Regional adiposity and markers of inflammation in pre-school age children
Bibliographic record
Abstract
In adults, upper body fat partially increases metabolic disease risk through increasing systemic inflammation. Our objective was to determine if this relationship exists in preschool-aged children. A subset of children (n = 71, 35 males), 3.7 ± 1.0 y, were studied from n = 515 children recruited from randomly selected daycares in Montréal, QC. According to WHO charts for 2-5 y, 49 children were healthy weight (HW) and 21 were overweight (OW). Adiposity was determined through dual-energy x-ray absorptiometry. Blood concentrations of C-reactive protein (CRP) and tumour necrosis factor alpha (TNFα) were determined via enzyme-linked immunosorbent and multiplex assays, respectively. OW children had higher (p = 0.03) android:gynoid ratio 0.50 ± 0.09 compared to HW children 0.56 ± 0.12, indicating excess fat was predominantly stored in the abdominal depot. CRP was higher (p = 0.01) in OW children 1.45 ± 2.02 mg/L compared to HW 0.74 ± 1.38 mg/L. Percent fat was correlated with CRP (r = 0.32; p < 0.01) and TNFα (r = 0.25; p = 0.04) concentrations. CRP also correlated with android adiposity (r = 0.24; p = 0.04) and TNFα correlated with gynoid adiposity (r = 0.24; p = 0.04). We observed that greater adiposity is associated with higher systemic inflammation in pre-school aged children. Future longitudinal studies are needed to understand the long term consequences of excess total and regional body fat in young children.
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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 | 0.000 | 0.001 |
| 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 | 0.000 |
| 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".