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完整後設資料紀錄
DC 欄位 | 值 | 語言 |
---|---|---|
dc.contributor.advisor | 程蘊菁(Yen-Ching Chen) | |
dc.contributor.author | Yueh-Hsuan Sheng | en |
dc.contributor.author | 盛業瑄 | zh_TW |
dc.date.accessioned | 2021-06-16T17:47:01Z | - |
dc.date.available | 2017-09-17 | |
dc.date.copyright | 2012-09-17 | |
dc.date.issued | 2012 | |
dc.date.submitted | 2012-08-14 | |
dc.identifier.citation | 1.IOF, Fixed risk factors. 2012. http://testsite.iofbonehealth.org/docs/patients-public/about-osteoporosis/symptoms-risk-factors/fixed.html
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BMJ, 1994. 309(6956): p. 691-695. 7.A Levin. GL Bakris, M.M., M Smulders, J Tian, LA Williams. et al., Prevalence of abnormal serum vitamin D, PTH, calcium, and phosphorus in patients with chronic kidney disease: results of the study to evaluate early kidney disease. Kidney Int. , 2007. 71: p. 31-38. 8.Mohammed S. Razzaque, R.S.-A., Takashi Taguchi,Beate Lanske, FGF-23, vitamin D and calcification: the unholy triad Nephrol. Dial. Transplant, 2005. 20: p. 2032-2035. 9.Fre´de´ric D. Debelle, J.-L.V., Joe¨lle L. Nortier, Aristolochic acid nephropathy: A worldwide problem. Kidney Int 2008. 74: p. 158-169. 10.Chi Pang Wen, T.Y.D.C., Min Kuang Tsai, Yen Chen Chang, Hui Ting Chan, Shan Pou Tsai. et al., All-cause mortality attributable to chronic kidney disease: a prospective cohort study based on 462293 adults in Taiwan Lancet, 2008. 371: p. 2173-2182. 11.Mark S. Stein, D.K.P., Peter R. Ebeling, Gavin J. Becker, Prevalence and risk factors for osteopenia in dialysis patients. Am J Kidney Dis, 1996. 28: p. 515-522. 12.AM Alem, D.S., DL Gillen, NS Weiss, SA Beresford, SR Heckbert . et al. , Increased risk of hip fracture among patients with end-stage renal disease. Kidney Int, 2000. 58: p. 396-399. 13.Simerjot K. Jassal, D.v.M., Elizabeth Barrett-Connor., Measures of renal function, bone mineral density, bone Loss and osteoporotic fracture in older adults: The Rancho Bernardo Study. J Bone Miner Res, 2007. 22: p. 203-210. 14.Hiroshi Kaji, M.Y., Toru Yamaguchi, Takashi Shigematsu,Toshitsugu Sugimoto, Mild renal dysfunction is a risk factor for a decrease in bone mineral density and vertebral fractures in Japanese postmenopausal women. J Clin Endocrinol Metab, 2010. 95: p. 4635-4642. 15.Hack-Lyoung Kim, I.Y.P., Jin Man Choi, Se-Min Hwang, Hyo Sang Kim, Jae-Sung Lim. et al., A decline in renal function is associated with loss of bone mass in Korean postmenopausal women with mild renal dysfunction J Korean Med Sci, 2011. 26: p. 392-398. 16.Sidney Klawansky, E.E.K., Paul F. Cavanaugh Jr, David Y. Mitchell, Matthew J. Gordon, Janet E. Connelly. et al., Relationship between age, renal function and bone mineral density in the US population. Osteoporos Int, 2003. 14: p. 570-576. 17.Marie Briet, G.e.M., C´edric Collin, Erwan Bozec, C´edric Gauci, Pierre Boutouyriel. et al., Age-independent association between arterial and bone remodeling in mild-to-moderate chronic kidney disease. Nephrol Dial Transplant, 2010. 25: p. 191-197. 18.M Aizawa, H.K., Shimaoka T, Yamaji K, Horikoshi S, Tomino Y., Comparison of prediction equations of glomerular filtration rate in Japanese adults. Nihon Jinzo Gakkai Shi 2006. 48(2): p. 62-66. 19.L Zuo, M.Y., Zhou YH, Wang M, Xu GB, Wang HY. , Application of GFR estimating equations in Chinese patients with chronic kidney disease. Am J Kidney Dis, 2005. 45(3): p. 463-472. 20.Joel S. Finkelstein, S.E.B., Vinay Mehta, Gail A. Greendale, MaryFran R. Sowers,Bruce Ettinger. et al. , Bone mineral density changes during the menopausetransition in a multiethnic cohort of women. J Clin Endocrinol Metab. , 2008. 93(3): p. 861-868. 21.Schunkert, D., Hense, Derkx, Kurzinger, Riegger, Effects of estrogen replacement therapy on the renin-angiotensin system in postmenopausal women Circulation, 1997. 95: p. 39-45. 22.Paul Munter, J.C., J.Clinton Smith, John Eckfeldt, Micheal J. Klag Plasma lipids and risk of developing renal dysfunction:The Atherosclerosis Risk in Communities Study. Kidney Int, 2000. 58: p. 293-301. 23.Hyun Soon Lee, C.Y.S., Oxidized low-density lipoprotein and oxidative stress in the development of glomerulosclerosis Am J Nephrol 2009. 29: p. 62-70. 24.Masanobu Kawai, C.J.R., The insulin-like growth factor system in bone: basic and clinical implications. Endocrinol Metab Clin N Am, 2012. 41: p. 323-333. 25.Farhad Parhami, A.G., Linda L. Demer, Role of lipid in osteoporosis. arterioscler thromb vasc biol, 2000. 20: p. 2346-2348. 26.Woo, J., Dietary intake, blood pressure and osteoporosis. Journal of Human Hypertension 2009. 23: p. 451-455. 27.Francesco P Cappuccio, E.M., Joseph M Zmuda, Jane A Cauley, High blood pressure and bone-mineral loss in elderly white women: a prospective study The Lancet, 1999. 354(9183): p. 971-975. | |
dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/64435 | - |
dc.description.abstract | 背景介紹
研究發現慢性腎臟疾病與骨質疏鬆症相關聯。少數幾個研究曾探討輕度慢性腎臟疾病與骨質密度間關聯性,但是停經作用是否影響此關聯卻從未被探討過且無研究同時探討停經前及之後的個案。 材料與方法 此為一個橫斷性研究。於2009-2010年間在台灣台北市美兆健檢中心收案,共招募1,575位受試者,年紀40-55歲停經前與停經後婦女。骨質密度使用雙光子骨密度檢測法 (dual-energy x-ray absorptiometry, DXA)測量受試者的腰椎骨質密度。腎功能估計使用Modification of Diet in Renal Disease (MDRD)公式和Cockcroft-Gault公式。統計方式使用多變項邏輯式迴歸分析及一般線性迴歸分析探討腎功能與骨質密度間關聯性。另外,根據停經狀態與是否使用中藥分別做分層分析。 結果 較低的估計腎絲球過濾速率,其低骨質密度的風險會降低 (估計腎絲球過濾速率: <80 vs. ≥ 80 毫升/分鐘/1.73平方公尺: 校正勝算比=0.63, 95%信賴區間=0.48-0.82)。較低的肌酸酐清除率則會增加低骨質密度的風險(肌酸酐清除率: <78 vs. ≥ 78 毫升/分鐘,校正勝算比=1.42,95%信賴區間 =1.10-1.84)。分層之後,較低的估計腎絲球過濾速率比起較高者在停經前婦女(估計腎絲球過濾速率< 80 vs. ≥ 80 毫升/分鐘/1.73平方公尺:校正勝算比=0.55,95%信賴區間=0.40-0.75),以及沒有使用中藥的婦女(估計腎絲球過濾速率: <80 vs. ≥ 80毫升/分鐘/1.73平方公尺,校正勝算比=0.59,95%信賴區間=0.45-0.77),低骨質密度的風險會降低。使用中藥與否會影響估計腎絲球過濾速率與骨質密度間的關聯性(P值=0.03)。於停經後婦女卻觀察到與停經前婦女相反的結果(估計腎絲球過濾速率: <80 vs. ≥ 80毫升/分鐘/1.73平方公尺,校正勝算比=2.21,95% 信賴區間=1.43-3.41; < 80毫升/分鐘/1.73平方公尺,校正勝算比=2.05,95%信賴區間=1.30-3.23)。較低的肌酸酐清除率則在停經前的婦女(肌酸酐清除率: <78 vs. ≥ 78 毫升/分鐘,校正勝算比=1.36, 95%信賴區間= 1.02-1.81),停經後的婦女 (肌酸酐清除率: ≥ 78 毫升/分鐘,校正勝算比=2.49,95%信賴區間=1.52-4.07; <78毫升/分鐘: 校正勝算比=3.96,95%信賴區間=2.57-6.12),以及沒有使用中藥的婦女 (校正勝算比=1.46,95%信賴區間= 1.12-1.90),均會增加低骨質密度的風險。骨質密度在停經前婦女較停經後顯著的較高 (1.21 vs. 1.10 克/平方公尺, p值<0.0001)。 結論 較低的肌酸酐清除率會增加低骨質密度的風險,尤其在停經前、停經後婦女與沒有使用中藥的婦女。估計腎絲球過濾速率有著相反的結果,可能是由於公式中沒有包含體重,而體重是骨質密度的一個很重要預測因子。 | zh_TW |
dc.description.abstract | Introduction: Chronic kidney disease has been associated with osteoporosis. Few studies have explored the association between mild renal dysfunction and bone mineral density (BMD). In addition, menopausal status was not considered while assessing this association as previous studies only included postmenopausal women.
Material and Methods: This is a cross-sectional study. A total of 1,575 women aged 40 to 55 were recruited from MJ health screening center in Taipei between 2009 and 2010. Spinal BMD was assessed by dual-energy x-ray absorptiometry. Renal function was estimated by Modification of Diet in Renal Disease equation and Cockcroft-Gault equation. Multivariate logistic regression model and generalized linear model were applied to assess the association between renal function and BMD. Stratification analyses were performed by menopausal status and use of Chinese herb, respectively. Results: Low estimated glomerular filtration rate (eGFR) was associated with decreased risk of low BMD [eGFR :<80 vs. ≥ 80 mL/mins/1.73m2, adjusted odds ratio (AOR) =0.63, 95% confidence interval (CI)=0.48-0.82]. In contrast, low creatinine clearance rate (CCr) was associated with increased risk of low BMD (CCr : <78 vs. ≥ 78 mL/mins, AOR=1.42, 95% CI=1.10-1.84). BMD level was significantly different between pre- and postmenopausal women (1.21 vs. 1.10 g/m2, p<0.0001). Chinese herb, but not menopausal status, significantly modify the association between eGFR and the risk of low BMD (P interaction=0.03). After stratification, low eGFR was associated with low BMD in premenopausal women (eGFR < 80 vs. ≥ 80 mL/mins/1.73m2: AOR=0.55, 95% CI=0.40-0.75), and in women who did not use of Chinese herb (eGFR: <80 vs. ≥ 80 mL/mins/1.73m2, AOR=0.59, 95% CI=0.45-0.77). An opposite association was observed in postmenopausal women (eGFR; ≥ 80 mL/mins/1.73m2: AOR=2.21, 95% CI=1.43-3.41; < 80 mL/mins/1.73m2: AOR=2.05, 95% CI=1.30-3.23). Low CCr was associated with increased risk of low BMD in premenopausal women (CCr <78 vs. ≥ 78 mL/mins AOR=1.36, 95% CI= 1.02-1.81), postmenopausal women ( CCr ≥ 78 mL/mins: AOR=2.49, 95% CI=1.52-4.07; <78 mL/mins: AOR=3.96, 95% CI=2.57-6.12) , and women who did not use of Chinese herb (CCr < 78 vs. ≥ 78 mL/mins: AOR=1.46, 95% CI= 1.12-1.90). Conclusion: Low CCr was associated with increased risk of low BMD, especially in premenopausal, postmenopausal women, and women who did not use of Chinese herb, respectively. In contrast, eGFR showed opposite association because the important predictor of BMD, body weight, was not incorporated in it. | en |
dc.description.provenance | Made available in DSpace on 2021-06-16T17:47:01Z (GMT). No. of bitstreams: 1 ntu-101-R99849040-1.pdf: 2827473 bytes, checksum: 1f767a0193bee434ddd7af4a4804e30b (MD5) Previous issue date: 2012 | en |
dc.description.tableofcontents | Index
口試委員審定書…………………………………………………………………..5 誌謝………………………………………………………………..6 中文摘要…………………………………………………………..7 Abstract…………………………………………………………..9 Chapter 1. Introduction 1.1 Importance of osteoporosis.......................11 1.2 Renal functions..................................11 1.3 Epidemiologic studies relating renal function and bone mineral density......................................12 1.4 Aims.............................................13 Chapter 2. Materials and Methods 2.1 Study population.................................15 2.2 Bone mineral density measurement.................16 2.3 Renal function assessment and biochemical measurements.........................................16 2.4 Statistical analyses.............................17 Chapter 3. Results 3.1 Characteristics of the study population...........19 3.2 Association between estimated glomerular filtration rate or creatinine clearance rate and BMD.............20 3.3 Effect modification by menopausal status..........20 3.4 Effect modification by the use of Chinese herb....21 3.5 Effect modification by alkaline phosphatase level.22 3.6 Effect modification by vascular risk factors......23 3.7 Effect modification by body weight............25 Chapter4. Discussions 4.1 Association of renal function with BMD and comparison with previous studies..................................27 4.2 Effect modification by menopausal status, the use of Chinese herb, and ALP.................................27 4.3 Effect modification by vascular risk factor.......29 4.4 Effect modification by body weight ...............29 4.5 Strengths and limitations.........................30 4.6 Conclusions.......................................31 References............................................32 Figure Index Figure 1. Flowchart of participant recruitment.........35 Figure 2. Scatter plots between important variables....36 Figure 3.(a) The distribution of age in the study population..............................................37 (b) The distribution of body weight in the study population ............................................,37 (c) The distribution of estimated glomerular filtration rate of the study population............................38 (d) The distribution of creatinine clearance rate of the study population........................................38 (e) The distribution of bone mineral density of the study population..............................................39 Figure 4.(a) Spline curve of BMD by body weight.........40 (b) Spline curve of BMD by estimated glomerular filtration .............................................41 (c) Spline curve of BMD by creatinine clearance rate....42 (d) Spline curve of BMD by creatinine clearance rate/ body weight..................................................43 Figure 5. Postulated mechanism relating renal function with bone mineral density and important factors..............44 Table Index Table 1.Thesis of mild renal dysfunction and bone mineral density.................................................45 Table 2. Cutoff points of important variables...........47 Table 3. Characteristics of the study population ........48 Table 4. Age-adjusted Spearman correlation coefficients between important covariates............................49 Table 5. Model comparisons for the association between estimated glomerlar filtration rate or creatinine clearance rate and bone mineral density (T1 vs. T2+T3 ..................................................50 Table 6. Association between estimated glomerlar filtration rate or creatinine clearance rate and bone mineral density (T1 vs. T2 + T3)........................................52 Table 7. Association between eGFR or CCr and bone mineral density by menopausal status............................54 Table 8. Association between eGFR or CCr and bone mineral density by use of Chinese herb..........................56 Table 9. Association between eGFR or CCr and bone mineral density by alkaline phosphatase.........................58 Table 10. Association between eGFR or CCr and bone mineral density by fasting glucose..............................61 Table 11. Association between estimated glomerlar filtration rate or creatinine clearance rate and bone mineral density by low-density lipoprotein cholesterol..64 Table 12. Association between eGFR or CCr and bone mineral density by systolic blood pressure......................67 Table 13. Association between eGFR or CCr and bone mineral density bybody weight...................................70 | |
dc.language.iso | en | |
dc.title | 台灣女性之腎功能、停經狀態與骨質密度關聯性研究 | zh_TW |
dc.title | Association of Renal Function, Menopausal Status, with Bone Mineral Density in Taiwanese Women | en |
dc.type | Thesis | |
dc.date.schoolyear | 100-2 | |
dc.description.degree | 碩士 | |
dc.contributor.oralexamcommittee | 簡國龍,蔡克嵩(Keh-Sung Tsai),丘政民(Jeng-Min Chiou) | |
dc.subject.keyword | 腎功能,停經狀態,中藥使用,骨質密度, | zh_TW |
dc.subject.keyword | renal function,menopausal status,use of Chinese herb,bone mineral density, | en |
dc.relation.page | 72 | |
dc.rights.note | 有償授權 | |
dc.date.accepted | 2012-08-14 | |
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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