ArticleFrontiers in public health2023
The relative and interactive effects of urinary multiple metals exposure on hyperuricemia among urban elderly in China.
Article in Frontiers in public health, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed, 9 citations in OpenAlex.
- Associations between multiple essential trace metal concentrations and risk of hyperuricemia: insights from a central Chinese population.Biometals : an international journal on the role of metal ions in biology, biochemistry, and medicine · 2026Article
- Selenium predominance in heavy metal mixtures is associated with hyperuricemia in Chinese adults: the role of insulin resistance.Frontiers in public health · 2026Article
- Estimation of Hair Toxic and Essential Trace Element and Mineral Profiles of Patients with Chronic Gout.Biological trace element research · 2025Article
- The Correlation between Metal Mixed Exposure and Lung Function in Different Ages of the Population.Metabolites · 2024Article
- Association between oxidative balance score and serum uric acid and hyperuricemia: a population-based study from the NHANES (2011-2018).Frontiers in endocrinology · 2024Article
- Associations between blood essential metal mixture and serum uric acid: a cross-sectional study.Frontiers in public health · 2023Article
- Urinary nicotine metabolites are associated with cognitive impairment among the elderly in southern China.Tobacco induced diseases · 2023Article
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Authors and funding
13 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objective: Independent and interactive effects of multiple metals levels in urine on the risk of hyperuricemia (HUA) in the elderly were investigated. Methods: A total of 6,508 individuals from the baseline population of the Shenzhen aging-related disorder cohort were included in this study. We detected urinary concentrations of 24 metals using inductively coupled plasma mass spectrometry, fitted unconditional logistic regression models, and the least absolute shrinkage and selection operator regression models for the selection of metals as well as unconditional stepwise logistic regression models and restricted cubic spline logistic regression models for assessing the associations of urinary metals and HUA risk, and finally applied generalized linear models to determine the interaction with urinary metals on the risk of HUA. Results: Unconditional stepwise logistic regression models showed the association between urinary vanadium, iron, nickel, zinc, or arsenic and HUA risk (all Conclusion: Urinary vanadium, iron, nickel, zinc, or arsenic levels were associated with HUA risk, and the additive interaction of low-iron (<78.56 μg/L) and high-zinc (≥385.39 μg/L) levels may lead to a higher risk of HUA.
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