Maternal Uric Acid Levels and Risk of Gestational Diabetes Mellitus: A Systematic Review and Dose-response Meta-analysis of Cohort Studies Including 105,380 Participants

Overview

Journal J Diabetes Investig

Specialty Endocrinology

Date 2023 May 3

PMID 37132415

Authors

Ali Nikparast

Jamal Rahmani

Reza Bagheri

Saba Mohammadpour

Mehdi Shadnoosh

Alexei Wong

Matin Ghanavati

Affiliations

Soon will be listed here.

Abstract

Aims/introduction: Although the association between uric acid levels and adverse pregnancy outcomes has been investigated, the effects of higher uric acid levels on the risk of gestational diabetes mellitus (GDM) have yet to be established. Therefore, this systematic review and meta-analysis aimed to investigate the relationship between uric acid levels during pregnancy and the risk of GDM.

Materials And Methods: PubMed/Medline, Scopus and Web of Science databases were searched up to April 2022 for relevant observational studies. A random effects model was used to estimate pooled odds ratios (OR) and 95% confidence intervals (95% CI). To assess the heterogeneity of included studies, the I index was used.

Results: Among the initial 262 studies that were recognized from the databases search, 23 studies including 105,380 participants were eligible. Pooled analysis showed that higher uric acid levels significantly affected the risk of GDM (OR 2.58, 95% CI 1.89-3.52, I = 90.8%, P < 0.001). Subgroup analyses based on the gestational week showed that higher uric acid levels before the 20th week of gestation were significantly associated with the risk of GDM (OR 3.26, 95% CI 2.26-4.71, I = 89.3%, P < 0.001). Based on the meta-regression analysis, uric acid levels and odds of GDM were significantly correlated with the participants' age, and it was more significant in younger pregnant women.

Conclusions: This study showed a positive association between uric acid levels and the risk of GDM. Also, our results indicate that measuring uric acid levels before 20 weeks of gestation can potentially predict GDM, especially in younger women.

Citing Articles

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