Dietary Clusters and Renal Function in a Taiwanese Cohort of 24,820 Adults

24,820 adults from the MJ Health Research Database in Taiwan were analyzed for dietary patterns and renal outcomes. Dietary intake was assessed via a food frequency questionnaire and clustered using the K-means++ algorithm into non-healthy, normal, and healthy groups. The study found an association between transitioning to a healthier dietary cluster and a lower risk of renal function decline.

Use Cases

• Analyzing associations between dietary patterns and renal function decline based on eGFR measurements.
• Evaluating the K-means++ algorithm for identifying stable dietary clusters in nutritional data.
• Studying the impact of specific food groups (e.g., sugar-sweetened beverages, vegetables) on long-term health outcomes.

Strengths

• Data from 24,820 participants provides a substantial cohort for analysis.
• Dietary patterns were derived using a validated food frequency questionnaire and the K-means++ algorithm.
• Clinical renal outcomes are defined by a specific eGFR decline threshold (>1 mL/min/1.73 m² per year).

Limitations

• Row count is unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• The dataset is small (423.3 KB), suggesting it may contain summary or supplementary material rather than raw participant data.

Provenance

Source

MJ Health Research Database in Taiwan.

Collection Method

Dietary intake assessed via a validated food frequency questionnaire; patterns derived with K-means++ clustering.

Freshness

Last updated 2026-06-02 06:35:12; freshness should be verified.

Geography

Taiwan