Association of cumulative systemic inflammation response index and all-cause mortality in adult with cardiovascular-kidney-metabolic syndrome stages 0–2: a prospective cohort study

Abstract

Background

Systemic inflammation has been linked to increased mortality risk. However, the prognostic value of cumulative systemic inflammation response index (SIRI) remains unclear in individuals with cardiovascular-kidney-metabolic (CKM) syndrome stages 0–2.

Methods

Participants were enrolled from the Tongzhou cohort and underwent health examinations in 2016 and 2018. Cumulative SIRI was calculated as the time-weighted average of SIRI from two pre-follow-up examinations to reflect cumulative inflammatory burden before follow-up. Participants were categorized into high and low cumulative SIRI groups according to a cut-off determined by time-dependent receiver operating characteristic (ROC) analysis. Follow-up ended on December 31, 2024, with all-cause mortality as the primary outcome. Cox proportional hazards models and restricted cubic spline (RCS) analyses were applied to evaluate the association between cumulative SIRI and mortality risk.

Results

A total of 3,410 middle-aged and elderly participants with CKM syndrome stages 0–2 were enrolled. During a median follow-up of 74 months, 71 deaths (2.08%) occurred. After adjusting for confounders, high cumulative SIRI was associated with an increased risk of all-cause mortality (HR = 2.24, 95% CI: 1.01–4.97). Subgroup analyses revealed no significant interactions between cumulative SIRI and age, sex, marital status, education, smoking, or drinking status. RCS analysis showed a linear positive association between cumulative SIRI and all-cause mortality risk.

Conclusion

Higher cumulative SIRI was associated with increased risk of all-cause mortality in middle-aged and older adults with CKM syndrome stages 0–2. These findings suggest that cumulative SIRI, estimated from two pre-follow-up measurements, may have potential prognostic relevance, although further validation is needed.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12872-026-05909-3.

Introduction

Non-communicable diseases (NCDs) account for approximately 71% of global deaths annually [1]. Cardiovascular disease (CVD), chronic kidney disease (CKD), diabetes, and high body mass index (BMI) are major contributors to mortality and disability [2]. In response, the American Heart Association (AHA) introduced the concept of cardiovascular-kidney-metabolic (CKM) syndrome in 2023, emphasizing the interrelated pathophysiological links among metabolic dysfunction, CKD, and cardiovascular disease [3]. According to the Global Burden of Disease (GBD) 2021 study, CKD affected 673.7 million individuals worldwide, while ischemic heart disease and stroke remained leading causes of disability-adjusted life years (DALYs) [4]. Recent data indicate that a large proportion of middle-aged and older adults meet criteria for CKM syndrome, particularly in early stages [5].

The AHA classifies CKM syndrome into five stages, with stages 3–4 representing advanced disease characterized by subclinical or overt CVD [6]. Advanced CKM is associated with substantially increased risks of all-cause and cardiovascular mortality [7]. Notably, approximately 85% of individuals with CKM syndrome are in stages 0–2, representing a critical window for early intervention [8].

Chronic systemic inflammation plays a central role in the progression of CKM components. It promotes glomerular injury and fibrosis, accelerating CKD progression [9], contributes to endothelial dysfunction and atherosclerosis [10, 11], and is closely linked to insulin resistance and metabolic dysregulation [12]. Accordingly, inflammatory biomarkers have gained attention for risk stratification. Ratios such as neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), and monocyte-to-lymphocyte ratio (MLR) have demonstrated prognostic value in cardiovascular populations [13, 14].

The systemic inflammation response index (SIRI), derived from peripheral neutrophil, monocyte, and lymphocyte counts, provides a more comprehensive assessment of immune-inflammatory status than traditional two-parameter markers [15–18]. Elevated SIRI has been associated with increased risks of all-cause and cardiovascular mortality in obese individuals [19] and in patients with early-stage CKD [20], as well as adverse outcomes in acute coronary syndrome and stroke populations [21, 22]. However, most prior studies have relied on single-time measurements, which may not adequately reflect cumulative inflammatory burden over time. Evidence regarding the impact of cumulative SIRI exposure on mortality risk remains limited.

Therefore, using a large community-based prospective cohort in Beijing, China, we investigated the association between cumulative SIRI and all-cause mortality among middle-aged and older individuals with CKM syndrome stages 0–2.

Methods

Study design and population

Tongzhou Cohort Study (ClinicalTrials.gov Identifier: NCT05156580) is a large community-based prospective cohort study conducted by Beijing Friendship Hospital, Capital Medical University. The primary aim of this study is to evaluate the risk factors for NCDs and the effectiveness of preventive interventions in the population of Beijing’s Tongzhou District. The cohort was established in 2016, with participants recruited from a population undergoing routine physical examination at multiple community health centers in Tongzhou District, Beijing. Data are collected annually, and any individual who has participated in at least one examination is enrolled in the cohort. The 2016 and 2018 examination cycles were included to calculate the cumulative SIRI due to substantial missing data on inflammatory markers (required for SIRI calculation) as well as key covariates in 2017. 21 782 middle-aged and elderly participants were initially enrolled in this study. We excluded participants based on the following criteria: (1) those who did not complete two health checkups between 2016 and 2018 (n = 17 029); (2) those with incomplete data for CKM staging (n = 26); (3) those diagnosed with advanced CKM syndrome (Stage 3 or 4) (n = 1,316); and (4) those who died between 2016 and 2018 (n = 1). Data from a total of 3,410 participants were ultimately included (Fig. 1). The study was performed in accordance with the ethical principles of the Declaration of Helsinki and approved by the Ethics Committee of Beijing Friendship Hospital, Capital Medical University (Beijing, China) (approval no. 2021-P2-163-02). Written informed consent was obtained from all participants.

Fig. 1.

Flowchart of the study population. The flowchart outlines the study design and participant enrollment process. Details of each step are described in the Methods section

Assessment of SIRI and cumulative SIRI

Fasting venous blood samples were collected after an 8-h fast and analyzed for complete blood count and biochemical parameters using a Hitachi 7180 automated biochemistry analyzer (Hitachi, Tokyo, Japan). SIRI was calculated as neutrophil count (10^9/ L) × monocyte count (10^9/ L) / lymphocyte count (10^9/ L), and the cumulative SIRI was calculated as the time-weighted sum of the mean SIRI values between the 2016 and 2018 examinations, using the formula: cumulative SIRI = [(SIRI_2016 + SIRI_2018) / 2] × time (2016–2018) [17, 23]. Thus, cumulative SIRI in the present study was intended to reflect cumulative inflammatory burden before follow-up rather than inflammatory status during the subsequent follow-up period.

Assessments of CKM syndrome

CKM Syndrome is a complex clinical syndrome involving multiple organ systems and is classified into five stages (0 to 4) based on AHA criteria [3]. Stage 0 has no CKM risk factors. Stage 1 involves overweight, obesity or prediabetes. Stage 2 is characterized by at least one metabolic risk factor—hypertension, diabetes, hypertriglyceridemia, or CKD. Stage 3 is defined as the presence of subclinical CVD and at least one metabolic abnormality or CKD. Stage 4 is marked by clinical CVD [24]. Stages 0 to 2 are referred to early-stage CKM syndrome, and stages 3 and 4 are collectively referred to advanced CKM syndrome [25].

Outcome ascertainment

Follow-up data updated as of December 31, 2024 and the primary outcome was all-cause mortality. The follow-up period for each participant commenced on the date of their 2018 health examination and concluded on either the date of death or December 31, 2024, whichever occurred first.

Data collection and measurements

A predesigned questionnaire, administered by trained physicians, was utilized to collect sociodemographic and health information. Sociodemographic variables included age, sex (male or female), BMI, marital status (single or non- single), and educational level (below high school, or high school and above). Health-related data comprised self-reported lifestyle factors, such as smoking and alcohol consumption (both recorded as yes/no), and history of physician-diagnosed conditions including hypertension, diabetes, arrhythmia, CHD, and stroke. Comorbidities such as hypertension and diabetes were self-reported by subjects. Abdominal obesity was defined as waist circumference (WC) ≥ 90 cm in men and ≥ 80 cm in women [26]. BMI was calculated as body mass in kilograms divided by height in meters, squared.

Statistical analysis

Participants were categorized into high and low cumulative SIRI groups based on the ROC-derived cut-off. Differences between the two groups were described using mean ± standard deviation or median (interquartile range) for continuous variables, while frequency (n) and percentage (%) for categorical variables. Kaplan-Meier curves were constructed to visualize survival differences across cumulative SIRI groups. Multivariable Cox proportional hazards models estimated the hazard ratios (HRs) with 95% confidence intervals (CIs), adjusting for age and sex (model 2), and further for marital status, education, smoking, and alcohol (model 3). Multiple interpolation was performed for missing covariates. We explored the potential nonlinear association between cumulative SIRI and all-cause mortality risk using the RCS analysis. Subgroup analyses were conducted to assess whether the observed associations varied across key covariates.

We performed sensitivity analyses to test the robustness of our results. First, participants who died within the first year of follow-up were excluded. Second, we modeled the association by treating cumulative SIRI as a continuous variable. All data analyses were performed using R software (version 4.2.0; R Foundation for Statistical Computing, Vienna, Austria). A two-sided P-value < 0.05 indicated significance for all analyses.

Results

Baseline characteristics of the participants

A total of 3,410 participants were included in the final analysis with a mean age of 60.13 ± 6.03 years in 2016. Females accounted for 80.85%. The baseline characteristics of participants, classified by cumulative SIRI cut-off value, are presented in Table 1. Compared with the low cumulative SIRI group, participants in the high cumulative SIRI group were older, had higher levels of BMI, WC, uric acid, creatinine, and had lower levels of total cholesterol (TC) and high-density lipoprotein cholesterol (HDL-C). Furthermore, this group had a higher proportion of males, a higher prevalence of current smoking and alcohol consumption, a lower educational level, and a higher proportion of single individuals. Similar patterns were observed for baseline characteristics in 2018 (Table S1).

Table 1.

Baseline characteristics of participants according to cumulative SIRI cut-off value in 2016

characteristics		cumulative SIRI groups
		Total		low			high		P
N		3410			949		2461			< 0.001
Age, years		60.13 ± 6.03			58.85 ± 5.74		60.63 ± 6.07			< 0.001
WC, cm		91.00 (85.00, 98.00)			90.00 (84.00, 96.00)		92.00 (86.00, 98.00)			< 0.001
BMI, kg/m2		25.77 (23.53, 28.19)			25.51 (23.34, 27.77)		25.89 (23.62, 28.33)			0.004
Creatinine, µmol/L		59.00 (53.00, 67.00)			57.00 (52.00, 64.00)		60.00 (53.00, 69.00)			< 0.001
Uric acid, µmol/L		301.00 (255.00, 354.75)			290.00 (246.00, 337.00)		306.00 (258.00, 361.00)			< 0.001
TG, mmol/l		1.47 (1.09, 2.07)			1.42 (1.06, 2.09)		1.50 (1.10, 2.07)			0.112
TC, mmol/L		5.23 (4.61, 5.89)			5.30 (4.77, 5.97)		5.20 (4.56, 5.85)			< 0.001
HDL-C, mmol/l		1.34 (1.17, 1.54)			1.37 (1.19, 1.59)		1.33 (1.16, 1.53)			< 0.001
LDL-C, mmol/l		3.22 (2.63, 3.83)			3.29 (2.70, 3.85)		3.20 (2.60, 3.82)			0.075
Sex, n (%)										< 0.001
female		2757 (80.85)			890 (93.78)		1867 (75.86)
male		653 (19.15)			59 (6.22)		594 (24.14)
Education, n (%)										< 0.001
high school and above		644 (18.89)			217 (22.87)		427 (17.35)
below high school		2766 (81.11)			732 (77.13)		2034 (82.65)
Marital status, n (%)										0.003
single		348 (10.21)			73 (7.69)		275 (11.17)
non- single		3062 (89.79)			876 (92.31)		2186 (88.83)
Drinking, n (%)										< 0.001
no		3088 (90.56)			900 (94.84)		2188 (88.91)
yes		322 (9.44)			49 (5.16)		273 (11.09)
Smoking, n (%)										< 0.001
no		3057 (89.65)			899 (94.73)		2158 (87.69)
yes		353 (10.35)			50 (5.27)		303 (12.31)
All-caused death, n (%)										< 0.001
no		3339 (97.92)			942 (99.26)		2397 (97.40)
yes		71 (2.08)			7 (0.74)		64 (2.60)

Relationship between cumulative SIRI and the risk of all-cause mortality

Over a median follow-up of 74.00 months (interquartile range, 72.00–75.00), 71 all-cause deaths (2.08%) were recorded. Kaplan-Meier survival curves demonstrated higher survival rates in the low cumulative SIRI group in middle-aged and elderly individuals with CKM syndrome stages 0–2 (Fig. 2, P < 0.001).

Fig. 2.

Kaplan-Meier curves for all-cause mortality according to cumulative SIRI groups. The figure shows the survival probability over time for patients in the high and low cumulative SIRI groups. The log-rank test was used to compare survival distributions between groups (p < 0.001). HR, hazard ratio; CI, confidential confidence interval; SIRI, Systemic Inflammation Response Index

After adjustment for potential confounders, high cumulative SIRI was associated with a higher risk of all-cause mortality compared with low cumulative SIRI (HR = 2.24; 95% CI, 1.01–4.97; P = 0.048), as shown in the fully adjusted model (Model 3, Table 2). To further evaluate model discrimination, Harrell’s C-index was calculated. The C-index of the conventional model including age, sex, education, drinking, smoking, and marital status was 0.743 (SE = 0.033). After addition of cumulative SIRI group, the C-index increased to 0.759 (SE = 0.032), indicating a slight improvement in discrimination. In addition, restricted cubic spline (RCS) analysis showed a positive association between cumulative SIRI and all-cause mortality risk (P for overall = 0.045). The test for non-linearity was not significant (P for non-linearity = 0.754), indicating a linear dose-response relationship between these two variables (Fig. 3).

Table 2.

Association of cumulative SIRI with all-cause mortality

Variables	Model1		Model2		Model3
	HR (95%CI)	P	HR (95%CI)	P	HR (95%CI)	P
cumulative SIRI group
Low (Reference)	1.00		1.00		1.00
High	3.55 (1.63–7.74)	0.001	2.29 (1.03–5.07)	0.041	2.24 (1.01–4.97)	0.048

Abbreviations: HR Hazard Ratio, CI Confidence Interval, SIRI Systemic Inflammation Response Index

Model 1: Crude model, unadjusted

Model 2: Adjusted for age and sex

Model 3: Adjusted for age, sex, education, marital status, drinking and smoking

Fig. 3.

The associations of cumulative SIRI with risk of all-cause mortality. Cox regression models with restricted cubic splines were fitted to the data with 3 knots at the 10th, 50th, and 90th percentiles of the cumulative SIRI. The solid line represents the point estimate of cumulative SIRI correlation with the risk of all-cause mortality, and the shaded part represents the 95% CI estimate. Covariates in the model include age, sex, education, marital status, drinking and smoking. CI, confidential confidence interval; SIRI, Systemic Inflammation Response Index

Results of the subgroup and sensitivity analyses

Stratified analyses were conducted to assess the association between cumulative SIRI and all-cause mortality across subgroups defined by age, sex, marital status, educational level, smoking status, and alcohol consumption. No significant interactions were observed (Fig. 4, P for interaction > 0.05 for all). In the sensitivity analysis, we excluded participants who died within 1 year of follow-up (Table S2), and the results were consistent with the primary findings. Furthermore, the results were unaffected after analyzing cumulative SIRI as a continuous variable (Table S3).

Fig. 4.

Subgroup analysis of the association between cumulative SIRI and risk of all-cause mortality. The forest plot shows the HRs and 95% CIs for the association across different subgroups. The P values for interaction are shown on the right. HR, hazard ratio; CI, confidence interval; SIRI, Systemic Inflammation Response Index

Discussion

The present study demonstrates that elevated cumulative SIRI is independently associated with an increased risk of all-cause mortality among middle-aged and older individuals with CKM syndrome stages 0–2. This association persisted after adjustment for traditional cardiovascular and metabolic risk factors and showed a clear linear dose–response relationship. Importantly, the association remained broadly consistent across subgroups stratified by age, sex, and lifestyle characteristics, with no statistically significant interactions. These findings suggest that cumulative inflammatory burden estimated from two repeated pre-follow-up measurements, rather than a single cross-sectional assessment, may provide supplementary prognostic information in individuals with early-stage CKM syndrome.

The AHA recently emphasized the importance of identifying individuals in CKM stages 0–2 as a key target for early prevention [6]. Although advanced CKM stages are well recognized to confer substantially elevated mortality risk, the majority of affected individuals remain in early stages, where risk stratification tools are urgently needed. Previous studies have demonstrated that SIRI is associated with cardiovascular and all-cause mortality across different CKM stages [27, 28]. Chen et al. further reported that higher SIRI quartiles were significantly associated with increased mortality risk in populations spanning CKM stages 0–3 [29]. However, evidence specifically focusing on early-stage CKM (stages 0–2) remains limited, and most prior analyses relied on single baseline measurements. By incorporating two pre-follow-up measurements to estimate cumulative exposure, our study extends previous findings and suggests that cumulative inflammatory burden may provide additional prognostic information in early-stage CKM. Even after multivariable adjustment, high cumulative SIRI remained independently associated with mortality (HR = 2.24, 95% CI: 1.01–4.97).

CKM syndrome is characterized by complex interactions among metabolic dysfunction, renal impairment, and cardiovascular pathology. Chronic low-grade inflammation is increasingly recognized as a unifying mechanism underlying these interrelated processes. Adipose tissue–derived cytokines promote insulin resistance and dysregulation of lipid metabolism [30, 31], while pro-inflammatory mediators such as TNF-α and IL-6 impair insulin receptor signaling and glucose uptake [32, 33]. In parallel, inflammatory activation of neutrophils and monocytes contributes to oxidative stress and endothelial dysfunction, thereby accelerating atherosclerosis and vascular stiffness [34, 35]. In the kidney, inflammatory cell infiltration and fibrotic remodeling represent central pathways driving CKD progression [36]. Persistent systemic inflammation may therefore act synergistically across organ systems, amplifying metabolic dysregulation, vascular injury, and renal damage, ultimately increasing mortality risk.

Within this context, cumulative SIRI may serve as an integrated reflecting the sustained activation of innate immune pathways. Compared with a single baseline measurement, cumulative exposure assessment based on two pre-follow-up measurements may partially better characterize inflammatory burden before follow-up and may reduce potential misclassification due to short-term biological fluctuations [37, 38]. This dynamic perspective may be particularly relevant in middle-aged and older populations, who are prone to immune dysregulation and inflammaging, potentially heightening vulnerability to chronic inflammatory insults [39, 40]. Given that SIRI is derived from routine hematological parameters, it represents a practical, cost-effective, and easily implementable tool for identifying high-risk individuals in both clinical and community settings.

Inflammation is increasingly recognized as a contributor to cardiovascular risk and adverse outcomes, and inflammatory biomarkers have attracted growing interest in risk assessment [41]. However, most evidence comes from high-risk cardiovascular settings, and the incremental clinical utility of these biomarkers may be modest and vary across populations and outcomes [42]. Therefore, the prognostic relevance of cumulative SIRI in a community-based CKM population should be interpreted cautiously and requires further validation before clinical use.

In subgroup analyses, although statistically significant associations were primarily observed among non-smokers and non-drinkers, no significant interaction terms were detected. This suggests that the overall association between cumulative SIRI and mortality was generally consistent across demographic and lifestyle strata. The lack of significance in certain subgroups may be attributable to limited statistical power due to smaller sample sizes, and these findings should therefore be interpreted cautiously.

Strengths

This study has several strengths. It is a large community-based prospective cohort with long-term follow-up and biomarker measurements at two pre-follow-up time points. To our knowledge, it is among the first to investigate the association between cumulative SIRI exposure and mortality risk in individuals with early-stage CKM syndrome. By moving beyond single-time measurements, our analysis provides additional information on cumulative inflammatory burden before follow-up.

Limitations

Nevertheless, several limitations should be acknowledged. First, cumulative SIRI was derived from only two pre-follow-up time points, which may not fully capture the complex temporal trajectories of inflammation. Therefore, cumulative SIRI in this study should be interpreted as a proxy for cumulative inflammatory burden before follow-up rather than as a fully dynamic long-term exposure measure. More frequent measurements would allow a more refined characterization of inflammatory dynamics. Second, despite adjustment for multiple covariates, residual confounding cannot be completely excluded. Third, the relatively small number of outcome events may have limited the stability and precision of the estimated association, particularly in stratified analyses, and may partly explain the borderline statistical significance and relatively wide confidence interval observed in the fully adjusted model. Fourth, although cumulative SIRI slightly improved model discrimination beyond conventional risk factors, its incremental predictive value relative to simpler inflammatory biomarkers, such as CRP, was not formally assessed in the present study. Finally, although CKM staging in the present study was based on the current AHA criteria and is therefore comparable with internationally used definitions, participants were recruited from three community health centers within the same district. Thus, the generalizability of the findings to other ethnic or geographic populations may still be limited, and further validation in broader populations and settings is needed.

Conclusion

In this prospective cohort study of middle-aged and older adults with CKM syndrome stages 0–2, elevated cumulative SIRI was independently associated with an increased risk of all-cause mortality. These findings suggest that cumulative SIRI estimated from two pre-follow-up measurements may help identify individuals at higher risk in this population, although further validation is needed.

Abbreviations

SIRI

Systemic inflammation response index

CKM syndrome

Cardiovascular-kidney-metabolic syndrome

NCDs

Non-communicable diseases

CVD

Cardiovascular disease

CKD

Chronic kidney disease

WC

Waist circumference

BMI

Body mass index

TC

Total cholesterol

HDL-C

High-density lipoprotein cholesterol

NLR

Neutrophil-to-lymphocyte ratio

PLR

Platelet-to-lymphocyte ratio

MLR

Monocyte-to-lymphocyte ratio

HR

Hazard ratio

CI

Confidence interval

ROC

Receiver operating characteristic

RCS

Restricted cubic spline

DALYs

Disability-adjusted life years

GBD

Global Burden of Disease

AHA

American Heart Association

Authors’ contributions

X.J.L: Writing – original draft, Writing- Reviewing and Editing, Formal analysis, Visualization, Conceptualization. W.H. C: Writing- Reviewing and Editing, Conceptualization, Methodology. W.L.L: Writing- Reviewing and Editing, Data curation, Conceptualization. Y.T. C: Writing- Reviewing and Editing, Conceptualization, Methodology. R.C.H: Writing- Reviewing and Editing, Conceptualization, Funding acquisition, Project administration, Supervision.

Funding

This work was partially supported by the Leading Talents Plan, Beijing Municipal Health Commission (No. LJRC20240306; Beijing, China).

Data availability

The datasets generated and/or analysed during the current study are not publicly available due to ethical and privacy restrictions, as they contain sensitive patient information collected from community hospitals and are part of an ongoing longitudinal study. Data may be available from the corresponding author upon reasonable request and with appropriate ethical approval.

Declarations

Ethics approval and consent to participate

Tongzhou Cohort Study (ClinicalTrials.gov Identifier: NCT05156580) is an ongoing prospective cohort established by Beijing Friendship Hospital, Capital Medical University. The study was conducted in accordance with the ethical principles of the 1975 Declaration of Helsinki and received approval from the Ethics Committee of Beijing Friendship Hospital, Capital Medical University (Beijing, China) (approval no. 2021-P2-163-02).

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.