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Fortification of maize flour with iron for preventing anaemia and iron deficiency in populations

  1. Sant-Rayn Pasricha1,
  2. Luz Maria De-Regil2,
  3. Maria N Garcia-Casal3,
  4. Belinda J Burford4,
  5. Jeffrey A Gwirtz5,
  6. Juan Pablo Peña-Rosas2,*

Editorial Group: Cochrane Public Health Group

Published Online: 14 NOV 2012

Assessed as up-to-date: 24 AUG 2012

DOI: 10.1002/14651858.CD010187

How to Cite

Pasricha SR, De-Regil LM, Garcia-Casal MN, Burford BJ, Gwirtz JA, Peña-Rosas JP. Fortification of maize flour with iron for preventing anaemia and iron deficiency in populations (Protocol). Cochrane Database of Systematic Reviews 2012, Issue 11. Art. No.: CD010187. DOI: 10.1002/14651858.CD010187.

Author Information

  1. 1

    Faculty of Medicine, Dentistry and Health Sciences, University of Melbourne, Nossal Institute for Global Health, Melbourne, VIC, Australia

  2. 2

    World Health Organization, Evidence and Programme Guidance, Department of Nutrition for Health and Development, Geneva, Switzerland

  3. 3

    Instituto Venezolano de Investigaciones Cientificas, Centro de Medicina Experimental, Laboratorio de Fisiopatología., Caracas, Caracas, Venezuela

  4. 4

    The University of Melbourne, The McCaughey Centre, Melbourne School of Population Health, Parkville, VIC, Australia

  5. 5

    Kansas State University, Department of Grain Science and Industry, Manhattan, Kansas, USA

*Juan Pablo Peña-Rosas, Evidence and Programme Guidance, Department of Nutrition for Health and Development, World Health Organization, 20 Avenue Appia, Geneva, 1211, Switzerland. penarosasj@who.int. juanpablopenarosas@outlook.com.

Publication History

  1. Publication Status: New
  2. Published Online: 14 NOV 2012

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Background

  1. Top of page
  2. Background
  3. Objectives
  4. Methods
  5. Acknowledgements
  6. Appendices
  7. History
  8. Contributions of authors
  9. Declarations of interest
  10. Sources of support
 

Description of the condition

Over 1.6 billion people, or a quarter of the world's population, are anaemic. The prevalence of anaemia is highest (47.4%) among preschool children, but over 40% of pregnant women, 30% of non-pregnant women and 25% of school-aged children are also affected (WHO/CDC 2008). Most anaemia occurs in developing countries, particularly in Asia, Africa and South America. At least half this burden is due to iron deficiency (Stoltzfus 2003), caused by poor dietary iron content and availability for absorption, together with increased requirements (during growth and pregnancy) and losses (especially due to intestinal parasitic infection and menstruation). Iron deficiency is thus thought to be the single most prevalent nutrient deficiency worldwide.

Iron deficiency is associated with considerable morbidity across the life cycle. In preschool children, iron deficiency anaemia appears to be associated with potentially irreversible impairments in cognitive development, and in school-aged children iron deficiency anaemia is associated with reduced school learning and educational performance (Beard 2007). Symptomatic anaemia, with fatigue, lethargy and pallor may also result in severe cases. Iron deficiency has been estimated to contribute to 0.2% of deaths in children under five, and to cost approximately 2.2 million disability adjusted life years (DALYs) annually (Stoltzfus 2004). In adolescents and adult non-pregnant women, iron deficiency is associated with impaired cognitive and physical capacity and reduced work performance. Prevention of iron deficiency anaemia during pregnancy has been associated in some studies with alleviation of low birth weight (Christian 2003), a condition which in turn is associated with reduced infant iron endowment and a subsequent increased risk of iron deficiency anaemia (Wharton 1999). Maternal iron deficiency is a global problem that may contribute to high rates of maternal depression and non-responsive care giving (Black 2011). Children can benefit from both nutritional interventions and early learning interventions that promote responsive mother-child interactions (Black 2012; Murray-Kolb 2009).

The major causes of iron deficiency include inadequate dietary iron intake due to consumption of a diet with a low overall iron content, or one that contains inhibitors of iron absorption (Nair 2009), and increased losses of iron because of chronic blood losses, most commonly due to intestinal hookworm infection (Stoltzfus 1996). Poor dietary intake and limited bioavailability (the quantity or fraction of the iron consumed that is absorbed and utilised) is considered a major contributor to the global burden of iron deficiency. Populations consuming diets that chiefly comprise cereals such as maize, wheat and rice, with an inadequate intake of iron-rich foods, in particular meat, but also legumes, nuts and other vegetables, are at high risk of iron deficiency. Cereals (including maize) contain phytates which bind to iron and prevent its absorption in the intestine (Sharpe 1950).

Iron deficiency is most likely to occur during times of increased iron requirements, and thus is seen most commonly in toddlers when rapid growth results in expansion of the blood volume and an escalation in iron requirements for production of red blood cells, during adolescence when growth and red cell production escalates again (Wharton 1999), compounded in females by the onset of menstruation with associated blood loss, and during pregnancy when women undergo expansion in blood volume, vigorous erythropoiesis and must supply iron to the developing foetus (Scholl 2000).

Diagnosis of iron deficiency and anaemia is dependent on laboratory investigation (WHO 2011a; WHO 2011b). Haemoglobin can be accurately measured using a variety of methods. Measurement of some iron indices is more specialised and in the field setting may be difficult (Lynch 2011; WHO/CDC/UNICEF 2001). Important tests for evaluating the iron status of populations include ferritin, soluble transferrin receptor (especially during concomitant inflammation and in pregnancy) and transferrin/iron binding capacity. Although bone marrow examination for macrophage iron is considered a gold standard for diagnosis of iron deficiency, it is rarely performed in field studies (WHO/CDC 2007).

Strategies to improve iron intake include improving overall dietary diversity, supplementation, point-of-use fortification of foods with micronutrient powders and fortification of staple foods with iron. Increasing the availability and consumption of a nutritionally adequate diet is the only sustainable and long-term solution, not just for overcoming iron deficiency and anaemia, but for overcoming other micronutrient deficiencies as well (FAO 2011). Food-based approaches include increasing overall food intake, increasing consumption of micronutrient-rich foods, modifying intake of dietary iron inhibitors and enhancers, using improved processing, preservation and preparation techniques, consumer education for behaviour change, improving food quality and safety and public health, and food fortification (FAO 2011).

Cereals are overwhelmingly the major source of food supplies for direct human consumption. Of the 2.4 billion tonnes of cereals currently produced, roughly 1.1 billion tonnes are destined for food use, around 800 million tonnes (35% of world consumption) are used as animal feed, and the remaining 500 million tonnes are diverted to industrial usage, seed or are wasted. With an ability to grow in diverse climates, maize – the world’s primary coarse grain – is cultivated in most parts of the world, although the vast quantity of production is concentrated in the Americas, especially the United States of America. In that country, transgenic (genetically modified) maize accounts for 85% of plantings. The major export markets have shifted increasingly to the developing countries. Currently, about 55% of world consumption of coarse grains is used for animal feed, but in many countries (mainly in sub-Saharan Africa and Latin America) they are also directly used for human consumption. At the global level, about 17% of aggregate consumption of coarse grains is devoted to food, but the share rises to as much as 80% in sub-Saharan Africa (FAO 2012).

 

Description of the intervention

Fortification is the addition of micronutrients to foods. Fortification is usually applied centrally, at the point of food production. Due to the relatively low cost and potential for wide distribution, fortification has been proposed as one of the most cost-effective of all health interventions. The success of fortification depends on several factors. The food 'vehicle' to which the fortificant is added must be consumed in adequate quantities by the population at risk of the micronutrient deficiency. Additionally the fortificants used must be effectively absorbed and should not diminish the taste, colour or smell of the food (WHO/FAO 2006). A variety of iron fortificants are suitable for use in flours, including ferrous sulphate, elemental iron powders, ferrous fumarate and sodium iron EDTA (Hurrell 2002; Hurrell 2010).

Maize (corn) is one of the world’s most important cereal grains. It is a dietary staple for more than 200 million people and provides approximately 20% of the world’s calories (Nuss 2010). Products of maize include corn flour, porridges, breakfast cereals, tortillas, tamales and arepas. Maize has comparable energy density to other cereal crops, and is a relatively good source of vitamin A, but also is rich in phytate, a compound that potently inhibits iron availability for absorption (McKevith 2004). In sub-Saharan Africa, Southeast Asia and Latin America, where iron deficiency is endemic, maize is a dietary staple (Nuss 2010).

 

Maize processing and products

A maize kernel comprises several components: the outer covering (pericarp and aleurone); the endosperm, comprising the largest fraction of the kernel; and the germ, consisting of the embryo and scutellum. Genetic background, variety, environmental conditions, plant age and geographic location can impact kernel composition within and between maize varieties (Nuss 2010). The nutritional properties of maize are located in distinct although overlapping components of the kernel. Maize contains about 72% starch, mainly found in the endosperm. The predominant source of fibre is the pericarp, although smaller amounts of fibre are also found in the endosperm. Maize contains about 10% protein, chiefly in the endosperm and germ: importantly, the essential amino acids lysine and tryptophan are only present in maize in small and inadequate quantities (FAO 1992). Quality protein maize (QPM) varieties have been developed to contain high levels of lysine and tryptophan (Prasanna 2001). Fat and lipid account for 3% to 6% of maize.

In general, maize is deficient in vitamin B12 and contains niacin in an inaccessible form, placing populations that consume high quantities of maize without sufficient dietary diversity at risk of pellagra (FAO 1992). Maize contains only modest amounts of zinc, and negligible amounts of iron, absorption of which is further diminished by the presence of phytates which bind to non-haem iron and prevent absorption: the bioavailability of iron from corn is thus estimated to be less than 2% to 5% (Beiseigel 2007). Phytases, genetically modified low phytate maize variants, and some pre-processing methods such as addition of ascorbic acid, may improve iron availability from maize (Beiseigel 2007; Hurrell 2002; Troesch 2011). 

Following harvest, maize undergoes several processing steps prior to preparation of an end product. Cobs are dried, hulled and shelled to remove the kernels prior to milling (ILO 1984). Wet milling is used to obtain starch, edible corn oil, sweeteners and syrups, and animal feed products. Dry milling is used to obtain flour, meal and grits. Some maize products use whole maize while others use degerminated kernels (Codex 1985a; Codex 1985b). This is an important consideration as it may impact the overall nutritional contents. Maize meal/flour derived from dry milling is used in different ways around the world (Herbst 2001). It is used as a substitute for wheat to make corn bread, as polenta in Italy, angu in Brazil, mamaliga in Romania, mush in the United States, mealie pap in South Africa and sadza, nshima and ugali in African countries. Corn flakes are also derived from corn meal that has undergone extrusion (Nuss 2010). Fermentation of milled kernels is also commonly used in African and South American settings: derived products including bread and alcohol may have improved bioavailability of niacin; fermented maize gruel has been recommended as a fluid for replacement of electrolytes in acute diarrhoea for children in developing countries.

In many settings, maize grains undergo pre-processing prior to milling. The process of nixtamalisation refers to cooking maize grains in a dilute alkali solution (traditionally, limewater - sodium and calcium hydroxide, ash or lye). Following washing, the pericarp is removed (hulling), leaving the endosperm and germ (Katz 1974). The softened grain may then be wet-milled to produce dough 'masa', which can be used to make tortillas, tamales and arepas. Alternatively, the nixtamalised grain may be dried in ovens, ground and then prepared as nixtamalised corn flour (masa harina) that can be reconstituted at the time of use to produce the full range of corn masa products. This flour is commercially available for purchase and consumption and expedites the maize preparation process for regular consumers (Bressani 1997). Although nixtamalisation was practised for many centuries in local and home settings, it has been adapted for large-scale corn masa flour production.

Nixtamalisation gives the final product a characteristic flavour, and changes the nutritional properties of the maize. Nixtamalised maize flour contains niacin in a bioavailable form, and populations consuming maize thus produced do not develop pellagra (Bressani 1997). Due to calcium absorbed from the lime, nixtamalised maize flour has a high calcium content and can provide most of the daily calcium requirement to populations consuming this product as a staple (Wyatt 1994). Phytic acid content is reduced in nixtamalised maize products. Iron content may be slightly increased by the process; variable changes in bioavailability have been reported, with some suggesting increased availability due to reduced phytate content and others suggesting impaired bioavailability perhaps due to inhibition by calcium (Bressani 1997). Limewater-treated corn remains deficient in other B-complex vitamins and essential amino acids including lysine and tryptophan (Bressani 1990). Commercial nixtamalisation with production of nixtamalised corn flour is performed throughout the Americas, but is less commonly undertaken in Europe, Africa and India, where the prevention of pellagra is dependent on consumption of niacin from other food sources.

Precooking is another procedure applied to de-hulled and degermed corn products after milling (a separation of the kernels components hull/bran, germ and low-fat endosperm in sizes ranging from grits, to meal to flour) and is common in some South American countries. Precooked maize flour is the product obtained from white or yellow corn, composed mainly of endosperm. The maize kernel is, with this process, sequentially dehulled, degermed, precooked, dried, flaked and reduced into a fine powder (Covenin 1996; Vielma 1998)

The definitions of corn flour and cornmeal are widely varied. The United States Food and Drug Administration (FDA) defines corn flour and meal as products obtained from the grinding of dried corn grains (yellow or white). These regulations define the size (as determined by the proportion of product that can pass through test sieves of various fineness), the moisture content of each product, and the amount of fibre and fat that is retained in the product. Corn flour (white or yellow) must be able to pass through the narrowest sieves, while corn meal must be able to pass through wider sieves, but not through sieves that would permit passage of corn grits; corn meal must contain at least 1.2% fibre (FDA 2011). Maize meal and flour may also be included as part of a composite flour, in combination with other products. Composite flours are mixtures of flours from tubers rich in starch (such as yam, cassava, sweet potato), protein-rich flours (e.g. soy, peanut) and cereals (maize, rice and wheat), designed to enhance the nutritional properties of foods made from the flour (Seibel 2006). For corn meal flours, there are three sorts of maize meal at different extraction rates: dehulled, degermed maize meal 65% to 70% extraction; sifted maize meal (usually in Africa) 80% to 85% extraction and whole maize meal 90% to 95% extraction (Eustace 1982; Milazzo 1986). In some countries the yield from degerminated corn products produced for human consumption includes products such as flour, cones, meal, snack grits, brewer's grits, #8 and #4 grits. These products have a lower yield range of 65% to 70%. As edible corn yield increases there is a corresponding increase in fat and fibre content (i.e. nutritional and potentially particle size). It makes sense to determine not only the amount of corn consumed per capita but also its form or type consumed as this will impact its nutritional quality. This in turn may influence fortification decisions appropriate to each region.

Fortification of maize flour and other sub-products produced from maize has been implemented in several settings around the world. Although there is less experience with fortification of maize flour than for wheat flour, mass fortification of maize flour with iron has been a reality for many years in several countries in the Americas (Dary 2002a; Garcia-Casal 2002) and Africa (voluntary fortification has been already introduced in Ghana, Kenya, Malawi and Mauritania, with mandatory fortification in South Africa (FFI 2012).

 

How the intervention might work

Iron fortification aims to improve the nutritional status of populations at risk of iron deficiency and anaemia by increasing dietary content and thus iron intake. Several fortificants are available for fortification of maize flour. Selection of fortificant is a trade-off between bioavailability, maximal concentration that can be added without affecting sensory aspects, cost and availability. The bioavailability, stability and sensory effects of different iron fortificants have been described (Dary 2002a). Ferrous sulphate has high bioavailability; has been used to fortify bread, pasta and infant formula; and although it is effective when added to flour, it may adversely affect flavours, especially following storage. Ferrous fumarate is also well absorbed, has a bioavailability similar to ferrous sulphate and overcomes many of the problems associated with adverse effects on taste. Electrolytic iron compounds added to cereals have poor bioavailability, especially related to high particle size, and also produce adverse effects on taste at the higher concentrations required to achieve optimal dietary iron intake (Cook 1983; Hallberg 1982). Other iron compounds such as sodium iron EDTA (NaFeEDTA), ferrous bis-glycinate and tris-glycinate (Bovell-Benjamin 2000; Hertptramp 2004; Mendoza 2001), which protect iron from dietary inhibitors of absorption (i.e. phytates), have superior bioavailability and do not impact product taste compared to other compounds, but may be limited by their higher costs; colour and rancidity has been associated with the latter compound following storage of wheat flour. Finally, encapsulated ferrous sulphate and ferrous fumarate, in which iron is encapsulated in an oil layer, has minimal reactivity with the food matrix but offers high bioavailability; this approach is limited by the relatively high cost of the fortificant (Dary 2002b; Hurrell 2002).

The amount and final concentration of additional iron added to the food vehicle depends on the daily intake of that food by the population as well as the characteristics of the fortificant as described. Based on the expected intake of the vehicle and the bioavailability of the iron, the concentration of fortificant added can then be adjusted to achieve an appropriate daily absorption of iron (˜1 to 2 mg per day) (WHO 2009). Formal testing of the absorption of iron added to the vehicle can also be performed using isotopic testing. Iron absorption may be further improved with addition of an enhancer such as ascorbic acid (Troesch 2011), and by reducing the level of phytic acid (inhibitor) using one of a variety of techniques (Hurrell 2002).

Thus, approaches to iron fortification of staple products (including maize flour and its integration as a component in a food product) vary, with different specific vehicles employed, heterogenous types and concentrations of fortificants added to the vehicle, and different complementary strategies applied to additionally enhance iron absorption.

 

Risks of flour fortification with iron

Several theoretical potential adverse effects of flour fortification have been described. Secondary iron overload, associated with long-term excessive iron absorption, is usually associated with hereditary disorders such as thalassaemia, pyruvate kinase deficiency, dyserythropoietic anaemia, glucose-6-phosphate dehydrogenase (G6PD) deficiency, hereditary spherocytosis, sideroblastic anaemia or with acquired conditions such as sideroblastic and other dyserythropoietic anaemias, or any anaemia except for that due to blood loss, in which multiple transfusions are required (Beutler 2003). Although men and post-menopausal women do not have a mechanism for losing iron and therefore may be at greater risk of accumulating iron long-term, consumption of iron-fortified foods by them does not appear to increase their risk of iron overload (Ballot 1989; Brittenham 2004; Pouraram 2012). Hereditary haemochromatosis is characterised by an accelerated rate of intestinal iron absorption and progressive iron deposition in various tissues that typically begins to be expressed in the third to fifth decades of life, but may also occur in children. Hereditary haemochromatosis due to mutations of the HFE gene is chiefly found in populations of European descent but is less common is among other ethnicities (Adams 2005). It has been speculated that fortification of staple foods with iron would restore (or partially restore) iron intake to 'recommended' levels, and thus pose a risk in predisposed individuals of iron overload that remains lower than the developed world (Brittenham 2004).

This proposed review will attempt to evaluate, based on existing research, the effectiveness of maize flour fortification with iron as a public health intervention. The World Health Organization/Centers for Disease Control and Prevention (WHO/CDC) logic model for micronutrient interventions in public health depicts the programme theory and plausible relationships between inputs and expected improvement in Millennium Development Goals (MDGs) and can be adapted to different contexts (WHO/CDC 2011). The effectiveness of maize flour fortification with iron in public health depends on several factors related to policies and legislation regulations; production and supply of the fortified rice; the development of delivery systems for the fortified maize flour; the development and implementation of external and internal food quality control systems; and the development and implementation of strategies for information, education and communication for behaviour change among consumers. A generic logic model for micronutrient interventions that depicts these processes and outcomes is presented in Figure 1.

 FigureFigure 1. WHO/CDC logic model for micronutrients interventions in public health (with permission from WHO)

 

Why it is important to do this review

Iron deficiency and anaemia remain important public health problems worldwide. One of the major limitations for development of iron fortification guidelines is a lack of a strong evidence base for this intervention (Dary 2002b). Although maize fortification with iron alone, or in combination with other micronutrients, has been implemented in many countries, to date there has been no systematic assessment of the safety and effectiveness of this intervention to inform policy making. This proposed systematic review will complement the findings of other Cochrane Reviews investigating the effects and safety of fortification of wheat flour, rice fortification (Ashong 2012), salt iodisation (Wu 2002) and fortification of condiments and seasonings (Self 2012) for preventing iron deficiency anaemia and improving health.

 

Objectives

  1. Top of page
  2. Background
  3. Objectives
  4. Methods
  5. Acknowledgements
  6. Appendices
  7. History
  8. Contributions of authors
  9. Declarations of interest
  10. Sources of support

To determine the benefits and harms of iron fortification of maize flour, corn meal and fortified maize flour products for anaemia and iron status among the general population.

For the purpose of this review, a fortified maize flour product includes any food prepared from fortified corn meal or maize flour.

 

Methods

  1. Top of page
  2. Background
  3. Objectives
  4. Methods
  5. Acknowledgements
  6. Appendices
  7. History
  8. Contributions of authors
  9. Declarations of interest
  10. Sources of support
 

Criteria for considering studies for this review

 

Types of studies

Fortification of maize flour is an intervention that aims to reach the entire population of a country or large sections of the population and is frequently delivered through the market system. We anticipate, therefore, that we will not be able to assess the benefits and harms of food fortification if we only include randomised trials; thus in addition, we plan to examine data from other study designs.

In summary we will include:

  • randomised controlled trials, with randomisation at either individual or cluster level;
  • quasi-randomised trials (where allocation of treatment has been made, for example, by alternate allocation, date of birth, alphabetical order, etc);
  • non-randomised controlled trials;
  • observational studies that are prospective and have a control group;

    • cohort studies (prospective and retrospective);
    • controlled before and after studies;
    • interrupted time series with at least three measurement points both before and after intervention (ITS).

Although we plan to include both randomised and non-randomised studies, we will not pool results from randomised trials together with those from non-randomised studies in meta-analysis and we will have separate meta-analysis estimates based on the different study designs.

In addition to the above-mentioned study designs before and after studies without a control group will also be considered for inclusion in this review. We will present results from these studies in a table but will not include them in a meta-analysis; we will discuss them but they will not directly inform the conclusions of the review. Such studies may provide information on the implementation, feasibility and other contextual factors relating to the interventions under review.

 

Types of participants

General population older than 2 years of age (including pregnant women), from any country. We will exclude studies of interventions targeted toward participants with a critical illness or severe co-morbidities.

 

Types of interventions

Interventions to be included in this review are those in which maize flours and/or maize sub-products have been fortified with iron alone or iron plus other vitamins/minerals. Maize flour refers to white or yellow maize (corn) flour or maize (corn) meal that is produced by grinding dried maize grains (FDA 2011) including nixtamalised dehydrated corn flour, also known as 'masa flour', as well as precooked corn flour. Composite flours that contain more than 50% maize will be included within the definition of flour in this review. Maize flour products include all products derived from fortified corn meal and flour (i.e. breads, cereals, polenta, porridges, grits, arepas). Included studies will be those where fortification of the maize flour or corn meal occurs during the flour production.

Comparisons to be made include:

  1. maize flour or maize flour products fortified with iron alone versus no intervention;
  2. maize flour or maize flour products fortified with iron plus other vitamins and minerals versus no intervention;
  3. maize flour or maize flour products fortified with iron alone versus unfortified maize flours or maize flour products (not containing iron nor any other vitamin and minerals);
  4. maize flour or maize flour products fortified with iron plus other vitamins and minerals versus unfortified maize flours or maize flour products (not containing iron nor any other vitamin and minerals).

We will include studies with co-interventions (e.g. fortified maize flour with education) only if the comparison group also receives the co-intervention (education component).

We will exclude studies evaluating products derived from wet milling of maize, including corn starch (which is often called 'corn flour' in the United Kingdom and Australia) and products that are fortified after recomposition of the flour will be excluded. For example, if maize flour is used to prepare a bread product, and fortification occurs at the level of bread or tortilla production, this will not be included.

We will not include comparisons of maize (corn) fortification versus other forms of micronutrient interventions comprising iron supplementation, point-of-use fortification of maize products with micronutrients powders or lipid-based spreads, bio fortification or fortification of wheat flour with iron or folic acid. These are currently subjects of other Cochrane systematic reviews and will be excluded from this review.

 

Types of outcome measures

 

Primary outcomes

The primary outcomes across all populations in this review are the presence of anaemia, iron deficiency, haemoglobin concentrations, iron status and any adverse effects.

 
Children (2 to 11.9 years of age)

  1. Anaemia (defined as haemoglobin (Hb) below 110 g/L or 115 g/L, adjusted for altitude as appropriate).
  2. Iron deficiency (as defined by trialists, based on a biomarker of iron status).
  3. Haemoglobin concentration (in g/L).
  4. Iron status (as reported: ferritin, transferrin saturation, soluble transferrin receptor, soluble transferrin receptor-ferritin index, total iron binding capacity, serum iron).
  5. Any adverse side effects (including constipation, nausea, vomiting, heartburn or diarrhoea, as measured by trialists).

 
Adolescent girls and boys  (12 to 18.9 years of age)

  1. Anaemia (defined as Hb below 115 g/L or 120 g/L, adjusted for altitude and smoking as appropriate).
  2. Iron deficiency  (as defined by trialists, based on a biomarker of iron status).
  3. Haemoglobin concentration (in g/L).
  4. Iron status (as reported: ferritin, transferrin saturation, soluble transferrin receptor, soluble transferrin receptor-ferritin index, total iron binding capacity, serum iron).
  5. Any adverse side effects (including constipation, nausea, vomiting, heartburn or diarrhoea, as measured by trialists).

 
Pregnant women (any age)

  1. Anaemia (defined as Hb below 110 g/L at any trimester of pregnancy, adjusted for altitude and smoking as appropriate).
  2. Iron deficiency (as defined by trialists, based on a biomarker of iron status).
  3. Haemoglobin concentration (in g/L).
  4. Iron status (as reported: ferritin, transferrin saturation, soluble transferrin receptor, soluble transferrin receptor-ferritin index, total iron binding capacity, serum iron).
  5. Any adverse side effects (including constipation, nausea, vomiting, heartburn or diarrhoea, as measured by trialists).

 
Adult males and females  (19 years of age or older)

  1. Anaemia (defined as Hb below 120 g/L or 130 g/L, adjusted for altitude and smoking as appropriate).
  2. Iron deficiency (as defined by trialists, based on a biomarker of iron status).
  3. Haemoglobin concentration (in g/L).
  4. Iron status (as reported: ferritin, transferrin saturation, soluble transferrin receptor, soluble transferrin receptor-ferritin index, total iron binding capacity, serum iron).
  5. Any adverse side effects (including constipation, nausea, vomiting, heartburn or diarrhoea, as measured by trialists).

 

Secondary outcomes

Secondary outcomes of interest may differ by participant group and we have listed these accordingly.

 
Children (2 to 11.9 years of age)

  1. Iron deficiency anaemia (as defined by trialists).
  2. Cognitive development (as defined by trialists).
  3. Motor skill development (as defined by trialists).
  4. Growth: height-for-age (Z scores).
  5. Growth: weight-for-height (Z scores).
  6. Malaria severity (only for malaria settings).
  7. Malaria incidence (only for malaria settings).

 
Adolescents (12 to 18.9 years of age)

  1. Iron deficiency anaemia (as defined by trialists).
  2. Malaria severity (only for malaria settings).
  3. Malaria incidence (only for malaria settings).

 
Pregnant women (any age)

  1. Iron deficiency anaemia (as defined by trialists).
  2. Premature birth (less than 37 weeks).
  3. Very premature birth (less than 34 weeks).
  4. Low birth weight (less than 2500 g).
  5. Congenital anomalies (including neural tube defect, cleft lip, cleft palate, congenital cardiovascular defects and other birth defects as reported by trialists).
  6. Malaria severity (only for malaria settings).
  7. Malaria incidence (only for malaria settings).

 
Adults (male and females 19 years of age and older)

  1. Iron deficiency anaemia (as defined by trialists).
  2. Work capacity (as defined by trialists).
  3. High ferritin concentrations (defined as more than 150 mg/L).
  4. Malaria severity (only for malaria settings).
  5. Malaria incidence (only for malaria settings).

 
All groups

If the reports also present figures with combined data for all populations, we will also include them.

 

Search methods for identification of studies

 

Electronic searches

We will search the following international and regional sources.

 

International databases

  1. Cochrane Central Register of Controlled Trials (CENTRAL)
  2. MEDLINE
  3. MEDLINE (R) In Process
  4. EMBASE
  5. Web of Science (both the Social Science Citation Index and the Science Citation Index)
  6. CINAHL
  7. POPLINE
  8. BIOSIS
  9. Food Science and Technology Abstracts (FSTA)
  10. OpenGrey (Grey literature resource)
  11. Bibliomap and TRoPHI

 

Regional databases

  1. Global Index Medicus - AFRO (includes African Index Medicus); EMRO (includes Index Medicus for the Eastern Mediterranean Region)
  2. LILACS
  3. PAHO (Pan American Health Library)
  4. WHOLIS (WHO Library)
  5. WPRO (includes Western Pacific Region Index Medicus)
  6. IMSEAR, Index Medicus for the South-East Asian Region
  7. IndMED, Indian medical journals (http://indmed.nic.in/)
  8. Native Health Research Database (https://hscssl.unm.edu/nhd/)

For theses we will search WorldCat, Networked Digital Library of Theses and Dissertations, DART-Europe E-theses Portal, Australasian Digital Theses Program, Theses Canada Portal and ProQuest-Desertations and Theses.

We will also contact the Trials Search Co-ordinator of the Cochrane Public Health Group to search the Cochrane Public Health Group Specialised Register.

The search will use keyword and controlled vocabulary (when available), using the search terms set out in Appendix 1 and we will adapt them as appropriate for each database. We will not apply any language or date restrictions.

We will handsearch the five journals with the highest number of included studies in the last 12 months to capture any article that may not have been indexed in the databases at the time of the search. As maize fortification technologies are not novel, we will not apply time restrictions for all databases. We will contact authors of included studies and check reference lists of included papers for identification of additional records.

We will search the International Clinical Trials Registry Platform (ICTRP) for any ongoing or planned trials, and contact authors of such studies to obtain further information or eligible data if available.

If we identify articles written in a language other than English, we will commission their translations into English. If this is not possible, we will seek advice from the Cochrane Public Health Group. We will store such articles in the 'Awaiting assessment' section of the review until a translation is available.

 

Searching other resources

For assistance in identifying ongoing or unpublished studies, we will contact the Department of Nutrition for Health and Development and the regional offices from the World Health Organization (WHO), as well as the nutrition section of the Centers for Disease Control and Prevention (CDC), the United Nations Children's Fund (UNICEF), the World Food Programme (WFP), the Micronutrient Initiative (MI), Global Alliance for Improved Nutrition (GAIN), Hellen Keller International (HKI), World Vision, Sight and Life, PATH, premix producers DSM and BASF and the Flour Fortification Initiative (FFI).

 

Data collection and analysis

 

Selection of studies

 

Managing references identified by the search strategy

Two review authors will screen the titles and abstracts of articles retrieved by each search independently to assess eligibility, as determined by the inclusion and exclusion criteria listed above. We will retrieve full copies of all eligible papers. When a title or abstract cannot be rejected with certainty, we will obtain the full text of the article for further evaluation. If full articles cannot be obtained, we will attempt to contact the authors to obtain further details of the study. Failing this, we will classify studies as 'awaiting assessment' until further information is published or made available to us. Disagreements at any stage of eligibility assessment process will be resolved through discussion and consultation with a third author where necessary.

 

Data extraction and management

Two review authors will extract data independently using data extraction forms based on those from the Cochrane Public Health Group (Cochrane PHG 2010) and the Cochrane Effective Practice and Organisation of Care (EPOC) Group.

All review authors will be involved in piloting the form using a subset of articles to enhance consistency amongst review authors and, based on this, we will modify the form if necessary. We will collect information on study design, study setting and participants (number and characteristics), and provide a full description of the interventions examined. We will extract details of outcomes measured (including a description of how and when outcomes were measured) and results.

We will design the form so that we are able to record results for our prespecified outcomes and for other (non-prespecified) outcomes (although such outcomes will not underpin any of our conclusions). We will extract additional items relating to study recruitment and the implementation of the intervention; these will include number of sites for an intervention, whether recruitment was similar at different sites, whether there were protocol deviations, levels of compliance/use of flours in different sites within studies, resources required for implementation, as well as findings from process evaluations conducted.

We will use the PROGRESS (place of residence, race/ethnicity, occupation, gender, religion/culture, education, socio-economic status, social capital) checklist to measure disadvantage across categories of social differentiation and will record whether or not data have been reported by socio-demographic characteristics known to be important from an equity perspective (Ueffing 2011). We will also record whether or not studies included specific strategies to address diversity or disadvantage. We will identify factors that determine the differential availability, accessibility, acceptability and effective usage of fortified maize flour and corn meal among population groups and will categorise them. Also we will define key areas of monitoring and suggest appropriate policy action to promote equity in access to these products. We will describe any financial issues related to the implementation of maize flour and corn meals fortification programmes, considering existing facilities, production and considerations for implementation of fortifying maize flours and corn meals in countries with different levels of market development.

We will highlight especially the importance of a significant difference in iron status by fortifying maize flours or cornmeal for the health and nutritional implications in  countries where maize is a staple food.

For eligible studies, two review authors will independently extract data using the agreed form. Two authors will enter data into Review Manager software (RevMan 2011) and two other authors will carry out checks for accuracy. We will resolve any discrepancies through discussion.

When information regarding any aspect of study design or results is unclear, we will attempt to contact authors of the original reports, asking them to provide further details.

 

Assessment of risk of bias in included studies

We will use the EPOC 'Risk of bias' tool for studies with a separate control group to assess the risk of bias of all studies (EPOC 2009). This includes five domains of bias: selection, performance, attrition, detection and reporting, as well as an 'other' bias category to capture other potential threats to validity.

Two review authors will independently assess risk of bias for each study and we will resolve any disagreement by discussion or by involving an additional review team member.

 

Assessing risk of bias in randomised trials

 
(1) Sequence generation (checking for possible selection bias)

We will assess studies as:

  • low risk of bias if there is a random component in the sequence generation process (any truly random process, e.g. random number table; computer random number generator);
  • high risk of bias if a non-random approach has been used (any non-random process, e.g. odd or even date of birth; hospital or clinic record number);
  • unclear risk of bias if not specified in the paper.   

 
(2) Allocation concealment (checking for possible selection bias)

We will assess studies as:

  • low risk of bias if participants and investigators enrolling participants could not foresee assignment because an appropriate method was used to conceal allocation (e.g. telephone or central randomisation; consecutively numbered sealed opaque envelopes). This rating will be given to studies where the unit of allocation was by institution and allocation was performed on all units at the start of the study;
  • high risk of bias if participants of investigators enrolling participants could possibly foresee assignments and potentially introduce selection bias (e.g. open random allocation; unsealed or non-opaque envelopes);
  • unclear risk of bias if not specified in the paper, and the unit of allocation was not by institution, performed on all units at the start of the study.   

 
(3) Similarity of baseline outcome measurements (checking for confounding, a potential consequence of selection bias)

We will assess studies as:

  • low risk of bias if outcomes were measured prior to the intervention, and no important differences were present across intervention groups;
  • high risk of bias if important differences in outcomes between groups were present prior to intervention and were not adjusted for in analysis;
  • unclear risk of bias if there was no baseline measure of outcome (note: if 'high' or 'unclear' but there is sufficient information to do an adjusted analysis, the assessment should be 'low').

 
(4) Similarity of baseline characteristics (checking for confounding, a potential consequence of selection bias)

We will assess studies as:

  • low risk of bias if baseline characteristics are reported and similar across intervention groups;
  • high risk of bias if baseline characteristics are not reported or if there are differences across groups;
  • unclear risk of bias if it is not clear (e.g. characteristics mentioned in text but no data presented).

 
5) Incomplete outcome data (checking for possible attrition bias through withdrawals, dropouts and protocol deviations)

We will assess outcomes in each included study as:

  • low risk of bias due to incomplete outcome data (this could be either that there were no missing outcome data, or that the missing outcome data were unlikely to bias the results based on the following considerations: study authors provided transparent documentation of participant flow throughout the study; the proportion of missing data was similar in the intervention and control groups; the reasons for missing data were provided and balanced across intervention and control groups; the reasons for missing data were not likely to bias the results (e.g. moving house));
  • high risk of bias if missing outcome data were likely to bias the results. Studies will also receive this rating if an 'as-treated (per protocol)' analysis is performed with substantial differences between the intervention received and that assigned at randomisation, or if potentially inappropriate methods for imputation have been used;
  • unclear risk of bias if participant flow throughout the study is not sufficiently documented to assess as either low risk of bias or high risk of bias based on the above criteria.

 
(6) Blinding (checking for possible performance and detection bias)

We will assess the risk of performance bias associated with blinding as:

  • low, high or unclear risk of bias for participants;
  • low, high or unclear risk of bias for personnel.

We will assess the risk of detection bias associated with blinding as:

  • low, high or unclear risk of bias for outcome assessors.

Whilst assessed separately, we will combine the results into a single evaluation of risk of bias associated with blinding as:

  • low risk of bias if there was blinding of participants and key study personnel and it was unlikely to have been broken, or the outcomes are objective. We will also give this rating to studies where either participants and key study personnel were not blinded, but outcome assessment was blinded and the non-blinding of others was unlikely to introduce bias;
  • high risk of bias if there was no blinding or incomplete blinding, or if there was blinding that was likely to have been broken, and the outcome or outcome assessment was likely to be influenced by a lack of blinding;
  • unclear risk of bias if not specified in the paper.

 
(7) Contamination (checking for possible performance bias)

We will assess studies as:

  • low risk of bias if allocation was by community, institution or practice and it is unlikely that the control group received the intervention;
  • high risk of bias if it is likely that the control group received the intervention;
  • unclear risk of bias if it is possible that contamination occurred but the risk of this happening is not clear.

 
(8) Selective reporting bias

We will describe for each included study how we investigated the possibility of selective outcome reporting bias and what we found. We will assess studies for this domain as:

  • low risk of bias (where it is clear that all of the study’s pre-specified outcomes and all expected outcomes of interest to the review have been reported);
  • high risk of bias (where not all the study’s pre-specified outcomes have been reported; one or more reported primary outcomes were not pre-specified; outcomes of interest were reported incompletely and so cannot be used; study fails to include results of a key outcome that would have been expected to have been reported); or
  • risk of bias unclear if it cannot be determined as either low risk of bias or high risk of bias based on the above criteria.

 
(9) Other sources of bias

We will describe other possible sources of bias for each included study and give a rating of low, high or unclear risk of bias for this item.

 

Assessing risk of bias in interrupted time-series (ITS)

We will assess the risk of bias for ITS studies using the EPOC 'Risk of bias' tool for ITS study designs which includes items (5), (6), (8) and (9) from the EPOC 'Risk of bias' tool above, as well as the following additional items:

  1. Was the intervention independent of other changes?
    1. low risk of bias if there are compelling arguments that the intervention occurred independently of other changes over time and the outcome was not influenced by other confounding variables/historic events during the study period;
    2. high risk of bias if it is reported or if there are grounds to suspect that the intervention was not independent of other changes over the time period of the study;
    3. unclear risk of bias if it is not clear from the information provided.
  2. Was the shape of the intervention effect pre-specified?
    1. low risk of bias if the point of analysis is the point of intervention or a rational explanation for the shape of the intervention effect was provided;
    2. hIgh risk of bias if it clear that these conditions were not met;
    3. unclear risk of bias if it is not clear from the information provided.
  3. Was the intervention unlikely to affect data collection?
    1. low risk of bias if it is reported that the intervention itself was unlikely to affect data collection (e.g. sources and methods of data collection were the same before and after the intervention);
    2. high risk of bias if the intervention itself was likely to affect data collection;
    3. unclear risk of bias if it is not clear from the information provided.

 

Overall risk of bias

For all included studies, we will summarise the overall risk of bias by primary outcome within each study. Studies at high risk of bias will be those with high or unclear risk of bias in the following domains: allocation concealment, similarity of baseline outcome measurements, completeness of outcome data. Judgements will also take into account the likely magnitude and direction of bias and whether it is likely to impact on the findings of the study.  

If there is insufficient information in study reports for us to be able to assess risk of bias, studies will await assessment until further information is published, or made available to us.

We will set out the main findings of the review in 'Summary of findings' (SoF) tables prepared using GRADE profiler software (GRADEpro 2008). We will list the primary outcomes for each comparison with estimates of relative effects along with the number of participants and studies contributing data for those outcomes. For each individual outcome, we will assess the quality of the evidence using the GRADE approach (Balshem 2010), which involves consideration of within-study risk of bias (methodological quality), directness of evidence, heterogeneity, precision of effect estimates and risk of publication bias. We will express the results as one of four levels of quality (high, moderate, low or very low).

 

Measures of treatment effect

 

Dichotomous data

For dichotomous data, we will present proportions and, for two-group comparisons, results as average risk ratio (RR) or odds ratio (OR) with 95% confidence intervals (95% CI).

 

Continuous data

We will report results for continuous outcomes as the mean difference (MD) with 95% confidence intervals if outcomes are measured in the same way between trials. Where some studies have reported endpoint data and others have reported change from baseline data (with errors) we will combine these in the meta-analysis if the outcomes have been reported using the same scale.

We will use standardised mean difference (SMD) with 95% confidence intervals to combine trials that measure the same outcome (e.g. haemoglobin) but use different methods.

If we do not find enough studies, or the studies cannot be pooled, we will summarise the results in a narrative form.

 

Unit of analysis issues

 

Cluster-randomised trials

We will combine results from both cluster and individually randomised studies if there is little heterogeneity between the studies. Cluster-randomised trials will be labelled with a (C). If the authors of cluster-randomised trials have conducted their analyses at a different level to that of allocation and they have not appropriately accounted for the cluster design in their analyses, we will calculate trials' effective sample size to account for the effect of clustering in data. We will utilise the intra cluster correlation coefficient (ICC) derived from the trial (if available), or from another source (e.g. using the ICCs derived from other, similar trials) and then calculate the design effect with the formula provided in the Cochrane Handbook for Systematic Reviews of Interventions (Higgins 2011). If this approach is used, we will report this and undertake sensitivity analysis to investigate the effect of variations in ICC.

 

Studies with more than two treatment groups

If we identify studies with more than two intervention groups (multi-arm studies), where possible we will combine groups to create a single pair-wise comparison or use the methods set out in the Cochrane Handbook to avoid double-counting study participants (Higgins 2011). For the subgroup analyses, when the control group is shared by two or more study arms, we will divide the control group (events and total population) over the number of relevant subgroups to avoid double-counting the participants.

 

Cross-over trials

From cross-over trials, we will consider the first period of measurement only and we will analyse the results together with the parallel-group studies.

 

Dealing with missing data

We will try to contact the authors if missing outcome data are unclear or have not been fully reported. We will capture the missing data in the data extraction form and report it in the 'Risk of bias' tables.

For all outcomes, we will carry out analysis, as far as possible, on an intention-to-treat basis, i.e. for randomised trials, we will attempt to include all participants randomised to each group in the analyses. The denominator for each outcome in each trial will be the number randomised, minus any participants whose outcomes are known to be missing. For non-randomised studies, where possible, we will analyse data according to initial group allocation irrespective of whether or not participants received, or complied with, the planned intervention.

When assessing adverse events, adhering to the principle of 'intention-to-treat' may be misleading, thus we will relate the results to the treatment received ('per protocol' or 'as observed'). This means that for side effects, we will base the analyses on the participants who actually received treatment and the number of adverse events that are reported in the studies.

 

Assessment of heterogeneity

We will examine the forest plots from meta-analysis to visually assess the level of heterogeneity (in terms of the size or direction of treatment effect) among studies. We will use the I2 and Tau2 statistics, and the Chi2 test to quantify the level of heterogeneity among the trials in each analysis. If we identify moderate or substantial heterogeneity, we will explore it by pre-specified subgroup effects analysis.

Heterogeneity may be a particular concern in non-randomised studies, and where there is evidence of heterogeneity, we will summarise findings using a forest plot but will not present the pooled estimate.

We will exercise caution in the interpretation of those results with high levels of unexplained heterogeneity.

 

Assessment of reporting biases

Where we suspect reporting bias (see 'Selective reporting bias' above), we will attempt to contact study authors asking them to provide missing outcome data. Where this is not possible, and the missing data are thought to introduce serious bias, we will explore the impact of including such studies in the overall assessment of results by a sensitivity analysis.

If more than 10 studies reporting the same outcome of interest are available, we will generate funnel plots in RevMan 2011 and visually examine them for asymmetry. Where we pool studies in meta-analysis we will order studies in terms of weight, so that a visual examination of forest plots may allow us to assess whether the results from smaller and larger studies are similar, or if there are any apparent differences (i.e. we will check that the effect size is similar in smaller and larger studies).

 

Data synthesis

We will carry out meta-analysis to provide an overall estimate of treatment effect when more that one study examines the same intervention, provided that studies use similar methods, and measure the same outcome in similar ways in similar populations. We will not combine results from randomised and non-randomised trials together in meta-analysis, nor will we present pooled estimates for non-randomised studies with different types of study designs. Evidence on different outcomes may be available from different types of studies (for example, it is likely that data on less common adverse events will be reported in larger non-randomised studies). Where there is evidence on a particular outcome from both randomised trials and non-randomised studies, we will use the evidence from trials which are at lower risk of bias to estimate treatment effect.

Where there is evidence from several randomised trials, or non-randomised studies at low risk of bias, we will carry out statistical analysis using the Review Manager software (RevMan 2011). We will use a random-effects meta-analysis for combining data, as we anticipate that there may be natural heterogeneity between studies attributable to the different doses, durations, populations and implementation/delivery strategies. For continuous variables we will use the inverse variance method while for dichotomous variables we will use the one proposed by Mantel-Haenszel (Higgins 2011).

For non-randomised studies, where results have been adjusted to take account of possible confounding factors, we will use the generic inverse variance method in RevMan 2011 to carry out any meta-analysis (if both adjusted and non-adjusted figures are provided we will carry out a sensitivity analysis using the unadjusted figures to examine any possible impact on the estimate of treatment effect).

We will explore heterogeneity according the subgroups identified below in the next section. In addition, we will use narrative synthesis, guided by the data extraction form in terms of the ways in which studies may be grouped and summarised, in this review to explore intervention implementation (using information about resource use and findings from process evaluations), and describe the impact of interventions by socio-demographic characteristics known to be important from an equity perspective based on the PROGRESS framework, where this information is available.

 

Subgroup analysis and investigation of heterogeneity

Where data are available we will conduct the following subgroup analyses:

  1. by prevalence of anaemia among trial participants: less than 20%; 20% to 39%; 40% or higher;
  2. by sex: males; females; mixed/unknown;
  3. by type of processing: whole maize milled meal; degermed maize milled meal; nixtamalised flour, precooked refined, others including mixtures of cereal flours;
  4. by type or iron compound: high relative bioavailability (e.g. iron EDTA) versus ferrous sulphate and comparable relative bioavailability (e.g. fumarate) versus low relative bioavailability (e.g. reduced iron, electrolytic iron, others);
  5. by extraction rate: less than 70% de-germinated, 70-95% partially de-germinated, 95-100% whole grain-fat 3.5-5.0% or unknown/mixed/unreported.
  6. by corn meal fibre/phytate content;
  7. by malaria endemicity at the time that the trial was conducted: malaria setting versus non/unknown malaria setting;
  8. by length of the intervention: less than six months; six months to one year; more than one year;
  9. by dose of iron per 100 g of product.

We will only use the primary outcomes in subgroup analysis. We will limit this analysis to those outcomes for which three or more trials contributed data.

We will examine differences between subgroups by visual inspection of the subgroups’ confidence intervals; non-overlapping confidence intervals suggesting a statistically significant difference in treatment effect between the subgroups. We will also formally investigate differences between two or more subgroups (Borenstein 2008). We will conduct analyses in Review Manager (RevMan 2011).

 

Sensitivity analysis

We will carry out sensitivity analysis to examine the effects of removing studies at high risk of bias (those with high or unclear risk of bias for allocation concealment, lack of similarity of baseline outcome measurements, or incomplete outcome data) from the meta-analysis. If cluster trials are included, we will carry out sensitivity analysis using a range of intra-cluster correlation values.

 

Acknowledgements

  1. Top of page
  2. Background
  3. Objectives
  4. Methods
  5. Acknowledgements
  6. Appendices
  7. History
  8. Contributions of authors
  9. Declarations of interest
  10. Sources of support

We would like to thank the Cochrane Public Health Group for support in the preparation of this protocol. As part of the pre-publication editorial process, this review will be commented on by external peers (an editor and two referees who are external to the editorial team) and one of the Group's statisticians.

 

Appendices

  1. Top of page
  2. Background
  3. Objectives
  4. Methods
  5. Acknowledgements
  6. Appendices
  7. History
  8. Contributions of authors
  9. Declarations of interest
  10. Sources of support
 

Appendix 1. Ovid MEDLINE(R) search strategy

1     Flour/

2     Zea mays/

3     (z$ mays or zeamays).tw.

4     (corn or cornmeal or cornflour$).tw.

5     (maize or mielies or mealies).tw.

6     or/1-5

7     Food, Fortified/

8     Iron/

9     exp Iron Compounds/

10     (Fe or ferrous or ferric).tw.

11     NaFeEDTA.tw.

12     (iron adj5 (enhanc$ or enrich$ or fortif$)).tw.

13     (iron adj5 (cereal$ or diet$ or flour$ or food$ or intake$)).tw.

14     or/7-13

15     6 and 14

16     exp animals/ not humans/

17     15 not 16 (910) 

We will modify search terms as necessary when searching other databases. We will not apply any date or language restrictions, and will obtain translations of relevant data where necessary.

 

History

  1. Top of page
  2. Background
  3. Objectives
  4. Methods
  5. Acknowledgements
  6. Appendices
  7. History
  8. Contributions of authors
  9. Declarations of interest
  10. Sources of support

Protocol first published: Issue 11, 2012

 

Contributions of authors

  1. Top of page
  2. Background
  3. Objectives
  4. Methods
  5. Acknowledgements
  6. Appendices
  7. History
  8. Contributions of authors
  9. Declarations of interest
  10. Sources of support

Sant-Rayn S Pasricha drafted an initial protocol with technical input from Maria Nieves Garcia-Casal, Luz Maria De-Regil and Juan Pablo Pena-Rosas. Luz Maria De-Regil, Belinda Burford and Juan Pablo Pena-Rosas developed the methods of the protocol. All authors provided input and contributed to drafting the final version of the protocol.

Disclaimer: Juan-Pablo Pena-Rosas and Luz Maria De-Regil are full-time staff members of the World Health Organization. The authors alone are responsible for the views expressed in this publication and they do not necessarily represent the decisions, policy or views of the World Health Organization.

 

Declarations of interest

  1. Top of page
  2. Background
  3. Objectives
  4. Methods
  5. Acknowledgements
  6. Appendices
  7. History
  8. Contributions of authors
  9. Declarations of interest
  10. Sources of support

Sant-Rayn S Pasricha - none.

Luz Maria De-Regil - none.

Maria Nieves Garcia-Casal - none.

Belinda Burford - none.

Dr Jeffrey Gwirtz is a consultant for the Flour Fortification Initiative (FFI), a network of partners working together to make flour fortification standard milling practice. FFI builds alliances between governments and international agencies, wheat and flour industries, and consumer and civic organisations. He also is a technical advisor to the International Association of Operative Millers (IAOM) on various consulting projects in the grain processing industry (private and governmental sectors) requiring both practical and academic experience.

Juan Pablo Pena-Rosas - none.

 

Sources of support

  1. Top of page
  2. Background
  3. Objectives
  4. Methods
  5. Acknowledgements
  6. Appendices
  7. History
  8. Contributions of authors
  9. Declarations of interest
  10. Sources of support
 

Internal sources

  • Evidence and Programme Guidance Unit, Department of Nutrition for Health and Development, World Health Organization, Switzerland.
  • Government of Victoria, Australia.
    Dr Sant-Rayn Parisha worked on the protocol during an internship at the World Health Organization. He was partially supported by the Government of Victoria, Australia
  • CRB Blackburn Travelling Scholarship (Royal Australasian College of Physicians), Australia.
    Dr Sant-Rayn Parisha worked on the protocol during an internship at the World Health Organization. He was partially supported by the CRB Blackburn Travelling Scholarship (Royal Australasian College of Physicians).
  • University of Melbourne Overseas Research Experience Scholarship, Australia.
    Dr Sant-Rayn Parisha worked on the protocol during an internship at the World Health Organization. He was partially supported by the Government of Victoria, Australia, CRB Blackburn Travelling Scholarship (Royal Australasian College of Physicians) and a University of Melbourne Overseas Research Experience Scholarship.

 

External sources

  • Global Alliance for Improved Nutrition (GAIN), Switzerland.
    WHO acknowledges the Global Alliance for Improved Nutrition (GAIN) for their financial support to the Evidence and Programme Guidance Unit for conducting systematic reviews on micronutrients interventions.
  • Evidence and Programme Guidance Unit, Department of Nutrition for Health and Development, World Health Organization, Switzerland.
    Dr Maria Nieves Garcia-Casal, Dr Jeff Gwirtz and Dr Belinda J Burford receive partial financial support from the Department of Nutrition for Health and Development for this work.

References

Additional references

  1. Top of page
  2. Abstract
  3. Background
  4. Objectives
  5. Methods
  6. Acknowledgements
  7. Appendices
  8. History
  9. Contributions of authors
  10. Declarations of interest
  11. Sources of support
  12. Additional references
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