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Iron bioavailability from maize and beans: a comparison of human measurements with Caco-2 cell and algorithm predictions
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Date
2007Author
Beiseigel, J.M.
Hunt, J.R.
Glahn, Raymond P.
Welch, R.M.
Menkir, A.
Maziya-Dixon, B.
Type
Target Audience
Scientists
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Show full item recordAbstract/Description
Background: An in vitro digestion and Caco-2 cell model may predict iron bioavailability to humans; however, direct comparisons are lacking.
Objective: The objective was to test the differences in iron bioavailability between 2 maize varieties and 2 bean varieties (white beans and colored beans) by comparing human, Caco-2, and algorithm results.
Design: Two randomized, 2 × 2 factorial experiments compared women's iron absorption from 2 maize varieties (ACR and TZB; n = 26) and 2 bean varieties (great northern and pinto; n = 13), each fed with and without ascorbic acid (AA) from orange juice. Nonheme iron bioavailability was determined from 2-wk retention of extrinsic radioiron tracers and was compared with Caco-2 cell and algorithm results from identical meals.
Results: Without AA supplementation, women absorbed only about 2% of the iron from the maize or bean meals. The results were unaffected by the variety of either maize or beans. Adding AA (15–20 molar ratios of AA:iron) roughly tripled the iron absorption (P < 0.0001) from all test meals. Although the Caco-2 model predicted a slightly improved bioavailability of iron from ACR maize than from TZB maize (P < 0.05), it accurately predicted relative iron absorption from the maize meals. However, the Caco-2 model inaccurately predicted both a considerable difference between bean varieties (P < 0.0001) and a strong interaction between bean varieties and enhancement by AA (P < 0.0001). The algorithm method was more qualitatively than quantitatively useful and requires further development to accurately predict the influence of polyphenols on iron absorption.
Conclusions: Caco-2 predictions confirmed human iron absorption results for maize meals but not for bean meals, and algorithm predictions were only qualitatively predictive.
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https://hdl.handle.net/20.500.12478/2451Non-IITA Authors ORCID
Abebe Menkirhttps://orcid.org/0000-0002-5907-9177