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Comparison between compositional data analysis and principal component analysis for identifying dietary patterns

Junkang Zhao^1,2, Yajie Zhao³, Jiannan Han^4,5

¹Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences, Third Hospital of Shanxi Medical University, Shanxi Province Clinical Research Center for Dermatologic and Immunologic Diseases (Rheumatic Diseases), Shanxi Province Clinical Theranostics Technology Innovation Center for Immunologic and Rheumatic Diseases, Taiyuan, China.

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|July 31, 2025

Summary

This summary is machine-generated.

A traditional southern Chinese diet, rich in rice and animal products, is linked to higher serum uric acid levels and increased hyperuricemia risk. This finding was consistent across multiple dietary pattern analysis methods.

Keywords:

China health and nutrition survey compositional data dietary patterns hyperuricemia principal component analysis

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Area of Science:

Nutrition Science
Public Health
Biostatistics

Background:

Dietary patterns significantly influence serum uric acid (SUA) levels.
Hyperuricemia risk is associated with specific dietary habits.
Compositional data analysis (CoDA) offers a novel approach to dietary pattern identification.

Purpose of the Study:

To compare the effectiveness of CoDA methods (CPCA, PBA) with traditional PCA in identifying dietary patterns linked to hyperuricemia.
To investigate the association between dietary patterns and hyperuricemia in a Chinese population.

Main Methods:

Utilized data from 3,954 participants in the China Health and Nutrition Survey (CHNS).
Employed a 3-day, 24-hour dietary recall method for data collection.
Applied Principal Component Analysis (PCA), Compositional Principal Component Analysis (CPCA), and Principal Balances Analysis (PBA) to determine dietary patterns.

Main Results:

All three methods identified a common dietary pattern, characterized as "traditional southern Chinese," high in rice and animal-based foods and low in wheat and dairy.
This specific dietary pattern was consistently associated with an increased risk of hyperuricemia across all analytical approaches (PCA, CPCA, PBA).

Conclusions:

The study confirms a robust association between the "traditional southern Chinese" dietary pattern and elevated hyperuricemia risk.
CoDA methods (CPCA, PBA) provide a valuable alternative for identifying dietary patterns related to metabolic health conditions like hyperuricemia.