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Author Spotlight: Assessing the Cardiovascular Profile of Patients with Metabolic Syndrome
Published on: September 27, 2024
National cohort study on cardiometabolic index and incident stroke in middle-aged and older adults in China
HaiXia He1, DanDan Li2, LiangYing Liao1
1The First Hospital of Hunan University of Chinese Medicine, Changsha, China.
Insights
The Cardiometabolic Index (CMI) is linked to higher stroke risk in older Chinese adults. This marker can help predict and prevent strokes in public health initiatives.
Area of Science:
- Cardiology
- Metabolic Health
- Public Health
Background:
- The Cardiometabolic Index (CMI) integrates central obesity and lipid metabolism.
- CMI is a marker for metabolic health, linked to diabetes and cardiovascular diseases.
- CMI's role in stroke risk prediction is not well-established.
Purpose of the Study:
- To investigate the association between CMI and stroke risk.
- To assess CMI as a predictive tool for stroke in Chinese adults aged 45+.
Main Methods:
- Analysis of data from the China Health and Retirement Longitudinal Study (CHARLS).
- Participants categorized into CMI quartiles; stroke incidence as primary endpoint.
- Cox proportional hazards models, Kaplan-Meier curves, and restricted cubic splines (RCS) used for analysis.
Main Results:
- 7,821 participants followed for 7 years; 418 strokes observed.
- Higher CMI significantly associated with increased stroke risk (HR=1.153, P=0.004).
- RCS showed a non-linear increase in stroke risk with rising CMI (P=0.005).
Conclusions:
- Elevated CMI correlates with increased stroke risk in middle-aged and older Chinese adults.
- Integrating CMI into routine assessments may enhance early stroke prevention.
- This approach can help manage the growing burden of cerebrovascular disease.
Abstract:
Background The Cardiometabolic Index (CMI), a novel marker integrating central obesity and lipid metabolism, serves as a comprehensive indicator of metabolic health. While CMI has been linked to metabolic disorders like diabetes and cardiovascular diseases, its role in predicting stroke risk remains unclear. This study examines the association between CMI and stroke risk in Chinese adults aged 45 and older, highlighting its potential as a predictive tool for public health.
Methods:
Data from the China Health and Retirement Longitudinal Study (CHARLS) were analyzed. Participants were divided into CMI quartiles. Stroke incidence was the primary endpoint. Cox proportional hazards models evaluated the CMI-stroke risk association. Kaplan-Meier curves compared stroke incidence across quartiles, while restricted cubic splines (RCS) assessed non-linear trends. Subgroup analyses verified robustness.
Results:
Among 7,821 participants (47 % male), 418 strokes (5.3 %) occurred over a mean follow-up of 7 years. Higher CMI was significantly associated with increased stroke risk [HR, 1.153 (95 % CI: 1.048-1.269), P = 0.004]. RCS revealed a non-linear rise in stroke risk with increasing CMI (P for nonlinearity = 0.005). No significant interactions were observed between CMI and subgroups (all P > 0.05).
Conclusion:
Elevated CMI correlates with higher stroke risk in middle-aged and older Chinese adults. Incorporating CMI into routine assessments could improve early stroke prevention strategies, addressing the increasing burden of cerebrovascular disease in aging populations.
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