Donor breast milk acceptability in Muslim populations in Canada
Bibliographic record
Abstract
PURPOSE: Human breast milk is identified as the best option for infants, and all efforts should be made to promote human milk feeding, even when a mother is unable to breastfeed her child. Donor breast milk (DBM) has been associated with improved outcomes over the use of preterm formula. Muslims living in Western countries may object to DBM use for their infant in the neonatal intensive care unit due to milk kinship, created when a non-biological mother nurses an infant. This review aims to educate clinicians on how these beliefs may impact their practice and how to communicate the benefits of DBM to Muslim patients. SUMMARY OF CONTENT: After delivering prematurely, a woman may have difficulty breastfeeding. Milk banks in North America pool the milk of up to 5 women, which does not pose a problem for most in the Western world. SYSTEMATIC APPROACH USED: Three databases; PubMed, Scopus and Web of Science were reviewed for relevant articles. Refence lists were verified for additional sources. A total of twelve articles were found and reviewed. CONCLUSIONS: Muslim religious officials have released a Fatwa (a ruling on a subject in Islamic law) supporting the use of DBM among Muslims. Clinicians can inform their Muslim patients that DBM use does not establish milk kinship and can be used as nutritional therapy for their preterm infants. RECOMMENDATIONS: Dietitians can educate Muslim patients on the acceptability of DBM. It is likely these families have not been made aware of the acceptability of DBM prior to having a premature infant. SIGNIFICANCE TO THE FIELD OF DIETETICS: In the past several decades, the number of Muslim immigrants in Canada has increased, thus Canadian dietitians working in NICU settings are more likely to encounter the concept of milk kinship. Dietitians need to be aware of these religious concerns.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| 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".