title: Prediction of dietary iron absorption: an algorithm for calculating absorption and bioavailability of dietary iron.
abstract: BACKGROUND
  Dietary iron absorption from a meal is determined by iron status, heme- and nonheme-iron contents, and amounts of various dietary factors that influence iron absorption. Limited information is available about the net effect of these factors.
  
  
  OBJECTIVE
  The objective was to develop an algorithm for predicting the effects of factors known to influence heme- and nonheme-iron absorption from meals and diets.
  
  
  METHODS
  The basis for the algorithm was the absorption of iron from a wheat roll (22.1 +/- 0.18%) containing no known inhibitors or enhancers of iron absorption and adjusted to a reference dose absorption of 40%. This basal absorption was multiplied by the expected effect of different amounts of dietary factors known to influence iron absorption: phytate, polyphenols, ascorbic acid, meat, fish and seafood, calcium, egg, soy protein, and alcohol. For each factor, an equation describing the dose-effect relation was developed. Special considerations were made for interactions between individual factors.
  
  
  RESULTS
  Good agreement was seen when measurements of iron absorption from 24 complete meals were compared with results from use of the algorithm (r(2) = 0.987) and when mean iron absorption in 31 subjects served a varied whole diet labeled with heme- and nonheme-iron tracers over a period of 5 d was compared with the mean total iron absorption calculated by using the algorithm (P = 0.958).
  
  
  CONCLUSIONS
  This algorithm has several applications. It can be used to predict iron absorption from various diets, to estimate the effects expected by dietary modification, and to translate physiologic into dietary iron requirements from different types of diets.
authors.affiliation: Institute of Internal Medicine, the Department of Clinical Nutrition, the University of Göteborg, Sweden.
authors.forename: L
authors.initials: L
authors.lastname: Hallberg
authors.forename: L
authors.initials: L
authors.lastname: Hulthén
mesh_terms: D000428:Alcohol Drinking; D000465:Algorithms; D000818:Animals; D001205:Ascorbic Acid / Q000378:metabolism; D001682:Biological Availability; D002118:Calcium / Q000378:metabolism / Q000502:physiology; D003069:Coffee / Q000378:metabolism / Q000502:physiology; D004531:Eggs; D005260:Female; D005296:Ferrous Compounds / Q000378:metabolism; D005419:Flavonoids; D006801:Humans; D007408:Intestinal Absorption / Q000502:physiology*; D019266:Iron, Dietary / Q000493:pharmacokinetics*; D008297:Male; D008460:Meat; D010636:Phenols / Q000378:metabolism; D011108:Polymers / Q000378:metabolism; D059808:Polyphenols; D011200:Poultry / Q000378:metabolism / Q000502:physiology; D017747:Seafood; D030262:Soybean Proteins / Q000378:metabolism; D013662:Tea / Q000378:metabolism / Q000502:physiology; D014908:Triticum / Q000378:metabolism / Q000502:physiology
chemical_list: D003069:Coffee; D005296:Ferrous Compounds; D005419:Flavonoids; D019266:Iron, Dietary; D010636:Phenols; D011108:Polymers; D059808:Polyphenols; D030262:Soybean Proteins; D013662:Tea; C020748:ferrous sulfate; D001205:Ascorbic Acid; D002118:Calcium