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Zheng X, Wang Q, Xu X, Huang X, Chen J, Huo X. Associations of insulin sensitivity and immune inflammatory responses with child blood lead (Pb) and PM 2.5 exposure at an e-waste recycling area during the COVID-19 lockdown. ENVIRONMENTAL GEOCHEMISTRY AND HEALTH 2024; 46:296. [PMID: 38980420 DOI: 10.1007/s10653-024-02066-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/08/2024] [Accepted: 06/04/2024] [Indexed: 07/10/2024]
Abstract
Fine particular matter (PM2.5) and lead (Pb) exposure can induce insulin resistance, elevating the likelihood of diabetes onset. Nonetheless, the underlying mechanism remains ambiguous. Consequently, we assessed the association of PM2.5 and Pb exposure with insulin resistance and inflammation biomarkers in children. A total of 235 children aged 3-7 years in a kindergarten in e-waste recycling areas were enrolled before and during the Corona Virus Disease 2019 (COVID-19) lockdown. Daily PM2.5 data was collected and used to calculate the individual PM2.5 daily exposure dose (DED-PM2.5). Concentrations of whole blood Pb, fasting blood glucose, serum insulin, and high mobility group box 1 (HMGB1) in serum were measured. Compared with that before COVID-19, the COVID-19 lockdown group had lower DED-PM2.5 and blood Pb, higher serum HMGB1, and lower blood glucose and homeostasis model assessment of insulin resistance (HOMA-IR) index. Decreased DED-PM2.5 and blood Pb levels were linked to decreased levels of fasting blood glucose and increased serum HMGB1 in all children. Increased serum HMGB1 levels were linked to reduced levels of blood glucose and HOMA-IR. Due to the implementation of COVID-19 prevention and control measures, e-waste dismantling activities and exposure levels of PM2.5 and Pb declined, which probably reduced the association of PM2.5 and Pb on insulin sensitivity and diabetes risk, but a high level of risk of chronic low-grade inflammation remained. Our findings add new evidence for the associations among PM2.5 and Pb exposure, systemic inflammation and insulin resistance, which could be a possible explanation for diabetes related to environmental exposure.
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Affiliation(s)
- Xiangbin Zheng
- Laboratory of Environmental Medicine and Developmental Toxicology, Guangdong Key Laboratory of Environmental Pollution and Health, School of Environment, Jinan University, 855 East Xingye Avenue, Guangzhou, 511443, Guangdong, China
- Center for Reproductive Medicine, Clinical Research Center, Shantou Central Hospital, Shantou, 515041, Guangdong, China
| | - Qihua Wang
- Laboratory of Environmental Medicine and Developmental Toxicology, Guangdong Key Laboratory of Environmental Pollution and Health, School of Environment, Jinan University, 855 East Xingye Avenue, Guangzhou, 511443, Guangdong, China
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, 9713 GZ, Groningen, The Netherlands
| | - Xijin Xu
- Laboratory of Environmental Medicine and Developmental Toxicology, Shantou University Medical College, Shantou, 515041, Guangdong, China
| | - Xiaofan Huang
- Center for Reproductive Medicine, Clinical Research Center, Shantou Central Hospital, Shantou, 515041, Guangdong, China
| | - Jiaxue Chen
- Laboratory of Environmental Medicine and Developmental Toxicology, Shantou University Medical College, Shantou, 515041, Guangdong, China
| | - Xia Huo
- Laboratory of Environmental Medicine and Developmental Toxicology, Guangdong Key Laboratory of Environmental Pollution and Health, School of Environment, Jinan University, 855 East Xingye Avenue, Guangzhou, 511443, Guangdong, China.
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Zhang J, Li J, Su Y, Chen C, Chen L, Huang X, Wang F, Huang Y, Wang G. Interannual evolution of the chemical composition, sources and processes of PM 2.5 in Chengdu, China: Insights from observations in four winters. J Environ Sci (China) 2024; 138:32-45. [PMID: 38135399 DOI: 10.1016/j.jes.2023.02.055] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2022] [Revised: 02/25/2023] [Accepted: 02/27/2023] [Indexed: 12/24/2023]
Abstract
The air quality in China has improved significantly in the last decade and, correspondingly, the characteristics of PM2.5 have also changed. We studied the interannual variation of PM2.5 in Chengdu, one of the most heavily polluted megacities in southwest China, during the most polluted season (winter). Our results show that the mass concentrations of PM2.5 decreased significantly year-by-year, from 195.8 ± 91.0 µg/m3 in winter 2016 to 96.1 ± 39.3 µg/m3 in winter 2020. The mass concentrations of organic matter (OM), SO42-, NH4+ and NO3- decreased by 49.6%, 57.1%, 49.7% and 28.7%, respectively. The differential reduction in the concentrations of chemical components increased the contributions from secondary organic carbon and NO3- and there was a larger contribution from mobile sources. The contribution of OM and NO3- not only increased with increasing levels of pollution, but also increased year-by-year at the same level of pollution. Four sources of PM2.5 were identified: combustion sources, vehicular emissions, dust and secondary aerosols. Secondary aerosols made the highest contribution and increased year-by-year, from 40.6% in winter 2016 to 46.3% in winter 2020. By contrast, the contribution from combustion sources decreased from 14.4% to 8.7%. Our results show the effectiveness of earlier pollution reduction policies and emphasizes that priority should be given to key pollutants (e.g., OM and NO3-) and sources (secondary aerosols and vehicular emissions) in future policies for the reduction of pollution in Chengdu during the winter months.
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Affiliation(s)
- Junke Zhang
- Faculty of Geosciences and Environmental Engineering, Southwest Jiaotong University, Chengdu 611756, China
| | - Jiaqi Li
- Faculty of Geosciences and Environmental Engineering, Southwest Jiaotong University, Chengdu 611756, China
| | - Yunfei Su
- Faculty of Geosciences and Environmental Engineering, Southwest Jiaotong University, Chengdu 611756, China
| | - Chunying Chen
- Faculty of Geosciences and Environmental Engineering, Southwest Jiaotong University, Chengdu 611756, China
| | - Luyao Chen
- Faculty of Geosciences and Environmental Engineering, Southwest Jiaotong University, Chengdu 611756, China
| | - Xiaojuan Huang
- Department of Environmental Science & Engineering, Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention (LAP3), Fudan University, Shanghai 200438, China.
| | - Fangzheng Wang
- Faculty of Geosciences and Environmental Engineering, Southwest Jiaotong University, Chengdu 611756, China
| | - Yawen Huang
- Faculty of Geosciences and Environmental Engineering, Southwest Jiaotong University, Chengdu 611756, China
| | - Gehui Wang
- Key Lab of Geographic Information Science of the Ministry of Education, School of Geographic Sciences, East China Normal University, Shanghai 200241, China
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