Association of urinary polycyclic aromatic hydrocarbons and obesity in children aged 3–18: Canadian Health Measures Survey 2009–2015
Bibliographic record
Abstract
Polycyclic aromatic hydrocarbons (PAHs) may contribute to obesity. Childhood obesity is a strong predictor of adult obesity and morbidity; however, the relationship between PAHs and obesity in young children (e.g., aged 3-5) has not been studied. We examined the association between urinary PAH metabolites and measures of obesity in children. We analyzed data from 3667 children aged 3-18 years who participated in the Canadian Health Measures Survey (CHMS, 2009-2015). We ran separate multivariable linear models to estimate the association between quartiles of PAH metabolites and each of body mass index (BMI) percentile, waist circumference (WC), and waist-to-height ratio (WHtR) in the total population, as well as in the age subgroups 3-5, 6-11, and 12-18, adjusting for age, sex, ethnicity, education, income quintile, diet, creatinine, and exposure to environmental tobacco smoke. A multinomial logistic regression model estimated adjusted odds ratios for risk of central obesity. BMI, WC, and WHtR were positively associated with total PAH and naphthalene metabolites in the total population aged 3-18 and in age groups 6-11 and 12-18. In 3-5 year olds, WHtR, but not BMI, was significantly associated with total PAH, naphthalene, and phenanthrene metabolites. Overall, those in the highest quartile for naphthalene or total PAH metabolites had three times greater odds of having central obesity compared with those in the lowest quartile. Urinary PAH metabolites are associated with WHtR, an indicator of central obesity and predictor of health risks associated with obesity, in children as young as 3-5.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".