The association between body mass index trajectories and cardiometabolic risk in young children
Bibliographic record
Abstract
BACKGROUND: Rapid growth is associated with increased cardiometabolic risk (CMR) in adolescence and adulthood. Little is known about whether the association between rapid growth and increased CMR originates in early childhood. OBJECTIVES: To identify age and sex standardized body mass index (zBMI) trajectories and to examine the association between zBMI trajectories and CMR outcomes in children 0 to 60 months. STUDY DESIGN: A longitudinal cohort study was conducted through The Applied Research Group for Kids (TARGet Kids!) in Toronto, Canada. Participants had repeated measures of weight and length or height performed from birth to 60 months of age. Latent class mixed modelling was used to identify the zBMI trajectories. Linear regressions were performed to determine the association between zBMI trajectories and the primary outcome, a CMR score, quantified as the sum of age- and sex- standardized waist circumference, systolic blood pressure, glucose, log-triglycerides and negative high-density lipoprotein cholesterol (HDL-C), divided by √5. Secondary outcomes were the individual components of the CMR formula as well as diastolic blood pressure and non-HDL-C. RESULTS: Four BMI trajectories were identified among the 1166 children. After adjusting for all covariates, children in the rapidly accelerating trajectory had increased total CMR score (β = 1.38, 95% CI 0.77; 1.99, P < .001) and increased waist circumference score (β = 2.39, 95% CI 1.92; 2.86, P < .001) compared to the stable low group. CONCLUSIONS: Rapid growth during early childhood is associated with increased CMR in preschool children, largely driven by larger waist circumference.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".