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Effect of Iron Supplementation on Haemoglobin Response in Children: Systematic Review of Randomised Controlled Trials

Gera, Tarun*; Sachdev, HPS; Nestel, Penelope; Sachdev, Sudeep Singh§

Journal of Pediatric Gastroenterology & Nutrition: April 2007 - Volume 44 - Issue 4 - p 468–486
doi: 10.1097/01.mpg.0000243440.85452.38
Original Articles: Hepatology & Nutrition

Objective: To evaluate the effect of iron supplementation on haemoglobin (Hb) in children through a systematic review of randomised controlled trials.

Materials and Methods: Electronic databases, personal files, hand search of reviews, bibliographies of books, and abstracts and proceedings of international conferences were reviewed. Randomised controlled trials evaluating change in Hb levels with interventions that included oral or parenteral iron supplementation or iron-fortified formula milk or cereals were analysed.

Results: A total of 55 trials (56 cohorts) provided relevant information. Publication bias was evident (P < 0.001). The pooled estimate (random-effects model) for change in Hb with iron supplementation (weighted mean difference) was 0.74 g/dL (95% CI, 0.61–0.87; P < 0.001; P < 0.001 for heterogeneity). Lower baseline Hb level, oral medicinal iron supplementation, and malarial nonhyperendemic region were significant predictors of greater Hb response and heterogeneity. Projections suggested that, on average, between 37.9% and 62.3% of baseline anaemia (Hb <11 g/dL) was responsive to iron supplementation among children under 6 years of age; the corresponding range for malarial hyperendemic regions was 5.8% to 31.8%.

Conclusions: This systematic review indicates that iron supplementation increases Hb levels in children significantly but modestly. The increase is greater in subjects who are anaemic at the start of the trial and lower in malarial hyperendemic areas and in those consuming iron-fortified food. The projected reductions in prevalence of anaemia with iron supplementation alone highlight the need for additional area-specific interventions, particularly in malaria-prone regions.

*S.L. Jain Hospital

Division of Clinical Epidemiology, Department of Paediatrics, Maulana Azad Medical College, New Delhi, India

HarvestPlus, International Food Policy Research Institute, Washington, DC

§University College of Medical Sciences and Guru Teg Bahadur Hospital, Delhi, India

Received 24 August, 2005

Accepted 19 April, 2006

Address correspondence and reprint requests to H.P.S. Sachdev, E-6/12 Vasant Vihar, New Delhi 110 057, India (e-mail:

T.G. prepared the protocol, applied the search strategy, performed the retrieval of articles, and extracted the data from the included studies. H.P.S.S. and P.N. developed the idea for the review and finalised the protocol and search strategy. H.P.S.S. performed the statistical analysis. S.S.S. helped with the search strategy, data extraction, and statistical analysis. All of the authors contributed to the drafting of the final version of the manuscript. H.P.S.S. and T.G. are the guarantors.

Funding was provided by the US Agency for International Development through its cooperative agreement (No. HRN-A-00-98-00027-00) with the Human Nutrition Institute of the International Life Sciences Institute (ILSI) Research Foundation. The funding source had no influence on the study design, analysis, and interpretation, and the decision to submit for publication.

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Anaemia is a major public health problem that affects nearly one third of the world's population (1). Infants and young children are particularly affected, with global estimates suggesting that 35% of all preschoolers are anaemic (2). The problem is more widespread in south Asia (53%) than in other regions of the world (2). More specifically, estimates from India show anaemia prevalence to be 74% among children 9 to 36 months old (3). The aetiology of anaemia is multifactorial, with the important causes being iron deficiency, other micronutrient deficiencies (eg, folate, vitamin B12, vitamin A), helminthic infestations, malaria, and haemoglobinopathies. Against this backdrop of multifactorial aetiology of anaemia, the success of a particular public health intervention will be determined by the relative contribution it makes to correct the underlying cause(s). Because the causes of anaemia are not well mapped, the earlier assumption that iron supplementation can control the problem is being increasingly questioned (4,5). It is therefore important to quantify the effect, if any, of iron supplementation on haemoglobin (Hb) response in children, and to identify effect predictors to encourage public health discussions on the best mix of interventions to control iron deficiency and anaemia. This systematic review attempts to fill some of the information gap to enable the latter.

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A MEDLINE search (1966–April 2003) was conducted by using the search word “iron” with limits pertaining to “all child (0–18 years),” “English language,” and “Human” for clinical trials and randomised controlled trials. A similar search of the Cochrane controlled trials register using the search words “iron and child,” “iron and newborn,” and “iron and adolescents” was also conducted. The search of the EMBASE database from 1982 to February 2003 using the search words “iron and child” limited to “human,” “English,” “infant, child or preschool child (1–6 years),” “school child (7–12 years),” and “adolescent (13–17 years)” was also made. Similar searches using the search words “iron” and “child” were also made using the IBIDS and Healthstar databases Reference lists of identified articles and hand-earched reviews, bibliographies of books, and abstracts and proceedings of international conferences or meetings were also reviewed. Donor agencies, “experts,” and authors of recent iron supplementation trials were contacted to identify any additional or ongoing trials. The titles and abstracts of the trials identified in the computerised search were scanned to exclude studies that were obviously irrelevant. Full texts of the remaining studies were reviewed and trials that fulfilled the inclusion criteria identified. To avoid publication bias, published and unpublished trials were included.

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Selection Criteria

To be included rials had to be randomised placebo-controlled trials, except for those in which iron was given parenterally, in which case trials could be non–placebo-controlled because it would be difficult to administer a similar placebo. Also, trials had to investigate iron supplementation through the oral or the parenteral route or as formula, milk, or cereals fortified with iron; and evaluate Hb as an outcome measure. Studies in which other micronutrients and drugs were simultaneously administered were included if the only difference between the study and control groups was iron supplementation.

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Validity Assessment

Trial quality was assessed (A, B, C, or D) according to recommended criteria (6,7). Concealment of allocation was classed as adequate, unclear, inadequate, or not used. To assess attrition, studies were classified by percentage of participants lost to follow-up (<3%, 3%–9.9%, 10%–19.9%, and ≥20%). Blinding was classified as double blinding, single blinding, no blinding, and unclear.

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Data Abstraction

Prepared questionnaires were used to abstract data. The data included in this review were derived from the published articles or were provided by the authors. If required and wherever possible, the authors were contacted for clarifications. All data were abstracted by 1 author (T.G.).

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Quantitative Data Synthesis

In studies with 2 or more iron intervention groups (ie, different dosage or administration regimins) and a single control group, the sample size of the control group was divided equally between the number of intervention groups while retaining the same value for the change in outcome and its SD. This was done to avoid multiple counting of the control group (A.D. Oxman, personal communication, 2003; J. Deeks, personal communication, 2003). Thus, some trials contributed >1 analytic component for statistical computations.

To compute pooled estimates, sample size, mean change in Hb level from the beginning to the end of the intervention, and the SDs of this change in the intervention and control groups were required. The following principles were used for derivations if actual variables were not stated: in a group, the lower of the 2 stated sample sizes at the beginning or at the end of a trial was assumed to be the sample size for the change; wherever feasible SDs were back-calculated from the stated standard errors, t, or P values; wherever not stated, the mean change in Hb was computed as the difference of mean scores before and after intervention; and wherever not stated, the mean age of subjects was computed as the average of the stated range.

The SD for the change in Hb level was available or could be back-calculated from some studies. For the rest this SD was computed assuming correlations of 0.5 and 0 (independent) between the pretest and posttest variances (8). Considering the number of assumptions and computations involved, and to be confident about the interpretation, 4 types of pooled estimates were calculated. In the first the available change values were used. In the second and third the change SD for values that were missing or could not be back-calculated were computed with the assumptions of a correlation of P = 0.5 or of independence. For the fourth the postintervention scores and their respective SDs were used.

The presence of publication bias in the extracted data was evaluated by funnel plots (9). The “metabias” command in STATA software (STATA, College Station, TX) was used for statistical testing for funnel plot asymmetry (10). The pooled estimates of the weighted mean difference (WMD) of Hb change between the control and intervention groups were calculated by fixed-effects and random-effects model assumptions using the “metan” command in STATA software (10). Random effects estimates are mainly reported here because most of the pooled results obtained were statistically heterogeneous.

Prespecified stratified analyses were carried out for methodological quality, location in a developing country, location in a malaria hyperendemic area, age of subjects, route of iron administration (oral supplement or iron-fortified food), frequency of iron supplementation per week (for those receiving iron as oral supplements), dose of oral supplement, duration of supplementation, and baseline Hb (mean of both groups). The contribution of these variables to heterogeneity was also explored by metaregression using the “metareg” command in STATA software with the restricted maximum likelihood option (10).

Estimates for the reduction in anaemia (Hb <11 g/dL) prevalence in malarial hyperendemic and nonhyperendemic areas were carried out following the procedure described in Appendix 1.

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Trial Flow

One hundred forty-seven randomised controlled trials were screened, of which 86 were potentially appropriate (11–92). Of these, 31 studies were ineligible (Fig. 1) (11–41); thus, 55 trials (42–92) were evaluated in this systematic review (52 published and 3 unpublished; Agarwal et al, Nagpal et al, and Abdelwahid et al). One study publication had data from 2 separate cohorts (84), which for analytic purposes were taken as 2 separate trials.

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Study Characteristics

Table 1 depicts the baseline characteristics of the included trials. Twenty-three studies were from Asia, 10 from Europe, 4 from North America, 8 from South America, and 11 from Africa. The age of the study population was almost equally distributed with 31 studies in infants and young preschool children (<6 years) and 25 among older children. In 14 studies evaluation was completed within 2 months, whereas 42 investigators followed the subjects for >2 months. In most of the studies (n = 47), subjects received oral medicinal iron; the rest (n = 9) received iron-fortified food. No trial used the parenteral route of administration.

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Quantitative Data Synthesis

The funnel plot (Fig. 2) was skewed, suggesting the presence of a publication bias, which was confirmed using the Egger weighted regression method (P = 0.001) and the Begg rank-correlation method (continuity-corrected P < 0.001).

Data were available for 12,198 children, 6584 of whom received iron and 5614 of whom received placebo (Table 2). The pooled weighted mean difference WMD of the Hb change (pretest vs posttest difference) after iron supplementation was 0.74 g/dL (95% CI, 0.61–0.87; P < 0.001; test for heterogeneity, 1592.5; P < 0.001; Fig. 3; Table 3). The results were similar when the missing SDs were calculated assuming a P value of 0.5, assuming independence, and with posttest scores. The effect size was similar when the analysis was restricted to those studies with available Hb change SD scores (WMD = 0.70 g/dL; 95% CI, 0.56–0.85; P < 0.001; test for heterogeneity, 240.20, P < 0.001). Sensitivity analyses suggested that a higher (nonoverlapping 95% CI) Hb increase was associated with oral medicinal supplementation and baseline Hb levels <11 g/dL (Table 3). Metaregression indicated that lower baseline Hb levels, oral medicinal intake, and location in a malarial nonhyperendemic region were significant predictors of a positive effect of iron supplementation (Table 4).

Estimates for an expected reduction in anaemia prevalence with varying Hb cutoff points in children <6 years of age receiving iron supplementation in malarial hyperendemic and nonhyperendemic regions were calculated with these Hb distribution shifts (Table 5). The average expected anaemia reduction with the World Health Organisation–recommended Hb cutoff point of 11 g/dL, using different baseline mean Hb levels, ranged from 37.9% to 62.3% in malarial nonhyperendemic regions and from 5.8% to 31.8% in malarial hyperendemic areas. The estimated reductions in prevalences of anaemia increased with lower Hb cutoff points to define anaemia.

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The results from this largely heterogeneous data derived from randomised controlled efficacy trials show that iron supplementation significantly increased the Hb concentration of children (WMD = 0.74 g/dL; 95% CI, 0.61–0.87; P < 0.001). Lower baseline Hb level, oral medicinal iron supplementation, and location in a malarial nonhyperendemic area were significant predictors of a greater Hb response and heterogeneity. Projections of expected reduction in baseline anaemia prevalence in children <6 years old receiving oral iron supplementation in malarial nonhyperendemic and hyperendemic regions ranged from 37.9% to 62.3%, and 5.8% to 31.8%, respectively.

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Strengths and Limitations of Analysis

The main conclusion regarding the increase in Hb level following iron supplementation remained stable over a large spectrum of sensitivity analyses performed. Significant explanatory variables were identified to explain heterogeneity, namely baseline Hb level, route of supplementation, and residence in a malarial hyperendemic area. Influence analyses, namely, the effect of omitting 1 study at a time (data not shown) did not reveal an overwhelming effect of any single trial.

Four limitations merit consideration. First, there was evidence of publication bias in the included trials. However, this bias is unlikely to substantially alter the main inference or the magnitude of the pooled estimate because the trials that had Hb change variability measures showed no evidence of publication bias (P > 0.05) and the pooled estimate was similar to that in the entire data set (Table 3). Second, most of the included trials did not identify the cause of anaemia and the contribution of iron deficiency. However, the trials were randomised and controlled, which should control for these factors. Third, because few studies provided relevant data or were designed as preventive interventions, it was not possible to confidently differentiate the preventive effects of iron supplementation. Finally, in trials with missing data on the variability of Hb change, several imputations were made on the basis of prespecified assumptions. The sensitivity analyses suggested that these imputations were robust (Table 3).

A few interesting observations emerged that have programmatic implications and can provide direction for future research. In the absence of definitive population-based data on iron nutriture, the unequivocal demonstration of increase in Hb concentration with iron supplementation highlights the importance of iron deficiency as a contributor to anaemia in children, and reaffirms the need for relevant public health efforts. The review also quantifies the realistic expectations in reductions in baseline anaemia prevalence with iron supplementation alone in malarial hyperendemic and nonhyperendemic settings. The “modest” effects (between 37.9% and 62.3% and 5.8% and 31.8% in malarial nonhyperendemic and hyperendemic areas, respectively) emphasise the multifactorial causes of anaemia and the need for additional interventions, particularly in malarial hyperendemic regions. Our projections in malarial nonhyperendemic regions are compatible with the earlier suggestion that roughly half of anaemia cases may not be due to iron deficiency (93–95). Data from Tanzania also indicate that malaria contributes to 60% of all cases of severe anaemia in infants, whereas iron deficiency contributes to only 30% (96). Evidence therefore supports the current recommendations, which stress integrated strategies to control iron deficiency and malaria where these conditions coexist (97).

The Hb cutoff points to define anaemia are primarily based on statistical considerations from several international data sources in apparently healthy subjects. Ideally, such cutoff points should be established on biological consequences, but unfortunately relevant data are lacking to formulate such definitions. From a public health or programmatic perspective, another approach could be the adoption of a specific intervention selected cutoff points for defining anaemia. As of this writing, iron supplementation is the principal public health intervention to control anaemia, particularly in the nonhyperendemic malaria regions of the developing world. Projections based on this review (Table 5) indicate that the expected reductions in anaemia with iron supplementation increase with the lowering of Hb cutoff points. The possibility of defining anaemia in children younger than 6 years of age with an Hb cutoff value of 10 g/dL instead of the current 11 g/dL therefore needs careful consideration and testing in the context of iron supplementation programs.

A noteworthy finding was the substantially lower increase in Hb concentration from consumption of iron-fortified food (9 trials; WMD = 0.25 g/dL; 95% CI, 0.02–0.52; P = 0.065), which was confirmed on univariate metaregression. The possible explanations for this finding include that most fortification trials (n = 6; 67%) were conducted in developed countries in nonanemic subjects (baseline Hb levels >11 g/dL in 7 of 9 trials); the fortification level may have been inadequate; the bioavailability of the iron may have been poor; and Hb may not have been a sensitive indicator of change in the iron status of the population. Food fortification is often cited as the best approach for combating iron deficiency because it has the potential to reach all sections of the society, compliance is not dependent on the cooperation of the individual, the initial cost is low, and the maintenance expenses may be less than that of medicinal iron supplementation (98). Considering these “obvious” advantages, some experts opine that it would be “reasonable” to forego expensive efficacy studies and proceed directly to a fortification program. However, in view of our findings, it would be prudent to conduct good-quality field trials using iron-fortified foods, particularly for food other than iron-fortified milk substitutes, to unequivocally demonstrate and quantify the hematological effect.

Medicinal iron supplementation was effective in increasing Hb concentration irrespective of the frequency of supplementation (daily or intermittent). These findings are in agreement with an earlier meta-analysis on this subject (4).

On metaregression, contrary to expectation, no significant association was found between the duration of iron supplementation and Hb response. Because the duration of iron supplementation was at least 2 months in 97% of the analytic components (n = 88) and ≥3 months in 75% of the analytic components (n = 68), the data may have been inadequate to detect an association below a threshold of 2 or 3 months. Recent evidence from pregnant women in Bangladesh indicated that, over a period of 12 weeks, 50% of the iron in a daily regimen (60 mg/day elemental iron) was sufficient for maximum Hb effect (99). We cannot critically examine this issue because most of the included trials do not provide relevant compliance data.

The present systematic review contains data from supplementation trials conducted over a period of nearly 4 decades. However, we could not detect any significant relationship between the year of publication and Hb response (data not depicted).

In conclusion, this systematic review indicates that iron supplementation results in a statistically significant increase in Hb in children (pooled estimate of 0.74 g/dL). The increase is greater with lower baseline Hb levels, oral medicinal supplementation, and location in malarial nonhyperendemic regions. Estimates suggest that on average, 37.9% to 62.3% and 5.8% to 31.8% of anaemia cases in the age group of 6 to 59 months are responsive to iron therapy in malarial nonhyperendemic and hyperendemic regions, respectively.

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The authors thank Clive Osmond for offering helpful advice for statistical analysis.

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Representative calculations were made with a cutoff level of 11 g/dL to define anaemia in children up to 6 years of age as per the World Health Organisation recommendations.

A normal distribution of Hb was assumed for computations. The National Family Health Survey data for India gave a prevalence of anaemia (Hb <11 g/dL) of 74%, and of severe anaemia (Hb <7 g/dL) of 5%. With normal mean and SD distributions, 5% corresponds to 1.64485 SD below the mean and 74% corresponds to 0.64335 SD above the mean. Thus, 4 g/dL (i.e., 11-7) corresponds to 1.64485+0.64335 = 2.2882 SD. This means that 1 SD = 4/2.2882 = 1.748 g/dL and that the mean must be 11-0.64335*1.748 = 9.875 g/dL.

In the multiple metaregression baseline Hb status and residence in a malarial hyperendemic region were significant predictors of effect (Table 4). The estimated contribution of these variables was also modeled in conjunction with the pooled estimates (0.74 g/dL; 95% CI, 0.61–0.87) derived from the assumption P = 0.5 as detailed in Table 3. The sample size weighted initial Hb level (11.61 g/dL) was used to derive the regression equations constants. Adjustment was first made only for the differential effect of mean baseline Hb levels as per Table 4, namely an average decrease in Hb response of 0.35 g/dL for 1 g/dL rise in mean baseline Hb concentration (95% CI, 0.47–0.23). Three estimates were derived to broadly give the expected range: Lower 95% CI limit of Hb response to iron supplementation (0.61 g/dL) and lower 95% CI limit of effect modification by mean baseline Hb (0.23 g/dL), which provided the most conservative estimate; average Hb response to iron supplementation (0.74 g/dL) and average effect modification by mean baseline Hb (0.35 g/dL), which provided the average estimate; and higher 95% CI limit of Hb response to iron supplementation (0.87 g/dL) and higher 95% CI limit of effect modification by mean baseline Hb (0.47 g/dL), which provided the maximum estimate.

The equation to estimate the differential effect of baseline Hb was modeled as below. Let Hb1 denote postsupplementation mean Hb and Hb0 mean baseline Hb. Then for the second estimate above:

To derive the value of “a” above:

Thus, the estimating equation was

Similarly, the estimating equations for estimates 1 and 3 above were derived as follows:

Finally, several possible settings with mean (hb0) and SD (hbsd) of baseline Hb were created. The baseline (hbprev0) and postiron (hbprev1) prevalences of anaemia at a specified cutoff point (hbcut), which was used as 11 g/dL as explained above, were calculated by normal distribution. The SPSS syntax used for estimate 2 above is as follows:

The estimated percentage anaemia reduction by iron supplementation was calculated as follows:

Anaemia percent reduction

To adjust for the response in malarial regions, only the average value was considered (Table 4), namely a 0.52 g/dL lower response in malarial region. This value was subtracted from the Hb1 estimates in the first 3 equations above and the changes in anaemia prevalences calculated as above.


Anaemia; Haemoglobin; Iron supplementation; Malaria; Meta-analysis

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