Evidence map›Paper›PMID 41913033›Full record

ArticleClinical rheumatology2026

Negative and nonlinear association between oxidative balance score and hyperuricemia: a cross-sectional analysis based on the NHANES database.

Hang Zhou, Chao Han, Liyuan Tan, Yanying Liu

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Article in Clinical rheumatology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

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4 authors.

Hang ZhouDepartment of Rheumatology, Beijing Friendship Hospital, Capital Medical University, No. 1 Courtyard, Luyuan South Street, Beijing, 100050, Tongzhou District, China.
Chao HanInterdisciplinary Research Center On Biology and Chemistry, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, Shanghai, China.
Liyuan TanSchool of Microelectronics Science and Technology, Sun Yat-Sen University, Zhuhai, China.
Yanying LiuDepartment of Rheumatology, Beijing Friendship Hospital, Capital Medical University, No. 1 Courtyard, Luyuan South Street, Beijing, 100050, Tongzhou District, China. liuyanying6850@126.com.ORCID http://orcid.org/0009-0004-6014-0635

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6 · The paper itself

Abstract

objectiveHyperuricemia (HUA) is a prevalent metabolic disorder linked to substantial morbidity. Oxidative stress is a key pathogenic mechanism, yet the cumulative effect of dietary and lifestyle pro- and anti-oxidants remains unclear. The Oxidative Balance Score (OBS) offers a comprehensive metric of oxidative potential. This study aimed to investigate the association between OBS and HUA in a large, nationally representative US adult population.

methodsThis cross-sectional study included 29,876 adults aged ≥ 20 years from the National Health and Nutrition Examination Survey (NHANES) 2007-2018. The OBS was constructed from 16 dietary and 4 lifestyle components. HUA was defined as serum uric acid ≥ 7.0 mg/dL for men and ≥ 6.0 mg/dL for women. Multivariable logistic regression models were used to estimate odds ratios (ORs) and 95% confidence intervals (CIs) for the association between OBS quartiles and HUA. Restricted cubic splines (RCS) were employed to model non-linear relationships. Subgroup analyses were conducted by gender, age, and estimated glomerular filtration rate (eGFR).

resultsThe overall prevalence of HUA was 20.2%. A significant inverse association was observed between OBS and HUA. After adjusting for multiple confounders, participants in the highest OBS quartile (Q4, most anti-oxidant profile) had a 42% lower odds of HUA compared to those in the lowest quartile (Q1) (OR: 0.58, 95% CI: 0.51-0.66, P-trend < 0.001). This association was more pronounced for lifestyle OBS (OR for Q4 vs. Q1: 0.35, 95% CI: 0.29-0.42) than for dietary OBS (OR for Q4 vs. Q1: 0.70, 95% CI: 0.61-0.81). RCS analysis revealed a significant nonlinear relationship (P-nonlinearity < 0.001), with the protective effect of OBS plateauing at higher scores. The inverse association was consistent across gender and age subgroups but appeared stronger in individuals with normal renal function (eGFR ≥ 90 mL/min/1.73m

conclusionA higher OBS, reflecting a lifestyle and diet rich in antioxidants, is independently and non-linearly associated with a lower prevalence of hyperuricemia. These findings highlight the importance of a holistic approach targeting overall oxidative balance, particularly through modifiable lifestyle factors, for the primary prevention of hyperuricemia. Key Points • A higher Oxidative Balance Score is linked to lower hyperuricemia prevalence. • Lifestyle factors show a stronger protective association than dietary factors. • The relationship is nonlinear, with benefits plateauing at higher scores.

Indexed as

HyperuricemiaOxidative StressAdultAgedAntioxidantsCross-Sectional StudiesDietFemaleGlomerular Filtration RateHumansLife StyleLogistic ModelsMaleMiddle AgedNutrition SurveysPrevalenceAntioxidantsUric AcidCross-sectional studyDietHyperuricemiaLifestyleNHANESOxidative Balance ScoreOxidative Stress

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.