scholarly journals Association between SLC30A8 rs13266634 Polymorphism and Type 2 Diabetes Risk: A Meta-Analysis

2015 ◽  
Vol 21 ◽  
pp. 2178-2189 ◽  
Author(s):  
Bing Chen
Mutagenesis ◽  
2012 ◽  
Vol 28 (1) ◽  
pp. 25-37 ◽  
Author(s):  
Sihua Peng ◽  
Yimin Zhu ◽  
Bingjian Lü ◽  
Fangying Xu ◽  
Xiaobo Li ◽  
...  

BMJ Open ◽  
2019 ◽  
Vol 9 (1) ◽  
pp. e024446 ◽  
Author(s):  
Nyuyki Clement Kufe ◽  
Maphoko Masemola ◽  
Tinashe Chikowore ◽  
Andre Pascal Kengne ◽  
Tommy Olsson ◽  
...  

AimTo present the protocol of a systematic review and meta-analysis of the available evidence examining the association between sex hormones and type 2 diabetes risk in ageing men and women of African descent.MethodsWe shall conduct a comprehensive search of published studies that examined the association between sex hormones and type 2 diabetes risk in men and women aged ≥40 years from 01/01/1980 to 31/03/2018 with no language restriction. Databases to be searched include: PubMed, Scopus, Cochrane Library, Cumulative Index to Nursing and Allied Health, ISI Web of Science, Clinical Trial registries, Google Scholar and institutional websites such as the WHO, American Diabetes Association, International Diabetes Federation, World Diabetes Foundation, European Association for the Study of Diabetes, African Journal Online and ProQuest databases. This protocol is developed in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Protocols guidelines. Independent screening for eligible studies using defined criteria and data extraction, will be completed in duplicate. Discrepancies will be resolved by consensus or consultation with a third researcher. Risk of bias of included studies will be assessed by the appropriate Cochrane risk of bias tool. The overall association estimates will be pooled using appropriate meta-analytic techniques. Heterogeneity will be assessed using Cochrane Q statistic and the inconsistency index (I2). The random effects model will be used to calculate a pooled estimate.Ethics and disseminationNo ethics clearance is required as no primary data will be collected. The systematic review and meta-analysis are part of a PhD project at WITS University (Johannesburg, South Africa) and results will be presented at conferences and published in a peer-review journal. The results will guide future population specific interventions.PROSPERO registration numberCRD42017074581.


2015 ◽  
Vol 19 (2) ◽  
pp. 230-241 ◽  
Author(s):  
Zahra Maghsoudi ◽  
Reza Ghiasvand ◽  
Amin Salehi-Abargouei

AbstractObjectiveTo systematically review prospective cohort studies about the association between dietary patterns and type 2 diabetes mellitus (T2DM) incidence, and to quantify the effects using a meta-analysis.DesignDatabases such as PubMed, ISI Web of Science, SCOPUS and Google Scholar were searched up to 15 January 2015. Cohort studies which tried to examine the association between empirically derived dietary patterns and incident T2DM were selected. The relative risks (RR) and their 95 % confidence intervals for diabetes among participants with highest v. lowest adherence to derived dietary patterns were incorporated into meta-analysis using random-effects models.ResultsTen studies (n 404 528) were enrolled in the systematic review and meta-analysis; our analysis revealed that adherence to the ‘healthy’ dietary patterns significantly reduced the risk of T2DM (RR=0·86; 95 % CI 0·82, 0·90), while the ‘unhealthy’ dietary patterns adversely affected diabetes risk (RR=1·30; 95 % CI 1·18, 1·43). Subgroup analysis showed that unhealthy dietary patterns in which foods with high phytochemical content were also loaded did not significantly increase T2DM risk (RR=1·06; 95 % CI 0·87, 1·30).Conclusions‘Healthy’ dietary patterns containing vegetables, fruits and whole grains can lower diabetes risk by 14 %. Consuming higher amounts of red and processed meats, high-fat dairy and refined grains in the context of ‘unhealthy’ dietary patterns will increase diabetes risk by 30 %; while including foods with high phytochemical content in these patterns can modify this effect.


2016 ◽  
Vol 175 (5) ◽  
pp. R231-R245 ◽  
Author(s):  
Peiyun Li ◽  
Zhilei Shan ◽  
Li Zhou ◽  
Manling Xie ◽  
Wei Bao ◽  
...  

Objective Epidemiologic studies regarding the association between parity and risk of type 2 diabetes have yielded inconsistent results. Therefore, we performed a systematic review and dose-response meta-analysis to determine the relation between parity and type 2 diabetes risk. Methods We searched PubMed and Embase for published epidemiologic studies that assessed the relation between parity and risk of type 2 diabetes up to 31 March 2016. A dose-response random-effects model was used to combine study-specific relative risks (RRs) and 95% confidence intervals (CIs). Potential sources of heterogeneity were explored by meta-regression and subgroup analyses. Results Seven cohort studies, 1 case-control study and 9 cross-sectional studies including 296 923 participants were eligible for inclusion. The combined RR for the highest versus lowest category of parity indicated a 54% increment in type 2 diabetes risk (95% CI: 29–83%). In the cubic spline model, a nonlinear association was found between parity and risk of type 2 diabetes (P = 0.02 for nonlinearity). Compared with nulliparous women, the estimated RR (95% CI) of type 2 diabetes for women with one to seven children was 1.01 (0.96–1.07), 1.08 (1.00–1.16), 1.20 (1.12–1.30), 1.32 (1.22–1.42), 1.37 (1.27–1.48), 1.39 (1.26–1.52) and 1.39 (1.23–1.57) respectively. Conclusions Higher parity is significantly associated with an increased risk of type 2 diabetes. Further studies are warranted to fully adjust for the potential confounders and explore the causality between parity and type 2 diabetes risk.


2011 ◽  
Vol 106 (11) ◽  
pp. 1649-1654 ◽  
Author(s):  
Jia-Yi Dong ◽  
Lijun Zhang ◽  
Yong-Hong Zhang ◽  
Li-Qiang Qin

Epidemiological studies of dietary glycaemic index (GI) and glycaemic load (GL) in relation to diabetes risk have yielded inconsistent results. We aimed to examine the associations between dietary GI and GL and the risk of type 2 diabetes by conducting a meta-analysis of prospective cohort studies. Relevant studies were identified by a PubMed database search up to February 2011. Reference lists from retrieved articles were also reviewed. We included prospective cohort studies that reported risk estimates with 95 % CI for the associations between dietary GI and GL and the risk of type 2 diabetes. Either a fixed- or random-effects model was used to compute the summary relative risk (RR). We identified thirteen prospective cohort studies of dietary GI or GL related to diabetes risk. The summary RR of type 2 diabetes for the highest category of the GI compared with the lowest was 1·16 (95 % CI 1·06, 1·26;n12), with moderate evidence of heterogeneity (P = 0·02,I2 = 50·8 %). For the GL, the summary RR was 1·20 (95 % CI 1·11, 1·30;n12), with little evidence of heterogeneity (P = 0·10,I2 = 34·8 %). No evidence of publication bias was observed. In addition, the associations persisted and remained statistically significant in the sensitivity analyses. In conclusion, the present meta-analysis provides further evidence in support of significantly positive associations between dietary GI and GL and the risk of type 2 diabetes. Reducing the intake of high-GI foods may bring benefits in diabetes prevention.


2021 ◽  
Author(s):  
Noa Gang ◽  
Kyle Van Allen ◽  
Paul J. Villeneuve ◽  
Heather MacDonald ◽  
Jennifer E. Bruin

AbstractThe relationship between persistent organic pollutants (POPs), including dioxins and dioxin-like polychlorinated biphenyls (DL-PCBs), and diabetes incidence in adults has been extensively studied. However, significant variability exists in the reported associations both between and within studies. Emerging data from rodent studies suggest that dioxin exposure disrupts glucose homeostasis in a sex-specific manner. Thus, we performed a meta-analysis of relevant epidemiological studies to investigate whether there are sex-specific associations between dioxin or DL-PCB exposure and type 2 diabetes incidence. Articles were organized into the following subcategories: data stratified by sex (16%), unstratified data (56%), and data from only 1 sex (16% male, 12% female). We also considered whether exposure occurred either abruptly at high levels through a contamination event (“disaster exposure”) or chronically at background levels (“non-disaster exposure”). Only 8 studies compared associations between dioxin/DL-PCB exposure and diabetes risk in males versus females within the same population. When all sex-stratified or single sex studies were considered in the meta-analysis, the summary odds ratio (OR) for increased diabetes risk was similar between females and males (1.78 and 1.95, respectively) when comparing exposed to reference populations, suggesting that this relationship is not sex-specific. However, when we considered disaster-exposed populations separately, the association differed substantially between sexes, with females showing a much higher OR than males (2.86 and 1.59, respectively). Moreover, the association between dioxin/DL-PCB exposure and diabetes was stronger for females than males in disaster-exposed populations. In contrast, both sexes had significantly increased ORs in non-disaster exposure populations and the OR for females was lower than males (1.40 and 2.02, respectively). Our review emphasizes the importance of considering sex differences, as well as the mode of pollutant exposure, when exploring the relationship between pollutant exposure and diabetes in epidemiological studies.


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