Association Between Intrapartum Factors and the Time to Breastfeeding Initiation
Bibliographic record
Abstract
Background/Objectives: Early breastfeeding initiation is strongly recommended. Reasons for delayed breastfeeding initiation often include intrapartum interventions such as induction of labor, opioid pain medication administration, epidural analgesia, and caesarean birth. The majority of existing studies examining the timeliness of breastfeeding initiation are from low- or middle-income countries. The objective of this study is to examine intrapartum interventions on the time to breastfeeding initiation in a cohort of mothers from a high-income country. Materials and Methods: A cohort of 1,277 new mothers was recruited within 24 hours after birth from 4 hospitals in Hong Kong from 2011 to 2012. Participants completed a self-administered questionnaire immediately after recruitment. The rates of intrapartum interventions and the time to the first breastfeed were collected from participants' hospital record. Results: Among participants, 575 (45.5%) initiated breastfeeding within 1 hour of birth and the median time to the first breastfeed was 1.5 hours. The use of opioid pain medication (adjusted hazard ratio [aHR]: 0.78, 95% confidence interval [CI]: 0.67–0.91), assisted vaginal birth (aHR: 0.74, 95% CI 0.56–0.97), and caesarean section (aHR: 0.30, 95% CI 0.25–0.36) were associated with delayed breastfeeding, whereas epidural analgesia and induction of labor had no effect on breastfeeding initiation. Natural birth (i.e., no intrapartum interventions) was also significantly associated with early breastfeeding initiation (aHR: 1.75, 95% CI 1.54–1.99). Conclusions: Breastfeeding initiation was delayed in participants who had a caesarean birth and who received opioid pain medication. These women may require additional support to initiate breastfeeding soon after birth.
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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 | 0.005 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".