Associations of cumulative exposure and dynamic trajectories of the combined estimated glucose disposal rate and frailty index with incident cardiometabolic multimorbidity comprising diabetes, heart disease, and stroke: a longitudinal analysis based on the China health and retirement longitudinal study (CHARLS)
5 affiliations
- 1Jiangxi Key Laboratory of Neurological Diseases, Department of Neurosurgery, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, Jiangxi China
- 2Department of Clinical Laboratory, The First Affiliated Hospital of Nanchang University, Nanchang University, Nanchang, Jiangxi China
- 3Department of Clinical Laboratory, The First Affiliated Hospital of Nanchang University, Nanchang, China
- 4Institute of Infection and Immunity, Jiangxi Medical College, Nanchang University, Nanchang, China
- 5Medical Center of Burn Plastic and Wound Repair, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, China
Abstract
Background: Cardiometabolic multimorbidity (CMM), encompassing the co-occurrence of major cardiometabolic conditions such as diabetes, heart disease, and stroke, is a growing clinical and public-health challenge associated with adverse functional outcomes and high long-term care needs. Insulin resistance and frailty are plausible, potentially interrelated determinants of CMM, including cerebrovascular complications, but their joint longitudinal contribution has not been fully characterized. We investigated whether estimated glucose disposal rate (eGDR), frailty index (FI), and FI-to-eGDR ratio (FI/eGDR), assessed as baseline values, time-weighted cumulative exposure, and two-wave repeated-exposure patterns, were associated with incident CMM.
Methods: This prospective cohort study included 5171 participants from the China Health and Retirement Longitudinal Study who were free of CMM at baseline. Baseline eGDR, FI, and FI/eGDR were evaluated as standardized continuous variables and tertiles. Time-weighted cumulative exposures were calculated from Wave 1 and Wave 3 values, and two-wave repeated-exposure patterns were identified using K-means clustering. Cox regression models with sequential covariate adjustment were used to estimate associations with incident CMM, with diabetes, heart disease, and stroke incorporated as components of the cardiometabolic disease burden within the outcome framework. Restricted cubic splines, exploratory subgroup analyses, conventional receiver operating characteristic and decision curve analyses, and sensitivity analyses were performed. A Wave 3 landmark cohort included 5052 participants who remained free of CMM through Wave 3.
Results: During follow-up, 441 participants developed CMM. In fully adjusted models, per-SD increases in baseline eGDR, FI, and FI/eGDR were associated with HRs of 0.57 (95% CI, 0.51–0.64), 1.29 (95% CI, 1.19–1.40), and 1.39 (95% CI, 1.29–1.48), respectively; corresponding HRs for cumulative measures were 0.52 (95% CI, 0.46–0.59), 1.51 (95% CI, 1.40–1.64), and 1.52 (95% CI, 1.43–1.60). Compared with T1, the fully adjusted HR for T3 of cumulative FI/eGDR was 6.52 (95% CI, 4.55–9.35). Compared with FI/eGDR repeated-exposure pattern class 1, HRs were 3.87 (95% CI, 3.03–4.93) for class 2 and 9.45 (95% CI, 6.95–12.86) for class 3. In the Wave 3 landmark cohort, FI/eGDR pattern class 2 and class 3 remained associated with higher risk (HR, 3.45 [95% CI, 2.62–4.54] and 6.38 [95% CI, 4.39–9.27], respectively). Spline analyses supported nonlinear associations. Cumulative FI/eGDR had the highest observed AUC among individual measures (0.742; 95% CI, 0.718–0.766), whereas the cumulative FI plus eGDR model had an AUC of 0.758 (95% CI, 0.735–0.781); in the landmark analysis, the corresponding AUCs were 0.731 (95% CI, 0.704–0.759) and 0.740 (95% CI, 0.714–0.767), respectively.
Conclusions: Lower eGDR, higher FI, and higher FI/eGDR were associated with incident CMM after multivariable adjustment. Cumulative and repeated-exposure pattern analyses provided complementary information beyond a single baseline measurement. Longitudinal integration of metabolic insulin-resistance and frailty measures may help characterize adults at increased risk of CMM, although the exploratory discrimination results require internal and external validation before any clinical application.
Supplementary information: The online version contains supplementary material available at https://doi.org/10.1186/s12933-026-03391-x.
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BibTeX
@article{lei2026associations,
title = {{Associations of cumulative exposure and dynamic trajectories of the combined estimated glucose disposal rate and frailty index with incident cardiometabolic multimorbidity comprising diabetes, heart disease, and stroke: a longitudinal analysis based on the China health and retirement longitudinal study (CHARLS)}},
author = {Yi Lei and Junming Li and Wenqiang Xin},
journal = {Cardiovascular Diabetology},
year = {2026},
month = oct,
doi = {10.1186/s12933-026-03391-x},
url = {https://doi.org/10.1186/s12933-026-03391-x},
note = {CC BY-NC-ND 4.0},
}
RIS
TY - JOUR
TI - Associations of cumulative exposure and dynamic trajectories of the combined estimated glucose disposal rate and frailty index with incident cardiometabolic multimorbidity comprising diabetes, heart disease, and stroke: a longitudinal analysis based on the China health and retirement longitudinal study (CHARLS)
AU - Yi Lei
AU - Junming Li
AU - Wenqiang Xin
PY - 2026
DA - 2026/10/01
JO - Cardiovascular Diabetology
DO - 10.1186/s12933-026-03391-x
UR - https://doi.org/10.1186/s12933-026-03391-x
AB - Background: Cardiometabolic multimorbidity (CMM), encompassing the co-occurrence of major cardiometabolic conditions such as diabetes, heart disease, and stroke, is a growing clinical and public-health challenge associated with adverse functional outcomes and high long-term care needs. Insulin resistance and frailty are plausible, potentially interrelated determinants of CMM, including cerebrovascular complications, but their joint longitudinal contribution has not been fully characterized. We investigated whether estimated glucose disposal rate (eGDR), frailty index (FI), and FI-to-eGDR ratio (FI/eGDR), assessed as baseline values, time-weighted cumulative exposure, and two-wave repeated-exposure patterns, were associated with incident CMM. Methods: This prospective cohort study included 5171 participants from the China Health and Retirement Longitudinal Study who were free of CMM at baseline. Baseline eGDR, FI, and FI/eGDR were evaluated as standardized continuous variables and tertiles. Time-weighted cumulative exposures were calculated from Wave 1 and Wave 3 values, and two-wave repeated-exposure patterns were identified using K-means clustering. Cox regression models with sequential covariate adjustment were used to estimate associations with incident CMM, with diabetes, heart disease, and stroke incorporated as components of the cardiometabolic disease burden within the outcome framework. Restricted cubic splines, exploratory subgroup analyses, conventional receiver operating characteristic and decision curve analyses, and sensitivity analyses were performed. A Wave 3 landmark cohort included 5052 participants who remained free of CMM through Wave 3. Results: During follow-up, 441 participants developed CMM. In fully adjusted models, per-SD increases in baseline eGDR, FI, and FI/eGDR were associated with HRs of 0.57 (95% CI, 0.51–0.64), 1.29 (95% CI, 1.19–1.40), and 1.39 (95% CI, 1.29–1.48), respectively; corresponding HRs for cumulative measures were 0.52 (95% CI, 0.46–0.59), 1.51 (95% CI, 1.40–1.64), and 1.52 (95% CI, 1.43–1.60). Compared with T1, the fully adjusted HR for T3 of cumulative FI/eGDR was 6.52 (95% CI, 4.55–9.35). Compared with FI/eGDR repeated-exposure pattern class 1, HRs were 3.87 (95% CI, 3.03–4.93) for class 2 and 9.45 (95% CI, 6.95–12.86) for class 3. In the Wave 3 landmark cohort, FI/eGDR pattern class 2 and class 3 remained associated with higher risk (HR, 3.45 [95% CI, 2.62–4.54] and 6.38 [95% CI, 4.39–9.27], respectively). Spline analyses supported nonlinear associations. Cumulative FI/eGDR had the highest observed AUC among individual measures (0.742; 95% CI, 0.718–0.766), whereas the cumulative FI plus eGDR model had an AUC of 0.758 (95% CI, 0.735–0.781); in the landmark analysis, the corresponding AUCs were 0.731 (95% CI, 0.704–0.759) and 0.740 (95% CI, 0.714–0.767), respectively. Conclusions: Lower eGDR, higher FI, and higher FI/eGDR were associated with incident CMM after multivariable adjustment. Cumulative and repeated-exposure pattern analyses provided complementary information beyond a single baseline measurement. Longitudinal integration of metabolic insulin-resistance and frailty measures may help characterize adults at increased risk of CMM, although the exploratory discrimination results require internal and external validation before any clinical application. Supplementary information: The online version contains supplementary material available at https://doi.org/10.1186/s12933-026-03391-x.
SN - 1475-2840
ER -