Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Videos

Algorithms to assess non-heme iron bioavailability.

Manju B Reddy1

  • 1Department of Food Science and Human Nutrition, Center for Designing Foods to Improve Nutrition, Iowa State University, Ames, IA 50011, USA. mbreddy@iastate.edu

International Journal for Vitamin and Nutrition Research. Internationale Zeitschrift Fur Vitamin- Und Ernahrungsforschung. Journal International De Vitaminologie Et De Nutrition
|May 23, 2006
PubMed
Summary
This summary is machine-generated.

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Perspective: Framework for Developing Prediction Equations for Estimating the Absorption and Bioavailability of Nutrients from Foods.

Advances in nutrition (Bethesda, Md.)·2025
Same author

The Protection of EGCG Against 6-OHDA-Induced Oxidative Damage by Regulating PPARγ and Nrf2/HO-1 Signaling.

Nutrition and metabolic insights·2024
Same author

Effects of green tea polyphenols on inflammation and iron status.

Journal of nutritional science·2023
Same author

Combined Effect of Maternal Obesity and Diabetes on Excessive Fetal Growth: Pregnancy Risk Assessment Monitoring System (PRAMS), United States, 2012-2015.

AJPM focus·2023
Same author

Iron Deficiency and Iron Deficiency Anemia in Women with and without Obesity: NHANES 2001-2006.

Nutrients·2023
Same author

Iron-enriched <i>Aspergillus oryzae</i> as an alternative to iron sulphate to limit iron accumulation, growth and motility of the enteric pathogen <i>S.</i> Typhimurium.

The British journal of nutrition·2022

Estimating iron absorption from meals is complex due to interacting enhancers and inhibitors. Current models need refinement for accurate prediction of non-heme iron bioavailability in diverse populations.

Area of Science:

  • Nutritional Science
  • Human Physiology

Background:

  • Iron absorption from mixed meals is influenced by multiple dietary factors, including enhancers and inhibitors.
  • Existing models for estimating non-heme iron bioavailability have limitations in accounting for the combined and interactive effects of these factors.

Purpose of the Study:

  • To review the evolution of models for estimating non-heme iron bioavailability.
  • To highlight the challenges and limitations of current models in accurately predicting iron absorption from complex meals.
  • To emphasize the need for refined models that consider interactive effects and are validated for whole diets.

Main Methods:

  • Review of historical and recent models for iron bioavailability estimation.
  • Analysis of the inclusion of enhancers and inhibitors in bioavailability models.

Related Experiment Videos

  • Evaluation of model accuracy based on quantitative measurements and interactive effects.

    • Main Results:

    • Early models focused on enhancers, later models included inhibitors but often separately or assuming additive effects.
    • Current refined models attempt to incorporate interactive effects but are based on single-meal studies.
    • Accuracy concerns persist due to lack of quantitative data, inability to capture interactions, and limited validation for population-level dietary assessments.

    Conclusions:

    • No single model accurately predicts non-heme iron bioavailability across all diets.
    • Further research and validation are crucial for developing accurate whole-diet models for population iron status assessment.
    • Addressing dietary adequacy requires improved bioavailability prediction models applicable to diverse populations.