Not water, sanitation and hygiene practice, but timing of stunting is associated with recovery from stunting at 24 months: results from a multi-country birth cohort study
Bibliographic record
Abstract
OBJECTIVES: To measure the role of water, sanitation and hygiene (WASH) practices on recovery from stunting and assess the role of timing of stunting on the reversal of this phenomenon. DESIGN: Data from the MAL-ED multi-country birth cohort study was used for the current analysis. Generalised linear mixed-effects models were used to estimate the probability of reversal of stunting with WASH practice and timing of stunting as the exposures of interest. SETTING: Seven different countries across three continents. PARTICIPANTS: A total of 612 children <2 years of age. RESULTS: We found that not WASH practice but timing of stunting had statistically significant association with recovery from stunting. In comparison with the children who were stunted at 6 months, children who were stunted at 12 months had 1·9 times (β = 0·63, P = 0·03) more chance of recovery at 24 months of age. And, children who were stunted at 18 months of age even had higher odds (adjusted OR = 3·01, β = 1·10, P < 0·001) of recovery than children who were stunted at 6 months. Additionally, mother's height (β = 0·59, P = 0·04) and household income (β = 0·02, P < 0·05) showed statistically significant associations with the outcome. CONCLUSIONS: The study provided evidence for the role of timing of stunting on the recovery from the phenomenon. This novel finding indicates that the programmes to promote linear growth should be directed at the earliest possible timepoints in the course of life.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".