Urinary Phthalates and Increased Insulin Resistance in Adolescents
Bibliographic record
Abstract
BACKGROUND: Di-2-ethylhexylphthalate (DEHP) is an environmental chemical commonly found in processed foods. Phthalate exposures, in particular to DEHP, have been associated with insulin resistance in adults, but have not been studied in adolescents. METHODS: Using cross-sectional data from 766 fasting 12- to 19-year-olds in the 2003-2008 NHANES, we examined associations of phthalate metabolites with continuous and categorical measures of homeostatic model assessment of insulin resistance (HOMA-IR). RESULTS: Controlling for demographic and behavioral factors, diet, continuous age, BMI category, and urinary creatinine, for each log (roughly threefold) increase in DEHP metabolites, a 0.27 increase (95% confidence interval 0.14-0.40; P < .001) in HOMA-IR was identified. Compared with the first tertile of DEHP metabolite in the study population (14.5% insulin resistant), the third tertile had 21.6% prevalence (95% confidence interval 17.2%-26.0%; P = .02). Associations persisted despite controlling for bisphenol A, another endocrine-disrupting chemical commonly found in foods, and HOMA-IR and insulin resistance were not significantly associated with metabolites of lower molecular weight phthalates commonly found in cosmetics and other personal care products. CONCLUSIONS: Urinary DEHP concentrations were associated with increased insulin resistance in this cross-sectional study of adolescents. This study cannot rule out the possibility that insulin-resistant children ingest food with higher phthalate content, or that insulin-resistant children excrete more DEHP.
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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 | 0.000 | 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".