Adding a Water, Sanitation and Hygiene Intervention and a Lipid‐Based Nutrient Supplement to an Integrated Agriculture and Nutrition Program Improved the Nutritional Status of Young Burkinabé Children
Bibliographic record
Abstract
An integrated agriculture and nutrition program, the Enhanced Homestead Food Production (EHFP) program, implemented by Helen Keller International (HKI) in Burkina Faso from 2010–2012 significantly reduced anemia among young children. Although these results were promising, it was hypothesized that greater nutritional impacts could be achieved with longer program exposure, the addition of a water, sanitation and hygiene (WASH) intervention, and an intervention to address micronutrient gaps such as providing children 6–23.9 mo of age with a daily lipid‐based nutrient supplement (LNS). To test these hypotheses we used a cluster randomized trial whereby the control and intervention villages from the 2010–12 EHFP evaluation were separately randomized to one of two groups for a total of four intervention groups (15 clusters each), all of which received HKI's base EHFP program. The 2010–12 control villages were randomized to receive the EHFP program for the first time from 2014–16, either alone (EHFP‐2014) or with a WASH intervention (EHFP‐2014+WASH) and the intervention villages that received the 2010–12 EHFP program were randomized to receive the EHFP program, for the second time at the community level, with WASH (EHFP‐2010+WASH) or with WASH and LNS (EHFP‐2010+WASH+LNS). Mothers with children 0–12 mo of age at baseline in 2014 were invited to participate in the 2 y program and associated evaluation. These groups helped answer the following 3 questions: 1) added benefit of prior community‐level exposure to the EHFP program (EHFP‐2010+WASH (n=353) compared to EHFP‐2014+WASH (n=442)); 2) added benefit of WASH (EHFP‐2014+WASH (n=442) compared to EHFP‐2014 (n=402)); and 3) added benefit of providing LNS (EHFP‐2010+WASH+LNS (n=356) compared to EHFP‐2010+WASH (n=353)). Impacts on anemia, iron deficiency anemia (IDA) and vitamin A deficiency (VAD) among children aged 3–12 mo at baseline (in 2014) were assessed using difference‐in‐difference (DID) impact estimates that controlled for relevant covariates and adjusted standard errors for clustering. Anemia (−15 pp) and IDA (−17 pp) decreased and VAD increased (+12 pp) over the 2 y in the EHFP‐2014 group. We found no additional benefit of prior exposure to the program on any of these outcomes. Adding WASH led to a significantly greater reduction in anemia compared to EHFP alone (DID=−11 pp; p<0.05)), but no impacts on IDA or VAD. Adding LNS to EHFP‐2010+WASH led to significantly greater decreases in anemia (DID=−12 pp; p<0.05), IDA (DID=−13 pp; p<0.05) and a marginally significantly greater decrease in VAD (DID=−8 pp; p<0.10). The two EHFP programs implemented by HKI in Burkina Faso (2010–12; 2014–16) reduced anemia among young children. Adding WASH to the program in 2014 led to a significantly greater reduction in anemia, and including both WASH and LNS in communities with prior EHFP program exposure led to the largest and most diverse nutritional impacts including significant reductions in anemia, IDA and VAD. These results highlight the importance of addressing the multiple causes of undernutrition simultaneously, through multisectoral programs. Support or Funding Information Funding was provided by Global Affairs Canada through HKI and by the CGIAR Research Program on Agriculture for Nutrition and Health (A4NH) led by IFPRI.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".