High serum uric acid (SUA) levels may be associated with hypertriglyceridemia. However, prospective cohort studies on the effect of longitudinal trajectory changes in SUA on new-onset hypertriglyceridemia are still lacking.

To investigate the correlation between the longitudinal trajectory of SUA and the new-onset hypertriglyceridemia.

A total of 3 871 architecture employees who underwent physical examinations in Shiyan Railway Hospital from 2015 to 2020 were selected as study subjects. The general data, physical examination data and laboratory test results of the study subjects were collected. Group-based trajectory model (GBTM) was used to group the uric acid trajectories of the study subjects, linear trend χ² test was used to detect linear trends in the density of hypertriglyceridemia development with SUA stratification. Generalized estimation equation (GEE) was used to analyze the relationship between each index and hypertriglyceridemia.

The trajectories of GBTM group 1 showed low SUA fluctuation levels (250-350 μmol/L), group 2 showed medium SUA fluctuation levels (>350-450 μmol/L), and group 3 showed high SUA fluctuation levels (>450 μmol/L), the three groups were named as low fluctuation group (n=1 103), medium fluctuation group (n=2 141), and high fluctuation group (n=627) sequentially according to the trajectory characteristics. The results of linear trend χ² test revealed that the density of hypertriglyceridemia development increased with the rise of uric acid fluctuating levels (χ²_trend=146.728, P<0.001). There were significant differences in age, total cholesterol (TC), triacylglycerol (TG), SUA, creatinine (Cr), systolic blood pressure (SBP), diastolic blood pressure (DBP), and BMI among the three groups (P<0.05). GEE analysis showed that TC, Cr, SBP, DBP, fasting blood glucose and BMI were influencing factors in the development of hypertriglyceridemia (P<0.05), and the risk of hypertriglyceridemia was increased in the medium fluctuation group〔RR=2.294, 95%CI (1.834, 2.868) 〕and high fluctuation group〔RR=3.012, 95%CI (2.295, 3.953) 〕using the low fluctuation group as a reference (P<0.05) .

The incidence density of hyperhyperacylglyceremia increases with the increase of uric acid locus, which is a risk factor for hyperacylglyceremia. Controlling SUA fluctuation in the normal range may help to reduce the risk of hyperacylglyceremia.

高血清尿酸（SUA）水平可能与高三酰甘油血症相关，但仍缺乏SUA纵向轨迹变化对新发高三酰甘油血症影响的前瞻性队列研究。

探讨SUA纵向变化轨迹与新发高三酰甘油血症的相关性。

纳入2015—2020年在十堰市铁建医院进行健康体检的建筑职工3 871人为研究对象，收集研究对象一般资料、体格检查资料与实验室检测结果。构建群组轨迹模型（GBTM）对研究对象尿酸轨迹进行分组，采用线性趋势χ²检验检测高三酰甘油血症发病密度随SUA分层的线性趋势。采用广义估计方程模型（GEE）分析各指标与高三酰甘油血症的关系。

GBTM分组第1组轨迹呈现低位SUA波动水平（250~350 μmol/L），第2组轨迹呈现中位SUA波动水平（>350~450 μmol/L），第3组轨迹呈现高位SUA波动水平（>450 μmol/L），根据轨迹特征将3组依次命名为低位波动组（n=1 103）、中位波动组（n=2 141）、高位波动组（n=627）。线性趋势χ²检验结果发现，高三酰甘油血症发病密度随尿酸波动水平的上升而升高（χ²_趋势=146.728，P<0.001）。三组受试者年龄、总胆固醇（TC）、三酰甘油（TG）、SUA、肌酐（Cr）、收缩压（SBP）、舒张压（DBP）、BMI比较，差异有统计学意义（P<0.05）。GEE分析结果显示，TC、Cr、SBP、DBP、空腹血糖、BMI为高三酰甘油血症发生的影响因素（P<0.05），以低位波动组为参照，中位波动组〔RR=2.294，95%CI（1.834，2.868）〕、高位波动组〔RR=3.012，95%CI（2.295，3.953）〕高三酰甘油血症的发生风险升高（P<0.05）。

高三酰甘油血症发病密度随着SUA轨迹的升高而增加，SUA轨迹升高是高三酰甘油血症发生的危险因素，控制SUA在参考范围波动将可能有助于降低高三酰甘油血症的患病风险。