Prevalence thresholds for wasting, overweight and stunting in children under 5 years
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
OBJECTIVE: Prevalence ranges to classify levels of wasting and stunting have been used since the 1990s for global monitoring of malnutrition. Recent developments prompted a re-examination of existing ranges and development of new ones for childhood overweight. The present paper reports from the WHO-UNICEF Technical Expert Advisory Group on Nutrition Monitoring. DESIGN: Thresholds were developed in relation to sd of the normative WHO Child Growth Standards. The international definition of 'normal' (2 sd below/above the WHO standards median) defines the first threshold, which includes 2·3 % of the area under the normalized distribution. Multipliers of this 'very low' level (rounded to 2·5 %) set the basis to establish subsequent thresholds. Country groupings using the thresholds were produced using the most recent set of national surveys. SETTING: One hundred and thirty-four countries. SUBJECTS: Children under 5 years. RESULTS: For wasting and overweight, thresholds are: 'very low' (≈6 times 2·5 %). For stunting, thresholds are: 'very low' (≈12 times 2·5 %). CONCLUSIONS: The proposed thresholds minimize changes and keep coherence across anthropometric indicators. They can be used for descriptive purposes to map countries according to severity levels; by donors and global actors to identify priority countries for action; and by governments to trigger action and target programmes aimed at achieving 'low' or 'very low' levels. Harmonized terminology will help avoid confusion and promote appropriate interventions.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it