BACKGROUND: Absorption factors are required to convert physiologic requirements for iron into Dietary Reference Values, but the absorption from single meals cannot be used to estimate dietary iron absorption. OBJECTIVE: The objective was to conduct a systematic review of iron absorption from whole diets. DESIGN: A structured search was completed by using the Medline, EMBASE, and Cochrane CENTRAL databases from inception to November 2011. Formal inclusion and exclusion criteria were applied, and data extraction, validity assessment, and meta-analyses were undertaken. RESULTS: Nineteen studies from the United States, Europe, and Mexico were included. Absorption from diets was higher with an enhancer (standard mean difference: 0.53; 95% CI: 0.21, 0.85; P = 0.001) and was also higher when compared with low-bioavailability diets (standard mean difference: 0.96; 95% CI: 0.51, 1.41; P < 0.0001); however, single inhibitors did not reduce absorption (possibly because of the limited number of studies and participants and their heterogeneity). A regression equation to calculate iron absorption was derived by pooling data for iron status (serum and plasma ferritin) and dietary enhancers and inhibitors from 58 individuals (all from US studies): log[nonheme-iron absorption, %] = -0.73 log[ferritin, μg/L] + 0.11 [modifier] + 1.82. In individuals with serum ferritin concentrations from 6 to 80 μg/L, predicted absorption ranged from 2.1% to 23.0%. CONCLUSIONS: Large variations were observed in mean nonheme-iron absorption (0.7-22.9%) between studies, which depended on iron status (diet had a greater effect at low serum and plasma ferritin concentrations) and dietary enhancers and inhibitors. Iron absorption was predicted from serum ferritin concentrations and dietary modifiers by using a regression equation. Extrapolation of these findings to developing countries and to men and women of different ages will require additional high-quality controlled trials.
BACKGROUND: Absorption factors are required to convert physiologic requirements for iron into Dietary Reference Values, but the absorption from single meals cannot be used to estimate dietary iron absorption. OBJECTIVE: The objective was to conduct a systematic review of iron absorption from whole diets. DESIGN: A structured search was completed by using the Medline, EMBASE, and Cochrane CENTRAL databases from inception to November 2011. Formal inclusion and exclusion criteria were applied, and data extraction, validity assessment, and meta-analyses were undertaken. RESULTS: Nineteen studies from the United States, Europe, and Mexico were included. Absorption from diets was higher with an enhancer (standard mean difference: 0.53; 95% CI: 0.21, 0.85; P = 0.001) and was also higher when compared with low-bioavailability diets (standard mean difference: 0.96; 95% CI: 0.51, 1.41; P < 0.0001); however, single inhibitors did not reduce absorption (possibly because of the limited number of studies and participants and their heterogeneity). A regression equation to calculate iron absorption was derived by pooling data for iron status (serum and plasma ferritin) and dietary enhancers and inhibitors from 58 individuals (all from US studies): log[nonheme-iron absorption, %] = -0.73 log[ferritin, μg/L] + 0.11 [modifier] + 1.82. In individuals with serum ferritin concentrations from 6 to 80 μg/L, predicted absorption ranged from 2.1% to 23.0%. CONCLUSIONS: Large variations were observed in mean nonheme-iron absorption (0.7-22.9%) between studies, which depended on iron status (diet had a greater effect at low serum and plasma ferritin concentrations) and dietary enhancers and inhibitors. Iron absorption was predicted from serum ferritin concentrations and dietary modifiers by using a regression equation. Extrapolation of these findings to developing countries and to men and women of different ages will require additional high-quality controlled trials.
Authors: Eun-Young Lee; Paul J Eslinger; Michael R Flynn; Daymond Wagner; Guangwei Du; Mechelle M Lewis; Lan Kong; Richard B Mailman; Xuemei Huang Journal: Neurotoxicology Date: 2016-11-18 Impact factor: 4.294
Authors: Philipp Helmer; Tobias Schlesinger; Sebastian Hottenrott; Michael Papsdorf; Achim Wöckel; Joachim Diessner; Jan Stumpner; Magdalena Sitter; Tobias Skazel; Thomas Wurmb; Christoph Härtel; Stefan Hofer; Ibrahim Alkatout; Thierry Girard; Patrick Meybohm; Peter Kranke Journal: Anaesthesist Date: 2022-03-02 Impact factor: 1.041
Authors: Eun-Young Lee; Michael R Flynn; Guangwei Du; Yunqing Li; Mechelle M Lewis; Amy H Herring; Eric Van Buren; Scott Van Buren; Lan Kong; Rebecca C Fry; Amanda M Snyder; James R Connor; Qing X Yang; Richard B Mailman; Xuemei Huang Journal: Toxicol Sci Date: 2016-01-14 Impact factor: 4.849
Authors: Susan J Fairweather-Tait; Anna A Wawer; Rachel Gillings; Amy Jennings; Phyo K Myint Journal: Mech Ageing Dev Date: 2013-11-22 Impact factor: 5.432