Burden trajectories of stroke attributable to lipid-glucose dysfunction and biomarker validation: evidence from the global burden of disease (GBD) 2023 and the China health and retirement longitudinal study (CHARLS).

Abstract

Background: Metabolic dysfunction is an important contributor to stroke burden and may also help identify individuals at higher future risk of stroke. However, the population-level burden attributable to major metabolic risks and the individual-level predictive value of lipid-glucose metabolic biomarkers have not been well characterized within a complementary analytical framework. This study assessed temporal trends in stroke burden attributable to high FPG and high LDL-C in China and compared the prognostic performance of lipid-glucose metabolic biomarkers for incident stroke.

Methods: GBD 2023 estimates were used to evaluate stroke burden attributable to high FPG and high LDL-C in China from 1990 to 2023. Individual-level analyses were conducted in CHARLS (2011-2020) as the discovery cohort and HRS (2016-2022) as an external-validation cohort. Network and correlation analyses were used to describe interrelationships among predictors. Cox proportional hazards models were applied to assess associations between biomarkers and incident stroke, with component-aware covariate adjustment and FDR correction. Machine-learning models with SHAP interpretation were used to evaluate predictor contribution. The incremental predictive value of eGDR was further assessed by adding it to conventional clinical risk models, with evaluation of discrimination, calibration, and decision-curve performance.

Results: From 1990 to 2023, age-standardized mortality and DALY rates for stroke attributable to high FPG and high LDL-C declined in China, whereas the absolute burden remained substantial. In 2023, high FPG accounted for 216.80 thousand stroke deaths and 4,378.51 thousand DALYs, while high LDL-C accounted for 233.09 thousand deaths and 5,642.72 thousand DALYs. In CHARLS, eGDR showed a consistent inverse association with stroke risk and ranked as the leading predictor in SHAP analyses. Similar patterns were observed in HRS. Adding eGDR to conventional clinical risk models modestly improved discrimination and reclassification in both cohorts, with AUC improvements of 0.017-0.025 in CHARLS and 0.009-0.013 in HRS.

Conclusion: Age-standardized stroke burden attributable to high FPG and high LDL-C in China has declined, but the absolute burden remains substantial. eGDR showed consistent associations with incident stroke and modest incremental predictive value across CHARLS and HRS, supporting its potential relevance for future stroke risk-stratification research.