Department of Epidemiology and Biostatistics, Michigan State University, 220 Trowbridge Rd, East Lansing, MI 48824, USA.
The Institute for Quantitative Health Science and Engineering, Michigan State University, 220 Trowbridge Rd, East Lansing, MI 48824, USA.
Arthritis Res Ther. 2018 May 3;20(1):90. doi: 10.1186/s13075-018-1558-3.
Many gout comorbidities (e.g., hypertension) are correlated with serum urate. In this investigation, we identified risk factors (e.g., systolic blood pressure [SBP]), that (1) are associated with incident gout, (2) have effects on gout risk that cannot be fully explained by correlated differences in serum urate, and (3) may modulate the relationship between gout and serum urate.
Using data from the Atherosclerosis Risk in Communities (ARIC) study, we estimated the unadjusted associations between gout and risk factors by calculating ORs and using chi-square tests. The adjusted associations were analyzed using logistic regression by sequentially adding (1) one risk factor at a time or (2) all risk factors, to a baseline model that includes serum urate only. Stepwise selection was used to select main effects. Two-way interactions of variables from the main effects model were also analyzed.
Average gout incidence was 2.7 per 1000 people per year. Serum urate was highly associated with incident gout, with odd ratios of 3.16 [95% CI 2.11, 4.76] and 25.9 [95% CI 17.2, 38.4] for moderately high (6-8 mg/dl) and high serum urate (> 8 mg/dl), relative to normal serum urate (< 6 mg/dl), respectively. Ethnicity and SBP were independently and additively associated with gout after accounting for serum urate levels. No significant interactions were found between serum urate and ethnicity or SBP.
Ethnicity and hypertension are predictive of gout risk, and the associations cannot be fully explained by serum urate. For serum urate levels near the crystallization threshold (6-8 mg/dl) African Americans and people with hypertension are at two to three times greater risk for developing gout. The gout risk for this group appears to increase before the onset of severe hyperuricemia.
许多痛风合并症(如高血压)与血清尿酸有关。在这项研究中,我们确定了与痛风发病相关的风险因素(如收缩压[SBP]),这些因素(1)与痛风发病相关,(2)对痛风风险的影响不能完全用相关的血清尿酸差异来解释,(3)可能调节痛风与血清尿酸之间的关系。
使用来自动脉粥样硬化风险社区(ARIC)研究的数据,我们通过计算 OR 并使用卡方检验来估计痛风与危险因素之间的未经调整的关联。使用逻辑回归分析调整关联,通过逐步添加(1)一个风险因素,或(2)所有风险因素,到仅包含血清尿酸的基线模型中,依次分析。逐步选择用于选择主要效应。还分析了主效应模型中变量的双向相互作用。
平均痛风发病率为每 1000 人每年 2.7 例。血清尿酸与痛风发病高度相关,中度高(6-8 mg/dl)和高血清尿酸(>8 mg/dl)的比值分别为 3.16[95%CI 2.11,4.76]和 25.9[95%CI 17.2,38.4],与正常血清尿酸(<6 mg/dl)相比。在考虑血清尿酸水平后,种族和 SBP 与痛风独立且呈累加性相关。未发现血清尿酸与种族或 SBP 之间存在显著的相互作用。
种族和高血压是痛风风险的预测因素,这些关联不能完全用血清尿酸来解释。对于接近结晶阈值(6-8 mg/dl)的血清尿酸水平,非裔美国人和高血压患者发生痛风的风险增加了两到三倍。对于这一人群,痛风风险似乎在严重高尿酸血症出现之前就已经增加了。