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<p>Estimated glucose disposal rate (eGDR), a surrogate marker of insulin resistance, has been associated with all-cause mortality, but most studies have treated eGDR as a static exposure based on a single baseline measurement. Using data from the China Health and Retirement Longitudinal Study (CHARLS), we examined the associations of short-term eGDR change patterns and cumulative eGDR with all-cause mortality in middle-aged and older Chinese adults. Short-term eGDR change-pattern classes between 2012 and 2015 were identified using K-means clustering based on two repeated measurements. Cox proportional hazards models were used to evaluate the associations of eGDR change-pattern classes and cumulative eGDR with all-cause mortality, and restricted cubic spline regression was applied to assess the potential nonlinear association of cumulative eGDR with mortality risk. Over 52,853.24 person-years of follow-up, 428 deaths occurred among 5,966 participants. Compared with Class 1, the adjusted hazard ratios (95% confidence intervals) for all-cause mortality were 1.25 (0.87–1.79) for Class 2, 1.68 (1.25–2.24) for Class 3, and 1.77 (1.40–2.24) for Class 4. Cumulative eGDR was inversely associated with all-cause mortality. These findings suggest that dynamic and cumulative assessment of eGDR may provide prognostic information beyond a single baseline measurement.</p>

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Longitudinal changes and cumulative exposure of estimated glucose disposal rate and all-cause mortality in middle-aged and older Chinese adults

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年6月16日

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  • Tengfei Long,
  • Xuejiao Hu,
  • Rui Zhang,
  • Zushan Zhang,
  • Zefang Zhang,
  • Xiaoting Chen

摘要

Estimated glucose disposal rate (eGDR), a surrogate marker of insulin resistance, has been associated with all-cause mortality, but most studies have treated eGDR as a static exposure based on a single baseline measurement. Using data from the China Health and Retirement Longitudinal Study (CHARLS), we examined the associations of short-term eGDR change patterns and cumulative eGDR with all-cause mortality in middle-aged and older Chinese adults. Short-term eGDR change-pattern classes between 2012 and 2015 were identified using K-means clustering based on two repeated measurements. Cox proportional hazards models were used to evaluate the associations of eGDR change-pattern classes and cumulative eGDR with all-cause mortality, and restricted cubic spline regression was applied to assess the potential nonlinear association of cumulative eGDR with mortality risk. Over 52,853.24 person-years of follow-up, 428 deaths occurred among 5,966 participants. Compared with Class 1, the adjusted hazard ratios (95% confidence intervals) for all-cause mortality were 1.25 (0.87–1.79) for Class 2, 1.68 (1.25–2.24) for Class 3, and 1.77 (1.40–2.24) for Class 4. Cumulative eGDR was inversely associated with all-cause mortality. These findings suggest that dynamic and cumulative assessment of eGDR may provide prognostic information beyond a single baseline measurement.