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基于潜变量与空间统计理论的耐多药结核病空间流行病学模型研究 被引量:3

Spatial Epidemiology Model about Multidrug-resistant TB Based on the Theory of Latent Variable and Spatial Statistics
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摘要 目的探讨耐多药结核病及其影响因素间的关系。方法利用全球耐多药结核病监测资料,基于潜变量分析理论和空间统计学方法,首先通过证实性因子分析从耐多药结核病影响因素中提取综合潜在影响因子,然后采用Kriging法估计综合潜在影响因子及耐多药率的空间分布,在此基础上分别构建耐多药率与其综合潜在影响因子之间的多元线性回归模型(全局模型)和GWR模型(局部模型),探讨耐多药率与综合潜在影响因子间的关系。结果经证实性因子分析共提取了6个综合潜在影响因子。全局模型显示,6个潜在影响因子均与耐多药率有关(P值均小于0.01);GWR局部模型显示,各模型的R2及参数估计值均呈显著的空间变异,其拟合效果优于全局模型。结论 GWR模型揭示综合潜在影响因子对结核病耐多药率的影响存在空间变异性;应根据各综合潜在影响因子的空间特征及其与耐多药率间的局域关系制定区域化的耐多药结核病监测规划和防控策略。 Objective To investigate the relationship between multidrug-resistant TB(MDR-TB) and its' influencing factors.MethodsUsing the global MDR-TB surveillance datas,based on latent variable analysis theory and the spatial statistics method,we first extracted the integrated potential impact factors from the influencing factors of MDR-TB by confirmatory factor analysis;secondly,used kriging method to estimate the spatial distribution of the integrated potential impact factors and MDR-TB rate;then,constructed multiple linear regression model(global model) and geographical weighted regression model(GWR)(local model) about MDR-TB rate and the integrated potential impact factors to explore the relationship between MDR-TB rate and the integrated potential impact factors.Results Six potential impact factors were extracted by confirmatory factor analysis.Global model showed that six potential factors were all related with MDR-TB rate(P0.01);GWR model displayed R2 and parameter estimation of each local model appeared significant spatial variability,and its' fitting effect was better than the global model.Conclusion The effect of the integrated potential impact factors on MDR-TB rate present spatial variability;so we should formulate local MDR-TB monitoring planning and prevention and control strategies based on the spatial characteristic of the integrated potential impact factors and the local relationship with MDR-TB.
出处 《中国卫生统计》 CSCD 北大核心 2011年第6期648-653,657,共7页 Chinese Journal of Health Statistics
基金 国家传染病重大专项资助(结核病发病模式研究 2008ZX10003-007) 国家自然科学基金青年基金项目资助(81001292)
关键词 耐多药结核病 影响因素 因子分析 Kriging法 地理权重回归 MDR-TB Influencing factors Factor analysis Kriging method Geographical weighted regression
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  • 1郭述良.多重耐药结核的发生[J].国外医学(内科学分册),1996,23(7):294-297. 被引量:5
  • 2宋文虎.结核病的治疗方针[J].中级医刊,1997,32(4):36-36. 被引量:1
  • 3K.G.Joreskog and D.Sorbom, LISRELS: User's Reference Guide Scientific Software International [Z] . 1996.
  • 4Joreskog, K.G.Latent variables scores and their uses.2000.7,http: //www.ssicentral.com.
  • 5K.G.Joreskog, D.Sorbom, S.H.C du Toit & M.du Toit. LISREL 8:New Statistical Features(second printing with revisions) [Z]. Chicago: Scientific Software International,2000.
  • 6Joreskog and D.Sorbom, LISREL 8: Structural Equation Modeling with the SIMPLIS Command Language Scientific Software International[Z].1993.
  • 7Long ER,Ferebee SH.A controlled investigation of streptomycin treat ment in pul monary tuberculosis. Public Health Reviews . 1950
  • 8American Thoracic Society.Treat ment of drug-resistant tuberculosis.Astatement by the Committee on Therapy. The American Review of Respiratory Disease . 1966
  • 9World Health Organization.The global MDR-TB&XDR-TB response plan2007—2008. WHO/HTM/STB/2007.2007.387 . 2007
  • 10Caminero JA.Extensively drug-resistant tuberculosis:is its definition correct?(Correspondence). European Respiratory Journal . 2008

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  • 1周晓农,汪天平,王立英,郭家钢,余晴,许静,王汝波,陈朝,贾铁武.中国血吸虫病流行现状分析[J].中华流行病学杂志,2004,25(7):555-558. 被引量:99
  • 2孟海英,刘桂芬,罗天娥.WinBUGS软件应用[J].中国卫生统计,2006,23(4):375-377. 被引量:12
  • 3杨子丹.五峰县2005年-2010年结核病疫情分析[J].中外健康文摘,2011,8(27).
  • 4Liu YN, Wang W, Li X, et al. Geographic distribution and risk factors of the initial adult hospitalized cases of 2009 pandemic influenza A ( H1 N1 ) virus infection in China's Mainland. PLoS One, 2011,6 ( 10 ) : e25934.
  • 5Cowles, MK. Review of WinBUGS 1.4. The American Statistician. 2004 ;58 (4) :330-336.
  • 6Liu Y, Li X, Wang W, et al. Investigation of space-time clusters and geo-spatial hotspots for the occurrence of tuberculosis in Beijing. Inter- national Journal of Tuberculosis and Lung Disease, 2012,16 ( 4 ) : 486 - 491.
  • 7Lawson, AB. Bayes Disease Mapping:Hierarchical Modeling in spatial, 2008.
  • 8Sales CM, Figueiredo TA, Zandonade E, et al. Spatial analysis on child- hood tuberculosis in the state of Espirito Santo, Brazil, 2000 to 2007. Revista da Sociedade Brasileira de Medicina Tropical, 2010,43 ( 4 ) : 435-439.
  • 9周晓农主编.空间流行病学.北京科学出版社,2006.
  • 10Fotheringham AS, Charlton ME. Geographically weighted regression: anatural evolution of the expansion method for spatial data analysis. En-vironment and Planning A, 1998,30: 1905-1927.

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