Algorithms to Assess non-Heme Iron Bioavailability

Abstract

While sufficient information exists on the effect of individual factors on iron absorption, their net effect in a mixed meal is less well characterized, being dependent on the combination and quantity of the factors present in the meal. Over a period of more than 25 years, several models have been developed to estimate non-heme iron bioavailability, either to assess iron absorption from a meal or iron sufficiency in populations. Initially, a model was developed to calculate iron absorption in individuals with varying iron status that included only enhancers. This model was useful in classifying the diets but has limited value for accurale assessment. Later models were modified and improved by including inhibitors in the calculations. However, some included either phytate or tea but not in combination. The models that included all the factors in calculations assumed their effect was independent and additive rather than interactive, which is an important issue in addressing iron bioavailability. Although some of the models correlated estimated bioavailability with iron status of the population, the accuracy of the estimations is of concern due to lack of quantitative measurements of bioavailability modifiers, inability to consider interactive effects, and the use of non-iron status measurements. Recent research has led to the development of refined models to assess iron bioavailability of complex meals by comprehensively taking into consideration the interactive effect among enhancers and inhibitors. However, the models are based on single-meal studies and their application to whole diets at a population level is not clear. Accurate measurements of dietary factors and independent validation are needed before using these models. To date, no single model is applicable to all diets and additional studies are needed to develop new models to predict bioavailability of whole diets accurately, in addition to addressing dietary adequacy in all populations.