five

Characteristics of study participants.

收藏
NIAID Data Ecosystem2026-05-01 收录
下载链接:
https://figshare.com/articles/dataset/Characteristics_of_study_participants_/22685793
下载链接
链接失效反馈
官方服务:
资源简介:
Background/objectives We aimed to determine whether serum uric acid (SUA) and body mass index (BMI) trajectories in childhood have longitudinal association with liver enzymes in adolescence. Methods We conducted a study using data from the Ewha Birth and Growth Cohort. Individual trajectories of SUA (n = 203) and BMI (n = 206) from 5, 7, and 9 years were defined by group-based trajectory modeling. Also, liver function enzymes were collected at 11 to 12 year of age (Aspartate Aminotransferase [AST], Alanine transaminase [ALT], and Gamma-glutamyl transferase [γ–GTP]) (n = 206). Using a generalized linear model, the effects of SUA trajectory and BMI trajectory on liver function enzymes were assessed. We also assessed the interaction effect of SUA and BMI trajectories on liver enzymes. Results For trajectory patterns, both SUA and BMI were classified into two distinct groups (High or Low). Both trajectory of SUA and BMI in childhood were positively associated with levels of liver enzymes at 11–12 years of age. The results showed that the combined effect of SUA and BMI trajectories on liver enzymes had a higher means in high-risk group (high SUA–high BMI trajectories group) than in low-risk group (low SUA-low BMI trajectories group) for ALT and γ–GTP, respectively. It remained significant association when adjusted for covariates. In addition, the interaction of BMI and SUA trajectories showed a significant synergistic effect. Conclusion Elevated childhood SUA and BMI trajectories are associated with increased liver enzymes in beginning of adolescent. This finding suggesting that early interventions in SUA and BMI may need for optimization of liver enzymes as potential marker for development of related disease in later life.
创建时间:
2023-04-24
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作