Growth During Infancy and Early Childhood and Its Association With Metabolic Risk Biomarkers at 11.5 Years of Age
Bibliographic record
Abstract
The evidence that fetal life and early infancy are "critical" or "sensitive" ages for later development of cardiometabolic disease is based on flawed methods for comparing different age periods. Moreover, most previous studies have limited their focus to weight gain, rather than growth in length/height or body mass index (weight (kg)/height (m)2). We undertook a secondary analysis of data from the Promotion of Breastfeeding Intervention Trial (1996-2010), a birth cohort study nested within a large cluster-randomized trial in the Republic of Belarus, that had repeated measurements of weight and length/height taken from birth to 11.5 years of age. We used mixed-effects linear models to analyze associations of changes in standardized weight, length/height, and body mass index during 5 age periods (conception to birth, birth to age 3 months, ages 3-12 months, ages 12 months-6.5 years, and ages 6.5-11.5 years) with fasting glucose, insulin, insulin resistance, β-cell function, and adiponectin at age 11.5 years. We observed strong associations between the metabolic markers and all 3 growth measures, with the largest magnitudes being observed during the latest age period (ages 6.5-11.5 years) and negligible associations during gestation and the first year of life. Later age periods appear more "sensitive" than earlier periods to the adverse metabolic association with rapid growth in childhood.
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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 | 0.003 |
| 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 | 0.000 | 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".