMed, Web of Science and SCOPUS databases. We also performed a manual search within the list of bibliographic references of the retrieved studies and systematic reviews. To weight Mn effects, a random effects versus fixed effect model was chosen after studying the heterogeneity of each outcome.Eighteen studies met the inclusion criteria. Among them, eleven studies reported data susceptible for meta-analysis through a pooled correlation or a standardized means difference (SMD) approach between exposed and non-exposed groups. Regarding cognitive function, the results of the studies showed heterogeneity among them (I2 = 76.49%, p < 0.001). The overall effect was a statistically significant negative correlation in the random effects model (pooled r = -0.165; 95%CI: -0.214 to -0.116; p < 0.001). For SMD, the results showed a lower heterogeneity with a negative SMD that did not reach statistical significance under the fixed effects model (SMD = -0.052; 95%CI -0.108 to 0.004; p = 0.068). Regarding motor function, heterogeneity (I2 = 75%) was also observed in the correlation approach with a pooled r (random effect model) = -0.150; 95%CI: -0.219 to -0.079; p < 0.001. Moderate heterogeneity was observed according to the SMD approach (I2 = 52.28%), with a pooled SMD = -0.136; 95%CI: -0.188 to-0.084; p < 0.001, indicating worse motor function in those exposed.Correlation approach results support a negative effect on cognitive and motor functions (the higher the Mn levels, the poorer the scores). Regarding the SMD approach, results also support a worse cognitive and motor functions in those exposed, although only for motor function statistical significance was obtained.Keywords:
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In randomized controlled trials (RCTs), endpoint scores, or change scores representing the difference between endpoint and baseline, are values of interest. These values are compared between experimental and control groups, yielding a mean difference between the experimental and control groups for each outcome that is compared. When the mean difference values for a specified outcome, obtained from different RCTs, are all in the same unit (such as when they were all obtained using the same rating instrument), they can be pooled in meta-analysis to yield a summary estimate that is also known as a mean difference (MD). Because pooling of the mean difference from individual RCTs is done after weighting the values for precision, this pooled MD is also known as the weighted mean difference (WMD). Sometimes, different studies use different rating instruments to measure the same outcome; that is, the units of measurement for the outcome of interest are different across studies. In such cases, the mean differences from the different RCTs cannot be pooled. However, these mean differences can be divided by their respective standard deviations (SDs) to yield a statistic known as the standardized mean difference (SMD). The SD that is used as the divisor is usually either the pooled SD or the SD of the control group; in the former instance, the SMD is known as Cohen's d, and in the latter instance, as Glass' delta. SMDs of 0.2, 0.5, and 0.8 are considered small, medium, and large, respectively. SMDs can be pooled in meta-analysis because the unit is uniform across studies. This article presents and explains the different terms and concepts with the help of simple examples.
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In meta-analyses involving a few trials, appropriate measures should be employed to assess between-study heterogeneity. When the number of studies is less than five and heterogeneity is evident, the Hartung and Knapp (HK) correction should be used. The aim of this study was to compare the reported estimates of published orthodontic meta-analyses with the pooled effect size estimates and prediction intervals (PI) calculated using eight heterogeneity estimators and corrected using the HK correction.
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BACKGROUND: Using the traditional random-effects model, a recent meta-analysis of randomized controlled trials reported a statistically significant standardized mean difference (SMD) reduction in cancer-related fatigue (CRF) as a result of aerobic exercise (SMD, -0.22, 95% CI, -0.39 to -0.04, p = 0.01). However, a recently developed inverse heterogeneity (IVhet) model has been shown to be more valid than the traditional random-effects model. PURPOSE: The purpose of this study was to compare these previous meta-analytic results with those using the IVhet model. METHODS: Using data from a previous meta-analysis that included 36 SMD effect sizes (ES’s) representing 2,830 adults (1,426 exercise, 1,404 control), results were pooled using the IVhet model. In addition, absolute and relative differences between the IVhet and random-effects results for CRF were calculated as well as influence analysis with each SMD ES deleted from the IVhet model once. Non-overlapping 95% confidence intervals were considered statistically significant. RESULTS: A statistically non-significant reduction in CRF fatigue was found as a result of aerobic exercise using the IVhet model (SMD, -0.08, 95% CI, -0.31 to 0.14, p = 0.46). The IVhet model yielded a SMD ES that was 0.14 (63.6%) smaller than the random-effects model. With each study deleted from the IVhet model once, results remained statistically non-significant with SMD ES’s ranging from -0.11 (95% CI, -0.33 to 0.11) to -0.06 (95% CI, -0.28 to 0.16). CONCLUSIONS: The results of the current study suggest that there is currently insufficient evidence to support the use of aerobic exercise for reducing CRF in adults. Future studies should consider use of the IVhet versus traditional random-effects model when conducting aggregate data meta-analyses. Supported by NIH Grant U54GM104942
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Heterogeneity in meta-analysis describes differences in treatment effects between trials that exceed those we may expect through chance alone. Accounting for heterogeneity drives different statistical methods for summarizing data and, if heterogeneity is anticipated, a random-effects model will be preferred to the fixed-effects model. Random-effects models assume that there may be different underlying true effects estimated in each trial which are distributed about an overall mean. The confidence intervals (CIs) around the mean include both within-study and between-study components of variance (uncertainty). Summary effects provide an estimation of the average treatment effect, and the CI depicts the uncertainty around this estimate. There are 5 statistics that are computed to identify and quantify heterogeneity. They have different meaning and give complementary information: Q statistic and its P-value simply test whether effect sizes depart from homogeneity, T2 and T quantify the amount of heterogeneity, and I2 expresses the proportion of dispersion due to heterogeneity. The point estimate and CIs for random-effects models describe the practical implications of the observed heterogeneity and may usefully be contrasted with the fixed-effects estimates.
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Whether environmental exposure to Manganese (Mn) in adults is associated with poorer results in cognitive and motor function is unclear. We aimed to determine these associations through a meta-analysis of published studies.A systematic review was conducted to identify epidemiological studies on a population ≥18 years old exposed to environmental airborne Mn, and in which results on specific tests to evaluate cognitive or motor functions were reported. We consulted Medline through PubMed, Web of Science and SCOPUS databases. We also performed a manual search within the list of bibliographic references of the retrieved studies and systematic reviews. To weight Mn effects, a random effects versus fixed effect model was chosen after studying the heterogeneity of each outcome.Eighteen studies met the inclusion criteria. Among them, eleven studies reported data susceptible for meta-analysis through a pooled correlation or a standardized means difference (SMD) approach between exposed and non-exposed groups. Regarding cognitive function, the results of the studies showed heterogeneity among them (I2 = 76.49%, p < 0.001). The overall effect was a statistically significant negative correlation in the random effects model (pooled r = -0.165; 95%CI: -0.214 to -0.116; p < 0.001). For SMD, the results showed a lower heterogeneity with a negative SMD that did not reach statistical significance under the fixed effects model (SMD = -0.052; 95%CI -0.108 to 0.004; p = 0.068). Regarding motor function, heterogeneity (I2 = 75%) was also observed in the correlation approach with a pooled r (random effect model) = -0.150; 95%CI: -0.219 to -0.079; p < 0.001. Moderate heterogeneity was observed according to the SMD approach (I2 = 52.28%), with a pooled SMD = -0.136; 95%CI: -0.188 to-0.084; p < 0.001, indicating worse motor function in those exposed.Correlation approach results support a negative effect on cognitive and motor functions (the higher the Mn levels, the poorer the scores). Regarding the SMD approach, results also support a worse cognitive and motor functions in those exposed, although only for motor function statistical significance was obtained.
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The prevalence and prognostic implications of pre-existing dyslipidaemia in patients infected by the SARS-CoV-2 remain unclear.To assess the prevalence and mortality risk in COVID-19 patients with pre-existing dyslipidaemia.Systematic review and meta-analysis.Preferred reporting items for systematic reviews and meta-analyses guidelines were followed in abstracting data and assessing validity. We searched MEDLINE and Scopus to locate all the articles published up to 31 January 2021, reporting data on dyslipidaemia among COVID-19 survivors and non-survivors. The pooled prevalence of dyslipidaemia was calculated using a random-effects model and presenting the related 95% confidence interval (CI), while the mortality risk was estimated using the Mantel-Haenszel random-effect models with odds ratio (OR) and related 95% CI. Statistical heterogeneity was measured using the Higgins I2 statistic.Of about 18 studies, enrolling 74 132 COVID-19 patients (mean age 70.6 years), met the inclusion criteria and were included in the final analysis. The pooled prevalence of dyslipidaemia was 17.5% of cases (95% CI: 12.3-24.3%, P < 0.0001), with high heterogeneity (I2 = 98.7%). Pre-existing dyslipidaemia was significantly associated with higher risk of short-term death (OR: 1.69, 95% CI: 1.19-2.41, P = 0.003), with high heterogeneity (I2 = 88.7%). Due to publication bias, according to the Trim-and-Fill method, the corrected random-effect ORs resulted 1.61, 95% CI 1.13-2.28, P < 0.0001 (one studies trimmed).Dyslipidaemia represents a major comorbidity in about 18% of COVID-19 patients but it is associated with a 60% increase of short-term mortality risk.
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Background/Aim. Whether environmental exposure to Mn in adults is associated with poorer results in cognitive and motor function is unclear. We aimed to determine these associations through a meta-analysis of published studies. Methods: A systematic review was conducted to identify environmental Mnepidemiologic studies in >=18 years old, and in which results on a specific test to evaluate cognitive or motor function were reported. Medline through PubMed, ISI Web of Knowledge and SCOPUS databases were consulted. A manual search in the references of retrieved studies and systematic reviews found that addressed the topic was also conducted. Data were pooled in meta-analysis using the method of random effects or fixed effects, as convenient, after examination of statistical heterogeneity. Results.Seventeen studies fulfill inclusion criteria. Among them, 13 studies reported data susceptible of meta-analysis through a pooled correlation or a Standardized Means Difference (SMD) approach between exposed and non-exposed. Regarding cognitive function, the results of the studies showed heterogeneity among them (I2=76.49%, p<0.001). The overall effect was a statistically significant negative correlation in the random effects model (pooled r=-0.165; 95%CI: -0.214 to -0.116; p<0.001). In terms of SMD, results showed also moderate heterogeneity but did not reach statistical significance under the random effects model (SMD=-0.049; 95%CI: -0.124 to 0.026; p=0.203). Regarding motor function, heterogeneity (I2=75%)was also observed in the correlation approach with a pooled r (random effect model)=-0.150; 95%CI: -0.219 to -0.079. Moderate heterogenety was observed according to SMD approach (I2=51.81%), with a pooled SMD=-0.136; 95%CI: -0.188 to-0.084; p<0.001, indicating worse motor function in exposed. Conclusions: Correlation approach results support a negative effect on cognitive and motor function (the higher the Mn levels, the poorer scores). Regarding SMD approach, results also support a worse cognitive and motor function in exposed, although only for motor function statistical significance was obtained.
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Although the results of a recent meta-analysis using the traditional random effects model yielded a statistically significant standardized mean difference (SMD) reduction in cancer-related fatigue (CRF) as a result of aerobic exercise, a recently developed inverse heterogeneity (IVhet) model has been shown to be more valid than the traditional random effects model. The purpose of this study was to compare these previous meta-analytic results using the IVhet model.Using data from a previous meta-analysis that included 36 SMD effect sizes (ES) representing 2,830 adults (1,426 exercise, 1,404 control), results were pooled using the IVhet model. Absolute and relative differences between the IVhet and random effects results for CRF were also calculated as well as influence analysis with each SMD ES deleted from the IVhet model. Nonoverlapping 95% confidence intervals (CI) were considered statistically significant.A statistically nonsignificant reduction in CRF fatigue was found as a result of aerobic exercise using the IVhet model (SMD, -0.08; 95% CI, -0.31-0.14; P = 0.46). The IVhet model yielded a SMD ES that was 0.14 (63.6%) smaller than the random effects model. With each study deleted from the IVhet model once, results remained statistically nonsignificant with SMD ESs ranging from -0.11 (95% CI, -0.33-0.11) to -0.06 (95% CI, -0.28-0.16).Insufficient evidence currently exists to support the use of aerobic exercise for reducing CRF in adults.Additional studies are needed to determine the certainty of aerobic exercise on CRF in adults. Cancer Epidemiol Biomarkers Prev; 26(2); 281-3. ©2016 AACR.
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