World Perspective on the Epidemiology of Stunting between 1990 and 2015
Bibliographic record
Abstract
BACKGROUND: Stunting is the most prevalent form of child undernutrition with current worldwide estimates at 156 million. The majority of these children reside in low- and middle-income countries. When stunting prevails to adulthood, optimal growth potential and economic productivity are minimized. RESULTS: In 2015 there were 98.5 million fewer stunted children under 5 years of age than in 1990. In East Asia and Pacific and South Asia, the stunting prevalence decreased by 24.8 and 25%, respectively. Minimal declines were observed in Latin America and the Caribbean at 12.6%, in the Middle East and North Africa at 12.9%, and in sub-Saharan Africa at 13.4%. But because large populations of children under 5 years of age are distributed disproportionately, decreases in prevalence do not translate to fewer numbers of stunted children globally. In sub-Saharan Africa, the number of stunted children increased by 12.4 million between 1990 and 2015. CONCLUSIONS: Adult height is dependent on nutrition-specific or nutrition-sensitive factors. Nutrition-specific factors can be targeted according to their impact at critical points of development and therefore offer multiple windows of opportunity for interventions. To date, many interventions focus on the first 1,000 days, but opportunities may extend into later childhood and adolescence. .
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".