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Anaemia, prenatal iron use, and risk of adverse pregnancy outcomes: systematic review and meta-analysis

BMJ 2013; 346 doi: (Published 21 June 2013) Cite this as: BMJ 2013;346:f3443
  1. Batool A Haider, ScD candidate1,
  2. Ibironke Olofin, ScD candidate2,
  3. Molin Wang, assistant professor3,
  4. Donna Spiegelman, professor4,
  5. Majid Ezzati, professor5,
  6. Wafaie W Fawzi, professor6
  7. on behalf of Nutrition Impact Model Study Group (anaemia)
  1. 1Departments of Epidemiology and Nutrition, Harvard School of Public Health, 677 Huntington Avenue, Boston, MA 02115, USA
  2. 2Department of Epidemiology, Harvard School of Public Health, Boston, MA 02115, USA
  3. 3Department of Medicine, Harvard Medical School, and Departments of Epidemiology and Biostatistics, Harvard School of Public Health, Boston, MA 02115, USA
  4. 4Departments of Epidemiology and Biostatistics, Harvard School of Public Health, Boston, MA 02115, USA
  5. 5MRC-HPA Centre for Environment and Health, Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London SW7 2AZ, UK
  6. 6Departments of Global Health and Population, Nutrition and Epidemiology, Harvard School of Public Health, Boston, MA 02115, USA
  1. Correspondence to: B A Haider bah201{at}
  • Accepted 20 May 2013


Objectives To summarise evidence on the associations of maternal anaemia and prenatal iron use with maternal haematological and adverse pregnancy outcomes; and to evaluate potential exposure-response relations of dose of iron, duration of use, and haemoglobin concentration in prenatal period with pregnancy outcomes.

Design Systematic review and meta-analysis

Data sources Searches of PubMed and Embase for studies published up to May 2012 and references of review articles.

Study selection criteria Randomised trials of prenatal iron use and prospective cohort studies of prenatal anaemia; cross sectional and case-control studies were excluded.

Results 48 randomised trials (17 793 women) and 44 cohort studies (1 851 682 women) were included. Iron use increased maternal mean haemoglobin concentration by 4.59 (95% confidence interval 3.72 to 5.46) g/L compared with controls and significantly reduced the risk of anaemia (relative risk 0.50, 0.42 to 0.59), iron deficiency (0.59, 0.46 to 0.79), iron deficiency anaemia (0.40, 0.26 to 0.60), and low birth weight (0.81, 0.71 to 0.93). The effect of iron on preterm birth was not significant (relative risk 0.84, 0.68 to 1.03). Analysis of cohort studies showed a significantly higher risk of low birth weight (adjusted odds ratio 1.29, 1.09 to 1.53) and preterm birth (1.21, 1.13 to 1.30) with anaemia in the first or second trimester. Exposure-response analysis indicated that for every 10 mg increase in iron dose/day, up to 66 mg/day, the relative risk of maternal anaemia was 0.88 (0.84 to 0.92) (P for linear trend<0.001). Birth weight increased by 15.1 (6.0 to 24.2) g (P for linear trend=0.005) and risk of low birth weight decreased by 3% (relative risk 0.97, 0.95 to 0.98) for every 10 mg increase in dose/day (P for linear trend<0.001). Duration of use was not significantly associated with the outcomes after adjustment for dose. Furthermore, for each 1 g/L increase in mean haemoglobin, birth weight increased by 14.0 (6.8 to 21.8) g (P for linear trend=0.002); however, mean haemoglobin was not associated with the risk of low birth weight and preterm birth. No evidence of a significant effect on duration of gestation, small for gestational age births, and birth length was noted.

Conclusions Daily prenatal use of iron substantially improved birth weight in a linear dose-response fashion, probably leading to a reduction in risk of low birth weight. An improvement in prenatal mean haemoglobin concentration linearly increased birth weight.


  • We thank Paul Bain at the Countway Library of Medicine, Harvard Medical School, for assistance in the development of search strategy; Ruifeng Li at the Department of Epidemiology, Harvard School of Public Health, for statistical assistance; and Xin Li for research assistance.

  • Writing Team: Batool A Haider (BAH), Ibironke Olofin (IO), Molin Wang (MW), Donna Spiegelman (DS), and Wafaie W Fawzi (WWF) (Harvard School of Public Health, Boston, MA, USA); Majid Ezzati (ME) (School of Public Health, Imperial College London, London, UK).

  • Iron Review and Re-analysis Team: Batool A Haider and Ibironke Olofin (Harvard School of Public Health, Boston, MA, USA); Gustavo F Gonzales (GFG) and Vilma Tapia (VT) (Universidad Peruana Cayetano Heredia, Lima, Peru); Aiguo Ren (AR) and Juan Wang (JW) (Peking University Health Science Center, Beijing, China).

  • Contributors: WWF, ME, and BAH designed the review. BAH wrote and implemented the protocol under the guidance of ME and WWF. BAH developed the search strategy and ran searches. BAH and IO screened the studies and extracted data. BAH analysed the data. DS and MW provided statistical guidance. BAH wrote the first draft of the manuscript. BAH, WWF, ME, and DS contributed to the interpretation of results and subsequent revisions. All writing team members approved the final version of the manuscript. GFG, VT, AR, and JW reanalysed their cohort study data for inclusion in the review. WWF is the guarantor.

  • Funding: The Nutrition Impact Model Study was funded by the Bill and Melinda Gates Foundation. Additional support came from the Saving Brains Program, Grand Challenges Canada Grant Number 0073-03. The funding sources had no role in the study design; in the collection, analysis, and interpretation of results; in the writing of the manuscript; or in the submission of the manuscript for publication. No author has any affiliation with the funding agency.

  • Competing interests: All authors have completed the ICMJE uniform disclosure form at (available on request from the corresponding author) and declare: no support from any organisation for the submitted work; no financial relationships with any organisations that might have an interest in the submitted work in the previous three years; no other relationships or activities that could appear to have influenced the submitted work.

  • Ethical approval: Not needed.

  • Data sharing: No additional data available.

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