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Wu Y, Song J, Li Y, Jin X, Liang Y, Qin W, Yi W, Pan R, Yan S, Sun X, Mei L, Song S, Cheng J, Su H. Association between exposure to a mixture of metals, parabens, and phthalates and fractional exhaled nitric oxide: A population-based study in US adults. ENVIRONMENTAL RESEARCH 2022; 214:113962. [PMID: 35940230 DOI: 10.1016/j.envres.2022.113962] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/20/2022] [Revised: 07/19/2022] [Accepted: 07/20/2022] [Indexed: 06/15/2023]
Abstract
The effects of environmental endocrine-disrupting chemicals (EDCs) (e.g., phthalates) on fractional exhaled nitric oxide (FeNO) in children have received much attention. However, few studies evaluated this relationship in adults, and the previous studies have considered only a unitary exposure or a set of similar exposures instead of mixed exposures, which contain complicated interactions. We aimed to evaluate simultaneously the relationship between three types of EDCs (six phthalate metabolites and two parabens in urine, two heavy metals in blood) and FeNO (as a continuous variable) in adults. Data of adults aged ≥20 years from the National Health and Nutrition Examination Survey (NHANES, 2007-2012) were collected and analyzed. The generalized linear (GLM) regression model was used to explore the association of chemicals with FeNO. The combined effect of 10 chemicals on the overall association with FeNO was evaluated by the weighted quantile sum regression (WQS) model. In addition, The Bayesian kernel machine regression (BKMR) model was explored to investigate the interaction and joint effects of multiple chemicals with FeNO. Of the 3296 study participants ultimately included, among the GLMs, we found that mercury (Hg) (β = 0.84, 95%CI:0.32-1.36, FDR = 0.01) and methyl paraben (MPB) (β = 0.47, 95%CI:0.16-0.78, FDR = 0.015) were positively correlated with FeNO. In the WQS model, the combined effect of chemicals almost had a significantly positive association with FeNO and the top three contributors to the WQS index were Hg (40.2%), MECPP (22.1%), and MPB (19.3%). BKMR analysis showed that there may be interactions between MPB and Hg, Mono (carboxyoctyl) phthalate (MCOP) and Hg and the overall effect of the mixture showed a positive correlation with FeNO. In conclusion, our study strengthens the credibility of the view that EDCs can affect respiratory health. In the future, we should be particularly careful with products containing Hg, MECPP, MPB, and MEHP for the prevention of respiratory diseases.
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Affiliation(s)
- Yudong Wu
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, 230032, China; Anhui Province Key Laboratory of Major Autoimmune Diseases, Hefei, Anhui, 230032, China
| | - Jian Song
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, 230032, China; Anhui Province Key Laboratory of Major Autoimmune Diseases, Hefei, Anhui, 230032, China
| | - Yuxuan Li
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, 230032, China; Anhui Province Key Laboratory of Major Autoimmune Diseases, Hefei, Anhui, 230032, China
| | - Xiaoyu Jin
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, 230032, China; Anhui Province Key Laboratory of Major Autoimmune Diseases, Hefei, Anhui, 230032, China
| | - Yunfeng Liang
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, 230032, China; Anhui Province Key Laboratory of Major Autoimmune Diseases, Hefei, Anhui, 230032, China
| | - Wei Qin
- Lu'an Municipal Center for Disease Control and Prevention, Lu'an, Anhui, China
| | - Weizhuo Yi
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, 230032, China; Anhui Province Key Laboratory of Major Autoimmune Diseases, Hefei, Anhui, 230032, China
| | - Rubing Pan
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, 230032, China; Anhui Province Key Laboratory of Major Autoimmune Diseases, Hefei, Anhui, 230032, China
| | - Shuangshuang Yan
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, 230032, China; Anhui Province Key Laboratory of Major Autoimmune Diseases, Hefei, Anhui, 230032, China
| | - Xiaoni Sun
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, 230032, China; Anhui Province Key Laboratory of Major Autoimmune Diseases, Hefei, Anhui, 230032, China
| | - Lu Mei
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, 230032, China; Anhui Province Key Laboratory of Major Autoimmune Diseases, Hefei, Anhui, 230032, China
| | - Shasha Song
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, 230032, China; Anhui Province Key Laboratory of Major Autoimmune Diseases, Hefei, Anhui, 230032, China
| | - Jian Cheng
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, 230032, China; Anhui Province Key Laboratory of Major Autoimmune Diseases, Hefei, Anhui, 230032, China
| | - Hong Su
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, 230032, China; Anhui Province Key Laboratory of Major Autoimmune Diseases, Hefei, Anhui, 230032, China.
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