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完整後設資料紀錄
DC 欄位 | 值 | 語言 |
---|---|---|
dc.contributor.advisor | 林先和(Hsien-Ho Lin) | |
dc.contributor.author | Chieh-Yin Wu | en |
dc.contributor.author | 伍倢瑩 | zh_TW |
dc.date.accessioned | 2021-06-15T16:09:37Z | - |
dc.date.available | 2017-09-14 | |
dc.date.copyright | 2015-09-14 | |
dc.date.issued | 2015 | |
dc.date.submitted | 2015-08-18 | |
dc.identifier.citation | 1. WHO, Global Tuberculosis Report. 2014.
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Di Castelnuovo, A., et al., Spousal concordance for major coronary risk factors: a systematic review and meta-analysis. Am J Epidemiol, 2009. 169(1): p. 1-8. 13. Silventoinen, K., et al., Assortative mating by body height and BMI: Finnish twins and their spouses. Am J Hum Biol, 2003. 15(5): p. 620-7. 14. Andrews, J.R., et al., The epidemiological advantage of preferential targeting of tuberculosis control at the poor. Int J Tuberc Lung Dis, 2015. 19(4): p. 375-80. 15. UNPD, World Population Prospects: The 2012 Revision. 16. Cegielski, J.P., Arab, L., & Cornoni-Huntley, J., Nutritional risk factors for tuberculosis among adults in the United States, 1971–1992. American journal of epidemiology, 2012. kws007. 17. Chandra, R.K., 1990 McCollum Award lecture. Nutrition and immunity: lessons from the past and new insights into the future. Am J Clin Nutr, 1991. 53(5): p. 1087-101. 18. Kim, H.J., et al., The impact of nutritional deficit on mortality of in-patients with pulmonary tuberculosis. 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BMC Public Health, 2014. 14: p. 371. 24. Whitlock, G., et al., Body-mass index and cause-specific mortality in 900 000 adults: collaborative analyses of 57 prospective studies. Lancet, 2009. 373(9669): p. 1083-96. 25. Yiengprugsawan, V., et al., Relationship between Body Mass Index Reference and All-Cause Mortality: Evidence from a Large Cohort of Thai Adults. Journal of Obesity, 2014. 2014: p. 6. 26. Getahun, B., et al., Mortality and associated risk factors in a cohort of tuberculosis patients treated under DOTS programme in Addis Ababa, Ethiopia. BMC Infect Dis, 2011. 11: p. 127. 27. Santha, T., Garg, R., Frieden, T., Chandrasekaran, V., Subramani, R., Gopi, P., ... & Narayanan, P., Risk factors associated with default, failure and death among tuberculosis patients treated in a DOTS programme in Tiruvallur District, South India, 2000. The International Journal of Tuberculosis and Lung Disease, 2002. 6(9): p. 780-788. 28. Murray, M., O. Oxlade, and H.H. Lin, Modeling social, environmental and biological determinants of tuberculosis. Int J Tuberc Lung Dis, 2011. 15 Suppl 2: p. S64-70. 29. Oxlade, O., C.C. Huang, and M. Murray, Estimating the Impact of Reducing Under-Nutrition on the Tuberculosis Epidemic in the Central Eastern States of India: A Dynamic Modeling Study. PLoS One, 2015. 10(6): p. e0128187. 30. Leung, C.C., Lam, T. H., Chan, W. M., Yew, W. W., Ho, K. S., Leung, G., ... & Chang, K. C., Lower risk of tuberculosis in obesity. Archives of internal medicine, 2007. 167(12): p. 1297-1304. 31. Stevens, G.A., Singh, G. M., Lu, Y., Danaei, G., Lin, J. K., Finucane, M. M., ... & Ezzati, M., National, regional, and global trends in adult overweight and obesity prevalences. Popul Health Metr, 2012. 10(1): p. 22. 32. Vynnycky E, F.P., The natural history of tuberculosis: the implications of age-dependent risks of disease and the role of reinfection. Epidemiology and infection, 1997. 119(02): p. 183-201. 33. Dye C, G.G., Sleeman K, Williams BG, Prospects for worldwide tuberculosis control under the WHO DOTS strategy. Directly observed short-course therapy. Lancet 1998. 52(9144): p. 1886-1891. 34. Hughes G, C.C., Corbett EL, Modeling tuberculosis in areas of high HIV prevalence. Proceedings of the 38th conference on Winter simulation, 2006: p. 459-465. 35. Andrews JR, N.F., Walensky RP, Cerda R, Losina E, Horsburgh CR, Risk of Progression to Active Tuberculosis Following Reinfection With Mycobacterium tuberculosis. Clinical Infectious Diseases, 2012. 54(6): p. 784-91. | |
dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/52211 | - |
dc.description.abstract | 背景
營養不良為結核病重要的危險因子之一。過去的研究是利用population attributable fraction (PAF) 評估降低營養不良盛行率對於結核病控制的影響,PAF的估計方法假設疾病傳播間是獨立的,但在傳染性疾病上違反此假設,因此可能低估其影響。我們利用動態數理模型的方法,在考量疾病傳播的相依性下,來評估營養不良盛行率變化對於結核病控制的影響。 方法 我們在中國和印度各建立一個動態數理模型,且將模型調整符合近五年結核病發生率變化。模型中我們根據文獻回顧,假定營養不良的人會增加結核病發病率及死亡率,而營養不良盛行率變化趨勢為參考一篇系統性分析的數據。我們設定三個不同的營養不良盛行率變化情況,來評估營養不良對於結核病至2035年累積發生率的影響。 結果 遵循近年營養不良盛行率下降趨勢的現狀,到2035年時在中國和印度的結核病發生率相較於2015年會分別下降43.0%和32.7%。若是較差的情況,2015年後營養不良盛行率不再下降,中國和印度結核病發生率到2035年僅能分別下降40.2%和28.1%,且相較於現狀會多增加28萬和97萬個結核病個案。而若2030年前達到營養不良盛行率為零的最佳情況下,結核病發生率至2035年分別在中國和印度能下降43.2%和47.5%,相較於現狀會預防5萬和420萬個結核病個案。若接觸模式為非隨機的狀況,而是同樣的營養狀態較易互相接觸,降低營養不良盛行率對於結核病發生率下降的影響更大。 討論與結論 若2030年前能達到營養不良盛行率降為零的目標,能避免許多結核病的發生數,尤其是在營養不良盛行率較高的國家,如印度,降低營養不良盛行率對於結核病控制的效果更明顯。另外,此結果指出除了傳統的結核病診斷與治療,減少結核病危險因子(如營養不良)也是重要的結核病防治方法之一,更能快速達到End TB策略的目標。 | zh_TW |
dc.description.abstract | Background
Underweight has been identified as a risk factor for tuberculosis (TB). Past studies estimated the impact of reducing underweight on TB using the method of population attributable fraction, which did not account for the effect of transmission and may therefore underestimate the impact. Mathematical model was used in this study to account for the indirect effect of transmission and to estimate the impact of the shift in underweight prevalence on the control of TB. Design/Methods We constructed dynamic compartmental models of TB transmission in China and India. The models were calibrated to the estimated trend of TB incidence respectively. The effects of underweight on the progression from latent infection to active disease and on mortality were based on literature review. The prevalence of underweight was based on the estimates from updates of a global systematic analysis. We estimated the cumulative reduction of TB incidence between 2015 and 2035 under three different scenarios of underweight prevalence. Results In the base case scenario where the trend of underweight continues its current trend, the incidence of TB is projected to fall by 43.0% and 32.7% respectively in China and India between 2015 and 2035. If the trend of underweight stops to decline after year 2015 (worst case), the reductions of TB incidence in China and India will be 40.2% and 28.1% respectively by 2035, and there will be 0.28 million and 0.97 million more TB cases over 20 years when compared to the base case. In the best case scenario where the end-hunger target of the Sustainable Development Goals is achieved by 2030, the reduction of incidence will accelerate to 43.2% in China and 47.5% in India, preventing 50 thousand and 4.2 million TB cases respectively over 20 years. If the contact pattern among individuals is not random and people from the same group (e.g., the underweight group) are more likely to make contact with each other, the effect of reducing underweight will be more significant. Conclusion If the target of end hunger is reached by 2030, many TB cases can be avoided especially in the places with higher burden of underweight like India. In addition to diagnosis and treatment of active cases, reducing the risk factors and determinants of TB such as underweight will likely be an important component in TB control in the march towards the goals of End TB strategy. | en |
dc.description.provenance | Made available in DSpace on 2021-06-15T16:09:37Z (GMT). No. of bitstreams: 1 ntu-104-R02849002-1.pdf: 2102687 bytes, checksum: 726c33d679f06d5cfe357e8289714393 (MD5) Previous issue date: 2015 | en |
dc.description.tableofcontents | 摘要 ………………………………………….……………………………..………. i
Abstract …………………………………………………………………………..… iii Chapter1 Introduction ………………………………………………….….......... 1 1.1 Background …………………….………………………………..…. 1 1.2 Nutrition status and tuberculosis ………..………………………..… 1 1.3 Measuring TB burden and research gap …………..….………..…… 2 1.4 Research aim ……………………………………………..……...…. 3 Chapter2 Methods ……….………………………………………………..…….. 4 2.1 Analytical model and settings ……………………….…………..…. 4 2.2 Data sources and model calibration …………...………………….... 4 2.3 Relative risks for underweight …………………………….……….. 4 2.4 Outcome measurements and scenarios of underweight trend …….... 5 2.5 Modelling non-random mixing …………………………………….. 6 2.6 Sensitivity analyses ………………….……………………………... 6 Chapter3 Results ……………………………………………..…………...……. 8 Chapter4 Discussion ………………………………………..…………..……….10 References………………………………………………...………………………. 24 Appendix………………………………………………………………………….. 27 | |
dc.language.iso | en | |
dc.title | 以數理模型評估促進群體營養狀態對於結核病防治的影響 | zh_TW |
dc.title | Impact of Reducing Underweight on the Control of tuberculosis in China and India: A Modelling Study | en |
dc.type | Thesis | |
dc.date.schoolyear | 103-2 | |
dc.description.degree | 碩士 | |
dc.contributor.oralexamcommittee | 江振源(Chen-Yuan Chiang),方啟泰(Chi-Tai Fang) | |
dc.subject.keyword | 結核病,危險因子,營養不良,動態數理模型,中國,印度, | zh_TW |
dc.subject.keyword | Tuberculosis,risk factor,underweight,dynamic modelling,contact pattern,China,India, | en |
dc.relation.page | 34 | |
dc.rights.note | 有償授權 | |
dc.date.accepted | 2015-08-19 | |
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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