Aim: To describe food scores that can be interpreted as indicators of the potential effects of a food on health outcomes.
Methods: The scores consist of weighted averages of the estimates of the association between a health outcome and nutrient balances. Each food contributes a set of weights depending on its nutrient composition. The nutrient balances of a food's constituents are defined in a manner that is similar to those included in the model from which the estimated associations are obtained. As the balances are based on log-ratios, the presence of zero observations is problematic, but observations recorded as trace (rounded zeros) can be suitably replaced by a small value. In order to overcome the essential zero problem, we propose a strategy that exploits the flexibility of sequential binary partitioning, a procedure used to define orthogonal balances, and also describe the estimates of the variance and confidence limits of food scores.
Results: Data from an Italian population-based study were used to provide examples regarding serum high-density lipoprotein and triglyceride levels and waist circumference values, and the scores calculated for some foods or groups of foods are shown.
Conclusions: Food scores allow foods to be ranked on the basis of their potential effects on health outcomes and, as they are not directly related to the amount of the food consumed, may be less subject to confounding. The accuracy of the estimates depends on the completeness of the food's nutrient composition: that is, the more complete the nutrient composition, the more accurate the estimate.
Keywords: compositional data; dietary exposure; food composition; nutrient balances.
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