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Fortification of staple foods with zinc for improving zinc status and other health outcomes in the general population

  1. Dheeraj Shah1,*,
  2. Harshpal S Sachdev2,
  3. Tarun Gera3,
  4. Luz Maria De-Regil4,
  5. Juan Pablo Peña-Rosas4

Editorial Group: Cochrane Public Health Group

Published Online: 13 AUG 2013

Assessed as up-to-date: 1 AUG 2013

DOI: 10.1002/14651858.CD010697


How to Cite

Shah D, Sachdev HS, Gera T, De-Regil LM, Peña-Rosas JP. Fortification of staple foods with zinc for improving zinc status and other health outcomes in the general population (Protocol). Cochrane Database of Systematic Reviews 2013, Issue 8. Art. No.: CD010697. DOI: 10.1002/14651858.CD010697.

Author Information

  1. 1

    University College of Medical Sciences (University of Delhi), Department of Pediatrics, New Delhi, Delhi, India

  2. 2

    Sitaram Bhartia Institute of Science and Research, Department of Pediatrics and Clinical Epidemiology, New Delhi, India

  3. 3

    SL Jain Hospital, Department of Pediatrics, New Delhi, India

  4. 4

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

*Dheeraj Shah, Department of Pediatrics, University College of Medical Sciences (University of Delhi), Dilshad Garden, New Delhi, Delhi, 110095, India. shahdheeraj@hotmail.com.

Publication History

  1. Publication Status: New
  2. Published Online: 13 AUG 2013

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Background

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

Description of the condition

Nutritional deficiencies continue to affect many people in low and middle income countries. Insufficient consumption of protein, energy and micronutrients, particularly iodine, iron, vitamin A and zinc, puts them at an increased risk of disease and death (WHO 2009a).

Zinc is a vital constituent of many metallo-enzymes important for the normal functioning of the human reproductive, neurologic, immune, dermatologic and gastrointestinal systems. This nutrient is widely present in foods. The highest concentrations are found in meat, fish and shellfish, nuts, seeds, legumes and whole grain cereals; lower concentrations are found in tubers. Animal products contain substantial amounts of zinc in a readily absorbable form. Conversely, zinc from whole grain cereals and legumes is absorbed less efficiently because uptake by the intestine is inhibited by other dietary components, such as fibre and phytate (Gibson 2012). As most of the diets in low-income households are rich in these foods, people eating them are more likely to develop zinc deficiency. Groups that are especially vulnerable to zinc deficiency include infants and young children who are receiving unfortified complementary foods, children recovering from malnutrition, adolescents, pregnant and lactating women, and the elderly.

Zinc deficiency is believed to be widespread globally, particularly in children and women residing in low and middle income countries. Data from these countries indicate that zinc deficiency occurs at a sufficient scale to be classified as a significant public health problem (Kapil 2011; Shah 2011, Wessells 2012). Estimates based on dietary zinc and phytate intakes suggest that more than 25% of the population in Latin America and the Caribbean, South and Southeast Asia, and sub-Saharan Africa is at risk of inadequate zinc intake (IZiNCG 2004). Zinc deficiency, in combination with other micronutrient deficiencies - such as iron or vitamin A, childhood undernutrition, and sub optimal breastfeeding causes 7% of deaths and 10% of the total disease burden (WHO 2009a). The combined burden from these nutritional risks is considered to be equivalent to the entire disease and injury burden of high-income countries (WHO 2009a).

The manifestation and severity of zinc deficiency varies at different ages. Zinc is ubiquitous, and because of its involvement in so many core areas of metabolism, the features of mild zinc deficiency are frequently nonspecific. Zinc deficiency in childhood may lead to diarrhoea (Lazzerini 2012), impairment of cognitive function and behavioural problems (Gogia 2012), hair loss, inflammation of the eyelids and conjunctiva, growth retardation (Imdad 2011; Levenson 2011), and recurrent infections (Yakoob 2011). Fertility, reproductive performance, and work capacity are also affected in adolescents and adults (Atig 2012; Bernhardt 2012; Kawade 2012; Lukaski 2000; Shah 2006), while infections are recurrent among the elderly (Pae 2012).

Most dietary zinc is absorbed by the small intestine, particularly in the jejunum, and the efficiency of intestinal zinc absorption is increased when there is zinc depletion. Once absorbed, it is bound to albumin, and transported from the intestine into the body. Zinc is found in all body tissues, with approximately 85% of the whole body zinc residing in muscle and bone and 11% in the skin and liver. The remaining 2% to 3% of the whole body zinc is found in the other tissues, including only 0.1% in the plasma (King 2000). Homeostatic regulation of zinc metabolism is achieved by adjusting zinc absorption and endogenous intestinal excretion from pancreatic and intestinal cell secretions (King 2000).

Biochemical and functional markers of zinc status are needed to assess the impact of programmes aimed at improving the zinc nutrition of populations. At present there are no simple, quantitative markers of zinc status that can be used to identify zinc deficiency in individuals. However, the International Zinc Nutrition Consultative Group recommends serum or plasma zinc as the best available biomarker of the zinc status in populations (IZiNCG 2004), because of its correlation with dietary zinc intake and a consistent response to zinc supplementation (de Benoist 2007; Hess 2009a). Serum zinc concentrations range between 80 µg/dL and 100 µg/dL (12 µmol/L to 15 µmol/L) in healthy adults, although concentrations differ by sex, age, infection, and fasting status. Currently there are reference data for most age and sex groups, and it has been proposed that if more than 20% of the population (or population sub-group) falls below the corresponding cut-off, the whole population (or sub-group) should be considered to be at risk of zinc deficiency (IZiNCG 2004).

Other biomarkers have also been suggested for assessing zinc status, including erythrocyte (red blood cell) zinc, hair zinc or alkaline phosphatase activity, but there are still many issues pending regarding their sensitivity, specificity, reliability and feasibility of use in the field. Stunting (low height- or length-for-age), however, remains as the preferred functional marker of zinc status, as it is often responsive to supplemental zinc, and is widely used in most health and nutrition monitoring activities (de Benoist 2007).

 

Description of the intervention

Fortification is defined as the process of adding nutrients to commonly eaten foods, beverages or condiments during food processing at the industrial (central) level, with the goal of improving the quality of the diet. Fortification programmes represent promising long-term strategies to combat various micronutrient deficiencies among recipients. For some vitamins and minerals, fortification has played a major role in increasing their dietary intake and has contributed to the elimination of vitamin and mineral malnutrition in certain settings. Fortification is postulated to have the advantages of better compliance, long-term sustainability, and potential to reach the intended population (WHO/FAO 2006). Iron and folic acid are two nutrients commonly added to staple foods and condiments. Fortification of foods with iron has been proved to improve iron status, and haemoglobin, along with a significant reduction of anaemia in the general population (Gera 2012). Fortification of cereal products, including wheat flour, with folic acid has also contributed to a reduction of neural tube defect-affected pregnancies (e.g. spina bifida) in some countries (Castillo-Lancellotti 2012). Thus, it is postulated that fortification of staple foods with zinc could result in an increased daily zinc intake, which may prevent deficiency, and improve zinc-related health outcomes.

The World Health Organization recommends the addition of zinc to wheat and maize (also known as corn) flours (WHO 2009b). However, the addition of this micronutrient to foods has generally been confined to infant formula milks (in the form of zinc sulphate), complementary foods and ready-to-eat breakfast cereals. In some countries - such as Indonesia - it is mandatory to add zinc to wheat noodles, while other countries - like Mexico - have voluntary fortification programmes where zinc and other micronutrients are added to wheat and corn flours used for preparing bread and tortillas, milk, and food supplements provided in social programmes. More recently, several Latin American countries have expressed some interest in fortifying cereal flours with zinc (Brown 2010). According to the Flour Fortification Initiative, in 2012 at least 20 countries had mandatory zinc fortification for wheat flour and three countries had it for maize flour, although the level of implementation may vary among countries (Flour Fortification Initiative 2012). From a public health perspective, mandatory fortification of staple foods with zinc has the potential to reach everyone in a population, particularly vulnerable groups. Effective fortification of staple foods with zinc can help ensure access and equity to adequate zinc in the diets of all children and women, especially those who are less well off.

 

How the intervention might work

Staple foods are those eaten regularly, and in such quantities that they constitute the dominant part of the diet, and supply a major proportion of energy and nutrient needs (FAO 2012). Staple foods are acceptable vehicles for a fortification programme as they are consumed by a large portion of the target population in relatively constant amounts. Potentially suitable staple food vehicles for zinc fortification in public health include cereal grains (rice); wheat, and maize flours; condiments and seasonings; and powdered or liquid milk (WHO/FAO 2006). Appropriate fortification of a staple food has the potential to ensure a predictable and fairly stable level of intake of the added nutrient. Moreover, it does not require changes in the dietary habits of the population, thereby simplifying the implementation process.

Zinc is a suitable micronutrient for fortification of staple foods, as total daily zinc absorption has been shown to increase following an increase in dietary zinc (Hess 2009b). Although phytates in food reduce zinc absorption, the total amount of zinc absorbed from fortified foods is greater than the amount absorbed from unfortified foods. Thus, fortification of staple foods with zinc has the potential to improve the zinc nutrition of populations, resulting in better health outcomes, such as improved childhood growth and reduction in infectious morbidity. However, the impact of zinc fortification could be dependent upon the baseline zinc status of populations, choice of food vehicle, dose and duration of the intervention, and selection of the fortificant.

The choice of a particular chemical form of zinc to be used in food fortification should be based on its solubility in water, intragastric (within the stomach) solubility, taste, cost, side effects and safety (IZiNCG 2004). In general, water-soluble compounds, such as zinc-EDTA, zinc acetate, zinc gluconate, and zinc sulphate, are considered to be more readily absorbable than compounds with limited solubility at neutral pH. Zinc sulphate and zinc oxide are thought to be the least expensive and most commonly used by the food industry (Brown 2007; IZINCG 2007).

In addition to efficacy, the effectiveness of fortification of foods with zinc in public health depends on several factors related to policies and legislation, including; production and supply of the fortified food; development of delivery systems; development and implementation of external and internal food quality control systems; and the development and implementation of strategies for information, education and communication for behavioural change among consumers. A generic logic model for micronutrient interventions in public health that depicts these processes and outcomes is presented in Figure 1 (WHO/CDC 2011; De-Regil 2013).

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

The potential concerns of adding zinc to food include its possible interactions with iron and copper. Anaemia may occur in zinc-supplemented populations due to interference with iron absorption, and inhibited iron transport via decreased copper absorption (Dekker 2010).Common metal transporters are involved in active transport of iron, copper and zinc (Espinoza 2012). In-vitro models have demonstrated the reduction in bioavailability of each of these minerals by the presence of other minerals in the diet (Arredondo 2006). Negative effects of zinc supplementation on indices of iron and copper status have been reported (Sandstrom 2001). However, a systematic review reported that zinc supplementation, at doses typically used in randomized trials, does not decrease the haemoglobin concentrations (Dekker 2010). On the other hand, a few randomized controlled trials have documented a beneficial effect of adding zinc to iron treatment on haemoglobin response and iron indices in anaemic women (Kolsteren 1999), and children (Alarcon 2004). The beneficial effects of zinc on haemoglobin concentration can be explained by its role in DNA synthesis (Ishido 1999), modulation of erythropoiesis (red blood cell production), and vitamin A metabolism (Alarcon 2004).

 

Why it is important to do this review

There are very few national surveys reporting on zinc status. Calculations based on diet and stunting suggest that zinc deficiency is widespread in low and middle income countries, especially among women and children. For example, in 2004 zinc deficiency was estimated to be responsible for 260,502 deaths in Africa, 182,546 in Asia and 10,159 in Latin America, accounting for 4.4 % of all childhood deaths between six months and five years of age (Fischer Walker 2009). Recent mathematical models based on national food balance data that were obtained from the Food and Agriculture Organization of the United Nations suggest that the estimated global prevalence of inadequate zinc intake varied between 12% to 66%, depending on which methodological assumptions were applied (Wessells 2012). Studies from developing countries report zinc deficiency of sufficient magnitude to be a significant public health problem (Kapil 2011; Shah 2011). Thus, interventions to improve population zinc status are recommended.

Fortification of food with zinc appears to be a promising strategy because of its relatively low cost and long-term sustainability. In rural Chinese women, for example, zinc concentrations improved  after 24 months of intervention (Hess 2009b; Huo 2011; Huo 2012). Fortification of other foods with zinc has shown that zinc intake and absorption increase when some zinc fortified foods are consumed, but the impact as a public health intervention remains unknown (WHO/FAO 2006). There is a paucity of systematic assessments of the benefits and safety of fortification of foods with zinc to inform public health policy. This systematic review attempts to address the gap in the information on this subject.

 

Objectives

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

To evaluate the beneficial and adverse effects of fortification of staple foods with zinc on health-related outcomes and biomarkers of zinc status in the general population.

 

Methods

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

Criteria for considering studies for this review

 

Types of studies

Randomized controlled trials, randomised at the level of the individual or cluster, will be included in this review. In anticipation of non-availability of sufficient trials of this nature, we plan to include data from the following additional study designs.

  • Non- randomised trials at the level of the individual or cluster. To be eligible, such trials should have a concurrent comparison group (as defined later), preferably with adjustment for baseline characteristics and confounders.
  • Controlled before-after (CBA) studies where allocation to the different comparison groups is not made by the investigators. Outcomes of interest will be measured in both intervention and control groups before zinc fortification intervention is introduced, and again after the intervention has been introduced.

We shall only include cluster-randomised trials, non-randomised cluster trials, and CBA studies with at least two intervention sites and two control sites.

Eligible studies will be included irrespective of the date of publication, language of publication or publication status.

 

Types of participants

Members of the general population who are over two years of age (including pregnant and lactating women), from any country. This age group has been chosen because the types of interventions being evaluated (see below) would be predominantly applicable to this population. We will exclude trials on: (i) participants with a critical illness or severe co-morbidities; (ii) participants who are being tube-fed or are nil-by-mouth; and (iii) older adults in long-term care facilities who would be receiving regular nutrition intervention and monitoring for clinical status. Although the risk of zinc deficiency is greater in low and middle income countries, it can also occur in relatively wealthy countries. We therefore propose to include trials conducted in any country irrespective of the income status, but will perform a sub-group analysis (low and middle income countries versus others) to probe any differences with this categorization.

 

Types of interventions

We will include trials in which common staple foods (e.g. wheat flour, maize flour or corn meal, oils, milk, pulses, bread, sauces, and beverages) or condiments or  seasonings have been industrially (centrally) fortified with zinc, irrespective of the fortification technology (or compound) used. The intervention must have been in operation for a minimum period of two weeks. Studies with co-interventions (for example, nutrition education, deworming, additional food supplementation, diarrhoea control and so forth) will be considered for inclusion if the only difference between the two comparison arms is micronutrient fortification (zinc alone or in combination with additional micronutrients).

We will include the following staple foods and condiments in this review.

The following comparisons will be made.

  • Food fortified with zinc versus same food without added zinc.
  • Food fortified with zinc versus no intervention.
  • Food fortified with zinc plus other micronutrients versus food fortified with other micronutrients without zinc.
  • Food fortified with zinc plus other micronutrients versus no intervention.

The comparisons mentioned above will be evaluated separately and not as a pooled comparison. We will not include comparisons of food fortification with zinc versus other forms of micronutrient interventions (i.e. supplementation or dietary diversification). We will not include studies examining point-of-use fortification of foods with micronutrient powders, biofortification or provision of zinc supplements. We will also exclude trials involving fortification of drinking water with zinc but will consider beverages fortified with zinc alone or with other vitamins and minerals (fruit juices, milk).

 

Types of outcome measures

The primary outcomes across all populations in this review will be the incidence of zinc deficiency, serum plasma zinc concentrations, and undernutrition.

 

Primary outcomes

 
Children (24 to 59 months of age)

  • Zinc deficiency (as defined by authors, depending on the age and gender).
  • Serum or plasma zinc (in µmol/L).
  • Stunting (defined as height-for-age below –2 standard deviations).
  • Underweight (defined as weight-for-age below –2 standard deviations)

 
Children (5-11.9 years of age)

  • Zinc deficiency (as defined by authors, depending on the age and gender).
  • Serum or plasma zinc (in µmol/L).

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

  • Zinc deficiency (as defined by authors, depending on the age and gender).
  • Serum or plasma zinc (in µmol/L).

 
Pregnant and lactating women (any age)

  • Zinc deficiency (as defined by authors, depending on the age).
  • Serum or plasma zinc (in µmol/L).

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

  • Zinc deficiency (as defined by authors, depending on the age and gender).
  • Serum or plasma zinc (in µmol/L).

 

Secondary outcomes

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

 
All participants

  • Diarrhea (as defined by authors).
  • Pneumonia (as defined by authors).
  • All-cause morbidity.
  • Haemoglobin (in g/L).
  • Anaemia (as defined by authors, depending on age and gender).
  • Adverse effect (iron status measured as serum ferritin in µg/L).
  • Adverse effect (iron status measured as serum transferrin receptor in mg/L).
  • Adverse effect (copper status as measured by serum or plasma copper level in µg/dL).
  • Vomiting (as defined by authors).
  • Any adverse effect reported (as defined by authors).

 
Children 24-59 months of age

  • Weight (in kg).
  • Height or length (in cm).
  • Mid-upper arm circumference (in cm).
  • Cognitive and motor skill development (as assessed by trialists, including use of indexes such as the Bayley Mental Development Index (MDI), Bayley Psychomotor Development Index (PDI), Stanford-Binet Test, and DENVER II Developmental Screening Test).
  • All cause death.

 
Male and female adults

  • Cognitive and work performance (as defined by authors).

 

Search methods for identification of studies

 

Electronic searches

We will contact the Trials Search Co-ordinator of the Cochrane Public Health Group to search the Cochrane Public Health Group Specialised Register.We will also 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 (Social Science Citation Index, Science Citation Index and Conference Proceedings 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.

The search will use keyword and controlled vocabulary (when available), using the search terms set out. The search strategy for PubMed is presented in Appendix 1 and we will adapt this appropriately for each database. We will not apply language or date restrictions for any database.

We will handsearch all the issues published in last 12 months of five journals with the highest number of studies eligible for inclusion in this review after search of all above databases, to capture any article that may not have been indexed in the databases at the time of the search. 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), which includes Clinical Trial Registry of India (CTRI) 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, Flour Fortification Initiative (FFI) and the International Zinc Nutrition Consultative Group (IZinCG).

We will also review the reference lists of identified articles, and handsearch reviews and abstracts of international micronutrient conferences of past three years. Experts in the field will be contacted to identify any additional or ongoing trials.

 

Data collection and analysis

 

Selection of studies

We will use Reference Manger v12 or EndNote for Reference Management. All citations and abstracts identified by search strategy will be screened independently by two review authors (DS and TG) to identify potentially eligible trials. Full text of potentially eligible trials will be obtained and assessed for inclusion in the review by two review authors (DS and TG). We will resolve any differences in opinion by simultaneous review, or if necessary by discussion with a third reviewer (LMD). We will exclude studies that do not meet the eligibility criteria and document the reasons for their exclusion in the Table of Excluded Studies. We anticipate sufficient information to be available to do a PRISMA flowchart.

 

Data extraction and management

We will deduplicate the retrieved records and, if multiple reports of the same study are available, these will be consolidated so that the unit of interest is the trial. Two review authors (DS and TG) will extract all data independently using a tailored and pre-tested data extraction form. We will extract data on study design, context, participant characteristics, interventions (including costs and process data where available), outcomes, PROGRESS framework characteristics (Cochrane-Campbell Methods Group Equity checklist items) and sustainability. We will consider the last recorded time point for the evaluated outcome measurements while the intervention is still operative or has just been terminated. If similar outcomes (for example, zinc deficiency) have been reported using multiple measures, we will average them. One author will enter data into Review Manager software (RevMan 2011), and a second author will carry out checks for accuracy. We will resolve any discrepancies between the extracted data by discussion and, if required, referral to a third person (LMD). If data are unclear or not presented in the trial papers, we will attempt to contact the trial authors for further details.

 

Assessment of risk of bias in included studies

We will assess the quality and risk of bias in each included study in relation to sequence generation, allocation sequence concealment, blinding and incomplete outcome data using the criteria outlined in the Cochrane Handbook for Systematic Reviews of Interventions (Higgins 2011). For randomised controlled trials, non-randomised controlled trials and controlled before-after studies these criteria will include: (i) sequence generation (selection bias), (ii) allocation sequence concealment (selection bias),  (iii) blinding of participants and personnel (performance bias), (iv) blinding of outcome assessment (detection bias), (v) incomplete outcome data (attrition bias), (vii) selective outcome reporting (reporting bias), (viii) comparability of baseline outcome and characteristics, (ix) protection from contamination and (x) other potential sources of bias. For cluster randomised trials particular biases to consider will include: (i) recruitment bias; (ii) baseline imbalance; (iii) loss of clusters; (iv) incorrect analysis; and (v) comparability with individually randomised trials (Higgins 2011). The judgment for each entry involves assessing the risk of bias as ‘low risk’, as ‘high risk, or as ‘unclear risk’, with the last category indicating either lack of information or uncertainty over the potential for bias. Plots of ‘Risk of bias’ assessments will be created in Review Manager (RevMan 2011). Two review authors (DS and TG) will independently assess risk of bias. Any disagreements will be resolved by mutual or group discussion, if required. The risk of bias assessment will provide essential input for data synthesis in the 'Summary of findings' table.

 

Measures of treatment effect

For two-group comparisons, we will give preference to pooling risk ratios (RR) or comparable measures including hazard ratios and odds ratios. For computing the summary relative risk, we will use individual study risk measures and 95% confidence intervals (CI) or standard error (SE). We will give preference to the risk measure stated by authors, in a hierarchical fashion, with a recheck of the calculations from the stated numbers, if possible.  If RR is not stated, we will compute with the following preference order for the denominator: (i) numbers with definite outcome known (complete follow-up) till completion of intervention period, or (ii) number randomised. If no events (or all events) are recorded in both groups, the trial will provide no information about relative probability of the event and will be automatically omitted from the meta-analysis (Higgins 2011).  For continuous data, we will use weighted mean difference (WMD) when outcomes are measured in the same way between trials. We will use the standardized mean difference (SMD) to combine trials that measured the same outcome with different methods.

 

Unit of analysis issues

For cluster-randomised trials, the stated cluster-adjusted RR and 95% CI will be used, irrespective of the method employed in their calculation. If the analyses have not been adjusted for cluster-design effect, we will use 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 as recommended (Higgins 2011). We will then recalculate the risk measures using a design effect inflation of SE from these external sources (Higgins 2011).

In factorial trials and in multi-arm designs yielding two or more intervention groups (different dosage or administration regimens) and a single control group, the data in the intervention groups, including the variation in the intervention characteristic, will be pooled and compared against the single control group to prevent unit-of-analysis error.

 

Dealing with missing data

We will contact the authors of relevant trials when information about any outcome is unclear or has not been fully reported.

We will prefer to use intention-to-treat analyses (author reported) when a per protocol analysis has also been reported. If the author has not reported an intention-to-treat analysis, we will use the reported analysis, but will judge the study to be at risk of bias due to these criteria.

When assessing adverse events, adhering to the principle of 'intention-to-treat' may be misleading, therefore, we will attempt to relate the results to the treatment received ('per protocol' or 'as observed'). This means that for side effects, we will attempt to 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 intend to assess contextual heterogeneity on the basis of information collected about the context in which the intervention was implemented. We will check for statistical heterogeneity by visual inspection of the forest plots and measure heterogeneity with formal tests including I2 and Chi2  (P value less than 0.10) to quantify the level of heterogeneity as recommended (Higgins 2011). If we identify moderate or substantial heterogeneity, we will explore it by pre-specified subgroup effect analyses.

 

Assessment of reporting biases

The presence of reporting bias in the extracted data will be evaluated visually using the funnel plot, if sufficient numbers of trials are available. If 10 or more trials are available per outcome, we will also use formal statistical tests for funnel plot asymmetry, namely Begg’s and Egger’s with the user-written “metabias” command in STATA ® (version 9) software (Sterne 2001, Steichen 1998).

 

Data synthesis

We will carry out meta-analysis with Review Manager software to provide an overall estimate of treatment effect when more than one study examines the same intervention (RevMan 2011), 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-randomized trials together in meta-analysis. Neither will we combine non-randomized studies with different types of study designs. Evidence about 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 about a particular outcome from both randomised trials and non-randomised studies, we will use the evidence from trials that are at a lower risk of bias to estimate treatment effect.

In anticipation of significant contextual heterogeneity between studies, we will use the random-effects model for pooling data. Pooled estimates of RR with 95% CIs will be calculated by the generic inverse variance method. 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). We will use the standardized mean difference (SMD) to combine trials that measured the same outcome with different methods. If we do not find enough studies, or the studies cannot be pooled, we will summarize the results related to outcomes in a narrative form.

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 present the main results as a 'Summary of findings' table for important outcomes (listed primary outcomes and adverse effects) and incorporate the GRADE assessment according to recommendations (Balshem 2011; Grade 2013).

The clinical relevance and importance of statistically significant results will be determined from the 'Summary of findings' table, giving due consideration to the quality of evidence and functional outcomes in addition to biochemical outcomes.

 

Subgroup analysis and investigation of heterogeneity

If a sufficient number of trials are available, we will explore significant heterogeneity and perform subgroup analyses only for the primary outcomes, ‘zinc deficiency’ and ‘serum zinc’, as a hypothesis-generating exercise. The pre-specified subgroup analyses will include analysis by:

  • sex: males versus females, versus mixed;
  • duration of intervention: less than six months; six months to one year; more than one year;
  • type of food vehicle: oils and fats versus sugar versus wheat flour versus maize flour and corn meals versus rice, versus condiments/seasonings, versus milk/dairy products, versus fruit juices/nectars, versus others;
  • type of zinc compound: zinc sulphate versus zinc oxide, versus other forms of zinc, versus unknown/unreported;
  • dose of zinc added per 100 g of food;
  • development status of country: Low and middle income countries versus others (World Bank 2012).

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’ CIs; non-overlapping CIs will suggest a statistically significant difference in treatment effect between the subgroups. We will also investigate formally differences between two or more subgroups (Borenstein 2008). We will conduct analyses in Review Manager (RevMan 2011).

If a sufficient number of trials is available, the contribution of these variables to heterogeneity will also be explored by meta-regression using the “metareg” command in STATA ® (version 9.0) software with the restricted maximum likelihood option (Sharp 1998).

We will also 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 to 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.

 

Sensitivity analysis

We will conduct a sensitivity analysis taking into account the trial quality components (allocation concealment, blinding and attrition), with each of these domains being considered separately (low risk versus others). Sensitivity analyses (specified above) will be conducted for the primary outcomes, provided three or more trials contribute data to the outcome.

 

Acknowledgements

  1. Top of page
  2. Background
  3. Objectives
  4. Methods
  5. Acknowledgements
  6. Appendices
  7. Contributions of authors
  8. Declarations of interest
  9. 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 protocol was also commented on by external peer referees and we are greatful for their thoughtful feedback.

 

Appendices

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

Appendix 1. Appendix 1

Search Strategy for Medline (OVID)

1 exp Zinc/

2 exp Zinc Compounds/

3 (zn or zinc).tw

4 exp Food, Fortified/

5 ((fortif* or enrich* or enhanc* or boost*) adj2 (food* or rice or flour or corn or wheat or semolina or pulse* or bread* or sauce* or beverage* or maize or oat* or sugar or salt or oil* or fat* or condiment* or seasoning* or spice* or milk or dairy or juice* or nectar*)).tw.

6 1 or 2 or 3

7 4 or 5

8 6 and 7

9 exp animals/ not humans.sh

10 8 not 9

 

 

Contributions of authors

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

Dheeraj Shah drafted an initial protocol with technical input from Harshpal S Sachdev, Tarun Gera, Luz Maria De-Regil and Juan Pablo Peña-Rosas. Luz Maria De-Regil, Harshpal S Sachdev and Juan Pablo Peña-Rosas developed the methods of the protocol. All authors provided input and contributed to drafting the final version of the protocol.

Disclaimer: Juan-Pablo Peña-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. Contributions of authors
  8. Declarations of interest
  9. Sources of support

Luz Maria De-Regil - none
Tarun Gera - none
Juan Pablo Peña-Rosas - none
Harshpal S Sachdev - none
Dheeraj Shah - none

 

Sources of support

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

Internal sources

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

 

External sources

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

References

Additional references

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