Literature DB >> 34717108

Dietary patterns and risk for hyperuricemia in the general population: Results from the TCLSIH cohort study.

Tingjing Zhang1, Sabina Rayamajhi1, Ge Meng2, Qing Zhang3, Li Liu3, Hongmei Wu1, Yeqing Gu4, Yawen Wang1, Shunming Zhang1, Xuena Wang1, Juanjuan Zhang1, Huiping Li1, Amrish Thapa1, Shaomei Sun3, Xing Wang3, Ming Zhou3, Qiyu Jia3, Kun Song3, Kaijun Niu5.   

Abstract

OBJECTIVE: Prospective cohort studies linking dietary patterns and hyperuricemia (HUA) are limited, especially in Asian populations. The aim of this study was to prospectively investigate the association between various dietary patterns and risk for HUA in a general adult population.
METHOD: We used data from the TCLSIH (Tianjin Chronic Low-grade Systemic Inflammation and Health) cohort study of 20 766 men and women who were free from HUA, cancer, and cardiovascular disease at baseline. Dietary patterns at baseline were identified with factor analysis based on responses to a validated 81-item food frequency questionnaire. HUA was defined as serum uric acid levels >420 μmol/L in men and >350 μmol/L in women. Cox proportional hazards regression models were used to examine the association of dietary patterns with incident HUA.
RESULTS: In all, 4389 first incident cases of HUA occurred during 73 822 person-years of follow-up (median follow-up of 4.2 y). Three main dietary patterns were extracted. They were the vegetable, sweet food, and animal food patterns. After adjusting for demographic characteristics, lifestyle factors, other dietary pattern scores, and inflammatory markers, comparing the highest with the lowest quartiles of dietary pattern scores, the multivariable hazard ratios (95% confidence interval) of HUA were 0.79 (0.72-0.87; Ptrend < 0.0001) for the vegetable pattern, 1.22 (1.12-1.33; Ptrend < 0.0001) for the sweet food pattern, and 1.24 (1.13-1.37; Ptrend < 0.0001) for the animal food pattern.
CONCLUSIONS: Dietary patterns rich in animal or sweet foods were positively associated with a higher risk for HUA, whereas the vegetable pattern was negatively associated.
Copyright © 2021 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Dietary patterns; Hyperuricemia; Prospective study; Uric acid

Mesh:

Substances:

Year:  2021        PMID: 34717108     DOI: 10.1016/j.nut.2021.111501

Source DB:  PubMed          Journal:  Nutrition        ISSN: 0899-9007            Impact factor:   4.008


  4 in total

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Journal:  Nutrients       Date:  2022-02-17       Impact factor: 5.717

2.  Docosahexaenoic Acid as the Bidirectional Biomarker of Dietary and Metabolic Risk Patterns in Chinese Children: A Comparison with Plasma and Erythrocyte.

Authors:  Zhi Huang; Ping Guo; Ying Wang; Ziming Li; Xiaochen Yin; Ming Chen; Yong Liu; Yuming Hu; Bo Chen
Journal:  Nutrients       Date:  2022-07-28       Impact factor: 6.706

Review 3.  The Good, the Bad and the New about Uric Acid in Cancer.

Authors:  Simone Allegrini; Mercedes Garcia-Gil; Rossana Pesi; Marcella Camici; Maria Grazia Tozzi
Journal:  Cancers (Basel)       Date:  2022-10-10       Impact factor: 6.575

4.  The Prevalence of Hyperuricemia and Its Correlates among Adults in China: Results from CNHS 2015-2017.

Authors:  Wei Piao; Liyun Zhao; Yuxiang Yang; Hongyun Fang; Lahong Ju; Shuya Cai; Dongmei Yu
Journal:  Nutrients       Date:  2022-10-02       Impact factor: 6.706

  4 in total

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