Prevalence of low birth weight and its association with maternal body weight status in selected countries in Africa: a cross-sectional study
Bibliographic record
Abstract
OBJECTIVES: The present study aimed to estimate the prevalence of low birth weight (LBW), and to investigate the association between maternal body weight measured in terms of body mass index (BMI) and birth weight in selected countries in Africa. SETTING: Urban and rural household in Burkina Faso, Ghana, Malawi, Senegal and Uganda. PARTICIPANTS: Mothers (n=11 418) aged between 15 and 49 years with a history of childbirth in the last 5 years. RESULTS: The prevalence of LBW in Burkina Faso, Ghana, Malawi, Senegal and Uganda was, respectively, 13.4%, 10.2%, 12.1%, 15.7% and 10%. Compared with women who are of normal weight, underweight mothers had a higher likelihood of giving birth to LBW babies in all countries except Ghana. However, the association between maternal BMI and birth weight was found to be statistically significant for Senegal only (OR=1.961 (95% CI 1.259 to 3.055)). CONCLUSION: Underweight mothers in Senegal share a greater risk of having LBW babies compared with their normal-weight counterparts. Programmes targeting to address infant mortality should focus on promoting nutritional status among women of childbearing age. Longitudinal studies are required to better elucidate the causal nature of the relationship between maternal underweight and LBW.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".