Gender-specific thresholds and nonlinear associations of obesity indices with hyperlipidemia: insights from NHANES 20072020

Hyperlipidemia, a significant contributor to cardiovascular ailments, have a close association with obesity, is closely linked to obesity. Traditional anthropometric indices (BMI, WHR, WHtR) are widely used to assess obesity, but their nonlinear relationships with hyperlipidemia and gender-specific risk thresholds remain poorly understood. Leveraging data from 2,739 participants in the NHANES 20072020, this research utilized multivariable logistic regression analysis along with restricted cubic splines (RCS) to investigate both linear and nonlinear relationships between various obesity indices and the presence of hyperlipidemia. Nonlinear dose-response relationships were observed for BMI, WHR, and WHtR with hyperlipidemia (P for nonlinear < 0.001). Gender-specific risk thresholds were identified: males: WHR > 0.94, WHtR > 0.76, BMI >28.0; Females: WHR 0.910.99, WHtR 0.610.69, BMI 29.434.39. Gender differences in effect sizes were significant (e.g., WHR : males 6.986, P<0.001 vs. females 5.666, P=0.023). Subgroup analysis showed stronger associations in younger individuals (50 years) without hypertension or diabetes. WHR remained an independent predictor in metabolic comorbidities, while BMI and WHtR were confounded by metabolic disturbances. This study highlights the importance of gender-specific risk thresholds for obesity indices, particularly WHR, in predicting hyperlipidemia. The results demonstrate that WHR serves as a more reliable predictor for metabolic disorder risks compared to other anthropometric indices, particularly highlighting the importance of implementing preventive measures in populations under 50 years of age. Future research should focus on developing precision stratification models to optimize obesity management.