Yanjing Medical College, Capital Medical University, Beijing 101300, China.
School of Public Health, Capital Medical University, Beijing 100069, China; Beijing Municipal Key Laboratory of Clinical Epidemiology, Capital Medical University, Beijing 100069, China; Centre for Precision Health, Edith Cowan University, Perth, WA 6027, Australia.
Nutr Metab Cardiovasc Dis. 2023 May;33(5):967-977. doi: 10.1016/j.numecd.2023.02.018. Epub 2023 Feb 28.
Conflicting results suggest a link between serum uric acid and diabetes and previous studies ignored the effect of continuous exposure of serum uric acid on diabetes risk. This study aims to characterize hyperuricemia trajectories in middle-aged adults and to examine its potential impact on diabetes risk, considering the role of obesity, dyslipidemia, and hypertension.
The cohort included 9192 participants who were free of diabetes before 2013. The hyperuricemia trajectories during 2009-2013 were identified by latent class growth models. Incident diabetes during 2014-2018 was used as the outcome. Modified Poisson regression models were used to assess the association of trajectories with diabetes. Furthermore, marginal structural models were used to estimate the mediating effects of the relationship between hyperuricemia trajectories and diabetes. We identified three discrete hyperuricemia trajectories: high-increasing (n = 5794), moderate-stable (n = 2049), and low-stable (n = 1349). During 5 years of follow-up, we documented 379 incident diabetes cases. Compared with the low-stable pattern, the high-increasing pattern had a higher risk of developing diabetes (RR, 1.42; 95% CI: 1.09-1.84). In addition, the percentages of total effect between the high-increasing hyperuricemia pattern and diabetes mediated by obesity, dyslipidemia, and hypertension were 24.41%, 18.26%, and 6.29%. However, the moderate-stable pattern was not associated with an increased risk of diabetes.
These results indicate that the high-increasing hyperuricemia trajectory is significantly associated with an increased risk of diabetes. Furthermore, obesity, dyslipidemia, and hypertension play mediating roles in the relationship between the high-increasing hyperuricemia pattern and increased diabetes risk.
有研究结果表明血清尿酸与糖尿病之间存在关联，但此前的研究忽略了血清尿酸持续暴露对糖尿病风险的影响。本研究旨在描述中年人群的高尿酸血症轨迹，并探讨其对糖尿病风险的潜在影响，同时考虑肥胖、血脂异常和高血压的作用。
该队列纳入了 9192 名在 2013 年前无糖尿病的参与者。采用潜在类别增长模型确定 2009-2013 年期间的高尿酸血症轨迹。2014-2018 年发生的糖尿病作为结局。采用校正泊松回归模型评估轨迹与糖尿病之间的关联。此外，采用边际结构模型估计高尿酸血症轨迹与糖尿病之间关系的中介效应。我们确定了三种离散的高尿酸血症轨迹：高升高（n=5794）、中稳定（n=2049）和低稳定（n=1349）。在 5 年的随访期间，我们记录了 379 例糖尿病发病病例。与低稳定模式相比，高升高模式发生糖尿病的风险更高（RR，1.42；95%CI：1.09-1.84）。此外，高升高高尿酸血症模式与糖尿病之间的总效应百分比，通过肥胖、血脂异常和高血压介导的分别为 24.41%、18.26%和 6.29%。然而，中稳定模式与糖尿病风险增加无关。
这些结果表明，高升高高尿酸血症轨迹与糖尿病风险增加显著相关。此外，肥胖、血脂异常和高血压在高升高高尿酸血症模式与糖尿病风险增加之间的关系中发挥中介作用。
