JoVE Video Dataset
Abstract
Endometriosis is a prevalent gynecological disorder associated with chronic low-grade inflammation, yet diagnosis is often delayed because symptoms are non-specific and definitive confirmation typically relies on invasive procedures. Composite indices that jointly capture inflammatory and metabolic disturbance may improve population-level risk stratification and inform earlier clinical evaluation. Using cross-sectional data from 1,805 women aged 20–54 years in NHANES 1999–2006 (146 self-reported endometriosis; 1,659 controls), we examined survey-weighted associations between a C-reactive protein–triglyceride–glucose composite index and endometriosis risk. Survey-weighted multivariable logistic regression was used to estimate odds ratios and 95% confidence intervals for the index modeled as a continuous exposure and by quartiles. Restricted cubic splines and piecewise regression were applied to evaluate non-linear patterns and to identify potential threshold effects. To contextualize the incremental value of the composite index, we compared its performance with established inflammatory indices and with component markers, including C-reactive protein and the triglyceride–glucose index, using receiver operating characteristic analyses. This workflow provides a reproducible, survey-weighted analytic framework for evaluating composite inflammation–metabolism indicators and their threshold behavior in relation to endometriosis risk.
Fields of Study & Subjects
Endometriosis Research and Treatment
Adipokines
Inflammation
and Metabolic Diseases
Inflammatory Biomarkers in Disease Prognosis
Publication details
- Publication date
- 11 March 2026
- Language
- EN
- Document type
- Dataset