Urinary bisphenol A and incidence of metabolic syndrome among Chinese men: a prospective cohort study from 2013 to 2017
Bibliographic record
Abstract
Objectives Experimental studies suggested that bisphenol A (BPA) exposure increased the risk of metabolic syndrome (MetS) through the mechanism of insulin resistance. All previous epidemiological studies of BPA and MetS were cross-sectional studies, and their findings were mixed. This study aims to provide further evidence on the association between urinary BPA and risk of MetS using a prospective cohort study in China. Methods The study population was from the Shenzhen Night shift workers’ cohort. A total of 1227 male workers were recruited from the baseline survey in 2013 and then followed until 2017. Modified Adult Treatment Panel III criteria were used to identify the cases of MetS. Urinary BPA concentration was assessed using high-performance liquid chromatography–tandem mass spectrometry, and it was categorised into three subgroups by tertiles to obtain the adjusted HR (aHR) and 95% CI using Cox proportional hazard model. Results During 4 years of follow-up, 200 subjects developed MetS. Compared with the lowest urinary BPA subgroup, a weakly increased risk of MetS was suggested among those with the middle (aHR=1.19, 95% CI 0.87 to 1.63) and high level of urinary BPA (aHR=1.16, 95% CI 0.84 to 1.59); however, the significant association with MetS was restricted primarily to the smokers, showing a positive gradient with urinary BPA (middle level: aHR=2.40, 95% CI 1.13 to 5.08; high level: aHR=2.87, 95% CI 1.38 to 5.98;p trend=0.010). Conclusion This prospective cohort study provided further evidence that exposure to BPA may increase the risk of MetS, and this association was further positively modified by cigarette smoking.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".