Relationship between weight-adjusted-waist index and erectile dysfunction in the United State: results from NHANES 2001-2004.

Objective: The purpose of this study is to examine the association between a novel adiposity parameter, the weight-adjusted-waist index (WWI), and erectile dysfunction (ED).
Methods: According to National Health and Nutrition Examination Survey (NHANES) 2001-2004, a total of 3884 participants were categorized as ED and non-ED individuals. WWI was calculated as waist circumference (WC, cm) divided by the square root of weight (kg). Weighted univariable and multivariable logistic regression models were conducted to assess the correlation between WWI and ED. Smooth curve fitting was utilized to examine the linear association. The receiver operating characteristic (ROC) curve and DeLong et al.'s test were applied to compare the area under curve (AUC) value and predictive power among WWI, body mass index (BMI), and WC for ED.
Results: WWI was positively related to ED with the full adjustment [odds ratio (OR)=1.75, 95% confidence interval (95% CI): 1.32-2.32, p=0.002]. After converting WWI to a categorical variable by quartiles (Q1-Q4), compared to Q1 the highest WWI quartile was linked to an obviously increased likelihood of ED (OR=2.78, 95% CI: 1.39-5.59. p=0.010). Subgroup analysis revealed the stability of the independent positive relationship between WWI and ED. It was shown that WWI had a stronger prediction for ED (AUC=0.745) than BMI (AUC=0.528) and WC (AUC=0.609). Sensitivity analysis was performed to verify the significantly positive connection between WWI and stricter ED (OR=2.00, 95% CI: 1.36-2.94, p=0.003).
Conclusion: An elevated WWI was related to higher risks of ED in the United State adults, and a stronger predictive power of WWI for ED was observed than BMI and WC.
Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
(Copyright © 2023 Cao, Hu, Shao, Wang, Tang, Ren and Li.)