臺灣博碩士論文加值系統

背景：石化工業日益增長的需求和擴張造成了環境污染，而生活在石化生產區周邊的居民首當其衝。此外，居住地暴露於石化工業區對致癌風險的影響可能會因人口的變化而有所不同。為了評估居住地暴露於石化工業區對不同人口致癌風險的影響，本研究認為需要全面的可比數據。

目標：本研究旨在探討石化工業區附近的居民與致癌風險之間的關係，並估算在2020至2040年期間，居住地暴露於石化工業區對致癌風險的整體影響，以觀察健康效應之變化。

方法：本研究進行了系統性回顧和後設分析來考察石化工業區附近的居民與致癌風險之間的關係。本文採用隨機效果後設分析模式估算石化工業區附近的居民致癌的相對風險 (RR)，而族群可歸因分率 (PAF) 則用於量化居住地暴露於石化工業區對致癌風險的影響。癌症的 PAF 是根據五種人口分布情境 (即共享社會經濟路徑 [SSP]) 推算的。

結果：我們觀察到，與居住得較遠的居民相比，石化工業區附近的居民罹患膀胱癌、白血病、肝癌、肺癌、胰臟癌和前列腺癌的風險更高。以下數據顯示了在五種SSP情境下，居住地暴露於石化工業區對致癌風險的整體影響 (下文稱 PAF) 。 在SSP1，2020年的癌症PAF為0.471% (95%不確定區間 [UI] = -0.486–1.412) ，癌症死亡病例有19,104起 (95% UI = -19,724–57,313)；而2040年的癌症PAF為0.453% (95% UI = -0.589–1.476) ，癌症死亡病例有28,097起 (95% UI = -36,548–91,633)。在SSP2，2020年的癌症PAF為0.470% (95% UI = -0.496–1.421) ，死亡病例有19,083起 (95% UI = -20,127–57,661) ；而2040年的癌症PAF為 0.441% (95% UI = -0.586–1.45) ，死亡病例有27,366起 (95% UI = -36,379–90,042) 。在SSP3，2020年的癌症PAF為0.470% (95% UI = -0.486–1.411) ，死亡病例有19,081起 (95% UI =-19,729–57,272) ；而2040年的癌症PAF為 0.426% (95% UI = -0.569–1.405) ，死亡病例有26,476起 (95% UI = -35,317–87,230) 。在SSP4，2020年的癌症PAF為0.471% (95% UI = -0.486–1.412)，死亡病例有19,098起 (95% UI = -19,724–57,303)；而2040年的癌症PAF為 0.450% (95% UI = -0.582–1.465)，死亡病例有27,922起 (95% UI = -36,162–90,928)。在SSP5，2020年的癌症PAF為0.471% (95% UI = -0.486–1.412)，死亡病例有19,100起 (95% UI = -19,723–57,306)；而2040年的癌症PAF為 0.455% (95% UI = -0.586–1.479)，死亡病例有28,280起 (95% UI = -36,365–91,830)。

結論：本研究表明，在2020至2040年期間，居住在石化工業區附近的居民死於癌症的人數增加了0.4%。我們的研究結果發現，生活在石化工業區附近的居民應得到更多關注，以儘量減少致癌的風險。

Background: The growing demand and expansion for petrochemical industry poses a threat of environmental pollution, which may particularly affect residents living near areas where they are manufactured. The impact of residential proximity to petrochemical industrial complexes on cancer risk may differ based on demographic shifts. For a comprehensive understanding, it’s essential to compare data on a global scale.

Objective: This study aims to determine the relationship between residents living near petrochemical industrial complexes and cancer risk, and to estimate the global impacts of such residential exposure to these complexes on cancer risk during 2020–2040 in order to observe the changes of health impacts.

Methods: We conducted a systematic review and meta-analysis to examine the association between residents living near petrochemical industrial complexes and cancer risk. A random-effects meta-analysis model was used to estimate the relative risk (RR) of cancer for these residents. Population attributable fraction (PAF) was used to quantify the impact of this residential exposure on cancer risk, based on five demographic scenarios (i.e., Shared Socioeconomic Pathways [SSPs]).

Results: We observed a higher risk of bladder, blood (leukemia), liver, lung, pancreatic, and prostate cancers among those living near the complexes compared to those who lived further away. The global impacts of residential exposures on cancer risks (PAFs, hereinafter) for five SSPs were presented in the following. In SSP1, PAFs of cancer were 0.471% (95% uncertainty interval [UI] = -0.486–1.412), with 19,104 cancer deaths (95% UI = -19,724–57,313) in 2020 and for 0.453% (95% UI = -0.589–1.476), with 28,097 cancer deaths (95% UI = -36,548–91,633) in 2040. In SSP2, PAFs of cancer were 0.470% (95% UI = -0.496–1.421), with 19,083 deaths (95% UI = -20,127–57,661) in 2020 and 0.441% (95% UI = -0.586–1.450), with 27,366 deaths (95% UI = -36,379–90,042) in 2040. In SSP3, PAFs of cancer were 0.470% (95% UI = -0.486–1.411), with 19,081 deaths (95% UI =-19,729–57,272) in 2020 and 0.426% (95% UI = -0.569–1.405), with 26,467 deaths (95% UI = -35,317–87,230) in 2040. In SSP4, PAFs of cancer were 0.471% (95% UI = -0.486–1.412), with 19,098 deaths (95% UI = -19,724–57,303) in 2020 and 0.450% (95% UI = -0.582–1.465), with 27,922 deaths (95% UI = -36,162–90,928) in 2040. In SSP5, PAFs of cancer were 0.471% (95% UI = -0.486–1.412), with 19,100 deaths (95% UI = -19,723–57,306) in 2020 and 0.455% (95% UI = -0.586–1.479), with 28,280 deaths (95% UI = -36,365–91,830) in 2040.

Conclusions: This study demonstrated that residents living near petrochemical industrial complexes could attributed to a 0.4% in cancer-related deaths between 2020 and 2040. Our findings suggested that people living near petrochemical industrial complexes should receive more attention for minimizing cancer risk.

Acknowledgement I
摘要 II
Abstract III
Chapter 1: Introduction 1
1.1 Overview of the study 1
1.2 Background 1
1.2.1 Overview of the petrochemical industry 1
1.2.2 Global burden of cancer due to environmental risk factors 2
1.2.3 Global demographic scenarios 2
1.2.4 Association between residents living near petrochemical industrial complexes and cancer risk 2
1.2.5 Population attributable fraction (PAF) for cancer 3
1.3 Research questions 3
1.4 Research hypotheses 4
1.5 Objectives 4
1.6 Significance 4
Chapter 2: Literature review 5
2.1 The definition and the process of petrochemical industrial complexes 5
2.2 Chemical agents released by petrochemical industrial complexes are known to be carcinogenic 6
2.3 Population attributable fraction (PAF) 6
2.3.1 The definition of PAF 6
2.3.2 The application of PAF in previous studies 8
2.3.3 The summary of literature review 9
Chapter 3: Materials and methods 11
3.1 Study framework 11
3.2 Study design 11
3.3 Study country 11
3.4 Formulating research question 15
3.5 Systematic literature review and estimating the effect size 15
3.5.1 Search strategy 15
3.5.2 Study selection and data collection 15
3.5.3 Cancer selection 16
3.5.4 Outcome and exposure indicators selection 18
3.5.5 Quality assurance 18
3.5.6 Quality assessment 18
3.5.7 Statistical analysis 19
3.5.8 Residential distances from the petrochemical industry classification 22
3.6 Identifying the lag time between exposure and different latency periods 22
3.7 Identifying the TMERL 24
3.8 Estimating the proportion of exposed population over the time window 24
3.8.1 Identify the source and collect the data 24
3.8.2 Estimate the number of people living near petrochemical industrial complexes 26
3.9 Estimating the PAF and burden of cancer 26
3.9.1 Estimating the PAF and uncertainty of intervals (UIs) 26
3.9.2 Estimating the burden of cancer 27
3.10 Sensitivity analyses 27
3.11 Research variable definition and explanation 27
Chapter 4: Results 29
4.1 Systematic review of epidemiological studies on the association between residential petrochemical industry exposure and cancer risk 29
4.1.1 Bladder cancer 29
4.1.2 Leukemia 30
4.1.3 Liver cancer 30
4.1.4 Lung cancer 30
4.1.5 Pancreatic cancer 31
4.1.6 Prostate cancer 32
4.2 The pooled RRs of cancer and residential exposure to petrochemical industrial complexes 32
4.2.1 Meta-analysis: Incidence outcome 32
4.2.2 Meta-analysis: Mortality outcome 33
4.2.3 Meta-analysis: Combined both outcomes 34
4.2.4 Meta-analysis: By different distances 35
4.2.5 Publication bias 36
4.2.6 Risk of bias assessment 36
4.2.7 Certainty of evidence 37
4.3 The petrochemical plants and oil refineries location and number of people living within 16 km from petrochemical industrial complexes for five SSPs during 2020–2040. 38
4.4 Estimation of global burden of cancer attributable to residential exposure to petrochemical industrial complexes during 2020–2040 in five SSPs 40
4.4.1 The trend of burden of cancer deaths at global level 40
4.4.2 The trend of burden of cancer deaths at regional level 41
4.4.3 The trend of burden of cancer deaths by SDI classification 44
4.4.4 The trend of burden of cancer deaths at country level 46
4.4.5 Global burden of cancer trend by six cancer types 49
4.4.6 Sensitivity analyses: Different time window of exposure 52
Chapter 5: Discussions 56
5.1 The pooled RRs of cancer among residents who live near petrochemical industrial complexes 56
5.2 Global number of residents living near petrochemical industrial complexes 57
5.3 The trend of global burden of cancer deaths attributable to residential exposure to petrochemical industrial complexes across five SSP scenarios 58
5.4 The trend of the burden of cancer deaths attributable to residential exposure to petrochemical industrial complexes by region and country 60
5.5 The trend of the burden of cancer deaths attributable to residential exposure to petrochemical industrial complexes by SDI classification 61
5.6 The trend of the burden of cancer deaths attributable to residential exposure to petrochemical industrial complexes by cancer types 61
5.7 Comparison between the main and sensitivity analyses 62
5.8 The influence of time window of exposure 62
5.9 Strengths of this study 63
5.10 Limitations 64
Chapter 6: Conclusions and suggestions 65
References 67
Appendices 75

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