Cardiovascular Risk Prediction Data for Overweight Chinese Adults

920 overweight or obese Chinese adults aged 40–80 years underwent health examinations at the First Affiliated Hospital of Xinjiang Medical University in 2019. The dataset likely contains baseline anthropometric indices and laboratory parameters, with participants followed through October 2024 to assess incident cardiovascular disease. Logistic regression and ROC analysis were used to evaluate the predictive value of the A Body Shape Index and Triglyceride-Glucose Index.

Use Cases

• Predicting cardiovascular disease risk based on combined ABSI and TyG index scores.
• Analyzing nonlinear relationships between insulin resistance markers and CVD outcomes.
• Comparing the predictive accuracy of different anthropometric indices like WC, BRI, and ABSI.
• Building logistic regression models for incident CVD using clinical and laboratory parameters.

Strengths

• Dataset includes 920 participants, providing a substantial cohort size.
• Follow-up period spans from January 2019 to October 2024, offering longitudinal data.
• Analysis includes multiple validated indices (ABSI, TyG, WC, BRI, TG) for comparison.
• Results show specific predictive performance metrics, such as AUC values of 0.679 for the combined model.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• Data may reflect geographic bias inherent to a single hospital in Xinjiang.

Provenance

Source

First Affiliated Hospital of Xinjiang Medical University

Collection Method

Retrospective cohort study using routine health examination data.

Time Range

Baseline data from January 2019 to October 2019, follow-up through October 2024.

Freshness

Last updated 2026-04-29 05:57:01; freshness should be verified.

Geography

China, specifically participants from Xinjiang.