American Journal of Epidemiology Vol. 140, No. 9: 848-855
Copyright © 1994 by The Johns Hopkins University School of Hygiene and Public Health
research-article |
Can Energy Adjustment Separate the Effects of Energy from Those of Specific Macronutrients?
1Biostatistics Branch, Division of Cancer Etiology, National Cancer Institute Bethesda, MD
2Division of Cancer Prevention and Control, National Cancer Institute Bethesda, MD
Reprint requests to Dr. Sholom Wacholder, National Cancer Institute, Epidemiologic Methods Section, Biostatistics Branch, 6130 Executive Blvd., EPN 403, Rockville, MD 20852
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one or more macronutrients from consideration, thereby allowing estimation, but the parameters that are estimated no longer represent specific macronutrient or generic energy effects.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, assump tions. 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. Am J Epidemiol 1994;140:848–55.
biometry; caloric intake; diet; dietary carbohydrates; dietary fats; dietary proteins; epidemiologic methods; regression analysis
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