Association of breastfeeding, maternal anthropometry and body composition in women at 30 years of age
Bibliographic record
Abstract
This study aimed at assessing the association of breastfeeding with maternal body mass index (BMI), waist circumference, fat mass index, fat free mass index, android/gynoid fat ratio and bone mineral density. In 1982, the maternity hospitals in Pelotas, Rio Grande do Sul State, Brazil, were daily visited and all live births were identified and examined. These subjects underwent follow-up for several times. At 30 years of age, the participants were interviewed and examined. Parous women provided information on parity and duration of breastfeeding. Multiple linear regression was used in the multivariate analysis, controlling for genomic ancestry, family income, schooling and smoking at 2004-2005. After controlling for confounding factors, breastfeeding was inversely associated with BMI and fat mass index, whereas breastfeeding per live birth was negatively associated with BMI, waist circumference and fat mass index. Women who had had a child in the last 5 years and had breastfed, showed lower BMI (β = -2.12, 95%CI: -4.2; -0.1), waist circumference (β = -4.46, 95%CI: -8.3; -0.6) and fat mass index (β = -1.79, 95%CI: -3.3; -0.3), whereas no association was observed among those whose last childbirth was > 5 years, but the p-value for the tests of interaction were > 0.05. Our findings suggest that breastfeeding is associated with lower BMI and other adiposity measures, mostly in the first years after delivery. Besides that, it has no negative impact on bone mineral density.
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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 | 0.001 |
| 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".