停經婦女骨質疏鬆危險因子分析及預測模型之建立

Identifying the Risk Factors and Establishing a Predictive Model of Osteoporosis in Menopause Women

詹文泰(Wen-Tai Chan)

指導教授 ： 詹前隆

元智大學/資訊學院/資訊管理學系/碩士(2008年)

摘要

本研究目的在找出影響停經婦女罹患骨質疏鬆症的獨立危險因子，建立台灣停經婦女骨質疏鬆風險預測模型，提供年齡、體重、身高、貝克憂鬱量表及Web平台網站登入，自動計算骨質疏鬆風險機率預測，達到個人建康的預防保健及臨床診療指引的參考。

本研究之樣本來源以某醫學中心婦科停經門診的病人為基本取樣對象，採立意取樣方式，共取樣450位之停經婦女及門診問卷、憂鬱量表問卷有效樣本收集，進行本項研究。
使用邏輯斯迴歸分析統計推論，來分析變項，與依變項「骨質疏鬆與否」之間的關係性，以二元邏輯斯迴歸，明確找出危險因子在統計上顯著的影響，本研究法採橫斷式研究，根據研究目的將描述性的研究結果，以平均數±標準偏差及百分率來表示。不同變項資料依據變項之屬性進行推論，若屬連續性變項之資料接受獨立樣本t檢定及單因子變異數分析來比較其差異是否顯著。 至於資料屬於非連續變項者(類別變數)，則以Chi-Square Test(卡方檢定) 檢定來探討與骨質疏鬆症間之相關性，找出顯著之骨質疏鬆症相關因子後，再以Forward Logistic regress (羅吉斯回歸分析)，檢定出真正不受干擾獨立顯著有關之變項，並建立邏輯斯回歸預測模型。
運用多變量邏輯斯迴歸分析，逐步迴歸分析後，結果發現年齡、身體質量、憂鬱症有統計上獨立顯著意義。
結論：
憂鬱症為骨質疏鬆症獨立危險因子。罹患骨質疏鬆症的風險，有憂鬱症的人是無憂鬱症的exp(0.756)=2.129倍。
身體質量指數為骨質疏鬆症獨立危險因子。罹患骨質疏鬆症的風險與身體質量指數有關，且BMI每增加一個單位，罹患骨質疏鬆的風險比是exp(-0.129)=0.879，換言之減少12.1%。
年齡為骨質疏鬆症獨立危險因子，罹患骨質疏鬆症的風險，年齡每增加一歲，罹患骨質疏鬆症的風險比是exp(0.134) = 1.143倍，每增加一歲，危險性增加14.3%，可見年齡愈大，危險性愈高。
本研究結果最能顯示影響停經婦女罹患骨質疏鬆症的危險因子，結果發現年
齡、身體質量、憂鬱症有統計上獨立顯著意義，並建立為一以證據為基礎的骨質疏鬆症預測模型及機率預測網頁，提供臨床上醫療保健指引參考。

關鍵字

骨質疏鬆 ； 骨質密度 ； 憂鬱症 ； 身體質量指數 ； 危險因子

並列摘要

This study aimed to identify the risk factors associated with osteoporosis in postmenopausal women, establish the predictive model for osteoporosis. In order to provide a reference for personal health care, prevention and clinical diagnosis, we also offered a web-based platform for the estimation of the risk of osteoporosis through the entry of age, body weight, body height, and Becker Depression Inventory.

Postmenopausal women from a Gynecology outpatient department in a medical center were enrolled. The questionnaire and evaluation scale were given to 450 eligible women and the results were analyzed.

Logistic regression analysis was used to identify the potential risk factors associated with the occurrence of osteoporosis in this cross-sectional study. Data were expressed as mean ± standard deviation and percentage for continuous variables and categorical variables, respectively. Student’s t-test or one-way ANOVA were used for continuous variables while Chi-square test was used for categorical variables in univariate analysis. In order to identify independent risk factors in the prediction model, variables that were significant in the univariate analysis were further evaluated with stepwise logistic regression in forward manner.

Age, BMI, BDI were identified independent risk factors for osteoporosis in postmenopausal women.

Conclusions:
BDI is an independent risk factor for osteoporosis with an odds ratio of 2.129. In addition, body mass index (BMI) is also an independent risk factor for osteoporosis. There is an 87.9% decrease of the risk of osteoporosis per unit increase of BMI, suggesting that osteoporosis more often occurs in non-obese people.
Age is another independent risk factor for osteoporosis. There is a 1.143-fold risk of osteoporosis per one-year increase in age, suggesting the risk for osteoporosis progressively increases with increasing age.
Our study indicates that age, BMI, BDI are independent risk factors for osteoporosis in postmenopausal women. We establish a useful and feasible predictive model for risk estimation using a web-based approach that may provide important information for health care.

並列關鍵字

Osteoporosis ； Bone mineral density ； Depression ； Body Mass Index ； Risk factor

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