An Investigation of Patterns and Factors Associated with Exclusive Breast Feeding in Northern Ghana
Bibliographic record
Abstract
Introduction: The main aim of this study was to assess the practice of exclusive breastfeeding (EBF) and explore its determinants in Tamale Metropolis, Northern Ghana. Methods: In this analytical cross-sectional study, systematic random sampling was used to select 355 mother- infant pairs between 0-6 months from among consenting mothers attending post natal care at the Tamale Teaching and West Hospitals in the Tamale Metropolis. Results: The prevalence of EBF among infants < 6 months in the Tamale Metropolis for the past 24 hours was 92.1 % but it was 75.5 % in the one month prior to the study. In logistic regression analyses, factors that had significant positive association with EBR were institutional delivery, current mother’s employment, maternal motivation and household wealth index. Compared to home delivery, women who delivered at a health institution were five times more likely to practice EBF (Adjusted odds ratio [AOR] = 5.17, CI: 2.45 – 10.90). Petty traders were four times more likely to exclusively breastfeed, compared to women who were unemployed (A OR = 4.05, CI: 1.93 – 8.51). EBF provided 80 % (Adjusted OR = 0.2, CI: 0.08-0.37) protection against chronic malnutrition whilst high household index reflecting socio-economic status provided only 10 % protection against chronic malnutrition in the study sample (Adjusted OR = 0.9, CI: 0.81- 0.98). Conclusion and Recommendation: Strategies that target improving knowledge and skills on lactation management among women, as well as strategies to improve health facility delivery especially among non-working mothers, may help to improve EBF in Northern Ghana.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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".