請用此 Handle URI 來引用此文件:
http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/43164
標題: | 牙周病之結構方程模型 Structural Equation Model for Periodontal Disease |
作者: | Wu-Han Chang 張婺涵 |
指導教授: | 陳秀熙(Hsiu-Hsi Chen) |
關鍵字: | 主成分分析,因子分析,結構方程模型,牙周病, Principal Components Analysis,Factor Analysis,Structural Equation Model,Periodontal disease, |
出版年 : | 2011 |
學位: | 碩士 |
摘要: | 研究背景:
傳統上,探討牙周病危險因子之關係時,採用二元變項為主之羅吉斯迴歸分析。就統計觀點而言,這些影響因子之間常存有高度相關問題。就牙周病預防而言,傳統方法的最大缺點是無法了解導致牙周病因子之因果路徑關係。 研究目的: 透過因果關係的示意圖,以結構方程模型建立導致牙周病的相關因子路徑分析。 材料與方法: 本研究所使用的資料主要為台灣地區18歲以上人口於牙周病盛行率及危險因子的調查結果,共計4061位民眾。蒐集牙周病指數、牙周病知識、生活型態、飲食習慣及生化值五種資料。首先透過因子分析求得牙周病之組成因子,接著利用驗證性因子分析建立測量模型以求得各資料間的共變關係,最後建立牙周病之結構方程模型,將生活型態與牙周病知識視為外生變項,而生化值及牙周病指數視為內生變項。 研究結果: 因子分析結果求得四個架構:牙周病知識、生活型態、飲食習慣及生化檢驗值。測量模型中,牙周病知識與牙周病指數有負向關係(-0.6528,p-value<0.0001),生活型態與生化值有正向關係(0.6582,p-value<0.0001),生化值與牙周病指數有正向關係(0.3705,p-value<0.0001)。從結果發現:牙周病知識對於牙周病指數有直接效應(-0.6350,p-value=0.0230),與生活型態有共變關係存在(-0.2935,p-value=0.0099),生活型態對於生化值有直接效應 (1.1255,p-value<0.0001),影響牙周病指數(0.0663,p-value=0.0038)。 結論: 藉由結構方程模型的應用,證實所建立的路徑:牙周病知識對於牙周病指數的直接效應,生活型態透過生化值對於牙周病指數的間接效應。 Background: Logistic regression model with binary outcome of periodontal disease (PD) has been traditionally used to investigate the associated risk factors. From statistical viewpoint, this approach dose not deal with the highly correlations between risk factors. From the preventive medicine viewpoint, the traditional approach fails to elucidate the causal relationships and pathways interplayed by these risk factors in association with PD. Aim: The aim of our study is to apply a series of structural equation models to build up a pathway diagram leading to PD through a series of causal relationships. Materials and Methods: Our study was based on national survey of the prevalence and risk factors in association with PD for adults aged 18 years on older in Taiwan. The sample size was 4061. Data on periodontal indexes, periodontal knowledge, lifestyle, eating habits and biomarkers were collected. Factor analysis was firstly used to find the construct aggregated by similar variables in each dimension. The measurement model is further built by using confirmatory factor analysis (CFA) to assess the covariance between constructs in addition to the relationship between variables and each construct. Finally, we built up the structural equation model (SEM) for PD by extending CFA. Result: Factor analysis was performed to form four constructs, periodontal knowledge, life style, eating habits and biomarkers. In measurement model, periodontal knowledge has negative relationship with periodontal indexes (-0.6528,p-value<0.0001), lifestyle has posistive relationship with biomarkers (0.6582,p-value<0.0001) and biomarkers has positive relationship with periodontal indexes (0.3705,p-value<0.0001). The exogenous variables in SEM are life style and periodontal knowledge, we found that the periodontal knowledge has direct effect on periodontal indexes (-0.6350,p-value=0.0230). Lifestyle, correlated to periodontal knowledge, may affect biomarkers (1.1255,p-value<0.0001) and, in turn, affect periodontal indexes (0.0663,p-value=0.0038). Conclusion: By the application of structural equation model, we constructed a pathway whereby the direct effect of periodontal knowledge and indirect effect of lifestyle through the influence of biomarkers on PD was demonstrated. |
URI: | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/43164 |
全文授權: | 有償授權 |
顯示於系所單位: | 流行病學與預防醫學研究所 |
文件中的檔案:
檔案 | 大小 | 格式 | |
---|---|---|---|
ntu-100-1.pdf 目前未授權公開取用 | 1.09 MB | Adobe PDF |
系統中的文件,除了特別指名其著作權條款之外,均受到著作權保護,並且保留所有的權利。