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Association of frailty-risk indicators with cardiovascular diseases: evidence from the CHARLS
Fangfang Zhuo1,2, Zhao' Xing Cao2,3, Zhipeng Pu1,2
1Guizhou Medical University, Guiyang, Guizhou, 550004, China.
Insights
Frailty risk factors, including handgrip strength and cystatin C, are associated with cardiovascular diseases (CVDs). Incorporating these indicators can improve CVD risk assessment and prevention strategies.
Area of Science:
- Gerontology
- Cardiology
- Public Health
Background:
- Cardiovascular diseases (CVDs) represent a significant global health burden, with China experiencing escalating healthcare costs.
- Frailty, a state of reduced physiological reserve, is linked to aging and increased health risks.
- Existing frailty assessments may not be fully applicable using available data, necessitating the use of "frailty risk factors".
Purpose of the Study:
- To investigate the association between specific frailty risk factors and the prevalence of cardiovascular diseases (CVDs) in a Chinese population.
- To evaluate the predictive performance of machine learning models for CVD risk stratification using these factors.
- To identify key frailty-related indicators that contribute to CVD risk.
Main Methods:
- Analysis of data from the 2015 China Health and Retirement Longitudinal Study (CHARLS) involving 10,657 participants.
- Utilized LASSO regression for variable selection, followed by logistic regression and machine learning models (LR, XGBoost, LightGBM, SVM, RF, DT).
- Model performance assessed through discrimination, calibration, decision curve analysis, and SHAP interpretability.
Main Results:
- The XGBoost model demonstrated superior performance in predicting CVDs.
- Key predictors of increased CVD risk included age, HbA1c, uric acid (UA), and cystatin C (Cys C).
- Higher handgrip strength (HGS)/weight ratio and lower blood pressure were associated with reduced CVD risk.
Conclusions:
- Frailty risk factors, particularly HGS/weight ratio and Cys C, offer valuable insights for CVD risk stratification beyond traditional markers.
- Simple physical performance assessments and frailty risk evaluations can enhance current CVD prevention strategies.
- Integrating these measures into clinical practice may improve early detection and management of cardiovascular disease.
Abstract:
Cardiovascular diseases (CVDs) impose a heavy global disease burden, and China faces increasing healthcare costs and socioeconomic losses. Frailty is an age-related clinical state characterized by reduced physiological reserve and multisystem dysfunction. Because a complete Fried frailty phenotype could not be reconstructed from the available CHARLS variables, this study used "frailty risk factors" to refer to available physical performance and biomarker indicators related to frailty or high frailty risk, including handgrip strength (HGS)-derived variables and cystatin C (Cys C). This study explored the association between these indicators and CVDs.Methods Data from the 2015 China Health and Retirement Longitudinal Study (CHARLS) were analyzed. Participants were grouped by prevalent CVDs, defined as self-reported physician-diagnosed hypertension, heart disease, or stroke. LASSO regression followed by simple and multiple logistic regression was used to screen variables. The dataset was randomly split 6:2:2 into training, testing, and validation sets to develop six models (LR, XGBoost, LightGBM, SVM, RF, and DT), and model performance was evaluated by discrimination, calibration, decision curve analysis, and SHAP interpretability analyses.Results A total of 10,657 participants were included (76% female), of whom 2,650 had CVDs (84% female). The XGBoost model showed the best overall performance. SHAP analysis identified age, HbA1c, UA, and Cys C as variables increasing the predicted risk of CVDs, whereas higher left HGS/weight ratio and lower blood pressure values were associated with lower predicted risk.Conclusion These findings suggest that frailty risk factors, especially HGS/weight ratio and Cys C, may provide additional information for CVD risk stratification beyond conventional factors. The results support incorporating simple physical performance assessment and frailty-risk evaluation into CVD prevention strategies.
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