Longitudinal body mass index trajectories at preschool age: children with rapid growth have differential composition of the gut microbiota in the first year of life
Bibliographic record
Abstract
BACKGROUND/OBJECTIVE: The steep rise in childhood obesity has emerged as a worldwide public health problem. The first 4 years of life are a critical window where long-term developmental patterns of body mass index (BMI) are established and a critical period for microbiota maturation. Understanding how the early-life microbiota relate to preschool growth may be useful for identifying preventive interventions for childhood obesity. We aim to investigate whether longitudinal shifts within the bacterial community between 3 months and 1 year of life are associated with preschool BMI z-score trajectories. METHODS: BMI trajectories from birth to 5 years of age were identified using group-based trajectory modeling in 3059 children. Their association with familial and environmental factors were analyzed. Infant gut microbiota at 3 months and 1 year was defined by 16S RNA sequencing and changes in diversity and composition within each BMIz trajectory were analyzed. RESULTS: Four BMIz trajectories were identified: low stable, normative, high stable, and rapid growth. Infants in the rapid growth trajectory were less likely to have been breastfed, and gained less microbiota diversity in the first year of life. Relative abundance of Akkermansia increased with age in children with stable growth, but decreased in those with rapid growth, abundance of Ruminococcus and Clostridium at 1 year were elevated in children with rapid growth. Children who were breastfed at 6 months had increased levels of Sutterella, and decreased levels of Ruminococcus and Clostridium. CONCLUSION: This study provides new insights into the relationship between the gut microbiota in infancy and patterns of growth in a cohort of preschool Canadian children. We highlight that rapid growth since birth is associated with bacteria shown in animal models to have a causative role in weight gain. Our findings support a novel avenue of research targeted on tangible interventions to reduce childhood obesity.
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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 | 0.001 |
| 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) | 0.002 | 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".