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Liu Q, Pan L, He H, Hu Y, Tu J, Zhang L, Sun Z, Cui Z, Han X, Huang H, Lin B, Fan Y, Ji Y, Shan G. Effects of long-term exposure to air pollutant mixture on blood pressure in typical areas of North China. ECOTOXICOLOGY AND ENVIRONMENTAL SAFETY 2024; 285:116987. [PMID: 39299210 DOI: 10.1016/j.ecoenv.2024.116987] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/27/2024] [Revised: 08/22/2024] [Accepted: 08/30/2024] [Indexed: 09/22/2024]
Abstract
BACKGROUND Studies about the combined effects of gaseous air pollutants and particulate matters are still rare. OBJECTIVES This study was performed based on baseline survey of the Diverse Life-Course Cohort in the Beijing-Tianjin-Hebei (BTH) Region of North China to evaluate the association of long-term air pollutants with blood pressure and the combined effect of the air pollutants mixture among 32821 natural han population aged 20 years or above. METHODS Three-year average exposure to air pollutants (PM10, PM2.5, PM1, O3, SO2, NO2, and CO) and PM2.5 components [black carbon (BC), ammonium (NH4+), nitrate (NO3-), sulfate (SO42-), and organic matter (OM)] of residential areas were calculated based on well-validated models. Generalized linear mixed models (GLMMs) were used to estimate the associations of air pollutants exposure with the systolic blood pressure (SBP), diastolic blood pressure (DBP), Mean arterial pressure (MAP), pulse pressure (PP) and prevalent hypertension. Quantile g-Computation and Bayesian Kernel Machine Regression (BKMR) were employed to assess the combined effect of the air pollutant mixture. RESULTS We found that long-term exposures of O3, PM2.5, and PM2.5 components were stably and strongly associated with elevated SBP, DBP, and MAP and prevalent hypertension. O3 increased SBP, DBP, and MAP at a similar extent, but with greater effects; while, PM2.5 and PM2.5 components had a greater impact on SBP than DBP, which increased PP simultaneously. In multi-pollutant models, the combined effects of the air pollutant mixture on blood pressure and prevalent hypertension was predominantly influenced by O3, PM2.5, and O3, OM in different models, respectively. For example, O3, PM2.5 contributed 57.25 %, 39.22 % of the positive combined effect of the air pollutant mixture on SBP; and O3, OM positively contributed 70.00 %, 30.00 % on prevalent hypertension, respectively. There were interactions between O3, CO, SO2 and PM2.5 components on hbp, SBP and PP. CONCLUSIONS The results showed positive associations of air pollutant mixtures with blood pressure, where O3 and PM2.5 (especially OM) might be primary contributors. There were interactions between gaseous air pollutants and PM2.5 components on blood pressure and prevalent hypertension.
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Affiliation(s)
- Qihang Liu
- Epidemiology and Statistics, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences & School of Basic Medicine, Peking Union Medical College, Beijing, China; State Key Laboratory of Common Mechanism Research for Major Diseases, Beijing, China
| | - Li Pan
- Epidemiology and Statistics, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences & School of Basic Medicine, Peking Union Medical College, Beijing, China; State Key Laboratory of Common Mechanism Research for Major Diseases, Beijing, China
| | - Huijing He
- Epidemiology and Statistics, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences & School of Basic Medicine, Peking Union Medical College, Beijing, China; State Key Laboratory of Common Mechanism Research for Major Diseases, Beijing, China
| | - Yaoda Hu
- Epidemiology and Statistics, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences & School of Basic Medicine, Peking Union Medical College, Beijing, China; State Key Laboratory of Common Mechanism Research for Major Diseases, Beijing, China
| | - Ji Tu
- Epidemiology and Statistics, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences & School of Basic Medicine, Peking Union Medical College, Beijing, China; State Key Laboratory of Common Mechanism Research for Major Diseases, Beijing, China
| | - Ling Zhang
- Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, and Beijing Municipal Key Laboratory of Clinical Epidemiology, Beijing, China
| | - Zhiwei Sun
- Department of Toxicology and Sanitary Chemistry, School of Public Health, Capital Medical University, Beijing, China; Key Laboratory of Environmental Toxicology, Capital Medical University, Beijing, China
| | - Ze Cui
- Hebei Provicel Center for diseases prevention and control, Shijiazhuang, Hebei, China
| | - Xiaoyan Han
- Chaoyang District Center for Disease Control and Prevention, Beijing, China
| | - Haibo Huang
- Epidemiology and Statistics, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences & School of Basic Medicine, Peking Union Medical College, Beijing, China; State Key Laboratory of Common Mechanism Research for Major Diseases, Beijing, China
| | - Binbin Lin
- Epidemiology and Statistics, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences & School of Basic Medicine, Peking Union Medical College, Beijing, China; State Key Laboratory of Common Mechanism Research for Major Diseases, Beijing, China
| | - Yajiao Fan
- Department of Preventive Medicine, School of Public Health, Hebei University, Baoding, Hebei, China
| | - Yanxin Ji
- Baoding Center for Disease Control and Prevention, Hebei, China
| | - Guangliang Shan
- Epidemiology and Statistics, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences & School of Basic Medicine, Peking Union Medical College, Beijing, China; State Key Laboratory of Common Mechanism Research for Major Diseases, Beijing, China.
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Zhou H, Hong F, Wang L, Tang X, Guo B, Luo Y, Yu H, Mao D, Liu T, Feng Y, Baima Y, Zhang J, Zhao X. Air pollution and risk of 32 health conditions: outcome-wide analyses in a population-based prospective cohort in Southwest China. BMC Med 2024; 22:370. [PMID: 39256817 PMCID: PMC11389248 DOI: 10.1186/s12916-024-03596-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/11/2024] [Accepted: 08/28/2024] [Indexed: 09/12/2024] Open
Abstract
BACKGROUND Uncertainty remains about the long-term effects of air pollutants (AP) on multiple diseases, especially subtypes of cardiovascular disease (CVD). We aimed to assess the individual and joint associations of fine particulate matter (PM2.5), along with its chemical components, nitrogen dioxide (NO2) and ozone (O3), with risks of 32 health conditions. METHODS A total of 17,566 participants in Sichuan Province, China, were included in 2018 and followed until 2022, with an average follow-up period of 4.2 years. The concentrations of AP were measured using a machine-learning approach. The Cox proportional hazards model and quantile g-computation were applied to assess the associations between AP and CVD. RESULTS Per interquartile range (IQR) increase in PM2.5 mass, NO2, O3, nitrate, ammonium, organic matter (OM), black carbon (BC), chloride, and sulfate were significantly associated with increased risks of various conditions, with hazard ratios (HRs) ranging from 1.06 to 2.48. Exposure to multiple air pollutants was associated with total cardiovascular disease (HR 1.75, 95% confidence intervals (CIs) 1.62-1.89), hypertensive diseases (1.49, 1.38-1.62), cardiac arrests (1.52, 1.30-1.77), arrhythmia (1.76, 1.44-2.15), cerebrovascular diseases (1.86, 1.65-2.10), stroke (1.77, 1.54-2.03), ischemic stroke (1.85, 1.61-2.12), atherosclerosis (1.77, 1.57-1.99), diseases of veins, lymphatic vessels, and lymph nodes (1.32, 1.15-1.51), pneumonia (1.37, 1.16-1.61), inflammatory bowel diseases (1.34, 1.16-1.55), liver diseases (1.59, 1.43-1.77), type 2 diabetes (1.48, 1.26-1.73), lipoprotein metabolism disorders (2.20, 1.96-2.47), purine metabolism disorders (1.61, 1.38-1.88), anemia (1.29, 1.15-1.45), sleep disorders (1.54, 1.33-1.78), renal failure (1.44, 1.21-1.72), kidney stone (1.27, 1.13-1.43), osteoarthritis (2.18, 2.00-2.39), osteoporosis (1.36, 1.14-1.61). OM had max weights for joint effects of AP on many conditions. CONCLUSIONS Long-term exposure to increased levels of multiple air pollutants was associated with risks of multiple health conditions. OM accounted for substantial weight for these increased risks, suggesting it may play an important role in these associations.
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Affiliation(s)
- Hanwen Zhou
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Feng Hong
- School of Public Health, the Key Laboratory of Environmental Pollution Monitoring and Disease Control, Ministry of Education, Guizhou Medical University, Guiyang, China
| | - Lele Wang
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Xuewei Tang
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Bing Guo
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Yuying Luo
- Health Information Center of Sichuan Province, Chengdu, Sichuan, China
| | - Hui Yu
- Health Information Center of Sichuan Province, Chengdu, Sichuan, China
| | - Deqiang Mao
- Chongqing Municipal Center for Disease Control and Prevention, Chongqing, China
| | - Ting Liu
- Chenghua District Center for Disease Control and Prevention, Chengdu, China
| | - Yuemei Feng
- School of Public Health, Kunming Medical University, Kunming, Yunnan, China
| | - Yangji Baima
- School of Medicine, Tibet University, Tibet, China
| | - Juying Zhang
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China.
| | - Xing Zhao
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China.
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Zhang J, Zhang J, Duan Z, Nie J, Li X, Yu W, Niu Z, Yan Y. Association between long-term exposure to PM 2.5 chemical components and metabolic syndrome in middle-aged and older adults. Front Public Health 2024; 12:1462548. [PMID: 39234085 PMCID: PMC11371722 DOI: 10.3389/fpubh.2024.1462548] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2024] [Accepted: 08/08/2024] [Indexed: 09/06/2024] Open
Abstract
Background Previous studies indicated that exposure to ambient fine particulate matter (PM2.5) could increase the risk of metabolic syndrome (MetS). However, the specific impact of PM2.5 chemical components remains uncertain. Methods A national cross-sectional study of 12,846 Chinese middle-aged and older adults was conducted. Satellite-based spatiotemporal models were employed to determine the 3-year average PM2.5 components exposure, including sulfates (SO4 2-), nitrates (NO3 -), ammonia (NH4 +), black carbon (BC), and organic matter (OM). Generalized linear models were used to investigate the associations of PM2.5 components with MetS and the components of MetS, and restricted cubic splines curves were used to establish the exposure-response relationships between PM2.5 components with MetS, as well as the components of MetS. Results MetS risk increased by 35.1, 33.5, 33.6, 31.2, 32.4, and 31.4% for every inter-quartile range rise in PM2.5, SO4 2-, NO3 -, NH4 +, OM and BC, respectively. For MetS components, PM2.5 chemical components were associated with evaluated risks of central obesity, high blood pressure (high-BP), high fasting glucose (high-FBG), and low high-density lipoprotein cholesterol (low-HDL). Conclusion This study indicated that exposure to PM2.5 components is related to increased risk of MetS and its components, including central obesity, high-BP, high-FBG, and low-HDL. Moreover, we found that the adverse effect of PM2.5 chemical components on MetS was more sensitive to people who were single, divorced, or widowed than married people.
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Affiliation(s)
- Jingjing Zhang
- Department of Medical Imaging Center, Northwest Women's and Children's Hospital, Xi'an, China
| | - Jinglong Zhang
- Department of Cardiovascular Surgery, Xijing Hospital, The Fourth Military Medical University, Xi'an, China
| | - Zhizhou Duan
- Preventive Health Service, Jiangxi Provincial People's Hospital, The First Affiliated Hospital of Nanchang Medical College, Nanchang, Jiangxi, China
| | - Jing Nie
- Population Research Institute, Nanjing University of Posts and Telecommunications, Nanjing, China
| | - Xiangyu Li
- Shanghai Tenth People's Hospital, Tongji University, Shanghai, China
| | - Wenyuan Yu
- School & Hospital of Stomatology, Wuhan University, Wuhan, China
| | - Zhiping Niu
- Department of Environmental Health, School of Public Health, Fudan University, Shanghai, China
| | - Yangjin Yan
- Department of Cardiology, Xi'an No.3 Hospital, The Affiliated Hospital of Northwest University, Xi'an, Shaanxi, China
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Wu R, Kang N, Zhang C, Song Y, Liao W, Hong Y, Hou J, Zhang K, Tian H, Lin H, Wang C. Long-term exposure to PM 2.5 and its components is associated with elevated blood pressure and hypertension prevalence: Evidence from rural adults. J Adv Res 2024; 60:173-181. [PMID: 37517519 PMCID: PMC11156605 DOI: 10.1016/j.jare.2023.07.012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2022] [Revised: 07/24/2023] [Accepted: 07/27/2023] [Indexed: 08/01/2023] Open
Abstract
INTRODUCTION The toxicity of fine particulate matter (PM2.5) is determined by its components, while the evidence regarding associations of PM2.5 components with blood pressure (BP) is limited, especially in rural areas. OBJECTIVES This study aimed to explore the associations of PM2.5 and its chemical components with systolic BP (SBP), diastolic BP (DBP), pulse pressure (PP), mean artery pressure (MAP) levels and hypertension prevalence, and to identify key components in Chinese rural areas. METHODS 39,211 adults from the Henan Rural Cohort were included during 2015-2017. Different periods of PM2.5 and chemical components were estimated by hybrid satellite model. The single-pollutant, component-PM2.5 model, component-residual model and component-proportion model were applied to explore the associations of pollutants with BP levels and hypertension prevalence. Exposure-response (E-R) relationships, stratified analyses and sensitivity analyses were used to explore these associations further. RESULTS 12,826 (32.71%) were identified with hypertension. For each 1 μg/m3 increase of pollutants, the adjusted odds ratio (OR) for hypertension prevalence was 1.03 for PM2.5 mass, 1.40 for BC, 1.16 for NH4+, 1.08 for NO3-, 1.17 for OM, 1.12 for SO42- and 1.25 for SOIL in the single-pollutant model. BC and SOIL were statistically significant in the component-PM2.5 model, component-residual model and component-proportion model. Similarly, associations of these pollutants with elevated BP levels were also found in aforementioned four models. These pollutants produced a stronger association with SBP than DBP, PP and MAP. Most of associations were non-linear in E-R relationships. The groups of older, the men, with lower per capita monthly income, lower educational level and higher BMI were more vulnerable to these pollutants in stratified analyses. The results remained stable in sensitivity analyses. CONCLUSION Long-term exposure to PM2.5 and its components, especially BC and SOIL, was associated with elevated BP and hypertension prevalence in rural adults, and decreasing pollutants may provide additional benefits.
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Affiliation(s)
- Ruiyu Wu
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, PR China
| | - Ning Kang
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, PR China
| | - Caiyun Zhang
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, PR China
| | - Yu Song
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, PR China
| | - Wei Liao
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, PR China
| | - Yueling Hong
- Department of Zhengzhou Center for Disease Control and Prevention, Zhengzhou, Henan, PR China
| | - Jian Hou
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, PR 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, PR China
| | - Hualiang Lin
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, PR China; Department of Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou, Guangdong, PR China.
| | - Chongjian Wang
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, PR China.
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Zhou H, Liang X, Zhang X, Wu J, Jiang Y, Guo B, Wang J, Meng Q, Ding X, Baima Y, Li J, Wei J, Zhang J, Zhao X. Associations of Long-Term Exposure to Fine Particulate Constituents With Cardiovascular Diseases and Underlying Metabolic Mediations: A Prospective Population-Based Cohort in Southwest China. J Am Heart Assoc 2024; 13:e033455. [PMID: 38761074 PMCID: PMC11179805 DOI: 10.1161/jaha.123.033455] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/07/2023] [Accepted: 04/01/2024] [Indexed: 05/20/2024]
Abstract
BACKGROUND The health effects of particulate matter with an aerodynamic diameter ≤2.5 μm (PM2.5) might differ depending on compositional variations. Little is known about the joint effect of PM2.5 constituents on metabolic syndrome and cardiovascular disease (CVD). This study aims to evaluate the combined associations of PM2.5 components with CVD, identify the most detrimental constituent, and further quantify the mediation effect of metabolic syndrome. METHODS AND RESULTS A total of 14 427 adults were included in a cohort study in Sichuan, China, and were followed to obtain the diagnosis of CVD until 2021. Metabolic syndrome was defined by the simultaneous occurrence of multiple metabolic disorders measured at baseline. The concentrations of PM2.5 chemical constituents within a 1-km2 grid were derived based on satellite- and ground-based detection methods. Cox proportional hazard models showed that black carbon, organic matter (OM), nitrate, ammonium, chloride, and sulfate were positively associated with CVD risks, with hazard ratios (HRs) ranging from 1.24 to 2.11 (all P<0.05). Quantile g-computation showed positive associations with 4 types of CVD risks (HRs ranging from 1.48 to 2.25, all P<0.05). OM and chloride had maximum weights for CVD risks. Causal mediation analysis showed that the positive association of OM with total CVD was mediated by metabolic syndrome, with a mediation proportion of 1.3% (all P<0.05). CONCLUSIONS Long-term exposure to PM2.5 chemical constituents is positively associated with CVD risks. OM and chloride appear to play the most responsible role in the positive associations between PM2.5 and CVD. OM is probably associated with CVD through metabolic-related pathways.
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Affiliation(s)
- Hanwen Zhou
- West China School of Public Health and West China Fourth Hospital Sichuan University Chengdu Sichuan China
| | - Xian Liang
- Chengdu Center for Disease Control and Prevention Chengdu Sichuan China
| | - Xueli Zhang
- Health Information Center of Sichuan Province Chengdu Sichuan China
| | - Jialong Wu
- West China School of Public Health and West China Fourth Hospital Sichuan University Chengdu Sichuan China
| | - Ye Jiang
- West China School of Public Health and West China Fourth Hospital Sichuan University Chengdu Sichuan China
| | - Bing Guo
- West China School of Public Health and West China Fourth Hospital Sichuan University Chengdu Sichuan China
| | - Junhua Wang
- School of Public Health, The key Laboratory of Environmental Pollution Monitoring and Disease Control, Ministry of Education Guizhou Medical University Guiyang China
| | - Qiong Meng
- Department of Epidemiology and Health Statistics, School of Public Health Kunming Medical University Kunming Yunnan China
| | - Xianbin Ding
- Chongqing Municipal Center for Disease Control and Prevention Chongqing China
| | | | - Jingzhong Li
- Tibet Center for Disease Control and Prevention Lhasa Tibet China
| | - Jing Wei
- Department of Atmospheric and Oceanic Science, Earth System Science Interdisciplinary Center University of Maryland College Park MD USA
| | - Juying Zhang
- West China School of Public Health and West China Fourth Hospital Sichuan University Chengdu Sichuan China
| | - Xing Zhao
- West China School of Public Health and West China Fourth Hospital Sichuan University Chengdu Sichuan China
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Dai Y, Yin J, Li S, Li J, Han X, Deji Q, Pengcuo C, Liu L, Yu Z, Chen L, Xie L, Guo B, Zhao X. Long-term exposure to fine particulate matter constituents in relation to chronic kidney disease: evidence from a large population-based study in China. ENVIRONMENTAL GEOCHEMISTRY AND HEALTH 2024; 46:174. [PMID: 38592609 DOI: 10.1007/s10653-024-01949-w] [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: 07/03/2023] [Accepted: 03/07/2024] [Indexed: 04/10/2024]
Abstract
The effects of long-term exposure to fine particulate matter (PM2.5) constituents on chronic kidney disease (CKD) are not fully known. This study sought to examine the association between long-term exposure to major PM2.5 constituents and CKD and look for potential constituents contributing substantially to CKD. This study included 81,137 adults from the 2018 to 2019 baseline survey of China Multi-Ethnic Cohort. CKD was defined by the estimated glomerular filtration rate. Exposure concentration data of 7 major PM2.5 constituents were assessed by satellite remote sensing. Logistic regression models were used to estimate the effect of each PM2.5 constituent exposure on CKD. The weighted quantile sum regression was used to estimate the effect of mixed exposure to all constituents. PM2.5 constituents had positive correlations with CKD (per standard deviation increase), with ORs (95% CIs) of 1.20 (1.02-1.41) for black carbon, 1.27 (1.07-1.51) for ammonium, 1.29 (1.08-1.55) for nitrate, 1.20 (1.01-1.43) for organic matter, 1.25 (1.06-1.46) for sulfate, 1.30 (1.11-1.54) for soil particles, and 1.63 (1.39-1.91) for sea salt. Mixed exposure to all constituents was positively associated with CKD (1.68, 1.32-2.11). Sea salt was the constituent with the largest weight (0.36), which suggested its importance in the PM2.5-CKD association, followed by nitrate (0.32), organic matter (0.18), soil particles (0.10), ammonium (0.03), BC (0.01). Sulfate had the least weight (< 0.01). Long-term exposure to PM2.5 sea salt and nitrate may contribute more than other constituents in increasing CKD risk, providing new evidence and insights for PM2.5-CKD mechanism research and air pollution control strategy.
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Affiliation(s)
- Yucen Dai
- West China School of Public Health and West China Fourth Hospital, Sichuan University, No.17, Section 3, South Renmin Road, Chengdu, 610041, Sichuan Province, China
| | - Jianzhong Yin
- School of Public Health, Kunming Medical University, Kunming, China
- Baoshan College of Traditional Chinese Medicine, Baoshan, China
| | - Sicheng Li
- West China School of Public Health and West China Fourth Hospital, Sichuan University, No.17, Section 3, South Renmin Road, Chengdu, 610041, Sichuan Province, China
| | - Jiawei Li
- West China School of Public Health and West China Fourth Hospital, Sichuan University, No.17, Section 3, South Renmin Road, Chengdu, 610041, Sichuan Province, China
| | - Xinyu Han
- West China School of Public Health and West China Fourth Hospital, Sichuan University, No.17, Section 3, South Renmin Road, Chengdu, 610041, Sichuan Province, China
| | | | - Ciren Pengcuo
- Tibet Center for Disease Control and Prevention CN, Lhasa, China
| | - Leilei Liu
- School of Public Health the Key Laboratory of Environmental Pollution Monitoring and Disease Control, Ministry of Education, Guizhou Medical University, Guiyang, China
| | - Zhimiao Yu
- Chengdu Center for Disease Control and Prevention, Chengdu, China
| | - Liling Chen
- Chongqing Municipal Center for Disease Control and Prevention, Chongqing, China
| | - Linshen Xie
- West China School of Public Health and West China Fourth Hospital, Sichuan University, No.17, Section 3, South Renmin Road, Chengdu, 610041, Sichuan Province, China.
| | - Bing Guo
- West China School of Public Health and West China Fourth Hospital, Sichuan University, No.17, Section 3, South Renmin Road, Chengdu, 610041, Sichuan Province, China.
| | - Xing Zhao
- West China School of Public Health and West China Fourth Hospital, Sichuan University, No.17, Section 3, South Renmin Road, Chengdu, 610041, Sichuan Province, China
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Lin L, Huang H, Lei F, Sun T, Chen Z, Qin K, Li M, Hu Y, Huang X, Zhang X, Zhang P, Zhang XJ, She ZG, Cai J, Yang S, Jia P, Li H. Long-Term Exposure to Fine Particulate Constituents and Vascular Damage in a Population with Metabolic Abnormality in China. J Atheroscler Thromb 2023; 30:1552-1567. [PMID: 37032101 PMCID: PMC10627764 DOI: 10.5551/jat.64062] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2022] [Accepted: 02/23/2023] [Indexed: 04/11/2023] Open
Abstract
AIM To date, PM2.5-associated vascular damage in metabolic abnormalities has remained controversial. We knew little about the vascular damage of PM2.5 constituents. Thus, this study aimed to investigate the relationship between long-term exposure to PM2.5 and its constituents and vascular damage in metabolic abnormalities. METHODS A total of 124,387 participants with metabolic abnormalities (defined as at least one metabolic disorder, such as obesity, elevated blood pressure, elevated triglyceride level, elevated fasting glucose level, or low HDL cholesterol level) were recruited in this study from 11 representative centers in China between January 2011 and December 2017. PM2.5 and its constituents (black carbon [BC], organic matter [OM], sulfate [SO42-], nitrate [NO3-], and ammonium salts [NH4+]) were extracted. Elevated brachial-ankle pulse wave velocity (baPWV) (≥ 1,400 cm/s) and declined ankle-brachial index (ABI) (<0.9) indicated vascular damage. Multivariable logistic regression and Quantile g-Computation models were utilized to explore the impact on outcomes. RESULTS Of the 124,387 participants (median age, 49 years), 87,870 (70.64%) were men. One-year lag exposure to PM2.5 and its constituents was significantly associated with vascular damage in single pollutant models. The adjusted odds ratios (OR) for each 1-µg/m3 increase in PM2.5 was 1.013 (95% CI, 1.012-1.015) and 1.031 (95% CI, 1.025-1.037) for elevated baPWV and decreased ABI, respectively. PM2.5 constituents were also associated with vascular damage in multi-pollutant models. Among the PM2.5 constituents, BC (47.17%), SO42- (33.59%), and NH4+ (19.23%) have the highest contribution to elevated baPWV and NO3- (47.89%) and BC (23.50%) to declined ABI. CONCLUSION Chronic exposure to PM2.5 and PM2.5 constituents was related to vascular damage in the abnormal metabolic population in China. The heterogeneous contribution of different PM2.5 constituents to vessel bed damage is worthy of attention when developing targeted strategies.
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Affiliation(s)
- Lijin Lin
- Department of Cardiology, Renmin Hospital of Wuhan University, Wuhan, China
- Institute of Model Animal, Wuhan University, Wuhan, China
- Medical Science Research Center, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Huxiang Huang
- Department of Respiratory and Critical Care Medicine, Huanggang central Hospital of Yangtze University, Huanggang, China
- Huanggang Institute of Translational Medicine, Huanggang, China
| | - Fang Lei
- Institute of Model Animal, Wuhan University, Wuhan, China
- School of Basic Medical Science, Wuhan University, Wuhan, China
| | - Tao Sun
- Department of Cardiology, Renmin Hospital of Wuhan University, Wuhan, China
- Institute of Model Animal, Wuhan University, Wuhan, China
| | - Ze Chen
- Institute of Model Animal, Wuhan University, Wuhan, China
- Department of Cardiology, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Kun Qin
- School of Resource and Environmental Sciences, Wuhan University, Wuhan, China
- International Institute of Spatial Lifecourse Health (ISLE), Wuhan University, Wuhan, China
| | - Manyao Li
- School of Resource and Environmental Sciences, Wuhan University, Wuhan, China
- International Institute of Spatial Lifecourse Health (ISLE), Wuhan University, Wuhan, China
| | - Yingying Hu
- Department of Cardiology, Renmin Hospital of Wuhan University, Wuhan, China
- Institute of Model Animal, Wuhan University, Wuhan, China
| | - Xuewei Huang
- Institute of Model Animal, Wuhan University, Wuhan, China
- Department of Cardiology, The Third Xiangya Hospital, Central South University, Changsha, China
| | - Xingyuan Zhang
- Institute of Model Animal, Wuhan University, Wuhan, China
- School of Basic Medical Science, Wuhan University, Wuhan, China
| | - Peng Zhang
- Institute of Model Animal, Wuhan University, Wuhan, China
- School of Basic Medical Science, Wuhan University, Wuhan, China
| | - Xiao-Jing Zhang
- Institute of Model Animal, Wuhan University, Wuhan, China
- School of Basic Medical Science, Wuhan University, Wuhan, China
| | - Zhi-Gang She
- Department of Cardiology, Renmin Hospital of Wuhan University, Wuhan, China
- Institute of Model Animal, Wuhan University, Wuhan, China
| | - Jingjing Cai
- Institute of Model Animal, Wuhan University, Wuhan, China
- Department of Cardiology, The Third Xiangya Hospital, Central South University, Changsha, China
| | - Shujuan Yang
- International Institute of Spatial Lifecourse Health (ISLE), Wuhan University, Wuhan, China
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Peng Jia
- School of Resource and Environmental Sciences, Wuhan University, Wuhan, China
- International Institute of Spatial Lifecourse Health (ISLE), Wuhan University, Wuhan, China
- Hubei Luojia Laboratory, Wuhan, China
- School of Public Health, Wuhan University, Wuhan, China
| | - Hongliang Li
- Department of Cardiology, Renmin Hospital of Wuhan University, Wuhan, China
- Institute of Model Animal, Wuhan University, Wuhan, China
- Huanggang Institute of Translational Medicine, Huanggang, China
- Medical Science Research Center, Zhongnan Hospital of Wuhan University, Wuhan, China
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8
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Mo S, Hu J, Yu C, Bao J, Shi Z, Zhou P, Yang Z, Luo S, Yin Z, Zhang Y. Short-term effects of fine particulate matter constituents on myocardial infarction death. J Environ Sci (China) 2023; 133:60-69. [PMID: 37451789 DOI: 10.1016/j.jes.2022.07.019] [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: 11/29/2021] [Revised: 07/07/2022] [Accepted: 07/11/2022] [Indexed: 07/18/2023]
Abstract
Existing evidence suggested that short-term exposure to fine particulate matter (PM2.5) may increase the risk of death from myocardial infarction (MI), while PM2.5 constituents responsible for this association has not been determined. We collected 12,927 MI deaths from 32 counties in southern China during 2011-2013. County-level exposures of ambient PM2.5 and its 5 constituents (i.e., elemental carbon (EC), organic carbon (OC), sulfate (SO42-), ammonium (NH4+), and nitrate (NO3-)) were aggregated from gridded datasets predicted by Community Multiscale Air Quality Modeling System. We employed a space-time-stratified case-crossover design and conditional logistic regression models to quantify the association of MI mortality with short-term exposure to PM2.5 and its constituents across various lag days. Over the study period, the daily mean PM2.5 mass concentration was 77.8 (standard deviation (SD) = 72.7) µg/m3. We estimated an odds ratio of 1.038 (95% confidence interval (CI): 1.003-1.074), 1.038 (1.013-1.063) and 1.057 (1.023-1.097) for MI mortality associated with per interquartile range (IQR) increase in the 3-day moving-average exposure to PM2.5 (IQR = 76.3 µg/m3), EC (4.1 µg/m3) and OC (9.1 µg/m3), respectively. We did not identify significant association between MI death and exposure to water-soluble ions (SO42-, NH4+ and NO3-). Likelihood ratio tests supported no evident violations of linear assumptions for constituents-MI associations. Subgroup analyses showed stronger associations between MI death and EC/OC exposure in the elderly, males and cold months. Short-term exposure to PM2.5 constituents, particularly those carbonaceous aerosols, was associated with increased risks of MI mortality.
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Affiliation(s)
- Shaocai Mo
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University of Science and Technology, Wuhan 430065, China
| | - Jianlin Hu
- Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Nanjing University of Information Science & Technology, Nanjing 210044, China
| | - Chuanhua Yu
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University, Wuhan 430071, China
| | - Junzhe Bao
- Department of Epidemiology and Biostatistics, School of Public Health, Zhengzhou University, Zhengzhou 450001, China
| | - Zhihao Shi
- Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Nanjing University of Information Science & Technology, Nanjing 210044, China
| | - Peixuan Zhou
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University of Science and Technology, Wuhan 430065, China
| | - Zhiming Yang
- School of Economics and Management, University of Science and Technology Beijing, Beijing 100083, China
| | - Siqi Luo
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University of Science and Technology, Wuhan 430065, China
| | - Zhouxin Yin
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University of Science and Technology, Wuhan 430065, China
| | - Yunquan Zhang
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University of Science and Technology, Wuhan 430065, China; Hubei Province Key Laboratory of Occupational Hazard Identification and Control, Wuhan University of Science and Technology, Wuhan 430065, China.
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9
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Wang S, Zhao G, Zhang C, Kang N, Liao W, Wang C, Xie F. Association of Fine Particulate Matter Constituents with the Predicted 10-Year Atherosclerotic Cardiovascular Disease Risk: Evidence from a Large-Scale Cross-Sectional Study. TOXICS 2023; 11:812. [PMID: 37888663 PMCID: PMC10611010 DOI: 10.3390/toxics11100812] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/02/2023] [Revised: 09/22/2023] [Accepted: 09/24/2023] [Indexed: 10/28/2023]
Abstract
Little is known concerning the associations of fine particulate matter (PM2.5) and its constituents with atherosclerotic cardiovascular disease (ASCVD). A total of 31,162 participants enrolled from the Henan Rural Cohort were used to specify associations of PM2.5 and its constituents with ASCVD. Hybrid machine learning was utilized to estimate the 3-year average concentration of PM2.5 and its constituents (black carbon [BC], nitrate [NO3-], ammonium [NH4+], inorganic sulfate [SO42-], organic matter [OM], and soil particles [SOIL]). Constituent concentration, proportion, and residual models were utilized to examine the associations of PM2.5 constituents with 10-year ASCVD risk and to identify the most hazardous constituent. The isochronous substitution model (ISM) was employed to analyze the substitution effect between PM2.5 constituents. We found that each 1 μg/m3 increase in PM2.5, BC, NH4+, NO3-, OM, SO42-, and SOIL was associated with a 3.5%, 49.3%, 19.4%, 10.5%, 21.4%, 14%, and 28.5% higher 10-year ASCVD risk, respectively (all p < 0.05). Comparable results were observed in proportion and residual models. The ISM found that replacing BC with other constituents will generate the greatest health benefits. The results indicated that long-term exposure to PM2.5 and its constituents were associated with increased risks of ASCVD, with BC being the most attributable constituent.
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Affiliation(s)
- Sheng Wang
- Key Laboratory of Tobacco Chemistry, Zhengzhou Tobacco Research Institute of CNTC, Zhengzhou 450003, China; (S.W.); (G.Z.)
| | - Ge Zhao
- Key Laboratory of Tobacco Chemistry, Zhengzhou Tobacco Research Institute of CNTC, Zhengzhou 450003, China; (S.W.); (G.Z.)
| | - Caiyun Zhang
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou 450001, China; (C.Z.); (N.K.); (W.L.)
| | - Ning Kang
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou 450001, China; (C.Z.); (N.K.); (W.L.)
| | - Wei Liao
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou 450001, China; (C.Z.); (N.K.); (W.L.)
| | - Chongjian Wang
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou 450001, China; (C.Z.); (N.K.); (W.L.)
| | - Fuwei Xie
- Key Laboratory of Tobacco Chemistry, Zhengzhou Tobacco Research Institute of CNTC, Zhengzhou 450003, China; (S.W.); (G.Z.)
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10
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Li J, Tang W, Li S, He C, Dai Y, Feng S, Zeng C, Yang T, Meng Q, Meng J, Pan Y, Deji S, Zhang J, Xie L, Guo B, Lin H, Zhao X. Ambient PM2.5 and its components associated with 10-year atherosclerotic cardiovascular disease risk in Chinese adults. ECOTOXICOLOGY AND ENVIRONMENTAL SAFETY 2023; 263:115371. [PMID: 37643506 DOI: 10.1016/j.ecoenv.2023.115371] [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: 05/06/2023] [Revised: 08/11/2023] [Accepted: 08/12/2023] [Indexed: 08/31/2023]
Abstract
BACKGROUND Exposure to particulate matter with aerodynamic diameters less than 2.5 µm (PM2.5) may increase the risk of 10-year atherosclerotic cardiovascular disease (ASCVD) risk. While PM2.5 is comprised of various components, the evidence on the correlation of its components with 10-year ASCVD risk and which component contributes most remains limited. METHODS Data were derived from the baseline assessments of China Multi-Ethnic Cohort (CMEC). In total, 69,722 individuals aged 35-74 years were included into this study. The annual average concentration of PM2.5 and its components (black carbon, ammonium, nitrate, sulfate, organic matter, soil particles, and sea salt) were estimated by satellite remote sensing and chemical transport models. The ASCVD risk of individuals was calculated by the equations from the China-PAR Project (prediction for ASCVD risk in China). The relationship between single exposure to PM2.5 and its components and predicted 10-year ASCVD risk was assessed using the logistic regression model. The effect of joint exposure was estimated, and the most significant contributor was identified using the weighted quantile sum approach. RESULTS Totally 69,722 participants were included, of which 95.8 % and 4.2 % had low and high 10-year ASCVD risk, respectively. Per standard deviation increases in the 3-year average concentration of PM2.5 mass (odds ratio [OR] 1.23, 95 % confidence interval [CI]: 1.12-1.35), black carbon (1.21, 1.11-1.33), ammonium (1.21, 1.10-1.32), nitrate (1.25, 1.14-1.38), organic matter (1.29, 1.18-1.42), sulfate (1.17, 1.07-1.28), and soil particles (1.15, 1.04-1.26) were related to high 10-year ASCVD risk. The overall effect (1.19, 1.11-1.28) of the PM2.5 components was positively associated with 10-year ASCVD risk, and organic matter had the most contribution to this relationship. Female participants were more significantly impacted by PM2.5, black carbon, ammonium, nitrate, organic matter, sulfate, and soil particles compared to others. CONCLUSION Long-term exposure to PM2.5 mass, black carbon, ammonium, nitrate, organic matter, sulfate, and soil particles were positively associated with high 10-year ASCVD risk, while sea salt exhibited a protective effect. Moreover, the organic matter might take primary responsibility for the relationship between PM2.5 and 10-year ASCVD risk. Females were more susceptible to the adverse effect.
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Affiliation(s)
- Jiawei Li
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan 610041, China
| | - Wenge Tang
- Chongqing Center for Disease Control and Prevention, Chongqing 400042, China
| | - Sicheng Li
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan 610041, China
| | - Congyuan He
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan 610041, China
| | - Yucen Dai
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan 610041, China
| | - Shiyu Feng
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan 610041, China
| | - Chunmei Zeng
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan 610041, China
| | - Tingting Yang
- School of Public Health, the Key Laboratory of Environmental Pollution Monitoring and Disease Control, Ministry of Education, Guizhou Medical University, Guiyang 550025, China
| | - Qiong Meng
- Department of Epidemiology and Health Statistics, School of Public Health, Kunming Medical University, Kunming, Yunnan 850000, China
| | - Jiantong Meng
- Chengdu Center for Disease Control & Prevention, Chengdu, Sichuan 610041, China
| | | | - Suolang Deji
- Tibet Center for Disease Control and Prevention CN, Lhasa 850000, China
| | - Juying Zhang
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan 610041, China
| | - Linshen Xie
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan 610041, China.
| | - Bing Guo
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan 610041, China.
| | - Hualiang Lin
- Department of Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou, Guangdong 510080, China
| | - Xing Zhao
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan 610041, China
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11
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Huang K, Yu D, Fang H, Ju L, Piao W, Guo Q, Xu X, Wei X, Yang Y, Zhao L. Association of fine particulate matter and its constituents with hypertension: the modifying effect of dietary patterns. Environ Health 2023; 22:55. [PMID: 37553681 PMCID: PMC10411005 DOI: 10.1186/s12940-023-01000-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2023] [Accepted: 06/19/2023] [Indexed: 08/10/2023]
Abstract
BACKGROUND Studies have shown that nutritional supplements could reduce the adverse effects induced by air pollution. However, whether dietary patterns can modify the association of long-term exposure to fine particulate matter (PM2.5) and its constituents with hypertension defined by the 2017 ACC/AHA guideline has not been evaluated. METHODS We included 47,501 Chinese adults from a nationwide cross-sectional study. PM2.5 and five constituents were estimated by satellite-based random forest models. Dietary approaches to stop hypertension (DASH) and alternative Mediterranean diet (AMED) scores were calculated for each participant. Interactions between dietary patterns and air pollution were examined by adding a multiplicative interaction term to logistic models. RESULTS Long-term exposure to PM2.5 and its constituents was associated with an increased risk of hypertension and stage 1-2 hypertension. The DASH and AMED scores significantly modified these associations, as individuals with higher scores had a significantly lower risk of air pollution-related hypertension and stage 1-2 hypertension (P-interaction < 0.05), except for interaction between PM2.5, sulfate, nitrate, ammonium, and AMED score on stage 1 hypertension. For each IQR increase in PM2.5, participants with the lowest DASH and AMED quintiles had hypertension risk with ORs (95%CI) of 1.20 (1.10, 1.30) and 1.19 (1.09, 1.29), whereas those with the highest DASH and AMED quintiles had lower risks with 0.98 (0.91, 1.05) and 1.04 (0.97, 1.11). The stratified analysis found modification effect was more prominent in the < 65 years age group. Consuming more fresh vegetables, fruits, whole grains, and dairy would reduce the risk of hypertension caused by PM2.5 and its constituents. CONCLUSIONS Dietary patterns rich in antioxidants can reduce long-term exposure to PM2.5 and its constituents-induced hypertension defined by the 2017 ACC/AHA guideline, especially in young and middle-aged individuals. Compared to the Mediterranean diet, the DASH diet offers superior dietary guidance to prevent stage 1 hypertension caused by air pollution.
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Affiliation(s)
- Kun Huang
- National Institute of Nutrition and Health, Chinese Center for Disease Control and Prevention, 27 Nanwei Road, Xicheng District, Beijing, 100050, China
| | - Dongmei Yu
- National Institute of Nutrition and Health, Chinese Center for Disease Control and Prevention, 27 Nanwei Road, Xicheng District, Beijing, 100050, China
- NHC Key Laboratory of Trace Element Nutrition, National Institute for Nutrition and Health, Chinese Center for Disease Control and Prevention, Beijing, 100050, China
| | - Hongyun Fang
- National Institute of Nutrition and Health, Chinese Center for Disease Control and Prevention, 27 Nanwei Road, Xicheng District, Beijing, 100050, China
- NHC Key Laboratory of Trace Element Nutrition, National Institute for Nutrition and Health, Chinese Center for Disease Control and Prevention, Beijing, 100050, China
| | - Lahong Ju
- National Institute of Nutrition and Health, Chinese Center for Disease Control and Prevention, 27 Nanwei Road, Xicheng District, Beijing, 100050, China
| | - Wei Piao
- National Institute of Nutrition and Health, Chinese Center for Disease Control and Prevention, 27 Nanwei Road, Xicheng District, Beijing, 100050, China
- NHC Key Laboratory of Trace Element Nutrition, National Institute for Nutrition and Health, Chinese Center for Disease Control and Prevention, Beijing, 100050, China
| | - Qiya Guo
- National Institute of Nutrition and Health, Chinese Center for Disease Control and Prevention, 27 Nanwei Road, Xicheng District, Beijing, 100050, China
| | - Xiaoli Xu
- National Institute of Nutrition and Health, Chinese Center for Disease Control and Prevention, 27 Nanwei Road, Xicheng District, Beijing, 100050, China
| | - Xiaoqi Wei
- National Institute of Nutrition and Health, Chinese Center for Disease Control and Prevention, 27 Nanwei Road, Xicheng District, Beijing, 100050, China
| | - Yuxiang Yang
- National Institute of Nutrition and Health, Chinese Center for Disease Control and Prevention, 27 Nanwei Road, Xicheng District, Beijing, 100050, China
| | - Liyun Zhao
- National Institute of Nutrition and Health, Chinese Center for Disease Control and Prevention, 27 Nanwei Road, Xicheng District, Beijing, 100050, China.
- NHC Key Laboratory of Trace Element Nutrition, National Institute for Nutrition and Health, Chinese Center for Disease Control and Prevention, Beijing, 100050, China.
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12
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Lv S, Shi Y, Xue Y, Hu Y, Hu M, Li S, Xie W, Li Y, Ouyang Y, Li Z, Liu M, Wei J, Guo X, Liu X. Long-term effects of particulate matter on incident cardiovascular diseases in middle-aged and elder adults: The CHARLS cohort study. ECOTOXICOLOGY AND ENVIRONMENTAL SAFETY 2023; 262:115181. [PMID: 37393817 DOI: 10.1016/j.ecoenv.2023.115181] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/03/2023] [Revised: 06/07/2023] [Accepted: 06/22/2023] [Indexed: 07/04/2023]
Abstract
BACKGROUND Although there is evidence of long-term effects of particulate matter (PM) on cardiovascular diseases (CVD), researches about long-term effects of PM1 on CVD are limited. We aimed to examine the long-term effects and magnitude of PM, especially PM1, on incident CVD in China. METHODS We included 6016 participants aged ≥ 45 years without CVD at baseline in 2011 from the China Health and Retirement Longitudinal Study. Personal PM (PM1, PM2.5, and PM10) concentrations were estimated using geocoded residential address. Generalized linear mixed models and SHapley Additive exPlanation were utilized to calculate the impacts and contributions of PM on CVD. Sensitivity analyses were used to check the robustness. RESULTS After a follow up of 4-year, 481 (7.99 %) participants developed CVD. Per 10 μg/m3 uptick in 1-year average concentrations of PM1, PM2.5 and PM10 was associated with a 1.20 [95 % confidence interval (CI): 1.05-1.37], 1.13 (95 % CI: 1.11-1.15), and 1.10 (95 % CI: 1.06-1.13) fold risk of incident CVD, respectively. The 2-year average concentrations of PM1, PM2.5 and PM10 were associated with incident CVD, corresponding to a 1.03 (95 % CI: 0.96-1.10), 1.11 (95 % CI: 1.02-1.21), and 1.09 (95 % CI: 1.03-1.15) fold risk, respectively. The SHapley Additive exPlanation values of PM1, PM2.5, and PM10 were 0.170, 0.153, and 0.053, respectively, corresponding to the first, second, and fifth among all air pollutants. Effects of PM1, PM2.5 and PM10 on CVD remained statistically significant in two-pollutant models. The elderly, males, smokers and alcohol drinkers tended to have slightly higher effects, while the differences were not statistically significant (all P-values > 0.05) between subgroups. CONCLUSION Long-term exposure to PM1, PM2.5, and PM10 was associated with an increased incidence of CVD. The smaller the particle size, the more important it was for incident CVD indicating that emphasis should be placed on small size of PM.
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Affiliation(s)
- Shiyun Lv
- School of Public Health, Capital Medical University, Beijing 100069, China; Beijing Municipal Key Laboratory of Clinical Epidemiology, Beijing 100069, China
| | - Yadi Shi
- School of Public Health, Capital Medical University, Beijing 100069, China
| | - Yongxi Xue
- School of Public Health, Capital Medical University, Beijing 100069, China
| | - Yaoyu Hu
- School of Public Health, Capital Medical University, Beijing 100069, China
| | - Meiling Hu
- School of Public Health, Capital Medical University, Beijing 100069, China
| | - Shuting Li
- School of Public Health, Capital Medical University, Beijing 100069, China
| | - Wenhan Xie
- School of Public Health, Capital Medical University, Beijing 100069, China
| | - Yuan Li
- School of Public Health, Capital Medical University, Beijing 100069, China
| | - Yixin Ouyang
- School of Public Health, Capital Medical University, Beijing 100069, China
| | - Zhiwei Li
- School of Public Health, Capital Medical University, Beijing 100069, China; Beijing Municipal Key Laboratory of Clinical Epidemiology, Beijing 100069, China
| | - Mengmeng Liu
- School of Public Health, Capital Medical University, Beijing 100069, China; Beijing Municipal Key Laboratory of Clinical Epidemiology, Beijing 100069, China; National Institute for Data Science in Health and Medicine, Capital Medical University, Beijing 100069, China
| | - Jing Wei
- Department of Atmospheric and Oceanic Science, Earth System Science Interdisciplinary Center, University of Maryland, College Park, Maryland 20742, USA
| | - Xiuhua Guo
- School of Public Health, Capital Medical University, Beijing 100069, China; Beijing Municipal Key Laboratory of Clinical Epidemiology, Beijing 100069, China; National Institute for Data Science in Health and Medicine, Capital Medical University, Beijing 100069, China.
| | - Xiangtong Liu
- School of Public Health, Capital Medical University, Beijing 100069, China; Beijing Municipal Key Laboratory of Clinical Epidemiology, Beijing 100069, China.
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13
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Lin W, Lin K, Du L, Du J. Can regional joint prevention and control of atmospheric reduce border pollution? Evidence from China's 12th Five-Year Plan on air pollution. JOURNAL OF ENVIRONMENTAL MANAGEMENT 2023; 342:118342. [PMID: 37302171 DOI: 10.1016/j.jenvman.2023.118342] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/09/2023] [Revised: 06/03/2023] [Accepted: 06/05/2023] [Indexed: 06/13/2023]
Abstract
Border pollution is usually a difficult problem in environmental governance. Based on the data at the county level in China from 2005 to 2019, this study takes the 12th Five-Year Plan (FYP) for atmospheric pollution as a policy shock, and uses the difference-in-differences (DID) method to explore the impact of regional joint prevention and control (JPC) of atmospheric pollution policy on air pollution of the border regions. Empirical results show that: (1) After implementing the JPC of atmospheric pollution policy, the PM2.5 concentration in the border regions is reduced by 3.5%. (2) The mechanism analysis shows that there is a spillover effect in the governing behaviors of local governments. In the border areas under low economic growth pressure and high environmental protection pressure, the reduction effect of the JPC of atmospheric pollution policy is more significant on the PM2.5 concentration of the border regions. The research conclusions have new insights into the role and effect of macro-regional environmental JPC policy and border pollution control, and provide practical guidance for social green governance.
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Affiliation(s)
- Weifen Lin
- School of Urban and Regional Sciences, Shanghai University of Finance and Economics, Shanghai, 200433, China
| | - Kai Lin
- Business School, Shandong Normal University, Jinan, 250358, China
| | - Longzheng Du
- Institute of Digital Economy and Green Development, Zhejiang International Studies University, Hangzhou, 310023, China.
| | - Jianhang Du
- Business Management Department, University of Finance and Economics Mongolia, Ulaanbaatar, 13381, Mongolia.
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14
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Ren Y, Feng Y, Wang Q, Qu P, Luo S, Huang D, Chen L, Zhao L, Liang X. Analysis of dietary patterns on cardiovascular risks in children: from a cross-sectional and a longitudinal study. Public Health 2023; 220:35-42. [PMID: 37263176 DOI: 10.1016/j.puhe.2023.04.018] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2022] [Revised: 03/17/2023] [Accepted: 04/25/2023] [Indexed: 06/03/2023]
Abstract
OBJECTIVES Diet is one of the main risk factors for cardiovascular disease (CVD), while the evidence about the relationship between dietary pattern (DP) and CVD in children is scarce. This study aims to explore the association between DP and CVD risk in children. STUDY DESIGN This was a cross-sectional and longitudinal study. METHODS This research was conducted among 4351 children aged 6-12 years old in 2014, then the subgroup children in 2014 were followed up in 2019. Dietary intakes were assessed using a food frequency questionnaire. DP was clustered based on 15 food items, and finally, four main DPs were obtained. RESULTS Four major DPs were identified: (1) low intake of nuts and algae pattern, (2) low-energy intake pattern, (3) high-energy intake pattern, and (4) regular DP. Compared with the regular diet pattern, the low intake of nuts and algae pattern was associated with the increased risk of higher systolic blood pressure (107.71 mm Hg vs 105.78 mm Hg, P < 0.001), diastolic blood pressure (64.98 mm Hg vs 63.91 mm Hg, P = 0.0056), hypertension (odds ratio [OR]:1.44, 95% confidence interval [CI]: 1.10, 1.88; P = 0.0036), dyslipidemia (OR: 2.41, 95% CI: 1.28, 4.52; P = 0.0194), and obesity (OR: 1.48, 95% CI: 1.16, 1.89; P = 0.0003) in children from a cross-sectional aspect in 2014 and it was also found associated with an increased risk of hypertension (OR: 2.67, 95% CI: 1.45, 4.92; P = 0.0017) in 2019. CONCLUSIONS Low nuts and algae intake combinations in children seemed associated with increased CVD risk. Such findings are imperative for national development of dietary recommendation for the prevention of CVDs.
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Affiliation(s)
- Y Ren
- Department of Clinical Epidemiology and Biostatistics, Children's Hospital of Chongqing Medical University, National Clinical Research Center for Child Health and Disorders, Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing Key Laboratory of Child Health and Nutrition, Chongqing, China
| | - Y Feng
- Department of Clinical Epidemiology and Biostatistics, Children's Hospital of Chongqing Medical University, National Clinical Research Center for Child Health and Disorders, Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing Key Laboratory of Child Health and Nutrition, Chongqing, China
| | - Q Wang
- Department of Epidemiology and Biostatistics, Institute of Traumatology and Orthopaedics, Beijing Jishuitan Hospital, Beijing, China
| | - P Qu
- Department of Clinical Epidemiology and Biostatistics, Children's Hospital of Chongqing Medical University, National Clinical Research Center for Child Health and Disorders, Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing Key Laboratory of Child Health and Nutrition, Chongqing, China
| | - S Luo
- Department of Clinical Epidemiology and Biostatistics, Children's Hospital of Chongqing Medical University, National Clinical Research Center for Child Health and Disorders, Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing Key Laboratory of Child Health and Nutrition, Chongqing, China
| | - D Huang
- Department of Clinical Epidemiology and Biostatistics, Children's Hospital of Chongqing Medical University, National Clinical Research Center for Child Health and Disorders, Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing Key Laboratory of Child Health and Nutrition, Chongqing, China
| | - L Chen
- Department of Clinical Epidemiology and Biostatistics, Children's Hospital of Chongqing Medical University, National Clinical Research Center for Child Health and Disorders, Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing Key Laboratory of Child Health and Nutrition, Chongqing, China
| | - L Zhao
- Department of Clinical Epidemiology and Biostatistics, Children's Hospital of Chongqing Medical University, National Clinical Research Center for Child Health and Disorders, Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing Key Laboratory of Child Health and Nutrition, Chongqing, China
| | - X Liang
- Department of Clinical Epidemiology and Biostatistics, Children's Hospital of Chongqing Medical University, National Clinical Research Center for Child Health and Disorders, Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing Key Laboratory of Child Health and Nutrition, Chongqing, China.
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15
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Lv S, Li Z, Li H, Liu M, Wu Z, Yu S, Wu B, Gao B, Tao L, Luo Y, Li X, Guo X, Liu X. Long-term effects of PM 2.5 components on hypertension: A national analysis in China. ENVIRONMENTAL RESEARCH 2023; 222:115323. [PMID: 36681144 DOI: 10.1016/j.envres.2023.115323] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/03/2022] [Revised: 01/08/2023] [Accepted: 01/16/2023] [Indexed: 06/17/2023]
Abstract
BACKGROUND Evidence is less about the associations between fine particulate matter (PM2.5) components and hypertension. We aimed to examine the long-term effects of PM2.5 components on prevalence of hypertension, diastolic blood pressure (DBP) and systolic blood pressure (SBP). METHODS We included participants between March 1, and July 31, 2021, from 13 provinces in China. Geocoded residential address was used for exposure assignment. Mixed-effect regression was used to assess 3-year average concentrations of PM2.5 and its components (black carbon, organic matter, nitrate, ammonium, and sulfate) on prevalence of hypertension, DBP and SBP with covariate-adjusted. SHapley Additive exPlanation was used to compare the contribution of PM2.5 components to hypertension, DBP, and SBP. Sex and age subgroup were also analyzed. RESULTS We enrolled a total of 113,159 participants aged ≥18 years. Long-term exposure to PM2.5 and its components (black carbon, organic matter, nitrate, ammonium, and sulfate) had associations with prevalence of hypertension, with the Odds Ratios and 95% confidence interval (CI) of 1.06 (95%CI: 1.03-1.09), 1.07 (95%CI: 1.04-1.09), 1.07 (95%CI: 1.04-1.10), 1.05 (95%CI: 1.01-1.08), 1.03 (95%CI: 1.00-1.06), and 1.03 (95%CI: 1.00-1.04), respectively. Effects of that except for black carbon on DBP with per interquartile upticks of concentration were 0.23 (95%CI: 0.11-0.35), 0.17 (95%CI: 0.04-0.29), 0.35 (95%CI: 0.21-0.48), 0.40 (95%CI: 0.28-0.52), and 0.25 (95%CI: 0.13-0.26), respectively. Ammonium was associated with SBP, corresponding to an increase of 0.18 (95%CI: 0.01-0.35). Males had higher risks of DBP (Z = 2.54-6.08, P < 0.001). Older people were substantially more affected by PM2.5 and its components. Nitrate showed the highest contribution to hypertension, DBP and SBP compared with other components. CONCLUSIONS Long-term exposure to PM2.5 and its components had adverse consequences on prevalence of hypertension, DBP and SBP, especially for males and older people. Nitrate contributed the highest to hypertension, DBP and SBP. Findings may have implications for pollution and hypertension control.
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Affiliation(s)
- Shiyun Lv
- School of Public Health, Capital Medical University, Beijing, China; Beijing Municipal Key Laboratory of Clinical Epidemiology, Beijing, China
| | - Zhiwei Li
- School of Public Health, Capital Medical University, Beijing, China; Beijing Municipal Key Laboratory of Clinical Epidemiology, Beijing, China
| | - Haibin Li
- Beijing Chaoyang Hospital, Capital Medical University, Beijing, China
| | - Mengmeng Liu
- School of Public Health, Capital Medical University, Beijing, China; Beijing Municipal Key Laboratory of Clinical Epidemiology, Beijing, China; National Institute for Data Science in Health and Medicine, Capital Medical University, Beijing, China
| | - Zhiyuan Wu
- School of Public Health, Capital Medical University, Beijing, China; Beijing Municipal Key Laboratory of Clinical Epidemiology, Beijing, China
| | - Siqi Yu
- School of Public Health, Capital Medical University, Beijing, China; Beijing Municipal Key Laboratory of Clinical Epidemiology, Beijing, China
| | - Binqiang Wu
- School of Public Health, Capital Medical University, Beijing, China
| | - Bo Gao
- School of Public Health, Capital Medical University, Beijing, China; Beijing Municipal Key Laboratory of Clinical Epidemiology, Beijing, China
| | - Lixin Tao
- School of Public Health, Capital Medical University, Beijing, China; Beijing Municipal Key Laboratory of Clinical Epidemiology, Beijing, China
| | - Yanxia Luo
- School of Public Health, Capital Medical University, Beijing, China; Beijing Municipal Key Laboratory of Clinical Epidemiology, Beijing, China
| | - Xia Li
- Department of Mathematics and Statistics, La Trobe University, Melbourne, Australia
| | - Xiuhua Guo
- School of Public Health, Capital Medical University, Beijing, China; Beijing Municipal Key Laboratory of Clinical Epidemiology, Beijing, China; National Institute for Data Science in Health and Medicine, Capital Medical University, Beijing, China.
| | - Xiangtong Liu
- School of Public Health, Capital Medical University, Beijing, China; Beijing Municipal Key Laboratory of Clinical Epidemiology, Beijing, China.
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16
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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. THE SCIENCE OF THE TOTAL ENVIRONMENT 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] [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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Li T, Zhang Y, Jiang N, Du H, Chen C, Wang J, Li Q, Feng D, Shi X. Ambient fine particulate matter and cardiopulmonary health risks in China. Chin Med J (Engl) 2023; 136:287-294. [PMID: 36780425 PMCID: PMC10106175 DOI: 10.1097/cm9.0000000000002218] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2022] [Indexed: 02/15/2023] Open
Abstract
ABSTRACT In China, the level of ambient fine particulate matter (PM 2.5 ) pollution far exceeds the air quality standards recommended by the World Health Organization. Moreover, the health effects of PM 2.5 exposure have become a major public health issue. More than half of PM 2.5 -related excess deaths are caused by cardiopulmonary disease, which has become a major health risk associated with PM 2.5 pollution. In this review, we discussed the latest epidemiological advances relating to the health effects of PM 2.5 on cardiopulmonary diseases in China, including studies relating to the effects of PM 2.5 on mortality, morbidity, and risk factors for cardiovascular and respiratory diseases. These data provided important evidence to highlight the cardiopulmonary risk associated with PM 2.5 across the world. In the future, further studies need to be carried out to investigate the specific relationship between the constituents and sources of PM 2.5 and cardiopulmonary disease. These studies provided scientific evidence for precise reduction measurement of pollution sources and public health risks. It is also necessary to identify effective biomarkers and elucidate the biological mechanisms and pathways involved; this may help us to take steps to reduce PM 2.5 pollution and reduce the incidence of cardiopulmonary disease.
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Affiliation(s)
- Tiantian Li
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
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18
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Nagrani R, Marron M, Bongaerts E, Nawrot TS, Ameloot M, de Hoogh K, Vienneau D, Lequy E, Jacquemin B, Guenther K, De Ruyter T, Mehlig K, Molnár D, Moreno LA, Russo P, Veidebaum T, Ahrens W, Buck C. Association of urinary and ambient black carbon, and other ambient air pollutants with risk of prediabetes and metabolic syndrome in children and adolescents. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2023; 317:120773. [PMID: 36455765 DOI: 10.1016/j.envpol.2022.120773] [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: 08/17/2022] [Revised: 11/10/2022] [Accepted: 11/26/2022] [Indexed: 06/17/2023]
Abstract
The effects of exposure to black carbon (BC) on various diseases remains unclear, one reason being potential exposure misclassification following modelling of ambient air pollution levels. Urinary BC particles may be a more precise measure to analyze the health effects of BC. We aimed to assess the risk of prediabetes and metabolic syndrome (MetS) in relation to urinary BC particles and ambient BC and to compare their associations in 5453 children from IDEFICS/I. Family cohort. We determined the amount of BC particles in urine using label-free white-light generation under femtosecond pulsed laser illumination. We assessed annual exposure to ambient air pollutants (BC, PM2.5 and NO2) at the place of residence using land use regression models for Europe, and we calculated the residential distance to major roads (≤250 m vs. more). We analyzed the cross-sectional relationships between urinary BC and air pollutants (BC, PM2.5 and NO2) and distance to roads, and the associations of all these variables to the risk of prediabetes and MetS, using logistic and linear regression models. Though we did not observe associations between urinary and ambient BC in overall analysis, we observed a positive association between urinary and ambient BC levels in boys and in children living ≤250 m to a major road compared to those living >250 m away from a major road. We observed a positive association between log-transformed urinary BC particles and MetS (ORper unit increase = 1.72, 95% CI = 1.21; 2.45). An association between ambient BC and MetS was only observed in children living closer to a major road. Our findings suggest that exposure to BC (ambient and biomarker) may contribute to the risk of MetS in children. By measuring the internal dose, the BC particles in urine may have additionally captured non-residential sources and reduced exposure misclassification. Larger studies, with longitudinal design including measurement of urinary BC at multiple time-points are warranted to confirm our findings.
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Affiliation(s)
- Rajini Nagrani
- Leibniz Institute for Prevention Research and Epidemiology - BIPS, Bremen, Germany.
| | - Manuela Marron
- Leibniz Institute for Prevention Research and Epidemiology - BIPS, Bremen, Germany
| | - Eva Bongaerts
- Centre for Environmental Sciences, Hasselt University, Hasselt, Belgium
| | - Tim S Nawrot
- Centre for Environmental Sciences, Hasselt University, Hasselt, Belgium; Department of Public Health and Primary Care, KU Leuven, Leuven, Belgium
| | - Marcel Ameloot
- Biomedical Research Institute, Hasselt University, Hasselt, Belgium
| | - Kees de Hoogh
- Swiss Tropical and Public Health Institute, Kreuzenstrasse 2, 4123 Allschwil, Switzerland; University of Basel, Petersplatz 1, 4001 Basel, Switzerland
| | - Danielle Vienneau
- Swiss Tropical and Public Health Institute, Kreuzenstrasse 2, 4123 Allschwil, Switzerland; University of Basel, Petersplatz 1, 4001 Basel, Switzerland
| | - Emeline Lequy
- Unité "Cohortes en Population" UMS 011 Inserm/Université Paris-Cité/Université Paris Saclay/UVSQ Villejuif, France
| | - Bénédicte Jacquemin
- Univ Rennes, Inserm, EHESP, Irset (Institut de Recherché en Santé, Environnement et Travail) - UMR_S 1085,Rennes, France
| | - Kathrin Guenther
- Leibniz Institute for Prevention Research and Epidemiology - BIPS, Bremen, Germany
| | - Thaïs De Ruyter
- Centre for Environmental Sciences, Hasselt University, Hasselt, Belgium; Department of Public Health and Primary Care, Ghent University, 9000, Ghent, Belgium
| | - Kirsten Mehlig
- School of Public Health and Community Medicine, Institute of Medicine, University of Gothenburg, Gothenburg, Sweden
| | - Dénes Molnár
- Department of Paediatrics, Medical School, University of Pécs, Pécs, Hungary
| | - Luis A Moreno
- GENUD (Growth, Exercise, Nutrition and Development) Research Group, University of Zaragoza, Instituto Agroalimentario de Aragón (IA2), Instituto de Investigación Sanitaria de Aragón (IIS Aragón) Zaragoza, Spain and Centro de Investigación Biomédica en Red de Fisiopatología de La Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III, Madrid, Spain
| | - Paola Russo
- Institute of Food Sciences, National Research Council, Avellino, Italy
| | | | - Wolfgang Ahrens
- Leibniz Institute for Prevention Research and Epidemiology - BIPS, Bremen, Germany; Institute of Statistics, Faculty of Mathematics and Computer Science, Bremen University, Bremen, Germany
| | - Christoph Buck
- Leibniz Institute for Prevention Research and Epidemiology - BIPS, Bremen, Germany
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Liu C, Cao G, Li J, Lian S, Zhao K, Zhong Y, Xu J, Chen Y, Bai J, Feng H, He G, Dong X, Yang P, Zeng F, Lin Z, Zhu S, Zhong X, Ma W, Liu T. Effect of long-term exposure to PM 2.5 on the risk of type 2 diabetes and arthritis in type 2 diabetes patients: Evidence from a national cohort in China. ENVIRONMENT INTERNATIONAL 2023; 171:107741. [PMID: 36628860 DOI: 10.1016/j.envint.2023.107741] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/12/2022] [Revised: 12/15/2022] [Accepted: 01/05/2023] [Indexed: 06/17/2023]
Abstract
BACKGROUND It remains unclear whether type 2 diabetes and the complication of arthritis are causally related to the PM2.5 pollutant. Therefore, we aimed to investigate the associations of long-term PM2.5 exposure with type 2 diabetes and with arthritis in type 2 diabetes patients. MATERIALS AND METHODS This study used data from the China Health and Retirement Longitudinal Survey (CHARLS) implemented during 2011-2018. The associations were analyzed by Cox proportional hazards regression models, and the population-attributable fraction (PAF) was calculated to assess the burden of type 2 diabetes and arthritis-attributable to PM2.5. RESULTS A total of 21,075 participants were finally included, with 19,121 analyzed for PM2.5 and type 2 diabetes risk and 12,427 analyzed for PM2.5 and arthritis risk, of which 1,382 with newly-diagnosed type 2 diabetes and 1,328 with arthritis during the follow-up. Overall, each 10 μg/m3 increment in PM2.5 concentration was significantly associated with an increase in the risk of type 2 diabetes (HR = 1.26, 95 %CI1.22 to 1.31), and the PAF of type 2 diabetes attributable to PM2.5 was 13.54 %. In type 2 diabetes patients, each 10 μg/m3 increment in PM2.5 exposure was associated with an increase in arthritis (HR = 1.42, 95 %CI: 1.28 to 1.57), and the association was significantly greater than that (H = 1.23, 95 %CI: 1.19 to 1.28) in adults without type 2 diabetes. The PAFs of arthritis-attributable to PM2.5 in participants with and without type 2 diabetes were 18.54 % and 10.69 %, respectively. CONCLUSION Long-term exposure to PM2.5 may increase the risk of type 2 diabetes and make type 2 diabetes patients susceptible to arthritis.
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Affiliation(s)
- Chaoqun Liu
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou 510080, China; China Greater Bay Area Research Center of Environmental Health, School of Medicine, Jinan University, Guangzhou 510632, China
| | - Ganxiang Cao
- School of Public Health, Guangdong Pharmaceutical University, Guangzhou 510080, China; Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, China
| | - Jieying Li
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou 510080, China; China Greater Bay Area Research Center of Environmental Health, School of Medicine, Jinan University, Guangzhou 510632, China
| | - Shaoyan Lian
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou 510080, China; China Greater Bay Area Research Center of Environmental Health, School of Medicine, Jinan University, Guangzhou 510632, China
| | - Ke Zhao
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou 510080, China; China Greater Bay Area Research Center of Environmental Health, School of Medicine, Jinan University, Guangzhou 510632, China
| | - Ying Zhong
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou 510080, China; China Greater Bay Area Research Center of Environmental Health, School of Medicine, Jinan University, Guangzhou 510632, China
| | - Jiahong Xu
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou 510080, China; China Greater Bay Area Research Center of Environmental Health, School of Medicine, Jinan University, Guangzhou 510632, China
| | - Yumeng Chen
- School of Public Health, Guangdong Pharmaceutical University, Guangzhou 510080, China; Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, China
| | - Jun Bai
- Foshan Women and Children Hospital Affiliated to Southern Medical University, Foshan 528000, China
| | - Hao Feng
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou 510080, China; China Greater Bay Area Research Center of Environmental Health, School of Medicine, Jinan University, Guangzhou 510632, China
| | - Guanhao He
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou 510080, China; China Greater Bay Area Research Center of Environmental Health, School of Medicine, Jinan University, Guangzhou 510632, China
| | - Xiaomei Dong
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou 510080, China; China Greater Bay Area Research Center of Environmental Health, School of Medicine, Jinan University, Guangzhou 510632, China
| | - Pan Yang
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou 510080, China; China Greater Bay Area Research Center of Environmental Health, School of Medicine, Jinan University, Guangzhou 510632, China
| | - Fangfang Zeng
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou 510080, China; China Greater Bay Area Research Center of Environmental Health, School of Medicine, Jinan University, Guangzhou 510632, China
| | - Ziqiang Lin
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou 510080, China; China Greater Bay Area Research Center of Environmental Health, School of Medicine, Jinan University, Guangzhou 510632, China
| | - Sui Zhu
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou 510080, China; China Greater Bay Area Research Center of Environmental Health, School of Medicine, Jinan University, Guangzhou 510632, China
| | - Xinqi Zhong
- Department of Neonatology, The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou 510150, Guangdong, China
| | - Wenjun Ma
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou 510080, China; China Greater Bay Area Research Center of Environmental Health, School of Medicine, Jinan University, Guangzhou 510632, China.
| | - Tao Liu
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou 510080, China; China Greater Bay Area Research Center of Environmental Health, School of Medicine, Jinan University, Guangzhou 510632, China.
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20
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Shi W, Chen C, Cui Q, Deng F, Yang B, Cao Y, Zhao F, Zhang Y, Du P, Wang J, Li T, Tang S, Shi X. Sleep disturbance exacerbates the cardiac conduction abnormalities induced by persistent heavy ambient fine particulate matter pollution: A multi-center cross-sectional study. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 838:156472. [PMID: 35660605 DOI: 10.1016/j.scitotenv.2022.156472] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/14/2022] [Revised: 05/30/2022] [Accepted: 05/31/2022] [Indexed: 06/15/2023]
Abstract
Fine particulate matter (PM2.5) exposure and sleep disturbance have been significantly associated with adverse cardiovascular outcomes, however, the combined effects of these two factors are still unclear. We conducted a multi-center cross-sectional study from November 2018 to May 2019 in the Beijing-Tianjin-Hebei region in China to investigate the potential modifying effects of sleep disturbance on associations between cardiac conduction abnormalities and PM2.5 exposure, as well as the combined effects of sleep disturbance and heavy pollution episodes, which were defined based on the PM2.5 mass concentration (≥75 μg/m3, falling in the 75th/90th percentile) and duration (1 day and ≥2 days). The sleep quality and sleep duration of all participants were evaluated using the Pittsburgh Sleep Quality Index. Standard 12-lead electrocardiogram (ECG) test was performed to measure the heart rate (HR), QRS duration (time taken for ventricular depolarization), HR corrected QT interval (time for ventricular depolarization and repolarization) and PR interval (time for atrioventricular conduction). Multivariable linear regression models were performed to evaluate the associations of PM2.5 and heavy pollution events on ECG parameters and the joint effects with sleep disturbance. We found PM2.5 exposure was independently associated with prolonged QRS and QTc intervals. Association between PM2.5 and the QTc interval was significantly stronger in participants with poor sleep quality. For each 10-μg/m3 increase in PM2.5 concentration, the QTc interval in the participants with poor sleep quality increased by 0.41 % (95 % confidence interval: 0.19, 0.64). In addition, heavy PM2.5 pollution episodes, especially extremely heavy pollution of long duration, were found to have synergistic effects with sleep disturbance on ECG parameters. Our findings provide evidence that PM2.5 exposure, especially heavy pollution episodes, may increase abnormal cardiac conduction and have a synergistic effect with sleep disturbance. Improving sleep hygiene is crucial to protect the heart health of the general population.
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Affiliation(s)
- Wanying Shi
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Chen Chen
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Qian Cui
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China; School of Ecology and Environment, Inner Mongolia University, Hohhot, China
| | - Fuchang Deng
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Bo Yang
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China; School of Public Health, Baotou Medical College, Inner Mongolia University of Science and Technology, Baotou, China
| | - Yaqiang Cao
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China; Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, China
| | - Feng Zhao
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Yi Zhang
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Peng Du
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Jiaonan Wang
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China; Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, China
| | - Tiantian Li
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China; Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, China
| | - Song Tang
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China; Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, China
| | - Xiaoming Shi
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China; Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, China.
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21
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Jia R, Wei M, Zhang X, Du R, Sun W, Wang L, Song L. Pyroptosis participates in PM 2.5-induced air-blood barrier dysfunction. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2022; 29:60987-60997. [PMID: 35435555 DOI: 10.1007/s11356-022-20098-0] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/17/2022] [Accepted: 04/01/2022] [Indexed: 06/14/2023]
Abstract
Epidemiological studies have shown that particulate matters with diameter less than 2.5 μm (PM2.5) play an important role in inducing and promoting respiratory diseases, but its underlying mechanism remains to be explored. The air-blood barrier, also known as the alveolar-capillary barrier, is the key element of the lung, working as the site of oxygen and carbon dioxide exchange between pulmonary vasculatures. In this study, a mouse PM2.5 exposure model was established, which leads to an induced lung injury and air-blood barrier disruption. Oxidative stress and pyroptosis were observed in this process. After reducing the oxidative stress by N-acetyl-L-cysteine (NAC) treatment, the air-blood barrier function was improved and the effect of PM2.5 was alleviated. The level of pyroptosis and related pathway were also effectively relieved. These results indicate that acute PM2.5 exposure can cause lung injury and the alveolar-capillary barrier disruption by inducing reactive oxygen species (ROS) with the participation of pyroptosis pathway.
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Affiliation(s)
- Ruxue Jia
- College of Medical Laboratory, Dalian Medical University, Dalian, Liaoning Province, People's Republic of China, 116044
- Department of Cardiology, Second Affiliated Hospital of Dalian Medical University, Dalian, Liaoning Province, People's Republic of China, 116023
| | - Min Wei
- College of Medical Laboratory, Dalian Medical University, Dalian, Liaoning Province, People's Republic of China, 116044
| | - Xiao Zhang
- College of Medical Laboratory, Dalian Medical University, Dalian, Liaoning Province, People's Republic of China, 116044
| | - Rui Du
- College of Medical Laboratory, Dalian Medical University, Dalian, Liaoning Province, People's Republic of China, 116044
| | - Wenping Sun
- College of Medical Laboratory, Dalian Medical University, Dalian, Liaoning Province, People's Republic of China, 116044
| | - Lili Wang
- Department of Cardiology, Second Affiliated Hospital of Dalian Medical University, Dalian, Liaoning Province, People's Republic of China, 116023
| | - Laiyu Song
- College of Medical Laboratory, Dalian Medical University, Dalian, Liaoning Province, People's Republic of China, 116044.
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22
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He J, Hu S, Xu X, Guo P, Niu Y, Zhang J, Zhang R, Chen S, Ma S, Liu F, Li Q, Li C, Zhang L, Wu Y, Zhang M, Zhang M. Association of long-term exposure to PM 2.5 in workplace with fasting plasma glucose among asymptomatic adults: A multicenter study in North China. ENVIRONMENT INTERNATIONAL 2022; 166:107353. [PMID: 35749995 DOI: 10.1016/j.envint.2022.107353] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/07/2022] [Revised: 06/08/2022] [Accepted: 06/13/2022] [Indexed: 06/15/2023]
Abstract
BACKGROUND The impacts of long-term high exposure to PM2.5 in workplace on glucose metabolism in asymptomatic working adults (AWAs) have rarely been explored. OBJECTIVES To assess the relationship between long-term exposure to workplace PM2.5 and glucose metabolism in asymptomatic general working adults in heavily polluted regions. METHODS We used the baseline data of the asymptomatic working participants from the Beijing-Tianjin-Hebei Medical Examination Cohort, which recruited adults undergoing medical examinations. A machine learning-based spatial-temporal model was used to estimate daily average PM2.5 concentrations in the participants' workplaces. We assessed the association of long-term PM2.5 concentrations (three years prior to the interview) and fasting plasma glucose (FPG) using generalized linear mixed-effects models (GLMM) with inclusion of potential confounders. Stratified analyses by sex, age, BMI and smoking status, and two pollutant models were further performed. RESULTS A total of 37,619 individuals were interviewed and 28,865 were included in the analyses. The mean FPG was 5.20 (0.96) mmol/L, and the estimated three-year average concentration of PM2.5 exposure was 69.51 (6.92) μg/m3. We detected a significant association of long-term exposure to workplace PM2.5 and FPG, a 10 µg/m3 increase in the long-term workplace PM2.5 exposure was associated with 0.075 (95%CI: 0.050-0.100) mmol/L elevated FPG and 25% (OR = 1.25, 95%CI: 1.05-1.50) elevated odds of abnormal fasting glucose metabolism with control of the potential confounding. The detected association between workplace PM2.5 and FPG metabolism remained significant in males, individuals aged > 44 years, overweight and/or obese people, both smokers and non-smokers, and when NO2, SO2, O3, and CO were included in the model. CONCLUSIONS Long-term exposure to workplace PM2.5 was associated with elevated FPG and/or odds of abnormal glucose metabolism among AWAs. Male, middle-aged, overweight and/or obese AWAs were more susceptible to workplace PM2.5 regardless of smoking status.
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Affiliation(s)
- Jiangshan He
- School of Medicine, Nankai University, Tianjin, China
| | - Songhua Hu
- School of Statistics and Data Science, Nankai University, Tianjin, China.
| | - Ximing Xu
- Big Data Center for Children's Medical Care, Children's Hospital of Chongqing Medical University, National Clinical Research Center for Child Health and Disorders, Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing, China.
| | - Pei Guo
- School of Medicine, Nankai University, Tianjin, China
| | - Yujie Niu
- Hebei Key Laboratory of Environment and Human Health, Shijiazhuang, China; Department of Occupational Health and Environmental Health, Hebei Medical University, Shijiazhuang, China.
| | - Jingbo Zhang
- Beijing Physical Examination Center, Beijing, China
| | - Rong Zhang
- Hebei Key Laboratory of Environment and Human Health, Shijiazhuang, China; Department of Occupational Health and Environmental Health, Hebei Medical University, Shijiazhuang, China.
| | - Shuo Chen
- Beijing Physical Examination Center, Beijing, China.
| | - Shitao Ma
- Hebei Key Laboratory of Environment and Human Health, Shijiazhuang, China; Department of Occupational Health and Environmental Health, Hebei Medical University, Shijiazhuang, China
| | - Feng Liu
- Beijing Physical Examination Center, Beijing, China.
| | - Qiang Li
- Beijing Physical Examination Center, Beijing, China
| | - Chunjun Li
- Tianjin People's Hospital, Tianjin, China
| | - Li Zhang
- Tianjin First Central Hospital, Tianjin, China
| | - Ying Wu
- School of Statistics and Data Science, Nankai University, Tianjin, China.
| | - Mianzhi Zhang
- Dongfang Hospital, Beijing University of Chinese Medicine, Beijing, China.
| | - Minying Zhang
- School of Medicine, Nankai University, Tianjin, China.
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23
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Tian Y, Fang J, Wang F, Luo Z, Zhao F, Zhang Y, Du P, Wang J, Li Y, Shi W, Liu Y, Ding E, Sun Q, Li C, Tang S, Yue X, Shi G, Wang B, Li T, Shen G, Shi X. Linking the Fasting Blood Glucose Level to Short-Term-Exposed Particulate Constituents and Pollution Sources: Results from a Multicenter Cross-Sectional Study in China. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2022; 56:10172-10182. [PMID: 35770491 DOI: 10.1021/acs.est.1c08860] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
Ambient PM2.5 (fine particulate matter with aerodynamic diameters ≤ 2.5 μm) is thought to be associated with the development of diabetes, but few studies traced the effects of PM2.5 components and pollution sources on the change in the fasting blood glucose (FBG). In the present study, we assessed the associations of PM2.5 constituents and their sources with the FBG in a general Chinese population aged over 40 years. Exposure to PM2.5 was positively associated with the FBG level, and each interquartile range (IQR) increase in a lag period of 30 days (18.4 μg/m3) showed the strongest association with an elevated FBG of 0.16 mmol/L (95% confidence interval: 0.04, 0.28). Among various constituents, increases in exposed elemental carbon, organic matter, arsenic, and heavy metals such as silver, cadmium, lead, and zinc were associated with higher FBG, whereas barium and chromium were associated with lower FBG levels. The elevated FBG level was closely associated with the PM2.5 from coal combustion, industrial sources, and vehicle emissions, while the association with secondary sources was statistically insignificant. Improving air quality by tracing back to the pollution sources would help to develop well-directed policies to protect human health.
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Affiliation(s)
- Yanlin Tian
- College of Urban and Environmental Sciences, Laboratory for Earth Surface Processes, Sino-French Institute for Earth System Science, Peking University, Beijing 100871, China
- Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control (AEMPC), Nanjing University of Information Science & Technology, Nanjing 210044, China
| | - Jianlong Fang
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
| | - Feng Wang
- State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control, Tianjin Key Laboratory of Urban Transport Emission Research, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China
| | - Zhihan Luo
- College of Urban and Environmental Sciences, Laboratory for Earth Surface Processes, Sino-French Institute for Earth System Science, Peking University, Beijing 100871, China
| | - Feng Zhao
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
| | - Yi Zhang
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
| | - Peng Du
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
| | - Jiaonan Wang
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
| | - Yawei Li
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
| | - Wanying Shi
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
| | - Yuanyuan Liu
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
| | - Enmin Ding
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
| | - Qinghua Sun
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
| | - Chengcheng Li
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
| | - Song Tang
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
| | - Xu Yue
- Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control (AEMPC), Nanjing University of Information Science & Technology, Nanjing 210044, China
| | - Guoliang Shi
- State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control, Tianjin Key Laboratory of Urban Transport Emission Research, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China
| | - Bin Wang
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
| | - Tiantian Li
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
| | - Guofeng Shen
- College of Urban and Environmental Sciences, Laboratory for Earth Surface Processes, Sino-French Institute for Earth System Science, Peking University, Beijing 100871, China
| | - Xiaoming Shi
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
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Yi W, Zhao F, Pan R, Zhang Y, Xu Z, Song J, Sun Q, Du P, Fang J, Cheng J, Liu Y, Chen C, Lu Y, Li T, Su H, Shi X. Associations of Fine Particulate Matter Constituents with Metabolic Syndrome and the Mediating Role of Apolipoprotein B: A Multicenter Study in Middle-Aged and Elderly Chinese Adults. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2022; 56:10161-10171. [PMID: 35802126 DOI: 10.1021/acs.est.1c08448] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
Fine particulate matter (PM2.5) was reported to be associated with metabolic syndrome (MetS), but how PM2.5 constituents affect MetS and the underlying mediators remains unclear. We aimed to investigate the associations of long-term exposure to 24 kinds of PM2.5 constituents with MetS (defined by five indicators) in middle-aged and elderly adults and to further explore the potential mediating role of apolipoprotein B (ApoB). A multicenter study was conducted by recruiting subjects (n = 2045) in the Beijing-Tianjin-Hebei region from the cohort of Sub-Clinical Outcomes of Polluted Air in China (SCOPA-China Cohort). Relationships among PM2.5 constituents, serum ApoB levels, and MetS were estimated by multiple logistic/linear regression models. Mediation analysis quantified the role of ApoB in "PM2.5 constituents-MetS" associations. Results indicated PM2.5 was significantly related to elevated MetS prevalence. The MetS odds increased after exposure to sulfate (SO42-), calcium ion (Ca2+), magnesium ion (Mg2+), Si, Zn, Ca, Mn, Ba, Cu, As, Cr, Ni, or Se (odds ratios ranged from 1.103 to 3.025 per interquartile range increase in each constituent). PM2.5 and some constituents (SO42-, Ca2+, Mg2+, Ca, and As) were positively related to serum ApoB levels. ApoB mediated 22.10% of the association between PM2.5 and MetS. Besides, ApoB mediated 24.59%, 50.17%, 12.70%, and 9.63% of the associations of SO42-, Ca2+, Ca, and As with MetS, respectively. Our findings suggest that ApoB partially mediates relationships between PM2.5 constituents and MetS risk in China.
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Affiliation(s)
- Weizhuo Yi
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, No. 81 Meishan Road, Shushan District, Hefei, Anhui 230031, China
- Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, No. 81 Meishan Road, Shushan District, Hefei, Anhui 230031, China
| | - Feng Zhao
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, No. 7 Panjiayuan Nanli, Chaoyang District, Beijing 100021, China
| | - Rubing Pan
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, No. 81 Meishan Road, Shushan District, Hefei, Anhui 230031, China
- Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, No. 81 Meishan Road, Shushan District, Hefei, Anhui 230031, China
| | - Yi Zhang
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, No. 7 Panjiayuan Nanli, Chaoyang District, Beijing 100021, China
| | - Zhiwei Xu
- School of Public Health, Faculty of Medicine, University of Queensland, 288 Herston Road, Herston, Brisbane, 4006 Queensland, Australia
| | - Jian Song
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, No. 81 Meishan Road, Shushan District, Hefei, Anhui 230031, China
- Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, No. 81 Meishan Road, Shushan District, Hefei, Anhui 230031, China
| | - Qinghua Sun
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, No. 7 Panjiayuan Nanli, Chaoyang District, Beijing 100021, China
| | - Peng Du
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, No. 7 Panjiayuan Nanli, Chaoyang District, Beijing 100021, China
| | - Jianlong Fang
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, No. 7 Panjiayuan Nanli, Chaoyang District, Beijing 100021, China
| | - Jian Cheng
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, No. 81 Meishan Road, Shushan District, Hefei, Anhui 230031, China
- Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, No. 81 Meishan Road, Shushan District, Hefei, Anhui 230031, China
| | - Yingchun Liu
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, No. 7 Panjiayuan Nanli, Chaoyang District, Beijing 100021, China
| | - Chen Chen
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, No. 7 Panjiayuan Nanli, Chaoyang District, Beijing 100021, China
| | - Yifu Lu
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, No. 7 Panjiayuan Nanli, Chaoyang District, Beijing 100021, China
| | - Tiantian Li
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, No. 7 Panjiayuan Nanli, Chaoyang District, Beijing 100021, China
| | - Hong Su
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, No. 81 Meishan Road, Shushan District, Hefei, Anhui 230031, China
- Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, No. 81 Meishan Road, Shushan District, Hefei, Anhui 230031, China
| | - Xiaoming Shi
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, No. 7 Panjiayuan Nanli, Chaoyang District, Beijing 100021, China
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25
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Chen T, Norback D, Deng Q, Huang C, Qian H, Zhang X, Sun Y, Wang T, Zhang Y, Li B, Kan H, Wei L, Liu C, Xu Y, Zhao Z. Maternal exposure to PM 2.5/BC during pregnancy predisposes children to allergic rhinitis which varies by regions and exclusive breastfeeding. ENVIRONMENT INTERNATIONAL 2022; 165:107315. [PMID: 35635966 DOI: 10.1016/j.envint.2022.107315] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/18/2022] [Revised: 05/02/2022] [Accepted: 05/18/2022] [Indexed: 06/15/2023]
Abstract
BACKGROUND Increasing prevalence of childhood allergic rhinitis(AR) needs a deeper understanding on the potential adverse effects of early life exposure to air pollution. OBJECTIVES The main aim was to evaluate the effects of maternal exposure to PM2.5 and chemical constituents during pregnancy on preschool children's AR, and further to explore the modification effects of regions and exclusive breastfeeding. METHODS A multi-center population-based study was performed in 6 cities from 3 regions of China in 2011-2012. Maternal exposure to ambient PM2.5 and main chemical constituents(BC, OM, SO42-, NO3-, NH4+) during pregnancy was assessed and a longitudinal prospective analysis was applied on preschool children's AR. The modification effects of regions and exclusive breastfeeding were investigated. RESULTS A total of 8.8% and 9.8% of children reported doctor-diagnosed allergic rhinitis(DDAR) and current hay fever, respectively, and 48.6% had less than 6 months of exclusive breastfeeding. The means of PM2.5 during pregnancy were 52.7 μg/m3, 70.3 μg/m3 and 76.4 μg/m3 in the east, north and central south of China, respectively. Multilevel log-binomial model regression showed that each interquartile range(IQR) increase of PM2.5 during pregnancy was associated with an average increase in prevalence ratio (PR) of DDAR by 1.43(95% confidence interval(CI): 1.11, 1.84) and current hay fever by 1.79(95% CI: 1.26, 2.55), respectively. Among chemical constituents, black carbon (BC) had the strongest associations. Across 3 regions, the eastern cities had the highest associations, followed by those in the central south and the north. For those equal to or longer than 6 months of exclusive breastfeeding, the associations were significantly reduced. CONCLUSIONS Children in east of China had the highest risks of developing AR per unit increase of maternal exposure to PM2.5 during pregnancy, especially BC constituent. Remarkable decline was found in association with an increase in breastfeeding for ≥6 months, in particular in east of China.
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Affiliation(s)
- Tianyi Chen
- Department of Environmental Health, School of Public Health, Fudan University, Shanghai 200032, China
| | - Dan Norback
- Department of Medical Sciences, Uppsala University, Uppsala SE-751, Sweden
| | - Qihong Deng
- School of Energy Science and Engineering, Central South University, Changsha 410083, China
| | - Chen Huang
- School of Environment and Architecture, University of Shanghai for Science and Technology, Shanghai 200093, China
| | - Hua Qian
- School of Energy & Environment, Southeast University, Nanjing 210096, China
| | - Xin Zhang
- Research Center for Environmental Science and Engineering, Shanxi University, Taiyuan 030006, China
| | - Yuexia Sun
- Tianjin Key Lab of Indoor Air Environmental Quality Control, Tianjin University, Tianjin 300072, China
| | - Tingting Wang
- School of Nursing & Health Management, Shanghai University of Medicine & Health Sciences, Shanghai 201318, China
| | - Yinping Zhang
- Department of Building Science, Tsinghua University, Beijing 100084, China
| | - Baizhan Li
- Key Laboratory of Three Gorges Reservoir Region's Eco-Environment, Chongqing University, Chongqing 400030, China
| | - Haidong Kan
- Department of Environmental Health, School of Public Health, Fudan University, Shanghai 200032, China; Key Laboratory of Public Health Safety of the Ministry of Education, NHC Key Laboratory of Health Technology Assessment (Fudan University), Shanghai Typhoon Institute/CMA, Shanghai Key Laboratory of Meteorology and Health, Shanghai 200030, China; IRDR International Center of Excellence on Risk Interconnectivity and Governance on Weather/Climate Extremes Impact and Public Health, Fudan University, Shanghai 200438, China; WMO/IGAC MAP-AQ Asian Office Shanghai, Fudan University, Shanghai 200438, China
| | - Lan Wei
- Department of Environmental Health, School of Public Health, Fudan University, Shanghai 200032, China
| | - Cong Liu
- Department of Environmental Health, School of Public Health, Fudan University, Shanghai 200032, China.
| | - Yanyi Xu
- Department of Environmental Health, School of Public Health, Fudan University, Shanghai 200032, China; Key Laboratory of Public Health Safety of the Ministry of Education, NHC Key Laboratory of Health Technology Assessment (Fudan University), Shanghai Typhoon Institute/CMA, Shanghai Key Laboratory of Meteorology and Health, Shanghai 200030, China; IRDR International Center of Excellence on Risk Interconnectivity and Governance on Weather/Climate Extremes Impact and Public Health, Fudan University, Shanghai 200438, China; WMO/IGAC MAP-AQ Asian Office Shanghai, Fudan University, Shanghai 200438, China.
| | - Zhuohui Zhao
- Department of Environmental Health, School of Public Health, Fudan University, Shanghai 200032, China; Key Laboratory of Public Health Safety of the Ministry of Education, NHC Key Laboratory of Health Technology Assessment (Fudan University), Shanghai Typhoon Institute/CMA, Shanghai Key Laboratory of Meteorology and Health, Shanghai 200030, China; IRDR International Center of Excellence on Risk Interconnectivity and Governance on Weather/Climate Extremes Impact and Public Health, Fudan University, Shanghai 200438, China; WMO/IGAC MAP-AQ Asian Office Shanghai, Fudan University, Shanghai 200438, China.
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26
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Lin MC, Wu CF. Transportation, Environmental Degradation, and Health Dynamics in the United States and China: Evidence From Bootstrap ARDL With a Fourier Function. Front Public Health 2022; 10:907390. [PMID: 35844846 PMCID: PMC9277069 DOI: 10.3389/fpubh.2022.907390] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2022] [Accepted: 05/31/2022] [Indexed: 12/03/2022] Open
Abstract
Transportation and environmental degradation, with indirect and direct effects, play a significant role in determining the health of a nation's citizens. This study uses bootstrap ARDL with a Fourier function to examine transportation, environmental degradation, and health dynamics in the United States and China. In the long run, the results support the cointegration relationship between transportation, environmental degradation, and health in both countries. The results show the contingency of the causality where a negative impact of transportation on environmental degradation exists in the United States while a positive impact exists in China. The effect of environmental degradation on health is negative in the United States while a positive effect exists in China. Regarding the causal direction between the variables of interest, the implications provide policymakers in developing strategy and policy for sustainable development.
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Affiliation(s)
- Meng-Chen Lin
- School of Business Administration, Hubei University of Economics, Wuhan, China
| | - Cheng-Feng Wu
- School of Business Administration, Hubei University of Economics, Wuhan, China
- School of Business, Wuchang University of Technology, Wuhan, China
- Research Center of Hubei Logistics Development, Hubei University of Economics, Wuhan, China
- *Correspondence: Cheng-Feng Wu
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27
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Hu J, Li W, Gao Y, Zhao G, Jiang Y, Wang W, Cao M, Zhu Y, Niu Y, Ge J, Chen R. Fine particulate matter air pollution and subclinical cardiovascular outcomes: A longitudinal study in 15 Chinese cities. ENVIRONMENT INTERNATIONAL 2022; 163:107218. [PMID: 35378443 DOI: 10.1016/j.envint.2022.107218] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/05/2021] [Revised: 03/06/2022] [Accepted: 03/25/2022] [Indexed: 06/14/2023]
Abstract
AIMS Although previous studies have linked short-term exposure to fine particulate matter (PM2.5) air pollution with various molecular biomarkers of cardiovascular system, limited evidence is available for indicators at clinical or subclinical levels. We examined the associations between short-term PM2.5 exposure and a range of clinical or subclinical indicators of cardiovascular health in general population. METHODS AND RESULTS A longitudinal repeated-measure study was conducted among 247,640 participants who repeatedly visited health examination centers in 15 typical cities across China from 2013 to 2020. A total of 19 well-established indicators of cardiovascular risk or injury were evaluated and air quality data at nearest fixed-site monitors were collected. Linear mixed-effects models with distributed lag models were used to analyze the potentially lagged effects of PM2.5. The average daily PM2.5 concentration was 48 μg/m3 during the study period. PM2.5 exposure was associated with significant changes of 16 indicators with the effects generally peaked on lag 0 to 3 day. For an interquartile range (IQR) elevation (37 μg/m3) in PM2.5 concentrations over lag 0-7 day, the cumulative percentage changes were 0.50% to 1.27% in heart rates and blood pressure, 0.10% to 5.04% in inflammatory markers, -0.29% to 1.39% in blood viscosity parameters, -0.67% to 3.45% in blood lipids, 0.89% in blood homocysteine, 0.13% to 0.78% in myocardial enzymes, and 3.03% in pulse wave velocity. These associations were not substantially changed after adjusting concomitant exposures to gaseous pollutants. CONCLUSION Short-term exposure to PM2.5 may induce early cardiovascular effects in general population, including acute inflammation, myocardial injury, increased blood viscosity, vascular stiffness and hyperlipidemia.
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Affiliation(s)
- Jialu Hu
- Department of Cardiology, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Wenshu Li
- School of Public Health, Key Lab of Public Health Safety of the Ministry of Education and NHC Key Laboratory of Health Technology Assessment, Fudan University, Shanghai, China
| | - Ya Gao
- School of Public Health, Key Lab of Public Health Safety of the Ministry of Education and NHC Key Laboratory of Health Technology Assessment, Fudan University, Shanghai, China
| | - Gang Zhao
- Department of Cardiology, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Yixuan Jiang
- School of Public Health, Key Lab of Public Health Safety of the Ministry of Education and NHC Key Laboratory of Health Technology Assessment, Fudan University, Shanghai, China
| | - Weidong Wang
- School of Public Health, Key Lab of Public Health Safety of the Ministry of Education and NHC Key Laboratory of Health Technology Assessment, Fudan University, Shanghai, China
| | - Mengying Cao
- Shanghai Institute of Cardiovascular Diseases, Shanghai Clinical Bioinformatics Research Institute, Zhongshan Hospital, Shanghai Medical College of Fudan University, Shanghai, China
| | - Yixiang Zhu
- School of Public Health, Key Lab of Public Health Safety of the Ministry of Education and NHC Key Laboratory of Health Technology Assessment, Fudan University, Shanghai, China
| | - Yue Niu
- School of Public Health, Key Lab of Public Health Safety of the Ministry of Education and NHC Key Laboratory of Health Technology Assessment, Fudan University, Shanghai, China
| | - Junbo Ge
- Department of Cardiology, Zhongshan Hospital, Fudan University, Shanghai, China.
| | - Renjie Chen
- School of Public Health, Key Lab of Public Health Safety of the Ministry of Education and NHC Key Laboratory of Health Technology Assessment, Fudan University, Shanghai, China.
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28
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Li J, Zhang L, Wang J, Jia R, Zhang X, Li X, Fu Y, Song L. Differential expression of long non-coding RNAs in the hippocampus of mice exposed to PM 2.5 in Dalian, China. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2022; 29:12136-12146. [PMID: 34561797 DOI: 10.1007/s11356-021-16496-5] [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: 01/08/2021] [Accepted: 09/07/2021] [Indexed: 06/13/2023]
Abstract
Evidence is mounting that PM2.5 exposure could lead to learning disability, memory deficits, and cognitive impairment; however, the underlying mechanisms are still not well demonstrated yet. Long non-coding RNAs (LncRNAs) play a crucial role in many human diseases. Although the relationship of Alzheimer's disease (AD) and lncRNAs have been discovered, the role of lncRNA in AD-like phenotype induced by PM2.5 needs further exploration. In this study, we profiled the expression of messenger RNAs (mRNAs) and lncRNAs in hippocampus after confirming the AD-like changes in mice. Compared with the control group, a total of 478 mRNAs and 151 lncRNAs were dysregulated after PM2.5 exposure. ECM-receptor interaction, focal adhesion, complement and coagulation cascades, and AGE-RAGE signaling pathway were found dysregulated through lncRNA-co-expressed genes analysis based on the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). Meanwhile, the genes related to microglia were significantly altered, such as CX3CR1, CD163, lncRNA Gm44750, and lncRNA Gm43509. Above evidences suggested that microglia-related lncRNAs dysregulation probably plays a crucial role in PM2.5exposure-associated learning and memory deficits.
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Affiliation(s)
- Jie Li
- College of Medical Laboratory, Dalian Medical University, Dalian, 116044, Liaoning Province, People's Republic of China
| | - Longying Zhang
- Department of Clinical Laboratory, Second Affiliated Hospital of Dalian Medical University, Dalian, 116023, Liaoning Province, People's Republic of China
| | - Jiaqi Wang
- College of Medical Laboratory, Dalian Medical University, Dalian, 116044, Liaoning Province, People's Republic of China
- The First Affiliated Hospital, Jinzhou Medical University, Jinzhou, 121000, Liaoning Province, People's Republic of China
| | - Ruxue Jia
- College of Medical Laboratory, Dalian Medical University, Dalian, 116044, Liaoning Province, People's Republic of China
| | - Xiao Zhang
- College of Medical Laboratory, Dalian Medical University, Dalian, 116044, Liaoning Province, People's Republic of China
| | - Xiaojing Li
- College of Medical Laboratory, Dalian Medical University, Dalian, 116044, Liaoning Province, People's Republic of China
| | - Ying Fu
- College of Medical Laboratory, Dalian Medical University, Dalian, 116044, Liaoning Province, People's Republic of China
| | - Laiyu Song
- College of Medical Laboratory, Dalian Medical University, Dalian, 116044, Liaoning Province, People's Republic of China.
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Wang T, Han Y, Li H, Fang Y, Liang P, Wang Y, Chen X, Qiu X, Gong J, Li W, Zhu T. Fine particulate matter and vasoactive 20-hydroxyeicosatetraenoic acid: Insights into the mechanisms of the prohypertensive effects of particulate air pollution. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 806:151298. [PMID: 34749965 DOI: 10.1016/j.scitotenv.2021.151298] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/23/2021] [Revised: 10/21/2021] [Accepted: 10/24/2021] [Indexed: 06/13/2023]
Abstract
BACKGROUND Emerging evidence suggests that biological intermediates play an important role in initiating fine particulate matter (PM2.5)-associated prohypertensive pathways, but sensitive biomarkers for this pathway are lacking. AIM To explore whether short-term exposure to PM2.5 is associated with the concentration of 20-hydroxyeicosatetraenoic acid (20-HETE), a potent vasoactive lipid relevant to the pathophysiology of hypertension. METHODS In this longitudinal panel study, we repeatedly (up to seven times) measured the blood concentrations of 20-HETE in 120 adults living in Beijing, China. Ambient exposure metrics included the concentrations of hourly PM2.5 mass and daily PM2.5 constituents, including three carbonaceous components, eight water-soluble ions, and 16 trace elements. Linear mixed-effects models were used to examine the associations between the change in the 20-HETE concentration and short-term exposure to ambient PM2.5 metrics after adjustment for age, sex, body mass index, behavioral exposure, socioeconomic characteristics, and meteorological factors. RESULTS The interquartile range (IQR) increase in the 7-15-hour-lag exposure to PM2.5 (80 μg/m3) was associated significantly with a 5.3% (95% confidence interval [CI], 0.1-10.7%) to 6.5% (95% CI, 1.7-11.6%) increase in the blood concentration of 20-HETE. The magnitude of the association differed by age, sex, prediabetic status, obesity, and hypertensive status, with a significantly greater increase in 20-HETE observed among those with fasting plasma glucose concentrations ≥ 6.1 mmol/L. In addition to the PM2.5 mass, the 20-HETE concentration was associated consistently with IQR increases in the 1-day lag exposure to organic carbon (5.7%), black carbon (9.5%), nitrate (3.9%), chloride (2.9%), copper (5.5%), zinc (4.7%), barium (4.1%), and lead (6.2%). The organic carbon estimate was robust in the two-pollutant models. Furthermore, increased 20-HETE correlated with elevated blood pressure (BP), although no mediation of 20-HETE on PM2.5-associated BP change was found. CONCLUSIONS The 20-HETE blood concentration increased significantly in response to short-term exposure to ambient PM2.5, which may be partly responsible for the prohypertensive effects of PM2.5.
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Affiliation(s)
- Teng Wang
- BIC-ESAT and SKL-ESPC, College of Environmental Sciences and Engineering, Peking University, Beijing, China
| | - Yiqun Han
- BIC-ESAT and SKL-ESPC, College of Environmental Sciences and Engineering, Peking University, Beijing, China; Environmental Research Group, MRC Centre for Environment and Health, Imperial College London, London, UK
| | - Haonan Li
- BIC-ESAT and SKL-ESPC, College of Environmental Sciences and Engineering, Peking University, Beijing, China
| | - Yanhua Fang
- BIC-ESAT and SKL-ESPC, College of Environmental Sciences and Engineering, Peking University, Beijing, China
| | - Pengfei Liang
- BIC-ESAT and SKL-ESPC, College of Environmental Sciences and Engineering, Peking University, Beijing, China
| | - Yanwen Wang
- BIC-ESAT and SKL-ESPC, College of Environmental Sciences and Engineering, Peking University, Beijing, China; National Institute of Environmental Health, Chinese Center for Disease control and Prevention, Beijing, China
| | - Xi Chen
- BIC-ESAT and SKL-ESPC, College of Environmental Sciences and Engineering, Peking University, Beijing, China; GRiC, Shenzhen Institute of Building Research Co., Ltd., Shenzhen, China
| | - Xinghua Qiu
- BIC-ESAT and SKL-ESPC, College of Environmental Sciences and Engineering, Peking University, Beijing, China
| | - Jicheng Gong
- BIC-ESAT and SKL-ESPC, College of Environmental Sciences and Engineering, Peking University, Beijing, China
| | - Weiju Li
- Peking University Hospital, Peking University, Beijing, China
| | - Tong Zhu
- BIC-ESAT and SKL-ESPC, College of Environmental Sciences and Engineering, Peking University, Beijing, China.
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