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醫療從業人員肥胖指標與心血管疾病風險的相關性-以台灣北部某醫院為例

The association between obesity indices and cardiovascular disease risk in a hospital in Northern Taiwan

摘要


目的:心血管疾病在全世界都是很重要的公共衛生議題。本研究的目的是探討內臟脂肪指數(VAI)、腰圍(WC)、身體質量指數(BMI)和佛萊明漢危險預估評分(FRS 2008年版)的相關性。方法:本研究為橫斷面的研究,收錄台灣北部某醫院員工年度健檢報告,所有員工根據佛萊明漢危險預估評分分成10年心血管疾病風險低、中、高三組,再以單因子獨立變異數分析(ANOVA)、卡方檢定(chi-square test)、皮爾森相關係數分析(Pearson correlation)心血管疾病風險高低與內臟脂肪指數(VAI)、腰圍(WC)、身體質量指數(BMI)的相關性。進一步用單變項與多變項羅吉斯迴歸分析求得內臟脂肪指數、腰圍、身體質量指數對心血管疾病風險的勝算比。最後以ROC曲線計算內臟脂肪指數、腰圍、身體質量指數對於心血管疾病風險的預測能力。結果:共有1312位員工納入分析。結果發現三組間的內臟脂肪指數、腰圍、身體質量指數有統計上顯著的差異(p<0.05),而且有隨風險上升而逐漸增加。經由計算內臟脂肪指數、腰圍、身體質量指數與佛萊明漢危險預估評分的皮爾森相關係數,得知兩者亦呈現相關性(<0.001)。多變項羅吉斯迴歸分析發現內臟脂肪指數(Odds ratio=1.38, 95% CI 1.13~1.70)與腰圍(Odds ratio=1.06, 95% CI 1.02~1.11)是中高度心血管疾病風險的危險因子。而針對內臟脂肪指數、腰圍、身體質量指數與心血管疾病風險≧10%繪製ROC曲線由可知,當內臟脂肪指數為0.947;腰圍為82.25(cm);身體質量指數為22.945(kg/m2)時,分別可作為預測中高度心血管疾病風險的最佳切點。結論:在使用三個人體量測的肥胖指標來預測心血管風險,內臟脂肪指數與腰圍比身體質量指數具有較強烈的相關性。因此,對於內臟脂肪指數與腰圍高的員工,醫師可提早介入和衛教,以減少之後心血管疾病發生的風險。

並列摘要


Background and Purpose: Cardiovascular disease (CVD) is a major public health concern around the world. The aim of this study was to investigate the association of visceral adiposity index( VAI), waist circumference(WC), body mass index(BMI) and CVD risk using the 2008 Framingham General Cardiovascular Risk Score(FRS) in Asian adults. Methods: A total of 1312 employees of a local hospital in Taoyuan City, Taiwan (501 men and 811 women, aged 25 to 68 years) were included in the study. All subjects were divided into three groups based on FRS. FRS was used to predict CVD risk and was analyzed in association with VAI, WC and BMI by One way ANOVA, Chi-squared test, Pearson's correlation, multivariate logistic regression and receiver operating characteristic(ROC) curves. Results: Three anthropometric variables of obesity gradually increased from the low to high CVD risk group (p<0.05). A significant association between VAI, WC, BMI and FRS was confirmed with Pearson's correlation coefficients of 0.33 (p<0.001) 0.39 (p<0.001), and 0.25 (p<0.001). The multivariate logistic regression revealed that VAI (OR=1.38) and WC (OR=1.06) are independent predictors of moderate to high CVD risk after adjusting confounding factors, but not in BMI. The area under ROC curves (AUC) of VAI and WC are bigger than BMI (AUC= 0.707, 0.764, 0.657). Conclusion: Among the three anthropometric variables of obesity, VAI and WC had the strongest association with CVD risk than BMI. Individuals with high VAI or WC require more aggressive life style modification and weight control.

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