Urinary 2,5-dicholorophenol and 2,4-dichlorophenol concentrations and prevalent disease among adults in the National Health and Nutrition Examination Survey (NHANES)
Bibliographic record
Abstract
Objective To test cross-sectional associations between urinary concentrations of 2,5-dichlorophenol (2,5-DCP) and 2,4-dichlorophenol (2,4-DCP) with the prevalence of cardiovascular disease (CVD), cancer, lung disease, thyroid problems and liver conditions. Methods Logistic regression was used to evaluate associations of urinary concentrations of 2,5-DCP and 2,4-DCP with prevalence of various medical conditions among 3617 National Health and Nutrition Examination Survey participants from 2007–2008 and 2009–2010. ORs and 95% CIs for each disease were estimated. All regression models were adjusted for urinary creatinine. Results We observed a monotonically increasing association between quartiles of 2,5-DCP and prevalence of CVD. After adjustment for sociodemographic and lifestyle characteristics, participants with the highest versus lowest quartile of urinary 2,5-DCP had an OR=1.84 (95% CI 1.26 to 2.70) (p linear trend=0.006). The association was similar with further adjustment for established clinical CVD risk factors. Higher 2,5-DCP was also associated with prevalence of all cancers combined (OR Q4 vs Q1 =1.50 (95% CI 1.00 to 2.26); p trend=0.05) and, in exploratory analyses, with gynaecological cancers (OR Q4 vs Q1 =4.15 (95% CI 1.51 to 11.40; p trend=0.01)). No associations were detected between 2,5-DCP and lung diseases, thyroid problems or liver conditions, nor between 2,4-DCP and prevalent disease. Conclusion In this nationally representative study, higher urinary 2,5-DCP concentrations were associated with greater prevalence of CVD and all cancers combined. Further examination may be warranted to assess whether chronic exposure to 2,5-DCP is associated with incidence of adverse health outcomes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".