Association between weight-adjusted-waist index and gynecologic cancers: a population-based study

This study aims to analyze the association between the weight-adjusted waist index (WWI) and the risk of gynecologic cancers, using data collected from the National Health and Nutrition Examination Survey (NHANES) from 2011 to 2016.

We employed multiple logistic regression analysis to investigate the relationship between WWI and risk of gynecologic cancers. Subsequent subgroup analyses were performed on specific populations of interest. A restricted cubic spline model was used to explore potential non-linear relationships. Additionally, the effectiveness of WWI in predicting sarcopenia was assessed through Receiver Operating Characteristic (ROC) curve analysis. K-fold cross-validation was applied for model assessment.

Among the 4,144 participants, 98 self-reported having gynecologic cancers. In the fully adjusted model, WWI was significantly associated with the prevalence of gynecologic cancers (OR = 1.38, 95% CI: 1.02-1.88, p = 0.0344). Our findings indicate a linear positive association between WWI and the risk of gynecologic cancers. Subgroup analysis revealed that WWI had the strongest association with cervical cancer (OR = 1.46, 95% CI: 0.97-2.18, p = 0.0354) and endometrial cancer (OR = 1.39, 95% CI: 0.81-2.39, p = 0.0142). No significant association was found between WWI and the risk of ovarian cancer (OR = 1.16, 95% CI: 0.48-2.72, p = 0.5359). Restricted cubic spline analysis confirmed a linear relationship between WWI and the risk of cervical, endometrial, and ovarian cancers. ROC curve analysis demonstrated that WWI had superior predictive capability for gynecologic cancers.

Elevated levels of WWI were significantly associated with an increased risk of gynecologic cancers in American women, displaying a stronger association than other obesity markers. Therefore, WWI may serve as a distinct and valuable biomarker for assessing the risk of gynecologic cancers, particularly cervical and endometrial cancers.