Diabetes research and clinical practice · 2026
Association between the insulin resistance indices and incident type 2 diabetes across different body mass index states: a cohort study and external validation from two East Asian populations.
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Huang Zhenhua, Gao Yuting, Liu Lixiang, Li Maolin, Yuan Qinghua
Аннотация
BACKGROUND: Insulin resistance (IR) indices like the TyG index are predictors of type 2 diabetes (T2DM), but their comparative performance across BMI categories in East Asians is unclear.
METHODS: This retrospective cohort study enrolled 114,293 Chinese adults without diabetes. Four IR indices (TyG, TyG-BMI, TG/HDL-C, METS-IR) were calculated. Their associations with incident T2DM were assessed using Cox models, restricted cubic splines, and machine learning, stratified by BMI. Findings were replicated in 15,453 Japanese adults from the NAGALA cohort.
RESULTS: Over a mean 3.10-year follow-up, 2,435 participants developed T2DM. All indices were independently associated with diabetes risk, but the association strength declined with higher BMI. For TyG, the fully adjusted hazard ratios were 4.60, 3.10, and 2.62 in the non-overweight, overweight, and obese groups, respectively-a "reverse gradient" observed for all indices. Non-linear relationships with clear inflection points were identified. Predictive performance was highest in the non-overweight group (e.g., TyG AUC 76.74%). External replication confirmed these findings.
CONCLUSIONS: IR indices, particularly TyG and TyG-BMI, are powerful predictors of T2DM across all BMI categories. Their predictive ability is most pronounced in non-overweight individuals, challenging the obesity-centric diabetes screening paradigm and underscoring the need for early metabolic risk assessment in lean adults.
METHODS: This retrospective cohort study enrolled 114,293 Chinese adults without diabetes. Four IR indices (TyG, TyG-BMI, TG/HDL-C, METS-IR) were calculated. Their associations with incident T2DM were assessed using Cox models, restricted cubic splines, and machine learning, stratified by BMI. Findings were replicated in 15,453 Japanese adults from the NAGALA cohort.
RESULTS: Over a mean 3.10-year follow-up, 2,435 participants developed T2DM. All indices were independently associated with diabetes risk, but the association strength declined with higher BMI. For TyG, the fully adjusted hazard ratios were 4.60, 3.10, and 2.62 in the non-overweight, overweight, and obese groups, respectively-a "reverse gradient" observed for all indices. Non-linear relationships with clear inflection points were identified. Predictive performance was highest in the non-overweight group (e.g., TyG AUC 76.74%). External replication confirmed these findings.
CONCLUSIONS: IR indices, particularly TyG and TyG-BMI, are powerful predictors of T2DM across all BMI categories. Their predictive ability is most pronounced in non-overweight individuals, challenging the obesity-centric diabetes screening paradigm and underscoring the need for early metabolic risk assessment in lean adults.