A quantitative model for prediction of iron bioavailability from Indian meals: An experimental study

Abstract

The major goal of the study was to explore the possibility of developing an updated model that integrates the effect of various enhancers and inhibitors for predicting the potential availability of iron from typical Indian vegetarian meals. The interaction effects of four constituents namely ascorbic acid, citric acid, tannic acid and calcium phosphate was studied using a standard cereal meal (STD meal) providing 3 mg non-heme iron/250 ml homogenate. Based on the data, a regression equation was evolved which was tested for its predictive power as applied to a set of 10 typical Indian meals. Regression analysis of the data revealed that both ascorbate and citrate emerged as equally strong enhancers while tannate and calcium phosphate demonstrated strong inhibitory effect on iron availability in the STD meal. Further, when the prediction equation, generated on the basis of the interaction effect data was applied to the typical Indian meals, it showed a high correlation coefficient (r = 0.76) between the analysed values for iron availability vs the values computed using the enhancer and inhibitor contents of the meals. Comparison with the only other model available in the literature namely that of Monsen & Balintfy (1982) revealed that the present model was far better in predicting iron availability from cereal based Indian meals (r = 0.76) than Monsen's model (r = 0.19). The findings of the present study substantiated the hypothesis that a regression model, evolved from a cereal meal, by integrating the effect of enhancers as well as inhibitors, rather than only enhancers, provides a more precise estimate of iron availability from typical Indian meals. A limitation of the model however, was that phytate could not be incorporated into the equation.