Exclusive breastfeeding in hospital predicts longer breastfeeding duration in Canada: Implications for health equity
Bibliographic record
Abstract
BACKGROUND: Breastfeeding has many established health benefits for women and children. We examined the association between maternal education, newborn feeding in hospital, and long-term breastfeeding duration. METHODS: We studied 3195 Canadian mother-infant dyads in the CHILD pregnancy cohort. Newborn feeding was documented from hospital records. Caregivers reported sociodemographic factors and infant feeding at 3, 6, 12, 18, and 24 months. RESULTS: Overall, 97% of newborns initiated breastfeeding and 74% were exclusively breastfed in hospital. Exclusively breastfed newborns were ultimately breastfed longer compared with those who received formula supplementation during their hospital stay (median 11.0 vs 7.0 months, P < .001). After controlling for maternal age, ethnicity, birth mode, and gestational age, exclusively breastfed newborns had a 21% reduced risk of breastfeeding cessation (HR = 0.79, 0.71-0.87). This effect was strongest among women without a postsecondary education (HR = 0.65, 0.53-0.79). DISCUSSION: Exclusive breastfeeding in hospital is associated with longer breastfeeding duration, particularly among women of lower socioeconomic status. Initiatives that support exclusive breastfeeding of newborns in hospital could improve long-term breastfeeding rates and help reduce health inequities arising in early life.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".