High-risk fertility behaviour and childhood anaemia in sub-Saharan Africa
Bibliographic record
Abstract
OBJECTIVE: This study sought to examine the association between high-risk fertility behaviour and childhood anaemia in sub-Saharan Africa . DESIGN: An analytical study was conducted using cross-sectional data from mothers with children under age 5 (n=64 512) from 28 sub-Saharan African countries. Multilevel logistic regression models were fitted to examine the association between high-risk fertility behaviour and childhood anaemia. The results were presented using adjusted odds ratios (aORs) with 95% confidence interval (CI). SETTING: Twenty-eight sub-Saharan African countries. OUTCOME MEASURE: Childhood anaemia. RESULTS: The percentage of children with anaemia in the 28 countries was 66.7%. We found that age more than 34 at delivery and short birth interval had significant associations with childhood anaemia. Children of mothers whose most recent delivery occurred after 34 years were less likely to be anaemic compared with those whose most recent delivery occurred before age 34 (aOR=0.89; 95% CI 0.83 to 0.95). We found that children born to mothers with short birth intervals were more likely to be anaemic, compared with those with long birth intervals (aOR=1.08; 95% CI 1.01 to 1.16). CONCLUSIONS: We, therefore, draw the attention of policy makers and programme implementers to invest in policies and programmes aimed at combating childhood anaemia in sub-Saharan Africa to focus on the population at risk, that is, women whose most recent delivery occurred at younger ages and those with short birth intervals. Encouraging contraceptive use and creating awareness about the importance of birth spacing among reproductive-age women would be more helpful.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".