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| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 簡國龍 | zh_TW |
| dc.contributor.advisor | Kuo-Liong Chien | en |
| dc.contributor.author | 蔡思盈 | zh_TW |
| dc.contributor.author | Szu-Ying Tsai | en |
| dc.date.accessioned | 2024-08-21T16:55:54Z | - |
| dc.date.available | 2024-08-22 | - |
| dc.date.copyright | 2024-08-21 | - |
| dc.date.issued | 2024 | - |
| dc.date.submitted | 2024-06-25 | - |
| dc.identifier.citation | 1. Mensah GA, Roth GA, Fuster V. The Global Burden of Cardiovascular Diseases and Risk Factors: 2020 and Beyond. J Am Coll Cardiol. 2019;74:2529-2532. doi: 10.1016/j.jacc.2019.10.009
2. Benjamin EJ, Muntner P, Alonso A, Bittencourt MS, Callaway CW, Carson AP, Chamberlain AM, Chang AR, Cheng S, Das SR, et al. Heart Disease and Stroke Statistics—2019 Update: A Report From the American Heart Association. Circulation. 2019;139:e56-e528. doi: 10.1161/CIR.0000000000000659 3. Tsao CW, Aday AW, Almarzooq ZI, Anderson CAM, Arora P, Avery CL, Baker-Smith CM, Beaton AZ, Boehme AK, Buxton AE, et al. Heart Disease and Stroke Statistics—2023 Update: A Report From the American Heart Association. Circulation. 2023;147:e93-e621. doi: 10.1161/CIR.0000000000001123 4. Roth GA, Mensah GA, Johnson CO, Addolorato G, Ammirati E, Baddour LM, Barengo NC, Beaton AZ, Benjamin EJ, Benziger CP, et al. Global Burden of Cardiovascular Diseases and Risk Factors, 1990-2019: Update From the GBD 2019 Study. J Am Coll Cardiol. 2020;76:2982-3021. doi: 10.1016/j.jacc.2020.11.010 5. Visseren FLJ, Mach F, Smulders YM, Carballo D, Koskinas KC, Bäck M, Benetos A, Biffi A, Boavida JM, Capodanno D, et al. 2021 ESC Guidelines on cardiovascular disease prevention in clinical practice. Eur Heart J. 2021;42:3227-3337. doi: 10.1093/eurheartj/ehab484 6. Noushad S, Ahmed S, Ansari B, Mustafa UH, Saleem Y, Hazrat H. Physiological biomarkers of chronic stress: A systematic review. Int J Health Sci (Qassim). 2021;15:46-59. 7. Dar T, Radfar A, Abohashem S, Pitman RK, Tawakol A, Osborne MT. Psychosocial Stress and Cardiovascular Disease. Curr Treat Options Cardiovasc Med. 2019;21:23. doi: 10.1007/s11936-019-0724-5 8. Osborne MT, Shin LM, Mehta NN, Pitman RK, Fayad ZA, Tawakol A. Disentangling the Links Between Psychosocial Stress and Cardiovascular Disease. Circulation: Cardiovascular Imaging. 2020;13:e010931. doi: 10.1161/CIRCIMAGING.120.010931 9. Leor J, Poole WK, Kloner Robert A. Sudden Cardiac Death Triggered by an Earthquake. New England Journal of Medicine. 1996;334:413-419. doi: 10.1056/NEJM199602153340701 10. Wilbert-Lampen U, Leistner D, Greven S, Pohl T, Sper S, Völker C, Güthlin D, Plasse A, Knez A, Küchenhoff H, et al. Cardiovascular Events during World Cup Soccer. New England Journal of Medicine. 2008;358:475-483. doi: doi:10.1056/NEJMoa0707427 11. Rosengren A, Hawken S, Ôunpuu S, Sliwa K, Zubaid M, Almahmeed WA, Blackett KN, Sitthi-amorn C, Sato H, Yusuf S. Association of psychosocial risk factors with risk of acute myocardial infarction in 11119 cases and 13648 controls from 52 countries (the INTERHEART study): case-control study. The Lancet. 2004;364:953-962. doi: 10.1016/S0140-6736(04)17019-0 12. Anand SS, Islam S, Rosengren A, Franzosi MG, Steyn K, Yusufali AH, Keltai M, Diaz R, Rangarajan S, Yusuf S. Risk factors for myocardial infarction in women and men: insights from the INTERHEART study. Eur Heart J. 2008;29:932-940. doi: 10.1093/eurheartj/ehn018 13. Rozanski A, Blumenthal JA, Kaplan J. Impact of psychological factors on the pathogenesis of cardiovascular disease and implications for therapy. Circulation. 1999;99:2192-2217. doi: 10.1161/01.cir.99.16.2192 14. McEwen BS, Wingfield JC. The concept of allostasis in biology and biomedicine. Horm Behav. 2003;43:2-15. doi: 10.1016/s0018-506x(02)00024-7 15. Kinlein SA, Karatsoreos IN. The hypothalamic-pituitary-adrenal axis as a substrate for stress resilience: Interactions with the circadian clock. Front Neuroendocrinol. 2020;56:100819. doi: 10.1016/j.yfrne.2019.100819 16. Kivimäki M, Steptoe A. Effects of stress on the development and progression of cardiovascular disease. Nature Reviews Cardiology. 2018;15:215-229. doi: 10.1038/nrcardio.2017.189 17. Inoue K, Horwich T, Bhatnagar R, Bhatt K, Goldwater D, Seeman T, Watson KE. Urinary Stress Hormones, Hypertension, and Cardiovascular Events: The Multi-Ethnic Study of Atherosclerosis. Hypertension. 2021;78:1640-1647. doi: 10.1161/HYPERTENSIONAHA.121.17618 18. Evolahti A, Hultcrantz M, Collins A. Women's work stress and cortisol levels: A longitudinal study of the association between the psychosocial work environment and serum cortisol. Journal of Psychosomatic Research. 2006;61:645-652. doi: https://doi.org/10.1016/j.jpsychores.2006.07.022 19. Faresjö Å, Jullander M, Götmalm S, Theodorsson E. Higher perceived stress and poorer health reflected in elevated cortisol concentrations measured in extracts of hair from middle-aged healthy women. BMC Psychology. 2014;2:30. doi: 10.1186/s40359-014-0030-7 20. Timio M, Gentili S, Pede S. Free adrenaline and noradrenaline excretion related to occupational stress. Br Heart J. 1979;42:471-474. doi: 10.1136/hrt.42.4.471 21. Vargatu I. Williams Textbook of Endocrinology. Acta Endocrinologica (Bucharest). 2016;12:113-113. doi: 10.4183/aeb.2016.113 22. Deussing JM, Chen A. The Corticotropin-Releasing Factor Family: Physiology of the Stress Response. Physiol Rev. 2018;98:2225-2286. doi: 10.1152/physrev.00042.2017 23. Hinds JA, Sanchez ER. The Role of the Hypothalamus–Pituitary–Adrenal (HPA) Axis in Test-Induced Anxiety: Assessments, Physiological Responses, and Molecular Details. Stresses. 2022;2:146-155. 24. Clayton RN. Cardiovascular complications of Cushings syndrome: Impact on morbidity and mortality. J Neuroendocrinol. 2022;34:e13175. doi: 10.1111/jne.13175 25. Goldstein DS. Chapter 2 - Differential responses of components of the autonomic nervous system. In: Buijs RM, Swaab DF, eds. Handbook of Clinical Neurology. Elsevier; 2013:13-22. 26. Bosker FJ, Wu T, Gladkevich A, Ge D, Treiber FA, Snieder H. Urinary norepinephrine and epinephrine excretion rates are heritable, but not associated with office and ambulatory blood pressure. Hypertension Research. 2012;35:1164-1170. doi: 10.1038/hr.2012.104 27. Hollstein T, Basolo A, Ando T, Votruba SB, Krakoff J, Piaggi P. Urinary Norepinephrine Is a Metabolic Determinant of 24-Hour Energy Expenditure and Sleeping Metabolic Rate in Adult Humans. J Clin Endocrinol Metab. 2020;105:1145-1156. doi: 10.1210/clinem/dgaa047 28. Wondisford FE. Adrenal Testing. In: Wondisford FE, ed. Essentials of Endocrinology and Metabolism: A Practical Guide for Medical Students. Cham: Springer International Publishing; 2020:177-182. 29. El-Farhan N, Rees DA, Evans C. Measuring cortisol in serum, urine and saliva - are our assays good enough? Ann Clin Biochem. 2017;54:308-322. doi: 10.1177/0004563216687335 30. Burch WM. Urine free-cortisol determination. A useful tool in the management of chronic hypoadrenal states. Jama. 1982;247:2002-2004. doi: 10.1001/jama.247.14.2002 31. Russell E, Koren G, Rieder M, Van Uum S. Hair cortisol as a biological marker of chronic stress: current status, future directions and unanswered questions. Psychoneuroendocrinology. 2012;37:589-601. doi: 10.1016/j.psyneuen.2011.09.009 32. Pereg D, Gow R, Mosseri M, Lishner M, Rieder M, Van Uum S, Koren G. Hair cortisol and the risk for acute myocardial infarction in adult men. Stress. 2011;14:73-81. doi: 10.3109/10253890.2010.511352 33. Gerber M, Brand S, Lindwall M, Elliot C, Kalak N, Herrmann C, Pühse U, Jonsdottir IH. Concerns regarding hair cortisol as a biomarker of chronic stress in exercise and sport science. J Sports Sci Med. 2012;11:571-581. 34. Sauvé B, Koren G, Walsh G, Tokmakejian S, Van Uum SH. Measurement of cortisol in human hair as a biomarker of systemic exposure. Clin Invest Med. 2007;30:E183-191. doi: 10.25011/cim.v30i5.2894 35. Vining RF, McGinley RA. The measurement of hormones in saliva: possibilities and pitfalls. J Steroid Biochem. 1987;27:81-94. doi: 10.1016/0022-4731(87)90297-4 36. Yamaguchi M, Matsuda Y, Sasaki S, Sasaki M, Kadoma Y, Imai Y, Niwa D, Shetty V. Immunosensor with fluid control mechanism for salivary cortisol analysis. Biosens Bioelectron. 2013;41:186-191. doi: 10.1016/j.bios.2012.08.016 37. Rouleau JL, Packer M, Moyé L, de Champlain J, Bichet D, Klein M, Rouleau JR, Sussex B, Arnold JM, Sestier F, et al. Prognostic value of neurohumoral activation in patients with an acute myocardial infarction: effect of captopril. J Am Coll Cardiol. 1994;24:583-591. doi: 10.1016/0735-1097(94)90001-9 38. Richards AM, Nicholls MG, Yandle TG, Ikram H, Espiner EA, Turner JG, Buttimore RC, Lainchbury JG, Elliott JM, Frampton C, et al. Neuroendocrine prediction of left ventricular function and heart failure after acute myocardial infarction. The Christchurch Cardioendocrine Research Group. Heart. 1999;81:114-120. doi: 10.1136/hrt.81.2.114 39. Katayama T, Nakashima H, Furudono S, Honda Y, Suzuki S, Yano K. Evaluation of neurohumoral activation (adrenomedullin, BNP, catecholamines, etc.) in patients with acute myocardial infarction. Intern Med. 2004;43:1015-1022. doi: 10.2169/internalmedicine.43.1015 40. Crawford AA, Soderberg S, Kirschbaum C, Murphy L, Eliasson M, Ebrahim S, Davey Smith G, Olsson T, Sattar N, Lawlor DA, et al. Morning plasma cortisol as a cardiovascular risk factor: findings from prospective cohort and Mendelian randomization studies. European Journal of Endocrinology. 2019;181:429-438. doi: 10.1530/eje-19-0161 41. Todaro JF, Shen BJ, Niaura R, Spiro A, 3rd, Ward KD. Effect of negative emotions on frequency of coronary heart disease (The Normative Aging Study). Am J Cardiol. 2003;92:901-906. doi: 10.1016/s0002-9149(03)00967-6 42. Goldman N, Glei DA, Lin YH, Weinstein M. Improving mortality prediction using biosocial surveys. Am J Epidemiol. 2009;169:769-779. doi: 10.1093/aje/kwn389 43. Cornman JC, Glei DA, Goldman N, Chang MC, Lin HS, Chuang YL, Hurng BS, Lin YH, Lin SH, Liu IW, et al. Cohort Profile: The Social Environment and Biomarkers of Aging Study (SEBAS) in Taiwan. Int J Epidemiol. 2016;45:54-63. doi: 10.1093/ije/dyu179 44. Tank AW, Lee Wong D. Peripheral and central effects of circulating catecholamines. Compr Physiol. 2015;5:1-15. doi: 10.1002/cphy.c140007 45. Goldman N, Glei DA, Seplaki C, Liu IW, Weinstein M. Perceived stress and physiological dysregulation in older adults. Stress. 2005;8:95-105. doi: 10.1080/10253890500141905 46. Pencina MJ, D'Agostino RB, Sr., D'Agostino RB, Jr., Vasan RS. Evaluating the added predictive ability of a new marker: from area under the ROC curve to reclassification and beyond. Stat Med. 2008;27:157-172; discussion 207-112. doi: 10.1002/sim.2929 47. Pruessner JC, Hellhammer DH, Kirschbaum C. Burnout, Perceived Stress, and Cortisol Responses to Awakening. Psychosomatic Medicine. 1999;61:197-204. 48. Gerber M, Ludyga S, Mücke M, Colledge F, Brand S, Pühse U. Low vigorous physical activity is associated with increased adrenocortical reactivity to psychosocial stress in students with high stress perceptions. Psychoneuroendocrinology. 2017;80:104-113. doi: 10.1016/j.psyneuen.2017.03.004 49. van Eck M, Berkhof H, Nicolson N, Sulon J. The effects of perceived stress, traits, mood states, and stressful daily events on salivary cortisol. Psychosom Med. 1996;58:447-458. doi: 10.1097/00006842-199609000-00007 50. Buzgoova K, Balagova L, Marko M, Kapsdorfer D, Riecansky I, Jezova D. Higher perceived stress is associated with lower cortisol concentrations but higher salivary interleukin-1beta in socially evaluated cold pressor test. Stress. 2020;23:248-255. doi: 10.1080/10253890.2019.1660872 51. Pollard TM, Ungpakorn G, Harrison GA, Parkes KR. Epinephrine and cortisol responses to work: A test of the models of Frankenhaeuser and Karasek1,2. Annals of Behavioral Medicine. 1996;18:229-237. doi: 10.1007/BF02895284 52. Forsman L, Lindblad LE. Effect of mental stress on baroreceptor-mediated changes in blood pressure and heart rate and on plasma catecholamines and subjective responses in healthy men and women. Psychosom Med. 1983;45:435-445. doi: 10.1097/00006842-198310000-00007 53. Benedict CR, Shelton B, Johnstone DE, Francis G, Greenberg B, Konstam M, Probstfield JL, Yusuf S. Prognostic Significance of Plasma Norepinephrine in Patients With Asymptomatic Left Ventricular Dysfunction. Circulation. 1996;94:690-697. doi: 10.1161/01.CIR.94.4.690 54. Sander D, Winbeck K, Klingelhöfer J, Etgen T, Conrad B. Prognostic relevance of pathological sympathetic activation after acute thromboembolic stroke. Neurology. 2001;57:833-838. doi: 10.1212/wnl.57.5.833 55. Yufu K, Okada N, Ebata Y, Murozono Y, Shinohara T, Nakagawa M, Takahashi N. Plasma norepinephrine is an independent predictor of adverse cerebral and cardiovascular events in type 2 diabetic patients without structural heart disease. J Cardiol. 2014;64:225-230. doi: 10.1016/j.jjcc.2013.12.009 56. D K. Norepinephrine Level as a Predictor of Mortality After First Myocardial Infarction. Journal of Clinical and Basic Cardiology. 2005;8:55. 57. Vogelzangs N, Beekman AT, Milaneschi Y, Bandinelli S, Ferrucci L, Penninx BW. Urinary cortisol and six-year risk of all-cause and cardiovascular mortality. J Clin Endocrinol Metab. 2010;95:4959-4964. doi: 10.1210/jc.2010-0192 58. van Ockenburg SL, Rosmalen JG, Bakker SJ, de Jonge P, Gans RO. Effects of urinary cortisol levels and resting heart rate on the risk for fatal and nonfatal cardiovascular events. Atherosclerosis. 2016;248:44-50. doi: 10.1016/j.atherosclerosis.2016.02.030 59. Wong DL, Tai TC, Wong-Faull DC, Claycomb R, Meloni EG, Myers KM, Carlezon WA, Jr., Kvetnansky R. Epinephrine: a short- and long-term regulator of stress and development of illness : a potential new role for epinephrine in stress. Cell Mol Neurobiol. 2012;32:737-748. doi: 10.1007/s10571-011-9768-0 60. Walker BR. Glucocorticoids and cardiovascular disease. Eur J Endocrinol. 2007;157:545-559. doi: 10.1530/eje-07-0455 61. Zvěřová M, Fišar Z, Jirák R, Kitzlerová E, Hroudová J, Raboch J. Plasma cortisol in Alzheimer's disease with or without depressive symptoms. Med Sci Monit. 2013;19:681-689. doi: 10.12659/msm.889110 62. Afzali A, Hatef B, Sahraei H, Meftahi GH, Khaleghi A, Jahromi GP. Changes in psychological and cognitive variables as well as cortisol levels in recovered Covid-19 patients: a longitudinal study. Current Psychology. 2024;43:12159-12168. doi: 10.1007/s12144-022-04211-7 63. Pilz S, Theiler-Schwetz V, Trummer C, Keppel MH, Grubler MR, Verheyen N, Odler B, Meinitzer A, Voelkl J, Marz W. Associations of Serum Cortisol with Cardiovascular Risk and Mortality in Patients Referred to Coronary Angiography. J Endocr Soc. 2021;5:bvab017. doi: 10.1210/jendso/bvab017 64. Devareddy A, Sawicki KT, Choudhury L, Wilcox JE. Reversible Biventricular Heart Failure Due to Primary Adrenal Insufficiency. JACC Case Rep. 2020;2:411-413. doi: 10.1016/j.jaccas.2019.12.039 | - |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/94961 | - |
| dc.description.abstract | 背景：心血管疾病是一個全球主要健康問題；然而，壓力激素與心血管疾病之間的關係仍然不確定。本研究的目的在於探討它們之間的關係。
研究材料與方法：本研究為前瞻性世代研究，我們使用的研究資料依據西元2000年時進行的老人健康之社會因素與生物指標計畫，其調查族群為台灣中老年族群。參與者接受了夜間尿液壓力荷爾蒙評估（腎上腺素、正腎上腺素、皮質醇），將尿液壓力激素濃度分成四等分位後，進行多變量羅吉斯回歸分析，以評估壓力激素濃度與心血管疾病事件和腦血管疾病事件之間的調整後勝算比。 結果與討論：經過6年的追蹤後，共有724名參與者納入分析。尿中腎上腺素在最高的四分位數濃度的受試者，相較於尿中腎上腺素在第一至第三個四分位數的受試者，有顯著較高的腦血管疾病風險(調整後勝算比，2.88，95信賴區間，1.23-6.73，p=0.01)。此外，尿中皮質醇濃度在第三個四分位數的受試者，相較第一個四分位數受試者，有顯著較低的腦血管疾病風險(調整後勝算比，0.19，95%信賴區間，0.15-0.73)。 結論：尿液腎上腺素濃度升高與腦血管疾病風險增加相關，相對較高的尿中皮質醇濃度與較低腦血管疾病風險相關。未來仍需要進一步研究以更深入探討此議題。 | zh_TW |
| dc.description.abstract | Introduction: Cardiovascular diseases (CVDs) remain a major global health concern; however, the relationship between stress hormones and CVDs remains uncertain. This study aimed to explore this relationship.
Methods: This is a prospective cohort study using data from the Social Environment and Biomarkers of Aging Study (SEBAS) conducted in 2000, which included middle-aged and elderly Taiwanese individuals. Participants were assessed for overnight urinary stress hormones (epinephrine, norepinephrine, and cortisol). Upon stratifying urinary stress hormone levels into quartiles, multivariable logistic regression analysis was conducted to assess the adjusted odds ratios (ORs) between stress hormone levels and cardiovascular and cerebrovascular events. Results: After 6-years of follow-up, 724 participants were included for analysis. Participants with the highest quartile concentration of urinary epinephrine had a significantly higher risk of cerebrovascular diseases compared with individuals in the first through third quartiles of urinary epinephrine (OR, 2.88, 95% Confidence interval (CI), 1.23-6.73, p=0.01). Additionally, participants in the third quartile of urinary cortisol had a significantly lower risk of cerebrovascular disease compared with those in the first quartile (OR, 0.19, 95% CI, 0.15-0.73). Conclusions: Elevated urine epinephrine level was linked to an increased risk of cerebrovascular disease. Relatively higher urinary cortisol concentration was associated with a lower risk of cerebrovascular disease. Further investigation is needed to explore this issue more thoroughly. | en |
| dc.description.provenance | Submitted by admin ntu (admin@lib.ntu.edu.tw) on 2024-08-21T16:55:54Z No. of bitstreams: 0 | en |
| dc.description.provenance | Made available in DSpace on 2024-08-21T16:55:54Z (GMT). No. of bitstreams: 0 | en |
| dc.description.tableofcontents | Contents
口試委員審定書 i 序言 ii 中文摘要 iii Abstract iv Abbreviations 1 Chapter 1. Introduction 2 1.1 The importance of cardiovascular diseases in public health 2 1.2 Psychosocial stress as a risk factor of cardiovascular diseases 3 1.3. Research about stress and cardiovascular diseases 4 1.4 The introduction of “allostasis theory” 5 1.5 The introduction of various methods of stress assessment 5 1.6 Regulation of stress response by effector system 7 1.7 The introduction of the measurement of epinephrine and norepinephrine 8 1.8 The introduction of the measurement of-cortisol 8 1.9 Studies about stress hormones and cardiovascular diseases 9 1.10 Research gaps 10 Chapter 2. Study hypothesis and aims 12 Chapter 3. Materials and Methods 13 3.1 Study design and participants 13 3.1.1 Study participants 13 3.1.2 Data source 13 3.1.3 Inclusion and exclusion criteria 15 3.2 Exposure assessments 15 3.2.1 Laboratory measurements 15 3.2.2 Biochemical data processing 16 3.3 Definition of outcomes 17 3.4 Definition of covariates 17 3.4.1 Definition of possible confounding factors 18 3.4.2 Perceived stress and stress index 19 3.5 Statistical Analyses 19 3.5.1 Descriptive part 20 3.5.2 Analytical part 20 3.5.3 Sample size estimation 21 3.5.4 Other statistical analysis – spline curve, AUC, IDI, NRI 22 Chapter 4. Results 23 4.1 Baseline characteristics of the current study 23 4.1.1 Baseline characteristics of all participants 23 4.1.2 Baseline characteristics of study participants by urinary epinephrine quartiles 23 4.1.3 Pearson correlation coefficients among stress hormones and stress index 24 4.2 The association among quartile levels of stress hormones and cardiovascular disease risk 25 4.2.1 Q1 as reference group 25 4.2.2 Q1-3 as reference group 26 4.3 The association among quartile levels of stress hormones and cerebrovascular disease risk 27 4.3.1 Q1 as reference group 27 4.3.2 Q1-3 as reference group 28 4.4 Subgroup analysis 28 4.5 Spline curves 30 4.6 The improvement in discrimination 30 Chapter 5. Discussion 32 5.1 Main findings 32 5.2 Comparison with previous studies 32 5.2.1 Perceived stress and stress hormones 32 5.2.2 The relationship between higher levels of epinephrine and cardiovascular disease risk 34 5.2.3 The relationship between higher levels of norepinephrine and cardiovascular disease risk 36 5.2.4 The relationship between higher levels of epinephrine and cardiovascular disease risk 39 5.3 Potential biological mechanisms 41 5.3.1 The biological mechanisms related to higher epinephrine and the risk of cardiovascular diseases 41 5.3.2 The biological mechanisms related to higher cortisol and the risk of cardiovascular diseases 43 5.4 The implication in public health and clinical practice 45 5.5 Strengths and study limitations 46 5.6 Conclusions 47 Chapter 6. References 49 Contents of tables 55 Table 1. Demographic characteristics in the study population specified by urine epinephrine quartiles (ug/L/creatinine), Social Environment and Biomarkers of Aging Study, Taiwan 55 Table 2. Pearson correlation coefficient table among stress measurement and different stress hormones 61 Table 3. The odds ratios from cardiovascular disease risk by quartiles of stress hormones, Social Environment and Biomarkers of Aging Study, Taiwan. 62 Table 4. The odds ratios from cardiovascular disease risk by quartiles (Q4 vs. Q1-Q3) of stress hormones, Social Environment and Biomarkers of Aging Study, Taiwan. 64 Table 5. The odds ratios from cerebrovascular disease risk by quartiles of stress hormones, Social Environment and Biomarkers of Aging Study, Taiwan. 66 Table 6. The odds ratios from cerebrovascular disease risk by quartiles (Q4 vs. Q1-Q3) of stress hormones, Social Environment and Biomarkers of Aging Study, Taiwan. 68 Table 7. Subgroup analysis by age group, sex, smoking, exercise, hypertension, and diabetes of cardiovascular disease risk and urine stress hormone quartiles (ug/L/creatinine) 70 Table 8. Subgroup analysis by age group, sex, smoking, exercise, hypertension, and diabetes of cerebrovascular disease risk and urine stress hormone quartiles (ug/L/creatinine) 72 Table 9. The improvement in discrimination of the risk of cardiovascular disease attributable to epinephrine, norepinephrine, and cortisol by AUC, IDI, and NRI 74 Table 10. The improvement in discrimination of the risk of cerebrovascular disease attributable to epinephrine, norepinephrine, and cortisol by AUC, IDI, and NRI 75 Contents of figures 76 Figure 1. The algorithm of cohort study of cardiovascular disease risk and stress hormones in SEBAS database 76 Figure 2. The algorithm of cohort study of cerebrovascular disease risk and stress hormones in SEBAS database 77 Figure 3. Scatter plots among different stress hormones 78 Figure 4. Subgroup analysis by age group, sex, smoking, physical activity, hypertension, diabetes and stress index of cardiovascular disease risk and urine epinephrine quartiles (ug/L/creatinine) (Q4 versus Q1-Q3) 79 Figure 5. Subgroup analysis by age group, sex, smoking, physical activity, hypertension, diabetes and stress index of cardiovascular disease risk and urine norepinephrine quartiles (ug/L/creatinine) (Q4 versus Q1-Q3) 80 Figure 6. Subgroup analysis by age group, sex, smoking, physical activity, hypertension, diabetes and stress index of cardiovascular disease risk and urine cortisol quartiles (ug/L/creatinine) (Q4 versus Q1-Q3) 81 Figure 7. Subgroup analysis by age group, sex, smoking, physical activity, hypertension, diabetes and stress index of cerebrovascular disease risk and urine epinephrine quartiles (ug/L/creatinine) (Q4 versus Q1-Q3) 82 Figure 8. Subgroup analysis by age group, sex, smoking, physical activity, hypertension, diabetes and stress index of cerebrovascular disease risk and urine norepinephrine quartiles (ug/L/creatinine) (Q4 versus Q1-Q3) 83 Figure 9. Subgroup analysis by age group, sex, smoking, physical activity, hypertension, diabetes and stress index of cerebrovascular disease risk and urine cortisol quartiles (ug/L/creatinine) (Q4 versus Q1-Q3) 84 Figure 10. Spline curve for urine epinephrine and cardiovascular disease risk 85 Figure 11. Spline curve for urine norepinephrine and cardiovascular disease risk 86 Figure 12. Spline curve for urine cortisol and cardiovascular disease risk 87 Figure 13. Spline curve for urine epinephrine and cerebrovascular disease risk 88 Figure 14. Spline curve for urine norepinephrine and cerebrovascular disease risk 89 Figure 15. Spline curve for urine cortisol and cerebrovascular disease risk 90 Figure 16. ROC curve for urine stress hormones and cardiovascular disease risk 91 Figure 17. ROC curve for urine stress hormones and cerebrovascular disease risk 92 Appendix 93 Certification from Institutional Review Board 93 Table S1. Characteristics of the studies included in the systematic review – highest versus lowest level of stress hormones (norepinephrine, 10 studies, epinephrine, 3 studies, cortisol, 7 studies) 94 Table S2. The odds ratios of cardiovascular disease risk by stress hormones (natural logarithm), Social Environment and Biomarkers of Aging Study, Taiwan. 99 Table S3. The odds ratios of cardiovascular disease risk by stress hormones (per IQR), Social Environment and Biomarkers of Aging Study, Taiwan. 100 Table S4. The odds ratios of cerebrovascular disease risk by stress hormones (natural logarithm), Social Environment and Biomarkers of Aging Study, Taiwan. 101 Table S5. The odds ratios of cerebrovascular disease risk by stress hormones (per IQR), Social Environment and Biomarkers of Aging Study, Taiwan. 102 Table S6. Model selection for stress hormone and cardiovascular diseases 103 Table S7. Model selection for stress hormone and cerebrovascular diseases 103 Table S8. Number of nodes selection for spline curve in cardiovascular diseases risk assessment 104 Table S9. Number of nodes selection for spline curve in cerebrovascular disease risk assessment 104 Table S10. Principle component analysis of stress hormones and stress index 105 Table S11. Demographic characteristics of the participants exclusion from the study population, Social Environment and Biomarkers of Aging Study, Taiwan 106 Table S12. The odds ratios from cerebrovascular disease risk by specific cut-off point of urine norepinephrine(ug/L/creatinine) 108 Figure S1. Spline curve for urine epinephrine and cardiovascular disease risk, odds ratio presented in log scale 109 Figure S2. Spline curve for urine norepinephrine and cardiovascular disease risk, odds ratio presented in log scale 110 Figure S3. Spline curve for urine cortisol and cardiovascular disease risk, odds ratio presented in log scale 111 Figure S4. Spline curve for urine epinephrine and cerebrovascular disease risk, odds ratio presented in log scale 112 Figure S5. Spline curve for urine norepinephrine and cerebrovascular disease risk, odds ratio presented in log scale 113 Figure S6. Spline curve for urine cortisol and cerebrovascular disease risk, odds ratio presented in log scale 114 | - |
| dc.language.iso | en | - |
| dc.subject | 壓力激素 | zh_TW |
| dc.subject | 腎上腺素 | zh_TW |
| dc.subject | 正腎上腺素 | zh_TW |
| dc.subject | 皮質醇 | zh_TW |
| dc.subject | 心血管疾病 | zh_TW |
| dc.subject | 腦血管疾病 | zh_TW |
| dc.subject | cerebrovascular diseases | en |
| dc.subject | stress hormone | en |
| dc.subject | epinephrine | en |
| dc.subject | norepinephrine | en |
| dc.subject | cortisol | en |
| dc.subject | cardiovascular diseases | en |
| dc.title | 壓力激素與心血管疾病風險的相關性－ 一個具代表性的台灣中老年族群世代研究 | zh_TW |
| dc.title | Association of Stress Hormones and the Risk of Cardiovascular Diseases – A Representative Cohort Study among Middle-to-Elderly Population in Taiwan | en |
| dc.type | Thesis | - |
| dc.date.schoolyear | 112-2 | - |
| dc.description.degree | 碩士 | - |
| dc.contributor.oralexamcommittee | 程藴菁;張慶國;李文宗;黃麗卿 | zh_TW |
| dc.contributor.oralexamcommittee | Yen-Ching Chen;Chin-Kuo chang;Wen-Chung Lee ;Lee-Ching Hwang | en |
| dc.subject.keyword | 壓力激素,腎上腺素,正腎上腺素,皮質醇,心血管疾病,腦血管疾病, | zh_TW |
| dc.subject.keyword | stress hormone,epinephrine,norepinephrine,cortisol,cardiovascular diseases,cerebrovascular diseases, | en |
| dc.relation.page | 114 | - |
| dc.identifier.doi | 10.6342/NTU202401308 | - |
| dc.rights.note | 未授權 | - |
| dc.date.accepted | 2024-06-25 | - |
| 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 | - |
| 顯示於系所單位： | 流行病學與預防醫學研究所 | |
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| ntu-112-2.pdf 未授權公開取用 | 2.81 MB | Adobe PDF |
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