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研究生:吳亭亭
研究生(外文):Ting-Ting Wu
論文名稱:短期臭氧暴露與全死因、糖尿病、心血管疾病死亡之關係
論文名稱(外文):Association of Short-term Ozone Exposure with Total, Diabetes, and Cardiovascular Diseases Mortalities
指導教授:鄭尊仁鄭尊仁引用關係
指導教授(外文):Tsun-Jen Cheng
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:2010
畢業學年度:98
語文別:英文
論文頁數:53
中文關鍵詞:糖尿病心血管疾病死亡臭氧
外文關鍵詞:diabetescardiovascular diseasemortalityozone
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在流行病學研究上已有文獻指出臭氧暴露與呼吸道及心血管疾病死亡具有相關性,然而在臭氧暴露與糖尿病死亡的關係上,尚未有一致的研究結果。本研究目的為探討大氣臭氧暴露對全死因、心血管疾病與糖尿病死亡之危險性。
本研究使用2006至2008年衛生署死亡資料庫,選取戶籍位於大台北地區(全台北市與部分台北縣鄉鎮市)死亡年齡高於五十歲之糖尿病死亡(ICD9, 250)個案(共5,767個案數)為研究對象,分析糖尿病死亡與臭氧暴露之危險性。全死因與心血管疾病死亡個案(ICD9, 390- 459)根據糖尿病死亡個案之年齡與性別分別以1:2之比例亂數選出(各11,543個案數),分析大氣臭氧暴露對全死因與心血管疾病死亡之危險性,進一步比較臭氧暴露對不同的疾病死亡風險。環境資料使用臺灣環保署環境監測站空氣品質監測網提供之量測數據,利用大台北地區之15個監測站之日平均量測值為死亡個案之暴露濃度。除了日平均值的計算,臭氧最大八小時值亦納入分析。在暴露評估模式上,以1天至7天的臭氧濃度移動平均值,以及1天至7天的單日延遲臭氧濃度代表不同的累積暴露情形。在此研究中,使用病例交叉研究設計,以死亡為健康效應,並定義危害期於死亡當天至前六天(共七個危害期),對照期為危害期前一、二、三、四週相對應之日期做選擇,分析大氣臭氧暴露對死亡造成之風險。在統計模式中,控制溫度、濕度、懸浮微粒(PM2.5與PM10)等影響因子。
本研究發現糖尿病在臭氧暴露下有顯著死亡風險,以24小時臭氧移動平均值模式並控制溫度、濕度、PM2.5(或PM10)等影響因子下,臭氧暴露對全死因、心血管疾病死亡與糖尿病死亡有累積效應情況。男性與性別50- 65歲糖尿病個案有顯著死亡風險。在利用最大八小時臭氧濃度值做分析時,亦發現有相似的結果。與全死因及心血管死亡相比,暴露於大氣臭氧下,糖尿病沒有較高的死亡風險。因本研究使用死亡資料庫提供之原死因為個案篩選條件,故糖尿病死亡個案確切死因在未來研究中應該要再釐清以利分析。


Background: Associations between ozone exposure and mortality have been reported, particularly in respiratory and cardiovascular diseases (CVD). However, the relationship between ozone (O3) exposure and diabetes mellitus (DM) mortality remains unclear.
Objective: To compare the relationships between ozone exposure with total mortality and those caused by CVD and DM.
Method: DM deaths (International ICD-9, 250; N=5,767) more than 50 years of age from National Mortality Registry in metropolitan Taipei, Taiwan between 2006 and 2008 were included for analysis. For comparison, total death and CVD deaths (ICD-9, 390- 459, N=11534) were chosen by match with gender and age with DM deaths. Average levels of ozone each day were calculated from 15 monitoring stations of Taiwan EPA in this area; daily maximum 8-hour concentrations of ozone were computed as well. Case-crossover design was applied to examine the risk between the hazard and reference periods while daily moving average from 0-day (the day of death) to 7-day was used and 4 reference days were chosen by every 7 days before the day of death for 1 month. Temperature and relative humidity were included in the single pollutant model, and PM10 or PM2.5 was further adjusted in two-pollutant model.
Results: In two-pollutant model with PM2.5 adjusted, the trend of accumulative effect of ozone was observed in total death, CVD and DM deaths. Diabetics (OR=1.11, 1.03-1.19) , total death (OR), and CVD (OR=1.10, 1.04-1.16) were at risk for deaths in an interquartile range increase of ozone (11.6 ppb) within 7 days exposure. Similar results were also obtained with maximum 8-hour ozone exposure. However, the risk of diabetes deaths from ozone exposure was not higher than those of total deaths and CVD deaths. In this study, either PM10 or PM2.5 was not associated with ozone exposure. Conclusion: Increased ozone exposure is associated with mortality in total deaths, DM and CVD deaths. However, diabetics were not at higher risk with exposure to ozone. Because the underlying causes of death from diabetes are not available from the National Mortality Registry, specific causes of death from diabetes need to be specified in the future study.


摘要 i
Abstract iii
Table Contents vi
Figure Contents vii
Chapter 1 Background and Objective 1
Chapter 2 Literature review 3
2.1 Air pollution and health 3
2.1.1 PM exposure and Health 3
2.1.2 O3 exposure and health 4
2.1.3 Air pollution and susceptible groups 10
2.2 Diabetes mellitus 10
2.3 National Mortality Registry 10
2.4 Case-crossover study design 11
Chapter 3 Material and Method 13
3.1 Health data 13
3.2 Environmental data 13
3.3 Statistical analysis 14
Chapter 4 Results 17
Chapter 5 Discussions 19
5.1 Ozone exposure and human health 19
5.2 Ozone exposure metrics 20
5.2.1 Daily average and maximum 8-hour means of O3 level 20
5.2.2 Moving average and single-lag models 20
5.3 Total, CVD, and DM mortalities 21
5.4 Gender and age differences 21
5.5 The National Mortality Registry data 22
Chapter 6 Conclusions and Recommendations 23
Chapter 7 References 24

Table Contents

Table 1 Literature Reviews of Positive Associations between O3 Exposure and Health Effects 6
Table 2Literature Reviews of Negative Associations between O3 Exposure and Health Effects 8
Table 3. Demographic Distribution of Total, CVD, and DM Death in Taipei, 2006- 2008 31
Table 4. Distribution of Air Pollutants in Taipei between 2006 and 2008 32
Table 5. Correlation Coefficients among Different Pollutants in Taipei, 2006- 2008 33


Figure Contents
Figure 1. The flowchart of the present study design. 16
Figure 2. The positions of monitoring stations and selected areas in Taiwan 34
Figure 3. The selection of risk and reference periods in the moving average model 35
Figure 4. OR of each IQR increase among DM deaths in the moving average model. 36
Figure 5. OR of each IQR increase among DM deaths in the moving average models with daily O3 concentrations. 37
Figure 6. OR of each IQR increase among DM deaths in the moving average models with maximum 8-hour O3 concentrations. 38
Figure 7. OR of each IQR increase among DM deaths in the single-lag model with daily O3 concentrations. 39
Figure 8. OR of each IQR increase among DM deaths in the single-lag model with maximum 8-hour O3 concentrations. 40
Figure 9. OR of each IQR increase among DM deaths in the moving average model by different genders with daily O3 concentrations. 41
Figure 10. OR of each IQR increase among DM deaths in the moving average model by different genders with maximum 8-hour O3 concentrations. 42
Figure 11. OR of each IQR increase among DM deaths in the single-lag model by different genders with daily O3 concentrations. 43
Figure 12. OR of each IQR increase among DM deaths in the single-lag model by different genders with maximum O3 concentrations. 44
Figure 13. OR of each IQR increase among DM deaths in the moving average model by different age groups with daily O3 concentrations. 45
Figure 14. OR of each IQR increase among DM deaths in the moving average model by different age groups with maximum 8-hour O3 concentrations. 46
Figure 15. OR of each IQR increase among DM deaths in the single-lag model by different age groups with daily O3 concentrations. 47
Figure 16. OR of each IQR increase among DM deaths in the single-lag model by different age groups with maximum O3 concentrations. 48
Figure 17. OR of each IQR increase in the moving average model for total, CVD, and DM deaths with daily O3 concentrations. 49
Figure 18. OR of each IQR increase in the moving average model for total, CVD, and DM deaths in different genders with daily O3 concentrations. 50
Figure 19. OR of each IQR increase in the moving average model for total, CVD, and DM deaths in different age groups with daily O3 concentrations. 51
Figure 20. The death certification in Taiwan 53


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