Rates and determinants of breastfeeding initiation in women with and without epilepsy: A 25-year study
Bibliographic record
Abstract
PURPOSE: To examine the rates and determinants of breastfeeding initiation (BFI) amongst women with epilepsy (WWE) and women without epilepsy (WWoE) in Manitoba, Canada. METHODS: We conducted a retrospective cohort study using province-wide health databases from 1995 to 2019. Annual BFI rates for WWE and WWoE were examined. Multivariable logistic regression models were used to quantify the association between maternal and infant characteristics and BFI in both groups. RESULTS: During the study period, 1,331 pregnant WWE and 357,334 WWoE were examined. Among WWE, 70.9 % initiated breastfeeding compared to 81.8 % among WWoE. We observed a significant small increase in yearly trends of BFI in both WWE (β=0.45, p = 0.008) and WWoE (β=0.23, p < 0.001). In WWE, BFI was associated with caesarean delivery (aOR=0.72,95 % CI: 0.53-0.97), chronic pain (aOR=0.67,95 % Cl: 0.46-0.97), lower income (aOR=0.34,95 % Cl: 0.26-0.44), and gestational age (aOR= 1.09,95 % CI:1.01-1.18). In WWoE, BFI was associated with chronic pain (aOR=0.83,95 % Cl: 0.80-0.86), lower income (aOR=0.45, 95 %CI:0.44-0.46), mood and anxiety disorder (aOR=0.84,95 % CI:0.81-0.86), and gestational age (aOR=1.13,95 % Cl:1.12-1.14). The use of any ASM (aOR=0.66,95 % Cl:0.51-0.85), new generation (aOR=0.86,95 % Cl: 0.62-1.20), polytherapy (aOR=0.46,95 % Cl: 0.31-0.69) and gabapentin (aOR=0.49,95 % Cl: 0.17-1.24) reduced the likelihood of BFI among WWE. CONCLUSION: BFI was approximately 10 % lower in WWE compared to WWoE. Determinants such as low income, ASM use, and comorbidities were significant contributors to a reduced BFI in both groups. Targeted counselling for WWE on breastfeeding benefits is essential. Further research is needed to investigate breastfeeding continuation in WWE.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".