Trial to Establish Causal Linkage Between Mycotoxin Exposure and Child Stunting
Phase: NA
Conditions: Aflatoxin Ingestion
Sponsor: Cornell University

1 
 
Research Protocol 
Official Tittle: Trial to establish causal linkage between mycotoxin exposure and child stunting 
Date of last Revision: September 18, 2019 
 
 
 

2 
 
Project Summary 
In 2018, an estimated 150.8 million children under 5 were stunted, with greatest burden in 
Southern Asia and Eastern Africa (1).  While the number of stunted children has fallen globally, 
it continues to increase only in Africa.  Stunting has been estimated to contribute to 14-17% of 
child deaths under 5 years of age and is a risk factor for poor cognitive and motor development 
and educational outcomes (2-6).  Inadequate dietary intake and disease are the immediate 
causes of undernutrition and stunting, along with multiple proximate and distal factors, 
including access to health care and maternal education (7). 
 
Improving infant diets through complementary feeding interventions has been shown to only 
modestly reduce stunting, improving length-for-age Z scores by 0.10, thus additional factors are 
likely contributing to the burden of stunting (8).  Multiple observational studies show an 
association between fetal and post-natal aflatoxin exposure and linear growth (9-11).  However, 
the effects of confounding factors such as socio-economic status, food insecurity and nutrient 
deficiencies due to monotonous diets have not been ruled out.  This trial will quantify the 
causal role of infant aflatoxin ingestion on post-natal growth by performing a cluster 
randomized trial in children 6-18 months of age in the Dodoma Region of Tanzania. 
 
All health facilities in one district in Dodoma will be randomized to the control or intervention 
arm.  Infants will be recruited into the study over one year to account for seasonal variation in 
AF exposure.  Both arms will receive infant and young child feeding education, a thermos flask 
and plastic measuring scoops.  The intervention arm will receive a low-aflatoxin pre-blended 
porridge flour containing maize and groundnut (ratio 4:1 respectively) and low-aflatoxin 
groundnut flour, whereas in the control arm the same porridge mix will be promoted through 
education, but acquired by the household.  The primary outcome is length-for-age Z-score at 18 
months. 
 
 

3 
 
I. General Information 
Project title: Trial to establish causal linkage between mycotoxin exposure and child stunting 
Funded by: The Bill and Melinda Gates Foundation (BMGF) 
 
Principle Investigator: Rebecca J. Stoltzfus, Ph.D. 
President 
Goshen College 
1700 South Main Street 
Goshen, Indiana 46526 
(574) 535-7180 
rstoltzfus@goshen.edu 
 
Co-PI: Rebecca J. Nelson, Ph.D. 
Professor 
Cornell University 
303A Plant Science 
Ithaca, New York 14853 
(607) 254-7475 
Rjn7@cornell.edu 
 
Research Partner in Tanzania: Nelson Mandela African Institute of Science and Technology 
Neema Kassim, PI 
Tengeru 
P. O. Box 447 
Arusha, TANZANIA 
Website:  www.nm-aist.ac.tz 
Direct Line: +255 272555070 
Mobile Phone: +255 682 541 996 
Fax: +255 272555071 
E-mail: mmt@nm-aist.ac.tz 
 
 

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II. Rationale and Background Information 
Mycotoxins are naturally occurring secondary metabolites produced by fungi that frequently 
colonize crops.  There are 300-400 identified mycotoxins, 12 of which are believed to be 
predominantly contribute to animal and human mycotoxicosis.  Of these, aflatoxin (AF) and 
fumonisin (FUM) are of particular concern.  AF is a carcinogen, known to cause hepatocellular 
carcinoma (HCC, liver cancer) and synergize with the hepatitis B virus to increase the risk of HCC 
30-fold, compared with either exposure alone (12, 13).  Consumption of FUM has been 
associated with renal tumors, esophageal cancer and increased risk for neural tube defects (14).  
AF is produced by Aspergillus mold strains and is commonly found in staple foods such as maize 
and groundnut.  FUM is produced by Fusarium mold strains and is commonly and 
predominantly found in maize. 
Approximately 0.5 billion people, mainly living in developing countries, are at risk of being 
chronically exposed to dietary AF at high levels (15).  Exposure to AF in low-income populations, 
especially those in rural sub-Saharan Africa, is particularly problematic because the diet is 
monotonous, largely based on highly AF-prone crops, grown and stored under conditions that 
predispose them to contamination.  While the consequences of intermittent outbreaks of 
extremely high levels of AF consumption and acute toxicosis are well understood, the effects of 
chronic AF exposure at moderate to high levels, especially during critical periods of fetal and 
early-life development, are not.  Exposure to both these mycotoxins is of concern, however 
current evidence more strongly implicates AF as the primary mycotoxin of concern for stunting.  
This trial will therefore focus on AF but we will assess FUM contamination and AF/FUM co-
exposures throughout the course of the trial.  
Two critical knowledge gaps hinder our understanding of the effects of AF and motivation to 
mitigate AF from food supplies in sub-Saharan Africa.  These include lack of causal evidence for 
the effect of AF on post-natal growth and lack of context-adapted strategies to mitigate AF 
consumption in low-resource settings.   
1. Lack of causal evidence for the effect of aflatoxins on post-natal growth: The weight of 
evidence linking aflatoxin exposure to intrauterine growth restriction and child stunting has 
increased over the years but is far from definitive, coming from animal or observational studies.  
The effects of confounding factors such as socio-economic status, food insecurity and nutrient 
deficiencies due to monotonous maize-based diet have not been ruled out in the evidence to 
date.  Serum aflatoxin albumin (AF-alb) concentration was associated with stunting among 
young children in rural Benin and Togo, as demonstrated by significant dose-response 
relationship with length-for-age (LAZ) and weight-for-age Z scores (WAZ) (9).  In a subsequent 
longitudinal study in rural Benin, infants in the highest quartile of AF- alb, compared to the 
lowest quartile were 1.7 cm shorter after 8 months (10).  A longitudinal survey of maternal AF 
exposure during pregnancy and subsequent infant growth from birth to 52 weeks conducted in 
The Gambia, also revealed a highly significant inverse relationship between maternal AF 
exposure and infant growth (11).  Early infant exposure (prior to week 16) additionally 
adversely contributed to the effects of maternal AF exposure on growth.   
In an observational study in Tanzania the effects of AF and FUM exposure on attained LAZ at 12 
months was assessed (16).  Urinary FUM was negatively associated with LAZ (p=0.014), with 

5 
 
children in the highest quartile of exposure 1.8 cm shorter than children in the lowest quartile 
of exposure; the negative association between AF-alb and LAZ did not reach statistical 
significance, however AF-alb levels were lower compared to studies in West Africa described 
above.  The MAL-ED study in Nepal also did not find an association between AF consumption 
and stunting, but it too was conducted in an area of lower exposure and lower prevalence of 
stunting compared to West Africa (17).  
The MAICE Trial in Kenya was the first RCT to assess an intervention to reduce AF consumption 
on child growth through household level sorting and community stocking interventions to 
reduce AF consumption (18).  There was not an improvement in LAZ at 18 months (endpoint) in 
the intervention group, despite a 27% decrease in AF-lys (19).  However, there was a significant 
difference in LAZ at midpoint, even though AF-lys did not differ between groups at midpoint.  
However, taking into account the relatively high loss to follow-up, incomplete data and the low 
percent of AF-lys samples analyzed (65%), these results are difficult to interpret. 
2. Lack of context-adapted strategies to mitigate aflatoxin.  Mycotoxin contamination of foods 
in low-input and fragmented food systems is a complex problem most effectively managed 
through multiple mitigation strategies(20).  Yet there are a limited number of effective 
mitigation interventions that are practical and feasible for small-scale rural farmers and 
communities, where populations are most at risk for mycotoxin exposure (14, 21).  A recent 
IARC Working Group concluded that there are four general intervention strategies considered 
to have sufficient evidence for implementation. Only two of these strategies are relevant to the 
sub-Saharan rural context: 1) sorting and 2) a package of post-harvest storage and handling 
practices (22).  
 
There is much more global experience with these two intervention strategies for groundnuts 
than maize.  Sorting of groundnuts to remove AF-contaminated kernels is simpler than sorting 
maize because visual and tactile inspection of pods is a good indicator of food safety: if the pod 
is average size and intact, the risk of AF is low (23).  By contrast, internal colonization of maize 
kernels can lead to cryptic toxicity: healthy-looking kernels can carry substantial levels of both 
AF and FUM, requiring additional techniques to sort contaminated grain.  Therefore, innovation 
is urgently needed to develop successful maize sorting techniques relevant to low-input foods 
systems and could be an evidence-based recommendation to policy makers, complimenting the 
results of our trial. 
 
 

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III. References 
1.  United Nations Children’s Fund (UNICEF) WHO, International  Bank for Reconstruction and 
Development/The World Bank. Levels and trends in child malnutrition: key findings of the 2018 
Edition of the Joint Child Malnutrition Estimates. Geneva: World Health Organization; 2018. 
2.  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. 
3.  Black RE AL, Bhutta ZA, et al, for the Maternal and Child Undernutrition Group. Maternal and 
child undernutrition: global and regional exposures and health consequences. Lancet. 
2008;371:243–60. 
4.  Walker SP, Wachs TD, Grantham-McGregor S, Black MM, Nelson CA, Huffman SL, et al. 
Inequality in early childhood: risk and protective factors for early child development. Lancet. 
2011;378(9799):1325-38. 
5.  Grantham-McGregor S, Cheung YB, Cueto S, Glewwe P, Richter L, Strupp B, et al. 
Developmental potential in the first 5 years for children in developing countries. Lancet. 
2007;369(9555):60-70. 
6.  Adair LS, Fall CH, 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;382(9891):525-34. 
7.  UNICEF. Conceptual Framework of Undernutrition. 1990. 
8.  Panjwani A, Heidkamp R. Complementary Feeding Interventions Have a Small but Significant 
Impact on Linear and Ponderal Growth of Children in Low- and Middle-Income Countries: A 
Systematic Review and Meta-Analysis. J Nutr. 2017;147(11):2169S-78S. 
9.  Gong YY, Cardwell K, Hounsa A, Egal S, Turner PC, Hall AJ, et al. Dietary aflatoxin exposure 
and impaired growth in young children from Benin and Togo: cross sectional study. BMJ. 
2002;325(7354):20-1. 
10.  Gong Y, Hounsa A, Egal S, Turner PC, Sutcliffe AE, Hall AJ, et al. Postweaning exposure to 
aflatoxin results in impaired child growth: a longitudinal study in Benin, West Africa. Environ 
Health Perspect. 2004;112(13):1334-8. 
11.  Turner PC, Collinson AC, Cheung YB, Gong Y, Hall AJ, Prentice AM, et al. Aflatoxin exposure 
in utero causes growth faltering in Gambian infants. Int J Epidemiol. 2007;36(5):1119-25. 
12.  National Toxicology Program (U.S.). Report on carcinogens. Monograph on. Research 
Triangle Park, NC: National Toxicology Program, U.S. Department of Health and Human 
Services,; 2013. Available from: http://ntp.niehs.nih.gov/pubhealth/roc/candidates/index.html. 
13.  Groopman JD, Kensler TW. Role of metabolism and viruses in aflatoxin-induced liver cancer. 
Toxicol Appl Pharmacol. 2005;206(2):131-7. 
14.  Wu F, Groopman JD, Pestka JJ. Public health impacts of foodborne mycotoxins. Annu Rev 
Food Sci Technol. 2014;5:351-72. 
15.  Williams JH, Phillips TD, Jolly PE, Stiles JK, Jolly CM, Aggarwal D. Human aflatoxicosis in 
developing countries: a review of toxicology, exposure, potential health consequences, and 
interventions. Am J Clin Nutr. 2004;80(5):1106-22. 

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16.  Shirima CP, Kimanya ME, Routledge MN, Srey C, Kinabo JL, Humpf HU, et al. A prospective 
study of growth and biomarkers of exposure to aflatoxin and fumonisin during early childhood 
in Tanzania. Environ Health Perspect. 2015;123(2):173-8. 
17.  Mitchell NJ, Hsu HH, Chandyo RK, Shrestha B, Bodhidatta L, Tu YK, et al. Aflatoxin exposure 
during the first 36 months of life was not associated with impaired growth in Nepalese children: 
An extension of the MAL-ED study. PLoS One. 2017;12(2):e0172124. 
18.  Hoffmann V, Jones K, Leroy J. Mitigating aflatoxin exposure to improve child growth in 
Eastern Kenya: study protocol for a randomized controlled trial. Trials. 2015;16:552. 
19.  Hoffmann V, Jones K, Leroy JL. The impact of reducing dietary aflatoxin exposure on child 
linear growth: a cluster randomised controlled trial in Kenya. BMJ Glob Health. 
2018;3(6):e000983. 
20.  Khlangwiset P, Wu F. Costs and efficacy of public health interventions to reduce aflatoxin-
induced human disease. Food Addit Contam Part A Chem Anal Control Expo Risk Assess. 
2010;27(7):998-1014. 
21.  Pitt J, Wild C, Baan R, Gelderblom W, Miller JD, Riley R, et al., editors. Improving public 
health through mycotoxin control. Lyon: IARC; 2012. 
22.  Wild CP, Miller DJ, Groopman JD, editors. Mycotoxin control in low- and middle-income 
countries. Lyon: International Agency for Research on Cancer; 2015. 
23.  Whitaker T. Estimating aflatoxin in farmers' stock peanut lots by measuring aflatoxin in 
various peanut-grade components. Journal of AOAC International. 1998;81(1):61-7. 
 
 
 

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IV. Study Goals and Objectives 
The goal of this research is to provide experimental evidence about the effect of aflatoxin 
ingestion on linear growth in infants and young children between 6 and 18 months of age. 
 
Primary objective:  To measure the effect of a reduced-AF diet on length-for-age Z scores at 18 
months in central Tanzania. 
 
Secondary objectives:  
1. To determine the effect of an intervention to reduce AF on LAZ scores at 12 months and 
stunting at 12 and 18 months 
2. To determine the effect of an intervention to reduce AF on weight for age Z scores 
(WAZ) at 12 months and 18 months and underweight at 12 and 18 months 
3. To examine the effect of an intervention to reduce AF on mid-upper arm circumference 
and head circumference at 12 and 18 months 
4. To assess the effect of an intervention to reduce AF on the blood biomarker AF-alb at 12 
and 18 months 
5. To assess the effect of an intervention to reduce AF on the urinary biomarker AFM1 in a 
cohort of 600 infants at 9, 12, 15 and 18 months 
6. To assess the effect of an intervention to reduce AF on the urinary biomarker FUM in a 
cohort of 600 infants at 9, 12, 15 and 18 months 
7. To describe the relationship between recent consumption AF in food and AFM1 in urine 
in a cohort of infants at 12 months 
8. To determine the relationship between FUM in food and urinary FUM biomarkers in a 
cohort of infants at 12 months 
9. To determine how demographics, geography and climate modify spatial measures of 
food consumption and food contamination with AF and FUM 
10. To determine how pre- and post-harvest practices influence contamination of food with 
AF and FUM 
11. To use blood and urinary biomarkers to hypothesize mechanisms of AF-induced stunting 
at 12 and 18 months, including a threshold of exposure 
12. To identify early life food and cultural behaviors that may influence food choices and AF 
exposure 
13. To investigate role AF and FUM co-exposure on stunting, LAZ, underweight and WAZ at 
12 and 18 months 
14. To determine the effect of an intervention to reduce AF on inflammatory markers (CRP 
and TNFa) at 18 months of age 
 
V. Study Design 
This study is a cluster randomized design.  The trial is designed to test the hypothesis that 
provision of a complementary food porridge flour and separate groundnut flour, both with very 
low levels of aflatoxin (TZ regulations for complementary foods is AF≤5ppb), will be associated 
with better linear growth in infants compared to the consumption of complementary porridge  
and foods made with similar ingredients and groundnut flour, but acquired by the household. 

9 
 
We have designed an IYCF educational intervention to improve IYCF practices and infant diets 
for all trial participants, which will take place in Kongwa District, Dodoma Region, an area with 
low dietary diversity and high rates of food insecurity (1, 2). The experimental group will be 
provided with infant feeding education and provision of pre-blended porridge flour made of 
maize and groundnut flour (ratio 4:1).  They will also be provided separate groundnut flour 
because infants eat groundnut flour in family foods.  The control group will be provided with 
the same infant feeding education and promotion of the same pre-blended porridge flour and 
groundnut flours, but these will be acquired by the household.  The control group will receive 
gifts related to baby care, including skin lotion and diaper covers. Both groups will be given a 
thermos flask to safely store the porridge and a plastic scoop to measure porridge flour. 
Inclusion and exclusion criteria 
Inclusion criteria: 
1. Babies >6 weeks old and <5 months old, who seek Expanded Program on 
Immunization (EPI) from a randomized health facility and reside in Kongwa District 
 
Exclusion criteria, assessed at recruitment and again at the 6-month visit: 
1. Babies with disabilities that preclude normal feeding and swallowing 
2. Refusal to consent to assigned intervention 
3. An infant who has shown signs of a potential groundnut allergy (assessed the first 
time mother reports groundnut consumption) 
4. An infant who is a twin 
5. If the mother plans to travel for more than 2 months at or after the randomized 
intervention begins 
6. If the mother is below 16 years of age 
 
VI. Methodology 
In the intervention group, the study will provide low-aflatoxin infant porridge flour.  In the 
control group we will recommend mothers feed a porridge made from similar flours. 
Complementary feeding porridge flours are culturally familiar in Tanzania (called lishe) and 
mothers’ awareness of them is high. We will educate and advise all mothers to provide porridge 
to their infants, with a composition, consistency and frequency that is consistent with World 
Health Organization infant feeding best practices. 
Critical to causal inference is the intervention’s ability to create a contrast of AF consumption 
between the control and intervention groups, without creating differential macro- or micro-
nutrient intake or differences in feeding and care practices that could affect stunting between 
arms.  To reduce the risk of introducing these biases, we designed the intervention to include: 
1) education to improve infant feeding and care practices, using Tanzania Food and Nutrition 
Center’s materials, and 2) behavior change communication on the use of blended infant 
porridge (Table 1). 

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Table 1.  IYCF Intervention Activities 
Intervention Group 
Control Group 
Infant feeding education: 
● Breastfeeding 
● Dietary diversity 
● Feeding frequency 
● Hand washing 
Infant feeding education: 
● Breastfeeding 
● Dietary diversity 
● Feeding frequency 
● Hand washing 
Behavior change communication on use on 
use of lishe 
● Timing of introduction, frequency of 
feeding, density and composition of 
lishe 
● Provision of 4:1 ratio of maize meal to 
groundnut powder 
● GN flour 
Behavior change communication on use of 
lishe 
● Timing of introduction, frequency of 
feeding, density and composition of 
lishe 
● Promotion of 4:1 ratio of maize meal 
to groundnut powder  
● GN flour 
 
All participants will be asked to respond to a survey at four time points.  The first survey, the 
recruitment survey, will take place when the index infant is between 1.5-4 months of age.  The 
second survey will take place at 6 months of age, the third at 12 months and the fourth and 
final survey at 18 months of age. We will also include a cohort of 600 infants (300 per arm) who 
will be visited at 9 and 15 months, in addition to the standard visits.  Therefore, children will be 
in the study from the time they are recruited, between 1.5-4 months, to the time they turn 18 
months of age.  However, the randomized intervention of providing pre-blended porridge flour 
and groundnut flour will start from 6 months of age onward, so as not to disrupt exclusive 
breastfeeding. 
The surveys will assess socio, demographic and economics of the household, infant feeding 
practices, access to health-care, food procurement practices, and water, sanitation and hygiene 
of the household and community health worker contact (Table 2).   At the 6, 12, and 18 month 
survey points we will perform anthropometric assessment of weight, height, middle upper arm 
circumference (MUAC) and head circumference in all infants.  Surveys and anthropometric data 
collection will be performed by data collectors who are hired and trained by the project  
We will collect blood at three time points (6, 12 and 18 months) in all infants in the study.  We 
will collect urine only from the cohort of 600 infants at five time points (6, 9, 12, 15 and 18 
months).  A certified nurse or laboratory technician will be hired to perform urine and blood 
collection, consistent with Tanzanian regulations and hired in collaboration with the Kongwa 
District Medical Officer.  In the full cohort we will collect infant food samples and assess 
adherence to the intervention and porridge-specific feeding practices.  We will perform 24-hour 
recalls in 200 cohort household households at 12 months. 
In the lab, samples will be cataloged, prepared and analyzed by lab technicians.  Disposal of 
biohazard material and sharps will be performed according to Tanzanian regulations and in 
partnership with the Kongwa District Hospital and NM-AIST, where research labs are already 
established.   

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Table 2 - Summary of Interventions, Measurement and Surveys by Randomized Treatment Arm  
 
Control Arm: Standard of Care 
Infant feeding and lishe education only+ 
distribution of lotion and baby gifts 
Intervention Arm: Lishe Provision 
Infant feeding and lishe education+ distribution 
of AF-free lishe 
Age in 
months 
Measurement 
Surveys 
Measurement 
Surveys 
42 day (6 
week) EPI 
visit up to 
4 months 
None 
(recruitment) 
Informed Consent 
Recruitment survey 
(including screening, infant 
health, socio demographic 
modules and antenatal care) 
None 
(recruitment) 
Informed Consent 
Recruitment survey (including 
screening, infant health, socio 
demographic modules and 
antenatal care) 
6 
AF-alb 
AFM1*, FUM* 
Anthropometry 
(weight, height, 
MUAC, head 
circumference) 
Baseline survey: food 
security, health and WASH, 
SES and assets, 
livelihood/shock, and 
intervention related 
questions, and health seeking 
behavior 
WHO IYCF indicators survey 
Lishe-specific feeding module 
AF-alb 
AFM1*, FUM* 
Anthropometry 
(weight, height, 
MUAC, head 
circumference) 
Baseline survey: food security, 
health and WASH, SES and 
assets, livelihood/shock, and 
intervention related questions 
and health seeking behavior 
WHO IYCF indicators survey 
Lishe-specific feeding module 
9* 
AFM1 
WHO IYCF indicators survey 
Lishe-specific feeding module 
AFM1 
WHO IYCF indicators survey 
Lishe-specific feeding module; 
Adherence to feeding AF-free 
lishe module 
12 
AF-alb 
AFM1* 
Anthropometry 
(weight, height, 
MUAC, head 
circumference) 
Midpoint survey (select 
matching modules to 
baseline) 
WHO IYCF indicators survey 
Lishe-specific feeding module 
Food testing* 
24-hour recalls (100 HH/arm) 
AF-alb 
AFM1* 
Anthropometry 
(weight, height, 
MUAC, head 
circumference) 
Midpoint survey (select 
matching modules to 
baseline) 
WHO IYCF indicators survey 
Lishe-specific feeding module 
Food testing* 
24-hour recalls (100 HH/arm) 
Adherence to feeding AF-free 
lishe module 
15* 
AFM1 
WHO IYCF indicators survey 
Lishe-specific feeding module 
AFM1 
WHO IYCF indicators survey 
Lishe-specific feeding module 
Adherence to feeding AF-free 
lishe module 
18 
AF-alb 
Multiple 
mycotoxin 
panel,  FUM and 
AFM1* 
Anthropometry 
(weight, height, 
MUAC, head 
circumference) 
Final survey (select matching 
modules to midpoint and 
baseline) 
WHO IYCF indicators survey 
Lishe-specific feeding module 
AF-alb 
Multiple 
mycotoxin 
panel or FUM 
and AFM1* 
Anthropometry 
(weight, height, 
MUAC, head 
circumference) 
Final survey (select matching 
modules to midpoint and 
baseline) 
WHO IYCF indicators survey 
Lishe-specific feeding module 
Adherence to feeding AF-free 
lishe module 
Notes: * indicates visit or measurement for longitudinal cohort only (n=600) 
 
 

12 
 
Randomization Protocol 
The unit of randomization is government-run health facilities (health centers, dispensaries and 
hospital, 52 clusters in total) in the Kongwa District.  Mothers and infants will be recruited into 
the trial based on 42 day EPI visit attendance, which has very high (>95%) coverage in Kongwa 
District.  We will recruitment infants for one complete calendar year to capture variability in 
exposure by season.   
 
The health facilities in Kongwa serve populations of different sizes, such that the annual 
attendance between August 2017 and July 2018 for the 6-week vaccination visit at the 50 
health facilities operating during that time ranged from 14 to 427 visits.  In 44 health facilities, 
more than 60 babies attend the 6-week vaccination visit in one year, and in 48 facilities more 
than 40 attend the 6-week visit annually.  Only two have less than 30 children attend this visit 
annually and two new dispensaries have opened in 2019.  We will randomize all 52 health 
facilities to capture full representation of the district. 
 
We want to ensure close balance between the two groups on two important characteristics:  
• Altitude, which is associated with mycotoxin risk in the altitude range of the district. 
• Health facility size/attendance, which is a proxy for population density and access to 
resources such as roads and markets. 
 
To do this, we: 
1. Sorted the health facilities by low v. high altitude. We began by using the cutoff of 1200 
meters. This altitude is near the median for the district, and 1000-1200 meters is 
considered the threshold for drier and colder conditions in which toxin-producing fungi 
are less likely to thrive.   
2. Sorted the health facilities by size within each altitude category, using 6-week 
immunization visit attendance data from the most recent year of data (August 2017-July 
2018). 
3. Grouped health facilities into successive pairs from the top to the bottom of each list.  
We randomly chose half of the pairs within a list.  For the chosen pairs, the first health 
facility in each pair was assigned to the experimental group and the other health facility 
assigned to the control group.  For the pairs not chosen, the assignments will be 
reversed:  the first health facility in each pair was be assigned to the control group and 
the other health facility assigned to the experimental group. 
There is no blinding in this study, as all parties will be able to see what is received by the 
participant – pre-blended flour and groundnut flour or lotion and baby-care gifts. 

13 
 
VII. Safety Considerations 
The safety of the research participants is critical.  Although we do not expect any severe events 
caused from our intervention, we can expect potential non-serious adverse events from blood 
draws.  As required by GCP and the Cornell IRB, we will report all unexpected and adverse 
events in the timeframe required and outlines below (Table 3). 
 

14 
 
Table 3 - Classification and Reporting of Adverse Events 
 
Classification of event 
Example 
Reporting to IRB 
Means of tracking/documenting events 
1 
Attrition 
Drop out and loss to follow-
up 
● 
Mothers drop out of study due to 
displeasure with the study, perceived 
risk, lack of time, etc. 
● 
Higher than expected 20% loss to 
follow up at 6, 9 12, 15 and 18 months 
Not reported to IRB 
Review study data for trends - monthly 
 
Data Collector Weekly Report 
2 
Participant complaints: 
not associated with potential 
for increased risk profile or 
changes to research 
● 
Caregiver complains child has an illness 
unrelated to infant food 
consumption/trial intervention 
(malaria, cough/upper respiratory 
infection, fever, etc.) 
Not reported to IRB 
Review study data for morbidity trends –
monthly 
 
Report of complaint to research team 
member, likely data collector; DC will file a 
report and submit to Field Supervisor 
 
Report of complaint to non-research team 
member (maternal, health facility staff, 
CHW, etc.); Trained to contact Intervention 
Officer or Field Supervisor to report event 
Participant complaints: 
associated with potential for 
increased risk profile or 
changes to research 
● 
Serious event – Hospitalization or 
death from any cause 
● 
Non-serious event - Caregiver 
complains child has diarrhea or other 
illness believe to be associated with 
consumption of provided infant food 
Report serious events 
(death or serious 
injury/illness) within 24 
hours of discovery 
 
Report non-serious 
events within 14 days of 
discovery 
Review study data for morbidity trends –
monthly; Compare incidence between 
groups at 6, 9, 12, 15 and 18 months 
 
Report of complaint to research team 
member, likely data collector; DC will file a 
report and submit to Field Supervisor 
 
Report of complaint to non-research team 
member (maternal, health facility staff, 
CHW, etc.); Trained to contact Intervention 
Officer or Field Supervisor to report event 
 
 

15 
 
3 
Protocol deviations: 
not associated with potential 
for increased risk profile or 
changes to research 
● 
Data collector skips survey section or 
fails to take all measurements 
● 
Project food runs out and is not 
available for participants on schedule 
● 
Lab technician fails to process samples 
according to the SOP 
Not reported to IRB 
Review study data for trends – weekly 
(missing questions, sections, excess refusal 
or DKs, etc.) 
 
DC and lab reports – review for trends 
weekly 
 
Field team meetings 
 
Active supervision of data collectors and lab 
staff 
 
Gift logistician and RCH weekly and monthly 
gift reports 
Protocol deviations: 
associated with potential for 
increased risk profile or 
changes to research 
● 
Breach of confidentiality or data 
privacy (non-serious) 
● 
Urine collection or blood draw that 
does not follow protocol (non-serious) 
Report serious events 
(death or serious 
injury/illness) within 24 
hours of discovery 
 
Report non-serious 
events within 14 days of 
discovery 
DC reports – review for trends weekly 
 
Field team meetings 
 
Active supervision of data collectors and lab 
staff 
 
IT staff QC weekly checks of data system 
4 
Expected or unexpected 
clinical complications: 
not related to any research 
procedures  
● 
Infant is found to have signs of clinical 
malnutrition or severe stunting or 
wasting based on anthropometric 
assessment by data collector 
● 
Infant has signs of severe illness, such 
as rapid, shallow breathing during 
evaluation by data collector 
Not reported to IRB 
 
Reported to caregiver as 
soon as possible and 
referred to health facility 
using referral form 
DC referral report submitted to Field 
Supervisor 
 
Review study data for morbidity trends –
monthly 
 
 

16 
 
5 
Expected serious events: 
related to the research  
● 
None expected 
Report serious events 
(death or serious 
injury/illness) within 24 
hours of discovery 
Report of event to research team member, 
likely data collector; DC will file a report and 
submit to Field Supervisor 
 
Report of complaint to non-research team 
member (maternal, health facility staff, 
CHW, etc.); Trained to contact Intervention 
Officer or Field Supervisor to report event 
Expected non-serious 
events: related to the 
research 
● 
Soreness/bruising from blood draw 
● 
Fainting from blood draw 
● 
Infant crying while being evaluated or 
taking of samples 
Not reported to IRB 
Study data - review for trends monthly 
Unexpected events: 
related to the research  
● 
Severe diarrhea reported by multiple 
mothers receiving project flour, leading 
to hospitalization (serious) 
● 
Chronic diarrhea reported by multiple 
mothers receiving project flour (non-
serious) 
● 
Increase in growth faltering in the 
intervention group compared to 
control group at 12 or 18 months (non-
serious) 
Report serious events 
(death or serious 
injury/illness) within 24 
hours of discovery 
 
Report non-serious 
events within 14 days of 
discovery 
Study data – review for morbidity trends 
monthly; compare morbidity between 
groups monthly; Compare LAZ between 
groups at 12 and 18 months, following 
collection of 6 months of LAZ data 
 
Report of event to research team member, 
likely data collector; DC will file a report and 
submit to Field Supervisor 
 
Report of complaint to non-research team 
member (maternal, health facility staff, 
CHW, etc.); Trained to contact Intervention 
Officer or Field Supervisor to report event 
6 
Unexpected events: 
not related to the research  
● 
Car accident 
● 
Broken limb 
Not reported to IRB 
Report of event to research team member, 
likely data collector; DC will file a report and 
submit to Field Supervisor 
 
Report of complaint to non-research team 
member (maternal, health facility staff, 
CHW, etc.); Trained to contact Intervention 
Officer or Field Supervisor to report event 
 
 

17 
 
7 
Unanticipated problem: 
unexpected, related to the 
research & associated with 
increased risk profile  
N/A (since unanticipated) 
Report serious events 
(death or serious 
injury/illness) within 24 
hours of discovery 
 
Report non-serious 
events within 14 days of 
discovery 
Study data – review for trends monthly 
 
Field team meetings 
 
Report of event to research team member, 
likely data collector; DC will file a report and 
submit to Field Supervisor 
 
Report of complaint to non-research team 
member (maternal, health facility staff, 
CHW, etc.); Trained to contact 
INTERVENTION Officer or Field Supervisor to 
report event 
 
Summary of non-reportable events:  
● 
Participant complaints not associated with potential for increased risk profile or changes to research  
● 
Protocol deviations not associated with potential for increased risk profile or changes to research  
● 
Clinical complications not related to research procedures  
● 
Non-serious expected events that are related to the research  
● 
Unexpected events that not related to the research 
 
All complaints, protocol deviations, events and problems will be documented by the research team member who receives the complaint.  This will likely be the 
data collector, but could also be the Data Collector Supervisor, Data Quality Supervisor, Intervention Officer, Field Supervisor or Lab Supervisor.  All 
documentation of these events will be submitted to the Research and Field Supervisor who will pass them on to N.K. and E.P. 
 
All weekly and monthly reports from the data will be generated by the biostatistician (E.M.) and sent to Neema Kassim, Edna Makule, Erica Phillips, Francis 
Ngure for review 
 

18 
 
VIII. Follow-up 
Participation in the study will end when infants turn 18 months of age.  Following the 18 month 
visit (conducted prior to 19 months), there will be no follow-up unless there is an adverse event 
or abnormal laboratory result (see below) that requires further resolution.  As there are no 
anticipated serious events from this research and few non-serious events, we will evaluate 
these on a case-by-case basis and work with the IRB and local health officials to resolve these 
problems. 
IV. Data Management and Statistical Analysis 
Data Collection, Management and Supervision 
Data will be collected electronically, using hand-held devices (Samsung Galaxy 7, KoBoToolbox 
Platform), with paper copies provided as back up in case of electronic failure.  The primary 
outcome of length will be recorded on the tablet and by hand. 
We will hire up to 22 data collectors at the peak of the trial.  For collection of biological 
samples, hiring of certified nurses will be performed in collaboration with the Kongwa District 
Medical Officer.  For collection of non-biological samples, non-nurses will be considered.  Data 
collectors will be supervised by the Data Collector Supervisor, who will travel with the data 
collectors on a daily basis (Figure 1). 
Before leaving the field at the end of each workday, the Data Collector Supervisor, Assistant 
Data Collector Supervisor and/or Data QC Supervisor will review all surveys for completeness 
and quality.  Additionally, data quality checks will be built into the tablet version of the survey, 
for example limiting ranges of responses/measurements to those that are within a credible 
range and consistency checks between questions.  Once the data quality is satisfactory the Data 
QC Supervisor will upload data on a daily basis.  This will be encrypted and transferred to 
Arusha or the KoboToolbox cloud for backup storage. 
The Lab Scientist in Kongwa will receive blood and urine samples and enter these samples into 
a lab archiving system that will be shared between research trial laboratory at Kongwa District 
Hospital and NM-AIST, Arusha.  He/she will also be hired in collaboration with the Kongwa 
District Medical Officer. 
Data quality will be monitored in multiple ways and at all levels of management, performed 
jointly between representatives from NM-AIST and Cornell.  In the field, adherence to all 
protocols and data quality will be full time responsibilities of the Data Collector Supervisor, 
Assistant Data Collector Supervisor and Data QC Supervisor.  Both of these positions will be 
supervised by the Field and Research Coordinator, who is in turn supervised by the PI and 
leadership team at Nelson Mandela.  The IT Data Manager (A.M.) based at NM-AIST in Arusha 
will be in frequent communication with the Data QC Supervisor to assure safe management and 
transfer of the data and will therefore help to supervise the Data QC Supervisor.  He will also 
stay in contact with the Data Collector Supervisor in case of any electronic problems/issues that 
might arise. 
Data monitoring will be performed on a weekly basis by Arusha-based IT Data Supervisor and 

19 
 
Biostatistician.  The IT Team will produce a weekly report of key data, including enrollment 
numbers, rejection/non-qualifier numbers, drop-out rates, completed visit rates, 
anthropometry and biological sample collection success rates.  Every other week to one month 
the IT Team will produce a report to show confirmation of receipt of biological sample by the 
Kongwa and Arusha labs and their condition. These reports will be shared with the core 
investigator team (N.K., E.E.M., E.P., F.N.), in addition to the event reporting described above.  
This data monitoring system will be discussed and approved by the DSMB, along with key “red 
flags” that will warrant rapid adjustment to protocols. The full data set will be shared through 
secure and IRB-approved means and will be stored in at least two sites (e.g. 
Arusha/KoBoToolbox Cloud and Ithaca). 
If need arises to correct data, the corrected file will be kept in a separate database with 
appropriate documentation for changes made. No data in the original database will be changed 
at any time. Access to edit data will be restricted to E.P., F.N. and N.K.  However any edits to 
data will be performed after reaching consensus by E.A.M., E.E.M., N.K, F.N and E.P. 
Identifiers will be removed from the data set and stored separately from other data and linked 
by a participant ID number. 
Plan for potential breaches 
Although we will only use IRB-approved and encrypted means of sending data, there remains a 
possibility of a data breach if somehow one of the servers storing the data was compromised or 
if a laptop or computer was stolen or compromised. 
To protect against a data breach, all field staff, including lab staff, will be trained and closely 
supervised on following the protocol of safe storage of laptops and hardcopies of forms and 
sending data only through approved means.  As stated above, identifiers will be kept separately 
from other data, to help protect privacy and confidentiality.  The IT Data Manager will be 
responsible for checking the integrity of the data on a weekly basis.  If ever data was found to 
be compromised, he will alert the PIs immediately.  If any identifiers have been compromised, 
this will be reported to the IRB within 24 hours and the affected participants as soon as 
possible.  If data that does not include identifiers have been somehow obtained, we will report 
this to the IRB within 48 hours, but will not inform participants, as their privacy has not been 
compromised. 

20 
 
Figure 1 – Field Research Team and Data Organization 
 
 
Data sharing plan 
Our funder, the Bill and Melinda Gates Foundation, has an Open Access Policy.  De-identified 
participant data that underlie the results related to the primary outcome will be made publicly 
available in a public data repository following the publication of the primary outcome paper in 
an open-access journal, ideally 12 months following the end of data collection. Data. that 
underlie the results for all secondary outcomes will also be placed in a public repository 
following the publication of these papers. 
 
Sample size calculation and cluster selection 
The sample size calculation was estimated to detect a difference of length-for-age Z score 
between the intervention and control groups using the STATA (version 15.1) command for two 
independent sample means in a CRT.  We based on our sample on the ability to detect a 
difference of 0.2 LAZ, which is believed to be clinically significant and would therefore motivate 
public health decision-making.  
Using a one-sided test of independent sample means, with a standard deviation of 1.2 Z, type I 
error of 0.05, and power of 0.90, design effect of 2.0 (justified below) and randomizing all 52 
health facilities (26 per arm), our total sample size is calculated to be 2,322 (1,161 infants per 
cluster).   This also assumes a CV of .144 for varying cluster size, based on previous year’s data 
for EPI attendance at 42 days.  If we conservatively estimate a 20% loss to follow-up and infant 
mortality, we will need a total of 2,787 infants, or 54 infants recruited per health cluster 
 
 
Head research team 
(Arusha) 
(N.K., E.E.M., E.P., F.N.) 
 
 Biostatistician 
(E.A.M.) 
 
IT Data Manager (A.M,.) 
 
Field and Research 
Coordinator 
(N.M.) 
 Data QC Supervisor 
 
Data collector 
supervisor 
 
Data collectors 
 
Lab scientist 

21 
 
annually or 4.5 infants per cluster per month.  We therefore will round up to 5 infants per 
cluster each month for a total of 3,120 potential infants, recognizing that in approximately 6 of 
the health facilities, it is unlikely that we will be able to recruit up to 60 infants because of the 
size of the population served by the facility. 
To estimate our design effect, we identified two cluster-randomized trials with educational 
and/or food or LiNS provision interventions delivered through community health workers with 
LAZ as an outcome1,2.  Based on these studies, we used an ICC of 0.02 to reach our design effect 
of 2.0 (rounding up slightly).  This is in line with the estimated design effects for stunting using 
population-based surveys in three African countries calculated by Katz3. 
Statistical Analysis and data analysis plan 
All outcomes will be presented using descriptive statistics; normally distributed data by the 
mean and standard deviation (SD) and skewed distributions by the median and interquartile 
range (IQR).  AF biomarkers and food contamination, usually skewed, will additionally be 
presented as geometric means and 95% Cis, medians and IQRs.  Binary and categorical variables 
will be presented using counts and percentages.  These outcomes will additionally be presented 
by study arm and season. 
The primary analysis will compare LAZ at 18 months between the control and intervention 
groups and will be analyzed using statistical approaches (such as Stata GEE regression 
procedure) to account for with-in cluster variance.  The primary analyses will be intention-to-
treat. 
Secondary analyses will include: 
• Intention-to-treat analyses of human mycotoxin biomarker outcomes 
• Analyses of mediation of mycotoxin biomarkers on the primary outcomes, using path 
analysis and/or regression approaches 
• Adjusted estimates of the randomized treatment effects on primary and secondary 
outcomes, using multiple regression equations to adjust for imbalances between 
randomized groups, and potentially increase precision of the effect estimate. For this 
analysis we will include covariates that differ substantially between randomized groups 
and/or that modify the intervention effect size by at least 10% when included in the 
model. 
• Per-protocol analysis of those with the highest contact with CHWs responsible for 
delivering the intervention and those who report high adherence to the intervention. In 
these analyses, we will consider the CHW contact and adherence to the intervention as 
ordinal variables defined by tertile or quartile of the continuous variables. 
 
Trial results will be reported in accordance with the extended CONSORT guidance for cluster 
randomized trials. 

22 
 
Specified subgroups 
• SES Quartile 
• Male/female 
• Elevation of residence 
• Quartiles of LAZ at 6 months 
Missing Data 
We will make our best effort to minimize missing data. In the main analyses we will include all 
relevant continuous covariates with less than 10% missing. For categorical variables, we will 
create a dummy variable for missing.  For variables that have substantial missing we will 
conduct sensitivity analyses with multiple imputation to compare to the main analyses. 
 
X. Quality Assurance 
A DSMB will be established, consisting of a biostatistician, a pediatrician and a nutritionist.  
They will convene (virtually) once around the time of the study’s launch, half way through the 
12 month data collection (estimated January 2020), when the 12 month data collection is 
complete (Estimated June 2020) and at the end of the trial. 
All researchers and staff working on this trial will be trained in GCP every three years.  Those 
with a strong internet connection and English comprehension will pass either the Society for 
Behavioral Medicine/NIH GCP or CITI Social and Behavioral Research e-course.  Those with 
limited internet and/or limited English ability, can choose from two options: a) the Johns 
Hopkins Good Clinical Practice for Social and Behavioral Research Field Guide in English or b) 
the condensed Kiswahili version of this guide (also by Johns Hopkins).  Record of passing the 
training will be kept R.N. and E.P. 
As mentioned in Section VII, we have designed an Unexpected Events Reporting plan and will 
train all staff in this plan to ensure appropriate and timely reporting to the Cornell IRB and 
NIMR.  This plan is proactive and will review data on a weekly, every other week, and monthly 
time interval to look for trends that might warrant further safety review. 
 
XI. Expected Outcomes of the Study 
There is evidence from multiple observational studies in sub-Saharan Africa of an inverse 
relationship between AF exposure and longitudinal child growth (the more exposure, the less 
linear growth).  Additionally, there appears to be a minimum threshold of exposure above 
which growth faulting takes place, although most observational studies have been small with 
varying assessment and analytic methods used between them, making this effect statistically 
difficult to analyze and compare between studies.  The only clinical trial conducted to assess the 
effect of AF on growth did not find an association between AF-lys and LAZ at 22months, but did 
at 13 months, albeit with a relatively high rate of loss to follow-up.  The current trial would 
strengthen the evidence base by generating evidence in a well-powered trial conducted in a site 
where 37% of children under 5 are stunted (<-2LAZ) and AF exposure is similar to those sites in 
West Africa where the association between AF and growth faltering was first described. 

23 
 
 
XII. Dissemination of Results and Publication Policy 
In accordance with the recommendations of the International Committee of Medical Journal 
Editors (ICMJE), authorship of any paper that is a result of data collection efforts from this trial 
will be based on 1) substantial contributions to conception and design, acquisition of data, or 
analysis and interpretation of data; 2) drafting the article or revising it critically for important 
intellectual content; and 3) final approval of the version to be published.  Any listed authors will 
all meet conditions 1, 2, and 3. 
Accepting co-authorship carries a level of accountability and authors should have the ability to 
discuss and publicly defend what is being presented as well as have confidence in the integrity 
of the contributions of their co-authors.  
Analysis, presentation, and publication of data 
All investigators, staff, partners and students are encouraged to initiate and contribute to 
dissemination projects. All manuscripts and materials containing data from the MMT must be 
reviewed and approved by the Principle Investigators, Rebecca Stoltzfus, Rebecca J Nelson and 
Neema Kassim before submission.  The data collected during this study may only be analyzed, 
presented, and/or published with the written consent of the PI’s.  No data or study information 
relating to the study should be used or shared without formal review and agreement.  A 
proposal should be submitted in writing to the PIs for review.  Reviews will receive one of the 
three designations: 1) approved; 2) approved with requested modifications; or 3) not approved. 
Such requests will be considered in light of the integrity of the overall program objectives. 
Non-author contributors 
Note that non-author contributors are those who meet fewer than all of the above criteria for 
authorship and should not be listed as authors, but they should be acknowledged. Those whose 
contributions do not justify authorship may be acknowledged individually or together as a 
group under a single heading, and their contributions should be specified (e.g., "served as 
scientific advisors," "critically reviewed the study proposal," "collected data, "participated in 
writing or technical editing of the manuscript", etc.). Common roles that meet the criteria for 
other contributions under the acknowledgement section include technical and supportive 
assistance, writing assistance, general support and scientific advisement, financial support, and 
critical review of the manuscript. 
 
The Bill and Melinda Gates Foundation, the funder of this trial, requires an open access data 
policy.  Therefore all manuscripts from this funded work to be published in open access journals 
with the data underlying the published research results.  More on this policy can be found: 
https://www.gatesfoundation.org/how-we-work/general-information/open-access-policy 
We will present our results with local (Kongwa) government officials, as well as a final report to 
NIMR and COSTECH.  We are not authorized to share any results with the participants or 
communities directly but can request the local government to share only summary results (not 
results by health facility) to assure confidentiality is upheld.  We will also share our results with 

24 
 
the national Steering Committee on Mycotoxins, possibly presenting our data to the committee 
in person. 
XIII. Duration of the Project 
We expect recruitment to begin in April of 2019.  All participants will be in the study until 18 
months of age and we will recruit over one year’s time.  If we meet our recruitment target, the 
trial should end in July 2021. 
XIV. Problems Anticipated 
Potential problems include: 
1. Mothers’ reluctance to participate in the trial, especially those in the control group who 
will not receive flours.  This could slow recruitment and/or results in a non-random 
group of participants.  We will monitor recruitment and attrition closely to reduce 
potential bias.  In an effort to educate mothers and communities about the trial, we 
conducted a series of informational meetings with community leaders across the district 
prior to recruitment. 
2. Difficulty in producing infant flours to meet Tanzanian food safety regulations.  We have 
been extremely proactive in setting up contacts with food traders who can source clean 
groundnuts and can provide strong QC systems to ensure that we can produce a clean 
product at a reasonable cost without further concentrating AF in the food supply. 
3. Provision of flours increases caloric intake in the experimental group compared to the 
control group.  The porridge flour we provide is based on the median composition of 
pre-blended flours in select villages in Kongwa.  Our education intervention will promote 
the same amount of porridge composition, consistency and frequency of feeding in both 
groups.  To check for any potential differences, we will perform 24-hour dietary recalls 
to measure intake in 100 infants per arm at 12 months. 
 
XV. Project Management 
● Rebecca Stoltzfus – Project PI, responsible for all project oversight 
● Rebecca Nelson – Project co-PI, responsible for leading the maize sorting innovation 
● Neema Kassim – PI of Nelson Mandela African Institution of Science and Technology, 
responsible for oversight of trial design and implementation in Tanzania 
● Edna Makule – Responsible for production of trial foods to meet legal safety standards 
● Erica Phillips – Responsible for providing technical leadership and support for trial 
design, implementation and analysis 
● Francis Ngure – Responsible for providing technical leadership on production of trial 
foods to meet legal safety standards; food surveys and analysis of food samples. 
Provides technical support on trial design, implementation and data analysis. 
● Laura Smith – Provide technical support and oversight for urinary and blood biomarker 
collection and laboratory and statistical analysis 

25 
 
● Paul Turner - Provide technical support and oversight for urinary and blood biomarker 
collection and laboratory and statistical analysis 
● Adam Mawenya – Responsible for electronic data management and database and IT 
support 
● Emmanuel Mpolya – Biostatistician responsible for co-data analysis 
● Nyabasi Makore – Research and Field Supervisor to oversee all field operations 
 
XVI. Ethics 
While planning for this trial, our team performed a literature review on ethical principles of 
trials with similar exposures and drafted a working paper on the ethical considerations of 
conducting such a trial.  Additionally, we communicated with the PIs of the MAICE trial to build 
from their knowledge and experience.  The current design is a result of consideration of 
multiple study and intervention designs and reporting options. 
Our first consideration was if a randomized trial was an ethical approach to testing this 
hypothesis, given that the exposure is AF consumption.  Considering the multitude of 
observational studies already performed analyzing this hypothesis, another observational study 
would not be conclusive enough to motivate decision makers.  Furthermore, we concluded that 
a randomized trial would meet the criteria for clinical equipoise because of lack of strong causal 
evidence about the effects of low to moderate chronic AF exposure in infancy.  To build strong 
causal evidence, this trial will collect multiple AF biomarkers in the full sample at three time 
points and in the cohort at five time points. 
Next, we considered multiple design options for this trial.  We considered implementing a 
stepped-wedge design, in which all participants would eventually receive the experimental 
package of interventions, as an alternative to a cluster-randomized design.  However, since we 
believe the trial does meet the criteria for equipoise, a stepped-wedge design does not increase 
the ethical value of the study, but would slow the time to inference and make inference more 
complicated. 
The intervention was designed to meet multiple objectives 1) provide strong causal evidence, 2) 
promote a nutritionally diverse and adequate diet for all infants, 3) minimize dietary differences 
between intervention arms, and 4) keep all recommendations for foods potentially 
contaminated with AF in line with current practices/local recommendations, so as not to 
increase AF consumption.  In Kongwa, both the District Nutrition Officer and the former USAID 
project called “Mwanzo Bora” promote(d) the use of lishe with a composition of 3:1 or 4:1 
maize meal to groundnut powder.  We therefore consider these lishe recipes to be the regional 
standard of care.  Our formative research confirmed that 66% of infants are fed groundnuts in a 
variety of foods, including porridges and sauces, as it is one of the few protein sources fed to 
infants in this area.   
Our IYCF education will include messages on dietary diversity and the importance of continued 
breastfeeding through 24 months, using education materials approved by the Tanzanian Food 
and Nutrition Center.  We will monitor IYCF and breastfeeding practices during the trial to 
assure the promotion and provision of lishe do not reduce dietary diversity or breast milk 

26 
 
intake. 
A final major consideration is if and how to respond to biomarker or food samples with results 
that could be considered “high” or are outliers.  To report these results to participants or 
relevant authorities we would need a). clearly established cut-off points, b) the ability to report 
results in a timeframe that could be clinically useful to the participant, and c) advice to prevent 
future contamination.  Each of these proves challenging given current knowledge and available 
technologies for locations similar to Kongwa. 
First, AF biomarkers are not clinical measures with determined cut-offs to distinguish between 
a safe or potentially unsafe level.  In the case of no established clinical cut-offs, there is no clear 
scientific or health justification to flag or report results except at the levels observed in cases of 
acute aflatoxicosis.  Outside of the range of acute illness, there will undoubtedly be results that 
are outliers and/or in the upper ranges compared to other research subjects or other reported 
data, prompting questions about the ethics of reporting to the participant’s guardian or the 
relevant government institutions in these cases. 
Secondly, there is no available technology that will allow rapid analysis of blood or urine 
samples in the field.  Currently there is no capacity to analyze AF-alb in Tanzania, so samples 
will be exported for analysis, guaranteeing a long delay between sample collection and 
obtaining results.  Because the dynamics of AFM1 and AF in food are highly variable, by the 
time sample outliers would be identified, the properties of food consumed by the individual 
would undoubtedly differ from those consumed when the sample was taken.  The results of the 
analyzed sample might not be relevant by the time it could be reported. 
Finally, once a sample was determined to be an outlier, what useful advice could be given to 
the parent or caretaker of the infant?  Proven interventions to reduce AF exist, but few are 
practical and feasible in resource-poor settings such as Kongwa.  Give these complexities, we 
have decided to take the following actions to prevent contamination and report our findings.  
Education to Prevent Contamination 
We will teach mothers how to sort groundnuts to reduce AF contamination as part of our 
blanket IYCF education after 12 months of age, when infants consume more groundnut.  
Manual groundnut sorting has shown to be effective to reduce AF, although the evidence is 
limited for household sorting in low-resource settings.  It is not effective to sort maize manually 
because contaminated kernels can’t be determined visually. 
Blood and Urinary Biomarker Reporting 
We will take the following precautions for AF-alb results, even with the understanding that 
there will be a significant time delay between taking the sample and analysis: 
1.  We will report the percent of samples above 1000pg/mg to the Kongwa District 
Council.  We have subjectively chosen this cut-off because these are these are levels 
usually found in the highest quintile in other high-risk countries.  One limited case-
control study of aflatoxicosis from Kenya reported cases (n=10) had higher AF-alb 
versus controls (n=50) with geometric means of 3500pg/mg vs 150pg/mg (Azziz-
Baumgartner et al., 2004).  The ages of these individuals was not clearly defined.  

27 
 
Several control individuals had AF-alb level between 1000-5000pg/mg.  We feel that 
1000pg/mg cut point represents our best estimate to identify this as a putative 
reporting concern. 
2.  If an infant is found to have an AF-alb value > 1000 pg/ml, we will make a home visit 
to the family to assess the health of the infant and understand more the food security 
and food quality issues in the household, particularly as they pertain to the infant. 
Based on the findings, research staff will provide customized advice to the caregivers of 
the child to protect the infant from continued high exposures, with possible referral to 
health and agricultural authorities.  
For AFM1, there is not sufficient evidence to intervene at any level.   
Food Sample Reporting 
Unlike biomarkers, there are stated safe limits to AF contamination found in food; in Tanzania 
the upper legal limit for commercial baby food is 5 ppb.  Given the documented AF problem in 
Dodoma and our formative research, we expect to find at least 30% of samples above this limit, 
which is the motivation for doing the trial here.  Food samples will be analyzed in Arusha and 
values will be known more rapidly than for AF-alb.  We have decided upon the following 
responses to exceptionally high levels of AF in for food samples (defined as >1000 ppb in maize 
or >5000 ppb in ground nut): 
1.  We will report the percent of maize samples above 1000ppb and groundnut samples 
>5000ppb to the Kongwa District Council.  We have subjectively chosen these cut-offs 
because these are these are levels usually found in the highest quintile in other high-risk 
countries.  Additionally, we estimate that maize is consumed 5 times as much as 
groundnut, the reason we set the limit 5 times higher for groundnut than maize. 
2. If a household sample of food reported to be fed to the study child exceeds these 
thresholds, we will return to the household to resample that food. This is to account for 
the high sampling variability in foods.  
3. If the second sample confirms high level of toxin, we will make a home visit to the 
family to assess the health of the infant and understand more the food security and 
food quality issues in the household, particularly as they pertain to the infant. Based on 
the findings, research staff will provide customized advice to the caregivers of the child 
to protect the infant from continued high exposures, with possible referral to health and 
agricultural authorities. 
Finally, because of the limited number of interventions that are feasible in low-resource 
settings, part of our overall project, but outside the scope of the trial, includes developing a 
maize and groundnut sorting innovation for use in such settings.  This is under development 
simultaneous to the trial.  If effective, we hope it will be rolled it out across Kongwa (and 
beyond). 
 
XVII. Informed Consent Forms 
Written informed consent will be asked and obtained by all participants in Kiswahili.  Our 

28 
 
informed consent forms have been written specifically for a population with limited research 
experience and research knowledge and contains multiple questions to check for 
comprehension of the study and the participant’s rights. 
All forms have been translated from English to Kiswahili.  Attached are the forms, adapted by 
randomized group. 
XVIII. Budget  
The budget for this research is provided solely from the BMGF.  Additional funding is being 
sought for future analysis of samples. 
 
 

29 
 
XIX. References Cited 
1.  Ngure F, Wells H. Final Trip Report to Tanzania: Formative research for the Mycotoxin 
Mitigation Trial in Kongdwa District. 2015. 
2.  Ministry of Health CD, Gender, Elderly and Children (MoHCDGEC);, [Zanzibar] MoHM, (NBS) 
NBoS, (OCGS) OotCGS, ICF. Tanzania Demographic and Health Survey and Malaria Indicator 
Survey (TDHS-MIS) 2015-16. Dar es Salaam 
Rockville; 2016. 
3.  Davey C, Hargreaves J, Thompson JA, Copas AJ, Beard E, Lewis JJ, et al. Analysis and 
reporting of stepped wedge randomised controlled trials: synthesis and critical appraisal of 
published studies, 2010 to 2014. Trials. 2015;16:358.