Potential interaction between timing of infant complementary feeding and breastfeeding duration in determination of early childhood gut microbiota composition and <scp>BMI</scp>
Bibliographic record
Abstract
BACKGROUND: Introducing complementary foods other than breastmilk or formula acutely changes the infant gut microbiota composition. However, it is unknown whether the timing of introduction to complementary foods (early vs. late) in infancy is associated with early childhood gut microbiota and BMI, and if these associations depend on breastfeeding duration. OBJECTIVE: Our primary objective was to investigate whether timing of infant complentary feeding with solid foods is associated with early childhood gut microbiota composition and BMI-z, and whether these associations differ by duration of breastfeeding. METHODS: We used data from a Canadian pre-birth cohort followed till age 5 years. We examined timing of introduction to solid foods with the gut microbiota, determined by 16S rRNA gene sequencing of stool collected at 5 years of age, and age-and-sex specific BMI-z. We conducted analyses before and after stratifying by breastfeeding duration, and adjusted for delivery mode, gestational age and birth weight. RESULTS: Of the 392 children in the analysis, 109 (27.8%) had early (≤4 months) solids. The association between early (vs later) solids and BMI-z at 5 years was modified by breastfeeding status at 4 months (P = .06). Among children breastfed >4 months, early (vs later) solids were associated with differential relative abundance of 6 bacterial taxa, including lower Roseburia, and 0.30 higher BMI-z (95% CI: 0.05, 0.55) at 5 years. In children breastfed <4 months, early solids were associated with differential relative abundance of 9 taxa, but not with child BMI-z. CONCLUSIONS: Early (vs. later) introduction to solid foods in infancy is associated with altered gut microbiota composition and BMI in early childhood, however these associations differ by duration of breastfeeding.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".