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研究生:黃雪倫
研究生(外文):Sharon Ng
論文名稱:一、都市垃圾焚化爐是否和學童注意力缺乏/過動症有關?--三座焚化廠周邊地區十二所國小流行病學研究;二、汞、APOE4與嬰兒生長及神經行為--台北出生世代研究
論文名稱(外文):1.Do Municipal Waste Incinerators associate with attention deficit and hyperactive disorder in children? -- An Epidemiological Study of 12 Primary Schools in the Vicinity of Three Municipal Waste Incinerators;2.Mercury, genetic polymorphism and child hea
指導教授:陳保中陳保中引用關係
指導教授(外文):Pau-Chung Chen
學位類別:碩士
校院名稱:國立臺灣大學
系所名稱:職業醫學與工業衛生研究所
學門:醫藥衛生學門
學類:公共衛生學類
論文出版年:2006
畢業學年度:94
語文別:英文
論文頁數:87
中文關鍵詞:兒童注意力/缺乏過動證焚化爐戴奧辛兒童神經行為發展基因多型性出生結果神經行為發展
外文關鍵詞:Child neurodevelopmentdioxinsprenatal exposureearly postnatal exposureADHDgenetic polymorphismcord blood mercuryfish consumptionbirth outcomeneurobehavioral development
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一、
我們的研究目的是探討焚化爐的空氣污染與兒童注意力不足過動症之關係。研究設計為橫斷式暴露對照研究,以台灣某地區的三座都市垃圾焚化爐周邊居民為研究對象,選擇距離三座焚化廠兩公里內的國小做為暴露族群,距離焚化廠三公里以上的國小作為對照族群,回收的有效問卷為92%。在兩組的人口結構方面,此為兩個同質性很高之兩個族群。在兒童過動症方面的測量,測量工具為兒童活動量表,cut off score採用常模值之P90為劃分點,篩選出10%疑似過動症的學童。統計分析的部份,利用卡方檢定,結果顯示暴露組與對照組之盛行率達到統計上的顯著差異,OR=1.43,95%CI為1.02, 2.01。另外,以二元邏輯式回歸分析方法分析,在控制了母親之教育程度、暴露二手煙、拜香、性別、年齡、母親的生育年齡後發現,除了空氣污染之外,性別、年齡和暴露二手煙與兒童之過動症的行為表現亦達到統計上之顯著差異。

二、
近年來,在許多的流行病學研究中發現,除了暴露物質的濃度,劑量之外,不同的基因多型性在暴露到疾病的發生之過程中扮演著關鍵的角色,尤其是低濃度的長期暴露。針對在環境中低濃度的金屬暴露下,基因易感受性族群尤其是懷孕中的婦女和其胎兒的成長發育和神經行為發展的研究仍然缺乏。本篇的研究目的是探討懷孕期間汞的暴露以及在不同的APOE4基因多型性之下對於兒童健康和神經行為發展的影響。

本研究族群為2004年9月到2005年1月在台北一間醫學中心,一間地區醫院和兩間診所所生產之孕婦及其嬰兒,共347對。暴露評估+透過收集孕婦生產時之血液、尿液及嬰兒之臍帶血。並且在嬰兒六個月時進行家訪追蹤兒童的成長與神經行為發展的評量,所使用的問卷為由台灣本土發展之嬰幼兒綜合發展測驗。
我們預期懷孕期間的金屬暴露和教養環境評估(HOME)對於嬰兒的神經行為的表現(NNE,CDIIT)會有些微的影響。加上基因多型性的考量,希望更能釐清懷孕期間的金屬暴露對於兒童的成長發育和神經行為的影響。

我們發現嬰兒的tone and motor表現隨著臍帶血的濃度增加而降低。針對臍帶血的汞濃度和兒童的神經行為的發展的部分,礙於研究設計的限制暫時無法解釋。汞的暴露和兒童神經行為的表現之關係,需要更多的研究來證實。
1.
The aim of our study is to investigate the relationship between municipal waste incinerators (MWIs) and attention deficit hyperactivity disorder (ADHD) among children in primary schools.
Materials and Methods: This was a cross-sectional study in design. Three municipal waste incinerators in Taipei, Taiwan, were selected. We chose two primary schools within two km from each incinerator as the exposure group, and two primary schools at a distance of at least two km from the incinerator as the reference group. We performed air sampling for dioxins, PM10, PM2.5, PM1, cadmium, and chromium in May and August 2003 for each school. We chose a class from each grade randomly (1 class × 6 grades × 4 schools × 3 incinerators), 1,948 children, performed the questionnaire survey including the Werry-Weiss-Peters Activity Scale as a screening tool for ADHD. Finally, we compared the prevalence of ADHD between the exposure and reference groups and employed multiple logistic regression models to calculate adjusted odds ratios and 95% confidence intervals.
Results: The ranges of dioxins were 0.011-0.317 and 0.016-0.046 pg-TEQ (I-TEF)/m3 for the exposure and reference groups, respectively. The prevalence rates of ADHD were 13.4% and 9.2% for the exposure and reference groups, respectively. The prenatal and / or early postnatal exposure was seen as critical related to AHDH performance among the students. After controlling for age, gender, exposure to environmental tobacco smoke (ETS), injury experience, MWIs sites, and maternal education and pregnant age, the exposure group had a higher risk (adjusted odds ratio, OR=1.43; 95% confidence interval, 95% CI: 1.02, 2.01) than the reference group. Prenatal and /or early postnatal (before 1 year old), exposure also had a higher risk (adjusted odds ratio, OR=1.87; 95% confidence interval, 95% CI: 1.2, 2.88).
Discussion and conclusions: Emissions from municipal waste incinerators might have a slightly adverse effect on children, increasing ADHD performance. However, the role of exposure misclassification and chance should also be considered. A prospective longitudinal study is warranted to elucidate the relation between emissions from incinerators and specific aspects of child health.

2.
The genetic polymorphism may play an important role to modulate the health effects, as well as people who are genetic susceptible will poor response to eliminate potential hazard even in low level exposure. In this study we focused on prenatal mercury (Hg) exposure and its related genetic polymorphism Apolipoprotein E (Apo E) to investigate the genetic and environmental interaction on child health. We aimed to explore the influence of gene polymorphism on Hg exposure child health especially on neurobehavioral development.
A total 347 infant-mother pairs, delivery during April 2004 and January 2005 will be recruited. We also collected maternal blood, cord blood and urine specimens at the time delivery. We employed ICP-MS to detect cord blood and maternal blood mercury level, and applied PCR-RFLP to analysis Apolipoprotein genotype.
Participants were asked to complete a questionnaire and invited their infant to have neonatal neurobehavioral examine. At aged 6 months and applied Comprehensive Developmental Inventory for Infants and Toddlers(CDIIT)as tool to implement the evaluation on infants physical growth and neurodevelopment. By the way, we also carried out the Home Observation for Measurement of the Environment (HOME).
Result: The cord blood concentration was significant associated with the item of tone and motor of NNE, but not associate with adverse effect on fetus growth or 6 months neurodevelopment outcome. Although at the part of CDIIT, we found almost positive association with cord blood mercury level, it might be due to the social economic status and beneficial of oceanic fish consumption or breastfeeding. There is no adversely association with
Do Municipal Waste Incinerators associate with attention deficit and hyperactive disorder in children? 2
Chinese abstract 3
Abstract 4
Introduction 9
Materials and methods 11
Study designs …..11
Study subjects 11
Exposure measurement 12
Dioxins 12
Heavy metals 13
Measurement and definition Attention deficit and hyperactivity disorder 13
Statistical analysis 14
Results 16
Discussion 18
Conclusions 23
Reference 24
Appendix 28
Questionnaire: 36
Part 1 Social demography and health survey 36
Part 2: Werry-Weiss Peters Activity scale 39
Standard operation process of dioxins analysis 41

List of tables
Table 1 Concentration of dioxins and metals between exposure and reference group. 28
Table 2 Comparison of Students Characteristics between exposure and reference group 29
Table 3 Comparison maternal characteristics and other environmental exposure of study population 30
Table 4. Relationship between time of exposure in children and risk of ADHD 31
Table 5 Odd ration and 95% confidence intervals of univariate and multivariate binary logistic regression 32
Table 6 International ambient air dioxins 33


List of figures
Figure 1. Location of the three municipal waste incinerators in the study and also long with their exposure group and reference group 35


Mercury, APOE4, and infant growth and neurobehavioral development 52
Chinese abstract 53
Abstract 54
Introduction 58
Mercury, fish consumption and child health 59
Apolipoprotein E polymorphism 59
Material and method 62
Study design 62
Study population 62
Exposure measurement 63
Biological specimen analysis 63
Heavy metal analysis 63
Single Nucleotide Polymorphism (SNP) analysis 64
Questionnaire 65
Home Observation for Measurement of the Environment (HOME) 66
Outcome measurements 67
Fetal growth 67
Neonatal neurobehavioral and development (NNE) 67
Comprehensive Developmental Inventory for Infants and Toddlers (CDIIT) 67
Statistical analysis 69
Results 71
Discussion 73
Conclusion 77
Reference: 78

List of tables :
Table 1 Demographic characteristic and potential confounder of three different cord blood levels. 81
Table 2 Compare the maternal and social demographic characteristic of three different cord blood levels. 82
Table 3 Compare the neurobehavioral performance of participant with three different cord blood levels. 83
Table 4 Compare the neurobehavioral performance and parenting environments of participant on 6th month, CDIIT and HOME scale, in three different cord blood levels. 84
Table 5 Estimate the relation of fetal growth and log-transformed cord blood mercury level, APOE genotype and adjusted with potential cofounder in linear regression model 85
Table 6 Estimate the relation of neurobehavioral development outcome – part of NNE and log-transformed cord blood mercury level, APOE genotype and adjusted with potential cofounder in linear regression model 86
Table 7 Estimate the relation of neurobehavioral development outcome – part of CDIIT and log-transformed cord blood mercury level, APOE genotype and adjusted with potential cofounder in linear regression model 87
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