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
. 2025 May 21:21925682251344593.
doi: 10.1177/21925682251344593. Online ahead of print.

Deciphering the Threshold and Segmented Nonlinear Association Between Systemic Inflammation Response Index and Spinal Bone Density: Insights From a Large-Scale Population Study

Affiliations

Deciphering the Threshold and Segmented Nonlinear Association Between Systemic Inflammation Response Index and Spinal Bone Density: Insights From a Large-Scale Population Study

Muradil Mardan et al. Global Spine J. .

Abstract

Study DesignCross-sectional study.ObjectiveTo examine the association between SIRI and spinal BMD and assess the influence of age, hypertension, and diabetes.MethodsWe analyzed data from 13,950 participants aged ≥20 years. SIRI was calculated using neutrophil, monocyte, and lymphocyte counts, and spinal BMD was measured by DXA. Linear regression, generalized additive models, and segmented regression were used, with subgroup analyses based on age, hypertension, and diabetes.ResultsA threshold effect was observed at SIRI = 0.68. Below this threshold, SIRI negatively correlated with spinal BMD (β = -0.0412, P = 0.0494), while above it, a positive correlation was found (β = 0.0079, P < 0.0001). Subgroup analyses showed stronger positive associations in older adults (≥65 years, β = 0.0136, P < 0.0001), and those with hypertension (β = 0.0089, P = 0.0004) and diabetes (β = 0.0187, P < 0.001).ConclusionA segmented nonlinear relationship exists between SIRI and spinal BMD, with age, hypertension, and diabetes as significant modifiers. SIRI may serve as a biomarker for osteoporosis risk.

Keywords: bone health; inflammation biomarkers; osteoporosis; population-based study; spinal bone mineral density; systemic inflammation response index.

PubMed Disclaimer

Conflict of interest statement

The authors declare no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Figures

Figure 1.
Figure 1.
Flowchart of participant selection and analytical steps.
Figure 2.
Figure 2.
Adjusted associations between SIRI and spinal BMD using GAM (A) unadjusted model - The smooth function displays the baseline association between SIRI and spinal BMD without adjustment for any covariates. (B) Minimally adjusted model - Adjusted for basic demographic characteristics, including sex, race, marital status, education level, smoking and drinking status, history of diabetes, and hypertension. Shows the independent effect of SIRI on spinal BMD. (C) Fully adjusted model - Adjusted for all key covariates, including sex, race, marital status, education level, lifestyle factors (smoking and drinking), diabetes and hypertension history, as well as age, weight, height, BMI, WC, TC, HDL-C, LDL-C, and TG, showing the effect of SIRI on spinal BMD with comprehensive variable control.
Figure 3.
Figure 3.
Scatter plot of the segmented relationship between SIRI and Spinal BMD (A) Displays the overall association between SIRI and spinal BMD, illustrating the general trend across the full range of SIRI values. (B) Shows the relationship between SIRI and spinal BMD for SIRI values below the identified threshold of 0.68. This segment indicates a slight negative association, aligning with the threshold effect observed in the analysis. (C) Illustrates the association for SIRI values equal to or above 0.68, where a positive relationship between SIRI and spinal BMD becomes evident, supporting the hypothesis that higher SIRI levels are associated with higher spinal BMD values.

Similar articles

References

    1. Wu A, Bisignano C, James SL, et al. Global, regional, and national burden of bone fractures in 204 countries and territories, 1990–2019: a systematic analysis from the global burden of disease study 2019. The Lancet Healthy Longevity. 2021;2(9):e580-e592. - PMC - PubMed
    1. Voltan G, Di Giovannantonio G, Carretta G, et al. A novel case-finding strategy based on artificial intelligence for the systematic identification and management of individuals with osteoporosis or at varying risk of fragility fracture. Arch Osteoporosis. 2024;19(1):45. - PubMed
    1. Kumar S, Beck BR, Nery L, et al. Study protocol for the ROLEX-DUO randomised placebo-controlled trial: romosozumab loaded with exercise - dual effects on bone and muscle in postmenopausal osteoporosis and osteopenia. BMJ Open. 2024;14(8):e086708. - PMC - PubMed
    1. Clark P, Calo M, Torres-Naranjo JF, et al. Osteoporosis and fragility fractures in Mexico: a call to action. Arch Med Res. 2024;55(7):103062. - PubMed
    1. Linton C, Schaumberg MA, Wright HH. Dietary inflammatory index is not associated with bone mineral density in functionally able community-dwelling older adults. Eur J Nutr. 2024;63(8):3195-3205. - PMC - PubMed

LinkOut - more resources