Effectiveness of Dietary Management for Moderate Wasting among Children > 6 Months of Age—A Systematic Review and Meta-Analysis Exploring Different Types, Quantities, and Durations
Bibliographic record
Abstract
Currently, no World Health Organization guidelines exist for the management of approximately 31.8 million moderately wasted children globally. The objective of this review was to synthesise evidence on the optimal type, quantity, and duration of dietary treatment for moderate wasting. Ten electronic databases were searched until the 23rd of August 2021. Experimental studies comparing interventions for the dietary management of moderate wasting were included. Meta-analyses were conducted and results were presented as risk ratios or mean differences with 95% confidence intervals. Seventeen studies comparing specially formulated foods were included involving 23,005 participants. Findings suggest little or no difference in recovery between Fortified Blended Foods (FBFs) with improved micronutrient and/or milk content (enhanced FBFs) and lipid-based nutrient supplements (LNS), whereas children treated with non-enhanced FBFs (locally produced FBFs or standard corn-soy blend) may have lower recovery rates than those treated with LNS. There was no difference in recovery when ready-to-use therapeutic and ready-to-use supplementary food were compared. Other outcomes mostly aligned with results for recovery. In conclusion, LNSs improve recovery compared to non-enhanced FBFs, but are comparable to enhanced FBFs. Programmatic choice of supplement should consider factors such as cost, cost-effectiveness, and acceptability. Further research is required to determine optimal dosing and duration of supplementation.
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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 | 0.007 | 0.019 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.022 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".