Cohort profile: Mother and Infant Metabolome and Microbiome (MIMM) study, a prospective cohort study of mothers and infants in Boston, Massachusetts
Notice bibliographique
Résumé
Purpose Breastfeeding is beneficial to the health of both the mother and infant. Despite recommendations to breastfeed by organisations including the WHO and the American Academy of Pediatrics, rates of breastfeeding remain below public health goals. The Mother and Infant Metabolome and Microbiome (MIMM) study is a prospective cohort study of healthy mother-term infant dyads designed to comprehensively assess the perinatal, maternal, neonatal and infant factors that are associated with breastfeeding outcomes and human milk composition. Participants MIMM participants were recruited from two medical centres in Boston, Massachusetts, from 2019 to 2023 and are followed for 2 years. Dyads were included if the mother delivered a singleton infant at ≥37 weeks’ gestation, was discharged home <72 hours after vaginal delivery or <6 days after caesarean delivery, spoke English, planned to breastfeed (either exclusively or with formula supplementation) and was willing and able to conduct follow-up through 2 years. Dyads were excluded from the study if the infant was admitted to the neonatal intensive care unit for longer than 72 hours. A total of 156 dyads were enroled in the study; however, eight participants dropped out prior to hospital discharge and will be excluded from all analyses (ie, no data was collected), resulting in a final cohort sample size of 148 mother-infant dyads. Approximately 62% of participants were White, 20% were Black or African American, 11% were Asian and 7% were more than one or unknown race. The cohort was highly educated, with 87% of participants having at least a college degree. Median maternal pre-pregnancy body mass index was 24.8 kg/m 2 and infant gestational age was 39.3 weeks. Approximately 43% of infants were born via caesarean delivery, and 45.5% were female. Findings to date MIMM study procedures include longitudinal (1) collections of maternal blood, vaginal swab, stool and milk and infant blood and stool samples and (2) assessments of breastfeeding status, child neurodevelopment and growth and maternal health at birth, 6 weeks and 6, 12, 18 and 24 months. Data collection through 18 months is complete. The overall objective of the MIMM study is to identify potential targets to improve breastfeeding outcomes, human milk composition and ultimately, maternal and child health. Preliminary analyses, reported in conference presentations (with ongoing analyses and results manuscripts pending), have found that (1) mothers with higher levels of stress were less likely to be exclusively breastfeeding their infants at 6 weeks; (2) higher breastfeeding intensity was associated with greater postpartum weight loss at 6 weeks; (3) feeding type was a more relevant predictor of feeding frequency and volume compared with feeding mode; (4) infants who received exclusive human milk had higher food enjoyment compared with those who received any formula; and (5) infants of mothers with obesity had higher average feeding volume per feed. Future plans Data collection for the final 24-month visit is expected to be completed by August 2025. We expect that all sample assays will be completed by December 2025. Findings will continue to be submitted for presentation at scientific conferences, and we expect to publish the first findings from this cohort in manuscript format in 2025.
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 machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,001 |
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 source (Gemma direct ou Codex distillé), 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 ».