Diabetes, Obesity & Metabolism · Mar 2, 2026

The 1-Hour Plasma Glucose for Early Risk Stratification in Young, Obese Chinese Adults: Implications for Clinical Management

By Yuan M, Zhang Z, Chen Y et al.

AIMS: To evaluate the impact of applying the International Diabetes Federation (IDF) 1-hour plasma glucose (1h-PG) criteria on diagnosing dysglycaemia in young Chinese adults with obesity, and to validate the metabolic basis and diagnostic performance of these criteria in this high-risk population. METHODS: This Cross-Sectional Study Included 2484 Obese Individuals (Aged 18-40 Years, BMI ≥ 28 kg/m²). Participants underwent a 75-g oral glucose tolerance test (OGTT). Glycaemic status was classified using both traditional American Diabetes Association (ADA) criteria (fasting and 2-hour PG) and the IDF criteria (1h-PG cutoffs: 8.6 mmol/L for intermediate hyperglycaemia, 11.6 mmol/L for diabetes). Insulin sensitivity, secretion and β-cell function indices were calculated. Reclassification patterns were assessed, and the diagnostic accuracy of the 1h-PG cutoffs was evaluated using receiver operating characteristic (ROC) curve analysis against the ADA criteria. RESULTS: Applying IDF criteria doubled the prevalence of diabetes (from 12.0% to 22.7%) and significantly increased total dysglycaemia. This newly identified dysglycaemic population exhibited an intermediate metabolic phenotype with worsening insulin resistance and impaired early-phase β-cell function. ROC analysis demonstrated excellent diagnostic accuracy for the IDF diabetes cutoff (11.6 mmol/L; AUC 0.927), which matched the population-optimal cutoff. The cutoff for intermediate hyperglycaemia (8.6 mmol/L) showed high sensitivity (86.8%) for detecting ADA-defined prediabetes. CONCLUSIONS: The IDF 1h-PG criteria uncover a substantial, previously unrecognised burden of dysglycaemia in young Chinese adults with obesity, supported by clear metabolic defects and strong diagnostic performance. These findings support the use of 1h-PG as a practical tool for earlier risk stratification in this vulnerable population.

doi.org/10.1111/dom.70620PubMed 41766524Biomarkers

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