Comparison between compositional data analysis and principal component analysis for identifying dietary patterns associated with hyperuricemia
Background/objectivesDietary patterns play an important role in regulating serum uric acid (SUA) levels in the body. Recently, compositional data analysis (CoDA) has been proposed as an alternative technique in identifying dietary patterns. However, the relative advantages of CoDA, particularly in i...
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Frontiers Media S.A.
2025-07-01
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| Series: | Frontiers in Nutrition |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fnut.2025.1582674/full |
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| author | Junkang Zhao Junkang Zhao Yajie Zhao Jiannan Han Jiannan Han Yixuan Zhao Sumiao Liu Zhida Liu Liyun Zhang Yan Zhang |
| author_facet | Junkang Zhao Junkang Zhao Yajie Zhao Jiannan Han Jiannan Han Yixuan Zhao Sumiao Liu Zhida Liu Liyun Zhang Yan Zhang |
| author_sort | Junkang Zhao |
| collection | DOAJ |
| description | Background/objectivesDietary patterns play an important role in regulating serum uric acid (SUA) levels in the body. Recently, compositional data analysis (CoDA) has been proposed as an alternative technique in identifying dietary patterns. However, the relative advantages of CoDA, particularly in identifying dietary patterns associated with hyperuricemia have not been investigated. We evaluated and compared CoDA, including compositional principal component analysis (CPCA) and principal balances analysis (PBA), with the most commonly used principal component analysis (PCA) in determining dietary patterns associated with hyperuricemia.MethodsThe 3 day 24-h dietary recall method was used to estimate dietary data from 3,954 study participants of the China Health and Nutrition Survey (CHNS). Dietary patterns were constructed using PCA, CPCA and PBA. These methods were compared based on the performance to identify plausible patterns associated with hyperuricemia.ResultsPCA, CPCA and PBA all identified three dietary patterns, with a common “traditional southern Chinese” pattern high in rice and animal-based foods and low in wheat products and dairy. Only this pattern was positively associated with risk of hyperuricemia [PCA: OR (95%CI) = 1.29 (1.15–1.46); CPCA: OR (95%CI) = 1.25 (1.10–1.40); PBA: OR (95%CI) = 1.23 (1.09–1.38)].ConclusionAll three dietary patterns methods in our study identified that a “traditional southern Chinese” dietary pattern was associated with increased risk of hyperuricemia, suggesting a robust and consistent finding. |
| format | Article |
| id | doaj-art-e2702681f6ff4c2ba317abc77256597f |
| institution | Kabale University |
| issn | 2296-861X |
| language | English |
| publishDate | 2025-07-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Nutrition |
| spelling | doaj-art-e2702681f6ff4c2ba317abc77256597f2025-08-20T03:50:49ZengFrontiers Media S.A.Frontiers in Nutrition2296-861X2025-07-011210.3389/fnut.2025.15826741582674Comparison between compositional data analysis and principal component analysis for identifying dietary patterns associated with hyperuricemiaJunkang Zhao0Junkang Zhao1Yajie Zhao2Jiannan Han3Jiannan Han4Yixuan Zhao5Sumiao Liu6Zhida Liu7Liyun Zhang8Yan Zhang9Shanxi 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, ChinaShanxi Academy of Advanced Research and Innovation (SAARI), Taiyuan, ChinaLaboratory of International Agro-Informatics, Department of Global Agricultural Sciences, Graduate School of Agricultural and Life Sciences, The University of Tokyo, Tokyo, JapanThird Hospital of Shanxi Medical University, Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences, Taiyuan, ChinaSchool of Public Health, Shanxi Medical University, Taiyuan, ChinaSecond Clinical College, Shanxi University of Chinese Medicine, Jinzhong, ChinaShanxi 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, ChinaShanxi Academy of Advanced Research and Innovation (SAARI), Taiyuan, ChinaThird Hospital of Shanxi Medical University, Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences, Taiyuan, ChinaNational Institute for Nutrition and Health, Chinese Center for Disease Control and Prevention, Beijing, ChinaBackground/objectivesDietary patterns play an important role in regulating serum uric acid (SUA) levels in the body. Recently, compositional data analysis (CoDA) has been proposed as an alternative technique in identifying dietary patterns. However, the relative advantages of CoDA, particularly in identifying dietary patterns associated with hyperuricemia have not been investigated. We evaluated and compared CoDA, including compositional principal component analysis (CPCA) and principal balances analysis (PBA), with the most commonly used principal component analysis (PCA) in determining dietary patterns associated with hyperuricemia.MethodsThe 3 day 24-h dietary recall method was used to estimate dietary data from 3,954 study participants of the China Health and Nutrition Survey (CHNS). Dietary patterns were constructed using PCA, CPCA and PBA. These methods were compared based on the performance to identify plausible patterns associated with hyperuricemia.ResultsPCA, CPCA and PBA all identified three dietary patterns, with a common “traditional southern Chinese” pattern high in rice and animal-based foods and low in wheat products and dairy. Only this pattern was positively associated with risk of hyperuricemia [PCA: OR (95%CI) = 1.29 (1.15–1.46); CPCA: OR (95%CI) = 1.25 (1.10–1.40); PBA: OR (95%CI) = 1.23 (1.09–1.38)].ConclusionAll three dietary patterns methods in our study identified that a “traditional southern Chinese” dietary pattern was associated with increased risk of hyperuricemia, suggesting a robust and consistent finding.https://www.frontiersin.org/articles/10.3389/fnut.2025.1582674/fulldietary patternscompositional datahyperuricemiaprincipal component analysisChina health and nutrition survey |
| spellingShingle | Junkang Zhao Junkang Zhao Yajie Zhao Jiannan Han Jiannan Han Yixuan Zhao Sumiao Liu Zhida Liu Liyun Zhang Yan Zhang Comparison between compositional data analysis and principal component analysis for identifying dietary patterns associated with hyperuricemia Frontiers in Nutrition dietary patterns compositional data hyperuricemia principal component analysis China health and nutrition survey |
| title | Comparison between compositional data analysis and principal component analysis for identifying dietary patterns associated with hyperuricemia |
| title_full | Comparison between compositional data analysis and principal component analysis for identifying dietary patterns associated with hyperuricemia |
| title_fullStr | Comparison between compositional data analysis and principal component analysis for identifying dietary patterns associated with hyperuricemia |
| title_full_unstemmed | Comparison between compositional data analysis and principal component analysis for identifying dietary patterns associated with hyperuricemia |
| title_short | Comparison between compositional data analysis and principal component analysis for identifying dietary patterns associated with hyperuricemia |
| title_sort | comparison between compositional data analysis and principal component analysis for identifying dietary patterns associated with hyperuricemia |
| topic | dietary patterns compositional data hyperuricemia principal component analysis China health and nutrition survey |
| url | https://www.frontiersin.org/articles/10.3389/fnut.2025.1582674/full |
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