Pedersen J I, Kirkhus B, Müller H
Institute for Nutrition Research, University of Oslo, P.O.B. 1046, Blindern, N-0316 Oslo, Norway.
Eur J Med Res. 2003 Aug 20;8(8):325-31.
The aim of the study was to incorporate trans fatty acids into predictive equations for serum cholesterol and compare their effects with the effects of the individual saturated fatty acids 12:0, 14:0 and 16:0. We have introduced trans fatty acids from partially hydrogenated soybean oil (TransV) and fish oil (TransF) into previously published equations by constrained regression analysis. Prior knowledge about the signs and ordering of existing regression coefficients were incorporated into the regression modelling by adding lower and upper bounds to the coefficients. Oleic acid (18:1) and polyunsaturated fatty acids (18:2, 18:3) were not sufficiently varied in the studies and the respective regression coefficients therefore set equal to those found by Yu et al. (Am J Clin Nutr 1995;61:1129-39). Stearic acid (18:0) considered to be neutral was not included in the equations. The regression analyses were based on results from four controlled dietary studies with a total of 95 participants and including 10 diets differing in fatty acid composition. The analyses resulted in the following equations where the change in cholesterol is expressed in mmol/L and the change in intake of fatty acids is expressed in E%: Delta Total cholesterol = 0.01 delta(12:0) + 0.12 Delta(14:0) + 0.057 delta(16:0) + 0.039 delta(TransF) + 0.031 delta(TransV)- 0.0044 delta(18:1) - 0.017 delta(18:2, 18:3) and deltaLDL cholesterol = 0.01 delta(12:0) + 0.071 delta(14:0) + 0.047 delta(16:0) + 0.043 delta(TransF) + 0.025 delta(TransV) - 0.0044 delta(18:1) - 0.017 delta(18:2, 18:3). The test set used for validation consisted of 22 data points from seven recently published dietary studies. The equation for total cholesterol showed good prediction ability with a correlation coefficient of 0.981 between observed and predicted values. The equation has been used to reformulate margarines into "trans free" products all with more favourable effects on serum cholesterol than previous products. Also a cholesterol reducing margarine has been produced. When tested against butter in an open clinical trial among subjects with mild hypercholesterolemia the observed cholesterol-lowering effect of this margarine corresponded reasonably well with the predicted (0.77 vs. 0.64 mmol/L). We conclude that the equation has practical applicability and can be used to formulate and nutritionally optimise fat products as well as to evaluate already existing products on the market.
本研究的目的是将反式脂肪酸纳入血清胆固醇预测方程,并将其效果与饱和脂肪酸12:0、14:0和16:0的效果进行比较。我们通过约束回归分析,将部分氢化大豆油(TransV)和鱼油(TransF)中的反式脂肪酸引入先前发表的方程中。通过给系数添加下限和上限,将关于现有回归系数的符号和排序的先验知识纳入回归建模。油酸(18:1)和多不饱和脂肪酸(18:2、18:3)在研究中的变化不足,因此各自的回归系数设定为与Yu等人(《美国临床营养学杂志》1995年;61:1129 - 39)所发现的系数相等。被认为是中性的硬脂酸(18:0)未包含在方程中。回归分析基于四项对照饮食研究的结果,共有95名参与者,包括10种脂肪酸组成不同的饮食。分析得出以下方程,其中胆固醇的变化以mmol/L表示,脂肪酸摄入量的变化以E%表示:总胆固醇变化量 = 0.01×(12:0)变化量 + 0.12×(14:0)变化量 + 0.057×(16:0)变化量 + 0.039×(TransF)变化量 + 0.031×(TransV)变化量 - 0.0044×(18:1)变化量 - 0.017×(18:2, 18:3)变化量,低密度脂蛋白胆固醇变化量 = 0.01×(12:0)变化量 + 0.071×(14:0)变化量 + 0.047×(16:0)变化量 + 0.043×(TransF)变化量 + 0.025×(TransV)变化量 - 0.0044×(18:1)变化量 - 0.017×(18:2, 18:3)变化量。用于验证的测试集由来自七项最近发表的饮食研究的22个数据点组成。总胆固醇方程显示出良好的预测能力,观测值与预测值之间的相关系数为0.981。该方程已被用于将人造黄油重新配方为“无反式”产品,所有这些产品对血清胆固醇的影响都比以前的产品更有利。还生产了一种降低胆固醇的人造黄油。在轻度高胆固醇血症患者的开放临床试验中与黄油进行对比测试时,这种人造黄油观察到的降胆固醇效果与预测值相当吻合(0.77对0.64 mmol/L)。我们得出结论,该方程具有实际适用性,可用于制定脂肪产品并对其进行营养优化,以及评估市场上已有的产品。