Diabetes, Metabolic Syndrome and Obesity (Mar 2022)

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

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

Journal volume & issue
Vol. Volume 15
pp. 921 – 931

Abstract

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Yanwu Nie,1,* Chenchen Wang,2,* Lei Yang,3 Zhen Yang,4 Yahong Sun,4 Maozai Tian,5,6 Yuhua Ma,7,8 Yuxia Zhang,9 Yimu Yuan,10 Liping Zhang6 1State Key Laboratory of Pathogenesis, Prevention and Treatment of High Incidence Diseases in Central Asia, School of Public Health, Xinjiang Medical University, Urumqi, 830017, People’s Republic of China; 2Center for Disease Control and prevention of Xinjiang Uygur Autonomous Region, Urumqi, 830017, People’s Republic of China; 3School of Nursing, Xinjiang Medical University, Urumqi, 830017, People’s Republic of China; 4School of Public Health, Xinjiang Medical University, Urumqi, 830017, People’s Republic of China; 5Center for Applied Statistics, School of Statistics, Renmin University of China, Beijing, 100872, People’s Republic of China; 6College of Medical Engineering and Technology, Xinjiang Medical University, Urumqi, 830017, People’s Republic of China; 7Department of Oncology, Shanghai East Hospital, Tongji University School of Medicine, Shanghai, 200120, People’s Republic of China; 8Department of Pathology, Karamay Central Hospital of XinJiang Karamay, Karamay, Xinjiang Uygur Autonomous Region, 834000, People’s Republic of China; 9Department of Clinical Nutrition, Urumqi Maternal and Child Health Institute, Urumqi, 830001, People’s Republic of China; 10Department of General Practice Medicine, Xinjiang Corps Hospital, Urumqi, People’s Republic of China*These authors contributed equally to this workCorrespondence: Liping Zhang, Email [email protected]: 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

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