Association between Breastfeeding, Maternal Weight Loss and Body Composition at 3 Months Postpartum
Notice bibliographique
Résumé
Background Pregnancy results in substantial increases in maternal body weight that may persist through postpartum. Weight gained during pregnancy and retained postpartum has been previously shown to contribute to obesity in women of childbearing age. It is often suggested that breastfeeding (BF) is an efficient means of promoting postpartum weight loss (PPWL) and favorable changes in body composition (reduction in body fat). However, the influence lactation has on short term changes in body weight and body composition have not been well‐described in contemporary women. Objective To explore the relationships between BF practices, PPWL, and % body fat at 3 months postpartum. Methods Fifty women (32.6 ± 4.1 years; 3.2 ± 0.2 months postpartum) reported their pre‐pregnancy weight and highest weight during pregnancy. Height, current weight, and % body fat (dual energy x‐ray absorptiometry) were measured. Women were categorized as any BF or non‐BF. For those who breast‐fed, their BF practices (number of feeds/day; total time feeding [min/day]; milk volume expressed [ml/day]; energy cost of lactation [kcal/day]) were estimated using a combination of infant test weighing (1 day) and a 3‐day BF diary. The PPWL was calculated as absolute (kg) and proportional (%) change from highest weight in pregnancy after subtracting baby birth weight. Differences in PPWL and % body fat between BF and non‐BF were assessed by independent t‐tests. Associations between BF practices, PPWL, and % body fat were assessed using Pearson correlation coefficients. Logistic regression was used to evaluate associations between BF and PPWL and % body fat; pre‐pregnancy BMI was included in the models for these analyses as it significantly correlated with PPWL. For all analyses statistical significance was set as p<0.05. Results The BF group (n=39) did not differ from non‐BF (n=11) for absolute PPWL (7.3 ± 3.7 vs. 5.0 ± 3.4kg), % PPWL (9.3 ± 4.8 vs 5.9 ± 4.3 %) and % body fat (37.6 ± 8.0% vs. 43.3 ± 6.9%) respectively. The BF women fed babies 9 ± 3 feeds/day for a total of 161 ± 74 min/day. Milk volume expressed was 738 ± 245 ml/day for an estimated energy cost of lactation of 653 ± 215 kcal/day. Absolute PPWL, % PPWL and % total body fat were not associated with any breastfeeding practices. In regression models, pre‐pregnancy BMI was significantly associated with PPWL (β = −0.4, p= 0.001) and % body fat (β = 1.1, p < 0.001) although BF was not. Having a higher pre‐pregnancy BMI was associated with less PPWL and higher % body fat at 3 months postpartum. Conclusions At 3 months postpartum, BF appears to have little association with PPWL or % body fat, while pre‐pregnancy BMI is significantly associated with both. This reinforces the idea that having a BMI in a healthy range prior to pregnancy may be important for postpartum weight management. Detailed assessment of factors affecting energy balance including intake and components of energy expenditure beyond 3 months are critical to understanding trajectories of weight and body composition change postpartum Support or Funding Information The ENRICH Program is funded through the Alberta Innovates ‐ Health Solutions, Collaborative Research and Innovation Opportunity (CRIO) team grant.
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 | 0,000 | 0,002 |
| 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 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 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 ».