Association between different metabolic obesity phenotypes and hyperuricemia: the modifying role of liver enzymes

Background: Hyperuricemia (HUA) is a rapidly increasing metabolic disorder that is closely linked to obesity, nonalcoholic fatty liver disease and cardiometabolic diseases. However, the relationships between different metabolic obesity phenotypes and HUA, and the potential modifying role of liver enzymes, remain unclear, particularly in occupational populations. Methods: In this cross-sectional study, we enrolled 1,867 Chinese oilfield workers undergoing routine occupational health examinations. Logistic regression models were used to estimate odds ratios (ORs) and 95% confidence intervals (CIs) for HUA. Generalized additive models with penalized smoothing splines were applied to explore potential non-linear associations of BMI and WC with HUA. Stratified analyses were conducted according to liver enzyme status. Results: The prevalence of HUA was 30.0% among oilfield workers. Both GO and AO were significantly associated with higher odds of HUA after multivariable adjustment (adjusted OR for GO: 1.83, 95% CI: 1.35-2.49; for AO: 1.38, 95% CI: 1.03-1.84). Compared with metabolically healthy non-obesity phenotypes, metabolically unhealthy obesity phenotypes showed the strongest associations with HUA, particularly MUGO (adjusted OR: 4.00, 95% CI: 2.69-6.06) and MUAO (adjusted OR: 3.73, 95% CI: 2.53-5.59). Generalized additive models revealed a linear positive relationship between BMI and HUA risk, whereas the association between WC and HUA was non-linear. Stronger associations between MUGO/MUAO and HUA were observed among individuals with elevated liver enzyme levels. Conclusion: In this population of oilfield workers, metabolically unhealthy obesity phenotypes, especially MUGO and MUAO, are strongly associated with HUA, with liver enzyme abnormalities acting as potential effect modifiers rather than causal determinants. Metabolic status and liver function appear to be important modifiers of obesity-related HUA risk. Integrating adiposity measures, metabolic components and liver enzyme indices may improve risk stratification and inform targeted prevention strategies for HUA in occupational settings.