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Association Between Vitamin D and Uric Acid in Adults: A Systematic Review and Meta-Analysis.

Ronny IsnuwardanaSanjeev BijukchheKunlawat ThadaniponAtiporn IngsathitAmmarin Thakkinstian
Published in: Hormone and metabolic research = Hormon- und Stoffwechselforschung = Hormones et metabolisme (2020)
Association between vitamin D and uric acid is complex and might be bidirectional. Our study aimed to determine the bidirectional association between vitamin D and uric acid in adults. Using MEDLINE via PubMed and Scopus, we systematically searched for observational or interventional studies in adults, which assessed the association between serum vitamin D and serum uric acid, extracted the data, and conducted analysis by direct and network meta-analysis. The present review included 32 studies, of which 21 had vitamin D as outcome and 11 had uric acid as outcome. Meta-analysis showed a significant pooled beta coefficient of serum uric acid level on serum 25(OH)D level from 3 studies of 0.512 (95% confidence interval: 0.199, 0.825) and a significant pooled odds ratio between vitamin D deficiency and hyperuricemia of 1.496 (1.141, 1.963). The pooled mean difference of serum 25(OH)D between groups with hyperuricemia and normouricemia was non-significant at 0.138 (-0.430, 0.707) ng/ml, and the pooled mean difference of serum uric acid between categories of 25(OH)D were also non-significant at 0.072 (-0.153, 0.298) mg/dl between deficiency and normal, 0.038 (-0.216, 0.292) mg/dl between insufficiency and normal, and 0.034 (-0.216, 0.283) mg/dl between deficiency and insufficiency. In conclusion, increasing serum uric acid might be associated with increasing 25(OH)D level, while vitamin D deficiency is associated with hyperuricemia. These reverse relationships should be further evaluated in a longitudinal study.
Keyphrases
  • uric acid
  • metabolic syndrome
  • systematic review
  • case control
  • randomized controlled trial
  • clinical trial
  • magnetic resonance
  • phase iii
  • electronic health record
  • cross sectional
  • deep learning
  • replacement therapy