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The Temporal Pattern of Arterial Stiffness during Aging: A Large-Scale Cross-Sectional Study
Zhengli Tang1, Yuanyuan Lu2, Yiming Hao3
1Shuguang Hospital Health Examination Center Affiliated with Shanghai University of Traditional Chinese Medicine, Shanghai 201203, China.
Journal of Diabetes Research
|December 20, 2021
Summary
Arterial stiffness, measured by brachial-ankle pulse wave velocity (baPWV), increases with age. This study reveals how age, sex, blood pressure, and glucose levels influence baPWV, aiding cardiovascular risk prediction.
Area of Science:
- Cardiovascular Physiology
- Biomedical Engineering
- Gerontology
Background:
- Brachial-ankle pulse wave velocity (baPWV) quantifies aortic and peripheral arterial stiffness noninvasively.
- Arterial stiffness increases with age and is linked to cardiovascular disease.
- Factors like hypertension, diabetes, and hyperlipidemia elevate baPWV.
Purpose of the Study:
- To investigate the temporal pattern of baPWV values throughout the aging process.
- To examine the influence of biological sex, blood pressure, and blood glucose on baPWV.
- To enhance prediction models for age-related cardiovascular events.
Main Methods:
- Longitudinal analysis of brachial-ankle pulse wave velocity (baPWV) measurements across different age groups.
- Statistical correlation of baPWV with age, biological sex, blood pressure, and blood glucose levels.
- Assessment of the difference between bilateral baPWV (ΔbaPWV) in relation to aging.
Main Results:
- A consistent increase in baPWV was observed with advancing age, indicating progressive arterial stiffening.
- Men exhibited higher baPWV than women until age 50; thereafter, women showed a faster increase.
- Blood pressure and blood glucose levels were significantly associated with baPWV values.
Conclusions:
- Aging is associated with increased arterial stiffness, as evidenced by rising baPWV.
- Sex-specific patterns in baPWV progression emerge after age 50.
- Incorporating age, sex, blood pressure, and glucose data can refine cardiovascular risk prediction models.
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