Red Cell Distribution Width-Standard Deviation Is Associated with Cumulative Metabolic Burden but Not Independently...

Background and Objectives: Red cell distribution width (RDW) has been associated with adverse cardiometabolic outcomes; however, whether RDW-particularly RDW standard deviation (RDW-SD)-represents an independent determinant of metabolic syndrome (MetS) or reflects cumulative metabolic burden remains unclear. This study evaluated the association between RDW-SD and MetS presence and examined its relationship with the quantitative accumulation of MetS components. Materials and Methods: In this single-center observational study, 222 adults undergoing evaluation for MetS were consecutively recruited. Participants with overt anemia, extreme mean corpuscular volume values, or acute inflammation were excluded. MetS was defined according to revised NCEP ATP-III criteria. Associations between RDW-SD and MetS were assessed using hierarchical multivariable logistic regression models. The relationship between RDW-SD and the number of MetS components was examined using multivariable linear regression. Discriminative performance was evaluated by receiver operating characteristic (ROC) curve analysis. Results: MetS was present in 68.0% of participants. RDW-SD levels were significantly higher in individuals with MetS and increased progressively across quartiles. RDW-SD was independently associated with the number of MetS components (standardized β = 0.226, p < 0.001). However, RDW-SD was not independently associated with MetS presence in fully adjusted logistic models (OR = 1.07, 95% CI: 0.97-1.18, p = 0.198). The addition of RDW-SD provided minimal incremental explanatory value (Nagelkerke R² increase from 0.348 to 0.356). ROC analysis demonstrated poor discriminatory ability (area under the curve [AUC] = 0.611, 95% CI: 0.535-0.687), supporting limited standalone diagnostic utility. Conclusions: RDW-SD was independently associated with cumulative metabolic burden but not with the independent presence of MetS after adjustment for established cardiometabolic factors. Given the cross-sectional design, these findings should be interpreted as associative rather than causal.