Department of Endocrinology, Beijing Jishuitan Hospital, Capital Medical University, 100035 Beijing, China.
Department of Medical Record Management and Statistics, Beijing Jishuitan Hospital, Capital Medical University, 100035 Beijing, China.
Nutr Metab Cardiovasc Dis. 2024 Nov;34(11):2472-2479. doi: 10.1016/j.numecd.2024.06.021. Epub 2024 Jul 4.
This study aims to investigate the association of Chinese visceral adiposity index (CVAI) with incident hyperuricemia (HUA).
We included 5186 adults aged ≥45 years from China Health and Retirement Longitudinal Study. Modified Poisson regression model was used to estimate the relative risks (RRs) of incident HUA associated with baseline CVAI, and logistic model was used to estimate the odds ratios (ORs) of HUA for CVAI change. Restricted cubic splines analysis was adopted to model the dose-response associations. The area under the receiver operating characteristic curve (AUC) analysis was used to evaluate the predictive value of CVAI. During 4-year follow-up, a total of 510 (9.8%) HUA cases were identified. The RRs (95%CIs) of incident HUA were 3.75 (2.85-4.93) for quartile 4 versus quartile 1 and 1.56 (1.45-1.69) for per-standard deviation increase in baseline CVAI. For the analyses of CVAI change, compared with stable group, participants in decreased group had 34% lower risk (OR 0.66, 95%CI 0.49-0.87) and those in increased group had 35% (1.35, 1.03-1.78) higher risk of HUA. Linear associations of baseline CVAI and its change with HUA were observed (P >0.05). Besides, the AUC value for HUA was 0.654 (0.629-0.679), which was higher than other five obesity indices.
Our study found linear associations between baseline CVAI and its change and risk of HUA. CVAI had the best predictive performance in predicting incident HUA. These findings suggest CVAI as a reliable obesity index to identify individuals with higher HUA risk.
本研究旨在探讨中国内脏脂肪指数(CVAI)与新发高尿酸血症(HUA)的相关性。
我们纳入了来自中国健康与退休纵向研究的 5186 名年龄≥45 岁的成年人。采用校正泊松回归模型估计基线 CVAI 与新发 HUA 相关的相对风险(RR),采用 logistic 模型估计 CVAI 变化与 HUA 的比值比(OR)。采用受限立方样条分析来模拟剂量-反应关系。采用受试者工作特征曲线(ROC)下面积(AUC)分析来评估 CVAI 的预测价值。在 4 年的随访期间,共发现 510 例(9.8%)HUA 病例。与 quartile 1 相比,quartile 4 的新发 HUA 的 RR(95%CI)分别为 3.75(2.85-4.93)和 1.56(1.45-1.69)。对于 CVAI 变化的分析,与稳定组相比,降低组的参与者发生 HUA 的风险降低了 34%(OR 0.66,95%CI 0.49-0.87),增加组的参与者发生 HUA 的风险增加了 35%(1.35,1.03-1.78)。观察到基线 CVAI 及其变化与 HUA 呈线性关系(P>0.05)。此外,HUA 的 AUC 值为 0.654(0.629-0.679),高于其他五个肥胖指数。
本研究发现基线 CVAI 及其变化与 HUA 风险之间存在线性关系。CVAI 在预测新发 HUA 方面具有最佳的预测性能。这些发现表明 CVAI 是一种可靠的肥胖指数,可以识别出具有更高 HUA 风险的个体。