TyG-WHtR Predicts Incident Type 2 Diabetes in NAFLD: A 12-Year Prospective Cohort Study

Nan’nan Chen's research dataset contains results from a 12-year prospective cohort study of 2,370 Japanese patients with nonalcoholic fatty liver disease (NAFLD). It compares the predictive ability of twelve metabolic composite indices for the onset of type 2 diabetes mellitus (T2DM). The dataset was last updated on 2026-05-01.

Use Cases

• Comparing the predictive performance of twelve metabolic composite indices for T2DM based on the study results
• Validating the TyG-WHtR index as a practical tool for T2DM risk stratification in NAFLD patients
• Conducting subgroup analyses on the association between metabolic indices and incident T2DM
• Applying multivariate Cox proportional hazards models to clinical cohort data

Strengths

• Dataset is based on a cohort of 2,370 NAFLD patients, providing a substantial sample size.
• The study spans a 12-year prospective follow-up period, offering longitudinal insights.
• Results include specific hazard ratios and AUC values for twelve different metabolic indices, such as TyG-WC (HR: 1.80) and TyG-WHtR (AUC = 0.680).

Limitations

• The dataset is a 21.6 KB DOCX file, which suggests it contains summary results rather than raw patient-level data.
• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment for certain analyses.

Provenance

Source

figshare, author Nan’nan Chen

Collection Method

Secondary analysis of a prospective Japanese cohort study.

Time Range

12-year prospective study period.

Freshness

Last updated 2026-05-01 04:16:23; freshness should be verified.

Geography

Japanese cohort.