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Clinical Trial Details — Status: Completed

Administrative data

NCT number NCT04209569
Other study ID # 13426
Secondary ID
Status Completed
Phase N/A
First received
Last updated
Start date January 17, 2020
Est. completion date December 30, 2022

Study information

Verified date January 2024
Source Tufts University
Contact n/a
Is FDA regulated No
Health authority
Study type Interventional

Clinical Trial Summary

This study asks the research question "Does enabling families (particularly mothers and other caregivers) to 'assess and act' on drivers of malnutrition through a targeted SBC+ package succeed in a sustained reduction of risk factors thereby improving child health and nutrition?" This study aims to implement and measure the effects of a multi-level multi-sectoral behavior change information intervention in Agago District of Northern Uganda and determine potential for scale up in a complex environment. The study design is a three-arm cluster randomized controlled superiority design (cRCT) with a 1:1:1 allocation ratio. The study arms will be: Group 1: NIPP arm; Group 2: NIPP+ arm; and Group 3: Non-intervention control arm. A barrier analysis will be conducted to ensure appropriate targeting and contextualization of the NIPP and NIPP+ approaches prior to implementation. Each intervention arm will receive a 12-week intervention (NIPP or NIPP+) with active monitoring and longitudinal follow ups post intervention at 2, 6, and 12-months post-intervention. The total sample size for the Barrier Analysis will be a maximum of 450 caregivers; for the main intervention, 900 households (300/arm) will be purposely sampled from the randomly selected communities. Respondents for the qualitative portion will be purposely selected.


Description:

Objective: This study asks the research question "Does enabling families (particularly mothers and other caregivers) to 'assess and act' on drivers of malnutrition through a targeted SBC+ package succeed in a sustained reduction of risk factors thereby improving child health and nutrition?" This study aims to implement and measure the effects of a multi-level multi-sectoral behavior change information intervention in Agago District of Northern Uganda and determine potential for scale up in a complex environment. Intervention: Through a collaboration between Tufts University, GOAL International, CIMMYT, and Cornell University, GOAL will implement Nutrition Impact and Positive Practice (NIPP) circles as the standard SBC intervention against which the hypotheses will be tested. GOAL will also implement a NIPP+ approach which will integrate additional interventions for water, sanitation, and hygiene (WASH), and use of improved agriculture inputs. These interventions will be measured by outcome indicators measuring aflatoxin exposure, water contamination, and knowledge transferred to action. Design: The study design is a three-arm cluster randomized controlled superiority design (cRCT) with a 1:1:1 allocation ratio. The study arms will be: Group 1: NIPP arm; Group 2: NIPP+ arm; and Group 3: Non-intervention control arm. A barrier analysis will be conducted to ensure appropriate targeting and contextualization of the NIPP and NIPP+ approaches prior to implementation. Each intervention arm will receive a 12-week intervention (NIPP or NIPP+) with active monitoring and longitudinal follow ups post intervention at 2, 6, and 12-months post-intervention. The total sample size for the Barrier Analysis will be a maximum of 450 caregivers; for the main intervention, 900 households (300/arm) will be purposely sampled from the randomly selected communities. Respondents for the qualitative portion will be purposely selected. Analysis: This longitudinal study will collect data from all participants at 3 time points: baseline, endline, and sustainability (12-months post-intervention). The analysis will utilize Intent-to-Treat (ITT) approach using the initial randomization of the treatment arms. Using ITT will allow us to determine the overall impact of having the NIPP vs. NIPP+ vs. control, thus better mimicking real world program implementation and impact. Mixed effects models will be used to determine the role of time-variant and invariant individual (by gender) household, and community characteristics, as well as measures of exposure and integration on key outcome indicators. A difference-in-difference analysis (baseline/endline, baseline/sustainability, endline/sustainability) will also be used to triangulate findings. Sub-study: a subset of reproductive age women will be purposively selected for enrollment into a validation sub-study that will examine the level of aflatoxin (AFB1-lysine concentration) exposure measured in venous blood compared to capillary blood compared to the innovative SAFE-phone method. This will serve as a validation and calibration sub-study to gauge the accuracy of the SAFE-Phone method compared to venous reference.


Recruitment information / eligibility

Status Completed
Enrollment 1834
Est. completion date December 30, 2022
Est. primary completion date December 30, 2022
Accepts healthy volunteers Accepts Healthy Volunteers
Gender All
Age group N/A and older
Eligibility The inclusion criteria: - Female circle: - Willingness to participate in the group - staying in the area for 12 weeks. - Have a child under the age of 2 (irrespective of status of malnutrition) - Male circle inclusion - Willingness to participate - staying the area for 12 weeks - Spouse, brothers and/or other influential male family members of the female caregiver enrolled in the female circle - Community circle - No specific criteria other than being key community leaders Exclusion Criteria: Individuals in households without eligible children (i.e. without a child under age 2), or who will not be present in the selected communities during the intervention and data collection periods and/or who are not willing to participate through the entire 12-week cycle.

Study Design


Intervention

Behavioral:
Nutrition Impact and Positive Practice Circle (NIPP)
GOAL's NIPP approach is a gendered, grass-roots SBC approach, tackling a package of underlying behavioral determinants of malnutrition, irrespective of the particular manifestation. The approach is multi-sectoral in nature. It also has a strong monitoring, evaluation and adaptive learning component by design. The intervention approach (based on GOAL's NIPP approach) involves the creation of community, male and female circles in each community with messaging and activities targeted towards the three groups in varying intensities. While the male and female circles meet 2-3 times per week for a maximum period of 12 weeks while the community circles will meet for approximately three hours at any one time over a period of 2-7 days. (See GOAL NIPP Implementation Guidelines)

Locations

Country Name City State
Uganda GOAL/Uganda Kampala

Sponsors (4)

Lead Sponsor Collaborator
Tufts University Centro Internacional de Mejoramiento de Maiz y Trigo Internacional, Mexico, Cornell University, GOAL, Ireland

Country where clinical trial is conducted

Uganda, 

References & Publications (39)

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Channa H., Ricker-Gilbert J., De Groote H., Marenya P., Bauchet J., Woloshuk C. Assessing Kenyan farmers and traders demand for low cost moisture meters to reduce aflatoxin in maize. Research brief by Purdue University and CIMMYT Kenya.

Dangour AD, Watson L, Cumming O, Boisson S, Che Y, Velleman Y, Cavill S, Allen E, Uauy R. Interventions to improve water quality and supply, sanitation and hygiene practices, and their effects on the nutritional status of children. Cochrane Database Syst Rev. 2013 Aug 1;(8):CD009382. doi: 10.1002/14651858.CD009382.pub2. — View Citation

Danso J.K., Osekre E.A., Opit G.P., Manu N., Armstrong P., Arthur F.H., Campbell J.F., Mbata G., and McNeill S.G. Post-harvest insect infestation and mycotoxin levels in maize markets in the Middle Belt of Ghana Journal of Stored Products Research 77 (2018) 9-15

Davis Jr., Thomas P. Barrier Analysis Facilitator's Guide: A Tool for Improving Behavior Change Communication in Child Survival and Community Development Programs, Washington, D.C.: Food for the Hungry. (2004).

ENN. Child wasting and stunting: time to overcome the separation. A Briefing Note for policy makers and programme implementers. Emergency Nutrition Network. June 2018.

FTF NIL Africa 2013. Baseline Report. Assessing the linkage between agriculture, food security, nutrition and health among women and children in rural Ugandan households. 66 pages. www.nutritioninnovationlab.org

GOAL. 2016. "Implementation guidelines for Nutrition Impact and Positive Practice (NIPP) approach." GOAL, Ireland

Hamoudi A, Jeuland M, Lombardo S, Patil S, Pattanayak SK, Rai S. The effect of water quality testing on household behavior: evidence from an experiment in rural India. Am J Trop Med Hyg. 2012 Jul;87(1):18-22. doi: 10.4269/ajtmh.2012.12-0051. — View Citation

Harding KL, Aguayo VM, Webb P. Factors associated with wasting among children under five years old in South Asia: Implications for action. PLoS One. 2018 Jul 3;13(7):e0198749. doi: 10.1371/journal.pone.0198749. eCollection 2018. — View Citation

Headey D, Nguyen P, Kim S, Rawat R, Ruel M, Menon P. Is Exposure to Animal Feces Harmful to Child Nutrition and Health Outcomes? A Multicountry Observational Analysis. Am J Trop Med Hyg. 2017 Apr;96(4):961-969. doi: 10.4269/ajtmh.16-0270. Epub 2016 Dec 19. — View Citation

Khara T, Dolan C. The relationship between wasting and stunting, policy, programming and research implications. Technical Briefing paper. Oxford, UK: Emergency Nutrition Network, 2014. 2.

Kikafunda JK, Walker AF, Collett D, Tumwine JK. Risk factors for early childhood malnutrition in Uganda. Pediatrics. 1998 Oct;102(4):E45. doi: 10.1542/peds.102.4.e45. — View Citation

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Kosinski KC, Kulinkina AV, Abrah AF, Adjei MN, Breen KM, Chaudhry HM, Nevin PE, Warner SH, Tendulkar SA. A mixed-methods approach to understanding water use and water infrastructure in a schistosomiasis-endemic community: case study of Asamama, Ghana. BMC Public Health. 2016 Apr 14;16:322. doi: 10.1186/s12889-016-2976-2. — View Citation

Lauer JM, Duggan CP, Ausman LM, Griffiths JK, Webb P, Agaba E, Nshakira N, Tran HQ, Gewirtz AT, Ghosh S. Biomarkers of maternal environmental enteric dysfunction are associated with shorter gestation and reduced length in newborn infants in Uganda. Am J Clin Nutr. 2018 Oct 1;108(4):889-896. doi: 10.1093/ajcn/nqy176. — View Citation

Lauer JM, Duggan CP, Ausman LM, Griffiths JK, Webb P, Bashaasha B, Agaba E, Turyashemererwa FM, Ghosh S. Unsafe Drinking Water Is Associated with Environmental Enteric Dysfunction and Poor Growth Outcomes in Young Children in Rural Southwestern Uganda. Am J Trop Med Hyg. 2018 Dec;99(6):1606-1612. doi: 10.4269/ajtmh.18-0143. — View Citation

Lauer JM, Duggan CP, Ausman LM, Griffiths JK, Webb P, Wang JS, Xue KS, Agaba E, Nshakira N, Ghosh S. Maternal aflatoxin exposure during pregnancy and adverse birth outcomes in Uganda. Matern Child Nutr. 2019 Apr;15(2):e12701. doi: 10.1111/mcn.12701. Epub 2018 Oct 23. — View Citation

Luby SP, Rahman M, Arnold BF, Unicomb L, Ashraf S, Winch PJ, Stewart CP, Begum F, Hussain F, Benjamin-Chung J, Leontsini E, Naser AM, Parvez SM, Hubbard AE, Lin A, Nizame FA, Jannat K, Ercumen A, Ram PK, Das KK, Abedin J, Clasen TF, Dewey KG, Fernald LC, Null C, Ahmed T, Colford JM Jr. Effects of water quality, sanitation, handwashing, and nutritional interventions on diarrhoea and child growth in rural Bangladesh: a cluster randomised controlled trial. Lancet Glob Health. 2018 Mar;6(3):e302-e315. doi: 10.1016/S2214-109X(17)30490-4. Epub 2018 Jan 29. — View Citation

Marshak A, Young H, Bontrager EN, Boyd EM. The Relationship Between Acute Malnutrition, Hygiene Practices, Water and Livestock, and Their Program Implications in Eastern Chad. Food Nutr Bull. 2017 Mar;38(1):115-127. doi: 10.1177/0379572116681682. Epub 2016 Dec 8. — View Citation

Marshak, A., H. Young, and A. Radday, Water, Livestock, and Malnutrition: Findings from an Impact Assessment of 'Community Resilience to Acute Malnutrition' Programming in the Dar Sila Region of Eastern Chad, 2012-2015. 2016, Feinstein International Center, Tufts University: Medford, MA.

Marshak, A., Mazurana, D., Opio, J., Gordon, R., and T. Atim. Tracking change in livelihoods, service delivery, and governance: evidence form a 2013-2015 panel survey in Uganda. ODI Working paper 59. September 2017.

Martorell R, Young MF. Patterns of stunting and wasting: potential explanatory factors. Adv Nutr. 2012 Mar 1;3(2):227-33. doi: 10.3945/an.111.001107. — View Citation

Masset E, Haddad L, Cornelius A, Isaza-Castro J. Effectiveness of agricultural interventions that aim to improve nutritional status of children: systematic review. BMJ. 2012 Jan 17;344:d8222. doi: 10.1136/bmj.d8222. — View Citation

Murdock L.L., Margam V., Baoua I., Balfe S., and Shade R.E. Death by desiccation: effects of hermetic storage on cowpea bruchids. J. Stored Prod. Res., 49 (2012), pp. 166-170

Omotilewa OJ, Ricker-Gilbert J, Ainembabazi JH, Shively GE. Does improved storage technology promote modern input use and food security? Evidence from a randomized trial in Uganda. J Dev Econ. 2018 Nov;135:176-198. doi: 10.1016/j.jdeveco.2018.07.006. — View Citation

Rogers, Beatrice; Sanchez, Leslie; and Feinstein, Jamie. 2016. Sustaining Development: Results from a Study of Sustainability and Exit Strategies among Development Food Assistance Projects-Honduras Country Study. Washington, DC: FHI 360/Food and Nutrition Technical Assistance III Project (FANTA).

Ruel M.T., Quisumbing A.R. and Balagamwalab M. Nutrition-sensitive agriculture: What have we learned so far? Global Food Security 17 (2018) 128-153

Schoenbuchner SM, Dolan C, Mwangome M, Hall A, Richard SA, Wells JC, Khara T, Sonko B, Prentice AM, Moore SE. The relationship between wasting and stunting: a retrospective cohort analysis of longitudinal data in Gambian children from 1976 to 2016. Am J Clin Nutr. 2019 Aug 1;110(2):498-507. doi: 10.1093/ajcn/nqy326. — View Citation

Stobaugh HC, Rogers BL, Rosenberg IH, Webb P, Maleta KM, Manary MJ, Trehan I. Children with Poor Linear Growth Are at Risk for Repeated Relapse to Wasting after Recovery from Moderate Acute Malnutrition. J Nutr. 2018 Jun 1;148(6):974-979. doi: 10.1093/jn/nxy033. — View Citation

Stobaugh HC, Rogers BL, Webb P, Rosenberg IH, Thakwalakwa C, Maleta KM, Trehan I, Manary MJ. Household-level factors associated with relapse following discharge from treatment for moderate acute malnutrition. Br J Nutr. 2018 May;119(9):1039-1046. doi: 10.1017/S0007114518000363. Epub 2018 Mar 5. — View Citation

Vella V, Tomkins A, Nviku J, Marshall T. Determinants of nutritional status in south-west Uganda. J Trop Pediatr. 1995 Apr;41(2):89-98. doi: 10.1093/tropej/41.2.89. — View Citation

Vetter TR, Mascha EJ. Defining the Primary Outcomes and Justifying Secondary Outcomes of a Study: Usually, the Fewer, the Better. Anesth Analg. 2017 Aug;125(2):678-681. doi: 10.1213/ANE.0000000000002224. — View Citation

Wilson, T. 2007. Perceptions, practices, principles and policies in provision of livestock-water in Africa. Agricultural Water Management, 90 (2007), pp. 1-12

Young H., Marshak A. Persistent Global Acute Malnutrition. A discussion paper on the scope of the problem, its drivers and recommendations for policy, practice and research. USA: Feinstein International Center, Tufts University, 2018.

* Note: There are 39 references in allClick here to view all references

Outcome

Type Measure Description Time frame Safety issue
Other Change in Mid-upper Arm Circumference cm of mid upper arm circumference taken with standard UNICEF tape prior to the intervention, immediately after the intervention, and 1 year following the intervention
Other Change in Food Insecurity Household food insecurity and access score (0-27, 72=highly insecure) prior to the intervention, immediately after the intervention, and 1 year following the intervention
Other Change in weight-for-height z score weight taken with SECA scale and height taken with standard height board applied to WHO growth charts prior to the intervention, immediately after the intervention, and 1 year following the intervention
Other Maize production acreage planted just before exposure to the training and 1 year after training
Other Maize production production levels (kg) just before exposure to the training and 1 year after training
Other Maize production yield (kg/acre) just before exposure to the training and 1 year after training
Primary Change in Aflatoxin Exposure in Maize aflatoxin in parts per billion in a random sample of maize in a given household's maize supply within 1-month of harvest immediately after the intervention and one year after the intervention.
Primary Change in E. coli exposure in household e. coli measured in colonies/100 ml prior to the intervention, immediately after the intervention, and 1 year following the intervention
Secondary Aflatoxin Exposure in blood serum venous total (ng/ml) AFB1-lysine adduct concentrations immediately after the intervention, and 1 year following the intervention
Secondary Aflatoxin Exposure in blood serum albumin normalized (pg/mg) AFB1-lysine adduct concentrations immediately after the intervention, and 1 year following the intervention
Secondary Change in Dietary Diversity - mother and child 24 hours recall applied to standard dietary diversity range prior to the intervention, immediately after the intervention, and 1 year following the intervention and 2 and 6-months after the intervention
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