Algorithms for iron and zinc bioavailability: are they accurate?

Area of Science:

• Nutritional biochemistry
• Human physiology
• Dietary assessment

Background:

• Bioavailability algorithms are crucial for assessing mineral absorption.
• Existing algorithms for iron and zinc face challenges in accuracy.
• Understanding factors influencing iron and zinc absorption is vital for public health.

Purpose of the Study:

• To review the accuracy of proposed bioavailability algorithms for iron and zinc.
• To highlight the complexities and current limitations in predicting mineral absorption.
• To assess the feasibility of developing validated algorithms for dietary iron and zinc.

Main Methods:

• Review of current scientific evidence on iron and zinc bioavailability algorithms.
• Analysis of factors influencing iron absorption, including body iron status and dietary components.
• Evaluation of models for predicting zinc absorption based on intake and inhibitors like phytic acid.

Main Results:

• Iron absorption is accurately predicted by body iron status (serum ferritin) in the absence of inflammation.
• Predicting dietary iron bioavailability remains challenging due to multiple interacting dietary factors.
• Zinc absorption prediction is less complex, with intake and phytic acid accounting for significant variance.
• A validated multivariate model exists for predicting zinc absorption.

Conclusions:

• Iron bioavailability algorithms require further development to account for dietary complexities.
• A validated algorithm for dietary iron bioavailability is currently lacking.
• A robust model for predicting zinc absorption based on intake and phytic acid is available.