Effects of micronutrient fortified milk and cereal food for infants and children: a systematic review

Three reviewers screened titles and abstracts for relevance and assessed potentially relevant studies for inclusion by full text. Teaching sessions were held in advance to improve conceptual consistency between reviewers. Disagreements were resolved by consensus meetings. If data of a specific population were published in several papers or if follow-up data were presented, we included each population only once. Using a predefined form, data were extracted by one reviewer in an Excel database and checked independently by a second reviewer.

We extracted data on general study information (e.g. study region; length and completeness of follow up), study setting (e.g. level of population recruitment), population details, intervention (e.g. daily amount of fortified MN, determined as daily difference between intervention and control group; composition of MN; comparator food) and outcome (e.g. morbidity rates; hemoglobin levels [g/dl; conversion to g/L with factor 10]).

One reviewer assessed risk of bias in individual studies with a component approach exploring methodological quality on the study level (adequate generation of random sequence, concealment of allocation, blinding) as well as on the outcome level (incomplete outcome data due to attrition; selective outcome reporting) [12].

First, we calculated pooled estimates. For continuous variables we computed weighted mean differences (WMD) and 95%-confidence intervals (CI). For example, for analysis of hemoglobin change we used the mean change in the intervention and in the control group and their pooled standard deviation (SD). If the sample size decreased during the study, we used the lower sample size at the end of the study. If mean hemoglobin change per group and SD were not reported, we calculated change as the difference of baseline and final values for intervention and control group and applied the SD of final values [20]. If 95%-CI of mean values were reported we converted them to SD assuming normal distribution [21]. To check results for robustness, we also calculated WMD for final hemoglobin values of both study groups, as this data was reported more often. Due to considerable heterogeneity between trials, we applied a random effects model [22]. When authors reported only medians for continuous data (e.g. for ferritin levels), we did not include those data in the meta-analysis. For binary data, we calculated risk ratios and 95%-CI. Heterogeneity between trials was calculated with I², that is the percentage of the total variation in estimated effects that is due to heterogeneity rather than chance (where values of 25% are assigned low, 50% moderate and 75% high) [23].

Second, we divided our dataset into pre-specified subgroups to explore the influence of possible modifying factors on the outcome (fortified milk vs. cereal food; high vs. low/middle-income countries; single- vs. dual/multi-micronutrient fortification strategy).

Third, we performed a meta-regression analysis weighted for the inverse of the variance of the outcome [12]. With this approach we evaluated the unique contribution of other a priori chosen independent factors on the most often reported outcome (dependent variable: hemoglobin level; independent variables: hemoglobin levels before intervention; daily amount of fortified MN; length of follow-up; completeness of follow-up).

For parametric and non-parametric tests P-values <0.05 were considered significant. Analyses were performed using the STATA SE 9 software package (StataCorp. 2007. Stata Statistical Software, College Station, Texas, USA).

Our searches retrieved 1153 potentially relevant studies (Figure 1). Eighteen RCT [8‐10, 24‐38] (n = 10 fortified milk; n = 8 fortified cereals) fulfilled inclusion criteria and were included for our main analysis (Table 2).

These 18 trials comprised 5468 infants and children from different regions (2 studies from Asia [8, 37], 5 studies from Africa [9, 33‐36]; 5 Studies from South- and Middle-America [10, 27, 29, 30, 38]; 6 Studies from Europe [24‐26, 28, 31, 32]).

Study population sizes varied from n = 33 to n = 1120 participants (median 166; IQR 92 to 361). Most participants belonged to vulnerable groups and had been recruited from different settings (8 studies: medical or community care centers:, 7 studies: low income risk groups; 2 studies: general population of peri-urban and rural areas; 1 study: no information given). The most frequent exclusion criteria were chronic diseases, severe anemia, severe mal-/under-nutrition, and low birth weight. Mean age of participants ranged from 6 to 23 months at inclusion (upper age limit was 3 years in one study [8]) and the sex ratio was well balanced. Mean hemoglobin values of children at baseline varied between studies from 9.0 g/dl to 12.6 g/dl (median of study values: 11.1 g/dl). Follow up periods were generally short and did not exceed one year (mean follow up: 8.2 months; range: 2.3 to 12).

Fortified milk was prepared with centrally processed fortified milk powder in most of the studies. Fortified cereals comprised centrally processed weaning or complementary food, such as fortified porridge, gruel or weaning rusk to prepare a pap. Iron was the most frequently used MN for fortification (15 of 18 trials), followed by zinc (9 trials) and vitamin A (6 trials). Seven studies used a single-MN fortification strategy (6 studies with iron only; 1 study with zinc only), two studies a dual- and 9 studies a multi-micronutrient (MMN) strategy (i.e. 3 or more MN, for example additional fortification with vitamin C and E, selenium, copper).

Hemoglobin blood level was the most frequently reported outcome parameter. Across 13 studies that tested iron fortification irrespective of other added MN, the mean increase of hemoglobin compared to the control group was 0.62 g/dl (95%-CI: 0.34 to 0.89) for children fed with fortified milk or cereals (Figure 2). Heterogeneity was high (I² = 86%). Comparison of different subgroups showed a stronger effect of the iron MMN fortification approach (n = 8 studies; hemoglobin increase 0.87 g/dl (95%-CI: 0.57 to 1.16; I² = 82%) compared to the iron single-fortification strategy (n = 5 studies; hemoglobin increase 0.20 g/dl (95%-CI: -0.05 to 0.45; I² = 43%). The daily applied iron dosage was similar for the single-iron approach (median: 6.5 mg) and the MMN-approach (median 6.7 mg).

Eleven trials provided data for anemia rates, all of them using iron as a single- or a MMN-fortification strategy. Applied thresholds for anemia varied between 10.5 g/dl and 11 g/dl and the median of anemia rates at baseline was 36% (IQR: 15% to 40%; 9 studies with data). Fortified milk or cereals reduced the risk of suffering from anemia by 50% (risk ratio 0.50, 95%-CI: 0.33 to 0.75; I² = 71%; Figure 3). Again, a stronger effect of the MMN fortification approach emerged (n = 7 studies; risk ratio 0.43 (95%-CI: 0.26 to 0.71; I² = 81%) compared to the iron single-fortification strategy (n = 4 studies; risk ratio 0.76 (95%-CI: 0.45 to 1.28; I² = 0%). Overall, the absolute risk reduction (ARR) of suffering from anemia was 14% (un-weighted data of 11 trials), translating into a number needed to treat (NNT) with fortified milk or cereals of 7 (95%-CI: 6 to 9) participants over a period of 8 months (i.e. the mean follow-up time) to avoid one case of anemia. For the MMN approach these results are even more favorable (un-weighted data of 7 trials: ARR 22%; NNT 5 [95%-CI: 4 to 6]).

Ferritin is the most direct measure to conclude if iron stores increase by iron-fortified food consumption. Eleven trials provided data for ferritin serum levels. Ferritin levels were not adjusted for subclinical infections. Given the skewed distribution of ferritin values, authors often reported median estimates. Medians were significantly higher in the intervention groups (ranges of ferritin medians at end of study [micro-g/l]: intervention: 15.8 to 44.6; control: 6.5 to 28; P < 0.01). Only three studies provided mean values to be included in a meta-analysis, which showed an effect in the same direction. The mean ferritin increase with iron fortification was 11.3 micro-g/l (95%-CI: 3.3 to 19.2; I² = 79%) compared to control groups.

Five studies provided data for change in serum zinc levels. MN fortification with zinc led to no relevant change in zinc serum levels (0.4 micro-g/dl (95%-CI: -1.7 to 2.6; I² = 0%) compared to control groups. However, fortification increased vitamin A serum levels compared to control groups (four studies with data: Retinol increase by 3.7 micro-g/dl [95%-CI: 1.3 to 6.1; I² = 37%]).

For three European studies, no relevant effect of fortification on height and weight was seen and morbidities were not an issue in this population.

All other results relate to non-European low-/middle income countries. Due to the short follow-up period in most of the studies, no meaningful conclusion can be drawn for possible effects of fortification on height or weight gain or z-scores (weight-for-age; height-for-age; weight-for-height). Of 9 studies with data, 7 trials reported no relevant differences between intervention and control group at the end of the study. In one study [36], more weight gain was seen in the intervention group after one year (4.6 kg vs. 2.0 kg; P < 0.05), in another study [8] children consuming fortified milk showed improvement in weight gain compared to control group (difference 0.21 kg/year [95%-CI 0.12 to 0.31) and height gain (difference 0.51 cm/year [95%-CI 0.27 to 0.75).

Of three studies with data for psychomotor development of children, two trials reported no relevant difference between groups [9, 35] and one study [33] found slight improvements compared to the control group.

Of four studies with morbidity data of children, three trials reported no relevant differences between groups for infections [29], for diarrhea, fever and respiratory illness [34] and for referral to hospital or death in partly HIV exposed children [35]. In one study [8] fortified milk significantly reduced the probability of days with severe illness (by 15%), and the relative risk of diarrhea (by 18%) and lower respiratory illness (by 26%).

In our pre-specified subgroup analyses no relevant influence on the outcome was detected for the mode of fortified food (fortified milk vs. cereals). Hemoglobin change was somewhat higher in studies from low/middle income countries (0.78 g/dl (95%-CI: 0.41 to 1.15) compared to high income countries (0.42 g/dl (95%-CI: 0.10 to 0.73), but the difference was not statistically significant. The dual-/multi-micronutrient approach led to a significantly stronger effect of iron fortification on hemoglobin increase than the iron single-fortification strategy (Figure 3).

In our multivariable meta-regression analysis, none of the tested independent variables (mean hemoglobin level before intervention; daily amount of consumed iron, length of follow-up, completeness of follow up) was significantly associated with the change in hemoglobin.

Only two [8, 25] of 18 trials provided enough information to conclude that both random sequence generation and allocation concealment was adequately performed (Table 3). For 11 trials this was unclear and inadequate procedures had been applied in 5 trials. Other criteria were fulfilled more often: Blinding was reported in 13 of 18 studies, incomplete outcome data were addressed in 8 of 18 trials and 12 of 18 studies showed no selective outcome reporting (i.e. besides serum markers also height/weight, functional measures or morbidities were reported).

In summary, the risk of bias for the most often reported outcomes hemoglobin change and anemia rates is unclear. However, a sensitivity analysis including only studies with low risk of bias led to similar results (three studies that fulfilled 4 of 5 quality criteria [8, 25, 26]: hemoglobin increase 0.87 g/dl (95%-CI: 0.09 to 1.65; I² = 92%). Another sensitivity analysis showed that the result pattern remained basically unchanged after performing analyses using mean values of groups at the end of the study, instead of mean changes of groups.

We applied a thorough search strategy with a stepwise retrieval of studies using electronic databases and additional sources. We cannot exclude having missed references but we believe that we found a near complete sample of relevant papers for our specific research question.

Some limitations have to be mentioned. First, included studies showed short follow-up periods, thus the impact of fortified milk or cereal food on functional health outcomes (such as sustainable height and weight gain or mental and motor development) could not be assessed thoroughly. Second, for zinc and vitamin A fortification only surrogate outcomes as serum levels are available. However, the presence of additional fortified micronutrients seems to be important for the effects of iron on hemoglobin levels. The MMN approach is more effective than iron single fortification in our review, reflecting that complex micronutrient deficiencies are responsible for health problems [20]. Third, risk of bias is unclear mainly due to underreporting of the randomization procedure and incomplete outcome data. Finally, pooled estimates have to be interpreted cautiously as statistical heterogeneity between studies was considerable and meta-regression did not reveal significant associations of pre-specified study characteristics with study results. Possible sources for unexplained heterogeneity might be underreporting for co-interventions (e.g. public supplementation or food programs) or the diversity of applied MN preparations that have influence on MN absorption. For example, five different iron compounds were used (12 studies with data: six times FeSulfate; twice FeGluconate; one time, each, FePyrophosphate; FeFumarate; Ferric ammonium citrate; electrolytic iron). In addition, the difference in daily consumed iron between intervention and control group varied between 1.8 mg and 14.3 mg. Furthermore, molar ratios, a determinant for MN absorption, also showed variation (ranges of molar ratios: ascorbic acid/iron: 0.68 to 30; phytic acid/iron: 1.7 to 2.2; calcium/iron: 40 to 134).

Important contributions have been made in the recent years with other systematic reviews to evaluate the health effects of MN interventions. These reviews differ from ours: Dewey and Adu-Afarwuah gave a broad systematic overview of studies and programs aimed at improving biochemical and functional outcomes with complementary foods [43]. However, they did not perform a meta-analysis and presented results in a tabulated form or as averaged effect sizes. Some reviews have concentrated on MN supplementation only [44‐48] or home fortification [49], other reviews have combined supplementation and fortification strategies for analysis [20, 50], included children as well as adolescents or adult women [6, 51, 52], or included fortified staple food interventions [6, 52].

The health effects found in our review are in line with effect sizes shown in some similar reviews above [20, 47, 52]. This underpins the validity of our findings and supports a strategy to intervene with fortified milk and cereal food for infants and children. Supplementation trials, for example with vitamin A, have been shown to reduce mortality and morbidity via improved nutritional status [47, 48], even though serum level increases were small [53], similar to our review. Thus, some authors conclude that fortification would also have an impact on morbidity and mortality, although a conclusive answer cannot yet be given [52]. On the other hand, negative aspects of iron supplementation have been reported, such as increased morbidity and mortality in regions where malaria transmission is intense [54]. Thus, recommendations concerning iron supplementation have been formulated [55]. These adverse effects, however, may not be that relevant for fortified foods. Daily micronutrient dosages of fortified foods are much lower as compared to supplementation. Furthermore, children stop eating once they get saturated, which may also not be the case for high dosage sprinkles, that can be seen as a specific application of supplementation. Nevertheless, long term data concerning negative effects of iron fortified foods in regions with high prevalence of malaria and infectious diseases are lacking.

Further compiled evidence is needed to agree on the optimal MN preparation for fortified milk and cereals (such as composition of MN; suitable compounds; molar ratios for additives) to fully exhaust the potential of this approach. Future studies should also focus on health outcomes of MN fortification beyond the effect of iron on hematological results, for example via long-term follow-up of study populations.

There are multiple delivery mechanisms for fortified milk and cereal food. Production and distribution via government programs and local public agencies would be an obvious option to strengthen local structures. Implementation of effective strategies, however, does not always work well in the field due to logistical problems or inappropriate priority setting [56]. Thus, some have discussed the role of the business community in improving nutrition in developing countries [56‐58]. Commercially distributed fortified foods (e.g. with iron) are already available in many markets, even in low-income countries. In a public private partnership, business partners can provide their professional knowledge and experience concerning technical problems with processing and fortification, supply and transport, or refrigeration and conservation issues (specifically important for milk) to get interventions more efficient.

A limitation of the market approach is that it may not reach the poorest of the poor. Thus, a combination of different delivery channels, as well as affordable prices, may be needed. Children with severe anemia, who may be overrepresented in very poor groups, are often excluded from trials due to ethical reasons. One may assume, that the positive effects on the hemoglobin levels may be even stronger for such children. Additional economic analyses are necessary to contribute to a deeper understanding of the health economic effects of such a strategy and to inform the priority setting of decision makers.