NHANES 1999–2020 Dietary Data for Diabetes and Renal Impairment Analysis

9,764 diabetic participants from the National Health and Nutrition Examination Survey (NHANES) 1999–2020 were analyzed by Xincan Chen. The study investigates associations between dietary oxidative balance components and renal impairment, using machine learning models and in vitro experiments.

Use Cases

• Training machine learning models to predict renal impairment based on dietary factors.
• Analyzing the association between antioxidant nutrients like vitamin E and renal outcomes in diabetes.
• Investigating the role of pro-oxidant dietary components in diabetic kidney disease.
• Conducting feature importance analysis to identify key dietary contributors to health outcomes.

Strengths

• Data from a large, nationally representative survey (NHANES) with 9,764 participants.
• Analysis spans a 21-year time range (1999–2020).
• Includes results from in vitro experiments to support observational findings.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count for the underlying dataset is unknown, which may limit suitability assessment.
• The primary file is a 23.8 KB DOCX document, suggesting limited raw data scope.

Provenance

Source

National Health and Nutrition Examination Survey (NHANES)

Collection Method

Secondary analysis of survey data combined with in vitro experiments.

Time Range

1999–2020

Freshness

Last updated 2026-05-04 04:24:14; freshness should be verified.

Geography

United States (implied by NHANES)