Association between maternal antenatal care visits and newborn low birth weight in Bangladesh: a national representative survey
Bibliographic record
Abstract
<ns4:p> <ns4:bold>Background:</ns4:bold> Low Birth Weight (LBW) is a global health concern for childhood mortality and morbidity. The objectives of this study were to assess the association between the number of Antenatal Care Visits (ANC) and LBW among Bangladeshi newborns, and to identify the demographic and socio-economic predictors of LBW. </ns4:p> <ns4:p> <ns4:bold>Methods:</ns4:bold> Our present cross-sectional study is based on the secondary data of the Bangladesh Demography and Health Survey (BDHS) 2014. Complete data of 4,235 (weighted) mother-child pairs were included in the analysis. </ns4:p> <ns4:p> <ns4:bold>Results:</ns4:bold> The overall prevalence of LBW among newborns were found to be 19.3% (95% CI: 17.8-20.9). Among the mothers who received antenatal care services 1-3 times during pregnancy, 35% had less possibility of having LBW babies [COR = 0.65, 95% CI: 0.50-0.85]. The association remained significant after adjusting the analysis with the sex of the newborn, administrative regions (division), maternal educational status, mother’s weight status and fathers’ occupation [AOR = 0.74, 95% CI: 0.55-0.99]. Additionally, the sex of the newborn, division, maternal education, maternal weight status, and fathers’ occupational status were found to be significantly associated with LBW. </ns4:p> <ns4:p> <ns4:bold>Conclusion:</ns4:bold> Increasing the coverage of antenatal services and enabling mothers to receive quality antenatal services may substantially contribute to reducing the prevalence of LBW in Bangladesh. </ns4:p>
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How this classification was reachedexpand
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.002 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".