Zhang Shan, Ma Zhimin, Li Qiang, Liu Jia, Tao Lixin, Han Yumei, Zhang Jingbo, Guo Xiuhua, Yang Xinghua
School of Public Health, Capital Medical University, Beijing 100069, China; Beijing Municipal Key Laboratory of Clinical Epidemiology, Beijing 100069, China.
Beijing Physical Examination Center, Beijing 100077, China.
Nutr Metab Cardiovasc Dis. 2021 Apr 9;31(4):1189-1199. doi: 10.1016/j.numecd.2020.12.007. Epub 2020 Dec 11.
Although high serum uric acid (SUA) at baseline has been linked to increased risk for metabolic syndrome (MetS), the association of longitudinal SUA changes with MetS risk is unclear. We aimed to examine the effect of distinct SUA trajectories on new-onset MetS risk by sex in a Chinese cohort.
A total of 2364 women and 2770 men who were free of MetS in 2013 were enrolled in this study and followed up to 2018. Group-based trajectory modeling was applied to identify SUA trajectories. Cox proportional hazards model was used to evaluate the association between SUA trajectory and new-onset MetS. The dose-response relationship between SUA trajectories and MetS risk was examined by treating trajectory groups as a continuous variable. During a median follow-up of 48.0 months, 311 (13.16%) women and 950 (34.30%) men developed MetS. SUA trajectories (2013-2018) were defined as four distinct patterns in both women and men: "low", "moderate", "moderate-high", and "high". Compared with "low" SUA trajectory, the adjusted hazard ratio for incident MetS among participants with "moderate", "moderate-high" and "high" trajectory was in a dose-response manner: 1.75 (95% CI: 1.08-2.82), 1.94 (95% CI: 1.20-3.14), and 3.05 (95% CI: 1.81-5.13), respectively, for women; 1.20 (95% CI: 0.97-1.49), 1.48 (95% CI: 1.19-1.85), and 1.66 (95% CI: 1.25-2.21), respectively, for men.
Elevated SUA trajectories are associated with increased risk for new-onset MetS in women and men. Monitoring SUA trajectories may assist in identifying subpopulations at higher risk for MetS.
尽管基线时高血清尿酸(SUA)与代谢综合征(MetS)风险增加相关,但SUA纵向变化与MetS风险之间的关联尚不清楚。我们旨在研究中国队列中不同的SUA轨迹对新发MetS风险的性别差异影响。
本研究纳入了2013年时无MetS的2364名女性和2770名男性,并随访至2018年。采用基于群组的轨迹模型来识别SUA轨迹。使用Cox比例风险模型评估SUA轨迹与新发MetS之间的关联。通过将轨迹组视为连续变量来检验SUA轨迹与MetS风险之间的剂量反应关系。在中位随访48.0个月期间,311名(13.16%)女性和950名(34.30%)男性发生了MetS。SUA轨迹(2013 - 2018年)在女性和男性中均被定义为四种不同模式:“低”、“中”、“中高”和“高”。与“低”SUA轨迹相比,“中”、“中高”和“高”轨迹参与者发生MetS的校正风险比呈剂量反应关系:女性分别为1.75(95%CI:1.08 - 2.82)、1.94(95%CI:1.20 - 3.14)和3.05(95%CI:1.81 - 5.13);男性分别为1.20(95%CI:0.97 - 1.49)、1.48(95%CI:1.19 - 1.85)和1.66(95%CI:1.25 - 2.21)。
SUA轨迹升高与女性和男性新发MetS风险增加相关。监测SUA轨迹可能有助于识别MetS风险较高的亚人群。