重金屬、發炎因子與第2型糖尿病相關之研究

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Title:	重金屬、發炎因子與第2型糖尿病相關之研究 A Study on the Relationship among Heavy Metal, Inflammation and Type 2 Diabetes
Authors:	魏榮男
Contributors:	嘉南藥理大學職業安全衛生系(含產業安全衛生與防災碩士班)
Keywords:	糖尿病胰島素阻抗發炎因子鉛鎘砷 diabetes mellitus insulin resistance inflammation lead cadmium arsenic
Date:	2014
Issue Date:	2015-11-06 16:10:38 (UTC+8)
Abstract:	研究目的： 1、探討重金屬與糖尿病的關係 2、探討慢性低度發炎於重金屬與糖尿病致病機轉扮演的角色 3、建立日後世代研究的基礎資料材料與方法：本研究對象為過去檢查或自認沒有糖尿病史的民眾，邀請他們參與本研究計畫，並安排時間到醫院做葡萄糖耐受試驗與其他生化檢查及測量血中發炎指標，同時進行問卷訪視與採取血液、尿液、頭髮等檢體，預計採取的樣本數為500人。血液的生化檢查主要有葡萄糖耐性測試、高低密度膽固醇、胰島素、總膽固醇等，發炎因子測量補體、C-反應蛋白質、氧化壓力 (thiobarbituric acid reactive substances)等。重金屬鉛鎘砷的分析是使用感應耦合電漿質譜儀。統計分析方法：描述性的資料與生理特徵，連續變項以平均值與標準差表示，各組間的差異以變異數分析（ANOVA）、t-test與卡方檢定方法，檢定不同組間的差異。分析重金屬、發炎因子與糖尿病和胰島素阻抗間的關係以單變項與多變項邏輯式迴歸分析（univariate and multivariatelogistic regression）方法，估計體內重金屬各濃度範圍造成血糖異常的勝算比，並以Receiver-Operator curve 找出合理的重金屬暴露量。本研究將以 SPSS 套裝軟體進行分析，統計差異顯著水準(p value)為 5%。 OBJECTIVE –The purposes of this study are 1. to examine the correlation between heavy metal and type 2 diabetes 2. to explore the role of chronic low-grade inflammation in the mechanism of heavy metal resulting in type 2 diabetes 3. to establish the baseline characteristics before follow-up for cohort study RESEARCH DESIGN AND METHODS – A total 500 subjects without reported type 2 diabetes mellitus will be invited to participate in this study. All the individuals will receive physical examination for diagnosis of diabetes, and urine and scalp hair are collected for evaluating the level of toxic heavy metals simultaneously. Biochemical characteristic will be measured including oral glucose tolerance test, TG, cholesterol, C3 complement, high sensitivity c-reactive protein (hsCRP) and oxidative stress (thiobarbituric acid reactive substances). Lead, cadmium and arsenic are measured by inductively coupled plasma mass spectrometry. Statistical Analysis - Descriptive data will be described as means and SDs for continuous variables, and analysis of variance (ANOVA) and Chi-square tests are used for assessing the significances. Bonferroni method is used for post-hoc comparison in ANOVA. Odds ratios and the 95% confidence interval are calculated to estimate the relative risk of diabetes mellitus by logistic regression model. The optimal cutoff of heavy metal exposure is suggested by Receiver-Operator curve. A p-value below 0.05 is considered significant. The statistical analyses are performed with SPSS statistical Package.
Relation:	計畫編號：MOST103-2314-B041-001 計畫年度：103；起迄日期：2014-08-01~2015-07-31
Appears in Collections:	[Dept. of Occupational Safety] MOST Project

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