Multiple studies have been carried out to assess the effect of zinc supplementation on children’s growth. The results of these studies are inconsistent, and the factors responsible for these varied outcomes are unknown. In the published systematic reviews on the topic [6,7], there is considerable variability in terms of participants, nature of interventions, choice of control groups, study setting, and other key variables. It is thus difficult to provide unambiguous evidence-based advice to policy makers in LMICs about the safety and benefits of investing in zinc supplementation programs to improve linear growth in under-five children. An updated systematic review, primarily focused on LMICs, may be helpful in crystalizing relevant policy. We conducted this systematic review to study the effect of zinc supplementation on growth (measured by anthropometry) and prevalence of malnutrition.

We included randomized controlled trials with variations in design, including random allocation of individuals or clusters, multi-arm trials, factorial trials and cross-over trials for the first period of measurement only. Quasi-randomized controlled trials (individual or cluster allocation done on the basis of a pseudo-random sequence; for example, odd/even, house number or date of birth, alternation) were also eligible for inclusion. We included trials conducted in children below 5 years of age from LMICs. Trials conducted exclusively in disease conditions and in children with severe acute malnutrition (SAM) were excluded

We included studies that provided zinc supplementation, either as medicinal supplementation or through food fortification. Trials with simultaneous fortification or supplementation of additional micronutrients, or simultaneous co-interventions like health education and/or drugs (for example, deworming or antimalarials) were included if the only difference between the intervention and comparison arms was zinc supplementation.

Primary: anthropometry: weight, height, weight-for-height (WFH), mid upper arm circumference (MUAC), head circumference; Secondary: prevalence of malnutrition.

We searched (June 2017) the following electronic databases: Medline, Web of Science, BIOSIS Previews, Greysource, Cochrane Controlled Trials Register, EMBASE and IBIDS. Reference lists of all included papers and relevant reviews were scanned to identify citations that have been missed in the primary search. We contacted authors of other relevant reviews in the field regarding additional studies of which they may be aware. We searched Science Citation Index and Social Sciences Citation Index for papers, which cite studies included in the review. Websites of organizations like Micronutrient Initiative and iZiNCG were also searched. The search results from the various databases and other sources were merged using reference management software (Endnote) to remove duplicate records. The title and abstract of the studies identified in the computerized search were scanned in duplicate to exclude references that were obviously irrelevant. In order to determine eligibility for inclusion of the remaining articles, their full texts were reviewed, and multiple reports of the same study were linked together. Two authors independently screened and assessed the eligibility of the studies, extracted relevant data and assessed the risk of bias for all included studies. Any dispute regarding these criteria was resolved among the investigators by mutual consultation. Web Appendix 1 outlines the search strategy adopted for the electronic databases.

We evaluated the risk of bias for each trial using the criteria outlined in the Cochrane Handbook for Systematic Reviews of Interventions [8]. Plots of ‘Risk of bias’ assessments were created in Review Manager (RevMan) [9].

Risk ratio (RR) estimates with 95% confidence intervals (CI) were used for binary outcomes; for continuous outcomes, mean differences (MD) were used. In order to maximize the data input for the pooled outcome measures, we utilized post-intervention values (means and standard deviations (SDs)) in preference to the changes from baseline [8]. In factorial trials and in multi-arm designs yielding two or more intervention groups (different zinc doses or salts used) and a single control group, the data in the intervention groups, including the variation in the intervention characteristic, was pooled and compared against the single control group to prevent unit-of-analysis error. For cluster-randomized trials, we used the stated cluster-adjusted RR or means and 95% CI, irrespective of the method employed for adjustment. In case of missing data, we contacted trial authors for information wherever possible; and where this could not be done, or the authors did not respond, we imputed the missing values, where feasible. In case any assumptions were made for such imputations, they were recorded, and are detailed in Web Appendix 2.

We performed statistical analysis using the Revman software. Pooled estimates of the evaluated outcome measures were calculated by the generic inverse variance method. Pooled WMD and SMD were calculated as per standard recommendations [8]. We expected variation in studies with respect to populations, interventions, comparators, outcomes and settings, and thus used the random-effects model. If it was not possible to synthesize the data from the included studies, we provided a narrative synthesis of the results. The data were finally synthesized as a ‘Summary of findings’ table. For each outcome, quality assessment of the results was also carried out using the GRADE approach [10], which specifies four levels of quality (high, moderate, low and very low) where the highest quality rating is for a body of evidence based on randomized trials. We planned to explore the following differences in effect for ‘length’, by subgroup analyses: (i) supplementation method (medicinal versus fortification); (ii) supplement compound; (iii) study population from South Asia; (iv) dose of zinc (mg); (v) duration of supplementation; (vi) compliance estimation (directly observed or replacement versus others); (vii) baseline zinc levels; and (viii) baseline prevalence of stunting. We chose length-for-age Z-score as the variable for subgroup analysis, as it is an age-independent parameter and more important from public health perspective. We could not do the subgroup analysis for the first parameter (supplementation method) as all studies had used medicinal supplementation.

The search output from various databases is detailed in Web Appendix 1, and the results are summarized in Fig. 1. We screened 3886 records, of which 237 were potentially eligible. Of these, 147 references were excluded and 91 publications (63 studies) were included in the final analyses [3,11-100]. These studies (5 cluster RCTs and 58 RCTs) incorporating data on 27372 children were included in the final analysis (Web Table I). Twenty-eight (44%) of the included trials were conducted in Asia (17 from South Asia), 16 trials were conducted in Africa and 19 in Latin America. The details of study location, intervention and outcomes are summarized in Web Table I.

Fig. 1 The PRISMA flow chart.

Web Fig. 1 and Web Fig. 2 summarize the Risk of Bias for the included studies. The risk of bias for the 55 trials was low for random sequence generation. It was considered to be high for two trials and unclear for the remaining six studies. The risk of bias for allocation concealment was judged to be low in 39, unclear in 21 and high in 3 studies. Blinding of participants and research personnel was at unclear risk in 5, at high risk in 2 studies and low risk in 56 trials. The risk of blinding of outcome assessment was considered low for 34 trials, unclear for 27 and high for 2 trials. The risk of bias for attrition was judged to be high for 32 trials, unclear for 2 trials because of no information available, and low for remaining 29 trials. In the five cluster randomized trials, two studies were considered to be at unclear risk for incorrect analysis and one trial for baseline imbalance. Seven trials were judged to be having other potential causes of bias, including baseline imbalance of groups (3), formula milk use (2) and protocol deviations related to key intervention (2).

Height/Length (Web Appendix 3A): Twenty-nine trials reported data on height-for-age Z-score (HAZ) in the study participants. Quantitative synthesis from 25 trials (Fig. 2) revealed no evidence of effect of zinc supplementation on HAZ (9165 participants; MD= 0.00; 95% CI -0.07, 0.07; P=0.98; Moderate Quality Evidence) in comparison to controls, with significant heterogeneity between trials (I² = 57%; P<0.001). In subset analysis to explore heterogeneity, the dose of zinc and duration of zinc supplementation were important predictors of heterogeneity. Supplement compound, location in South Asia, compliance estimation, baseline serum zinc levels, baseline prevalence of stunting and baseline HAZ did not predict heterogeneity. Thirteen trials studied the effect of zinc supplementation on change in HAZ. On quantitative synthesis in 8852 participants, the MD for change in HAZ was 0.11 (95% CI -0.00, 0.21; P=0.05; Moderate Quality Evidence; Fig. 3) with substantial heterogeneity between trials (I² = 94%; P<0.001). Twenty-one trials reported the effect of zinc supplementation on length/height at the end of supplementation period. On quantitative synthesis from 19 trials, there was no evidence of effect on length/height (6303 participants; MD= 1.18 cm; 95% CI -0.63, 2.99 cm, P=0.20; Moderate Quality Evidence; considerable heterogeneity, I²=99%; Fig. 4) with zinc supplementation as compared to controls. Twenty-six trials reported the effect of zinc supplementation (vs. controls) on change in length/height (cm) from baseline to the end of supplementation period. In 25 of these trials with 10783 participants, the pooled change in length/height with zinc supplementation as compared to controls was 0.43 cm (95% CI 0.16, 0.70, P=0.002; considerable hetero-geneity, I²=93%; Moderate Quality Evidence; Fig. 5). Funnel plots of all height-related outcomes showed no evidence of publication bias (Web Fig. 3a to 3d).

Fig. 2 Forest plot of effect of zinc supplementation on height-for-age Z scores.

Fig. 3 Forest plot of effect of zinc supplementation on change in height-for-age Z scores.

Fig. 4 Forest plot of effect of zinc supplementation on height/length at the end of supplementation period.

Fig. 5 Forest plot of effect of zinc supplementation on change in height/length.

Weight (Web Appendix 3B): Twenty-five trials reported data on weight-for-age Z-score (WAZ) in the study participants. In 23 trials on 9033 participants (Fig. 6), the mean difference in WAZ was 0.05 (95% CI -0.03, 0.13; P=0.19; Moderate Quality Evidence; substantial heterogeneity, I²=75%) between zinc supplemented and control group. Thirteen trials studied the effect of zinc supplementation on change in WAZ from baseline. Quantitative synthesis from these trials (Fig. 7) showed no evidence of effect on change in WAZ with zinc supplementation in comparison to controls (8851 study participants; MD= 0.03; 95% CI -0.01, 0.08; P=0.17; Moderate Quality Evidence; substantial heterogeneity, I²=66%). Weight at the end of the supplementation period was reported in 20 studies. Quantitative synthesis from 19 of these trials (Fig. 8) showed positive effect of zinc supplementation on weight as compared to control population (8851 study participants; MD= 0.23 kg; 95% CI 0.03, 0.42; P=0.02; Moderate Quality Evidence). Twenty-three trials reported on change in weight (kg) from baseline to the end of supplementation period. Quantitative synthesis (Fig. 9) revealed a positive effect (10143 participants; MD=0.11 kg; 95% CI 0.05, 0.17; P<0.001; Moderate Quality Evidence) of zinc supplementation in comparison to controls. There was significant heterogeneity between trials comparing weight parameters between the two groups, and funnel pots showed no evidence of publication bias (figures not shown).

Fig. 6 Forest plot of effect of zinc supplementation on weight-for-age Z scores.

Fig. 7 Forest plot of effect of zinc supplementation on change in weight-for-age Z scores.

Fig. 8 Forest plot of effect of zinc supplementation on weight at the end of supplementation period.

Fig. 9 Forest plot of effect of zinc supplementation on change in weight.

Weight-for-height (Web Appendix 3C): In 22 trials reporting data on weight-for-height Z-score (WHZ), there was no evidence of effect of zinc supplementation on WHZ in comparison to controls (19 trials; 8392 study participants; MD=0.03; 95% CI -0.02, 0.08; P=0.21; Moderate Quality Evidence; considerable heterogeneity, I²=91%; Fig. 10). In 12 trials evaluating the change in weight from height Z-scores, there was no evidence of effect on change in WHZ with zinc supplementation as against controls (8706 study participants; MD= 0.01; 95% CI -0.03, 0.04; P=0.74; Moderate Quality Evidence; substantial heterogeneity, I²=80%; Fig. 11). There was no evidence of publication bias on examining the funnel plots (figures not shown).

Fig. 10 Forest plot of effect of zinc supplementation on weight-for-height Z scores at the end of supplementation period.

Fig. 11 Forest plot of effect of zinc supplementation on change in weight-for-height Z scores.

MUAC (Web Appendix 3C): In 7 trials evaluating MUAC, there was no effect of zinc supplementation (vs. controls) on MUAC (4236 participants; MD = 0.0 cm; 95% CI -0.08, 0.09; P=0.93; Moderate Quality Evidence) with no significant heterogeneity between trials (I² = 18%; P=0.29) (Fig. 12). There was moderate quality evidence of little increase in the change in MUAC from baseline (8 trials; 1724 participants; MD = 0.09 cm; 95% CI 0.01, 0.16; P=0.03; no heterogeneity, I²=0%) by zinc supplementation in comparison to controls (Fig. 13).

Fig. 12 Forest plot of effect of zinc supplementation on mid upper arm circumference at the end of supplementation period.

Fig. 13 Forest plot of effect of zinc supplementation on change in mid upper arm circumference.

Head circumference (Web Appendix 3D): In quantitative synthesis from six trials (Fig. 14) showed higher head circumference in zinc supplemented group as against control group (2966 participants; MD= 0.39 cm; 95% CI 0.03, 0.75; P=0.03; Moderate Quality Evidence; substantial heterogeneity, I²=67%). However, change in head circumference was not different in the zinc supplemented and placebo groups (4 trials; 497 participants; MD = 0.26 cm; 95% CI -0.18, 0.71: P=0.24; Moderate Quality Evidence; substantial heterogeneity, I²=79%) (Fig. 15).

Fig. 14 Forest plot of effect of zinc supplementation on head circumference at the end of supplementation period.

Fig. 15 Forest plot of effect of zinc supplementation on change in head circumference.

Nutritional Status (Web Appendix 3D): In trials reporting on stunting, underweight or wasting, funnel plots did not show any evidence of publication bias (figures not shown). Quantitative synthesis from nine trials (Fig. 16) showed no effect on stunting (11838 participants; RR= 1.0; 95% CI 0.95, 1.06; P=0.89; Moderate Quality Evidence; no significant heterogeneity, I²=11%) with zinc supplementation in comparison to controls. In 7 trials reporting on the prevalence of underweight children, quantitative synthesis (Fig. 17) showed no effect of zinc supplementation (vs. controls) on underweight (8988 participants; RR= 0.94; 95% CI 0.82, 1.06; P=0.31; Moderate Quality Evidence; substantial heterogeneity, I²=73%). Quantitative synthesis (Fig. 18) from seven trials showed no effect of zinc supplemen- tation on wasting (8677 participants; RR= 1.08; 95% CI 0.96, 1.21; P=0.19; Moderate Quality Evidence) with no significant heterogeneity (I²=13%, P=0.33).

Fig. 16 Forest plot of effect of zinc supplementation on stunting.

Fig. 17 Forest plot of effect of zinc supplementation on underweight.

Fig. 18 Forest plot of effect of zinc supplementation on wasting.

In this systematic review of 63 trials incorporating data on 27372 children, there was no evidence of any difference in the final length/height for age or Z scores or change in length/height-for-age Z scores at the end of the supplementation period with zinc or placebo/no intervention, but studies assessing the change in length/height showed slight benefit with zinc supplementation. In addition, there was marginal increase in weight of children receiving zinc supplementation in comparison to placebo, but it did not affect weight-for-age or weight-for-height Z scores. There was a marginal positive effect on the change in MUAC from baseline. Zinc supplemented children also had a slightly higher head circumference at the end of supplementation period, but there was no evidence of effect on change in head circumference. Moreover, there was no evidence of a beneficial effect on prevalence of wasting, stunting or underweight at the end of supplementation period.

All included studies involved children under five years from LMICs. This is a population that is likely to have poor zinc nutriture and, therefore, benefit more from zinc supplementation. A large number of trials were available from varied geographical settings (28 from Asia, 16 from Africa, and 19 from Latin America), conducted in different age groups and in different population settings (ranging from tertiary level medical institutions to community studies in urban slums and rural communities). Control groups in most trials were comparable with intervention groups at baseline. Thus any observed effects, or lack thereof, in the intervention groups are more likely to be attributable to zinc supplementation. We, therefore, believe that the evidence from this review is largely applicable to real-life situations among under-five children in LMICs.

Most studies in this systematic review had a low risk of bias for key parameters, including sequence generation, allocation concealment and blinding. Also given the large number of studies available for most outcomes, the certainty of evidence is reasonable (moderate quality) for most of the important outcomes, and this review is likely to provide a good indication of the likely effect. The review was conducted by following the guidelines laid down in the Cochrane Handbook for Systematic Review [8], and this is likely to eliminate most sources of bias and identify the remaining. In some studies, anthropometric measurements were not available as the results were either depicted only in graphs or summary statistics, which is a potential source of bias. However, this is unlikely to affect the overall direction of results as narrative synthesis from these few studies was broadly in agreement with quantitative synthesis from this systematic review.

The earliest systematic review on this topic by Brown, et al. [6] included 33 studies, and reported a meaningful positive effects of zinc supplementation in height-for-age Z-score and weight-for-age Z-score without significant effect on weight-for-height indices. However, this review also included older children, besides being not restricted to LMICs. Ramakrishnan, et al. [7] reviewed 43 trials, and reported marginal benefits in terms of change in HAZ, WAZ and WHZ. Imdad, et al. [101] reported a significant positive effect of zinc supplementation on height gain in the developing countries, but studies providing other micronutrients in addition to zinc were also included. Mayo-Wilson, et al. [102], in a review of 50 studies (including children from all countries), showed no evidence of difference in height or stunting with little increase in weight and weight-to-height ratio. A very recent systematic review [103] evaluated effect of zinc supplementation provided during antenatal period or during childhood, and reported slightly increased height, weight and weight-for-age Z-score, but no effect on height-for-age Z-score, weight-for-height Z score, stunting, underweight or wasting, with supplementation provided after birth. In comparison to this review, our review focussed on LMIC where the problem of zinc deficiency is considered a major public health problem. In comparison to the review by Liu, et al. [103], the present review included more trials (63 vs. 54), probably because of a wide variety of database search and inclusion of trials with shorter (<3 mo) duration of supplementation. However, these results are broadly in conformity with our findings; marginal differences probably arise from variations in populations and analytical methods.

Evidence from this review suggests that zinc supplementation probably leads to little or no improvement in anthropometric indices and malnutrition (stunting, underweight and wasting) in children under five years of age from LMICs. Advocating zinc supplementation as a public health measure to improve growth, therefore, appears unjustified in these settings with scarce resources. Using high stunting prevalence as an indicator of population-level zinc deficiency is also questionable. However, as most studies in this review examined the effects of medicinal supplementation with zinc, effect of fortification of foods with zinc on growth needs to be evaluated in pragmatic modes. Considering other potential benefits of zinc supplementation, comprehensive evaluation of cost effectiveness, including relative effects of medicinal and fortification routes, is also desirable.

Contributors: TG: conceptualized the review, literature search, data analysis and manuscript writing; DS: literature search, data analysis and manuscript writing; HPS: conceptualized the review, data analysis and its interpretation, and critical inputs into manuscript writing.

Funding: Indian Council of Medical Research (5/7/869/2012-RCH (CH)).

Competing interests: None stated.

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