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Background Systemic immune-inflammation index (SII) and systemic inflammation response index (SIRI) are comprehensive markers of inflammatory status. However, the correlation between SII and SIRI and the prevalence of cardiovascular disease (CVD) in populations with obesity remains unknown. Methods This is a cross-sectional study with data obtained from the National Health and Nutrition Examination Survey from 1999 to 2018. SII and SIRI were calculated using the following equations: SII = (platelet count × neutrophil count)/lymphocyte count. SIRI = (neutrophil count × monocyte count)/lymphocyte count. Spearman’s rank correlation coefficient was used to assess the relationship between SII and SIRI and baseline variables. Logistic regression models and generalized additive model (GAM) with a spline smoothing function were used to evaluate the association between SIRI and CVD prevalence. Nomogram and receiver operating characteristic curve (ROC) analysis were used to assess the value of the risk prediction model. Results A total of 17,261 participants with obesity and SII and SIRI publicly available data were used for this study. Multivariate logistic regression analysis revealed that SIRI, rather than SII, was an independent risk factor for CVD prevalence. For every standard deviation increase in SIRI, there was a 13%, 15%, and 28% increase in the odds ratios of CVD prevalence (OR = 1.13, 95% CI: 1.04–1.22, P = 0.01), coronary heart disease (OR = 1.15, 95% CI: 1.05–1.26, P = 0.002), and congestive heart failure (OR = 1.28, 95% CI: 1.16–1.41, P 0.001). ROC results demonstrated that SIRI had a certain accuracy in predicting CVD prevalence (AUC = 0.604), especially when combined with other variables used in the nomogram (AUC = 0.828). The smooth curve fitting regression analysis demonstrated a significant linear association between the risk of SIRI and the odds ratio of CVD prevalence ( P for nonlinear = 0.275). Conclusions SIRI is a relatively stable indicator of inflammation and is independently associated with the prevalence of CVD. It may serve as a novel inflammatory indicator to estimate CVD prevalence in populations with obesity.
Liu et al. (Thu,) studied this question.