Infant and Maternal Morbidity Symptoms as Predictors for the Interruption of Exclusive Breastfeeding in Lima, Peru: A Prospective Study
Bibliographic record
Abstract
INTRODUCTION: The global prevalence of exclusive breastfeeding for 6 months is 48%. This analysis examined the relationship between infant and maternal morbidity symptoms and the interruption of exclusive breastfeeding. METHODS: Data from a cohort study among women living in a peri-urban community in Peru were used. Data were collected during pregnancy, birth, and the first 6 months postpartum among 179 dyads... RESULTS: After the first month, interruption of exclusive breastfeeding was almost twofold (adjusted odds ration [aOR] = 1.99, 95% confidence interval [CI]: 1.14, 3.45) more likely among infants with symptoms (e.g., diarrhea, cough) than those without. Maternal morbidity symptoms (e.g., gastrointestinal, respiratory) and breast problems were positively associated with interruption of exclusive breastfeeding throughout the first 6 months (aOR = 1.77, 95% CI: 1.11, 2.82 and aOR = 3.23, 95% CI: 1.84, 5.69, respectively). DISCUSSION: Mother-infant dyads often experience illness symptoms that are not contraindications to breastfeeding. Health professionals need to reinforce that exclusive breastfeeding should continue during illness.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".