Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2024 Aug 19;14(1):19151.
doi: 10.1038/s41598-024-69819-0.

Association between systemic immune-inflammation index and cardiovascular-kidney-metabolic syndrome

Affiliations

Association between systemic immune-inflammation index and cardiovascular-kidney-metabolic syndrome

Chenxuan Gao et al. Sci Rep. .

Abstract

This study aims to explore the relationship between the Systemic Immune-Inflammation Index (SII) and Cardiovascular-Kidney-Metabolic (CKM) Syndrome and its components. Data from the National Health and Nutrition Examination Survey (NHANES) from 2001 to 2018 were analyzed. CKM Syndrome is defined as the coexistence of Cardiometabolic Syndrome (CMS) and Chronic Kidney Disease (CKD). The SII is calculated using the formula: SII = (Platelet count × Neutrophil count)/Lymphocyte count. Weighted logistic regression models were used to examine the associations between SII and CKM, as well as its specific components. Restricted cubic splines explored non-linear relationships, and piecewise linear regression models assessed threshold effects. A consistent positive correlation was observed between elevated SII levels and the likelihood of CKM and its related diseases. In the fully adjusted Model 3, an increase of 1000 units in SII was associated with a 1.48-fold increase in the odds of CKM (95% CI 1.20-1.81, p < 0.001). Quartile analysis revealed a dose-response relationship, with the highest quartile of SII (Q4) showing the strongest association with CKM and its components. Nonlinear analyses revealed inflection points for waist circumference, triglycerides, low HDL-C, and cardiometabolic syndrome at specific SII levels, indicating a change in the direction or strength of associations beyond these points. Conversely, a linear relationship was observed between SII and chronic kidney disease. The SII is positively correlated with the risk of CKM Syndrome and its individual components, with evidence of non-linear relationships and threshold effects for some components.

Keywords: Cardiometabolic syndrome; Cardiovascular-kidney-metabolic syndrome; Chronic kidney disease; National health and nutrition examination survey; Systemic immune-inflammation index.

PubMed Disclaimer

Conflict of interest statement

The authors declare no competing interests.

Figures

Figure 1
Figure 1
Screening flow of respondents.
Figure 2
Figure 2
Nonlinear relationship between SII and Cardiovascular-Kidney-Metabolic Syndrome (A). Nonlinear relationship between SII and elevated Waist Circumference (B). Nonlinear relationship between SII and Elevated Triglycerides (C). Nonlinear relationship between SII and Low HDL-C (D). Nonlinear relationship between SII and Elevated Fasting Plasma Glucose (E). Nonlinear relationship between SII and Elevated Blood Pressure (F). Nonlinear relationship between SII and Cardiometabolic Syndrome (G). Nonlinear relationship between SII and Chronic Kidney Disease (H).
Figure 2
Figure 2
Nonlinear relationship between SII and Cardiovascular-Kidney-Metabolic Syndrome (A). Nonlinear relationship between SII and elevated Waist Circumference (B). Nonlinear relationship between SII and Elevated Triglycerides (C). Nonlinear relationship between SII and Low HDL-C (D). Nonlinear relationship between SII and Elevated Fasting Plasma Glucose (E). Nonlinear relationship between SII and Elevated Blood Pressure (F). Nonlinear relationship between SII and Cardiometabolic Syndrome (G). Nonlinear relationship between SII and Chronic Kidney Disease (H).

References

    1. Ndumele, C. E. et al. A synopsis of the evidence for the science and clinical management of cardiovascular-kidney-metabolic (CKM) syndrome: A scientific statement from the American heart association. Circulation148(20), 1636–1664 (2023). 10.1161/CIR.0000000000001186 - DOI - PubMed
    1. Rao Kondapally Seshasai, S. et al. Diabetes mellitus, fasting glucose, and risk of cause-specific death. N. Engl. J. Med.364(9), 829–841 (2011). 10.1056/NEJMoa1008862 - DOI - PMC - PubMed
    1. Matsushita, K. et al. Association of estimated glomerular filtration rate and albuminuria with all-cause and cardiovascular mortality in general population cohorts: A collaborative meta-analysis. Lancet375(9731), 2073–2081 (2010). 10.1016/S0140-6736(10)60674-5 - DOI - PMC - PubMed
    1. Navarro-González, J. F. et al. Inflammatory molecules and pathways in the pathogenesis of diabetic nephropathy. Nat. Rev. Nephrol.7(6), 327–340 (2011). 10.1038/nrneph.2011.51 - DOI - PubMed
    1. Ridker, P. M. et al. C-reactive protein and other markers of inflammation in the prediction of cardiovascular disease in women. N. Engl. J. Med.342(12), 836–843 (2000). 10.1056/NEJM200003233421202 - DOI - PubMed