Association Between Systemic Immune‐Inflammation Index and Low Back Pain in American Adults: Evidence From a Large Population‐Based Study

BACKGROUND: Low back pain imposes a substantial global health burden, impairing productivity and quality of life. Emerging evidence implicates systemic inflammation in its pathogenesis. The Systemic Immune-Inflammation Index (SII), a validated inflammatory biomarker, may elucidate this relationship. This study investigated the SII-low back pain association. METHODS: The study employed data from the National Health and Nutrition Examination Survey (NHANES) for the cycles 2001-2004 and 2009-2010. The connection of SII with low back pain was investigated using a weighted multivariable regression analysis model. Subgroup analyses were conducted, stratifying participants by gender and age. Restricted cubic spline (RCS) examined potential nonlinear dose-response relationships. RESULTS: This research analysed 17,286 subjects. Following log-transformation of SII, a fully adjusted model demonstrated that SII was significantly associated with low back pain (OR = 1.41; 95% CI: [1.31, 1.52]; p < 0.001). Participants in the highest quartile of SII had a 66% higher probability of having low back pain compared with those in the lowest quartile (OR = 1.66; 95% CI: [1.44, 1.92]; p < 0.001). This positive association remained significant in both sexes (OR = 1.37; 95% CI: [1.19, 1.57]; p < 0.001; OR = 1.45; 95% CI: [1.33, 1.59]; p < 0.001). In the 20-40 and 40-60 years age groups, the study found a similar association (OR = 2.05; 95% CI: [1.65, 2.55]; p < 0.001; OR = 1.46; 95% CI: [1.14, 1.86]; p = 0.004). CONCLUSIONS: Higher SII values show a significant correlation with a greater likelihood of developing low back pain. SIGNIFICANCE STATEMENT: This large-scale study reveals, for the first time, a significant association between the systemic immune-inflammation index (SII) and low back pain in U.S. adults. Through stratified analysis, our study provides potential stratification indicators for the early prediction of low back pain.