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.
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).
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.
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).
The authors thank Clive Osmond for offering helpful advice for statistical analysis.
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APPENDIX. SUMMARY OF ASSUMPTIONS AND THE METHOD OF ESTIMATING REDUCTION IN ANAEMIA PREVALENCE
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.
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