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Applying compositional data methodology to nutritional epidemiology

The purpose of epidemiological studies of nutrition and disease is to investigate the effects of specific dietary components regardless of total energy intake, but this is sometimes hampered by the compositional nature of dietary data. Compositional data are those that measure parts of a whole, such as percentages or proportions, and particular methodologies have been developed to allow their statistical analysis and theoretical and practical applications in various sciences. This paper describes the use of a compositional data perspective for statistical analyses in the field of nutritional epidemiology. The approach is based on isometric log-ratio transformation and has been previously proposed for the construction of regression models using compositional explanatory variables. The new isometric log-ratio variables allow full inferences about each element of dietary composition and adjustment by total energy intake. Using data from an Italian population-based study, logistic regression models were fitted to evaluate the effects of the intake of macronutrients (proteins, fats and carbohydrates) on the odds of having metabolic syndrome in middle-aged subjects.