Evidence map›Paper›PMID 42634923›Full record

ArticleMaternal & child nutrition2026

Quantifying the Potential Impact of Food Fortification on Iron Intake, Hemoglobin Concentration and Anemia Prevalence Among Women of Reproductive Age in India.

Hanqi Luo, Elizabeth Lambert, Xinrui Hu, Manpreet Chadha, Daniel López de Romaña, Mandana Arabi, Helena Pachón

Abstract read
In one paragraph

Article in Maternal & child nutrition, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Hanqi LuoHubert Department of Global Health, Rollins School of Public Health, Emory University, Atlanta, USA.ORCID 0000-0001-6253-5818
Elizabeth LambertDepartment of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, USA.
Xinrui HuDepartment of Biostatistics and Bioinformatics, Rollins School of Public Health, Emory University, Atlanta, USA.
Manpreet ChadhaUNICEF, Brussels, Belgium.
Daniel López de RomañaNutrition International, Ottawa, Canada.
Mandana ArabiNutrition International, Ottawa, Canada.
Helena PachónHubert Department of Global Health, Rollins School of Public Health, Emory University, Atlanta, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Anemia is a public health burden, particularly in women of reproductive age (WRA). Food fortification, by adding micronutrients to foods, may alleviate anemia caused by nutritional deficiencies. To model the impact of iron-fortified rice, wheat flour, and salt in India, we simulated three scenarios: no fortification, intermediate fortification (50% coverage for rice and wheat flour and 26.6% coverage for salt, with 100% industry compliance), and maximum fortification (100% coverage and compliance) in WRA. We first used a single-day, 24-h dietary recall survey from the National Nutrition Monitoring Bureau to simulate mean iron intake under these scenarios (n = 11,625). We then used data from the National Family Health Survey 4 (n = 667,258) to simulate hemoglobin changes due to increased iron intake, based on established parameters from a meta-regression analysis. Subsequently, we calculated anemia prevalence. Compared to the no-fortification scenario, the intermediate and maximum fortification scenarios were predicted to increase daily iron intake by 4.3-6.5 mg and 8.6-13.1 mg (35%-53% and 70%-106% increases), respectively, and decrease anemia prevalence from 52.6% to 45-48% and 36-43%, respectively. Our results suggest that combined fortification of rice, wheat flour, and salt with iron at varying levels of coverage and 100% compliance can improve iron intakes and hemoglobin concentration and thus reduce anemia prevalence among WRA in India.

Indexed as

Anemia, Iron-DeficiencyFood, FortifiedHemoglobinsIron, DietaryAdolescentAdultFemaleFlourHumansIndiaNutrition SurveysOryzaPrevalenceSodium Chloride, DietaryTriticumYoung AdultHemoglobinsIron, DietarySodium Chloride, DietaryanemiafortificationironmodelingSouth Asia

Identifiers

PMID42634923
PMCPMC13501248

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.