Association between Breastfeeding, Maternal Weight Loss and Body Composition at 3 Months Postpartum
Bibliographic record
Abstract
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.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".