Relationship Analysis of Inorganic Arsenic Exposure and Metabolic Syndrome Based on Propensity Score Matching in Xinjiang, China

• Published in: Diabetes, metabolic syndrome and obesity metabolic syndrome and obesity, 2022-01, Vol.15, p.921-931
• Main Authors: Nie, Yanwu, Wang, Chenchen, Yang, Lei, Yang, Zhen, Sun, Yahong, Tian, Maozai, Ma, Yuhua, Zhang, Yuxia, Yuan, Yimu, Zhang, Liping
• Format: Article
• Language: English
• Subjects: Analysis; Arsenic; metabolic syndrome; Original Research; propensity score matching; subgroup analysis; Type 2 diabetes; urinary inorganic arsenic
• ISSN: 1178-7007; 1178-7007
• DOI: 10.2147/DMSO.S349583

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. 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. 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