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中国南方超重和肥胖儿童及青少年尿酸代谢及其与糖脂代谢关系的横断面研究
Authors Tang B, Li Y, Lin J, Zhu Y, Chen D, Mou Y, Zhu S
Received 25 March 2025
Accepted for publication 28 July 2025
Published 9 August 2025 Volume 2025:18 Pages 2797—2806
DOI https://doi.org/10.2147/DMSO.S527026
Checked for plagiarism Yes
Review by Single anonymous peer review
Peer reviewer comments 2
Editor who approved publication: Dr Pablo Corral
Benyu Tang,* Yinya Li,* Juan Lin,* Yuxing Zhu, Danchun Chen, Yikun Mou, Shunye Zhu
Children’s Medical Center, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, Guangdong, 510630, People’s Republic of China
*These authors contributed equally to this work
Correspondence: Shunye Zhu, Children’s Medical Center, The Third Affiliated Hospital of Sun Yat-Sen University, 600 Tianhe Road, Tianhe District, Guangzhou, Guangdong, 510630, People’s Republic of China, Email zhushuny@mail.sysu.edu.cn Yikun Mou, Children’s Medical Center, The Third Affiliated Hospital of Sun Yat-Sen University, 600 Tianhe Road, Tianhe District, Guangzhou, Guangdong, 510630, People’s Republic of China, Email mouyikun@mail.sysu.edu.cn
Background: Overweight and obesity in children and adolescents have emerged as significant public health issues in China. This study aims to analyze the characteristics of serum uric acid (SUA) metabolism in overweight and obese children and adolescents in South China, exploring its associations with metabolic parameters.
Methods: A single-center retrospective study was conducted, involving children and adolescents aged 3 to 18 years diagnosed with overweight and obesity. Spearman correlation coefficients were calculated to evaluate relationships between SUA and other metabolic parameters. Multivariate linear regression analyses were conducted to adjust for confounders. Comparisons were made between participants with hyperuricemia and those with normal SUA levels, and logistic regression analyses were conducted to adjust for confounders. Hierarchical clustering was performed to explore the relationships among the parameters. A dendrogram was generated to visualize the cluster structure.
Results: Among 172 participants (96 males, 76 females), the mean age was 10.88± 2.70 years. The prevalence of hyperuricemia was 36.30%, with 38.46% in males and 33.82% in females. Every 1 kg/m² increase in body mass index was associated with a 7.156 μmol/L increase in SUA and an 8.9% increase in hyperuricemia risk. Significant correlations were observed between SUA levels and insulin resistance (HOMA-IR), fasting insulin, and high-density lipoprotein cholesterol. Hierarchical clustering analysis revealed two distinct clusters. One cluster includes SUA along with insulin resistance and lipid metabolism parameters, while the other comprises obesity metrics, urinary microalbumin, and blood glucose.
Conclusion: The findings show a high prevalence of hyperuricemia in overweight and obese children and adolescents, linked to insulin resistance and dyslipidemia. These results highlight the need for early screening and targeted interventions to improve metabolic health outcomes in this vulnerable population.
Keywords: pediatric obesity, uric acid, hyperuricemia, blood glucose, lipid metabolism, cluster analysis