Study Protocol: The Impact of Growth Charts and Nutritional Supplements on Child Growth in Zambia (ZamCharts): A Cluster Randomized Controlled Trial

doi:10.21203/rs.3.rs-2816403/v1

Download PDF

Study protocol

Study Protocol: The Impact of Growth Charts and Nutritional Supplements on Child Growth in Zambia (ZamCharts): A Cluster Randomized Controlled Trial

https://doi.org/10.21203/rs.3.rs-2816403/v1

This work is licensed under a CC BY 4.0 License

Version 1

posted

You are reading this latest preprint version

Background:Almost a quarter of children under the age of five in low- and middle-income countries (LMICs) currently experience growth faltering. Early childhood stunting (height/length-for-age z-score < -2) is associated with a range of adverse later life outcomes including reduced cognitive development, poor school achievement and increased probability of living in poverty as adults. Few effective interventions are currently available to address stunting in LMICs.

Methods: We will conduct a 2x2 cluster-randomized factorial trial with ~2300 caregiver-child dyads residing in 280 communities (clusters) located in Luapula, Lusaka, and Southern Provinces of Zambia. Clusters will be randomized into four groups each comprising 70 clusters with ~560 caregiver-child dyads: i) a control group ii) a growth charts only group; iii) a small quantity lipid-based nutrient supplements (SQ-LNS) only group; and iv) a growth charts + SQ-LNS group. Families in the growth charts groups (ii and iv) will receive a locally developed poster installed in their home that allows them to compare the height of their children to the World Health Organization’s international growth reference tables. The poster will also include health and nutrition messages for infants and young children in alignment with Ministry of Health recommended practices. Families in the SQ-LNS groups (iii and iv) will be given monthly rations (30 sachets) of SQ-LNS over a period of 18 months. Pediatric anthropometry and a caregiver survey will be conducted at baseline and endline. The primary study outcome is height-for-age z-score and stunting (HAZ < -2) after 18-months of intervention, when children will be between 24 and 36 months of age. Secondary outcomes will be anemia, weight-for-height, weight-for-age and child development. In a subsample we will also assess micronutrient status (Retinol-binding protein (RBP) for Vitamin A deficiency, ferritin for iron deficiency, and hemoglobin for anemia), inflammation (C-reactive protein (CRP), α1-acid glycoprotein (AGP)), biomarkers of environmental enteric dysfunction, the composition of the bacterial community in the gut microbiome and saccadic reaction time (SRT), an eye-tracking measure of neural function.

Discussion:This study was designed to assess the impact of growth charts as well as the extent to which early childhood growth faltering can be mitigated through SQ-LNS supplementation in three purposely selected highly diverse areas of Zambia.

Trial registration: This study is registered at clinicaltrials.gov as NCT0512042. https://clinicaltrials.gov/ct2/show/NCT05120427

nutrition

height-for-age z-score

growth charts

supplements

lipid-based nutrients

home-based fortification

anemia

child development

micro-nutrients

More than 250 million children under the age of five are currently estimated to not reach their developmental potential due to poverty, malnutrition, and infectious diseases (1). According to the latest estimates, 21% of children under age five in low- and middle- income countries (LMICs) (2) are more than two standard deviations shorter than the global reference median and thus considered stunted according to World Health Organization (WHO) guidelines (3). Early life malnutrition interferes with children’s ability to learn (4) and has been associated with reduced cognitive development and physical growth (5, 6). Stunting has also been linked to delayed school enrolment (7), reduced educational attainment (7–10), poor health (11), and decreased well-being (12).

There is a growing consensus among scientists, the global public health and development community, as well as among governments that addressing stunting is a top priority for promoting children’s development and wellbeing, and for increasing children’s future economic potential (13). While a large body of literature has highlighted the importance of favourable environmental and socioeconomic factors for the prevention of early growth faltering (2, 14, 15), effective interventions to reduce growth faltering in LMIC settings remain scarce. Among families of affected children, stunting often goes unrecognized in communities where growth faltering is common (13). Even children with substantial delays in their physical development may be perceived as of normal size in comparison to peer children in their community. In many parts of Zambia as well as other LMICs, height measurements are not routinely conducted as part of child health check-ups (16), and many caregivers are unaware of their child’s growth deficits and needs for additional nutritional inputs (17).

Growth monitoring, traditionally performed through primary healthcare or community-based services, is meant to be a diagnostic tool for assessing the status of a child’s growth and to instigate appropriate action, such as improved feeding practices or referral for supplemental feeding programs, to prevent child malnutrition and mortality. Critically, growth monitoring is meant to make growth faltering visible to caregivers so that they can adopt improved childcare behaviors (18). However, the evidence for traditional growth monitoring suggests little or no effect on children’s nutritional status (19), and that infrequent monitoring may not be sufficient to improve caregiver understanding of child growth status and related practices (20).

Providing home-based growth charts, which include clear and context-adapted health and nutrition messages, for caregivers to measure their children’s growth is one potentially affordable and sustainable way to increase access to information about children’s nutrition and growth, specifically height information. Growth charts can be easily placed on walls inside homes and allow caregivers to directly compare their children’s heights to their expected age- and sex-appropriate reference distributions. The charts can also provide caregivers with information on key infant and young child feeding practices including promoting breastfeeding and age-appropriate recipes, and the presence of the chart in their home has the potential to serve as a frequent cue to action for caregivers (21, 22). In a previous pilot study, we found that providing caregivers with growth charts reduced stunting rates among previously malnourished children by 22 percentage points over a period of 15 months in Chipata district, Zambia (17).

Infants in LMIC settings are often fed diets that fall short in delivering the needed macro and micronutrients for adequate growth and development (23). According to a survey conducted in Zambia in 2018, only 13% of children age 6–23 months were fed a minimum acceptable diet in the 24 hours before the survey, and 58% of children age 6–59 months were anaemic (24). Small-quantity lipid-based nutrient supplements (SQ-LNS) have the potential to fill important nutrient gaps. SQ-LNS typically comes in the form of single-serving sachet that provides energy, protein, essential fatty acids, and a wide range of micronutrients. Recent meta-analytic evidence (25) based on randomized trials that included a total of more than 37,000 children shows that SQ-LNS can reduce the prevalence of stunting by 12 to 14 percent (26) and wasting by 14 to 30 percent (27). SQ-LNS can also lower the prevalence of micronutrient deficiencies (28), including iron deficiency anaemia, and reduce the risk of cognitive, socio-emotional, and motor development delay (29). The Lancet 2021 series on Maternal and Child Undernutrition included SQ-LNS as one of the recommended interventions for preventing/reducing malnutrition among children (30). Programs using SQ-LNS have reported higher uptake and adherence both among children and caregivers than micronutrient programs using supplements and powders in other sub-Saharan African settings (31, 32), possibly due to their appealing taste and added caloric content.

Though SQ-LNS has been shown to improve children’s nutrition and growth, further research is needed with regard to the effect of SQ-LNS on gastrointestinal health, including its influence on environmental enteric dysfunction (EED) and the gut microbiome. As part of this trial, we will assess the effect of SQ-LNS on EED and the gut microbiome in a sub-sample of children in Lusaka district. EED is an acquired, sub-clinical condition of the small intestine characterized by mucosal inflammation, villous blunting, altered barrier integrity, and reduced intestinal absorptive capacity. EED is highly prevalent in many LMICs and has been linked to adverse growth and development, and may limit responsiveness to dietary interventions (33). While EED is thought to be predominantly caused by exposures to unhygenic environments, SQ-LNS holds promise to enhance children’s ability to reduce risk of EED. Thus far, only a few studies have focused on the impact of SQ-LNS on intestinal health and results from these studies have shown mixed results. For example, studies from Zimbabwe (34) and Malawi (35) showed no difference in EED biomarker concentrations between children who did and did not receive SQ‐LNS. However, another recent study from Bangladesh showed SQ‐LNS reduced intestinal inflammation at 14 months of age but increased intestinal inflammation and permeability at 28 months of age (36).

To date, only two studies have assessed the effect of regular consumption of lipid-based nutrient supplements on the gut microbiota (37, 38). One integrated human-mouse study based on fecal transplantation from Malawian twins discordant for kwashiorkor found that the provision of LNS produced temporary effects on metabolic functions in kwashiorkor gut microbiomes, and that these changes regressed when LNS was stopped (38). A recent trial in Malawi also found that the provision of SQ-LNS during pregnancy and from 6–18 months in children resulted in an increase in infant gut microbiota diversity at 18 months after 12-months of direct LNS consumption, and that the effect of SQ-LNS on alpha diversity indices was modified by season and household assets (37). However, the effect of SQ-LNS on taxonomic composition of the gut microbiome at other ages was minimal. Early life microbial colonization of the GI tract is critical for health and development. A recent series of human and animal studies show that the GI microbiota can play a causal role in the development of severe acute malnutrition (38–41); however, few studies have assessed the gut microbiome of children in African contexts (42, 43), with the exception of a few seminal studies from children in Malawi (44–47). Given its critical role in the development of the metabolic (48, 49), endocrine (50) and immune systems (51–53), early life perturbations in the GI microbiome could impair nutrient absorption and metabolism, and increase the risk of malnutrition and impaired growth (39, 54, 55). Understanding the influence of SQ-LNS on the infant gut microbiome is thus critical for understanding the potential long-term consequences of the supplements for child health and development.

Aims of the study

The overall objective of this project is to assess the impact of growth charts as well as SQ-LNS on children’s physical growth in three purposely selected highly diverse areas of Zambia . This larger objective can be divided into three specific aims, as well as four sub-aims:

Specific Aim 1: Estimate the respective independent impacts of home-installed growth charts and monthly home delivery of SQ-LNS on children’s physical growth.

Specific Aim 2: Estimate the respective independent impacts of home-installed growth charts and monthly home delivery of SQ-LNS on children’s weight, haemoglobin levels and overall development.

Specific Aim 3: Estimate the joint impact of home-installed growth charts and SQ-LNS on physical growth.

We will also pursue the following sub-aims:

Sub-Aim 1: Estimate the independent and joint impacts of growth charts and SQ-LNS on micronutrient status (RBP for Vitamin A deficiency, and ferritin iron deficiency) in a sub-sample of children residing in Lusaka district

Sub-Aim 2: Estimate the independent and joint impacts of growth charts and SQ-LNS on the relative abundance of specific taxa and diversity of bacteria in the gut microbiome in a sub-sample of children residing in Lusaka district

Sub-Aim 3: Estimate the independent and joint impacts of growth charts and SQ-LNS on serum biomarkers of EED and systemic inflammation, including zonulin, intestinal fatty-acid binding protein (I-FABP), lipopolysaccharide (LPS), CRP, and AGP.

Sub-Aim 4:Estimate the independent and joint impacts of growth charts and SQ-LNS on saccadic reaction time (SRT), an eye-tracking measure of neural function.

Study design

We will conduct a multi-center 2x2 factorial, cluster-randomized controlled trial with ~2300 children and their caregivers in three geographically and culturally diverse areas of Zambia.

Study setting

This study will be in Lusaka district, Mansa district and Choma district in Zambia. These areas were selected to capture the variation in local diet, food availability, and child stunting rates across Zambia. Lusaka city is the capital of Zambia with a population of around 3 million. Study participants from Lusaka district are from predominantly urban and peri-urban areas. By contrast, Mansa district in Luapula province is 765 km from the capital city and is a predominantly rural area where the majority of the population engages in agriculture. Finally, Choma in Southern province is located 300 km South of Lusaka, and has some rural, peri-urban and urban parts. The prevalence of stunting in children <5yrs in Lusaka, Luapula and Southern provinces was 36%, 29% and 45% in 2018, respectively (24). In terms of primary crops, maize is the primary staple crop in Southern Province, while Luapula traditionally relies more on cassava.

Study participants and recruitment and inclusion criteria

A total of ~2,300 caregiver-child dyads will be enrolled in the study. Caregivers will be identified using two-stage stratified sampling procedures. In the first step, we will randomly select 90 enumeration areas from each of the three districts using the 2020 census sampling frame from the Central Statistical Office of Zambia (CSO). In a second step, we will visit all households in these areas (~250 households) to create a list of all eligible households – i.e. households with an infant between 7 and 14 months. All eligible dyads (~8 per cluster) will be visited by trained study staff, who will explain the study to caregivers and enroll them into the study conditional on their consent. Caregiver-child dyads will be excluded if they state their intention to migrate out of the study area within 12 months of the recruitment time point..

Interventions

This study aims to assess two interventions: growth charts and SQ-LNS provision.

Growth charts: Growth charts will be locally developed, placed on the walls inside homes, and allow caregivers an easy means of assessing their child’s height at home. The charts will also contain information on the importance of exclusive breastfeeding, diverse diets, frequent feeding, washing hands with soaps, and age-appropriate recipes using local foods. After the home installation of growth charts, caregivers will be given a short introduction on how to use them and how to interpret the measurements by study staff. The overall structure of the gender-specific posters is illustrated in Supplemental Materials Figure SF 1.

Small-quantity lipid-based nutrient supplements (SQ-LNS): SQ-LNS are 20 g/~110 calorie nutrient supplements that provide energy, protein, essential fatty acids and a wide range of micronutrients critical for children ages 6 to 24 months of age. The SQ-LNS used in this study will be Nutributter+, produced by Nutriset. They are designed to complement diets without displacing breastmilk and local dietary preferences and can be mixed into the child’s meal or eaten directly from the sachet. SQ-LNS has an 18-24 month shelf life, can be stored at room temperature and is not vulnerable to spoilage at high temperatures. To ensure an appropriate supply of SQ-LNS, a monthly supply of 30 sachets will be delivered to caregivers in the clusters selected for this intervention.

Primary endpoint

The primary endpoint will be children’s height and stunting (HAZ < -2) after 18 months of interventions, when children will be between 24 and 35 months old. Height will be assessed using standard anthropometric assessment kits. Height measures will be converted to height-for-age z-scores (HAZ) using the WHO anthro software package (56).

Secondary endpoints
Secondary outcomes include: weight-for-height z-score, weight-for-age z-score, hemoglobin concentration, child development (assessed through the global scales of early development) as well as the prevalence of stunting, wasting, underweight and anemia. In a sub-sample of children we will also assess micronutrient status ), inflammation, biomarkers of EED, the composition of the bacterial community in the gut microbiome, and SRT.

Measures to minimize bias

This study will be conducted as a cluster-randomized controlled trial, which should minimize the risk of selection and confounding bias. We chose to randomize at the cluster level to minimize the risk of spillover. Children’s development will be assessed objectively through trained interviewers minimizing the risk of reporting or social desirability biases.

Sample size and power calculations

The study is statistically powered (p=0.9) to detect a 0.25 SD improvement in HAZ over an 18-month period between the control group and any of the intervention arms (charts only, LNS only, combined intervention). This calculation is based on α=0.05, a follow-up rate of 85% (attrition <= 15%), and an intra-class correlation coefficient (ICC) of 0.05 (DEFF=1.95 with 20 children per cluster).

The estimated improvement in HAZ 0.25 is based on the results from the pilot study. The ICC in the pilot study was 0.02. A more conservative ICC of 0.05 was assumed for this study to ensure sufficient power.

Randomization/Sequence Generation

This is a cluster-randomized controlled trials. Clusters will be assigned with equal probability to arms 1,2, 3 and 4 using a random number draw generated by the senior author (GF) using the Stata SE 16.0 statistical software package.

Blinding/Masking

Given the nature of the interventions, blinding of participating caregivers and children is not possible. Interviewers will not be aware of the treatment group of children, and analysis will be done using concealed treatment assignment (analyst blinding).

Statistical Analysis

We will use standard linear regression models to assess the impact of the two intervention arms on child development. The primary outcome variable will be HAZ, which is normalized globally to mean zero and standard deviation 1. Cluster-robust standard errors will be used to account for the cluster-level randomization of the intervention. Separate models will be estimated with and without baseline covariates. Our primary model will be estimated following an intent-to-treat approach; we will also estimate complementary per-protocol models restricted to children complying with the two interventions. Compliance with posters will be defined as still having a poster hanging at children’s home at endline; compliance with the supplementation will be defined as having received the monthly supplements for 75% or more of the intervention period.

The final analysis will primarily rely on the data collected in the endline survey. Baseline variables will be used to 1) assess the extent to which balance was reached through the randomization and 2) create a set of control variables used in adjusted models.

Ethics

The study was approved by the Ethics Committee for North-Western Switzerland (EKNZ) as well as by the Biomedical Research Ethics Committee of the University of Zambia.

All changes to the protocol will be reported to both ethics committees.

Interim analyses

No interim analysis is foreseen.

Deviation(s) from the original statistical plan

Any deviations from the original statistical plan will be reported in the Methods section of the trial paper.

Handling of data

Missing data will arise when a participant refuses to answer a question or complete part of the examination. Missing data may also arise is a participant drops out of the study. All participants are informed that their participation is completely voluntary and that they may refuse to answer any of the questions asked and can stop the evaluation at any time as well as discontinue participation at any time without any consequences. Missing data on covariates will be imputed using multiple imputations using chained equations. Missing outcome data due to sample attrition will not be imputed; however, we will conduct and report analyses examining the extent to which attrition differed across treatment conditions.

Access to data

All data collected as part of this trial will be made publicly available (in de-identified form) after publication of the trial results.

This study will be conducted in close collaboration with the Zambian Ministry of Health (MoH). We will be providing briefings on study progress through the Department of Public Health and will discuss technical and other essential matters with an advisory board purposely set up for this study comprising a UNICEF nutrition specialist, a WHO Nutrition specialists and members of the Zambian National Food and Nutrition Commission.

The ultimate objective of this study is to assess if the two interventions can have a positive impact when delivered at a large scale as well as the relative investment needed to achieve this impact. The study will also involve direct observations of local feeding practices, detailed tracking of costs related to the distribution of SQ-LNS and the growth charts, as well as assessment of local willingness to pay for SQ-LNS, which will be critical to determine optimal pricing strategies for potential future government- or NGO-operated programs. The study will also implement a detailed assessment of children’s cognitive development at age 2, using the newly developed Global Scales of Early Development (GSED), as well as eye-tracking technologies to asses SRT – these measures will allow us to better understand the links between early life nutritional intake and children’s early neuro-cognitive development. The study will also include a detailed assessment of children’s micronutrient status as well as their gut biome in a subsample of children – these assessments will not only help us better understand the extent to which SQ-LNS nutrients are actually absorbed by children, but also how improved diets can modify gut health more broadly.

EED environmental enteric dysfunction

HAZ height-for-age z-score

LMICs low and middle income countries

SQ-LNS Small-quantity lipid-based nutrient supplements

SRT Saccadic reaction time (SRT),

Ethics and consent

Written informed consent was obtained from all caregivers prior to the interview and assessment. The study protocol was reviewed and approved by the Ethics Committee Northwest Switzerland (EKNZ – AO2021-00016) as well as the University of Zambia Biomedical Research Ethics Committee (1411-2020). All research will be conducted in accordance with the Declaration of Helsinki.

Consent for publication

All authors have consented to the publication of this protocol.

Availability of data and materials

De-identified data will be made publicly available after the publication of the trial.

Competing interests

The authors declare no competing interests.

Funding

This project was funded by Sint Antonius Stichting. The funder played no role in the study design, analysis or interpretation of results.

Authors' contributions

GF, DP and PR designed the original trial. LL and JL led all biomarker-related work, including development of field protocols and quality monitoring, and co-developed the study protocol. DS provided input into the design and coordinated the selection of localities with the government. TBM and MC coordinated local study implementation, IRB and ensured data quality. SH supported all logistical aspects of the project and coordinated all research activities. CK designed and supervised the nutritional intake home observation study. JL and JP coordinated and supervised all neuro-cognitive assessments. All authors provided input to this protocol and approved the final version.

Acknowledgements

We would like to thank all IPA field workers for their outstanding effort and all participating families for helping us with this project.

Black MM, Walker SP, Fernald LC, Andersen CT, DiGirolamo AM, Lu C, et al. Early childhood development coming of age: science through the life course. 2017;389(10064):77-90.
Vaivada T, Akseer N, Akseer S, Somaskandan A, Stefopulos M, Bhutta ZA. Stunting in childhood: an overview of global burden, trends, determinants, and drivers of decline. The American Journal of Clinical Nutrition. 2020;112(Supplement_2):777S-91S.
WHO Multicentre Growth Reference Study Group. WHO Child Growth Standards: Length/height-for-age, weight-for-age, weight-for-length, weight-for-height and body mass index-for-age: Methods and development. Geneva: World Health Organization; 2006.
McCoy DC, Zuilkowski SS, Fink G. Poverty, Physical Stature, and Cognitive Skills: Mechanisms Underlying Children's School Enrollment in Zambia. Dev Psychol. 2015.
Victora CG, Adair L, Fall C, Hallal PC, Martorell R, Richter L, et al. Maternal and child undernutrition: consequences for adult health and human capital. The Lancet. 2008;371(9609):340-57.
Victora CG, Onis Md, Hallal PC, Blössner M, Shrimpton R. Worldwide timing of growth faltering: revisiting implications for interventions. Pediatrics. 2010;125(3):e473-80.
Fink G, Rockers PC. Childhood growth, schooling, and cognitive development: further evidence from the Young Lives study. Am J Clin Nutr. 2014;100(1):182-8.
Adair LS, Fall CHD, Osmond C, Stein AD, Martorell R, Ramirez-Zea M, et al. Associations of linear growth and relative weight gain during early life with adult health and human capital in countries of low and middle income: findings from five birth cohort studies. Lancet. 2013.
Daniels M, Adair L. Growth in young Filipino children predicts schooling trajectories through high school. J Nutr. 2004;134:1439-46.
Victora CG, Adair L, Fall C, Hallal PC, Martorell R, Richter L, et al. Maternal and child undernutrition: consequences for adult health and human capital. Lancet Infectious Diseases. 2008;371(9609):340-57.
Cutler D, Lleras-Muney A. Education and health: evaluating theories and evidence. In: Schoeni R, House J, Kaplan G, Pollack H, editors. Making Americans healthier: social and economic policy as health policy. New York: Russell Sage Foundation; 2008. p. 29-60.
Deaton A. Income, aging, health and wellbeing around the world: Evidence from the Gallup World Poll. mimeo: http://wwwprincetonedu/~deaton/papershtml. 2007.
Dewey KG, Begum K. Long-term consequences of stunting in early life. Maternal & child nutrition. 2011;7 Suppl 3:5-18.
Black RE, Victora CG, Walker SP, Bhutta ZA, Christian P, de Onis M, et al. Maternal and child undernutrition and overweight in low-income and middle-income countries. Lancet. 2013;382(9890):427-51.
Bhutta ZA, Das JK, Rizvi A, Gaffey MF, Walker N, Horton S, et al. Evidence-based interventions for improvement of maternal and child nutrition: what can be done and at what cost? The Lancet. 2013;382(9890):452-77.
de Onis M, Wijnhoven TM, Onyango AW. Worldwide practices in child growth monitoring. The Journal of pediatrics. 2004;144(4):461-5.
Fink G, Levenson R, Tembo S, Rockers PC. Home- and community-based growth monitoring to reduce early life growth faltering: an open-label, cluster-randomized controlled trial. Am J Clin Nutr. 2017;106(4):1070-7.
Ashworth A, Shrimpton R, Jamil K. Growth monitoring and promotion: review of evidence of impact. Maternal & child nutrition. 2008;4:86-117.
Bryce J, Coitinho D, Darnton-Hill I, Pelletier D, Pinstrup-Andersen P. Maternal and child undernutrition: effective action at national level. The Lancet. 2008;371(9611):510-26.
Mangasaryan N, Arabi M, Schultink W. Revisiting the concept of growth monitoring and its possible role in community-based nutrition programs. Food and nutrition bulletin. 2011;32(1):42-53.
Kim SS, Nguyen PH, Tran LM, Alayon S, Menon P, Frongillo EA. Different Combinations of Behavior Change Interventions and Frequencies of Interpersonal Contacts Are Associated with Infant and Young Child Feeding Practices in Bangladesh, Ethiopia, and Vietnam. Curr Dev Nutr. 2020;4(2):nzz140.
Locks LM, Dahal P, Pokharel R, Joshi N, Paudyal N, Whitehead RD, Jr, et al. Infant and Young Child Feeding (IYCF) Practices Improved in 2 Districts in Nepal during the Scale-Up of an Integrated IYCF and Micronutrient Powder Program. Curr Dev Nutr. 2018;2(6).
Dewey KG. The challenge of meeting nutrient needs of infants and young children during the period of complementary feeding: an evolutionary perspective. The Journal of nutrition. 2013;143(12):2050-4.
Zambia CSO & Measure DHS. Zambia Demographic and Health Survey 2018. Lusaka: Measure DHS; 2019.
Dewey KG, Stewart CP, Wessells KR, Prado EL, Arnold CD. Small-quantity lipid-based nutrient supplements for the prevention of child malnutrition and promotion of healthy development: overview of individual participant data meta-analysis and programmatic implications. The American journal of clinical nutrition. 2021;114(Supplement_1):3S-14S.
Dewey KG, Wessells KR, Arnold CD, Prado EL, Abbeddou S, Adu-Afarwuah S, et al. Characteristics that modify the effect of small-quantity lipid-based nutrient supplementation on child growth: an individual participant data meta-analysis of randomized controlled trials. The American journal of clinical nutrition. 2021;114(Supplement_1):15S-42S.
Dewey KG, Arnold CD, Wessells KR, Prado EL, Abbeddou S, Adu-Afarwuah S, et al. Preventive small-quantity lipid-based nutrient supplements reduce severe wasting and severe stunting among young children: an individual participant data meta-analysis of randomized controlled trials. The American journal of clinical nutrition. 2022;116(5):1314-33.
Wessells KR, Arnold CD, Stewart CP, Prado EL, Abbeddou S, Adu-Afarwuah S, et al. Characteristics that modify the effect of small-quantity lipid-based nutrient supplementation on child anemia and micronutrient status: an individual participant data meta-analysis of randomized controlled trials. The American journal of clinical nutrition. 2021;114(Supplement_1):68S-94S.
Prado EL, Arnold CD, Wessells KR, Stewart CP, Abbeddou S, Adu-Afarwuah S, et al. Small-quantity lipid-based nutrient supplements for children age 6–24 months: a systematic review and individual participant data meta-analysis of effects on developmental outcomes and effect modifiers. The American journal of clinical nutrition. 2021;114(Supplement_1):43S-67S.
Heidkamp RA, Piwoz E, Gillespie S, Keats EC, D'Alimonte MR, Menon P, et al. Mobilising evidence, data, and resources to achieve global maternal and child undernutrition targets and the Sustainable Development Goals: an agenda for action. The Lancet. 2021;397(10282):1400-18.
Addo OY, Tripp K, Nanama S, Albert B, Sandalinas F, Nanema A, et al. An Integrated Infant and Young Child Feeding and Small-Quantity Lipid-based Nutrient Supplementation Program Is Associated with Improved Gross Motor and Communication Scores of Children 6-18 Months in the Democratic Republic of Congo. The Journal of pediatrics. 2020;222:154-63.
Addo OY, Locks LM, Jefferds ME, Nanama S, Albert B, Sandalinas F, et al. Combined infant and young child feeding with small-quantity lipid-based nutrient supplementation is associated with a reduction in anemia but no changes in anthropometric status of young children from Katanga Province of the Democratic Republic of Congo: a quasi-experimental effectiveness study. Am J Clin Nutr. 2020;112(3):683-94.
Tickell KD, Atlas HE, Walson JL. Environmental enteric dysfunction: a review of potential mechanisms, consequences and management strategies. BMC medicine. 2019;17(1):181.
Gough EK, Moulton LH, Mutasa K, Ntozini R, Stoltzfus RJ, Majo FD, et al. Effects of improved water, sanitation, and hygiene and improved complementary feeding on environmental enteric dysfunction in children in rural Zimbabwe: A cluster-randomized controlled trial. PLoS neglected tropical diseases. 2020;14(2):e0007963.
Liu Z, Ashorn U, Chingwanda C, Maleta K, Hallamaa L, Matchado A, et al. Provision of small-quantity lipid-based nutrient supplements does not improve intestinal health among rural Malawian children. Maternal & child nutrition. 2022;18(3):e13331.
Lin A, Ali S, Arnold BF, Rahman MZ, Alauddin M, Grembi J, et al. Effects of Water, Sanitation, Handwashing, and Nutritional Interventions on Environmental Enteric Dysfunction in Young Children: A Cluster-randomized, Controlled Trial in Rural Bangladesh. Clinical infectious diseases : an official publication of the Infectious Diseases Society of America. 2020;70(5):738-47.
Kamng'ona AW, Young R, Arnold CD, Patson N, Jorgensen JM, Kortekangas E, et al. Provision of Lipid-Based Nutrient Supplements to Mothers During Pregnancy and 6 Months Postpartum and to Their Infants from 6 to 18 Months Promotes Infant Gut Microbiota Diversity at 18 Months of Age but Not Microbiota Maturation in a Rural Malawian Setting: Secondary Outcomes of a Randomized Trial. J Nutr. 2020;150(4):918-28.
Blanton LV, Charbonneau MR, Salih T, Barratt MJ, Venkatesh S, Ilkaveya O, et al. Gut bacteria that prevent growth impairments transmitted by microbiota from malnourished children. Science. 2016;351(6275).
Subramanian S, Huq S, Yatsunenko T, Haque R, Mahfuz M, Alam MA, et al. Persistent gut microbiota immaturity in malnourished Bangladeshi children. Nature. 2014;510(7505):417-21.
Mostafa I, Nahar NN, Islam MM, Huq S, Mustafa M, Barratt M, et al. Proof-of-concept study of the efficacy of a microbiota-directed complementary food formulation (MDCF) for treating moderate acute malnutrition. BMC public health. 2020;20(1):242.
Chen RY, Mostafa I, Hibberd MC, Das S, Mahfuz M, Naila NN, et al. A Microbiota-Directed Food Intervention for Undernourished Children. The New England journal of medicine. 2021;384(16):1517-28.
Wilson AS, Koller KR, Ramaboli MC, Nesengani LT, Ocvirk S, Chen C, et al. Diet and the Human Gut Microbiome: An International Review. Dig Dis Sci. 2020;65(3):723-40.
Brewster R, Tamburini FB, Asiimwe E, Oduaran O, Hazelhurst S, Bhatt AS. Surveying Gut Microbiome Research in Africans: Toward Improved Diversity and Representation. Trends Microbiol. 2019;27(10):824-35.
Smith MI, Yatsunenko T, Manary MJ, Trehan I, Mkakosya R, Cheng J, et al. Gut microbiomes of Malawian twin pairs discordant for kwashiorkor. Science. 2013;339(6119):548-54.
Kamng'ona AW, Young R, Arnold CD, Kortekangas E, Patson N, Jorgensen JM, et al. The association of gut microbiota characteristics in Malawian infants with growth and inflammation. Scientific reports. 2019;9(1):12893.
Aakko J, Grześkowiak Ł, Asukas T, Päivänsäde E, Lehto KM, Fan YM, et al. Lipid-based Nutrient Supplements Do Not Affect Gut Bifidobacterium Microbiota in Malawian Infants: A Randomized Trial. J Pediatr Gastroenterol Nutr. 2017;64(4):610-5.
Hughes RL, Arnold CD, Young RR, Ashorn P, Maleta K, Fan YM, et al. Infant gut microbiota characteristics generally do not modify effects of lipid-based nutrient supplementation on growth or inflammation: secondary analysis of a randomized controlled trial in Malawi. Scientific reports. 2020;10(1):14861.
Hoffman DJ, Campos-Ponce M, Taddei CR, Doak CM. Microbiome, growth retardation and metabolism: are they related? Ann Hum Biol. 2017;44(3):201-7.
Million M, Tidjani Alou M, Khelaifia S, Bachar D, Lagier JC, Dione N, et al. Increased Gut Redox and Depletion of Anaerobic and Methanogenic Prokaryotes in Severe Acute Malnutrition. Scientific reports. 2016;6:26051.
Ghosh TS, Gupta SS, Bhattacharya T, Yadav D, Barik A, Chowdhury A, et al. Gut microbiomes of Indian children of varying nutritional status. PloS one. 2014;9(4):e95547.
Yan J, Herzog JW, Tsang K, Brennan CA, Bower MA, Garrett WS, et al. Gut microbiota induce IGF-1 and promote bone formation and growth. Proc Natl Acad Sci U S A. 2016;113(47):E7554-e63.
Macpherson AJ, de Agüero MG, Ganal-Vonarburg SC. How nutrition and the maternal microbiota shape the neonatal immune system. Nat Rev Immunol. 2017;17(8):508-17.
Maynard CL, Elson CO, Hatton RD, Weaver CT. Reciprocal interactions of the intestinal microbiota and immune system. Nature. 2012;489(7415):231-41.
Huda MN, Lewis Z, Kalanetra KM, Rashid M, Ahmad SM, Raqib R, et al. Stool microbiota and vaccine responses of infants. Pediatrics. 2014;134(2):e362-72.
Robertson RC, Manges AR, Finlay BB, Prendergast AJ. The Human Microbiome and Child Growth - First 1000 Days and Beyond. Trends Microbiol. 2019;27(2):131-47.
WHO. Anthro Software for assessing growth and development of the world's children. Geneva: WHO; 2006.

No competing interests reported.

Download PDF

Version 1

posted

You are reading this latest preprint version

Study Protocol: The Impact of Growth Charts and Nutritional Supplements on Child Growth in Zambia (ZamCharts): A Cluster Randomized Controlled Trial

Status:

Version 1

Abstract

Background

Methods/design

Primary endpoint

Interim analyses

Deviation(s) from the original statistical plan

Handling of data

Discussion

Abbreviations

Declarations

References

Additional Declarations

Supplementary Files

Status:

Version 1