Estimated pulse wave velocity, waist-to-height ratio, and risk of cardiometabolic multimorbidity: A secondary dataset analysis of the China Health and Retirement Longitudinal Study (CHARLS)

估计脉搏波速度、腰高比和心血管代谢多病风险:中国健康与养老追踪调查(CHARLS)的二次数据集分析

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Abstract

INTRODUCTION: Obesity, smoking, and atherosclerosis increase the risk of developing various cardiometabolic diseases. The estimated pulse wave velocity (ePWV) is a new indicator of arterial stiffness. However, the relationship between ePWV, waist-to-height ratio (WHtR), smoking, and cardiometabolic multimorbidity (CMM) remains unclear. METHODS: The study is a secondary dataset analysis of CHARLS, which included 8414 participants from the China Health and Retirement Longitudinal Study conducted between 2011 and 2018. The ePWV was calculated using the mean blood pressure and age. Cox proportional hazards models were used to explore the relationship between ePWV, WHtR, and CMM in both smoking and non-smoking populations. Additionally, we also employed restricted cubic spline (RCS) analysis and mediation analysis to investigate the relationship between ePWV, WHtR, and CMM. A p<0.05 was considered statistically significant. RESULTS: During the 7-year follow-up period, 1545 participants (18.36%) developed new-onset CMM. The RCS model exhibited a U-shaped relationship between WHtR and CMM incidence, with a positive correlation when WHtR exceeded 0.5. Cox regression analysis revealed that ePWV and WHtR were independent predictors of CMM in both smoking and non-smoking populations. Additionally, ePWV significantly mediated the association between WHtR and CMM risk. CONCLUSIONS: Our findings indicate that ePWV and WHtR are associated with increased CMM risk. Early detection of ePWV and WHtR, combined with smoking cessation, may help identify high-risk individuals and provide a basis for future preventive research.

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