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.