Changes in remnant cholesterol and the incidence of diabetes: Results from two large prospective cohort studies.

Objective: This study seeks to analyse the effect of the change and accumulation of residual cholesterol (RC) on the risk of diabetes.

Methods: The analysis included 5124 participants from the China Health and Retirement Longitudinal Study (CHARLS) and 2704 participants from the English Longitudinal Study of Ageing (ELSA), all of whom underwent two repeated RC measurements. Changes in the RC were assessed through K-means clustering analysis, and the cumulative RC was determined using the formula: by (RC_first + RC_second)/2 × (time interval between first and second assessments). We employed Cox proportional hazards regression models to analyse the effect of the changes and accumulation of RC on the development of diabetes.

Results: Individuals with consistently elevated RC levels (class 4) demonstrated a 1.98-fold increase in diabetes risk 95% confidence interval (CI: 1.38-2.84) in the CHARLS study and a 2.73-fold increase (95% CI: 1.69-4.38) in the ELSA study, compared with those with consistently low RC levels (class 1). Similarly, the risk of diabetes increased by 1.62 (95% CI: 1.21-2.18) times in CHARLS and 2.98 (95% CI: 1.81-4.88) folds in ELSA for participants with highest levels of cumulative RC relative to those with lowest levels of cumulative RC. Elevated cumulative RC remains a substantial risk factor for diabetes, irrespective of the cumulative LDL-C level.

Conclusions: Long-term exposure to high RC levels links to an elevated risk of diabetes. Therefore, maintaining optimal RC levels and continuously monitoring them may contribute to reducing the incidence of diabetes.