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In January 2013, the Food and Agriculture Organization ( FAO) of the United Nations released a new report on dietary protein quality, the result from an Expert Consultation that followed the International Symposium on Dietary Protein for Human Health, held in New Zealand during March 2011. The report, 'Dietary protein quality evaluation in human nutrition', is part of the call from the United Nations to promote sustainable diets and health, and was motivated mainly by advances in methods available to measure the quality of nutritional proteins with more accuracy. The main recommendation from the report concerns a new, advanced method of assessing nutritional protein quality. The FAO report recommends that the new method, known as Digestible Indispensable Amino Acid Score ( DIAAS), replaces Protein Digestibility Corrected Amino Acid Score as the preferred method to describe protein quality and that it is adopted in Codex food labelling and claims guidelines. In addition, the report recommends that future research determines protein and amino acid needs that may be above the minimum requirements in certain circumstances. This article provides a summary of the report's findings, discusses its recommendations and implications, and outlines the next steps before the new protein quality method DIAAS can be fully adopted. [ABSTRACT FROM AUTHOR]

Background. This study describes a decision-theoretic approach to nutrient assessment based on Bayesian methods, which can be used to give accurate estimates of optimum intakes. Analysis of risk is an incomplete technique for dealing with nutrients and other substances that, by definition, have an associated benefit. Results. This paper shows that the risk analysis methods being developed by the Codex Commission on Nutrition and European Food Safety Authority, among others, are inappropriate for assessing safe nutrient intake levels. Decision theoretic methods incorporate benefits associated with these essential nutrients, as well as potential risk. Conclusion. These methods allow for missing or incomplete data, which conventional risk analysis does not. [ABSTRACT FROM AUTHOR]