Structural equation modeling for analyzing erythrocyte fatty acids in Framingham.
Structural equation modeling for analyzing erythrocyte fatty acids in Framingham.
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DOI：
10.1155/2014/160520
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发表时间：
2014
影响因子：
--
通讯作者：
Harris WS
中科院分区：
文献类型：
--
作者：
Pottala JV;Djira GD;Espeland MA;Ye J;Larson MG;Harris WS
研究表明，几种类型的红细胞脂肪酸（即，ω-3、ω-6和反式）与心血管疾病的风险有关。然而，脂肪酸之间存在复杂的代谢和饮食关系，这导致了在将其用作风险预测因子时通常被忽视的相关性。潜变量方法可以将这些复杂的关系总结为几个潜变量分数，用于统计模型。在果糖（N = 3196）中测定了22种红细胞（RBC）脂肪酸。使用结构方程模型对脂肪酸的相关矩阵进行建模;检验模型的拟合优度和性别不变性。十三种脂肪酸由三个潜在变量总结，并且拒绝了性别不变性，因此为男性和女性开发了单独的模型。为多不饱和脂肪酸（PUFA）潜变量开发了一个评分，该变量解释了数据中约30%的方差。PUFA评分包括三种omega-3和三种omega-6脂肪酸之间相反方向的负荷，并纳入它们之间的生物合成和饮食关系。PUFA因子评分是否能提高心血管疾病风险预测的性能仍有待检验。
Research has shown that several types of erythrocyte fatty acids (i.e., omega-3, omega-6, and trans) are associated with risk for cardiovascular diseases. However, there are complex metabolic and dietary relations among fatty acids, which induce correlations that are typically ignored when using them as risk predictors. A latent variable approach could summarize these complex relations into a few latent variable scores for use in statistical models. Twenty-two red blood cell (RBC) fatty acids were measured in Framingham (N = 3196). The correlation matrix of the fatty acids was modeled using structural equation modeling; the model was tested for goodness-of-fit and gender invariance. Thirteen fatty acids were summarized by three latent variables, and gender invariance was rejected so separate models were developed for men and women. A score was developed for the polyunsaturated fatty acid (PUFA) latent variable, which explained about 30% of the variance in the data. The PUFA score included loadings in opposing directions among three omega-3 and three omega-6 fatty acids, and incorporated the biosynthetic and dietary relations among them. Whether the PUFA factor score can improve the performance of risk prediction in cardiovascular diseases remains to be tested.
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