Evaluating and comparing the predictive ability with hypertension risk among obesity indicators: a prospective cohort integrating Mendelian randomization analysis.

Objective: This study aimed to compare and evaluate the predictive ability of obesity-related indicators for new-onset hypertension, and to explore causal effects using Mendelian randomization (MR). Methods: A total of 22, 912 eligible participants were included from the Henan Rural Cohort Study. Logistic regression was used to identify key predictors of hypertension, and gradient boosting machine (GBM) models incorporating ten obesity indices were developed. Model performance was evaluated using the area under the curve (AUC), and indicator importance was assessed with SHapley Additive exPlanations (SHAP). A multi-state Markov model estimated life expectancy (LE) and health-adjusted life expectancy (HALE). Causal associations were examined through MR analysis. Results: The basic GBM model achieved an AUC of 0.835 (95% Conclusion: Obesity-related indicators are significantly associated with new-onset hypertension, and they are linked to increased LE and reduced HALE. The findings provide evidence to early recognition and prevention of hypertension risk based on obesity-related indicators.