Early Infant Feeding and BMI Trajectories in the First 5 Years of Life
Bibliographic record
Abstract
OBJECTIVE: This study examined the relative impact of breastfeeding duration and timing of solids introduction on BMI z score (BMIz) trajectory in early childhood. METHODS: This study conducted secondary analyses of data from the Melbourne Infant Feeding, Activity and Nutrition Trial (InFANT) Program (N = 542), a prospective cohort study with data collected at birth and 3, 9, 18, 42, and 60 months. Linear spline multilevel models were performed. RESULTS: Differential growth rates were observed from birth to 3 months and from 9 to 18 months by breastfeeding duration (≥ 6 vs. < 6 months) and timing of solids introduction (before vs. after 6 months). Children who were breastfed for ≥ 6 versus < 6 months had lower BMIz at all ages from 3 to 60 months. The difference remained after adjusting for child and maternal factors, and the adjusted mean differences in BMIz at 3, 9, 18, 42, and 60 months were -0.34, -0.44, -0.13, -0.19, and -0.23, respectively. Children who received solids before versus after 6 months of age had higher BMIz at 18 and 42 months, but adjustment for child and maternal factors attenuated these differences. CONCLUSIONS: Longer breastfeeding duration was associated with lower BMIz to 5 years of age, providing further support for infant feeding guidelines to prolong breastfeeding duration for healthy growth.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".