Association between systemic immune-inflammation index and metabolic syndrome and its components: results from the National Health and Nutrition Examination Survey 2011–2016

Abstract Background Metabolic syndrome (MetS), a worldwide public health problem, affects human health and quality of life in a dramatic manner. A growing evidence base suggests that MetS is strongly associated with levels of systemic immune inflammation. The present study aimed to investigate the possible relationship between the systemic immune-inflammation index (SII), a novel inflammatory marker, and MetS to provide data support for effective MetS prevention by reducing the systemic inflammatory response. Methods We included adult participants with complete SII and MetS information from the 2011–2016 National Health and Nutrition Examination Survey (NHANES). MetS was defined as using the criteria developed by the Adult Treatment Program III of the National Cholesterol Education Program. The formula for SII was as follows: SII = platelet counts × neutrophil counts/ lymphocyte counts. Weighted linear regression was used to assess differences in variables across SII quartile groups after the SII score was divided into 4 quartiles. The independent interaction between SII and MetS was investigated using weighted multivariate logistic regression analysis and subgroup analysis, and the relationship between SII levels and 5 particular MetS items was further explored in depth. Results A total of 12,402 participants, 3,489 of whom were diagnosed with MetS, were included in this study. After correcting for covariates, the results of a logistic regression of multistage weighted complex sampling data revealed that participants with higher SII scores had a higher chance of developing MetS (odds ratio (OR) = 1.33, 95% confidence interval (CI): 1.14–1.55) and that SII levels could be used as an independent risk factor to predict that likelihood of MetS onset. In the Q1–Q4 SII quartile group, the risk of developing MetS was 1.33 times higher in the Q4 group, which had the highest level of systemic immune inflammation than in the Q1 group. After adjusting for all confounding factors, SII scores were found to have a negative correlation with high-density lipoprotein cholesterol (OR = 1.29; 95% CI, 0.99–1.67, P = 0.056) and a significant positive correlation with waist circumference (OR = 2.17; 95% CI, 1.65–2.87, P < 0.001) and blood pressure (BP) (OR = 1.65; 95% CI, 1.20–2.27, P = 0.003). Gender, age, and smoking status were shown to alter the positive association between SII and MetS in subgroup analyses and interaction tests ( p for interaction < 0.05). Additionally, we demonstrated a nonlinear correlation between SII and MetS. The findings of the restricted cubic spline indicated that there was an inverted U-shaped association between SII and MetS. Conclusions Our findings imply that increased SII levels are related to MetS, and SII may be a simple and cost-effective method to identify individuals with MetS. Therefore, protective measures such as early investigation and anti-inflammatory interventions are necessary to reduce the overall incidence of MetS.