The association of triglyceride-glucose index and uric acid-high-density lipoprotein cholesterol ratio with the risk of uterine fibroids: a real-world analysis based on health examination data
摘要
To investigate the association of triglyceride-glucose index (TyG) and uric acid to high-density lipoprotein cholesterol ratio (UHR) with the prevalence of uterine fibroids (UF), and to evaluate the dose-response relationship and differences in different subgroups.
MethodsThis cross-sectional study employed real-world data from 40,529 adult female participants who underwent health examinations at Hebei Province Health Examination Center between January 1 and December 31, 2024. This study used multiple logistic regression analysis to determine the independent association between standardized TyG index, UHR, and UF risk. The dose-response relationship was evaluated with restricted cubic spline (RCS), and stratified analysis was conducted according to BMI, diabetes and menopause status.
ResultsAmong 40,529 participants, the prevalence of UF was 29.8% (12,081 cases). The results of the fully adjusted model (Model 3) showed that both the standardized TyG index and UHR were significantly positively correlated with UF risk: for every 1 standard deviation (SD) increase in TyG, UF risk increased by 2.068 times (OR = 3.068); For every 1 SD increase in UHR, the risk increased by 11.7% (OR = 1.117). RCS analysis revealed that both the TyG index and UHR exhibited significant nonlinear associations with the risk of UF (P_overall < 0.001). Hierarchical analysis showed that TyG maintained significant correlation in all subgroups, while the effect of UHR was weakened in people with BMI ≥ 25 kg/m2 and diabetes (P > 0.05).
ConclusionElevated TyG index and UHR are significantly correlated with an increased prevalence risk of UF in women, and exhibit a non-linear dose-response relationship. The TyG index demonstrated a relatively significant association with UF risk, and the findings remained robust, supporting its utility as a simple indicator for capturing the relationship between metabolic abnormalities and UF risk.