China Medical University, Shenyang, China.
Department of Endocrinology, Dalian Municipal Central Hospital, Dalian, China.
Lipids Health Dis. 2024 Aug 24;23(1):267. doi: 10.1186/s12944-024-02247-1.
Recent years have seen the emergence of numerous novel indicators for visceral obesity. This study investigates the potential correlation between the Chinese visceral adiposity index (CVAI) and hyperuricemia (HUA).
This research, derived from a 2011 cross-sectional analysis in Dalian, China, employed restricted cubic spline (RCS) plots to identify inflection points. Subsequently, one-way and multifactorial logistic regression models were utilized, with HUA as the outcome variable. Additionally, subgroup analyses and interaction tests were conducted. Eventually, receiver operating characteristic (ROC) curves were calculated to assess the effectiveness of CVAI and other body composition indices in predicting HUA.
The study included 10,061 individuals, with a HUA prevalence of 14.25%. Significant relationships with HUA were observed for CVAI. RCS analysis revealed a J-shaped relationship between CVAI and HUA. Compared to those in the low CVAI category, HUA was notably associated with individuals in the high CVAI category in multifactorial logistic regression (OR = 2.661, 95% CI: 2.323, 3.047). Subgroup analyses demonstrated stronger relationships in women, participants without hypertension, and participants without diabetes. Additional modeling via ROC curves suggested that the CVAI may offer effective predictive value for HUA.
This study confirmed that an elevated CVAI elevates the risk of HUA in middle-aged and elderly populations in the Dalian community. The findings advance obesity prevention strategies that mitigate HUA risk and support healthcare initiatives for China's aging population.
近年来，出现了许多新的内脏肥胖指标。本研究探讨了中国内脏脂肪指数（CVAI）与高尿酸血症（HUA）之间的潜在相关性。
本研究源自 2011 年在中国大连进行的横断面分析，采用限制性立方样条（RCS）图确定拐点。随后，采用单因素和多因素逻辑回归模型，以 HUA 为因变量。此外，还进行了亚组分析和交互检验。最终，计算了受试者工作特征（ROC）曲线，以评估 CVAI 和其他身体成分指标预测 HUA 的有效性。
本研究纳入了 10061 名个体，HUA 的患病率为 14.25%。CVAI 与 HUA 显著相关。RCS 分析显示 CVAI 与 HUA 之间呈 J 形关系。与低 CVAI 组相比，多因素逻辑回归显示高 CVAI 组与 HUA 显著相关（OR=2.661，95%CI：2.323，3.047）。亚组分析显示，女性、无高血压和无糖尿病的参与者中相关性更强。通过 ROC 曲线进一步建模表明，CVAI 可能对 HUA 具有有效的预测价值。
本研究证实，中年和老年大连社区人群中 CVAI 升高会增加 HUA 的风险。这些发现为预防肥胖策略提供了依据，以降低 HUA 风险，并支持中国老龄化人口的医疗保健计划。
