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Chen Y, Wang Y, Chen Q, Chung MK, Liu Y, Lan M, Wei Y, Lin L, Cai L. Gestational and Postpartum Exposure to PM 2.5 Components and Glucose Metabolism in Chinese Women: A Prospective Cohort Study. Environ Sci Technol 2024. [PMID: 38728584 DOI: 10.1021/acs.est.4c03087] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/12/2024]
Abstract
Pregnant women are physiologically prone to glucose intolerance, while the puerperium represents a critical phase for recovery. However, how air pollution disrupts glucose homeostasis during the gestational and early postpartum periods remains unclear. This prospective cohort study conducted an oral glucose tolerance test and measured the insulin levels of 834 pregnant women in Guangzhou, with a follow-up for 443 puerperae at 6-8 weeks postpartum. Residential PM2.5 and five chemical components were estimated by an established spatiotemporal model. The adjusted linear model showed that an IQR increase in gestational PM2.5 exposure was associated with an increase of 0.17 mmol/L (95% CI: 0.06, 0.28) in fasting plasma glucose (FPG) and 0.24 (95% CI: 0.05, 0.42) in the insulin resistance index. Postpartum PM2.5 exposure was linked to a 0.17 mmol/L (95% CI: 0.05, 0.28) elevation in FPG per IQR, with a strengthened association found in women with gestational diabetes (Pinteraction = 0.003). In the quantile-based g-computation model, NO3- consistently contributed to the combined effect of PM2.5 components on gestational and postpartum FPG. This study was the first to suggest that PM2.5 components were associated with exacerbated gestational insulin resistance and elevated postpartum FPG. Targeted interventions reducing the emissions of toxic PM2.5 components are essential to improving maternal glucose metabolism.
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Affiliation(s)
- Yujing Chen
- Department of Maternal and Child Health, School of Public Health, Sun Yat-sen University, Guangzhou 510080, Guangdong, China
- The Jockey Club School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong, 999077, China
| | - Yuxuan Wang
- Global Health Research Center, Duke Kunshan University, Kunshan 215316, Jiangsu, China
| | - Qian Chen
- Department of Neonatology, Guangzhou Key Laboratory of Neonatal Intestinal Diseases, The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou 510080, Guangdong, China
| | - Ming Kei Chung
- The Jockey Club School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong, 999077, China
- Institute of Environment, Energy and Sustainability, The Chinese University of Hong Kong, Hong Kong 999077, China
- Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong 999077, China
| | - Yu Liu
- Department of Maternal and Child Health, School of Public Health, Sun Yat-sen University, Guangzhou 510080, Guangdong, China
| | - Minyan Lan
- Department of Maternal and Child Health, School of Public Health, Sun Yat-sen University, Guangzhou 510080, Guangdong, China
| | - Yanhong Wei
- Guangdong Provincial Key Laboratory of Food, Nutrition and Health, Department of Toxicology, School of Public Health, Sun Yat-sen University, Guangzhou 510080 Guangdong, China
| | - Lizi Lin
- Joint International Research Laboratory of Environment and Health, Ministry of Education, Guangdong Provincial Engineering Technology Research Center of Environmental Pollution and Health Risk Assessment, Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou 510080, Guangdong, China
| | - Li Cai
- Department of Maternal and Child Health, School of Public Health, Sun Yat-sen University, Guangzhou 510080, Guangdong, China
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Yang C, Wang W, Wang F, Wang Y, Zhang F, Liang Z, Liang C, Wang J, Ma L, Li P, Li S, Zhang L. Ambient PM 2.5 components and prevalence of chronic kidney disease: a nationwide cross-sectional survey in China. Environ Geochem Health 2024; 46:70. [PMID: 38353840 DOI: 10.1007/s10653-024-01867-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/25/2023] [Accepted: 01/10/2024] [Indexed: 02/16/2024]
Abstract
OBJECTIVES Chronic kidney disease (CKD) is a global public health concern, and accumulating evidence has indicated that air pollution increases the odds of CKD. However, a limited number of studies have examined the long-term effects of ambient fine particulate matter (PM2.5) components on the risk of CKD among general population; thus, major knowledge gaps remain. METHODS Using data from a nationwide representative cross-sectional survey in China and a validated PM2.5 composition dataset, we established generalized linear models to quantify the association between five major components of PM2.5 and CKD prevalence. RESULTS There were significant associations between long-term exposure to three PM2.5 components [including black carbon (BC), sulfate (SO42-), organic matter (OM)] and increased odds of CKD prevalence. Along with an interquartile range (IQR) increment in BC (3.3 μg/m3), SO42- (9.7 μg/m3), and OM (16.2 μg/m3) at a 4-year moving average, the odds ratios (ORs) for CKD prevalence were 1.28 (95% CI 1.07, 1.54), 1.23 (95% CI 1.03, 1.45), and 1.23 (95% CI 1.02, 1.47), respectively. We did not detect any significant association of the other two PM2.5 components [nitrate (NO3-) or ammonium (NH4+)] with CKD prevalence. Stratified analyses revealed no differences (P ≥ 0.05) in the effect estimates of subgroups based on administrative region, sex, age, and other demographic characteristics. For instance, along with an IQR increment in BC at a 4-year moving average, the ORs of CKD prevalence among males and females were 1.30 (95% CI 0.98, 1.73) and 1.29 (95% CI 1.01, 1.65), respectively. The odds of CKD were generally higher with increasing PM2.5 composition concentration. CONCLUSIONS Our study demonstrated that long-term exposure to specific PM2.5 components including BC, SO42-, and OM increased CKD risk in the general population. This study could provide new insights into source-directed PM2.5 control and CKD prevention.
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Affiliation(s)
- Chao Yang
- Renal Division, Department of Medicine, Peking University First Hospital, Peking University Institute of Nephrology, Beijing, 100034, China
- Research Units of Diagnosis and Treatment of Immune-Mediated Kidney Diseases, Chinese Academy of Medical Sciences, Beijing, 100034, China
- Advanced Institute of Information Technology, Peking University, Hangzhou, 311215, China
| | - Wanzhou Wang
- Department of Occupational and Environmental Health Sciences, School of Public Health, Peking University, Beijing, 100191, China
- National Institute of Health Data Science at Peking University, Beijing, 100191, China
| | - Fulin Wang
- National Institute of Health Data Science at Peking University, Beijing, 100191, China
- Institute of Medical Technology, Peking University Health Science Center, Beijing, 100191, China
| | - Yueyao Wang
- Key Laboratory for Earth Surface Processes of the Ministry of Education, College of Urban and Environmental Sciences, Peking University, Beijing, 100871, China
| | - Feifei Zhang
- National Institute of Health Data Science at Peking University, Beijing, 100191, China
- Institute of Medical Technology, Peking University Health Science Center, Beijing, 100191, China
| | - Ze Liang
- Key Laboratory for Earth Surface Processes of the Ministry of Education, College of Urban and Environmental Sciences, Peking University, Beijing, 100871, China
| | - Chenyu Liang
- Key Laboratory for Earth Surface Processes of the Ministry of Education, College of Urban and Environmental Sciences, Peking University, Beijing, 100871, China
| | - Jinwei Wang
- Renal Division, Department of Medicine, Peking University First Hospital, Peking University Institute of Nephrology, Beijing, 100034, China
- Research Units of Diagnosis and Treatment of Immune-Mediated Kidney Diseases, Chinese Academy of Medical Sciences, Beijing, 100034, China
| | - Lin Ma
- Key Laboratory for Earth Surface Processes of the Ministry of Education, College of Urban and Environmental Sciences, Peking University, Beijing, 100871, China
| | - Pengfei Li
- Advanced Institute of Information Technology, Peking University, Hangzhou, 311215, China
| | - Shuangcheng Li
- Key Laboratory for Earth Surface Processes of the Ministry of Education, College of Urban and Environmental Sciences, Peking University, Beijing, 100871, China
| | - Luxia Zhang
- Renal Division, Department of Medicine, Peking University First Hospital, Peking University Institute of Nephrology, Beijing, 100034, China.
- Advanced Institute of Information Technology, Peking University, Hangzhou, 311215, China.
- National Institute of Health Data Science at Peking University, Beijing, 100191, China.
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Wang M, He Y, Zhao Y, Zhang L, Liu J, Zheng S, Bai Y. Exposure to PM 2.5 and its five constituents is associated with the incidence of type 2 diabetes mellitus: a prospective cohort study in northwest China. Environ Geochem Health 2024; 46:34. [PMID: 38227152 DOI: 10.1007/s10653-023-01794-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/16/2023] [Accepted: 10/31/2023] [Indexed: 01/17/2024]
Abstract
Studies have demonstrated that fine particulate matter (PM2.5) is an underlying risk factor for type 2 diabetes mellitus (T2DM), but evidence exploring the relationship between PM2.5 chemical components and T2DM was extremely limited, to investigate the effects of long-term exposure to PM2.5 and its five constituents (sulfate [SO42-], nitrate [NO3-], ammonium [NH4+]), organic matter [OM] and black carbon [BC]) on incidence of T2DM. Based on the "Jinchang Cohort" platform, a total of 19,884 participants were selected for analysis. Daily average concentrations of pollutants were gained from Tracking Air Pollution in China (TAP). Cox proportional hazards regression models were utilized to estimate the hazard ratios (HR) and 95% confidence interval (CI) in single-pollutant models, restricted cubic splines functions were used to examine the dose-response relationships, and quantile g-computation (QgC) was applied to evaluate the combined effect of PM2.5 compositions on T2DM. Stratification analysis was also considered. A total of 791 developed new cases of T2DM were observed during a follow-up period of 45254.16 person-years. The concentrations of PM2.5, NO3-, NH4+, OM and BC were significantly associated with incidence of T2DM (P-trend < 0.05), with the HRs in the highest quartiles of 2.16 (95% CI 1.79, 2.62), 1.43 (95% CI 1.16, 1.75), 1.75 (95% CI 1.45, 2.11), 1.31 (95% CI 1.08, 1.59) and 1.79 (95% CI 1.46, 2.21), respectively. Findings of QgC model showed a noticeably positive joint effect of one quartile increase in PM2.5 constituents on increased T2DM morbidity (HR 1.27, 95% CI 1.09, 1.49), and BC (32.7%) contributed the most to the overall effect. The drinkers, workers and subjects with hypertension, obesity, higher physical activity, and lower education and income were generally more susceptible to PM2.5 components hazards. Long-term exposure to PM2.5 and its components (i.e., NO3-, NH4+, OM, BC) was positively correlated with T2DM incidence. Moreover, BC may be the most responsible for the association between PM2.5 constituents and T2DM. In the future, more epidemiological and experimental studies are needed to identify the link and potential biological mechanisms.
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Affiliation(s)
- Minzhen Wang
- Department of Epidemiology and Statistics, School of Public Health, Lanzhou University, No. 199 Donggang West Road, Lanzhou, 730000, China
| | - Yingqian He
- Department of Epidemiology and Statistics, School of Public Health, Lanzhou University, No. 199 Donggang West Road, Lanzhou, 730000, China
| | - Yanan Zhao
- Department of Epidemiology and Statistics, School of Public Health, Lanzhou University, No. 199 Donggang West Road, Lanzhou, 730000, China
| | - Lulu Zhang
- Department of Epidemiology and Statistics, School of Public Health, Lanzhou University, No. 199 Donggang West Road, Lanzhou, 730000, China
| | - Jing Liu
- Department of Epidemiology and Statistics, School of Public Health, Lanzhou University, No. 199 Donggang West Road, Lanzhou, 730000, China
| | - Shan Zheng
- Department of Epidemiology and Statistics, School of Public Health, Lanzhou University, No. 199 Donggang West Road, Lanzhou, 730000, China.
| | - Yana Bai
- Department of Epidemiology and Statistics, School of Public Health, Lanzhou University, No. 199 Donggang West Road, Lanzhou, 730000, China
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Gong Z, Yue H, Li Z, Bai S, Cheng Z, He J, Wang H, Li G, Sang N. Association between maternal exposure to air pollution and gestational diabetes mellitus in Taiyuan, North China. Sci Total Environ 2023; 875:162515. [PMID: 36868286 DOI: 10.1016/j.scitotenv.2023.162515] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/02/2022] [Revised: 02/22/2023] [Accepted: 02/24/2023] [Indexed: 06/18/2023]
Abstract
BACKGROUND The effect of air pollution on human health has been a major concern, especially the association between air pollution and gestational diabetes mellitus (GDM). METHODS In this study, we conducted a retrospective cohort study in Taiyuan, a typical energy production base in China. This study included 28,977 pairs of mothers and infants between January 2018 and December 2020. To screen for GDM, oral glucose tolerance test (OGTT) was performed in pregnant women at 24-28 weeks of gestation. Logistic regression was used to assess the trimester-specific association between 5 common air pollutants (PM10, PM2.5, NO2, SO2, and O3) and GDM, and the weekly-based association was also assessed using distributed lag non-linear models (DLNMs). Odds ratios (ORs) with 95 % confidence intervals (CIs) were calculated for the association between GDM and each air pollutant. RESULTS The overall incidence of GDM was 3.29 %. PM2.5 was positively associated with GDM over the second trimester (OR [95 % CI], 1.105 [1.021, 1.196]). O3 was positively associated with GDM in the preconception period (OR [95 % CI], 1.125 [1.024, 1.236]), the first trimester (OR [95 % CI], 1.088 [1.019, 1.161]) and the 1st + 2nd trimester (OR [95 % CI], 1.643 [1.387, 1.945]). For the weekly-based association, PM2.5 was positively associated with GDM at 19-24 weeks of gestation, with the strongest association at week 24 (OR [95 % CI], 1.044 [1.021, 1.067]). PM10 was positively associated with GDM at 18-24 weeks of gestation, with the strongest association at week 24 (OR [95 % CI], 1.016 [1.003, 1.030]). O3 was positively associated with GDM during the 3rd week before conception to the 8th gestational week, with the strongest association at week 3 of gestation (OR [95 % CI], 1.054 [1.032, 1.077]). CONCLUSION The findings are important for the development of effective air quality policies and the optimization of preventive strategies for preconception and prenatal care.
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Affiliation(s)
- Zhihua Gong
- College of Environment and Resource, Research Center of Environment and Health, Shanxi University, Taiyuan, Shanxi 030006, PR China; Department of Clinical Laboratory, Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences, Tongji Shanxi Hospital, Third Hospital of Shanxi Medical University, Taiyuan, Shanxi 030032, PR China; Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, PR China
| | - Huifeng Yue
- College of Environment and Resource, Research Center of Environment and Health, Shanxi University, Taiyuan, Shanxi 030006, PR China
| | - Zhihong Li
- Taiyuan Taihang Hospital, Taiyuan, Shanxi 030006, PR China
| | - Shuqing Bai
- Taiyuan Taihang Hospital, Taiyuan, Shanxi 030006, PR China
| | - Zhonghui Cheng
- Xiaodian District Maternal and Child Health Care Hospital, Taiyuan 030032, PR China
| | - Jing He
- Department of Obstetrics and Gynecology, Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences, Tongji Shanxi Hospital, Third Hospital of Shanxi Medical University, Taiyuan, Shanxi 030032, PR China; Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, PR China
| | - Huimin Wang
- Fengtai Mental Health Center, Beijing 100071, PR China
| | - Guangke Li
- College of Environment and Resource, Research Center of Environment and Health, Shanxi University, Taiyuan, Shanxi 030006, PR China.
| | - Nan Sang
- College of Environment and Resource, Research Center of Environment and Health, Shanxi University, Taiyuan, Shanxi 030006, PR China
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Kang N, Wu R, Liao W, Zhang C, Liu X, Mao Z, Huo W, Hou J, Zhang K, Tian H, Lin H, Wang C. Association of long-term exposure to PM 2.5 constituents with glucose metabolism in Chinese rural population. Sci Total Environ 2023; 859:160364. [PMID: 36427733 DOI: 10.1016/j.scitotenv.2022.160364] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/12/2022] [Revised: 10/26/2022] [Accepted: 11/17/2022] [Indexed: 06/16/2023]
Abstract
BACKGROUND Evidence on the associations of fine particulate matter (PM2.5) constituents and glucose metabolism is limited in resource-limited areas. This study aimed to explore the associations of PM2.5 constituents with glucose metabolism in rural areas, and to further specify the most responsible constituent. METHODS A total of 38,442 adults were recruited from the Henan Rural Cohort Study during 2015-2017. Three-year averaged concentrations of PM2.5 mass and its constituents (black carbon (BC), ammonium (NH4+), nitrate (NO3-), organic matter (OM), inorganic sulfate (SO42-), soil particles (SOIL) and sea salt (SS)) were estimated by a hybrid satellite-based model. Generalized linear model was applied to explore the associations of PM2.5 mass and its constituents with type 2 diabetes mellitus (T2DM), fasting blood glucose (FBG), insulin, and HOMA-β. Proportion and residual analyses were employed to specify the most responsible constituent. RESULTS The adjusted odds ratio (OR) for T2DM associated with 1 μg/m3 increase was 1.02 for PM2.5 mass, 1.28 for BC, 1.15 for NH4+, 1.08 for NO3-, 1.10 for OM, 1.11 for SO42-, and 1.12 for SOIL. Significant associations of PM2.5 mass and its constituents with elevated FBG, decreased insulin and HOMA-β were also observed. Proportion and residual analyses indicated that BC was the most responsible constituent, in which 1 percentage increment in the proportion of BC in PM2.5 corresponded with 1.51-fold risk for T2DM, 0.17 mmol/L increase in FBG, 2.18 μU/mL decrease in insulin, and 38.26 % decrease in HOMA-β; and 1 μg/m3 increment in the PM2.5-adjusted BC corresponded with 1.59-fold risk for T2DM, 0.53 mmol/L increase in FBG, 4.79 μU/mL decrease in insulin, and 91.32 % decrease in HOMA-β. CONCLUSIONS PM2.5 mass and its constituents (BC, NH4+, NO3-, OM, SO42-, SOIL) were associated with T2DM, increased FBG, decreased insulin and HOMA-β, of which BC was most responsible for these associations. TRIAL REGISTRATION The Henan Rural Cohort Study has been registered at Chinese Clinical Trial Register (Registration number: ChiCTR-OOC-15006699). Date of registration: 06 July 2015. http://www.chictr.org.cn/showproj.aspx?proj=11375.
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Affiliation(s)
- Ning Kang
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, China
| | - Ruiyu Wu
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, China
| | - Wei Liao
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, China
| | - Caiyun Zhang
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, China
| | - Xiaotian Liu
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, China
| | - Zhenxing Mao
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, China
| | - Wenqian Huo
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, China
| | - Jian Hou
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, China
| | - Kai Zhang
- Department of Environmental Health Sciences, School of Public Health, University at Albany, State University of New York, Albany, NY, USA
| | - Hezhong Tian
- State Key Joint Laboratory of Environmental Simulation & Pollution Control, School of Environment, Beijing Normal University, Beijing, China
| | - Hualiang Lin
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, China; Department of Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou, Guangdong, China.
| | - Chongjian Wang
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, China.
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Zhang L, Wang P, Zhou Y, Cheng Y, Li J, Xiao X, Yin C, Li J, Meng X, Zhang Y. Associations of ozone exposure with gestational diabetes mellitus and glucose homeostasis: Evidence from a birth cohort in Shanghai, China. Sci Total Environ 2023; 857:159184. [PMID: 36202368 DOI: 10.1016/j.scitotenv.2022.159184] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/30/2022] [Revised: 09/28/2022] [Accepted: 09/29/2022] [Indexed: 06/16/2023]
Abstract
BACKGROUND Associations between individual exposure to ozone (O3) and gestational diabetes mellitus (GDM) have rarely been investigated, and critical windows of O3 exposure for GDM have not been identified. OBJECTIVES We aimed to explore the associations of gestational O3 exposure with GDM and glucose homeostasis as well as to identify the potential critical windows. METHODS A total of 7834 pregnant women were included. Individual O3 exposure concentrations were evaluated using a high temporal-spatial resolution model. Each participant underwent an oral glucose tolerance test (OGTT) to screen for GDM between 24 and 28 gestational weeks. Multiple logistic and multiple linear regression models were used to estimate the associations of O3 with GDM risks and with blood glucose levels of OGTT, respectively. Distributed lag nonlinear models (DLNMs) were used to estimate the critical windows of O3 exposure for GDM. RESULTS Nearly 13.29 % of participants developed GDM. After controlling for covariates, we observed increased GDM risks per IQR increment of O3 exposure in the first trimester (OR = 1.738, 95 % CI: 1.002-3.016) and the first two trimesters (OR = 1.576, 95 % CI: 1.005-2.473). Gestational O3 exposure was positively associated with increased fasting blood glucose (the first trimester: β = 2.964, 95 % CI: 1.529-4.398; the first two trimesters: β = 1.620, 95 % CI: 0.436-2.804) and 2 h blood glucose (the first trimester: β = 6.569, 95 % CI: 1.775-11.363; the first two trimesters: β = 6.839, 95 % CI: 2.896-10.782). We also observed a concentration-response relationship of gestational O3 exposure with GDM risk, as well as fasting and 2 h blood glucose levels. Additionally, 5-10 gestational weeks was identified as a critical window of O3 exposure for GDM development. CONCLUSION In summary, we found that gestational O3 exposure disrupts glucose homeostasis and increases the risk of GDM in pregnant women. Furthermore, 5-10 gestational weeks could be a critical window for the effects of O3 exposure on GDM.
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Affiliation(s)
- Liyi Zhang
- Key Lab of Health Technology Assessment, National Health Commission of the People's Republic of China, Fudan University, Shanghai 200032, China; Key Laboratory of Public Health Safety, Ministry of Education, School of Public Health, Fudan University, Shanghai 200032, China
| | - Pengpeng Wang
- Key Lab of Health Technology Assessment, National Health Commission of the People's Republic of China, Fudan University, Shanghai 200032, China; Key Laboratory of Public Health Safety, Ministry of Education, School of Public Health, Fudan University, Shanghai 200032, China
| | - Yuhan Zhou
- Key Lab of Health Technology Assessment, National Health Commission of the People's Republic of China, Fudan University, Shanghai 200032, China; Key Laboratory of Public Health Safety, Ministry of Education, School of Public Health, Fudan University, Shanghai 200032, China
| | - Yukai Cheng
- Key Lab of Health Technology Assessment, National Health Commission of the People's Republic of China, Fudan University, Shanghai 200032, China; Key Laboratory of Public Health Safety, Ministry of Education, School of Public Health, Fudan University, Shanghai 200032, China
| | - Jialin Li
- Key Lab of Health Technology Assessment, National Health Commission of the People's Republic of China, Fudan University, Shanghai 200032, China; Key Laboratory of Public Health Safety, Ministry of Education, School of Public Health, Fudan University, Shanghai 200032, China
| | - Xirong Xiao
- Department of Obstetrics and Gynecology, Obstetrics and Gynecology Hospital of Fudan University, Shanghai 200011, China
| | - Chuanmin Yin
- Department of Obstetrics and Gynecology, Obstetrics and Gynecology Hospital of Fudan University, Shanghai 200011, China
| | - Jiufeng Li
- Key Lab of Health Technology Assessment, National Health Commission of the People's Republic of China, Fudan University, Shanghai 200032, China; Key Laboratory of Public Health Safety, Ministry of Education, School of Public Health, Fudan University, Shanghai 200032, China
| | - Xia Meng
- Key Lab of Health Technology Assessment, National Health Commission of the People's Republic of China, Fudan University, Shanghai 200032, China; Key Laboratory of Public Health Safety, Ministry of Education, School of Public Health, Fudan University, Shanghai 200032, China.
| | - Yunhui Zhang
- Key Lab of Health Technology Assessment, National Health Commission of the People's Republic of China, Fudan University, Shanghai 200032, China; Key Laboratory of Public Health Safety, Ministry of Education, School of Public Health, Fudan University, Shanghai 200032, China.
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Yan RH, Peng X, Lin W, He LY, Wei FH, Tang MX, Huang XF. Trends and Challenges Regarding the Source-Specific Health Risk of PM 2.5-Bound Metals in a Chinese Megacity from 2014 to 2020. Environ Sci Technol 2022; 56:6996-7005. [PMID: 35050611 DOI: 10.1021/acs.est.1c06948] [Citation(s) in RCA: 20] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/23/2023]
Abstract
Identifying the health risk of PM2.5 is essential for urban air pollution control. In 2013, China announced the ever-strict national Air Pollution Prevention and Control Action Plan, and its health benefit should be evaluated to provide reference for future policymaking. In this study, we conducted a seven-year (2014-2020) continuous observation of PM2.5 in Shenzhen, the third largest city in China, which has relatively good air quality. The results showed that the annual mean PM2.5 and total concentration of 21 associated metals dropped from 37.7 to 18.5 μg/m3 and from 2.4 to 1.1 μg/m3, respectively. Combining methods for source apportionment and health risk assessment, we found that the total carcinogenic risk (CR) of five hazardous metals (Cd, Cr, Ni, Co, and Pb) showed a clear decreasing trend. However, the total CR (1.8 × 10-6) in 2020 still exceeded the widely acceptable risk level (i.e., 1 × 10-6), with the primary contributor changing from industrial emissions (61%) to vehicle emissions (63%). Further analysis indicated that the CR of vehicles mainly came from Cr and Ni released by braking and tire wearing and has fluctuated in recent years, highlighting a great challenge of controlling nonexhaust emissions of vehicles (including electric cars) in the future.
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Affiliation(s)
- Run-Hua Yan
- Laboratory of Atmospheric Observation Supersite, School of Environment and Energy, Peking University Shenzhen Graduate School, Shenzhen 518055, China
| | - Xing Peng
- Laboratory of Atmospheric Observation Supersite, School of Environment and Energy, Peking University Shenzhen Graduate School, Shenzhen 518055, China
| | - Weiwei Lin
- Department of Occupational and Environmental Health, School of Public Health, Sun Yat-Sen University, Guangzhou 510080, China
| | - Ling-Yan He
- Laboratory of Atmospheric Observation Supersite, School of Environment and Energy, Peking University Shenzhen Graduate School, Shenzhen 518055, China
| | - Feng-Hua Wei
- Laboratory of Atmospheric Observation Supersite, School of Environment and Energy, Peking University Shenzhen Graduate School, Shenzhen 518055, China
| | - Meng-Xue Tang
- Laboratory of Atmospheric Observation Supersite, School of Environment and Energy, Peking University Shenzhen Graduate School, Shenzhen 518055, China
| | - Xiao-Feng Huang
- Laboratory of Atmospheric Observation Supersite, School of Environment and Energy, Peking University Shenzhen Graduate School, Shenzhen 518055, China
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