Dioxin Exposure and Age of Pubertal Onset among Russian Boys
Bibliographic record
Abstract
BACKGROUND: Animal data demonstrate associations of dioxin, furan, and polychlorinated biphenyl (PCB) exposures with altered male gonadal maturation. It is unclear whether these associations apply to human populations. OBJECTIVES: We investigated the association of dioxins, furans, PCBs, and corresponding toxic equivalent (TEQ) concentrations with pubertal onset among boys in a dioxin-contaminated region. METHODS: Between 2003 and 2005, 499 boys 8-9 years of age were enrolled in a longitudinal study in Chapaevsk, Russia. Pubertal onset [stage 2 or higher for genitalia (G2+) or testicular volume (TV) > 3 mL] was assessed annually between ages 8 and 12 years. Serum levels at enrollment were analyzed by the Centers for Disease Control and Prevention, Atlanta, Georgia, USA. We used Cox proportional hazards models to assess age at pubertal onset as a function of exposure adjusted for potential confounders. We conducted sensitivity analyses excluding boys with pubertal onset at enrollment. RESULTS: The median (range) total serum TEQ concentration was 21 (4-175) pg/g lipid, approximately three times higher than values in European children. At enrollment, boys were generally healthy and normal weight (mean body mass index, 15.9 kg/m2), with 30% having entered puberty by G2+ and 14% by TV criteria. Higher dioxin TEQs were associated with later pubertal onset by TV (hazard ratio = 0.68, 95% confidence interval, 0.49-0.95 for the highest compared with the lowest quartile). Similar associations were observed for 2,3,7,8-tetrachlorodibenzo-p-dioxin and dioxin concentrations for TV but not G2+. Results were robust to sensitivity analyses. CONCLUSIONS: Findings support an association of higher peripubertal serum dioxin TEQs and concentrations with later male pubertal onset reflected in delayed testicular maturation.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.001 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".