Red cell distribution width/albumin ratio as a marker for metabolic syndrome: findings from a cross-sectional study.

IF 2.8 3区 医学 Q3 ENDOCRINOLOGY & METABOLISM BMC Endocrine Disorders Pub Date : 2024-10-25 DOI:10.1186/s12902-024-01762-7
Hao Guo, Yu Wang, Ying Miao, Qiang Lin
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Abstract

Background: Metabolic syndrome (MetS) imposes a significant health burden on patients globally. Chronic low-grade inflammation is pivotal in the onset and progression of this condition. However, the role of the novel inflammatory marker, red cell distribution width to albumin ratio (RAR), in the development of MetS remains unclear.

Methods: This population-based cross-sectional study utilized data from the 2011-2020 National Health and Nutrition Examination Survey (NHANES). Participants included individuals over 18 years old with complete data on serum albumin concentration, red cell distribution, and MetS and its components. MetS was defined using the criteria established by the National Cholesterol Education Program Adult Treatment Panel III. The calculation formula for RAR is: RAR = Red cell distribution width (%)/serum albumin (g/dL). Study participants were stratified into four quartiles based on RAR levels. Logistic regression analysis and subgroup analysis were employed to explore the independent interaction between RAR and MetS, as well as investigate the relationship between RAR levels and the specific components of MetS. Finally, the receiver operating characteristic (ROC) curve was used to assess the predictive efficacy of RAR for MetS.

Results: A total of 4899 participants were included in this study, comprising 2450 males and 2449 females; 1715 individuals (35.01%) were diagnosed with MetS. As the quartile of RAR increased, the proportion of individuals with MetS also increased. Spearman correlation analysis indicated a positive correlation between RAR and the insulin resistance index HOMA-IR. Logistic regression analysis, adjusting for multiple confounding factors, showed that each standard deviation increase in RAR was associated with a significant 1.665-fold increase (95% CI, 1.404-1.975; P < 0.001) in the odds of MetS prevalence. In logistic regression analysis stratified by quartiles of RAR, the risks of MetS in Q1-Q4 were 1.372 (95% CI, 1.105-1.704; P = 0.004), 1.783 (95% CI, 1.434-2.216; P < 0.001), and 2.173 (95% CI, 1.729-2.732; P < 0.001), respectively. Subgroup analyses and interaction tests demonstrated that gender, age, race, education, smoking status, and physical activity modified the positive association between RAR and MetS (p for interaction < 0.05). Additionally, analysis of the area under the receiver operating characteristic (ROC) curve showed that the optimal cutoff value for predicting MetS using RAR was 3.1348 (sensitivity: 59.9%; specificity: 60.6%; and AUC: 0.628).

Conclusions: Increasing RAR levels are associated with a higher risk of MetS. Therefore, greater attention should be given to patients with high RAR levels for improved prevention and treatment of MetS.

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作为代谢综合征标志物的红细胞分布宽度/白蛋白比率:一项横断面研究的结果。
背景:代谢综合征(MetS代谢综合征(MetS)给全球患者带来了巨大的健康负担。慢性低度炎症是该病症发病和发展的关键因素。然而,新型炎症标志物--红细胞分布宽度与白蛋白比值(RAR)在代谢综合征发病中的作用仍不清楚:这项基于人群的横断面研究利用了 2011-2020 年美国国家健康与营养调查(NHANES)的数据。研究对象包括 18 岁以上、血清白蛋白浓度、红细胞分布、MetS 及其组成部分数据完整的个体。MetS 的定义采用美国国家胆固醇教育计划成人治疗小组 III 制定的标准。RAR 的计算公式为RAR = 红细胞分布宽度(%)/血清白蛋白(克/分升)。研究参与者根据 RAR 水平被分为四个四分位数。采用逻辑回归分析和亚组分析来探讨 RAR 与 MetS 之间的独立交互作用,并研究 RAR 水平与 MetS 特定成分之间的关系。最后,采用接收者操作特征曲线(ROC)评估 RAR 对 MetS 的预测效果:本研究共纳入 4899 名参与者,其中男性 2450 人,女性 2449 人;1715 人(35.01%)被诊断为 MetS。随着 RAR 四分位数的增加,MetS 患者的比例也在增加。斯皮尔曼相关分析表明,RAR 与胰岛素抵抗指数 HOMA-IR 呈正相关。调整多种混杂因素的逻辑回归分析表明,RAR 每增加一个标准差,MetS 患者的比例就会显著增加 1.665 倍(95% CI,1.404-1.975;P 结论:RAR 水平的增加与胰岛素抵抗指数 HOMA-IR 呈正相关:RAR 水平的升高与 MetS 风险的升高有关。因此,应更加关注 RAR 水平高的患者,以改善 MetS 的预防和治疗。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
BMC Endocrine Disorders
BMC Endocrine Disorders ENDOCRINOLOGY & METABOLISM-
CiteScore
4.40
自引率
0.00%
发文量
280
审稿时长
>12 weeks
期刊介绍: BMC Endocrine Disorders is an open access, peer-reviewed journal that considers articles on all aspects of the prevention, diagnosis and management of endocrine disorders, as well as related molecular genetics, pathophysiology, and epidemiology.
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