Hospital Formula Supplementation Postbreastfeeding Initiation, Neighborhood Economy, and Race
Notice bibliographique
Résumé
Importance: Breastfeeding supports lifelong health, but socioeconomic and racial disparities persist. Biases in hospital formula supplementation practices may be an underlying contributor. Objective: To examine whether nonmedically indicated hospital formula supplementation of term-born breastfed newborns is associated with neighborhood socioeconomic status and/or maternal race. Design, Setting, and Participants: Provincial registry data were used to build a cohort of all live births of term-born singleton infants who initiated breastfeeding in Ontario, Canada, hospitals from April 1, 2015 through March 31, 2021, and for whom prenatal screening data were available. Of 570 936 eligible births, 148 888 were excluded, primarily due to missing outcome data, preterm birth, or not initiating breastfeeding. These data were analyzed from December 2023 through October 2025. Exposures: The 2 exposures were socioeconomic status, derived by linking maternal postal codes with 2021 Ontario Marginalization Index neighborhood-level quintiles for material resources, and maternal race (Asian, Black, White, or other [Indigenous, multiracial, or unknown race]), determined from prenatal screening data. Main Outcome and Measure: The primary outcome was nonmedically indicated formula supplementation, determined from hospital feeding records. Results: This cohort included 422 048 maternal-infant dyads, 28% of whom were in the Asian racial group, 7% in the Black racial group, 59% in the White racial group, and 5% in the other racial group. Overall, 27% of infants received nonmedically indicated formula supplementation, with an increase from 23% to 32% over the study period. Participants in the Asian, Black, and other racial groups were more likely than those in the White group to be in the most marginalized socioeconomic quintile (20%, 43%, and 23% vs 16%). Risk of nonmedically indicated formula supplementation increased in a gradient across quintiles of increasing socioeconomic marginalization (quintile 5 vs quintile 1: adjusted relative risk [aRR], 1.68; 95% CI, 1.64-1.72) and was significantly elevated for the Asian (aRR, 2.69; 95% CI, 2.64-2.74), Black (aRR, 2.07; 95% CI, 2.01-2.13), and other (aRR, 1.43; 95% CI, 1.39-1.48) racial groups compared with the White group. Conclusions and Relevance: In this population-level analysis, nonmedically indicated formula supplementation prevalence was high and increased over time, with elevated risk associated with socioeconomic marginalization and maternal racialization. Increased hospital adherence to breastfeeding support guidelines is needed to improve health equity.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».