Quantitative computed tomography for assessing body composition in schizophrenia: a potential indicator of insulin resistance

Objective To investigate the relationship between the Homeostasis Model Assessment of Insulin Resistance (HOMA-IR) index and organ body composition, and to evaluate the potential of quantitative computed tomography (QCT) parameters as biomarkers for indicating insulin resistance (IR) in schizophrenia. Materials and methods A total of 924 patients with schizophrenia were enrolled and categorized into non-IR (HOMA-IR ≤ 2.5) and IR (HOMA-IR > 2.5) groups. Quantitative computed tomography (QCT) systematically measured parameters such as bone mineral density (BMD), hepatic fat fraction, and areas of subcutaneous adipose tissues (SAT) and visceral adipose tissues (VAT). Univariate and multivariate logistic regression analyses were performed to identify independent predictors of IR. The indicative performance of individual parameters and combined models-including a QCT parameters-only model and a model integrating QCT parameters with clinical covariates (gender, age, BMI)-was evaluated using receiver operating characteristic (ROC) curve analysis. Results Patients in the IR group (n=332) demonstrated significantly elevated levels of all QCT parameters compared to the non-IR group (n=592): BMD (125.27 vs. 114.01 mg/cm³), liver fat (10.14% vs. 6.61%), SAT (138.55 vs. 82.20 cm²), and VAT (222.83 vs. 131.92 cm²) (all P < 0.001). While all four parameters were significant in univariate analysis, multivariate analysis adjusted for age, sex, and BMI identified VAT (Adjusted OR: 1.013, 95% CI: 1.009–1.016, P < 0.001) and liver fat content (Adjusted OR: 1.092, 95% CI: 1.051–1.135, P < 0.001) as the only independent indicators. The area under the curve (AUC) for individual parameters was 0.790 for VAT, 0.769 for SAT, 0.664 for liver fat, and 0.574 for BMD. The combined QCT parameters-only model achieved an AUC of 0.834, which was significantly improved to 0.852 ( P = 0.001 by DeLong’s test) after incorporating clinical covariates. Conclusion Visceral adipose tissue and liver fat content, as measured by QCT, are robust and independent indicator of insulin resistance in patients with schizophrenia. A model combining QCT parameters with basic clinical covariates offers the best predictive performance for identifying IR risk in this population, highlighting the critical role of ectopic fat deposition in metabolic dysregulation.