Temporal and geographic variability of bisphenol levels in humans: A systematic review and meta-analysis of international biomonitoring data
Bibliographic record
Abstract
INTRODUCTION: Bisphenols are endocrine-disrupting chemicals known to contribute to chronic disease across the lifespan. With increased awareness of their health effects, changes in regulation and health behaviors have contributed to reductions in urinary bisphenol A (BPA) levels in the United States, Canada, and Europe. However, global trends in bisphenols outside these regions, especially bisphenol S (BPS) exposure, have been less studied. AIM: We examine trends in urinary BPA and BPS concentration in non-occupationally exposed populations, where representative data at a country level is unavailable. METHODS: index, and funnel plots. RESULTS: , 95% CI: [-0.50, -0.08], respectively). In the sensitivity analyses excluding studies with geometric or arithmetic mean values, each displayed significant shifts from the main findings with some consistent outcomes occurring internationally and/or in specific regions. Heterogeneity was high across studies, suggesting possible bias in our estimations. CONCLUSIONS: Our findings provide evidence for concern about increasing population exposure to BPA and BPS. Further studies estimating attributable disease burden and costs at regional and global levels are warranted to show these chemicals' impact on population health and economies.
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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 | 0.015 | 0.036 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.013 | 0.027 |
| Bibliometrics | 0.009 | 0.013 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 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".