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

评估和比较肥胖指标对高血压风险的预测能力:一项整合孟德尔随机化分析的前瞻性队列研究

阅读:3

Abstract

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% CI: 0.826-0.844), with body mass index (BMI) showing the highest predictive value (AUC = 0.844). SHAP analysis revealed that all obesity indicators were positively associated with new-onset hypertension but ranked below age and blood pressure level in importance. At age 18, LE was 62.72, 66.11, 68.79 years for individuals with normal weight, overweight, and obesity, respectively. The corresponding HALE was 29.45, 26.23, 22.29 years. MR analysis confirmed causal associations of obesity indicators with hypertension. 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.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。