Association between eight anthropometric indices and chronic low back pain: A cross-sectional study from the NHANES...

Emerging evidence establishes a robust association between obesity and chronic low back pain (CLBP) development. This cross-sectional study systematically evaluated 8 body composition metrics and their associations with CLBP risk using data from 4751 participants (mean age: 43.03 ± 0.33 years; 50.61% female) in the National Health and Nutrition Examination Survey. Following National Health and Nutrition Examination Survey protocols and established formulas, we computed 8 anthropometric indices: body mass index, waist circumference, waist-to-height ratio, body roundness index, weight-adjusted waist index, conicity index (CI), relative fat mass, and a body shape index. Multivariate regression analysis and restricted cubic splines were used to analyze the associations between these 8 anthropometric indices and CLBP prevalence. Stratified analyses evaluated subgroup variations, while receiver operating characteristic curve analysis was employed to quantify the predictive validity of these anthropometric indices. Analytical findings revealed significant associations between CLBP and all adiposity metrics except a body shape index. Specifically, in the model adjusted for all covariates, per 1 z-score increase in waist circumference, WtHR, body mass index, weight-adjusted waist index, body roundness index, relative fat mass, CI was a significantly correlated with elevated CLBP risks of 27% (odds ratio [OR]: 1.27, 95% CI: 1.15-1.41; P < .001), 26% (OR: 1.26, 1.14-1.40; P < .001), 25% (OR: 1.25, 1.13-1.37; P < .001), 19% (OR: 1.19, 1.06-1.34; P = .004), 25% (OR: 1.25, 1.14-1.38; P < .001), 44% (OR: 1.44, 1.21-1.71; P < .001), and 22% (OR: 1.22,1.09-1.36; P < .001), respectively. Restricted cubic splines analyses established linear dose-response relationships between these indices and CLBP risk (P-value for nonlinearity ≥ .253 for all). Among all adiposity metrics evaluated, the CI yielded the highest area under the curve value (0.5976, 95% CI: 0.573-0.622) in receiver operating characteristic analysis, indicating enhanced discriminatory capacity. Subgroup and interaction analyses validated the consistency of these findings. This study revealed that various anthropometric measures are significantly associated with the risk of CLBP development. Therefore, integrating these anthropometric factors into early preventive strategies may significantly reduce the incidence of CLBP and improve public health outcomes.