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研究生：	黃志偉 Huang, Jhih-Wei
論文名稱：	柬埔寨居民砷暴露與高血糖症之相關性評估 Association between arsenic exposure and hyperglycemia in Cambodia
指導教授：	郭浩然 Guo, How-Ran
學位類別：	碩士 Master
系所名稱：	醫學院 - 環境醫學研究所 Department of Environmental and Occupational Health
論文出版年：	2013
畢業學年度：	101
語文別：	英文
論文頁數：	72
中文關鍵詞：	砷、地下水、暴露評估、高血糖症、柬埔寨
外文關鍵詞：	arsenic, groundwater, exposure assessment, hyperglycemia, Cambodia
相關次數：	點閱：81 下載：1
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背景: 砷廣泛分佈於自然界，主要以水體在環境中遷移。暴露高濃度的砷，已被認定為人類致癌物。砷通常存在於深層地下水層，並在許多國家都有發現高濃度的地下水含砷量，其中包括阿根廷，孟加拉國，印度，巴基斯坦，墨西哥，德國，泰國，中國，智利，美國，加拿大，匈牙利，羅馬尼亞，越南，尼泊爾，緬甸和柬埔寨。過去在台灣研究發現砷在飲用水中的濃度與糖尿病之間存在著關聯，但是目前在其他國家的研究則結果不一；柬埔寨並未有相關方面的文獻探討，尤其是柬埔寨是一個非西方飲食習慣的國家，傳統糖尿病危險因子的盛行率應該較低，對研究結果的影響較少。因此，本研究的目的在於評估柬埔寨居民透過飲用水的砷暴露與高血糖症之間的相關性，並對過去的相關文獻進行統合分析以驗證結果。
方法: 我們針對柬埔寨Kandal, Preak Russy居民收集井水以及尿液樣本來評估個人砷暴露量，並採用問卷調查獲取基本人口學、飲食習慣以及過去病史等資料，另以手指血糖測試儀器測試空腹指尖血糖濃度篩檢高血糖症的病人，之後進行糖化血色素的檢測以確診。砷暴露的指標包含井水總砷濃度、尿液中總砷濃度以及砷中毒皮膚徵兆。我們以邏輯斯回歸評估飲用水砷暴露與高血糖症的相關性，並且考量潛在的干擾因子例如性別、年齡進行校正。此外，我們以MIX 2.0對過去針對砷暴露與糖尿病之間相關性的流行病學研究資料進行統合分析來驗證本研究的發現。
結果:參加調查的142 位受試者包括43 位男性以及99 女性，平均年齡為40.4（±18.8）歲，尿液中以及井水中的總砷濃度中位數分別為52.03 微克/升和907.25 微克/升。尿液中總砷對高血糖之間的勝算比為0.86（95％CI：0.29-2.51），暴露到高於井水總砷濃度中位數（907.25μg/L）的受試者得到高血糖症的機會為暴露濃度較低的受試者的1.91 倍（95％CI:0.57-6.31）。校正年齡與BMI 後，砷中毒皮膚徵兆與高血糖症之間的暴露勝算比為1.19（95％CI：0.33-4.31）。利用統合分析將過流行病學研究與本篇研究做比較得到一個統合值RR=1.64 (95%CI 1.34-2.12)，發現在砷暴露以及高血糖症之間有相關性。
結論: 綜合統合分析與柬埔寨實地調查結果，本研究發現飲水砷暴露與高血糖症有關；然而由於參與實地調查的個案數太少，導致研究結果未達統計顯著意義。

Background: Arsenic is widely distributed in the nature and mainly transported in the environment by water. Arsenic exposure at high levels has been characterized as a human carcinogen. Arsenic usually exists in groundwater, and high concentrations have been observed in many countries, including Argentina, Bangladesh, India, Pakistan, Mexico, Germany, Thailand, China, Chile, the USA, Canada, Hungary, Romania, Vietnam, Nepal, Myanmar, and Cambodia. Studies in Taiwan found associations between arsenic exposure from drinking water and diabetes mellitus (DM), but studies in other countries yielded inconsistent results. Because Cambodians have non-Western style diets, data on the association are less affected by traditional risk factors for DM, but such data are limited. Therefore, this study aims to evaluate the association between arsenic exposure and DM through a field study in Preak Russey Village of Kandal in Cambodia and a meta-analysis of related literature.
Methods: We collected well water and urine samples to assess arsenic exposure and used questionnaires interview to obtain data including those on demographics, diet, historical exposure, and disease. We performed a fingertip blood glucose test and then measured hemoglobin A1c when test was positive for hyperglycemia to confirm the existence of DM. We also examined the participants for skin lesions of arsenicosis. Logistic regression was applied to evaluate the relationship between arsenic exposure and DM after adjusting for potential confounders such as demographic factors. MIX 2.0 was used to conduct meta-analyses on results from previous epidemiology studies to verify our findings.
Results: The 142 participants included 43 men and 99 women, with an average age of 40.4 (standard deviation 18.8) years. The median levels of total arsenic in the urine and well water were 52.03 μg/L and 907.25 μg/L. The odds ratio (OR) associated with a urine arsenic level above the median for DM was 0.86 (95% confidence interval [CI]: 0.29-2.51). People exposed to well water arsenic levels greater than the median had an OR of 1.91 (95% CI: 0.57-6.31). The OR associated with arsenicosis for DM was 1.19 (95% CI: 0.33-4.31) after adjustment for age, body mass index (BMI). The meta-analyses yielded an association between arsenic exposure and DM with an ln RR 1.64 (95%CI 1.34-2.12).
Conclusion: We found an association between arsenic exposure and DM in the meta-analysis and our field study. However, the association in the field study did not reach statistical significance most likely because the small sample size.

Table of contents
摘要	i
Abstract	iii
Acknowledgement	v
Table of contents	vi
List of tables	ix
List of figures	x
Chapter 1 Introduction	1
1.	Background	1
2.	Objective	3
Chapter 2 Literature review	4
1.	Characteristic of arsenic	4
2.	Exposure route and metabolism of arsenic	5
3.	Health impact of arsenic	5
4.	Black foot disease	6
5.	Cancers	6
6.	Hyperglycemia	7
7.	Possible mechanism of arsenic effect on glucose circulation	8
8.	Studies in Cambodia	9
9.	Sample size estimation	10
Chapter 3 Materials and methods	11
1.	Study design and structure.	11
2.	Source of participants and selection criteria	12
2.1	Study area	12
2.2	Study population	12
2.3	Questionnaire	13
3.	Individual arsenic exposure	13
4.	Arsenic levels analysis	14
5.	Urine sample collection	15
6.	Urine samples analyzing	15
7.	Arsenic levels in well water estimation	15
8.	Definition of hyperglycemia	15
9.	References searching for meta-analysis	16
10.	Reference inclusion criteria and exclusion criteria	17
11.	Statistical analysis	17
Chapter 4 Results	18
1.	Demographical characteristics	18
2.	Association between urine arsenic levels and hyperglycemia	18
3.	Association between arsenicosis and hyperglycemia	19
4.	Association between arsenic levels in well water and hyperglycemia	19
5.	Meta-analysis	20
5.1	Total literature of arsenic and DM	20
5.2	Association between arsenic exposure and DM through Inhalation	20
5.3	Association between arsenic exposure and DM through Ingestion	20
5.4	Literature of arsenic and DM through ingestion with confirmed DM diagnosis	21
5.5	Dose-response meta-analysis	21
Chapter 5 Discussions	22
1.	Representative of population	22
2.	Association between arsenic levels in urine and hyperglycemia	22
3.	Association between arsenic levels in well water and hyperglycemia	23
4.	Representative of arsenicosis as an exposure indicator	23
5.	Hyperglycemia definition comparing with recent epidemiology studies	24
6.	Lack of seafood consumption	25
7.	Study limitations	25
Chapter 6 Conclusions	27
References	28

List of tables
Table 1 Demographical data between hyperglycemia cases group and reference group	38
Table 2 Demographic characteristics between two groups of arsenic levels of urine in village Preak Russey	39
Table 3 Association of urine arsenic levels with hyperglycemia	40
Table 4 Demographic characteristics among arsenicosis participants	41
Table 5 Association of arsenicosis with hyperglycemia	42
Table 6 Demographic characteristics between two groups of arsenic levels of well water in Preak Russey village	43
Table 7 Association of arsenic levels of well water with hyperglycemia	44
Table 8 Studies of dose-response analysis	45
Table 9 Average of participants’ age and living period	46
Table 10 Characteristics of some recent epidemiological studies investigating the association between arsenic (As) detected in drinking water and in different biological samples (B: blood; S: serum; H: hair; N: nails), and urinary As-biomarkers (U: urines).	47
Table 11 Association between arsenicosis and arsenic levels in well water	51
Table 12 Diabetes mellitus (DM) definitions of some recent epidemiological studies investigating the association between arsenic and DM	52
 
List of figures
Figure 1 Oxidative methylation of arsenic	54
Figure 2 Black—foot disease	55
Figure 3 Possible mechanism of arsenic-induced diabetes mellitus	56
Figure 4 Sample size estimation curve	57
Figure 5 Study design and structure	58
Figure 6 Cambodia and neighboring countries	59
Figure 7 Provinces in Cambodia	60
Figure 8 Meta-analysis references searching protocol	61
Figure 9 Forest plot of random effects meta-analysis of studies examining the effect of arsenic exposure and DM	62
Figure 10 Forest plot of random effects meta-analysis of studies examining the effect of arsenic exposure and DM (combine with this study)	63
Figure 11 Forest plot of random effects meta-analysis of studies examining the effect of arsenic exposure and DM through inhalation	64
Figure 12 Forest plot of random effects meta-analysis of studies examining the effect of arsenic exposure and DM through ingestion	65
Figure 13 Forest plot of random effects meta-analysis of studies examining the effect of arsenic exposure and DM through ingestion (combine with this study)	66
Figure 14 Forest plot of random effects meta-analysis of studies examining the effect of arsenic exposure and DM through ingestion with confirmed DM diagnosis	67
Figure 15 Forest plot of random effects meta-analysis of studies examining the effect of arsenic exposure and DM through ingestion with confirmed DM diagnosis (combined with this study)	68
Figure 16 Forest plot of random effects meta-analysis of dose-response analysis relation between arsenic exposure and DM	69
Figure 17 Source of inorganic and organic arsenic	70
Figure 18 Burden of disease estimation of Ministry of Health of Cambodia	71
Figure 19 Disease information of Ministry of Health of Cambodia	72




                                    

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