Determinants of continued breastfeeding in children aged 12–23 months in three regions of Haiti
Bibliographic record
Abstract
Objectives: To identify the prevalence and determinants of continued breastfeeding in Haitian children aged 12-23 months. Methods: Three cross-sectional surveys were conducted yearly during the summers of 2017 to 2019 as part of a 4-year (2016-2020) multisectoral maternal and infant health initiative in the regions of Les Cayes, Jérémie, and Anse d'Hainault in Haiti. A total of 455 children 12-23 months of age and their mothers participated in the study. A child was considered to be continuing breastfeeding if the mother reported giving breast milk in the 24-hour dietary recall. Unadjusted and adjusted prevalence ratios were estimated, and associations were assessed between continued breastfeeding and explanatory factors related to sociodemographic characteristics, household food security, maternal nutrition, and breastfeeding knowledge and practices. Results: The prevalence of continued breastfeeding was 45.8%. Continued breastfeeding was significantly more prevalent among younger children, children who did not have a younger sibling, children whose mother was not pregnant, those living in the Jérémie region, children who had been exclusively breastfed for less than 1 month, and children whose mother knew the World Health Organization's recommendation for continued breastfeeding up to 2 years or beyond. Conclusions: The study results highlight the need for geographically equitable access to tailored and adequate health services and education that support breastfeeding in a way that is compatible with the local context.
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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 | 0.001 | 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".