Breastfeeding in women with diabetes: lower rates despite greater rewards. A population‐based study
Bibliographic record
Abstract
AIMS: To explore intention to breastfeed and breastfeeding rates in hospital and on discharge across women with pre-gestational or gestational diabetes mellitus, or no diabetes. METHODS: A retrospective cohort analysis was conducted using data from four Ontario hospitals. Women who delivered a viable infant between 1 April 2008 and 31 March 2010 were included in the study. Unadjusted and adjusted odds ratios were calculated for each outcome measure and were used to compare the breastfeeding rates among women with and without diabetes. RESULTS: After controlling for potential confounders, women with insulin-treated diabetes were less likely to intend to breastfeed, when compared with women without diabetes (adjusted odds ratio 0.49, 95% CI 0.27-0.89). In hospital, women with insulin-treated diabetes were least likely to breastfeed (odds ratio 0.42, 95% CI 0.26-0.67), followed by women with non-insulin-treated diabetes (odds ratio 0.50, 95% CI 0.26-0.96) and women with gestational diabetes (odds ratio 0.77, 95% CI 0.68-0.87) when compared with women without diabetes. On discharge, women with insulin-treated diabetes were least likely to breastfeed (odds ratio 0.38, 95% CI 0.24-0.60), followed by women with gestational diabetes (odds ratio 0.75, 95% CI 0.66-0.85); rates of breastfeeding among women with non-insulin-treated diabetes were comparable on discharge with those of women without diabetes. Women seeking care from an antenatal provider other than a physician were 2-3 times more likely to breastfeed in hospital and on discharge. CONCLUSIONS: Women with insulin-treated diabetes had the poorest outcomes with respect to breastfeeding rates. Gestational and non-insulin-treated diabetes were associated with lower rates of breastfeeding in hospital, while gestational diabetes was additionally associated with lower breastfeeding rates on discharge.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".