已发表论文

新疆无机砷暴露与代谢综合征的倾向评分匹配关系分析

 

Authors Nie Y, Wang C, Yang L, Yang Z, Sun Y, Tian M , Ma Y, Zhang Y, Yuan Y, Zhang L

Received 19 November 2021

Accepted for publication 17 March 2022

Published 25 March 2022 Volume 2022:15 Pages 921—931

DOI https://doi.org/10.2147/DMSO.S349583

Checked for plagiarism Yes

Review by Single anonymous peer review

Peer reviewer comments 3

Editor who approved publication: Professor Ming-Hui Zou

Purpose: The role of inorganic arsenic (iAs) in the risk of metabolic syndrome (MetS) remains unclear. This investigation focused on the effect of iAs exposure on MetS and whether the results are consistent in different subgroups.
Patients and Methods: The present study was conducted on 629 men and 616 women aged 35– 70 years and living in Xinjiang Uygur Autonomous Region, China. The 1:1 propensity score matching (PSM) was adopted to regulate the confounding factors, and the multivariate logistic regression was performed to assess the relationship between urinary iAs and MetS.
Results: The median content of urinary iAs was examined as 2.20 μg/dL (interquartile range: 1.30– 3.20 μg/dL), and the MetS prevalence reached 23.69% (295 cases/950 participants). After the confounding factors were adjusted, the ORs (95% CIs) for MetS from the minimal to the maximum urinary iAs quartiles reached 1.171 (0.736,1.863), 1.568 (1.008, 2.440) and 2.011 (1.296, 3.120), respectively (referencing 1.00) (P for trend=0.001). After the PSM, the urinary iAs content still plays a potential prediction role in MetS (P for trend=0.011). In addition, as revealed from the subgroup analysis, the urinary iAs content was a predictor of MetS in the female patients, whereas it did not serve as a significant predictor of MetS in the male patients (P for interaction< 0.05).
Conclusion: The increased urinary iAs content was associated with the increased prevalence of MetS in Chinese population. More attention should be paid to female urinary iAs content to avoid the high prevalence of MetS.
Keywords: metabolic syndrome, urinary inorganic arsenic, propensity score matching, subgroup analysis