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  1. NTU Theses and Dissertations Repository
  2. 公共衛生學院
  3. 流行病學與預防醫學研究所
請用此 Handle URI 來引用此文件: http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/99864
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dc.contributor.advisor林先和zh_TW
dc.contributor.advisorHsien-Ho Linen
dc.contributor.author羅苡晅zh_TW
dc.contributor.authorYi-Hsuan Loen
dc.date.accessioned2025-09-19T16:07:56Z-
dc.date.available2025-09-20-
dc.date.copyright2025-09-19-
dc.date.issued2025-
dc.date.submitted2025-07-02-
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15. Huang, Y., Cai, X., Mai, W., Li, M. & Hu, Y. Association between prediabetes and risk of cardiovascular disease and all cause mortality: systematic review and meta-analysis. BMJ i5953 (2016) doi:10.1136/bmj.i5953.
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33. Gakidou, E. et al. Global, regional, and national comparative risk assessment of 84 behavioural, environmental and occupational, and metabolic risks or clusters of risks, 1990–2016: a systematic analysis for the Global Burden of Disease Study 2016. The Lancet 390, 1345–1422 (2017).
34. Chang, Y. K. et al. A Point-based Mortality Prediction System for Older Adults with Diabetes. Sci Rep 7, 12652 (2017).
35. Lee, H. et al. Prediction model for type 2 diabetes mellitus and its association with mortality using machine learning in three independent cohorts from South Korea, Japan, and the UK: a model development and validation study. eClinicalMedicine 80, 103069 (2025).
36. Ikeda, N. et al. Adult Mortality Attributable to Preventable Risk Factors for Non-Communicable Diseases and Injuries in Japan: A Comparative Risk Assessment. PLoS Med 9, e1001160 (2012).
37. Ng, T.-C., Lo, W.-C., Ku, C.-C., Lu, T.-H. & Lin, H.-H. Improving the Use of Mortality Data in Public Health: A Comparison of Garbage Code Redistribution Models. Am J Public Health 110, 222–229 (2020).
38. 衛生福利部國民健康署. National Health Interview Survey (NHIS). https://www.hpa.gov.tw/Pages/Detail.aspx.nodeid=1077&pid=6198 (2016).
39. Brauer, M. et al. Global burden and strength of evidence for 88 risk factors in 204 countries and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021. The Lancet 403, 2162–2203 (2024).
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42. Kontis, V. et al. Contribution of six risk factors to achieving the 25×25 non-communicable disease mortality reduction target: a modelling study. The Lancet 384, 427–437 (2014).
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47. Su, S.-Y. et al. An evaluation of the 25 by 25 goal for premature cardiovascular disease mortality in Taiwan: an age-period-cohort analysis, population attributable fraction and national population-based study. Heart Asia 9, e010905 (2017).
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dc.identifier.urihttp://tdr.lib.ntu.edu.tw/jspui/handle/123456789/99864-
dc.description.abstract背景:第二型糖尿病(Type 2 Diabetes Mellitus, T2DM)為全球主要的健康負擔之一,而高身體質量指數(Body Mass Index, BMI)為T2DM死亡率的重要危險因子。本研究旨在探討不同之未來過重及肥胖情境下,對台灣T2DM死亡率趨勢的影響及預測結果。

方法:本研究採用全球疾病負擔計畫(Global Burden of Disease, GBD)所開發之比較風險評估(Comparative Risk Assessment, CRA)方法,利用2001-2020年資料估算2021-2035年族群可歸因分率及不可歸因之糖尿病死亡負擔,進而推算未來BMI不同情境下所致T2DM死亡率。數據來源包括全國第二型糖尿病死亡統計資料、人口統計資料及國健署BMI盛行率調查。族群可歸因分率(Population Attributable Fractions, PAFs)根據BMI分布、相對風險估計值(Relative Risk)及理論最小風險暴露水平(Theoretical Minimum Risk Exposure Level, TMREL)計算。死亡率預測結合了四種未來過重及肥胖情境,並利用蒙地卡羅模擬(Monte Carlo simulation)進行不確定性分析(uncertainty analysis)與使用及三種基線非BMI歸因死亡率模型作為敏感性分析(sensitivity analysis)。

結果:資料顯示自2021年起糖尿病粗死亡率呈上升趨勢,然而年齡標準化後的T2DM死亡率持續下降,反映人口老化趨勢及實際死亡人數的重要性。根據2001至2020年歷史資料,T2DM每年死亡人數約介於一萬至一萬三千人之間;高BMI於該期間對T2DM死亡的可歸因分率約為男性26-30%,女性25-28%。在2021至2035年的累計死亡預測中,若能將全國過重及肥胖率降至32.7%,可避免約15,821例死亡;若降至43.3%,則可避免約8,787例;若穩定於50%,則約可避免4,130例死亡。年長者及男性死亡率較高,顯示政策應優先針對特定族群進行介入。

結論:積極且持續的過重及肥胖控制對降低台灣T2DM死亡率至關重要。但實質減少總死亡負擔,需同步推動針對肥胖及非肥胖相關因素的綜合公共衛生策略。本研究為政策制定者提供的科學數據,可供未來肥胖管理、糖尿病照護與公共衛生長期規劃參考。
zh_TW
dc.description.abstractBackground: Type 2 diabetes mellitus (T2DM) is a major global health burden, with high body mass index (BMI) being a significant risk factor for T2DM mortality. This study aims to examine the impact of various future overweight and obesity scenarios on projected T2DM mortality trends in Taiwan.

Method: This study applied the Comparative Risk Assessment (CRA) methodology developed by the Global Burden of Disease (GBD) project. Using data from 2001 to 2020, we estimated population attributable fractions (PAF) and non-attributable diabetes mortality burdens for 2021–2035, and further projected T2DM mortality attributable to high BMI. Data sources included national T2DM mortality statistics, demographic data, and BMI prevalence surveys from the Health Promotion Administration. PAFs were calculated based on BMI distribution, relative risk estimates, and theoretical minimum risk exposure levels (TMREL). Mortality projections incorporated four overweight and obesity scenarios and three non-attributable death rate models, with sensitivity and uncertainty analyses conducted using Monte Carlo simulations.

Results: While crude T2DM mortality showed an increasing trend after 2021, age-standardized mortality continued to decline, reflecting the impact of population aging and underscoring the importance of absolute death counts. From 2001 to 2020, annual T2DM deaths ranged from 10,000 to 13,000. During this period, high BMI contributed to an estimated 26–30% of T2DM mortality in males and 25–28% in females. In cumulative mortality projections for 2021–2035, reducing the national overweight and obesity rate to 32.7% could prevent approximately 15,821 deaths; reducing it to 43.3% could prevent about 8,787 deaths; and stabilizing it at 50% could prevent around 4,130 deaths. Higher mortality rates were observed among older adults and males, indicating the need for targeted interventions for these populations.

Conclusion: Aggressive and sustained interventions to reduce overweight and obesity are essential for lowering future T2DM mortality in Taiwan. However, to substantially reduce the overall mortality burden, comprehensive public health strategies addressing both obesity-related and non-obesity-related factors are necessary. This study provides scientific evidence to inform policymakers in the planning of obesity management, diabetes care, and long-term public health strategies.
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dc.description.provenanceSubmitted by admin ntu (admin@lib.ntu.edu.tw) on 2025-09-19T16:07:56Z
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dc.description.provenanceMade available in DSpace on 2025-09-19T16:07:56Z (GMT). No. of bitstreams: 0en
dc.description.tableofcontents口試委員會審定書 i
誌謝 ii
中文摘要 iii
ABSTRACT v
CONTENTS vii
LIST OF FIGURES x
LIST OF TABLES xii
Chapter 1 Introduction 1
1.1 Overview of Diabetes Mellitus 1
1.2 Obesity and Public Health in Taiwan 2
1.3 High Body Mass Index as a Risk Factor for Type 2 Diabetes Mellitus 3
1.4 Research Gap and Study Aims 4
Chapter 2 Methodology 6
2.1 Study Structure and Health Metrics 6
2.2 Data Sources and Risk Factor Selection 6
2.2.1 Risk Factor Selection 6
2.2.2 Relative Risk Estimation 7
2.2.3 Theoretical Minimum Risk Exposure Level (TMREL) 7
2.3 Population Attributable Fraction (PAF) Estimation 7
2.4 Predictive Modelling and Mortality Burden Estimation 8
2.4.1 BMI Future Projection Scenarios 9
2.4.2 BMI Scenarios Analysis Process 10
2.4.3 Non-Attributable Death Rate Models 11
2.4.4 Predicted Type 2 Diabetes Mortality Analysis 13
2.5 Sensitivity and Uncertainty Analyses 13
2.5.1 Sensitivity Analysis 13
2.5.2 Uncertainty Analysis 14
Chapter 3 Results 15
3.1 Historical Trends in Type 2 Diabetes Mortality in Taiwan 15
3.2 Projected Type 2 Diabetes Mortality under Four BMI Future Scenarios (2021-2035) 16
3.3 Non-Attributable Death Rate Models and Timeframe Comparison 17
3.4 BMI Non-attributable Death Rate and Population Attributable Fraction on Type 2 Diabetes Mellitus in Taiwan 19
Chapter 4 Discussion 21
4.1 Main Findings and Interpretation 21
4.2 Relations between Population Attributable Fraction, Attributable Death Rate, and Mortality Rate 23
4.3 Strengths and Limitations 24
4.4 Study Implications and Further Research 26
4.5 Conclusion 27
REFERENCE 51
APPENDIX 56
Appendix A. T2DM Projections Using Combined Age Groups (Based on Five Historical Data Points) 56
Appendix B. Type 2 Diabetes Mortality Projections by 14 Age Groups with Monte Carlo Simulations 68
Appendix C. Non-Attributable Mortality Estimates Using the Single-Point Model 90
Appendix D. High BMI–Related Relative Risks for Diabetes (GBD 2021) and Historical T2DM Mortality by Age and Gender (2000–2021) 94
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dc.language.isoen-
dc.subject第二型糖尿病zh_TW
dc.subject身體質量指數zh_TW
dc.subject死亡率zh_TW
dc.subject族群可歸因分率zh_TW
dc.subject比較風險評估zh_TW
dc.subject台灣zh_TW
dc.subject死亡率預測zh_TW
dc.subjectBody Mass Indexen
dc.subjectMortality Projectionen
dc.subjectTaiwanen
dc.subjectComparative Risk Assessmenten
dc.subjectPopulation Attributable Fractionen
dc.subjectMortalityen
dc.subjectType 2 Diabetes Mellitusen
dc.title探討身體質量指數對台灣第二型糖尿病死亡率的影響:不同肥胖情境下的當前與未來趨勢zh_TW
dc.titleEvaluating the Impact of High Body Mass Index on Type 2 Diabetes Mortality in Taiwan: Current and Future Trends Across Various Obesity Scenariosen
dc.typeThesis-
dc.date.schoolyear113-2-
dc.description.degree碩士-
dc.contributor.oralexamcommittee賈淑麗;李文宗;簡國龍zh_TW
dc.contributor.oralexamcommitteeShu-Li Chia;Wen-Chung Lee;Kuo-Liong Chienen
dc.subject.keyword第二型糖尿病,身體質量指數,死亡率,族群可歸因分率,比較風險評估,台灣,死亡率預測,zh_TW
dc.subject.keywordType 2 Diabetes Mellitus,Body Mass Index,Mortality,Population Attributable Fraction,Comparative Risk Assessment,Taiwan,Mortality Projection,en
dc.relation.page99-
dc.identifier.doi10.6342/NTU202501343-
dc.rights.note未授權-
dc.date.accepted2025-07-03-
dc.contributor.author-college公共衛生學院-
dc.contributor.author-dept流行病學與預防醫學研究所-
dc.date.embargo-liftN/A-
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