Impacts of Ambient Temperatures on Pediatric Anemia in Sub-Saharan Africa: A Regional Ecological Study
Bibliographic record
Abstract
Anemia has been a growing concern for the pediatric population in sub-Saharan Africa. Emerging risk factors for anemia under five years of age in low-income countries are multifaceted, including infectious diseases, nutritional deficiencies, hidden hunger, and various economic determinants, and its health burdens include childhood stunting and reduced cognitive function diminished school performance in children. However, the influence of climatic factors, particularly ambient temperatures, on pediatric anemia remains understudied. In this population-based study, we assess the region-specific associations between pediatric anemia and ambient temperatures in 43 countries in Africa from 2000 to 2019. Using generalized linear regression models (upon adjusting for covariates), we found that the risk of temperatures on pediatric anemia varies across four African regions, whereby the Central and Southern African regions have a positive association between pediatric anemia and ambient temperatures, and Western and Eastern regions are negatively affected. The study aims to provide evidence to stakeholders to curtail the onset of pediatric anemia in high-risk African regions to set up key interventions based on the sustainability goals set by the World Health Organization.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".