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完整後設資料紀錄
DC 欄位 | 值 | 語言 |
---|---|---|
dc.contributor.advisor | 陳秀熙(Tony Hsiu-Hsi Chen) | |
dc.contributor.author | Ya-Ping Huang | en |
dc.contributor.author | 黃雅萍 | zh_TW |
dc.date.accessioned | 2021-06-15T04:22:52Z | - |
dc.date.available | 2016-10-03 | |
dc.date.copyright | 2011-10-03 | |
dc.date.issued | 2011 | |
dc.date.submitted | 2011-08-17 | |
dc.identifier.citation | 1. Wolf-Maier, K., et al., Hypertension prevalence and blood pressure levels in 6 European countries, Canada, and the United States. JAMA : the journal of the American Medical Association. 2003; 289:2363-9.
2. Fauci, A.S., Harrison's principles of internal medicine. Vol. 2. 1998: McGraw-Hill New York, NY. 3. Vasan, R.S., et al., Assessment of frequency of progression to hypertension in non-hypertensive participants in the Framingham Heart Study: a cohort study. Lancet. 2001; 358:1682-6. 4. Chobanian, A.V., et al., The Seventh Report of the Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure: the JNC 7 report. JAMA : the journal of the American Medical Association. 2003; 289:2560-72. 5. Chobanian, A.V., et al., Seventh report of the Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure. Hypertension. 2003; 42:1206-52. 6. Egan, B.M., Y. Zhao, and R.N. Axon, US trends in prevalence, awareness, treatment, and control of hypertension, 1988-2008. JAMA : the journal of the American Medical Association. 2010; 303:2043-50. 7. Su, T.C., et al., Ethnic variation in hypertension prevalence of women in Taiwan. Journal of human hypertension. 2009; 23:160-7. 8. Su, T.C., et al., Evidence for improved control of hypertension in Taiwan: 1993-2002. Journal of hypertension. 2008; 26:600-6. 9. Berkey, C.S., et al., Modelling adolescent blood pressure patterns and their prediction of adult pressures. Biometrics. 1991; 47:1005-18. 10. Lambrechtsen, J., et al., Tracking and factors predicting rising in 'tracking quartile' in blood pressure from childhood to adulthood: Odense Schoolchild Study. Journal of human hypertension. 1999; 13:385-91. 11. Wang, W., et al., A longitudinal study of hypertension risk factors and their relation to cardiovascular disease: the Strong Heart Study. Hypertension. 2006; 47:403-9. 12. Suka, M., et al., Risk factors for hypertension. A longitudinal study of middle-aged Japanese male workers. Japanese journal of public health. 2001; 48:543. 13. Arnlov, J., et al., Relations of insulin sensitivity to longitudinal blood pressure tracking: variations with baseline age, body mass index, and blood pressure. Circulation. 2005; 112:1719-27. 14. Chen, W., et al., Adult hypertension is associated with blood pressure variability in childhood in blacks and whites: the bogalusa heart study. American journal of hypertension. 2011; 24:77-82. 15. Rothwell, P.M., et al., Prognostic significance of visit-to-visit variability, maximum systolic blood pressure, and episodic hypertension. Lancet. 2010; 375:895-905. 16. Rothwell, P.M., et al., Effects of beta blockers and calcium-channel blockers on within-individual variability in blood pressure and risk of stroke. Lancet neurology. 2010; 9:469-80. 17. Hildrum, B., et al., Effect of anxiety and depression on blood pressure: 11-year longitudinal population study. The British journal of psychiatry : the journal of mental science. 2008; 193:108-13. 18. Rosenberger, E.L., et al., Control of blood pressure in North Carolina primary care: baseline data from the GLAD Heart Trial. North Carolina medical journal. 2008; 69:441-6. 19. Zucker, D.M., G.O. Zerbe, and M.C. Wu, Inference for the association between coefficients in a multivariate growth curve model. Biometrics. 1995; 51:413-24. 20. Chiu, Y.H., et al., Progression of pre-hypertension, stage 1 and 2 hypertension (JNC 7): a population-based study in Keelung, Taiwan (Keelung Community-based Integrated Screening No. 9). Journal of hypertension. 2006; 24:821-8. 21. Chen, T.H., et al., Community-based multiple screening model: design, implementation, and analysis of 42,387 participants. Cancer. 2004; 100:1734-43. 22. Chiu, Y.H., et al., Health information system for community-based multiple screening in Keelung, Taiwan (Keelung Community-based Integrated Screening No. 3). International journal of medical informatics. 2006; 75:369-83. 23. Brown, H. and R. Prescott, Applied mixed models in medicine2006: Wiley. 24. Fry, J., Natural history of hypertension. A case for selective non-treatment. Lancet. 1974; 2: 431-3. 25. Saladini, F., et al., Natural history of hypertension subtypes in young and middle-age adults. American journal of hypertension, 2009; 22:531-7. 26. Verdecchia, P. and F. Angeli, Natural history of hypertension subtypes. Circulation. 2005; 111:1094-6. 27. Chung, F.M., et al., The role of angiotensin-converting enzyme gene insertion/deletion polymorphism for blood pressure regulation in areca nut chewers. Translational Research. 2007; 150:58-65. | |
dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/45486 | - |
dc.description.abstract | 目的:高血壓為腦中風及心血管疾病的重要危險因子,高血壓防治在公共衛生上具相當重要性,尤其是JNC7提出利用生活型態改變高血壓前期族群。過去研究較少利用血壓重複測量資料觀測血壓由正常進展為高血壓間的動態變化。因此本研究欲利用社區重複篩檢資料,觀察由正常血壓進展高血壓的自然史,並了解影響血壓發展及血壓變化之相關因子。
研究材料及方法:本研究設計為一前膽性長期追蹤世代研究,乃利用台灣某地區2001年至2009年期間參與篩檢者具重複受檢之特性,收集血壓及其可能相關因子重複檢測資料。參加者資料收集起始時間點並非全部相同,為不同時間點進入的研究設計,並根據JNC-7定義,將所有參加者收縮壓分為正常血壓、高血壓前期,及高血壓三組,將第一次接受篩檢收縮壓值超過140mmHg以及自我記錄為高血壓族群的參加者排除後共56227人,區分非高血壓族群為正常血壓以及高血壓前期兩個族群後,追蹤後續重複篩檢之血壓測量資料,共計有110679筆重複測量之收縮壓及111029筆重複測量之舒張壓資料。本研究所使用重複資料尚包含空腹血糖值、總膽固醇、三酸甘油脂及高密度脂蛋白膽固醇。影響血壓之其他分析變項包括年齡、性別、身高、體重、腰圍、教育程度、抽菸習慣、飲酒習慣、檳榔嚼食習慣,參加者是否有糖尿病及高血壓病史之主訴等變項。利用線性混合模式分析影響血壓及血壓變化量相關危險因子並比較線性模式及線性混合模式對於重複測量資料分析上的差異。比例風險廻歸模型則用以評估血壓經長期追蹤下發展為高血壓之相關危險因子。 結果:分析結果顯示,在長期追蹤下,高血壓前期較正常血壓者有更高的危險性會發展成為高血壓。比較整體血壓變化的趨勢,在高血壓前期血壓有下降的趨勢,但在正常血壓組的血壓確有稍微上揚的趨勢。影響收縮壓及舒張壓兩者血壓變化的共變項並不一致,整體舒張壓血壓變化幅度較小,且發展成高血壓的機率較低。正常血壓與高血壓前期之族群其血壓發展相關危險因子包括基準收縮壓、年齡、性別、身體質量指數、空腹血糖、總膽固醇、三酸甘油脂、高密度脂蛋白膽固醇、教育程度、抽菸及飲酒習慣。高血壓前期者之收縮壓進展危險因子有別於正常血壓者,其危險因子不包含高密度脂蛋白膽固醇,高血壓前期者之舒張壓進展危險因子有別於正常血壓者,其危險因子不包含教育程度。由比例風險廻歸分析發現,高血壓前期者,危險因子有別於正常血壓者,危險因子包括血壓基準值、年齡、身體質量指數、總膽固醇、高密度脂蛋白膽固醇以及性別,與高血壓進展有關。 結論:本研究藉由社區整合式多重疾病篩檢資料進行前瞻性世代研究,此種以族群為主之世代長期追蹤重複測量資料有助於了解血壓之自然進展,以及血壓變化與高血壓發生相關重要危險因子,就血壓防治上,可藉由生活型態調整以修飾這些危險因子,進而降低族群高血壓發生的機會,因此,本研究就血壓進展及高血壓發生相關因子的發現,可做為未來對血壓防治策略參考。 | zh_TW |
dc.description.abstract | Purpose:Hypertension has been recognized as a major risk factor for stroke and cardiovascular disease. Its prevention becomes the core subject of public health, particularly life-style modification offered for patients with pre-hypertension pursuant to JNC7 guideline in order to reduce the incidence of hypertension. Very few studies revealed the dynamic change of blood pressure from normal status to hypertension based on longitudinal repeated measurements of blood pressure. Therefore, we aimed to assess the risk factors responsible for the changes of blood pressure based on a longitudinal follow-up cohort on screening for multiple diseases.
Methods:The data with repeated measurement for analysis was derived from a Taiwanese Community-based Integrated Screening (CIS) program with 10-year longitudinal follow-up. A longitudinal and prospective cohort follow-up design was conducted in this study. After excluding the prevalent hypertension cases at first screen, we enrolled a total of 56,227 participants without hypertension including normal and pre-hypertension groups to collect the information on the measurement of systolic and diabolic blood pressure followed with periodical repeated screens. The additional information on repeated characteristics was also collected including fasting blood sugar, total cholesterol, triglyceride, high density lipoprotein. The baseline characteristics including age, gender, body mass index, education level, life styles including smoking, drinking, and betel nut chewing, personal disease history were also collected in this study. With repeated measurement data, a series of linear mixed models were applied to assess the risk of blood pressure progress or change in normal blood pressure and pre-hypertension groups. Proportional hazard regression model was also used to assess the risk of hypertension development in same cohort with long-term follow up. Results:Compared with normal blood pressure group, pre-hypertensive subjects had higher risk of incident hypertension, and had tendency to decrease blood pressure while normal blood pressure group tended to increase blood pressure mildly. The diastolic blood pressure showed less change of blood pressure and less incidence of new developed hypertension compared with systolic blood pressure. This result revealed that baseline SBP, age, gender, body mass index (BMI), fasting blood sugar, cholesterol, triglyceride, high density lipoprotein, education level, smoking and drinking were risk factors for blood pressure change. The different risk factors have been demonstrated between normal blood pressure and pre-hypertension group. Conclusion The risk factors for blood pressure progress and hypertension development were revealed in this study. The result was very useful to apply the life-style modification based on the light of risk factors from our findings to reduce the incidence of hypertension in terms of population-based hypertension preventive approach. | en |
dc.description.provenance | Made available in DSpace on 2021-06-15T04:22:52Z (GMT). No. of bitstreams: 1 ntu-100-P98842003-1.pdf: 1427902 bytes, checksum: 8ccc6a8dbe6fc1b4fab2da259f764b54 (MD5) Previous issue date: 2011 | en |
dc.description.tableofcontents | 口試委員會審定書 i
中文摘要 ii ABSTRACT iv 目錄 vi 圖目錄 ix 表目錄 x Chapter 1 前言 1 1.1 研究背景 1 1.2 研究目的 2 Chapter 2 文獻探討 3 2.1 高血壓定義與分期 3 2.2 高血壓盛行率 4 2.3 影響新發生高血壓的因子 5 2.3.1 影響正常血壓發展成高血壓的因子 5 2.3.2 新發生高血壓預測模式 5 2.3.3 總結影響新發生高血壓的因子 6 Chapter 3 研究方法 7 3.1 研究族群 7 3.2 研究設計 7 3.3 主要分析變項 8 3.4 統計分析 8 Chapter 4 研究結果 10 4.1 研究族群基本資料特性 10 4.2 研究族群血壓特性 12 4.2.1 各年血壓統計量 12 4.2.2 血壓與年齡相關性分析 12 4.2.3 重複血壓測量間之相關性 12 4.2.4 不同血壓分期之血壓變化 13 4.3 線性混合模式分析 13 4.3.1 常態分佈檢定 13 4.3.2 最佳模式及共變異數結構確立 13 4.3.3 單變項線性混合模式估計 14 4.3.4 多變項線性混合模式估計 14 4.3.5 高血壓發生相關危險因子 15 4.3.6 正常血壓族群與高血壓前期族群之高血壓危險因子 16 4.3.7 模型驗證 17 Chapter 5 討論與結論 18 5.1 主要結果 18 5.2 高血壓發展自然史 19 5.3 影響血壓及血壓變化相關因子 20 5.3.1 檢驗室生化資料 20 5.3.2 生活型態之危險因子 20 5.4 正常血壓族群與高血壓前期族群之血壓變化比較 21 5.5 線性混合模式分析與一般線性模式分析比較 22 5.6 線性混合模式分析與Cox迴歸分析比較 22 5.7 正常血壓族群與高血壓前期族群高血壓危險因子比較 23 5.8 研究限制 23 5.9 結論 23 參考資料 24 圖目錄 Fig. 3.1 研究設計及流程圖 26 Fig. 4.1 各年資料中收縮壓及舒張壓之平均值 27 Fig. 4.2 各年齡層的收縮壓及舒張壓 28 Fig. 4.3 各年之間血壓相關性的散佈圖陣列(收縮壓) 29 Fig. 4.4 各年之間血壓相關性的散佈圖陣列(舒張壓) 30 Fig. 4.5 各年收縮壓及舒張壓之血壓變化量 31 Fig. 4.6 各年血壓變化量 32 Fig. 4.7 收縮壓基準值低於140mmHg及舒張壓基準值低90mmHg之受檢者重複受檢血壓測量值分佈 33 Fig. 4.8 收縮壓及舒張壓分佈之殘差圖 34 表目錄 Table 2.1 高血壓指引第六版與第七版之血壓分類比較 35 Table 2.2 JNC 7 對於十八歲以上成年人血壓分類及處理建議 35 Table 4.1 各年第一次接受篩檢人數及收集資料總人次統計表 37 Table 4.2 不同測量次數統計表 38 Table 4.3 研究族群之基本資料 39 Table 4.4 以收縮壓之重複測量資料比較不同的共變異數結構的模式適配度 41 Table 4.5 以舒張壓之重複測量資料比較不同的共變異數結構的模式適配度 41 Table 4.6 以收縮壓基準值及其他相關因子探討收縮壓之單變項線性混合模式估計結果 42 Table 4.7 以舒張壓基準值及其他相關因子探討舒張壓之單變項線性混合模式估計結果 43 Table 4.8 以收縮壓基準值及其他相關因子探討收縮壓變化之單變項線性混合模式估計結果 44 Table 4.9 以舒張壓基準值及其他相關因子探討舒張壓變化之單變項線性混合模式估計結果 45 Table 4.10 以收縮壓基準值及其他相關因子探討收縮壓之多變項線性混合模式估計結果 46 Table 4.11 以舒張壓基準值及其他相關因子探討舒張壓之多變項線性混合模式估計結果 47 Table 4.12 以收縮壓基準值及其他相關因子探討收縮壓改變之多變項線性混合模式估計結果 48 Table 4.13 以舒張壓基準值及其他相關因子探討舒張壓改變之多變項線性混合模式估計結果 49 Table 4.14 以收縮壓基準值分組及其他相關因子探討收縮壓之多變項線性混合模式估計結果 50 Table 4.15 以舒張壓基準值分組及其他相關因子探討舒張壓之多變項線性混合模式估計結果 51 Table 4.16 以收縮壓基準值分組及其他相關因子探討收縮壓改變之多變項線性混合模式估計結果 52 Table 4.17 以舒張壓基準值分組及其他相關因子探討舒張壓改變之多變項線性混合模式估計結果 53 Table 4.18 以Cox廻歸分析探討高血壓相關因子 54 Table 4.19 以收縮壓基準值分組探討收縮壓相關因子之多變項線性混合模式估計結果 55 Table 4.20 以舒張壓基準值分組探討舒張壓相關因子之多變項線性混合模式估計結果 56 Table 4.21 以Cox廻歸分析探討收縮壓型高血壓(SBP>140 mmHg)相關因子 57 Table 4.22 以Cox廻歸分析探討舒張壓型高血壓(DBP>90 mmHg)相關因子 58 | |
dc.language.iso | zh-TW | |
dc.title | 血壓重複測量之線性混合模式分析 | zh_TW |
dc.title | Analysis of Repeated Measurements of Blood Pressure with Linear Mixed Model | en |
dc.type | Thesis | |
dc.date.schoolyear | 99-2 | |
dc.description.degree | 碩士 | |
dc.contributor.oralexamcommittee | 戴政,張淑惠,曾春典 | |
dc.subject.keyword | 血壓,重複測量,高血壓前期,線性混合模式, | zh_TW |
dc.subject.keyword | Blood pressure,repeated measurement,prehypertension,linear mixed model, | en |
dc.relation.page | 58 | |
dc.rights.note | 有償授權 | |
dc.date.accepted | 2011-08-17 | |
dc.contributor.author-college | 公共衛生學院 | zh_TW |
dc.contributor.author-dept | 流行病學與預防醫學研究所 | zh_TW |
顯示於系所單位: | 流行病學與預防醫學研究所 |
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