1. 2025;28;E667-E676The Association Between the Triglyceride-Glucose Index and Its Combination with Obesity Metrics and Adult Spinal Pain: A Cross-Sectional Study
   Cross-Sectional Study
   Liu ZX, MD, and Gong DK, PhD.

BACKGROUND: Spinal pain, particularly low back pain, poses a significant health and economic burden, contributing to widespread disability and economic costs. Emerging evidence suggests a connection between spinal pain and metabolic conditions, such as insulin resistance and obesity. When combined with obesity metrics, the triglyceride-glucose (TyG) index, a reliable marker for insulin resistance, may provide enhanced predictive value for metabolic syndrome and related health outcomes. However, the association of the TyG index with spinal pain remains underexplored. 

OBJECTIVES: This study explores the connection of the TyG and TyG-obesity metrics (TyG-WC, TyG-WHtR, and TyG-BMI) to spinal pain. The analysis relies on data collected through the National Health and Nutrition Examination Survey from 1999 to 2004.

STUDY DESIGN: A cross-sectional study was conducted on 31,126 NHANES participants aged >= 20 years. 

METHODS: Weighted multivariable logistic regression models were utilized to evaluate the associations of the TyG index and TyG-obesity metrics with spinal pain outcomes. Restricted cubic spline analysis was employed to assess dose-response relationships, and receiver operating characteristic (ROC) analysis quantified the predictive accuracy of these indicators.

RESULTS: Higher levels of the TyG index and TyG-obesity metrics (TyG-WC, TyG-WHtR, and TyG-BMI) were strongly linked to a greater occurrence of spinal pain and associated functional impairments (P trend < 0.001). Among these indicators, TyG-WC demonstrated the greatest predictive value for spinal pain (OR 1.70; 95% CI 1.53-1.89), whereas TyG-WHtR showed the most effective diagnostic performance across various spinal pain outcomes (AUC: 0.647; 95% CI 0.635-0.659). The associations demonstrated both linear and nonlinear trends, emphasizing the complex interplay between metabolic factors and spinal pain.

LIMITATIONS: This study's cross-sectional design means that temporal relationships cannot be established, thus limiting causal inference. Additionally, self-reported data may introduce bias, and residual confounding cannot be fully excluded.

CONCLUSIONS: This research work highlights the potential of the TyG and TyG-obesity metrics as valuable tools for predicting and diagnosing spinal pain and associated functional limitations. Incorporating these metabolic markers into clinical assessments could enhance early detection and intervention strategies for individuals at risk of spinal pain.

KEY WORDS: Triglyceride-glucose index, spinal pain, metabolic syndrome, obesity metrics, NHANES