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    政大機構典藏 > 商學院 > 統計學系 > 學位論文 >  Item 140.119/153364
    Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/153364


    Title: 臺灣居民的全死因及主要死因時空分析
    Spatial-Temporal Analysis of All-Cause and Leading Causes of Death for Taiwan’s Residents
    Authors: 陳玟儒
    Chen, Wen-Ru
    Contributors: 余清祥
    Yue, Ching-Syang
    陳玟儒
    Chen, Wen-Ru
    Keywords: 小區域估計
    地區差異
    主要死因
    空間分析
    標準化死亡率
    Small Area Estimation
    Regional Differences
    Major Death Causes
    Spatial Analysis
    Standardized Mortality Ratio
    Date: 2024
    Issue Date: 2024-09-04 14:56:23 (UTC+8)
    Abstract: 臺灣幅員不大,縣市甚至鄉鎮市區間的差異不小,不僅人口數及人口結構非常不同,再加上地理及先天環境的區隔,政府或民間企業需要因地制宜,制訂屬於各地區特色的發展政策。但評估各地居民需求的方法及模型,又會因為人數少而產生偏誤,以平均餘命的估計為例,小區域可能面臨人口數較少、死亡數為零而導致死亡率震盪,造成死亡率估計上的困難,這也是我國生命表編算不考慮鄉鎮市區層級的主因之一。本文目標為透過擴大樣本,集結與目標小區域特性相似之地區,降低小區域死亡率之估計誤差。
    但如何判斷參考地區的特性與小區域類似,至今尚未定論。本文以我國鄉鎮市區的全死因、主要死因為依據,找出臺灣居民死亡率的時空特性,作為挑選參考地區的標準。各鄉鎮市區死亡率特色的分析,包括各地全死因及三大主要死因(惡性腫瘤、心臟疾病、肺炎)之標準化死亡率(Standardized Death Rate, SDR)與人口密度及經緯度的關係。除了考慮各年度的死亡率數值大小,亦加入死亡率的時間變化率,作為判斷地區特性是否相似的標準。分析發現全死因及三大主要死因死亡趨勢明顯不同,全死因呈下降趨勢;惡性腫瘤先升後降;心臟疾病下降後持平;肺炎則呈上升趨勢,而相同死因在各地區的趨勢也存在差異。另外,全死因及惡性腫瘤的SDR隨著人口數及人口密度增加而下降,人口數少或人口密度低的地區改善幅度高,但變異程度也高。心臟疾病SDR同樣隨人口數增加而下降,但在人口數少的地區改善幅度較不一致;肺炎SDR與人口數的關係較不明顯,不論人口數多少皆隨時間惡化,背後應與2021年及2022年新冠肺炎疫情有關。
    Although Taiwan is small, the population structure and natural environment vary greatly among counties, cities and township. Local governments need to adapt local conditions and formulate policies that are unique to each region. Mortality models are one of popular choices for dealing with specific local needs, but they often suffer from estimation bias when faced with areas with small populations. This is one of the main reasons why Taiwan’s life tables do not cover smaller administrative levels, such as township. In this study, we introduce an approach to reduce estimation errors by increasing sample sizes via grouping areas with similar mortality profile.
    This article focuses on all causes of death and main causes of death in Taiwan. We explore the spatiotemporal characteristics of mortality rates (in terms of standardized death rate, SDR) in the township level, and use them to select reference population for small areas. The analysis showed that the death trends for all causes of death and three major causes of death (cancer, heart disease, and pneumonia) were significantly different: overall mortality declines; cancer rates first rise and then fall; heart disease decreases then stabilizes; pneumonia trends upward. SDR for all causes and cancer decreases with larger populations and higher densities, but smaller areas show greater variability. The relationship between pneumonia SDR and population size is less clear, and the pneumonia SDR recently, likely caused by COVID-19 pandemic.
    Reference: 一、 中文部分
    王信忠、金碩、余清祥(2012),「小區域死亡率推估之研究」,《人口學刊》,45期,頁121-154。
    王信忠、余清祥、王子瑜(2017),「臺灣原住民族死亡率暨生命表編撰研究」,《人口學刊》,55期,頁99-131。
    江信緯(2015),「臺灣分區人口死亡率之解析」,長庚大學醫務管理學系碩士論文。
    余清祥、王信忠、陳譽騰(2021),「年輪變動比用於小區域人口推估的探討」,《人口學刊》,63期,頁99-133。
    林正祥、劉士嘉、劉冠暐(2015),「台灣重要死因變動趨勢對潛在生命年數與經濟損失影響探討」,《台灣公共衛生雜誌》,34卷2期,頁168-179。
    林于凱、俞菘維、林沛練、王玉純(2015),「台灣不同地區之氣溫與全死因及心血管疾病死亡風險之相關分析」,《台灣公共衛生雜誌》,34卷1期,頁103-114。
    施淑芳、江東亮(2014),「臺灣新生兒後期死亡率區域健康不平等:時間趨勢及死因分析」,《健康促進與衛生教育學報》,42期,頁59-76。
    胡立諄、賴進貴(2006),「臺灣女性癌症的空間分析」,《台灣地理資訊學刊》,4期,頁39-55。
    張晉豪、梁燕青、廖勇柏、李文宗(2002),「臺灣地區不同行政區域主要死因之累積死亡與潛在生命損失累積率」,《台灣公共衛生雜誌》,21卷4期,頁243-252。
    梁穎誼、余清祥、梁舒涵(2023),「空間異質性檢測方法之比較及其在臺灣主要死因的應用」,《人口學刊》,66期,頁1-40。
    楊啟賢、楊金峰、郭智宇(2014),「台灣地區2003~2008年男女性勞工主要死因統計」,《勞工安全衛生研究季刊》,22卷2期,頁169-178。
    潘怜燕、邱淑媞(2011),「台灣地區1991~2007年男女性之健康差距:以平均餘命、死亡率及潛在生命年數損失為指標」,《台灣公共衛生雜誌》,30卷2期,頁135-149。
    鄧詠竹、郭巧玲、陳建州、葉耀鮮、高瑞鴻、林柏丞、范毅軍、詹大千(2016),「利用政府開放性資料建構台灣線上互動式疾病死因地圖」,《台灣公共衛生雜誌》,35卷5期,頁553-566。

    二、 英文部分
    Ahmad, O. B., Boschi-Pinto, C., Lopez, A. D., Murray, C. J., Lozano, R., and Inoue, M. (2001). “Age Standardization of Rates: A New WHO Standard,” Geneva: World Health Organization, Volume 9, Issue 10, 1-14.
    Coulomb, J.-B., Salhi, Y., and Thérond, P.-E. (2020). Credibility Adjustment of the Lee-Carter Longevity Model for Multiple Populations. HAL Open Science. https://hal.science/hal-02557208
    Jun, H. and Kang, S. (2023). “Regional Health Disparities between Mortality Rates in Three Leading Causes of Death : A Comparative Study of Spatial Dependence in Local Death Rate between Cancer, Heart Disease, and Pneumonia,” Journal of Korea Planning Association, Volume 58, Issue 2, 38-51.
    Kalogirou, S., Tsimbos, C., Verropoulou, G., and Kotsifakis, G. (2012). “Regional mortality differentials in Greece by selected causes of death: 2006-2008,” Journal of maps, Volume 8, Issue 4, 354-360.
    Lee, R. D. and Carter, L. R. (1992). “Modeling and Forecasting U.S. Mortality,” Journal of the American Statistical Association, Volume 87, Issue 419, 659-671.
    Lee, W. C. (2003). “A Partial SMR Approach to Smoothing Age-specific Rates,” Annals of Epidemiology, Volume 13, Issue 2, 89-99.
    Lewis, C. D. (1982). Industrial and Business Forecasting Methods: A Practical Guide to Exponential Smoothing and Curve Fitting, London, England: Butterworth Scientific.
    Li, N. and Lee, R. (2005). “Coherent Mortality Forecasts for a Group of Populations: An Extension of the Lee-Carter Method,” Demography, Volume 42, Issue 3, 575-594.
    Massimiliano, M., Maria, F. M., and Manuela, S. (2019). “Mortality Projections for Small Populations: An Application to the Maltese Elderly,” Risks, Volume 7, Issue 2, 35-59.
    Moran, P. (1950). “A Test for the Serial Independence of Residuals,” Biometrika, Volume 37, no. 1/2, 178-181.
    Wang, H., Yue, C.J., and Chong, C. (2018). “Mortality Models and Longevity Risk for Small Populations”, Insurance: Mathematics and Economics, Volume 78, 351-359.
    Whittaker, E. T. (1922). “On a New Method of Graduation,” Proceedings of the Edinburgh Mathematical Society, Volume 41, 63-75.
    Woo, H. and Kim, J. (2023). “Regional Disparities in the Infant Mortality Rate in Korea Between 2001 and 2021”, Journal of Korean medical science, Volume 38, Issue 44, 367-367.
    Yue, C.J., Wang, H. and Wang, T. (2021), “Using Graduation to Modify the Estimation of Lee-Carter Model for Small Populations,” North American Actuarial Journal, Volume 25, 410-420.
    Description: 碩士
    國立政治大學
    統計學系
    111354018
    Source URI: http://thesis.lib.nccu.edu.tw/record/#G0111354018
    Data Type: thesis
    Appears in Collections:[統計學系] 學位論文

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