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. 2018 Aug 3;2018(8):CD010201. doi: 10.1002/14651858.CD010201.pub2

Food fortification with calcium and vitamin D: impact on health outcomes

Jai K Das 1, Rehana A Salam 1, Zohra S Lassi 1,2, Zulfiqar A Bhutta 3,4,✉, Rohail Kumar 5, Anoosh Moin 1, Maria N Garcia‐Casal 6, Saleel Fatima 1, Gerardo Zamora 6
PMCID: PMC6513481

Abstract

This is a protocol for a Cochrane Review (Intervention). The objectives are as follows:

To assess the impact of food fortification with vitamin D and/or calcium on health outcomes in general population (including men, women and children)..

Background

Description of the condition

Vitamin D is a family of fat‐soluble molecules that are important micronutrients for humans with its two forms: vitamin D2 and vitamin D3 playing a central role in bone growth by increasing the uptake of calcium from the gut. Calcium and vitamin D work together to protect the bones. Vitamin D can be acquired through three main channels: through the skin, from diet, and from supplements. Humans can obtain both vitamin D2 and D3 from their diet, with fish liver oils, eggs and milk being particularly rich. But most of our vitamin D is obtained in the form of vitamin D3, synthesized directly when our skin is exposed to sunlight (Wagner 2008). Vitamin D levels in the body are best measured using the concentration of 25D in blood serum. Generally in adults, normal (sufficient) concentrations are greater than 30 to 32 ng/mL (75 to 80 nM). People with levels below 20 ng/mL (50 nM) are considered deficient, while those with between 20 ng/mL (50 nM) and 30 to 32 ng/mL (75 to 80 nM) are termed vitamin D insufficient (Walker 2009). It is estimated that around 1 billion people in the world may be vitamin D insufficient or deficient. Lack of sunlight (especially during winter months), vegetarian diet, a dark pigmented skin (as melanin acts as a natural sunscreen), increased pollution, and wearing long‐sleeved garments or clothes completely covering the body are the major risk factors (Williams 2008). Over the past 20 years, much attention has been paid in recognizing vitamin D insufficiency and deficiency in populations worldwide. Vitamin D deficiency is prevalent in many countries, even those with abundant sunlight such as Turkey (Ozgur 1996), Iran (Salimpour 1975), Saudi Arabia (Elidrissy 1984), India (Ghai 1991; Wayse 2004), China (Du 2001; Zhao 1991; Zhao 1992), Algeria (Garabedian 1991), and Nigeria (Akpede 1999; Akpede 2001). A study on the health status of children in low‐ and middle‐income countries (LMIC) reported that 73.1% of socio‐economically underprivileged children were 25D deficient (<8 ng/mL) and 23.1% were 25D insufficient (8 to 15 ng/mL) (Manaseki‐Holland 2008). A high occurrence of insufficiency or deficiency of vitamin D has also been reported in high‐income countries (Prentice 2008), such as US (Mansbach 2009), UK (Lawson 1999), Greece (Nicolaidou 2006), Finland (Lehtonen‐Veromaa 1999), Canada (Ward 2007), and New Zealand (Grant 2009). Lately, increasing scientific evidence has also linked vitamin D deficiency to many infectious and non‐infectious chronic diseases including hypertension, diabetes, and cardiovascular diseases (Chiu 2004; Cigolini 2006; Ford 2005; Targher 2006; Zittermann 2006).

Calcium is an important nutrient needed for major biological functions such as nerve conduction, muscle contraction, cell adhesiveness, mitosis, blood coagulation and structural support of skeleton (Miller 1999). It is an essential nutrient for several body functions including enzymatic and hormonal homoeostasis. It is required for the proper functioning of heart, muscles, nerves and blood clotting. Inadequate calcium intake significantly contributes to the development of osteoporosis. Many studies have shown that low calcium intake is associated with low bone mass and high fracture rates. National nutrition surveys have shown that most people are not getting the calcium they need to grow and maintain healthy bones (NIH 2005).There is also evidence for the association between maternal dietary calcium intake and maternal bone density and fetal mineralization but it is inconsistent (Prentice 1994). Epidemiological evidence does show an inverse association between calcium intake and development of hypertension in pregnancy and gestational hypertensive disorders are the second leading cause of maternal morbidity and mortality and are associated with increased risk of preterm birth and fetal growth restriction (Black 2013). Substantial evidence suggests that calcium supplementation in pregnancy is associated with a reduction in gestational hypertensive disorders and preterm birth (Hofmeyr 2010), however, the effect varies according to the baseline calcium intake of the population and preexisting risk factors. Dairy foods are the major source of calcium and. other foods such as certain green leafy vegetables also provide calcium, but generally in lesser amounts per serving than milk and other dairy foods..

Vitamin D and calcium deficiency have various manifestations in different age groups.

In children: In growing children calcium deficiency can lead to rickets, which is characterised by weak and deformed bones. Vitamin D deficiency has been associated with tuberculosis (TB), influenza and other respiratory infections. Many epidemiological studies have recently been conducted in children to observe the link between inadequate vitamin D concentrations and respiratory infections, including TB (Karatekin 2009; McNally 2009; Muhe 1997; Najada 2004; Nnoaham 2008; Roth 2009; Salimpour 1975; Wayse 2004; Williams 2008). A small randomised controlled trial of vitamin D supplementation among children with pneumonia was associated with a reduction in repeat episodes of pneumonia (Manaseki‐Holland 2010). In general population: Vitamin D and calcium have also been linked with various other inflammatory and long‐term diseases, including cardiovascular diseases (myocardial infarction), multiple sclerosis, asthma, rheumatoid arthritis, type 1 and type 2 diabetes (Wagner 2008), and cancers such as breast, ovarian, colorectal, and prostate (Cavalier 2009).

Pregnant women: During pregnancy, maternal 1,25(OH)2D requirements can increase up to four‐ to five‐fold to facilitate the availability of extra calcium required for fetal skeletal growth (Pérez‐López 2007). Approximately, 25‐30 grams (g) of calcium is transferred to the fetus by the end of pregnancy with the majority of this occurring in the last trimester (Abrams 2007; Salle 2000). Calcium levels in the third trimester fetus are higher than in the maternal plasma with maternal total serum calcium concentrations declining as the pregnancy progresses (Salle 2000), highlighting the role of active transport across the placenta. Low calcium intake is associated with gestational hypertension and related consequences.

In elderly population: Calcium is required for the proper functioning of heart, muscles, nerves and blood clotting. Inadequate calcium intake significantly contributes to the development of osteoporosis. Many studies have shown that low calcium intake is associated with low bone mass and high fracture rates. Hip fractures are the most serious and costly fractures among older persons (Cooper 1998). About 90% of hip fractures involve falls. Fractures caused by falls occur in about 5% of elderly persons each year, 1‐2% involving the hip. Long‐term vitamin D and calcium supplementation in elderly person is associated with reduced non vertebral fractures (Chapuy 1994; Dawson‐Hughes 1997). However, a meta‐analysis of prospective studies and randomised controlled trials found that calcium intake and calcium supplements were not associated with a lower risk for hip fractures (Bischoff‐Ferrari 2007).

Description of the intervention

Several strategies have been employed for micronutrient supplementation including dietary modification and education, oral supplementation, fortification (home and commercial) and sprinkles. Food fortification is one of the strategies that can be used to prevent vitamin and mineral deficiencies. Food fortification is the process of adding micronutrient (essential trace elements and vitamins) to food. According to World Health Organization (WHO) and Food and Agricultural Organization of the United Nations (FAO) fortification is done to increase the content of an essential micronutrient, i.e. vitamins and minerals (including trace elements) in a food irrespective of whether the nutrients were originally in the food before processing or not, so as to improve the nutritional quality of the food supply and to provide a public health benefit with minimal risk to health (Allen 2006). However, mandatory fortification is where food manufacturers are required to add a certain mineral or vitamin to a specified food in a certain quantity directly at mills. Since its origin, fortification programs have taken different forms:

  • Mass (or universal) fortification involves fortifying foods that are widely consumed by the general population.

  • Targeted fortification involves fortifying a food eaten by a specific subgroup of the population that has a particular need, for example, complementary food for young children.

  • Market‐driven (or industry‐driven)fortification involves the food industry choosing to fortify, within regulatory limits set by the government.

Fortification of foods and staples has been practiced in High Income Countries (HIC) for over a century and its use is now increasing in many LMIC. Today in many countries of Africa, Asia and Latin America, various foods including flour, salt, sugar, noodles, milk and chocolate powders are being fortified with various micronutrients. The food vehicles commonly used can be categorized in three broader categories: (1) staples (Wheat, rice, oils); (2) condiments (salt, soy sauce, sugar); and (3) processed commercial foods (noodles, infant complementary foods, beverages, dairy products).

However, there are some issues with fortification. Firstly, there is very limited data on the prevalence of micronutrient deficiencies in various population groups and hence it is difficult to establish the acceptable limit of micronutrient fortification as well as the target population groups (Dwyer 2015; Fletcher 2004). Secondly, the non‐specific nature of adverse effects on health, the public health implications of fortification are less well understood, limiting the applicability of the intervention (Dwyer 2015). Thirdly, there are issues with identifying the right amount of the micronutrient to be fortified to avoid exceeding the safe upper limits that have been established (Allen 2006). Moreoevr, the number of foods suited to fortification are also considerably limited by several factors, including technological properties (notably moisture, pH and O2 permeability), leading to unacceptable taste and appearance, as well as cost and consumer expectations (Fletcher 2004). Fortification requires careful consideration of safety concerns associated with the potentially increased level or proportion of fortified foods for nutrients with relatively low tolerable upper intake levels and potential benefit and risks in different sub‐populations.

How the intervention might work

In infectious diseases

The precise molecular mechanisms by which vitamin D helps defend against infectious disease are now being elucidated. It has become clear that 1,25 D plays a role not only in calcium homeostasis and bone metabolism, but also in the integrity of the innate immune system (Bhutta 2008; Wagner 2008). Acting via the VDR, 1,25 D alters the activity of many immune system cells, including macrophages, regulatory T cells and natural killer cells.

For bones

Vitamin D, in addition to its effects on calcium homeostasis, binds to specific receptors on skeletal muscle for 1,25‐dihydroxyvitamin D (Costa 1986; Haddad 1976). The hormonal form of vitamin D3, i.e. 1,25‐dihydroxyvitamin D3, acts through a nuclear receptor to carry out its many functions, including calcium absorption, phosphate absorption in the intestine, calcium mobilization in bone, and calcium reabsorption in the kidney (DeLuca 2004).

During pregnancy

The serum 1,25(OH)2D concentrations increase 50‐100% over the nonpregnant state during the second trimester and by 100% during the third trimester. Such increases could be explained by increasing synthesis and/or decreasing catabolism of 1,25(OH)2D. There is an increased expression of 1a‐hydroxylase and VDR genes and high levels of 1a‐hydroxylase (Zehnder 2002) in human placental and decidual tissues during the first and early second trimesters. Decreased catabolism may also contribute to higher placental levels of 1,25(OH)2D, as there is some evidence of specific epigenetic down regulation of the CYP24A1 (24‐hydroxylase) gene (Novakovic 2009) in the placenta.

Other diseases

The well‐known calcitropic functions of 1,25(OH)2D include the physiological regulation of calcium transport and bone mineralization by increasing intestinal calcium absorption (Holick 2008), suppressing parathyroid secretion (Bikle 2009) and promoting mineralization of the skeleton (DeLuca 1998). It is now being increasingly recognized that vitamin D has important non‐calcitropic actions, involving VDR activation by locally produced 1,25(OH)2D in a number of tissues in a paracrine and autocrine manner. The pleiotropic effects of 1,25(OH)2D include stimulation of insulin production (Chiu 2004), thyroid‐stimulating hormone secretion (Smith 1989) and improvement of myocardial contractility. Substantial scientific evidence supports a beneficial role for calcium or calcium‐rich dairy foods in blood pressure regulation (Obarzanek 1999). Evidence also suggests beneficial role of calcium against colon cancer (Holt 1999).

Impact of fortification at population level

Food fortification is an attractive public health strategy and a number of programs have been initiated especially in HIC. Surprisingly this has not been systematically evaluated to assess the impact (Allen 2006). Much of the putative benefits of fortification are derived from supplementation trials, frequently small scale and focused and extrapolation to benefits in a fortification mode, where the vehicle and dosage differs greatly, is difficult. Food fortification can be a potentially cost‐effective public health intervention and target a larger population through a single strategy.

Why it is important to do this review

Food fortification could be one of the potential public health strategies to improve the nutrient intake at the population level. However, limited data on the prevalence of these micronutrient deficiencies in various population groups and the non‐specific nature of adverse effects on health, the public health implications of fortification are less well understood (Dwyer 2015). Furthermore, there are issues with identifying the right amount of the micronutrient to be fortified to avoid exceeding the safe upper limits that have been established (Allen 2006). There are many reviews on vitamin D supplementation in different population groups but few on Vitamin D fortification. The recent review on Vitamin D fortification have focused on specific age groups like children (aged 6months to 5 years) (Eichler 2012) or adults only (Black 2012). In this review, we have attempted to quantify the impacts of Vitamin D and calcium fortification (in combination or alone) on all age groups in HIC as well as LMIC. The protocol for this review has been published earlier (Das 2012).

Objectives

To assess the impact of food fortification with vitamin D and/or calcium on health outcomes in general population (including men, women and children)..

Methods

Criteria for considering studies for this review

Types of studies

We have included:

  1. Randomised controlled trials (RCTs)        

  2. Quasi‐randomised trials (Trials that may attempt to randomly assign participants to groups but use an inadequate approach to generate the random sequence)

We have also included cluster randomised controlled trials. No language or publication status restrictions were applied. We made an attempt to obtain translations when and if required.

Types of participants

We included studies that assessed the impact of food fortification with vitamin D and/or calcium in general population (including men, women and children).

Food fortification studies from both HIC and LMIC were included.

Types of interventions

Intervention: Vitamin D and/or Calcium fortification with any food vehicle

The following comparisons were included:

  1. Calcium food fortification versus no fortification: This comparison included studies comparing food fortification with calcium alone to no fortification.

  2. Vitamin D food fortification versus no fortification: This comparison included studies comparing food fortification with vitamin D alone to no fortification.

  3. Vitamin D and calcium food fortification versus no fortification: This comparison included studies comparing combined vitamin D and calcium to no fortification.

Types of outcome measures

Primary outcomes

  • Rickets (osteomalacia) ‐ Defined as a bone disorder in which bones soften and become prone to fractures and deformity. This will measured as a dichotomous outcome.

  • Morbidity (including but not limited to infectious diseases like pneumonia, sepsis, diarrhoea, TB). This will be measured as a dichotomous outcome.

  • All‐cause mortality rate ‐ Defined as death due to any cause.

  • Cause‐specific mortality due to pneumonia, diarrhoea, TB, malaria or any other cause specific mortality reported by the trial authors.

Secondary outcomes

  • Serum 25‐OH D3 concentration ‐ This will be measured as a continuous outcome.

  • Bone mineral density ‐ This will be measured as a continuous outcome.

  • Bone resorption markers ‐ This will be measured as a continuous outcome.

  • Anthropometric markers including body mass index (BMI), weight, length, height.

  • Alkaline phosphatase level ‐ This will be measured as a continuous outcome.

  • Serum parathyroid hormone (PTH) concentration ‐ This will be measured as a continuous outcome.

  • Potential adverse outcomes (e.g. hypercalcaemia, kidney stones or any other reported in papers) ‐ This will be measured as a dichotomous outcome.

Search methods for identification of studies

Electronic searches

We have searched the following electronic databases for primary studies. The search period was from 1990 to date and the last search date was 10 April 2017.

  • Cochrane Central Register of Controlled Trials (CENTRAL, The Cochrane Library), including the Cochrane Effective Practice and Organisation of Care (EPOC) Group Specialised Register and Cochrane Public Health Specialised Register

  • MEDLINE and MEDLINE(R) In‐Process (https://www.nlm.nih.gov/bsd/pmresources.html#)

  • Pubmed (http://www.ncbi.nlm.nih.gov/pubmed)

  • EMBASE (www.embase.com)

  • CINAHL (www.cinahl.com)

  • PsycINFO (http://www.apa.org/pubs/databases/psycinfo/index.aspx)

  • ERIC (www.eric.ed.gov/)‎

  • LILACS (www.http://lilacs.bvsalud.org/en/

  • Science Citation Index and Social Sciences Citation Index (thomsonreuters.com/social‐sciences‐citation‐index/)

  • Current Controlled Trials (http://www.controlled‐trials.com/)

  • Food Science and Technology Abstracts (www.library.ethz.ch/en/Resources/Databases/FSTA‐Food‐Science‐and‐Technology‐Abstracts)

  • AgriCOLA (http://agricola.nal.usda.gov/)

  • Global Index Medicus ‐ AFRO (www.http://indexmedicus.afro.who.int/)

  • EMRO (www.applications.emro.who.int/library/Databases/wxis.exe/Library/Databases/iah/?IsisScript=iah/iah.xis&lang=I&base=imemr)

  • PAHO (Pan American Health library) (http://library.paho.org/uhtbin/cgisirsi.exe/urTmAL11Wf/59170009/60/50/X)

  • WHOLIS (WHO Library) (www.who.int/library/databases/en/)

  • WPRO (http://www.wprim.org/)

  • IMSEAR (Index Medicus for the South‐East Asian Region) (www.http://imsear.hellis.org/)

  • 3ie Database of Impact studies (http://www.3ieimpact.org/en/evidence/)        

  • EPPI centre databases (https://eppi.ioe.ac.uk/cms/Default.aspx?tabid=185)

  • Dopher and TROPHI (https://eppi.ioe.ac.uk/cms/Default.aspx?tabid=185)

  • Grey Literature through Google (www.google.com)

  • System for Information on Grey Literature in Europe (SIGLE) (www.opengrey.eu/)

  • Index to Conference Proceedings (www.thomsonreuters.com/conference‐proceedings‐citation‐index/)

The MEDLINE search strategy was adapted for use in other databases using the appropriate controlled vocabulary as applicable. We also hand searched journals (Journal of Nutrition, American Journal of Clinical Nutrition and Europeon Journal of Clinical Nutrition) for the last ten years and the proceedings of major relevant conferences.

Searching other resources

Reference lists of included studies and relevant systematic reviews identified were examined for additional papers to be considered for inclusion.

Data collection and analysis

Selection of studies

Two review authors independently assessed for inclusion all the potential studies that were identified as a result of the search strategy. We resolved any disagreement through discussion or, if required, consulted a third author.

Data extraction and management

For eligible studies, two authors extracted the data using the agreed extraction form. We resolved discrepancies through discussion or, if required, consulted a third author. We entered data into the Cochrane Collaboration statistical software Review Manager 5.2, and checked for accuracy. When information regarding any of the above was unclear, we attempted to contact authors of the original papers/reports to provide further details.

We examined the studies according to the PROGRESS‐Plus framework (Place, Race/ethnicity/culture/religion, Occupation, Gender/sex, Religion, Education, Socio‐economic status, Social capital) to record whether or not outcome data have been reported by these factors, which are relevant from an equity perspective (O'Neill 2014; Welch 2013; Welch 2016). Although most of the studies did not provide enough information, we extracted the factors that were reported. We also attempted to record whether or not studies included specific strategies to address diversity or disadvantage, but this information was not reported by individual studies included in our review.

Assessment of risk of bias in included studies

Two review authors independently assessed risk of bias for each study using the criteria outlined in the Cochrane Handbook for Systematic Reviews of Interventions (Higgins 2011). We resolved any disagreement by discussion or by involving a third assessor.

Random sequence generation (checking for possible selection bias)

We have described for each included study the method used to generate the allocation sequence in sufficient detail to allow an assessment of whether it should produce comparable groups. We have assessed the methods as:

  • low risk of bias (any truly random process, e.g. random number table; computer random number generator);

  • high risk of bias (any non‐random process, e.g. odd or even date of birth; hospital or clinic record number);

  • unclear risk of bias.   

Allocation concealment (checking for possible selection bias)

We have described for each included study the method used to conceal allocation to interventions prior to assignment and assessed whether intervention allocation could have been foreseen in advance of, or during recruitment, or changed after assignment. We have assessed the methods as:

  • low risk of bias (e.g. telephone or central randomisation; consecutively numbered sealed opaque envelopes);

  • high risk of bias (open random allocation; unsealed or non‐opaque envelopes, alternation; date of birth);

  • unclear risk of bias.   

Blinding of participants and personnel (checking for possible performance bias)

We have described for each included study the methods used, if any, to blind study participants and personnel from knowledge of which intervention a participant received. We have considered that studies are at low risk of bias if they were blinded, or if we judge that the lack of blinding would be unlikely to affect results. We have assessed blinding separately for different outcomes or classes of outcomes. We have assessed the methods as:

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

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

Blinding of outcome assessment (checking for possible detection bias)

We have described for each included study the methods used, if any, to blind outcome assessors from knowledge of which intervention a participant received. We have assessed blinding separately for different outcomes or classes of outcomes. We have assessed methods used to blind outcome assessment as:

  • low, high or unclear risk of bias.

Incomplete outcome data (checking for possible attrition bias due to the amount, nature and handling of incomplete outcome data)

We have described for each included study, and for each outcome or class of outcomes, the completeness of data including attrition and exclusions from the analysis. We have stated whether attrition and exclusions were reported and the numbers included in the analysis at each stage (compared with the total randomised participants), reasons for attrition or exclusion where reported, and whether missing data were balanced across groups or were related to outcomes. Where sufficient information was reported, or was supplied by the trial authors, we have re‐included missing data in the analyses which we undertook. We assessed methods as:

  • low risk of bias (e.g. no missing outcome data; missing outcome data balanced across groups);

  • high risk of bias (e.g. numbers or reasons for missing data imbalanced across groups; 'as treated' analysis done with substantial departure of intervention received from that assigned at randomisation);

  • unclear risk of bias.

Selective reporting (checking for reporting bias)

We have described for each included study how we investigated the possibility of selective outcome reporting bias and what we found. We have assessed the methods 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 are 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);

  • unclear risk of bias.

Other bias

We have described for each included study any important concerns we have about other possible sources of bias like the baseline characteristics and nutritional status of the participants. we also explored the funding source of the studies and whether the food industry was involved wholly or partly in funding the study. We have assessed whether each study was free of other problems that could put it at risk of bias:

  • low risk of other bias;

  • high risk of other bias;

  • unclear whether there is risk of other bias.

Overall risk of bias

We have made explicit judgements about whether studies are at high risk of bias, according to the criteria given in Higgins 2011. We have assessed the likely magnitude and direction of the bias and whether we consider it is likely to impact on the findings. Blinding of outcome assessor was considered as a critical factor in determining this considering the level of industry funding. We have explored the impact of the level of bias through undertaking sensitivity analyses.

Measures of treatment effect

Dichotomous data

For dichotomous data, we have presented results as summary risk ratio (RR) with 95% confidence intervals (CI). 

Continuous data

For continuous data, we have used the mean difference (MD) if outcomes are measured in the same way between trials. We have used the standardised mean difference (SMD) to combine trials that measure the same outcome, but use different methods.  

Unit of analysis issues

When we identified studies with more than two intervention groups (multi‐arm studies), we combined groups to create a single pair‐wise comparison or use the methods set out in the Cochrane Handbook for Systematic Reviews of Interventions to avoid double‐counting study participants (Higgins 2011). For the subgroup analyses, when the control group was shared by two or more study arms, we divided the control group (events and total population) over the number of relevant subgroups to avoid double counting the participants.

Dealing with missing data

We have described missing data, including dropouts. Differential dropout rates can lead to biased estimates of the effect size, and bias may arise if the reasons for dropping out differ across groups. We have reported the reasons for dropout. If data was missing for some cases, or if the reasons for dropping out were not reported, we have contacted the authors. For included studies, we have noted levels of attrition. We have explored the impact of including studies with high levels of missing data in the overall assessment of treatment effect by using sensitivity analysis. For all outcomes, we have carried out analyses, as far as possible, on an intention‐to‐treat basis, i.e. we attempted to include all participants randomised to each group in the analyses, and all participants were analysed in the group to which they were allocated, regardless of whether or not they received the allocated intervention. The denominator for each outcome in each trial was the number randomised minus any participants whose outcomes were known to be missing.

Assessment of heterogeneity

We assessed included studies for clinical, methodological, and statistical heterogeneity. We assessed clinical heterogeneity by comparing the distribution of important factors, such as the study participants, study setting, dose and duration of the intervention and co‐interventions. We evaluated methodological heterogeneity on the basis of factors such as the method of sequence generation, allocation concealment, blinding of outcome assessment, and losses to follow up. We have assessed statistical heterogeneity in each meta‐analysis using the T2, I2 and Chi2 statistics. We have regarded heterogeneity as substantial if I2 was greater than 30% and either T2 was greater than zero, or there was a low P value (< 0.10) in the Chi2 test for heterogeneity.

Assessment of reporting biases

If there were 10 or more studies in the meta‐analysis we investigated reporting biases (such as publication bias) using funnel plots. We assessed funnel plot asymmetry visually, and used formal tests for funnel plot asymmetry. For continuous outcomes we used the test proposed by Egger 1997, and for dichotomous outcomes we used the test proposed by Harbord 2006. If asymmetry was detected in any of these tests or was suggested by a visual assessment, we performed exploratory analyses to investigate it.

Data synthesis

We carried out statistical analysis using the Review Manager software (Review Manager 5.2). We used random‐effect meta‐analysis for combining data as the characteristics of study participants and interventions differed significantly. The results are presented as the average treatment effect with 95% confidence intervals, and the estimates of  T2 and I2.

We have set out the findings of the primary outcomes in summary of findings tables prepared using the GRADE approach (Guyatt 2008) using GRADE profiler software. We have listed the 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 assessed the quality of the evidence using the GRADE approach, 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 have rated the quality of the body of evidence for each key outcomes as "high", "moderate", "low" or "very low".

Subgroup analysis and investigation of heterogeneity

If we identified substantial heterogeneity, we have investigated it using subgroup analyses and sensitivity analyses. We considered whether an overall summary was meaningful, and if it was, we used random‐effects analysis to produce it.

We carried out the subgroup analyses based on age and gender, duration of intervention, concentration of micronutrient in fortified food, different food vehicles used and whether the evidence was from LMIC or HIC. We attempted to conduct subgroup analysis based on funding sources however since majority of the studies were funded by food industries, we could not conduct subgroup analysis.

Sensitivity analysis

We performed sensitivity analyses to examine the affect of removing studies at high risk of bias (those with high or unclear risk of bias according to method and adequacy of allocation concealment; blinding status of the participants; percentage lost to follow up or with an attrition of greater than or equal to 20%; and random‐effects model of the primary analysis). Moreover, sensitivity analyses was performed based on different ICC values.

Acknowledgements

We thank the Cochrane Public Health Group for its support in the preparation of this review.

Appendices

Appendix 1. Search Strategy

1. ((Bread or flour or wheat or triticum or rice or cereal* or grain* or cheese* or dairy or cake or cakes or biscuit* or juice or juices or yogurt* or yoghurt* or chocolate* or margarine* or butter* or cream) adj3 (enrich* or forti* or enhanc* or refin*)).ti,ab.
2. (food/ or Flour/ or Bread/ or rice/ or exp dairy products/ or butter/ or cheese/ or ice cream/ or margarine/ or exp milk/ or Triticum/) and (enrich* or forti* or enhanc* or refin*).ti,ab.
3. food, fortified/
4. or/1‐3
5. (Calcium or vitamin D or vitamin D3).ti,ab.
6. Vitamin D/ or calcium/
7. or/5‐6
8. 4 and 7
Open in a new tab

Appendix 2. Search Strategy

MEDLINE

1. (bread or flour or wheat or triticum or rice or cereal* or grain* or cheese or exp dairy or cake* or biscuit* or juice* or yogurt or chocolate or margarine or butter or cream) adj3 (enrich* or forti* or enhance* or refin* or fortified/).ti,ab

2. (food/ or flour/ or bread/ or rice/ or exp dairy products/ or butter/ or cheese/ or ice cream/ or margarine/ or exp milk/ or triticum/) and (enrich* or forti* or enhance* or refine*)ti,ab

3. exp Food fortification/

4. 1‐3

5. exp calcium/ or exp vitamin D/ or exp vitamin D3/

6. 4 and 5

7. limit 6 to (randomized controlled trial or RCT or trial or quasi‐randomized trial or quasi‐experimental)

EMBASE

1. (bread or flour or wheat or triticum or rice or cereal* or grain* or cheese or exp dairy or cake* or biscuit* or juice* or yogurt or chocolate or margarine or butter or cream) adj3 (enrich* or forti* or enhance* or refin* or fortified/).mp.

2. (food/ or flour/ or bread/ or rice/ or exp dairy products/ or butter/ or cheese/ or ice cream/ or margarine/ or exp milk/ or triticum/) and (enrich* or forti* or enhance* or refine*).mp

3. exp Food fortification/

4. 1‐3

5. exp calcium/ or exp vitamin D/ or exp vitamin D3/

6. 4 and 5

7. (interven* or compar* or control*).mp. or intervention studies/

8. 6 and 7

CINAHL

1. (bread or flour or wheat or triticum or rice or cereal* or grain* or cheese or MH dairy or cake* or biscuit* or juice* or yogurt or chocolate or margarine or butter or cream) AND MH(enrich* or forti* or enhance* or refin* or MH fortified)

2. (food or flour or bread or rice or MH “dairy products”/ or butter/ or cheese/ or ice cream/ or margarine/ or MH milk/ or triticum/) AND MH (enrich* or forti* or enhance* or refine*)

3. MH “Food fortification”

4. 1‐3

5. MH (calcium or “vitamin D” or “vitamin D3”

6. 4 and 5

7. (MH “randomized controlled trial”) OR (MH “RCT”) OR (MH “trial”) OR (MH “quasi‐randomized trial”) OR (MH “quasi‐experimental”)

8. 6 and 7

Cochrane

1. MeSH descriptor: [Food, Fortified] explode all trees

2. MeSH descriptor: [Calcium] explode all trees

3. MeSH descriptor: [Vitamin D] explode all trees

4. #1 or #2 or #3

Wholis

1. words or phrase “bread or flour or wheat or triticum or rice or cereal or grain or cheese or dairy or dairy products or cake or biscuit or juice or yogurt or chocolate or margarine or butter or cream or milk” AND words or phrase "fortified or fortification or enriched or enhanced or refined” AND words or phrase "intervention or interven* or compar* or “intervention study” or control or RCT or trial or “randomized trial” or “randomized controlled trial” or “quasi‐randomized trial” or “quasi‐experimental”

What's new

Last assessed as up‐to‐date: 10 April 2017.

Date Event Description
3 August 2017 Amended Protocol withdrawn due to cessation of review development through editorial process.
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Contributions of authors

All authors contributed to the development of the review. Rohail Kumar (RK), Anoosh Moin (AM) and Saleel Fatima (SF) developed and run the search strategy and obtained copies of the studies; Jai K Das (JKD) and Rehana A Salam (RAS) selected which studies to include; RK, AM, SF and Zohra S Lassi (ZSL) extracted data from studies and entered data into RevMan; JKD RAS and ZSL carried out and interpreted the analysis. Maria N Garcia‐Casal, (MG) and Gerardo Zamora (GZ) evaluated the studies according to the PROGRESS‐PLUS criteria. JKD, RAS, Zulfiqar A Bhutta, MG and GZ drafted the final review.

Disclaimer: Gerardo Zamora is a full‐time staff member of the World Health Organization (WHO). 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 WHO.

Sources of support

Internal sources

  • Aga Khan University, Pakistan.

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

    Gerardo Zamora is a full time staff of the World Health Organization.

External sources

  • The Bill & Melinda Gates Foundation, USA.

    The World Health Organization gratefully acknowledges the financial contribution of The Bill & Melinda Gates Foundation towards the development of systematic reviews of the evidence on the effects of nutrition interventions.

  • Nestle Nutrition Institute, Other.

    Nestle Nutrition Institute provided some funding at the protocol stage that expired before commencement of the review and there has been no contact between the authors and Nestle regarding this review subsequent to the publication of the protocol.

Declarations of interest

The review was conducted independently by the review team and all authors confirm no interest to declare.

Notes

Protocol withdrawn due to cessation of review development through editorial process.

Withdrawn from publication for reasons stated in the review

References

Additional references

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