Association of Metabolic Syndrome With Serum Uric Acid Level in Male Workers
Bibliographic record
Abstract
Background: Metabolic syndrome (MetS) is a type of the inflammatory diseases that is a known risk factor for many conditions, including type 2 diabetes mellitus (DM) and cardiovascular disease (CVD). Preventing or managing of MetS involves biomarkers for early identification or predicting the risk of developing the condition. The association between serum uric acid (SUA) and MetS in a large population of Korean male workers was investigated. Methods: We conducted a cross-sectional study of 9,191 male workers who comprised 6,626 daytime workers (DW) and 2,565 shift workers (SW) aged 20 - 58 years who had undergone regular health check-up in 2021. Body mass index (BMI), waist circumference (WC), blood pressure (BP), white blood cell count (WBC), biochemical parameters including SUA, liver enzymes, lipid profile and serum creatinine (Cr) were measured and participants responded to a questionnaire on health-related behavior. Participants were placed in quartiles based on their SUA levels. Associations between SUA and the prevalence of MetS or metabolic components (MS) were explored using multiple logistic regression analysis. Results: The overall prevalence of MetS was 24.6%, and the prevalence of MetS in DW was significantly higher than in SW (25.8% vs. 21.7%, P = 0.001). The prevalence of MetS, number of MS, and number of SW were positively correlated with SUA levels, as were all other variables except age, high-density lipoprotein cholesterol (HDL-C) and prevalence of DM, which were negatively correlated with SUA levels. After adjusting for multiple potential confounders, the odds ratio (OR) for MetS of the highest SUA quartile compared to the reference was 1.86 (95% confidence interval (CI): 1.60 - 2.15); however, after adjusting for BMI, it was 1.32 (95% CI: 1.12 - 1.54). The SUA level was also associated with high BP, high fasting plasma glucose (FPG) and hypertriglyceridemia after full adjustment. Notably, hypertriglyceridemia was also associated with a high-normal SUA level. Conclusions: SUA levels may be independent predictors of MetS in Korean male workers. Hypertriglyceridemia is closely associated with SUA levels. J Endocrinol Metab. 2024;14(1):21-32 doi: https://doi.org/10.14740/jem927
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".