Neonatal and Adolescent Adipocytokines as Predictors of Adiposity and Cardiometabolic Risk in Adolescence
Bibliographic record
Abstract
OBJECTIVE: This study aimed to examine associations of changes in leptin and adiponectin concentrations from birth to age 12 years with adolescent adiposity and cardiometabolic risk in the Health Outcomes and Measures of Environment (HOME) Study, a prospective birth cohort (Cincinnati, Ohio; N = 166). METHODS: Adiposity and cardiometabolic risk factors were assessed at age 12 years using anthropometry, dual-energy x-ray absorptiometry, and fasting serum biomarkers. Cardiometabolic risk scores were calculated by summing age- and sex- standardized z scores for individual cardiometabolic risk factors. RESULTS: Most serum adipocytokine concentrations at birth were not associated with adiposity or cardiometabolic risk outcomes. Leptin and adiponectin concentrations at age 12 years were associated with all outcomes in the expected direction. Adolescents with increasing (β: 4.2; 95% CI: 3.2 to 5.2) and stable (β: 2.2; 95% CI: 1.2 to 3.2) leptin concentrations from birth to age 12 years had higher cardiometabolic risk scores than adolescents with decreasing concentrations (reference group). Adolescents with increasing (e.g., fat mass index = β: -1.04; 95% CI: -1.27 to -0.80) and stable (β: 0.66; 95% CI: -0.92 to -0.40) adiponectin/leptin ratios had more favorable adiposity outcomes than adolescents with decreasing ratios. CONCLUSIONS: In this cohort, changes in leptin concentrations and adiponectin/leptin ratios over childhood were associated with adiposity and cardiometabolic risk scores, indicating that adipocytokine concentrations are potential biomarkers for predicting excess adiposity and cardiometabolic risk in adolescence.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".