Association Between Body Composition Phenotypes and Prediabetes Outcomes in Chinese Adults

A 2024 cross-sectional study of 3,905 Chinese adults undergoing health check-ups, authored by Ren Lin and published on figshare. It analyzes associations between body composition phenotypes—defined by relative muscle mass and the Chinese visceral adiposity index (CVAI)—and prediabetes outcomes like impaired fasting glucose and elevated HbA1c. The dataset compares the discriminatory performance of CVAI against BMI and waist-to-height ratio.

Use Cases

• Assessing the association between combined low muscle mass and visceral obesity with prediabetes risk based on logistic regression results.
• Comparing the discriminatory power of CVAI, BMI, and waist-to-height ratio for abnormal glycemia using receiver operating characteristic curves.
• Investigating the independent association of low relative muscle mass alone with prediabetes outcomes after adjusting for confounders.
• Modeling prediabetes risk based on body composition phenotypes categorized as normal, low muscle mass alone, visceral obesity alone, or combined.

Strengths

• Dataset includes 3,905 adult participants, providing a substantial sample size for analysis.
• Analysis adjusts for multiple confounders including age, sex, blood pressure, LDL-C, ALT, and eGFR across three statistical models.
• Results are specific, reporting odds ratios (2.42–2.84) and phenotype distribution percentages (e.g., 13.2% had combined phenotype).

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• Data is from a single health check-up center in 2024, which may limit generalizability.

Provenance

Source

figshare

Collection Method

Data obtained from adults attending a health check-up center.

Time Range

2024

Freshness

Last updated 2026-05-14 05:23:36; freshness should be verified.

Geography

China