Marked Influence of Adiposity on Laboratory Biomarkers in a Healthy Cohort of Children and Adolescents
Bibliographic record
Abstract
BACKGROUND: The prevalence of pediatric obesity is increasing worldwide and strongly associates with metabolic abnormalities, including inflammation, insulin resistance, and dyslipidemia. This study assessed the influence of 3 measures of adiposity on levels of routinely assessed biochemical markers in apparently healthy children and adolescents. METHODS: The influence of adiposity on 35 biochemical markers was examined in the Canadian Laboratory Initiative on Pediatric Reference Intervals (CALIPER) cohort of healthy children and adolescents by comparing serum biomarker levels between subjects with a normal weight, overweight, and obese body mass index (BMI). The cohort comprised 1332 subjects 5.1 to 19.0 years of age with a BMI ranging from 13.4 to 65.0 kg/m2. The association between each biochemical marker and BMI, waist circumference, and waist-to-height ratio z-scores was assessed, while adjusting for age and sex. Reference intervals were established for all biochemical markers before and after removing overweight/obese subjects. RESULTS: In children and adolescents, levels of 13 routinely assessed biochemical markers, including alanine aminotransferase, apolipoprotein B, complement components 3 and 4, cholinesterase, high sensitivity C-reactive protein, gamma-glutamyl transferase, haptoglobin, high-density lipoprotein cholesterol, iron, transferrin, triglycerides, and uric acid, were significantly different between BMI categories. BMI, waist circumference, and/or waist-to-height ratio were significantly associated with the serum concentration of 24 of the 35 markers examined, after adjusting for age and sex. CONCLUSIONS: Excess adiposity significantly influences circulating levels of routinely assessed laboratory markers, most notably liver enzymes, lipids/lipoproteins, inflammatory markers, and uric acid in children and adolescents. Although it is unknown whether altered biochemical marker levels in subjects with overweight/obesity reflect health or indolent disease, clinicians should be aware of the effect of weight status on several laboratory tests.
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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 | 0.001 | 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".