BACKGROUND: The response of status biomarkers to an increase in iron supply depends on several physiologic and environmental factors, which make it difficult to predict the outcome of an intervention. OBJECTIVE: We assessed effects of baseline iron status, sex, menopausal status, duration of intervention, iron form, and daily dose on the change in iron status in response to iron supplementation. DESIGN: A systematic review of randomized controlled trials (RCTs) of iron-supplementation and -fortification trials that assessed effects on hemoglobin, serum ferritin (SF), soluble transferrin receptor, or body iron was conducted. Subgrouping and straight-line and curved metaregression were used to describe the magnitude and dose-responsiveness of effect modifiers with respect to changes in status. RESULTS: Forty-one RCTs were included; none of the RCTs were judged at low risk of bias. Random-effects meta-analyses showed that iron supplementation significantly improved iron status but with high levels of heterogeneity. Metaregression explained approximately one-quarter of between-study variance in effect size. There were clear effects on SF with study duration (increase in SF concentration/wk: 0.51 μg/L; 95% CI: 0.02, 1.00 μg/L; P = 0.04) and dose (increase in SF concentration/g Fe: 0.10 μg/L; 95% CI: 0.01, 0.20 μg/L; P = 0.036) and on hemoglobin concentrations with baseline iron status [-0.08 g/dL (95% CI: 0.15, 0.00 g/dL) per 10-μg/L increase in baseline SF concentration; P = 0.02]. Insufficient data were available to assess effects on body iron, sex, or menopausal status. CONCLUSION: Quantitative relations between baseline iron status, study duration, and iron dose on changes in iron-status biomarkers, which were generated from the meta-analyses, can be used to predict effects of trials of iron supplementation and fortification and to design iron-intervention programs.
BACKGROUND: The response of status biomarkers to an increase in iron supply depends on several physiologic and environmental factors, which make it difficult to predict the outcome of an intervention. OBJECTIVE: We assessed effects of baseline iron status, sex, menopausal status, duration of intervention, iron form, and daily dose on the change in iron status in response to iron supplementation. DESIGN: A systematic review of randomized controlled trials (RCTs) of iron-supplementation and -fortification trials that assessed effects on hemoglobin, serum ferritin (SF), soluble transferrin receptor, or body iron was conducted. Subgrouping and straight-line and curved metaregression were used to describe the magnitude and dose-responsiveness of effect modifiers with respect to changes in status. RESULTS: Forty-one RCTs were included; none of the RCTs were judged at low risk of bias. Random-effects meta-analyses showed that iron supplementation significantly improved iron status but with high levels of heterogeneity. Metaregression explained approximately one-quarter of between-study variance in effect size. There were clear effects on SF with study duration (increase in SF concentration/wk: 0.51 μg/L; 95% CI: 0.02, 1.00 μg/L; P = 0.04) and dose (increase in SF concentration/g Fe: 0.10 μg/L; 95% CI: 0.01, 0.20 μg/L; P = 0.036) and on hemoglobin concentrations with baseline iron status [-0.08 g/dL (95% CI: 0.15, 0.00 g/dL) per 10-μg/L increase in baseline SF concentration; P = 0.02]. Insufficient data were available to assess effects on body iron, sex, or menopausal status. CONCLUSION: Quantitative relations between baseline iron status, study duration, and iron dose on changes in iron-status biomarkers, which were generated from the meta-analyses, can be used to predict effects of trials of iron supplementation and fortification and to design iron-intervention programs.
Authors: Kelsey M Cochrane; Brock A Williams; Jordie A J Fischer; Kaitlyn L I Samson; Lulu X Pei; Crystal D Karakochuk Journal: Curr Dev Nutr Date: 2020-09-24
Authors: Ajibola I Abioye; Said Aboud; Zulfiqar Premji; Analee J Etheredge; Nilupa S Gunaratna; Christopher R Sudfeld; Robert Mongi; Laura Meloney; Anne Marie Darling; Ramadhani A Noor; Donna Spiegelman; Christopher Duggan; Wafaie Fawzi Journal: J Nutr Date: 2016-04-27 Impact factor: 4.798
Authors: Sophie Waldvogel-Abramowski; Gérard Waeber; Christoph Gassner; Andreas Buser; Beat M Frey; Bernard Favrat; Jean-Daniel Tissot Journal: Transfus Med Hemother Date: 2014-05-12 Impact factor: 3.747
Authors: Nicholas J Kassebaum; Rashmi Jasrasaria; Mohsen Naghavi; Sarah K Wulf; Nicole Johns; Rafael Lozano; Mathilda Regan; David Weatherall; David P Chou; Thomas P Eisele; Seth R Flaxman; Rachel L Pullan; Simon J Brooker; Christopher J L Murray Journal: Blood Date: 2013-12-02 Impact factor: 22.113