Wacholder S, Schatzkin A, Freedman L S, Kipnis V, Hartman A, Brown C C
Biostatistics Branch, National Cancer Institute, Bethesda, MD 20852.
Am J Epidemiol. 1994 Nov 1;140(9):848-55. doi: 10.1093/oxfordjournals.aje.a117333.
Energy adjustment is used in nutritional epidemiology in an attempt to separate specific effects of macronutrients (carbohydrate, fat, and protein) from one another and from the generic effect of the total quantity of energy consumed. However, models in which the risk of disease is allowed to depend simultaneously on daily total energy consumption and separate components of energy that sum to the total are not identifiable: the specific effects of individual macronutrients and the generic effect of energy cannot be disentangled by multivariate analysis. The standard, residual, and partition methods exclude one or more macronutrients from consideration, thereby allowing estimation, but the parameters that are estimated no longer represent specific macronutrient or generic energy effects. Therefore, an interpretation of a regression coefficient from these methods as a specific effect of a macronutrient or as the generic effect of energy requires additional, almost always questionable, assumptions. For example, a conclusion based on data alone that there is a specific fat effect upon the development of breast cancer but no specific effects of other macronutrients and no generic energy effect is not possible. Notwithstanding these serious problems, some useful etiologic inference still can be made.
能量调整在营养流行病学中被采用，旨在将宏量营养素（碳水化合物、脂肪和蛋白质）的特定影响相互分离，并与所摄入能量总量的一般影响区分开来。然而，允许疾病风险同时取决于每日总能量消耗以及构成总能量的各个能量成分的模型是无法识别的：个体宏量营养素的特定影响和能量的一般影响无法通过多变量分析来区分。标准法、残差法和分割法将一种或多种宏量营养素排除在考虑范围之外，从而实现估计，但所估计的参数不再代表特定宏量营养素或能量的一般影响。因此，将这些方法得出的回归系数解释为宏量营养素的特定影响或能量的一般影响，需要额外的、几乎总是有问题的假设。例如，仅基于数据就得出脂肪对乳腺癌发展有特定影响而其他宏量营养素无特定影响且能量无一般影响的结论是不可能的。尽管存在这些严重问题，但仍可进行一些有用的病因推断。
