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

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.