Abstract
宋国慧,孟凡书,陈超,陈志峰.食管癌高发区早诊早治内镜普查顺应性调查[J].Chinese journal of Epidemiology,2009,30(9):977-978
食管癌高发区早诊早治内镜普查顺应性调查
Analysis on the factors influencing the compliance to endoscopic screening for early diagnosis and treatment in High-risk area of esophageal cancer
Received:February 25, 2009  Revised:November 23, 2007
DOI:
KeyWord: 食管癌  顺应性  普查
English Key Word: Esophageal cancer  Compliance  Screening
FundProject:上海市科委重大项目基金资助(04DEl9501)
Author NameAffiliationE-mail
SONG Guohui Cixian Cancer Institute, Cixian, 056500, China  
MENG Fanshu Cixian Cancer Institute, Cixian, 056500, China  
CHEN Chao Cixian Cancer Institute, Cixian, 056500, China  
CHEN Xiaofeng 河北省肿瘤研究所 sghui2009@163.com 
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Abstract:
      食管癌的筛查除与防治策略本身有关外,还与人群的认识和接受程度有很大关系?,接受程度高其顺应性就高,反之亦然,从而影响阳性病例的检出率及早期诊断率。为此本研究对磁县食管癌早诊早治普查顺应性进行分析,探讨高发区食管癌内镜普查的影响因素,以提高食管癌早诊率。
English Abstract:
      To elucidate the principal of orthogonal factor analysis, using an example of factor analysis of metabolic syndrome. The basic structures and the fundamental concepts of orthogonal factor analysis were introduced and data involving 1877 women aged of 35-65 years,selected from a cross-sectional study,which was conducted in 1998一2001 in Shanghai,were included in this study. Factor analysis was carried out using principle components analysis with Varimax orthogonal rotation of the components of the metabolic syndrome. The different components of the metabolic syndrome were not linked closely with the other components and loaded on the six different factors,which mainly reflected by the variables of obesity, blood pressure, plasma glucose, plasma insulin, triglycerides and IIDL-cholesterol respectively. Six major factors of the metabolic syndrome were uncorrelated with each other and explained 86% of the variance in the original data. The factor score and total factor score for the individual could be obtained according to the component score coefficient matrix. Although the components of the metabolic syndrome were related statistically, the finding of six factors suggested that the components of the metabolic syndrome did not show high degrees of intercorrelation. As a linear method of data reduction, the mode reduced a large set of measured intercorrelation variables into a smaller set of uncorreiated factors, which explained the majority of the variance in the original variables. Factor analysis was well suited for revealing underlying patterns or structure among variables showing high degrees of intercorrelation
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