Effects of Breastfeeding on Weight Changes in Family-based Pediatric Obesity Treatment
Bibliographic record
Abstract
Research indicates that breastfeeding may provide protective effects against the development of obesity; however, breastfed children may still become obese because of the obesogenic environment. This study is designed to examine the effects of retrospective recall of breastfeeding on weight changes in children participating in a 6-month behavioral treatment program for childhood obesity. The independent variable of breastfeeding was defined as children who were exclusively breastfed for 4 weeks (excluding water or medication) versus those who were never breastfed. Child percent overweight and body mass index changes during 6 and 12 months were evaluated for 94 families based on mother report of breastfeeding status using analysis of covariance, controlling for socioeconomic status and initial child weight status. Data were compiled for secondary analysis from pediatric obesity randomized controlled outcome studies evaluating core components of family-based treatments. Results showed that, compared with nonbreastfed (formula) children (n = 28), breastfed children (n = 66) showed significantly larger reductions in (mean +/- SEM) percent overweight at 6 months (-15.2 +/- 1.1 vs -10.2 +/- 1.7, p <.05) and 1 year (-10.3 +/- 1.3 vs -5.9 +/- 1.8, p <.05). Similarly, breastfed children showed greater reductions in body mass index at 6 months (-2.1 +/- 0.19 vs -1.1 +/- 0.28) and 1 year (-0.8 +/- 0.23 vs +0.1 +/- 0.32). Findings suggest the beneficial effects of breastfeeding may extend beyond obesity prevention to include improved outcome in family-based pediatric obesity treatment. Potential mechanisms relating breastfeeding, obesity prevention, and enhanced outcome in pediatric obesity treatment are discussed.
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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 | 0.001 | 0.004 |
| 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".