廖中明Liao, Chung-Min臺灣大學:生物環境系統工程學研究所林姿伶Lin, Tzu-LingTzu-LingLin2010-05-052018-06-292010-05-052018-06-292008U0001-2706200816372200http://ntur.lib.ntu.edu.tw//handle/246246/181129本研究主要目的為預測及評估孩童因暴露於含砷飲用水而誘導皮膚損害之險，並探討18 歲以下孩童各年齡層之飲用水安全含砷量。皮膚損害之色素沉症 (Hyperpigmentation) 及角化症 (Keratosis) 與慢性砷暴露有著密不可分之係。本研究以印度西孟加拉 (West Bengal, India) 砷流行疫區之流行病學調查料為基礎，利用韋伯 (Weibull) 模式建立砷暴露劑量、年齡及孩童皮膚損害效之關係，評估孩童飲用水安全含砷量，再結合以生理為基礎之藥理動力學Physiologically Based Pharmacokinetic, PBPK) 模式模擬孩童不同生理狀況及代機制，以探討飲水量變異所造成體內濃度之變化。生命階段之PBPK 模式描述童對主要代謝物種砷As(III)、As(V)、MMA(III)、MMA(V)、DMA(III) 及DMA(V)吸收、分佈、代謝及排除，並評估孩童體內各器官物種砷濃度之動態變化。本究利用勝算比 (Odds Ratio, OR) 推估孩童暴露於砷所造成皮膚損害之不利健效應之相對危險性大小，主要利用PBPK 模式模擬暴露組及控制組孩童尿液中MA(III) 之濃度，結合韋伯模式模擬不同年齡及不同砷濃度之盛行率，計算暴amp;#63800;組及控制組累積盛行率之比值。結果顯示，砷暴露濃度與皮膚損害之累積盛行amp;#63841;呈正相關 (R2=0.91−0.96)，因男性皮膚損害最為嚴重，故以男性皮膚損害為基，並設其最高可接受風險為10-3，可得0−6 歲男性及女性之飲用水安全含砷量別為2.2 及6 μg/L，而7−18 歲男性及女性則分別為1 及2.8 μg/L。本研究以勝比 (95%信賴區間) 評估印度西孟加拉、孟加拉以及台灣西南部之平均飲用水濃度分別為283.19、282.65 及468.61 μg/L 時，18 歲以下孩童之OR 分別為.38−5.20、2.03−20.97 及3.50−21.10。本研究建議尿液MMA(III) 濃度之增加與誘導孩童皮膚損害風險之增加有關。本論文提供環境風險管理之架構並整合流amp;#64008;病學做為政府訂定規範之建議。The purpose of this study was to predict and assess the arsenic-related children skin lesions risk from drinking water and estimate the safe drinking water arsenic standard below 18 years old children. Chronic arsenic exposure and skin lesions (such as hyperpigmentation and keratosis) are inextricably linked. We established the relationship among arsenic exposure dose, age and effects of children skin lesions with Weibull model based on arsenic epidemiological data in West Bengal, India. We assessed the safe drinking water arsenic standard for children with Weibull model and linked Physiologically Based Pharmacokinetic (PBPK) model to estimate children organ-specific arsenic concentrations varied with methylating activity and drinking water consumption rates. This study present an integrated approach by using Weibull model-based framework on the basis of gender/age-specific epidemiological data on arsenic exposure, skin lesions prevalence, and using PBPK model to predict monomethylarsonous acid (MMA(III)) levels in urine to estimate the likelihood risk obtained from studies conducted in arseiasis-endemic in West Bengal, India. A life-stage PBPK model is used to describe the absorption, distribution, metabolism, and excretion of the metabolites: arsenate (As(V)), arsenite (As(III)), monomethylarsonic acid (MMA(V)), monomethylarsonous acid (MMA(III)), dimethylarsinic acid (DMA(V)), and dimethylarsinous acid (DMA(III)) in target tissue groups, considering the potential impact by physiologically life-stage differences. We calculated odds ratio (OR) to assess the relative magnitude of the effect of the arsenic exposure on the likelihood of the prevalence of children skin lesions. The results show that arsenic exposure dose, age and cumulative prevalence ratio of the hyperpigmentation and keratosis are correlated significantly (R2=0.91-0.96). On the other hands, arsenic exposure dose raised followed cumulative prevalence ratio. The safe arsenic drinking water standards were estimated to be 2.2, 6 respectively for 0-6 years males and females as well as 1, and 2.8 μg/L respectively for 7-18 years males and females based on the index skin lesions of male hyperpigmentation with cumulative prevalence ratio equals 10-3. Risk predictions indicate that estimated ORs have 95% confidence intervals of 1.83−5.20, 2.03−20.97,nd 3.50−21.10 based on mean drinking water arsenic concentrations of 283.65,82.65, and 468.81 μg/L, respectively, in West Bengal, Bangladesh, and southwesternaiwan. Our finding also suggests that increasing urinary MMA(III) levels aressociated with an increase in risks of arsenic-induced children skin lesions. Thistudy offers an environmental risk management framework to suggest regulations anddministrating process by linking arsenic epidemiological data.中文摘要 I文摘要 II錄 IV目錄 VII目錄 VIII號說明 XI、前言 1amp;#36014;、動機與目的 3 2.1 研究動機 3 2.2 研究目的 4、文獻回顧 5 3.1 砷的代謝與毒性 5 3.1.1 砷的物化性質 5 3.1.2 砷的代謝 7 3.1.3 砷的毒性 10 3.2 含砷飲用水之流行病學資料 11 3.2.1 印度西孟加拉含砷飲用水之流行病學調查 11 3.2.2 孟加拉含砷飲用水之流行病學調查 12 3.2.3 台灣含砷飲用水之流行病學調查 13 3.3 以生理為基礎之藥理動力學模式 15 3.3.1 生理為基礎之藥理動力學之概念 15 3.3.2 砷暴露之生理為基礎之藥理動力學模式 18 3.4 劑量反應模式 20 3.4.1 常用劑量反應模式類型 20 3.4.2 韋伯分佈模式 21 3.5 風險評估 25 3.5.1 風險評估之架構 25 3.5.2 風險特性化之勝算比 28 3.5.3 風險分析之變異性與不確定性 29、材料與方法 31 4.1 研究架構及地區 31 4.2 研究區域流行病學資料分析 33 4.2.1 印度西孟加拉砷流行疫區砷危害之研究 33 4.2.2 砷暴露健康指標分析 33 4.3 孩童之生理為基礎之藥理動力學模式 35 4.3.1 動力學基本公式 35 4.3.2 生理為基礎之藥理動力學模式之建立 36 4.3.3 考量生命階段生理為基礎之藥理動力學模式 51 4.4 韋伯劑量反應模式 53 4.5 勝算比 55 4.6 不確定分析 56、結果 58 5.1 韋伯模式之擬合 58 5.2 孩童器官之砷濃度動態 63 5.2.1 孩童長期暴露之體內砷濃度與時間關係 63 5.2.2 飲水量變異分析 70 5.2.3 生理階段變異分析 70 5.3 韋伯模式為基礎之飲用水安全含砷量 75 5.4 孩童皮膚損害之風險 77、討論 80 6.1 皮膚損害之韋伯-生理為基礎之藥理動力學模式 80 6.2 孩童皮膚損害之砷安全指標 85 6.3 應用 88、結論 89、未來研究建議 92考文獻 94錄A：PBPK模式各區塊中砷之吸收、排除與代謝方程式 108錄B：皮膚損害人數與盛行率 113application/pdf1420380 bytesapplication/pdfen-US砷暴露孩童皮膚損害甲基化韋伯模式藥理動力學風險評估印度西孟加拉Arsenic ExposureChildrenSkin lesionsMethylation CapacityWeibullPBPKRisk assessmentWest Bengal (India)[SDGs]SDG6thesishttp://ntur.lib.ntu.edu.tw/bitstream/246246/181129/1/ntu-97-R95622018-1.pdf