Nutrient Supplementation on the Health Status of Pre-Pubertal Children: A Meta-Analysis By: Susan Chen

ABSTRACT Background: Multiple studies have been carried out to assess the effect of nutrient supplements on children’s health either through direct vitamin and mineral supplementation, food fortification or both. The results of these studies are inconsistent, and the factors behind these varied outcomes are unknown. Objective: Meta-analyses of randomized controlled trials, randomized placebo control trials and retrospective difference-in-difference evaluations were therefore completed to assess the effect of nutrient supplementation on the health of children ages 0-5 years in developing countries. Design: A total of 18 acceptable studies published in the last 20 years were identified by searches in journals of renowned reputation, such as The Lancet (American and British editions), The Journal of Nutrition, The American Journal of Nutrition and The Journal of Pediatrics. These studies identified clear outcomes that would measure changes in the nutritional status of the population (mainly variations in stunting, wasting, infant mortality, anemia). The factors associated with effect sizes were explored by meta-regression techniques. Results: The overall effect of nutrition supplements on health outcomes was positive although the studies indicate that nearly half of all interventions (7 out of 18 studies) had a neutral effect. In this meta-analysis, the impacts might be influenced by design features such as the type of intervention and sample size. The impacts might also vary by geographical location and by infants who are breast-fed versus those who are not. However, a meta-regression of these factors on study outcomes reveals that these factors are insignificant (p>0.1). Conclusions: Interventions to improve children’s health should be considered in populations at risk of undernourishment, especially where there are elevated rates of disease or mortality. However, policymakers should think twice about distributing certain supplements, like iron tablets, to children who have malaria or other diseases as preexisting underlying conditions. In these cases, interventions to address malnutrition should be complemented with interventions toward disease control and management.

INTRODUCTION

Micronutrients play a central part in metabolism and in the maintenance of tissue

function. For example, zinc plays a critical role in the cellular growth and metabolism in humans.

Zinc deficiency is associated with impaired growth, increased susceptibility to infections, and

other functional abnormalities (Institute of Medicine, 2001). Thus, an adequate nutrient intake is

necessary, but provision of excess supplements to people who do not need them may be harmful.

There is growing interest in the role of the micronutrients (vitamins and minerals) in

optimizing health, and in prevention or treatment of disease. This stems partly from the increase

in knowledge and understanding of the biochemical functions of these nutrients. The best

evidence for benefit is in children in developing countries consuming a deficient diet (seen in

some of the studies in this meta-analyses).

Since then, a considerable number of intervention trials have been completed in multiple

countries to assess the effect of nutrient supplements on children’s health. These studies have

yielded inconsistent results, however, possibly because of differences in 1) the preexisting health

status of the study subjects, 2) the content and availability of nutrients in the local diets, and 3)

the incidence of disease that can affect health independently of nutritional intervention.

Moreover, methodological aspects of these studies, such as variations in the nutrition dose and

method of administration may have influenced their results. Finally, in some cases, the sample

sizes may have been inadequate to detect potentially important differences in health with

statistical confidence.

For these reasons, a systematic, quantitative review of available studies is needed to

determine the overall effect of nutrient supplementation on children’s health. This review will

therefore consider current knowledge of the requirements in health, those people at risk of an

inadequate intake, and the conditions where supplements may be clinically required (Institute of

Medicine, 2001). The review will focus only on the generally accepted essential inorganic

micronutrients (trace elements) and organic micronutrients (fat soluble and water soluble

vitamins) for which deficiency states, with biochemical, physiological, or structural changes,

have been clearly reported—such states occur after prolonged consumption of a diet lacking the

single nutrient under consideration, and are uniquely remedied by including the nutrient back

into the diet.

I believe that a meta-analysis of several studies of mortality and morbidity will help to

make evidence-based recommendations for the role of nutrient supplementation in public health

policy to improve mortality, morbidity, growth, and development in young children. Therefore, I

completed a meta-analyses of intervention trials that were conducted to assess the effect of direct

vitamin and mineral supplementation, food fortification or both on pre-pubertal (ages 0-5 years)

children. I also explored characteristics of the study populations that could be used to predict

these responses to nutrient supplementation.

METHODS

Preliminary meta-analyses have been published previously on the effects of certain

nutrition supplements (iron, zinc, Vitamin A, etc) on specific health outcomes (height, weight,

mortality, etc). An example meta-analysis evaluated vitamin A supplementation on child

mortality (Fawzi, 1993). My meta-analyses differ from the earlier ones in several important

ways: 1) additional studies were identified by using a comprehensive bibliographic search in

several journals of renowned reputation and 2) a holistic approach was taken to evaluate general

health outcomes (improve or not improve health) through at least three different types of

interventions (address malnutrition either through direct vitamin and mineral supplementation,

food fortification or both). Furthermore, additional analyses were completed in the present

version to determine the characteristics of individual studies that may have influenced the

observed responses to supplemental nutrients.

Identification of studies

The studies considered for possible inclusion in the current meta-analyses were identified

by comprehensive searches in The Lancet (American and British editions), The Journal of

Nutrition, The American Journal of Nutrition and The Journal of Pediatrics. The studies of

choice were published within the last 20 years – 1991 to 2011. The studies were screened to

evaluate if they addressed undernourishment either through direct vitamin and mineral

supplementation, food fortification or both.

Inclusion criteria Studies were considered for inclusion in the meta-analyses if they met the following criteria:

1) Provide a comparison between treatment and control groups - or before and after the intervention, including randomized controlled trials, randomized placebo control trials and retrospective difference-in-difference – evaluations.

2) Identify clear outcomes that would measure changes in the nutritional status of the population.

3) Include sample sizes greater than 100.

4) Include at least five different covariates in the analyses, with special emphasis on age,

sex, and nutritional status at baseline, underlying diseases, ancillary interventions, and maternal health.

5) Target the population of children and young infants between 0 and 60 months, or a

subgroup within (i.e. neonates between 0 - 90 days).

6) Target geographical areas known to have prevalent malnutrition (South East Asia, West and East Africa and the Caribbean).

7) Provide adequate details about the design and implementation of the experiment, and the

statistical analysis completed to support conclusions.

I was intent on my identification of studies that met these criteria, and by doing so, found

studies of interest. Since no irrelevant studies were identified, no studies were excluded from my

meta-analyses. Irrelevant studies include those that target the elderly, include too few covariates,

intervene in developed countries, or have small sample sizes.

Review of studies and extraction of summary data

I assessed the suitability of 30 studies for inclusion in the meta-analyses, and the results

of these assessments were then independently re-evaluated. Consensus for inclusion relied on the

use of the pre-established inclusion criteria. Once the final set of studies for inclusion in the

analyses was established, I prepared written summaries of key descriptive information

concerning the study design, baseline characteristics of the study subjects, and outcomes of the

intervention. This summary is included in Table 1.

Analysis of data

The primary response variables included in each of the separate analyses were variations

in stunting, wasting, infant mortality, and anemia. For simplicity’s sake, I labeled the health

outcomes as positive (+1), negative (-1), or neutral (0). The use of effect sizes solves the problem

that the measurement units applied and the durations of observation were inconsistent by study.

Table 1: Summary of Studies

Author (Year) Location Outcomes Intervention / Program Impact Design Covariates Sample Size Menon et al (2005)

Haiti Change in health status

Iron supplementation and food fortification

+1 RCT 8 425

Sedgh et al (2000)

Sudan “ Vitamin A supplementation*

+1 RCT 7 28,753

Bryce et al (2010)

Benin, Ghana, Mali

“ Vitamin A and Iron/Folic Acid supplementation during pregnancy

0

Retrospective Evaluation**

14 6,820

Andang’o et al (2007)

Kenya “ High and low doses of Iron supplementation

+1 RCT 14 505

Sazawal et al (2006)

Zanzibar “ Iron and Folic Acid Supplementation***

+1 RCT 12 24,076

Darboe et al (2007)

Gambia “ Vitamin A supplementation

0 RCT 13 220

Umeta et al (2000)

Ethiopia “ Zinc supplementation

+1 RCT 17 200

Tielsch et al (2007)

Nepal “ Iron and Zinc supplementation***/****

0 RCT 13 41,276

Rahman et al (2002)

Bangladesh “ Vitamin A and zinc supplementation

+1 RCT 9 411

Ruel et al (2008)

Haiti “ Vitamin A supplementation

+1 RCT 14 1,588

SUMMIT (2008)

Indonesia “ Multiple micronutrients supplementation****

+1 RCT 12 31,290

Vaidya et al (2008)

Nepal “ Multiple micronutrient supplementation*

+1

RCT 19 917

Kerac et al (2009)

Malawi “ Probiotics

0 RCT 30 795

Verhoef et al (2002)

Kenya “ High and low doses of Iron supplementation

+1 RCT 24 516

Kirkwood et al (1996)

Ghana “ Vitamin A supplementation * 0 RCT 18 1455

Ramakrishanan et al (1995)

India “ Vitamin A supplementation 0 RCT 9 592

West et al (1991)

Nepal “ Vitamin A supplementation

+1 RCT 7 24,085

Sazawal et al. (2007)

Zanzibar “ Zinc supplementation***

0 RCT 12 42,546

NB: Change in nutritional status includes increased weight and height (growth/stunting), decreased morbidity, changes in mortality levels, vitamin levels, blood (anemia reduction, hemoglobin levels) * Control group was not a placebo but another vitamin (E or iron and folic acid) ** Difference-in-difference analysis between treatment and country-level data based on Demographic and Health Surveys and Multiple Indicator Cluster Surveys. *** In addition, all groups received Vitamin A supplementation. **** Control group was standard iron and folic acid supplementation.

The overall effect of nutrition supplements on health outcomes was positive (with a mean

impact of +0.611, shown in the blue line in Table 2), although the studies indicate that nearly

half of all interventions (7 out of 18 studies) had a middle-of-the-road effect.

To validate the findings, I have conducted a simple statistical analysis of factors that

might influence the estimated policy impact. In this meta-analysis, the impacts might be

influenced by design features such as the type of intervention and sample size. The impacts

might also vary by geographical location and infants that are breast-fed compared to those who

are not.

Table 2

Generally, none of these factors influenced my study. All the factors (type of

intervention, sample size, location, and breast-fed status) show insignificant p-values of p>0.1.

RESULTS

Description of studies and study subjects

Eighteen studies were considered acceptable for inclusion in the analyses. The general

characteristics of the studies and their participating subjects are shown in Table 1. The data sets

that were used for the present analyses provided information for 206,470 children in 14 different

countries where malnutrition is an issue. The 18 studies were published between 1991 and 2010

(median: 2006). The number of subjects per study ranged from 200 to 42,546 (mean: 11,470).

Ambiguous Results

0   0.5   1  

Menon et al (2005) Sedgh et al (2000) Bryce et al (2010)

Andang’o et al (2007) Sazawal et al (2006) Darboe et al (2007) Umeta et al (2000)

Tielsch et al (2007) Rahman et al (2002)

Ruel et al (2008) SUMMIT (2008)

Vaidya et al (2008) Kerac et al (2009)

Verhoef et al (2002) Kirkwood et al (1996)

Ramakrishanan et al West et al (1991)

Sazawal et al. (2007) Impact

Impact  

In Sazawal et al (2009), there was a non-significant (p=0.29) reduction in the relative risk

of all cause mortality associated with zinc supplementation. In Kerac et al (2009), nutritional

findings were similar in both control and treatment groups (p=0.4). Thus, the probiotics did not

improve proscribed nutritional or clinical outcomes from severe acute malnutrition. In Tielsch et

al (2007), there were no significant differences in mortality between the zinc and placebo groups

(p<0.05). The frequency and duration of diarrhea, persistent diarrhea, dysentery, and acute lower

respiratory infections did not differ between the groups. In Darboe et al (2007), some trials have

shown possible adverse effects of higher doses of vitamin A (p<0.01). In Bryce et al (2010), the

researchers recorded no significant improvements in nutritional status attributable to vitamin A

supplements in the three countries. Mortality in children younger than 5 years decreased in

intervention areas by 13% in Benin (p=0.12), 20% in Ghana (p=0.10), and 24% in Mali

(p<0.0001), but these decreases were not greater than those in comparison areas in Benin (25%;

p=0.15) or Mali (31%; p=0.30). In Ramakrishanan et al (1995), the differences in growth

increments between the two groups were not statistically significant (the independent variables

are considered statistically significant for p<0.05). In Kirkwood et al (1996), vitamin A

supplementation did not lead to significant height increases in Ghanaian children (p>0.02).

Positive Results

In Umeta et al (2000), the length of stunted infants increased significantly more

(p<0.001) when supplemented with zinc than with placebo and the effect was greater (p<0.01)

than in non-stunted infants. Zinc supplementation also increased the weight of stunted children

(p<0.001) and of non-stunted children (p<0.05). In West et al (1991), the positive effect of

vitamin A supplementation was evident across age and gender (p<0.05). In Ruel et al (2008),

stunting, underweight, and wasting were 4–6 percentage points lower in preventive than in

recuperative communities; and mean anthropometric indicators were higher by +0.14 Z scores

(height for age; p=0.07), and +0.24 Z scores (weight for age and weight for height; p<0.0001). In

Vaidya et al (2008), the intervention group showed a slightly significant increase in weight-for-

age (p=0.048) after micronutrient supplementation. In the SUMMIT (2008) study, infants of

women consuming micronutrient supplements had an 18% reduction in early infant mortality

compared with those in the control group (p=0.01). Combined fetal loss and neonatal deaths

were reduced by 11% (p=0.045), with significant effects in infants of undernourished and anemic

women. In Sazawal et al (2006), those who received iron and folic acid with or without zinc

were 12% (p=0.02) more likely to die or need treatment in hospital for an adverse event and 11%

(p=0.03) more likely to be admitted to hospital; there were also 15% (p=0.19) more deaths in

these groups. In Verhoef et al (2002), the groups assigned iron plus sulfadoxine-pyrimethamine,

iron alone, or sulfadoxine-pyrimethamine alone had higher hemoglobin concentrations than the

group assigned placebo (p=0.08). In Andang’o et al (2007) the prevalence of iron-deficiency

anemia in children given flour fortified with high-dose iron edetic acid (NaFeEDTA), low-dose

NaFeEDTA, and electrolytic iron changed by −89%, −48%, and 59%, respectively. In Sedgh et

al (2000), children in the vitamin A intervention group grew 13 mm more during the study than

children in the control group (p=0.08). In Menon et al (2005), mean hemoglobin levels increased

for the children treated with micronutrient sprinkles (p<0.001). In Rahman et al (2002), joint zinc

and vitamin A supplementation improves vitamin A levels in vitamin A–deficient children

(p<0.05). Interestingly, zinc alone was associated with a significant increase in acute respiratory

infection, but this adverse effect was reduced by interaction between zinc and vitamin A.

Publication Bias

Formal analyses were completed to detect possible publication bias, which can occur

when authors fail to submit papers with insignificant results or journals fail to accept these

papers for publication. If publication bias is occurring, then studies with both small sample sizes

and small effect sizes are less likely to be found, resulting in a negative correlation between

absolute effect size and sample size. Therefore, one method of assessing publication bias is to

examine the correlation between effect size and sample size.

In each meta-analysis, the correlation between the number of subjects and the effect size

of individual studies was examined for possible publication bias. The correlation coefficients

ranged from –0.28 to 0.20, suggesting that there was not a problem with publication bias.

I also examined the strength of the conclusions by calculating how many additional

(possibly unpublished) studies with zero effect size would have to be available to negate the

slightly positive results of the current meta-analyses examining health improvements through

nutrient provision. Three more studies with ambiguous findings are necessary (bringing the total

negated effect studies to 10 (7+3) out of a possible 21 (18+3) studies.

DISCUSSION

Meta-analysis techniques are increasingly being used to consolidate results from multiple

studies of the same topic and to develop evidence-based policies for public health intervention.

The reliability of the conclusions derived from meta-analyses depends on the methodological

quality of the original studies, the appropriateness of the study inclusion criteria, and the

thoroughness of the review and synthesis of information.

In the current analyses, I included a sizeable number of rigorously designed intervention

trials of the effect of nutrient supplementation on children’s health outcomes. The results indicate

that changes in the nutritional status of the population (variations in stunting, wasting, infant

mortality, anemia) are positive in populations at risk of undernourishment, especially where there

are elevated rates of disease or mortality. However, certain supplements, like iron tablets, may

have adverse effects on children who have malaria or other diseases as preexisting underlying

conditions. In these cases, interventions to address malnutrition should be complemented with

interventions toward disease control and management.

The failure to identify any significant correlations between the sample sizes of individual

studies and the magnitude of the effect of supplementation suggests that these conclusions are

not likely to have been influenced by publication bias. The strength of the findings is further

supported by the fact that all of the studies included in the meta-analyses used a suitable clinical

trial design, including randomized controlled trials, randomized placebo control trials and

retrospective difference-in-difference evaluations, confirming that the supplements were

successfully delivered to the study subjects.

The criteria for inclusion of studies in the current analyses differed somewhat from

existing health provision meta-analyses studies. I was more holistic in my approach, looking at

the effect of three types of intervention- either through direct vitamin and mineral

supplementation, food fortification or both- on general health outcomes in children ages 0-5

years. Thus, it may not be appropriate to combine results from the different sets of study subjects

in a single meta-analysis. A more exacting meta-analyses looking at specific nutrient

supplements on certain health outcomes may be more suitable for generalizing findings and

translating results into policy interventions. Despite these changes in the inclusion criteria, the

results of the current analyses are generally consistent with previously published findings. The

positive effect of 0.611 is consistent with overall findings that nutrient supplementation can

produce positive health outcomes in undernourished children.

APPENDIX A List of Studies and Authors

Study Author and Year

1 Micronutrient Sprinkles Reduce Anemia among 9- to 24-Mo-Old Children When Delivered through an Integrated Health and Nutrition Program in Rural Haiti Menon et al (2005)

2 Dietary Vitamin A Intake and Nondietary Factors Are Associated with Reversal of Stunting in Children Sedgh et al (2000)

3 The Accelerated Child Survival and Development programme in west Africa: a retrospective evaluation Bryce et al (2010)

4 Efficacy of iron-fortified whole maize flour on iron status of schoolchildren in Kenya: a randomised controlled trial

Andang’o et al (2007)

5 Effects of routine prophylactic supplementation with iron and folic acid on admission to hospital and mortality in preschool children in a high malaria transmission setting: community-based, randomised, placebo-controlled trial

Sazawal et al (2006)

6 Effectiveness of an early supplementation scheme of high-dose vitamin A versus standard WHO protocol in Gambian mothers and infants: a randomised controlled trial Darboe et al (2007)

7 Zinc supplementation and stunted infants in Ethiopia: a randomised controlled trial Umeta et al (2000)

8 Effect of daily zinc supplementation on child mortality in southern Nepal: a community based, cluster randomized, placebo-controlled trial Tielsch et al (2007)

9 Effect of zinc supplementation on mortality in children aged 1–48 months: a community-based randomised placebo- controlled trial Sazawal et al. (2007)

10 Age-based preventive targeting of food assistance and behaviour change and communication for reduction of childhood undernutrition in Haiti: a cluster randomised trial Ruel et al (2008)

11 Synergistic effect of zinc and vitamin A on the biochemical indexes of vitamin A nutrition in children Rahman et al (2002)

12 Effect of maternal multiple micronutrient supplementation on fetal loss and infant death in Indonesia: a double-blind cluster-randomised trial SUMMIT (2008)

13 Effects of antenatal multiple micronutrient supplementation on children’s weight and size at 2 years of age in Nepal: follow-up of a double-blind randomised controlled trial Vaidya et al (2008)

14 Probiotics and prebiotics for severe acute malnutrition (PRONUT study): a double-blind efficacy randomised controlled trial in Malawi Kerac et al (2009)

15 Intermittent administration of iron and sulfadoxine- pyrimethamine to control anaemia in Kenyan children: a randomised controlled trial Verhoef et al (2002)

16 Effect of vitamin A supplementation on the growth of young children in northern Ghana Kirkwood et al (1996)

17 Vitamin A Supplementation Does Not Improve Growth of Preschool Children: A Randomized, Double-Blind Field Trial in South India

Ramakrishanan et al (1995)

18 Efficacy of vitamin A in reducing preschool child mortality in Nepal West et al (1991)

APPENDIX B STATA Outputs NB: chg_stat_bin indicates the change in health status 1) Type of Intervention . probit chg_stat_bin type_int Probit regression Number of obs = 20 LR chi2(1) = 1.19

Prob > chi2 = 0.2756 Log likelihood = -12.865862 Pseudo R2 = 0.0442

2) Breast-Fed Infants . probit chg_stat_bin ante_bfeed Probit regression Number of obs = 20

LR chi2(1) = 0.84 Prob > chi2 = 0.3593

Log likelihood = -13.040115 Pseudo R2 = 0.0312 chg_stat_bin Coef. Std. Err. z P>|z| [95% Conf.

Interval] ante_bfeed .5244005 .5751444 0.91 0.362 -.6028617

1.651663 _cons 6.23e-17 .3963327 0.00 1.000 -.7767979

.7767979 3) Sample Size . probit chg_stat_bin samp_size Probit regression Number of obs = 20 LR chi2(1) = 0.16 Prob > chi2 = 0.6884 Log likelihood = -13.379798 Pseudo R2 = 0.0060 chg_stat_bin Coef. Std. Err. z P>|z| [95% Conf.

Interval] samp_size -.2507149 .6274383 -0.40 0.689 -1.480471

.9790415

chg_stat_bin Coef. Std. Err. z P>|z| [95% Conf. Interval]

type_int -.7579695 .7164222 1.06 -0.290 -2.162131 .6461922

_cons .8416212 .6389635 1.32 0.188 -.4107241 2.093967

_cons .4307273 .529291 0.81 0.416 -.606664 1.468119

4) Location . probit chg_stat_bin afc_loc Probit regression Number of obs = 20

LR chi2(1) = 1.29 Prob > chi2 = 0.2565

Log likelihood = -12.816447 Pseudo R2 = 0.0478 chg_stat_bin Coef. Std. Err. z P>|z| [95% Conf.

Interval] afc_loc -.6744897 .6024912 -1.12 0.263 -1.855351

.5063713 _cons .6744897 .4817634 1.40 0.162 -.2697491

1.618729 5) All Factors . probit chg_stat_bin type_int ante_bfeed samp_size afc_loc Probit regression Number of obs = 20

LR chi2(7) = 7.46 Prob > chi2 = 0.3829

Log likelihood = -9.7318457 Pseudo R2 = 0.2770 chg_stat_bin Coef. Std. Err. z P>|z| [95% Conf.

Interval] type_int -.7434057 1.053212 -0.71 0.480 -2.807663

1.320851 ante_bfeed 1.593766 1.021614 1.56 0.119 -.4085603

3.596091 samp_size -.2051846 1.06916 -0.19 0.848 -2.300699

1.89033 afc_loc -.8897456 1.245409 -0.71 0.475 -3.330703

1.551212 _cons .8274845 1.689028 0.49 0.624 -2.482949

4.137918 6) Summary . sum type_int ante_bfeed samp_size afc_loc Variable Obs Mean Std. Dev. Min Max type_int 20 .75 .4442617 0 1 ante_bfeed 20 .5 .5129892 0 1 samp_size 20 .7 .4701623 0 1 afc_loc 20 .6 .5027247 0 1

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