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系統識別號 U0002-0407201110340600
中文論文名稱 代謝症候群、心血管疾病與就業
英文論文名稱 Metabolic syndrome, cardiovascular disease and employment
校院名稱 淡江大學
系所名稱(中) 產業經濟學系碩士班
系所名稱(英) Department of Industrial Economics
學年度 99
學期 2
出版年 100
研究生中文姓名 梁妍慧
研究生英文姓名 Yen-Huei Liang
學號 698540027
學位類別 碩士
語文別 中文
口試日期 2011-06-10
論文頁數 56頁
口試委員 指導教授-胡登淵
委員-陳鎮洲
委員-鄒孟文
中文關鍵字 代謝症候群  心血管疾病  就業  trivariate probit model 
英文關鍵字 metabolic syndrome  cardiovascular disease  employment  trivariate probit model 
學科別分類 學科別社會科學經濟學
中文摘要 在過去十年當中,我國心血管疾病及其相關危險因子(例如:肥胖、高血壓、高血糖和高血脂)的盛行率皆呈現持續上升的趨勢,這些慢性的健康問題不僅對醫療保健制度形成了巨額負擔,也將可能對社會生產力造成嚴重的負面影響。有鑑於此,本研究採用2005年國民健康訪問調查(NHIS)的資料,探討代謝症候群如何影響心血管疾病(心臟病和中風)以及其如何透過心血管疾病影響就業,考量到慢性病的潛在內生性以及疾病之間的相關性,因此使用帶有工具變數的trivariate probit模型來估計疾病與就業之間的關聯性,而我們所使用的工具變數包含有疾病的區域盛行率以及父母親的遺傳因素。實證研究之結果顯示:無論對於男性或女性,罹患心血管疾病對於個人就業的機率皆存在顯著的負面影響,一旦罹患心血管疾病將會使男性和女性的勞動參與率分別降低44.31% 與26.98%;同時,我們也發現代謝症候群對於心血管疾病存在正向顯著的影響,會使男性和女性心血管疾病的發生率分別提高17.01% 以及30.37%,證實了罹患代謝症候群將提高發生心血管疾病的可能性;而若能避免代謝症候群的發生,將可緩和5.8%(男性)與7.73%(女性)間接因心血管疾病而導致的失業率。因此,在代謝症候群的發生率持續大幅增長的情況下,採取多方辦法去對抗這項趨勢仍有其必要性,例如:透過教育水準的提升,可降低女性代謝症候群與心血管疾病的發生率,進而促進社會生產力;除此之外,心血管疾病的預防與治療也應當要能夠改善個人成功求職以及持續就業的機率。
英文摘要 The prevalence of cardiovascular diseases and its risk factors (including overweight/obesity, diabetes, hypertension and hyperlipidemia) has been on the rise in the past decade in developing countries. These chronic health problems not only place a huge burden on health care and welfare systems, but may also affect labor market performance. We hence examine the negative impact of metabolic syndrome on the probability of cardiovascular disease and also on the probability of employment through increase of the risk of cardiovascular disease by analyzing the 2005 National Health Interview Survey (NHIS) of Taiwan. It uses an endogenous trivariate probit model with a recursive structure, and the instrumental variables include prevalence rate of disease and genetic factors. The empirical results indicate that cardiovascular disease has a significantly negative effect on both male’s and female’s employment probability. For men, the effect of cardiovascular disease is to reduce labor force participation by 44.31% while for women the effect is 26.98%. On the other hand, the results confirm that metabolic syndrome increases the risk for cardiovascular disease significantly. Metabolic syndrome will increase the incidence rate of cardiovascular disease by 17.01% for men and 30.37% for women. If metabolic syndrome can be avoided, the employment rates will rise by 5.8% and 7.73% for men and women, respectively. Therefore, given the significant increase in the incidence of metabolic syndrome, it is imperative that a multifaceted approach to combat this trend be undertaken. For example, enhance the education level will reduce the risk for metabolic syndrome and cardiovascular disease for women, and hence it would improve the social productivity. In addition, the prevention and treatment of cardiovascular disease should improve the probability of individuals finding and retaining employment.
論文目次 目錄
第一章 緒 論 1
第二章 文獻回顧 4
第三章 資料來源與變數定義 8
第一節 資料來源 8
第二節 資料處理 9
第三節 變數定義與敘述統計 10
第四章 實證模型設定 20
第五章 實證結果與分析 25
第一節 實證結果 25
第二節 討論 41
第六章 結論 44
第一節 結論 44
第二節 研究限制與未來研究方向 45
參考文獻 47



表目錄
表一 變數定義表........................................................................................................ 13
表二 男性18~65歲敘述統計表 ............................................................................... 15
表三 女性18~65歲敘述統計表 ............................................................................... 16
表四 區域盛行率........................................................................................................ 17
表五 代謝症候群各項指標之敘述統計表................................................................ 18
表六 樣本罹病比例統計表........................................................................................ 19
表七 就業比率統計表................................................................................................ 19
表八 男性Trivariate probit估計結果—模型(一) ..................................................... 31
表九 女性Trivariate probit估計結果—模型(一) ..................................................... 32
表十 男性Trivariate probit估計結果—模型(二) ..................................................... 33
表十一 女性Trivariate probit估計結果—模型(二) ................................................. 34
表十二 工具變數檢定................................................................................................ 35
表十三 男性Univariate probit估計結果 .................................................................. 36
表十四 女性Univariate probit估計結果 .................................................................. 37
表十五 模型(一)就業預測機率(%) ........................................................................... 38
表十六 模型(二)就業預測機率(%) ........................................................................... 39
表十七 Univariate probit模型-就業預測機率(%) .................................................... 40
附錄
附表一 男性18~65歲敘述統計表–( MS定義Ⅱ) ................................................... 50
附表二 女性18~65歲敘述統計表–( MS定義Ⅱ) ................................................... 51
III
附表三 代謝症候群各項指標統計表–( MS定義Ⅱ) ............................................... 52
附表四 就業預測機率(%)–( MS定義Ⅱ) ................................................................. 53
附表五 模型(一)就業預測機率(%) —年齡與教育程度未分層模型 ...................... 54
附表六 模型(二)就業預測機率(%) —年齡與教育程度未分層模型 ...................... 55
附表七 Univariate probit模型-就業預測機率(%) —年齡與教育程度未分層模型 ................................................................................................................ 56



參考文獻 參考文獻
中文部份
1. 行政院衛生署國民健康局網站
2. 陳明豐(2007)「高血壓、膽固醇和心臟病」,(健康世界叢書: 178)
3. 楊振德(2007)「肝病、就業與收入關聯性之兩篇探討」,碩士論文,淡江大學產業經濟研究所。
4. 楊靜江(2009)「母親就業、食品營養標籤使用與小孩肥胖」,碩士論文,淡江大學產業經濟研究所。
英文部份
1. Bartel, A. & Taubman, P. (1979), “Health and Labor Market Success: The Role of Various Diseases”, The Review of Economics and Statistics, 61, issue 1, 1–8.
2. Cappellari, L. & S. P. Jenkins. (2003), “Multivariate probit regression using simulated maximum likelihood”, The Stata Journal, 3(3), 278–294.
3. Monfardini, C. & Radice, R. (2008), “Testing Exogeneity in the Bivariate Probit Model: A Monte Carlo Study”, Oxford Bulletin of Economics and Statistics, 70(2), 271–282, 04.
4. Currie, J. & Madrian, B. (1999), “Health, health insurance and the labor market”, Handbook of Labor Economics, 3309–3407.
5. Gallo WT, Teng HM, Falba TA, Kasl SV, Krumholz HM, Bradley EH. (2006), “The impact of late career job loss on myocardial infarction and stroke: a 10 year follow up using the health and retirement survey”, Occupational and Environmental Medicine, 63(10), 683–687.
6. Harris, A. (2009), “Diabetes, Cardiovascular Disease and Labour Force Participation in Australia: An Endogenous Multivariate Probit Analysis of Clinical Prevalence Data”, Economic Record, 85, 472–484.
7. Kritz-Silverstein D, Wingard DL, Barrett-Connor E. (1992), “Employment status and heart disease risk factors in middle-aged women: the Rancho Bernardo study”, Am J Public Health, 82, 215–248.
8. Stock, J. H. & Trebbi, F. (2003), “Who invented instrumental variable regression?”, Journal of Economic Perspectives, 17(3), 177–194.
9. Sullivan, P. W. & Ghushchyan, V. (2007), “Cardiovascular Risk Factor Clusters and Employment in the United States”, Value in Health, 10, S52–S58.
10. World Health Statistics (2008). Geneva, World Health Organization, 2008.
11. Yucel Demiral, Ahmet Soysal, Ahmet Can Bilgin, Bulent Kiliç, Belgin Unal, Reyhan Uçku & Tores Theorell. (2006), “The Association of Job Strain with Coronary Heart Disease and Metabolic Syndrome in Municipal Workers in Turkey”, Journal of Occupational Health, 48, 332–338.
12. Zhang, X., Zhao, X., & Harris, A. (2009), “Chronic diseases and labour force participation in Australia”, Journal of Health Economics, 28(1), 91–108.
13. Zwerling, C., P.S. Whitten, N.L. Sprince, C.S. Davis, R.B. Wallace, P.D. Blanck, & Steven Heeringa. (2002), “Workforce Participation by Persons With Disabilities: the National Health Interview Survey Disability Supplement, 1994 to 1995”, Journal of Occupational and Environmental Medicine, 44, 358–364.
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