Digestible Carbohydrate Intake and Maternal-Infant Outcomes: A Systematic Review
Notice bibliographique
Résumé
Background. Optimal nutrition is needed to support individuals during pregnancy and placental development, fetal growth, and growth and development during infancy. Many foods contain digestible carbohydrates, or carbohydrates other than fiber/nondigestible carbohydrate. Digestible carbohydrates, including sugars and starches, are important sources of energy during these life stages. This review was designed to identify and summarize the evidence on the relationships between digestible carbohydrate intake during pregnancy and newborn size and development (Key Question 1) and gestational weight gain (Key Question 2), and between infant digestible carbohydrate intake and infant growth parameters, size, and body composition from birth to 24 months of age (Key Question 3). The results are intended to contribute to the update and expansion of the 2005 United States-Canadian Dietary Reference Intakes (DRIs) for macronutrients. Methods. A medical research librarian designed and conducted a search of Ovid MEDLINE®, EMBASE, and Cochrane CENTRAL from 2000 to April 2025. Researchers manually reviewed reference lists. Using a priori specified inclusion and exclusion criteria, we triaged abstracts and conducted a dual, independent review of full-text articles. Risk of bias was assessed using criteria based on study design. Meta-analyses were not conducted due to limited data and heterogeneity of studies; included studies were synthesized qualitatively and described in tables and text. Results. Searches identified 3,194 abstracts. Eight studies in 10 publications were included for the three Key Questions. One randomized controlled trial was rated low risk of bias and a second was rated high; three nonrandomized studies were rated moderate and three were rated high risk of bias. Identified studies yielded low strength of evidence of no difference in infant weight, and insufficient evidence for length, head circumference, or size (small or large for gestational age) at birth (Key Question 1) and low strength of evidence of no difference in gestational weight gain given different amounts of digestible carbohydrate intake during pregnancy (Key Question 2). Evidence was insufficient to reach conclusions about the relationship between digestible carbohydrate intake by infants and growth outcomes (weight, length, and head circumference) and body mass index or other body composition outcomes up to 24 months of age (Key Question 3). Conclusions. We identified a small number of studies resulting in findings of no differences in infant size at birth and gestational weight gain by amount of digestible carbohydrate consumed during pregnancy. There was insufficient evidence to draw a conclusion about the relationship between the amount of digestible carbohydrate consumed during infancy and growth parameters and body composition up to 24 months of age. Factors contributing to the limited evidence available to answer the key questions in this review include: “digestible carbohydrate” is not commonly used in the scientific literature to categorize dietary carbohydrates as the alternative to fiber/nondigestible carbohydrate; most studies identified, those included in or excluded from the evidence base, were not designed to answer this review’s key questions; and there is an increasing trend toward reporting dietary consumption patterns instead of isolated nutrients and using principal component analysis to categorize and analyze dietary consumption patterns. While both types of information are important to informing how diet affects health, analyses of patterns do not provide the specific quantitative information needed for a systematic review of the effect of digestible carbohydrate consumption on maternal and infant outcomes. The limited evidence and our concerns about the lack of methodologic standardization and the validity of dietary intake measurement used to estimate usual dietary intake during pregnancy and lactation and of infants consuming human milk reduced our confidence in the findings and support the need for additional and more rigorous research on this topic.
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 | 0,008 | 0,032 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,009 | 0,008 |
| Bibliométrie | 0,007 | 0,009 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,003 | 0,002 |
| Science ouverte | 0,002 | 0,001 |
| Intégrité de la recherche | 0,002 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,005 | 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 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 ».