Association between Visceral Adiposity Index and Hyperuricemia among Steelworkers: The Moderating Effects of Drinking Tea
Bibliographic record
Abstract
Background/Objectives: Steelworkers are more likely to have a higher prevalence of hyperuricemia due to their exposure to special occupational factors and dietary habits. The interrelationships of visceral adiposity index (VAI), hyperuricemia, and drinking tea remain uncertain. This study aimed to assess the association between VAI and hyperuricemia among steelworkers, and if drinking tea modified this association. Methods: A total of 9928 steelworkers from Hunan Hualing Xiangtan Iron and Steel Company participated in this cross-sectional study. All participants completed a questionnaire, received anthropometric measurements, and provided blood samples for biochemical testing. Three logistic regression models were used to analyze the association between VAI and hyperuricemia. Results: In this study, the prevalence of hyperuricemia was approximately 23.74% (males: 24.41%; females: 20.63%), and a positive correlation between VAI and hyperuricemia risk was observed. In multivariate logistic regression analysis, the risk of hyperuricemia increased 1.76 times (95% CI: 1.64–1.89) and 2.13 times (95% CI: 1.76–2.57) with the increase of ln VAI in males and females, respectively. For males, compared to quartile 1, the risk of hyperuricemia in the second, third, and fourth quartile of VAI were 1.75 (95% CI: 1.11–2.71), 2.56 (95% CI: 1.67–3.93) and 4.89 (95% CI: 3.22–7.43). For females, compared to quartile 1, the risk of hyperuricemia in the second, third, and fourth quartile of VAI were 1.99 (95% CI: 1.40–2.82), 2.92 (95% CI: 1.96–4.34) and 4.51 (95% CI: 2.89–7.02). Additionally, our study found that, compared with not consuming tea, drinking tea could reduce uric acid levels by 0.014 in male steelworkers (t = −2.051, p = 0.040), 0.020 in workers consuming smoked food (t = −2.569, p = 0.010), and 0.022 in workers consuming pickled food (t = −2.764, p = 0.006). Conclusions: In conclusion, VAI is positively correlated with hyperuricemia in steelworkers. Drinking tea may lower uric acid levels in male steelworkers and steelworkers who prefer smoked and pickled foods.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".