Susan stata.project-meta analysisDocument Transcript
Nutrient Supplementation on the Health Status of Pre-Pubertal Children:A Meta-AnalysisBy: 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 tissuefunction. 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, andother functional abnormalities (Institute of Medicine, 2001). Thus, an adequate nutrient intake isnecessary, 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) inoptimizing health, and in prevention or treatment of disease. This stems partly from the increasein knowledge and understanding of the biochemical functions of these nutrients. The bestevidence for benefit is in children in developing countries consuming a deficient diet (seen insome of the studies in this meta-analyses). Since then, a considerable number of intervention trials have been completed in multiplecountries to assess the effect of nutrient supplements on children’s health. These studies haveyielded inconsistent results, however, possibly because of differences in 1) the preexisting healthstatus 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 andmethod of administration may have influenced their results. Finally, in some cases, the samplesizes may have been inadequate to detect potentially important differences in health withstatistical confidence. For these reasons, a systematic, quantitative review of available studies is needed todetermine the overall effect of nutrient supplementation on children’s health. This review willtherefore 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 ofMedicine, 2001). The review will focus only on the generally accepted essential inorganicmicronutrients (trace elements) and organic micronutrients (fat soluble and water solublevitamins) for which deficiency states, with biochemical, physiological, or structural changes,have been clearly reported—such states occur after prolonged consumption of a diet lacking thesingle nutrient under consideration, and are uniquely remedied by including the nutrient backinto the diet. I believe that a meta-analysis of several studies of mortality and morbidity will help tomake evidence-based recommendations for the role of nutrient supplementation in public healthpolicy to improve mortality, morbidity, growth, and development in young children. Therefore, Icompleted a meta-analyses of intervention trials that were conducted to assess the effect of directvitamin 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 predictthese responses to nutrient supplementation.METHODS Preliminary meta-analyses have been published previously on the effects of certainnutrition supplements (iron, zinc, Vitamin A, etc) on specific health outcomes (height, weight,mortality, etc). An example meta-analysis evaluated vitamin A supplementation on childmortality (Fawzi, 1993). My meta-analyses differ from the earlier ones in several importantways: 1) additional studies were identified by using a comprehensive bibliographic search inseveral journals of renowned reputation and 2) a holistic approach was taken to evaluate generalhealth outcomes (improve or not improve health) through at least three different types ofinterventions (address malnutrition either through direct vitamin and mineral supplementation,
food fortification or both). Furthermore, additional analyses were completed in the presentversion to determine the characteristics of individual studies that may have influenced theobserved responses to supplemental nutrients.Identification of studies The studies considered for possible inclusion in the current meta-analyses were identifiedby comprehensive searches in The Lancet (American and British editions), The Journal ofNutrition, The American Journal of Nutrition and The Journal of Pediatrics. The studies ofchoice were published within the last 20 years – 1991 to 2011. The studies were screened toevaluate if they addressed undernourishment either through direct vitamin and mineralsupplementation, food fortification or both.Inclusion criteriaStudies 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 StudiesAuthor (Year) Location Outcomes Intervention / Program Impact Design Covariates Sample SizeMenon et al Haiti Change in Iron supplementation and food +1 RCT 8 425(2005) health status fortificationSedgh et al Sudan “ Vitamin A supplementation* +1 RCT 7 28,753(2000)Bryce et al Benin, “ Vitamin A and Iron/Folic Acid 0 Retrospective 14 6,820(2010) Ghana, Mali supplementation during pregnancy Evaluation**Andang’o et al Kenya “ High and low doses of Iron +1 RCT 14 505(2007) supplementationSazawal et al Zanzibar “ Iron and Folic Acid +1 RCT 12 24,076(2006) Supplementation***
Darboe et al Gambia “ Vitamin A supplementation 0 RCT 13 220(2007)Umeta et al Ethiopia “ Zinc supplementation +1 RCT 17 200(2000)Tielsch et al Nepal “ Iron and Zinc 0 RCT 13 41,276(2007) supplementation***/****Rahman et al Bangladesh “ Vitamin A and zinc +1 RCT 9 411(2002) supplementationRuel et al Haiti “ Vitamin A supplementation +1 RCT 14 1,588(2008)SUMMIT Indonesia “ Multiple micronutrients +1 RCT 12 31,290(2008) supplementation****Vaidya et al Nepal “ Multiple micronutrient +1 RCT 19 917(2008) supplementation*Kerac et al Malawi “ Probiotics 0 RCT 30 795(2009)Verhoef et al Kenya “ High and low doses of Iron +1 RCT 24 516(2002) supplementationKirkwood et al Ghana “ Vitamin A supplementation * 0 RCT 18 1455(1996)Ramakrishanan India “ Vitamin A supplementation 0 RCT 9 592et al (1995)West et al Nepal “ Vitamin A supplementation +1 RCT 7 24,085(1991)Sazawal et al. Zanzibar “ Zinc supplementation*** 0 RCT 12 42,546(2007) 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 Impact Sazawal et al. (2007) West et al (1991) Ramakrishanan et al Kirkwood et al (1996) Verhoef et al (2002) Kerac et al (2009) Vaidya et al (2008) SUMMIT (2008) Ruel et al (2008) Rahman et al (2002) Impact Tielsch et al (2007) Umeta et al (2000) Darboe et al (2007) Sazawal et al (2006) Andang’o et al (2007) Bryce et al (2010) Sedgh et al (2000) Menon et al (2005) 0 0.5 1 Generally, none of these factors influenced my study. All the factors (type ofintervention, sample size, location, and breast-fed status) show insignificant p-values of p>0.1.RESULTSDescription of studies and study subjects Eighteen studies were considered acceptable for inclusion in the analyses. The generalcharacteristics of the studies and their participating subjects are shown in Table 1. The data setsthat were used for the present analyses provided information for 206,470 children in 14 differentcountries 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
In Sazawal et al (2009), there was a non-significant (p=0.29) reduction in the relative riskof all cause mortality associated with zinc supplementation. In Kerac et al (2009), nutritionalfindings were similar in both control and treatment groups (p=0.4). Thus, the probiotics did notimprove proscribed nutritional or clinical outcomes from severe acute malnutrition. In Tielsch etal (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 lowerrespiratory infections did not differ between the groups. In Darboe et al (2007), some trials haveshown possible adverse effects of higher doses of vitamin A (p<0.01). In Bryce et al (2010), theresearchers recorded no significant improvements in nutritional status attributable to vitamin Asupplements in the three countries. Mortality in children younger than 5 years decreased inintervention 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 growthincrements between the two groups were not statistically significant (the independent variablesare considered statistically significant for p<0.05). In Kirkwood et al (1996), vitamin Asupplementation 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 ofvitamin 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). InVaidya 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 ofwomen consuming micronutrient supplements had an 18% reduction in early infant mortalitycompared with those in the control group (p=0.01). Combined fetal loss and neonatal deathswere reduced by 11% (p=0.045), with significant effects in infants of undernourished and anemicwomen. In Sazawal et al (2006), those who received iron and folic acid with or without zincwere 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 inthese groups. In Verhoef et al (2002), the groups assigned iron plus sulfadoxine-pyrimethamine,iron alone, or sulfadoxine-pyrimethamine alone had higher hemoglobin concentrations than thegroup assigned placebo (p=0.08). In Andang’o et al (2007) the prevalence of iron-deficiencyanemia in children given flour fortified with high-dose iron edetic acid (NaFeEDTA), low-doseNaFeEDTA, and electrolytic iron changed by −89%, −48%, and 59%, respectively. In Sedgh etal (2000), children in the vitamin A intervention group grew 13 mm more during the study thanchildren in the control group (p=0.08). In Menon et al (2005), mean hemoglobin levels increasedfor the children treated with micronutrient sprinkles (p<0.001). In Rahman et al (2002), joint zincand 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 respiratoryinfection, 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 thesepapers for publication. If publication bias is occurring, then studies with both small sample sizesand small effect sizes are less likely to be found, resulting in a negative correlation betweenabsolute effect size and sample size. Therefore, one method of assessing publication bias is toexamine the correlation between effect size and sample size. In each meta-analysis, the correlation between the number of subjects and the effect sizeof individual studies was examined for possible publication bias. The correlation coefficientsranged 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 theslightly positive results of the current meta-analyses examining health improvements throughnutrient provision. Three more studies with ambiguous findings are necessary (bringing the totalnegated 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 multiplestudies 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 methodologicalquality of the original studies, the appropriateness of the study inclusion criteria, and thethoroughness of the review and synthesis of information. In the current analyses, I included a sizeable number of rigorously designed interventiontrials of the effect of nutrient supplementation on children’s health outcomes. The results indicatethat 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 thereare elevated rates of disease or mortality. However, certain supplements, like iron tablets, mayhave adverse effects on children who have malaria or other diseases as preexisting underlyingconditions. In these cases, interventions to address malnutrition should be complemented withinterventions toward disease control and management. The failure to identify any significant correlations between the sample sizes of individualstudies and the magnitude of the effect of supplementation suggests that these conclusions arenot likely to have been influenced by publication bias. The strength of the findings is furthersupported by the fact that all of the studies included in the meta-analyses used a suitable clinicaltrial design, including randomized controlled trials, randomized placebo control trials andretrospective difference-in-difference evaluations, confirming that the supplements weresuccessfully delivered to the study subjects. The criteria for inclusion of studies in the current analyses differed somewhat fromexisting health provision meta-analyses studies. I was more holistic in my approach, looking atthe effect of three types of intervention- either through direct vitamin and mineralsupplementation, food fortification or both- on general health outcomes in children ages 0-5years. Thus, it may not be appropriate to combine results from the different sets of study subjectsin a single meta-analysis. A more exacting meta-analyses looking at specific nutrientsupplements on certain health outcomes may be more suitable for generalizing findings andtranslating results into policy interventions. Despite these changes in the inclusion criteria, theresults of the current analyses are generally consistent with previously published findings. Thepositive effect of 0.611 is consistent with overall findings that nutrient supplementation canproduce positive health outcomes in undernourished children.
APPENDIX A List of Studies and Authors Study Author and Year Micronutrient Sprinkles Reduce Anemia among 9- to 24-Mo-Old Children When Delivered1 Menon et al (2005) through an Integrated Health and Nutrition Program in Rural Haiti Dietary Vitamin A Intake and Nondietary Factors Are Associated with Reversal of Stunting2 Sedgh et al (2000) in Children The Accelerated Child Survival and Development programme in west Africa: a retrospective3 Bryce et al (2010) evaluation Efficacy of iron-fortified whole maize flour on iron status of schoolchildren in Kenya: a Andang’o et al4 randomised controlled trial (2007) Effects of routine prophylactic supplementation with iron and folic acid on admission to5 hospital and mortality in preschool children in a high malaria transmission setting: Sazawal et al (2006) community-based, randomised, placebo-controlled trial Effectiveness of an early supplementation scheme of high-dose vitamin A versus standard6 Darboe et al (2007) WHO protocol in Gambian mothers and infants: a randomised controlled trial7 Zinc supplementation and stunted infants in Ethiopia: a randomised controlled trial Umeta et al (2000) Effect of daily zinc supplementation on child mortality in southern Nepal: a community8 Tielsch et al (2007) based, cluster randomized, placebo-controlled trial Effect of zinc supplementation on mortality in children aged 1–48 months: a community-9 Sazawal et al. (2007) based randomised placebo- controlled trial Age-based preventive targeting of food assistance and behaviour change and communication10 Ruel et al (2008) for reduction of childhood undernutrition in Haiti: a cluster randomised trial Synergistic effect of zinc and vitamin A on the biochemical indexes11 Rahman et al (2002) of vitamin A nutrition in children Effect of maternal multiple micronutrient supplementation on fetal loss and infant death in12 SUMMIT (2008) Indonesia: a double-blind cluster-randomised trial Effects of antenatal multiple micronutrient supplementation on children’s weight and size at13 Vaidya et al (2008) 2 years of age in Nepal: follow-up of a double-blind randomised controlled trial Probiotics and prebiotics for severe acute malnutrition (PRONUT study): a double-blind14 Kerac et al (2009) efficacy randomised controlled trial in Malawi Intermittent administration of iron and sulfadoxine- pyrimethamine to control anaemia in15 Verhoef et al (2002) Kenyan children: a randomised controlled trial Kirkwood et al16 Effect of vitamin A supplementation on the growth of young children in northern Ghana (1996) Vitamin A Supplementation Does Not Improve Growth of Preschool Children: A Ramakrishanan et al17 Randomized, Double-Blind Field Trial in South India (1995)18 Efficacy of vitamin A in reducing preschool child mortality in Nepal West et al (1991)
APPENDIX BSTATA OutputsNB: chg_stat_bin indicates the change in health status1) Type of Intervention. probit chg_stat_bin type_intProbit regression Number of obs = 20 LR chi2(1) = 1.19 Prob > chi2 = 0.2756Log likelihood = -12.865862 Pseudo R2 = 0.0442chg_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 2.0939672) Breast-Fed Infants. probit chg_stat_bin ante_bfeedProbit regression Number of obs = 20 LR chi2(1) = 0.84 Prob > chi2 = 0.3593Log likelihood = -13.040115 Pseudo R2 = 0.0312chg_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 .77679793) Sample Size. probit chg_stat_bin samp_sizeProbit regression Number of obs = 20 LR chi2(1) = 0.16 Prob > chi2 = 0.6884Log likelihood = -13.379798 Pseudo R2 = 0.0060chg_stat_bin Coef. Std. Err. z P>|z| [95% Conf. Interval]samp_size -.2507149 .6274383 -0.40 0.689 -1.480471 .9790415
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