Estimated glucose disposal rate shows the broadest associations with cardiometabolic multimorbidity progression in early cardiovascular-kidney-metabolic stages: a longitudinal cohort study.
Wang Z, Liu Y, Ling Y, Sun Y • Frontiers in endocrinology • 2026
Among three insulin resistance indices, eGDR showed the most consistent associations with cardiometabolic multimorbidity progression across all disease-accumulation transitions and the largest single-marker gain in prediction, while TyG was complementary and AIP added little beyond eGDR and TyG.
Key Findings
Results
All three cardiometabolic indices were significantly associated with incident cardiometabolic multimorbidity (CMM), with eGDR showing the strongest association.
Primary-model HR per adverse standard deviation was 1.92 (95% CI, 1.77–2.09) for eGDR
HR was 1.69 (95% CI, 1.57–1.82) for TyG index
HR was 1.51 (95% CI, 1.39–1.64) for AIP
During a median follow-up of 9.0 years, 593 of 6,407 participants developed CMM
Study population included adults aged 45–79 years at CKM stages 0–3, free of CMM at baseline in 2011, followed through 2020
Results
After CKM-stage adjustment, eGDR remained significantly associated with all three disease-accumulation transitions, while TyG was associated only with the earliest transition and no AIP transition survived correction.
eGDR remained associated with all three disease-accumulation transitions at false-discovery-rate-adjusted P ≤ 0.009
TyG remained associated only with the earliest transition after CKM-stage adjustment
No AIP transition association survived false-discovery-rate correction
Multistate models were used to assess disease transitions
Restricted cubic-spline analyses were used to assess dose-response patterns
Results
eGDR yielded the largest single-marker gain in 9-year discrimination for CMM prediction among the three indices.
eGDR addition yielded ΔC-index of 0.041 (95% CI, 0.027–0.055)
Adding TyG to eGDR further increased C-index by 0.012 (95% CI, 0.005–0.020)
Adding AIP to eGDR plus TyG changed the C-index by only 0.001 (95% CI, −0.003 to 0.005), indicating negligible added value
Prediction was evaluated using five repetitions of stratified fivefold out-of-fold validation over a 9-year horizon
Calibration slopes ranged from 0.910 to 0.945
Results
TyG index was complementary to eGDR in CMM prediction but AIP added little incremental predictive value beyond eGDR and TyG combined.
Adding TyG to a model containing eGDR increased the C-index by 0.012 (95% CI, 0.005–0.020), a statistically meaningful gain
Adding AIP to the model containing both eGDR and TyG produced a C-index change of 0.001 (95% CI, −0.003 to 0.005), with the confidence interval crossing zero
These results indicate AIP does not provide meaningful discrimination beyond the combination of eGDR and TyG
Interval-aware and competing-risk analyses were consistent with primary findings
Methods
The study used a longitudinal cohort design in Chinese middle-aged and older adults across early CKM stages to compare three insulin resistance-related indices for CMM prediction.
6,407 China Health and Retirement Longitudinal Study (CHARLS) participants were included, aged 45–79 years
Participants were at CKM stages 0–3 and free of CMM (coexistence of at least two of diabetes, heart disease, and stroke) at baseline in 2011
Follow-up extended through 2020, with a median follow-up of 9.0 years
Cox proportional hazards models estimated HRs per standard deviation in the adverse direction (lower eGDR or higher TyG or AIP)
The authors note that independent external validation and clinical-utility assessment are needed before use in early risk stratification
What This Means
This research suggests that among three blood-based markers used to assess metabolic and cardiovascular risk, the estimated glucose disposal rate (eGDR) — a measure of how well the body responds to insulin — was the most useful for predicting whether middle-aged and older Chinese adults would develop cardiometabolic multimorbidity (CMM), defined as having at least two of diabetes, heart disease, or stroke at the same time. Over a nine-year follow-up period, 593 out of 6,407 adults developed CMM, and people with worse eGDR scores were nearly twice as likely to develop CMM compared to those with better scores. The other two markers — the triglyceride-glucose (TyG) index and the atherogenic index of plasma (AIP), both measures of fat and glucose metabolism — were also associated with CMM, but less strongly than eGDR.
When the researchers looked specifically at how people transitioned through stages of disease accumulation (going from having no conditions, to one, to two or more), eGDR was the only marker associated with all three types of transitions, while TyG was only linked to the earliest transition and AIP did not survive statistical correction for any transition. In terms of improving risk prediction beyond standard clinical information, adding eGDR to prediction models provided the largest improvement, and adding TyG on top of eGDR offered additional but smaller benefit. Adding AIP to a model that already included both eGDR and TyG provided essentially no additional predictive value.
This research suggests that eGDR may be a particularly informative and broadly applicable marker for identifying people at early cardiovascular-kidney-metabolic disease stages who are at risk of developing multiple cardiometabolic diseases. The TyG index appears to add complementary information to eGDR, but AIP offers little beyond these two markers. The authors caution that the findings come from a single Chinese cohort and that independent external validation and assessments of clinical usefulness are needed before these markers are used in routine early risk stratification.
Wang Z, Liu Y, Ling Y, Sun Y. (2026). Estimated glucose disposal rate shows the broadest associations with cardiometabolic multimorbidity progression in early cardiovascular-kidney-metabolic stages: a longitudinal cohort study.. Frontiers in endocrinology. https://doi.org/10.3389/fendo.2026.1948249