Serum Vitamin D and Metabolic Syndrome Association in 29,214 Health Screening Participants

A cross-sectional study of 29,214 adults undergoing routine health examinations between January 2024 and November 2025. The dataset, authored by Jia He and shared on figshare, investigates the association between serum 25-hydroxyvitamin D levels and metabolic syndrome, with 6,002 participants (20.5%) diagnosed with MetS. The analysis includes dose-response modeling and sensitivity checks.

Use Cases

• Analyze the dose-response relationship between serum vitamin D levels and metabolic syndrome risk based on the restricted cubic spline analysis described.
• Investigate potential confounding effects on the vitamin D-MetS association using the described adjustment for hepatic and renal function indicators.
• Assess the robustness of epidemiological findings to unmeasured confounding using the E-value estimation method mentioned in the description.
• Model the non-linear association between a continuous biomarker and a binary health outcome based on the described quartile-based odds ratio analysis.

Strengths

• Large sample size of 29,214 participants from a health screening population.
• Specific, quantified finding: a 36% lower likelihood of MetS in the highest vitamin D quartile (OR=0.64, 95% CI: 0.57–0.71).
• Study design includes multiple analytical methods: multivariable logistic regression, restricted cubic splines, and sensitivity analyses.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment for specific modeling tasks.
• The cross-sectional nature, noted in the description, prevents causal inference.

Provenance

Source

Jia He via figshare.

Collection Method

Cross-sectional study of adults undergoing routine health examinations at a tertiary hospital.

Time Range

January 2024 to November 2025.

Freshness

Last updated 2026-04-30 14:15:21; freshness should be verified.

Geography

Likely China, based on the reference to Chinese expert consensus criteria, but not explicitly stated.