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- Abstract: adrenarche x
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- Obesity x
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Background
Reproductive hormones may be a risk factor for cardiovascular disease (CVD), but their influence is often underestimated. Obesity can exacerbate the progression of CVD. Arterial stiffness (AS) is correlated with the risk of CVD. Brachial-ankle pulse wave velocity (baPWV) has served as a practical tool for assessing AS with broad clinical applications. This study aimed to investigate the association between reproductive hormones and baPWV in obese male and female subjects.
Methods
A retrospective case–control design was designed. AS was assessed using baPWV, with a baPWV ≥ 1400 cm/s indicating increased AS. Between September 2018 and October 2022, 241 obese subjects with increased AS were recruited from Ningbo Yinzhou No. 2 Hospital. The control group consisted of 241 obese subjects without increased AS. A 1:1 propensity score matching was performed to correct potential confounders by age and sex. We additionally performed a sex-based sub-analysis.
Results
Correlation analysis demonstrated that luteinizing hormone (LH) (r = 0.214, P = 0.001) and follicle-stimulating hormone (FSH) (r = 0.328, P < 0.001) were positively correlated with baPWV in obese male subjects. In the multivariate conditional logistic regression analysis, FSH (OR = 1.407, 95% CI = 1.040–1.902, P = 0.027) rather than LH (OR = 1.210, 95% CI = 0.908–1.612, P = 0.194) was independently and positively associated with increased AS in obese male subjects. However, there was no significant correlation between reproductive hormones and baPWV in women.
Conclusions
Our study identified FSH as a potential risk factor for arteriosclerosis in obese male subjects. This provides a novel and intriguing perspective on the pathogenesis of CVD in obese subjects.
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Objective
To create a nomogram-based model to estimate the Chinese population's 5-year risk of metabolic dysfunction-associated steatotic liver disease (MASLD).
Methods
We randomly divided 7582 participants into two groups in a 7:3 ratio: one group was assigned to work with the training set, which consisted of 5307 cases, and the other group was assigned to validate the model using 2275 cases. The least absolute shrinkage and selection operator model was employed to ascertain the variables with the highest correlation among all potential variables. A logistic model was constructed by incorporating these selected variables, which were subsequently visualized using a nomogram. The discriminatory ability, calibration, and clinical utility of the model were assessed using the receiver operating characteristic (ROC) curve, calibration curve, and decision curve analysis (DCA).
Results
During the 5-year follow-up, 1034 (13.64%) total participants were newly diagnosed with MASLD. Using eight variables (gender, body mass index, waist, hemoglobin, alanine aminotransferase, uric acid, triglycerides, and high-density lipoprotein), we built a 5-year MASLD risk prediction model. The nomogram showed an area under the ROC of 0.795 (95% CI: 0.779–0.811) in the training set and 0.785 (95% CI: 0.760–0.810) in the validation set. The calibration curves revealed a 5-year period of agreement between the observed and predicted MASLD risks. DCA curves illustrated the practicality of this nomogram over threshold probability profiles ranging from 5% to 50%.
Conclusion
We created and tested a nomogram to forecast the risk of MASLD prevalence over the next 5 years.
