1
|
He G, Jiang M, Tian S, He L, Bai X, Chen S, Li G, Wang C, Zhang Z, Wu Y, Su M, Li X, Guo X, Yang Y, Zhang X, Cui J, Xu W, Song L, Yang H, He W, Zhang Y, Li X, Gao X, Chen L. Clean air policy reduces the atherogenic lipid profile levels: Results from China Health Evaluation And risk Reduction through nationwide Teamwork (ChinaHEART) Study. JOURNAL OF HAZARDOUS MATERIALS 2024; 478:135394. [PMID: 39128148 DOI: 10.1016/j.jhazmat.2024.135394] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/08/2024] [Revised: 07/16/2024] [Accepted: 07/30/2024] [Indexed: 08/13/2024]
Abstract
Evidence of the associations between long-term exposure to PM2.5 and O3 and human blood lipid concentrations is abundant yet inconclusive. Whether clean air policies could improve lipid profiles remains unclear. In total, 2979312 participants from a Chinese nationwide prospective study were included. For cross-sectional analyses, linear mixed-effects models were utilized to assess the associations of pollutants with lipid profiles (TC, LDL-C, TG, HDL-C). For longitudinal analyses, a quasi-experimental design and difference-in-differences models were employed to investigate the impact of China's Clean Air Act. In the cross-sectional analyses, each IQR increase in PM2.5 was associated with 2.49 % (95 % CI: 2.36 %, 2.62 %), 2.51 % (95 % CI: 2.26 %, 2.75 %), 3.94 % (95 % CI: 3.65 %, 4.23 %), and 1.54 % (95 % CI: 1.38 %, 1.70 %) increases in TC, LDL-C, TG, and HDL-C, respectively. For each IQR increase in O3, TC, LDL-C, TG, and HDL-C changed by 1.06 % (95 % CI: 0.95 %, 1.17 %), 1.21 % (95 % CI: 1.01 %, 1.42 %), 1.78 % (95 % CI: 1.54 %, 2.02 %), and -0.63 % (95 % CI: -0.76 %, -0.49 %), respectively. Longitudinal analyses showed that the intervention group experienced greater TC, LDL-C, and HDL-C reductions (1.77 %, 4.26 %, and 7.70 %, respectively). Our findings suggest that clean air policies could improve lipid metabolism and should be implemented in countries with heavy air pollution burdens.
Collapse
Affiliation(s)
- Guangda He
- National Clinical Research Center for Cardiovascular Diseases, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Meijie Jiang
- Department of Occupational and Environmental Health Sciences, School of Public Health, Peking University, Beijing, China
| | - Sifan Tian
- National Clinical Research Center for Cardiovascular Diseases, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China; Department of Occupational and Environmental Health Sciences, School of Public Health, Peking University, Beijing, China
| | - Linkang He
- National Clinical Research Center for Cardiovascular Diseases, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Xueke Bai
- National Clinical Research Center for Cardiovascular Diseases, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Shi Chen
- National Clinical Research Center for Cardiovascular Diseases, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Guangyu Li
- National Clinical Research Center for Cardiovascular Diseases, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China; 4+4 Medical Doctor Program, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Chunqi Wang
- National Clinical Research Center for Cardiovascular Diseases, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Zenglei Zhang
- National Clinical Research Center for Cardiovascular Diseases, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Yi Wu
- National Clinical Research Center for Cardiovascular Diseases, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Mingming Su
- National Clinical Research Center for Cardiovascular Diseases, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Xiangjie Li
- National Clinical Research Center for Cardiovascular Diseases, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Xinxin Guo
- National Clinical Research Center for Cardiovascular Diseases, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Yang Yang
- National Clinical Research Center for Cardiovascular Diseases, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Xiaoyan Zhang
- National Clinical Research Center for Cardiovascular Diseases, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Jianlan Cui
- National Clinical Research Center for Cardiovascular Diseases, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Wei Xu
- National Clinical Research Center for Cardiovascular Diseases, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Lijuan Song
- National Clinical Research Center for Cardiovascular Diseases, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Hao Yang
- National Clinical Research Center for Cardiovascular Diseases, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Wenyan He
- National Clinical Research Center for Cardiovascular Diseases, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Yan Zhang
- National Clinical Research Center for Cardiovascular Diseases, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Xi Li
- National Clinical Research Center for Cardiovascular Diseases, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Xu Gao
- Department of Occupational and Environmental Health Sciences, School of Public Health, Peking University, Beijing, China.
| | - Liang Chen
- National Clinical Research Center for Cardiovascular Diseases, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
| |
Collapse
|
2
|
Li Y, Lv Y, Jiang Z, Ma C, Li R, Zhao M, Guo Y, Guo H, Zhang X, Li A, Liu Y. Association of co-exposure to organophosphate esters and per- and polyfluoroalkyl substances and mixture with cardiovascular-kidney-liver-metabolic biomarkers among Chinese adults. ECOTOXICOLOGY AND ENVIRONMENTAL SAFETY 2024; 280:116524. [PMID: 38838464 DOI: 10.1016/j.ecoenv.2024.116524] [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: 02/23/2024] [Revised: 05/14/2024] [Accepted: 05/27/2024] [Indexed: 06/07/2024]
Abstract
BACKGROUND Organophosphate esters (OPEs) and Per- and polyfluoroalkyl substances (PFAS) are ubiquitous environmental contaminants with common exposure sources, leading to their widespread presence in human body. However, evidence on co-exposure to OPEs and PFAS and its impact on cardiovascular-kidney-liver-metabolic biomarkers remains limited. METHODS In this cross-sectional study, 467 adults were enrolled from January to May 2022 during physical visits in Shijiazhuang, Hebei province. Eleven types of OPEs and twelves types of PFAS were detected, among which eight OPEs and six PFAS contaminants were detected in more than 60% of plasma samples. Seventeen biomarkers were assessed to comprehensively evaluate the cardiovascular-kidney-liver-metabolic function. Multiple linear regression, multipollutant models with sparse partial least squares, and Bayesian kernel machine regression (BKMR) models were applied to examine the associations of individual OPEs and PFAS and their mixtures with organ function and metabolism, respectively. RESULTS Of the over 400 exposure-outcome associations tested when modelling, we observed robust results across three models that perfluorohexanoic acid (PFHxS) was significantly positively associated with alanine aminotransferase (ALT), aspartate aminotransferase (AST), total bilirubin (TBIL), and indirect bilirubin (IBIL). Perfluorononanoic acid was significantly associated with decreased AST/ALT and increased very-low-density lipoprotein cholesterol levels. Besides, perfluorodecanoic acid was correlated with increased high lipoprotein cholesterol and perfluoroundecanoic acid was consistently associated with lower glucose level. BKMR analysis showed that OPEs and PFAS mixtures were positively associated with IBIL and TBIL, among which PFHxS was the main toxic chemicals. CONCLUSIONS Our findings suggest that exposure to OPEs and PFAS, especially PFHxS and PFNA, may disrupt organ function and metabolism in the general population, providing insight into the potential pathophysiological mechanisms of OPEs and PFAS co-exposure and chronic diseases.
Collapse
Affiliation(s)
- Yanbing Li
- Department of Epidemiology and Biostatistics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing 100005, PR China; Center of Environmental and Health Sciences, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing 100005, PR China
| | - Yi Lv
- Department of Toxicology, School of Public Health, Hebei Medical University, Shijiazhuang 050017, PR China
| | - Zexuan Jiang
- Department of Toxicology, School of Public Health, Hebei Medical University, Shijiazhuang 050017, PR China
| | - Chaoying Ma
- Department of Toxicology, School of Public Health, Hebei Medical University, Shijiazhuang 050017, PR China
| | - Ran Li
- Department of Toxicology, School of Public Health, Hebei Medical University, Shijiazhuang 050017, PR China
| | - Mengwei Zhao
- Department of Toxicology, School of Public Health, Hebei Medical University, Shijiazhuang 050017, PR China
| | - Yi Guo
- Department of Toxicology, School of Public Health, Hebei Medical University, Shijiazhuang 050017, PR China
| | - Huicai Guo
- Department of Toxicology, School of Public Health, Hebei Medical University, Shijiazhuang 050017, PR China; Hebei Key Laboratory of Environment and Human Health, Shijiazhuang, Hebei Province 050017, PR China; The Key Laboratory of Neural and Vascular Biology, Ministry of Education, Shijiazhuang 050017, PR China
| | - Xiaoguang Zhang
- Core Facilities and Centers of Hebei Medical University, Shijiazhuang 050017, PR China
| | - Ang Li
- Department of Epidemiology and Biostatistics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing 100005, PR China; Center of Environmental and Health Sciences, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing 100005, PR China; Hebei Key Laboratory of Environment and Human Health, Shijiazhuang, Hebei Province 050017, PR China.
| | - Yi Liu
- Department of Toxicology, School of Public Health, Hebei Medical University, Shijiazhuang 050017, PR China; Hebei Key Laboratory of Environment and Human Health, Shijiazhuang, Hebei Province 050017, PR China.
| |
Collapse
|
3
|
Lu W, Jiang C, Chen Y, Lu Z, Xu X, Zhu L, Xi H, Ye G, Yan C, Chen J, Zhang J, Zuo L, Huang Q. Altered metabolome and microbiome associated with compromised intestinal barrier induced hepatic lipid metabolic disorder in mice after subacute and subchronic ozone exposure. ENVIRONMENT INTERNATIONAL 2024; 185:108559. [PMID: 38461778 DOI: 10.1016/j.envint.2024.108559] [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: 12/02/2023] [Revised: 02/05/2024] [Accepted: 03/04/2024] [Indexed: 03/12/2024]
Abstract
Exposure to ozone has been associated with metabolic disorders in humans, but the underlying mechanism remains unclear. In this study, the role of the gut-liver axis and the potential mechanism behind the metabolic disorder were investigated by histological examination, microbiome and metabolome approaches in mice during the subacute (4-week) and subchronic (12-week) exposure to 0.5 ppm and 2.5 ppm ozone. Ozone exposure resulted in slowed weight gain and reduced hepatic lipid contents in a dose-dependent manner. After exposure to ozone, the number of intestinal goblet cells decreased, while the number of tuft cells increased. Tight junction protein zonula occludens-1 (ZO-1) was significantly downregulated, and the apoptosis of epithelial cells increased with compensatory proliferation, indicating a compromised chemical and physical layer of the intestinal barrier. The hepatic and cecal metabolic profiles were altered, primarily related to lipid metabolism and oxidative stress. The abundance of Muribaculaceae increased dose-dependently in both colon and cecum, and was associated with the decrease of metabolites such as bile acids, betaine, and L-carnitine, which subsequently disrupted the intestinal barrier and lipid metabolism. Overall, this study found that subacute and subchronic exposure to ozone induced metabolic disorder via disturbing the gut-liver axis, especially the intestinal barrier. These findings provide new mechanistic understanding of the health risks associated with environmental ozone exposure and other oxidative stressors.
Collapse
Affiliation(s)
- Wenjia Lu
- Xiamen Key Laboratory of Indoor Air and Health, Key Lab of Urban Environment and Health, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China; College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Chonggui Jiang
- Innovation and Entrepreneurship Laboratory for college students, Department of Biochemistry and Molecular Biology, Metabolic Disease Research Center, School of Basic Medicine, Anhui Medical University, Hefei 230032, China
| | - Yajie Chen
- Guangdong Provincial Key Laboratory of Large Animal Models for Biomedicine, School of Biotechnology and Health Sciences, Wuyi University, Jiangmen 529020, China
| | - Zhonghua Lu
- State Key Laboratory of Vaccines for Infectious Diseases, Xiang An Biomedicine Laboratory, State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, National Innovation Platform for Industry-Education Integration in Vaccine Research, School of Public Health, Xiamen University, Xiamen 361102, China
| | - Xueli Xu
- Xiamen Key Laboratory of Indoor Air and Health, Key Lab of Urban Environment and Health, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China; College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Liting Zhu
- Xiamen Key Laboratory of Indoor Air and Health, Key Lab of Urban Environment and Health, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China; College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Haotong Xi
- Guangdong Provincial Key Laboratory of Large Animal Models for Biomedicine, School of Biotechnology and Health Sciences, Wuyi University, Jiangmen 529020, China
| | - Guozhu Ye
- Xiamen Key Laboratory of Indoor Air and Health, Key Lab of Urban Environment and Health, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China
| | - Changzhou Yan
- Xiamen Key Laboratory of Indoor Air and Health, Key Lab of Urban Environment and Health, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China
| | - Jinsheng Chen
- Center for Excellence in Regional Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China
| | - Jie Zhang
- State Key Laboratory of Vaccines for Infectious Diseases, Xiang An Biomedicine Laboratory, State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, National Innovation Platform for Industry-Education Integration in Vaccine Research, School of Public Health, Xiamen University, Xiamen 361102, China.
| | - Li Zuo
- Innovation and Entrepreneurship Laboratory for college students, Department of Biochemistry and Molecular Biology, Metabolic Disease Research Center, School of Basic Medicine, Anhui Medical University, Hefei 230032, China.
| | - Qiansheng Huang
- Xiamen Key Laboratory of Indoor Air and Health, Key Lab of Urban Environment and Health, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China; National Basic Science Data Center, Beijing 100190, China.
| |
Collapse
|
4
|
Wang X, Li A, Zhao M, Xu J, Mei Y, Xu Q. Differential effects of PM 2.5 and its carbon components on blood pressure in hypertensive and non-hypertensive populations: a panel study in Beijing. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2023; 30:123226-123236. [PMID: 37981604 DOI: 10.1007/s11356-023-30532-6] [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: 03/03/2022] [Accepted: 10/13/2023] [Indexed: 11/21/2023]
Abstract
Published literature considering the association between ambient air pollution and blood pressure is highly inconsistent, which may be explained by the different proportions of susceptible subpopulations. We hypothesized that hypertensive patients are more sensitive to air pollution due to the disruption of neurohumoral system. The study aimed to reveal the association between PM2.5 and its carbon components and blood pressure, and whether this association is modified by hypertension status. We conducted a panel study in Beijing, China. Four repeated measurements were performed from 2016 to 2018. Linear mixed-effects models and generalized additive mixed models were performed to investigate the associations between PM2.5 and its carbon components and blood pressure. Subgroup analyses were performed by hypertension status to reveal potential effect modification. Among hypertensive patients, for every 1 μg/m3 increment of PM2.5, TC, OC, and EC in 1-day to 2-day MA, SBP increased from 0.16 mmHg (95% CI, 0.03 to 0.29) to 6.75 mmHg (95% CI, 2.82 to 10.68), and PP increased from 0.14 mmHg (95% CI, 0.02 to 0.26) to 6.03% (95% CI, 2.46 to 9.59%), but no significant association was observed among non-hypertensive subjects. The p values for the interaction between pollutants and hypertension status in 1-day to 2-day MA were less than 0.05. These findings suggest that hypertensive patients may be more susceptible to the adverse effects of air pollution than non-hypertensive subjects, which might provide guidance to hypertensive patients living in areas with high levels of particle pollution.
Collapse
Affiliation(s)
- Xue Wang
- Department of Allergy and Clinical Immunology, Peking Union Medical College Hospital, Peking Union Medical College and Chinese Academy of Medical Sciences, National Clinical Research Center for Immunologic Diseases, Beijing, 100730, China
| | - Ang Li
- Department of Epidemiology and Biostatistics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing, 100005, China
- Center of Environmental and Health Sciences, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, 100005, China
| | - Meiduo Zhao
- Department of Epidemiology and Biostatistics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing, 100005, China
- Center of Environmental and Health Sciences, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, 100005, China
| | - Jing Xu
- Department of Epidemiology and Biostatistics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing, 100005, China
- Center of Environmental and Health Sciences, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, 100005, China
| | - Yayuan Mei
- Department of Epidemiology and Biostatistics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing, 100005, China
- Center of Environmental and Health Sciences, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, 100005, China
| | - Qun Xu
- Department of Epidemiology and Biostatistics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing, 100005, China.
- Center of Environmental and Health Sciences, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, 100005, China.
| |
Collapse
|
5
|
Li A, Li Y, Mei Y, Zhao J, Zhou Q, Li K, Zhao M, Xu J, Ge X, Xu Q. Associations of metals and metals mixture with lipid profiles: A repeated-measures study of older adults in Beijing. CHEMOSPHERE 2023; 319:137833. [PMID: 36693480 DOI: 10.1016/j.chemosphere.2023.137833] [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: 10/11/2022] [Revised: 12/25/2022] [Accepted: 01/10/2023] [Indexed: 06/17/2023]
Abstract
Metals inevitably and easily enter into human bodies and can induce a series of pathophysiological changes, such as oxidative stress damage and lipid peroxidation, which then may further induce dyslipidemia. However, the effects of metals and metals mixture on the lipid profiles are still unclear, especially in older adults. A three-visits repeated measurement of 201 older adults in Beijing was conducted from November 2016 to January 2018. Linear Mixed Effects models and Bayesian kernel machine regression models were used to estimate associations of eight blood metals and metals mixture with lipid profiles, including total cholesterol (TC), triglycerides (TG), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), Castelli risk indexes I (CRI-1), Castelli risk indexes II (CRI-2), atherogenic coefficient (AC), and non-HDL cholesterol (NHC). Cesium (Cs) was positively associated with TG (βCs = 0.14; 95% CI: 0.02, 0.26) whereas copper (Cu) was inversely related to TG (βCu = -0.65; 95%CI: -1.14, -0.17) in adjusted models. Manganese (Mn) was mainly related to higher HDL-C (βMn = 0.14; 95% CI: 0.07, 0.21) whereas molybdenum showed opposite association. Metals mixture was marginally positive associated with HDL-C, among which Mn played a crucial role. Our findings suggest that the effects of single metal on lipid profiles may be counteracted in mixtures in the context of multiple metal exposures; however, future studies with large sample size are still needed to focus on the detrimental effects of single metals on lipid profiles as well as to identify key components.
Collapse
Affiliation(s)
- Ang Li
- Department of Epidemiology and Biostatistics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing, 100005, China; Center of Environmental and Health Sciences, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, 100005, China
| | - Yanbing Li
- Department of Epidemiology and Biostatistics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing, 100005, China; Center of Environmental and Health Sciences, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, 100005, China
| | - Yayuan Mei
- Department of Epidemiology and Biostatistics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing, 100005, China; Center of Environmental and Health Sciences, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, 100005, China
| | - Jiaxin Zhao
- Department of Epidemiology and Biostatistics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing, 100005, China; Center of Environmental and Health Sciences, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, 100005, China
| | - Quan Zhou
- Department of Epidemiology and Biostatistics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing, 100005, China; Center of Environmental and Health Sciences, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, 100005, China
| | - Kai Li
- Department of Epidemiology and Biostatistics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing, 100005, China; Center of Environmental and Health Sciences, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, 100005, China
| | - Meiduo Zhao
- Department of Epidemiology and Biostatistics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing, 100005, China; Center of Environmental and Health Sciences, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, 100005, China
| | - Jing Xu
- Department of Epidemiology and Biostatistics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing, 100005, China; Center of Environmental and Health Sciences, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, 100005, China
| | - Xiaoyu Ge
- Department of Epidemiology and Biostatistics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing, 100005, China; Center of Environmental and Health Sciences, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, 100005, China
| | - Qun Xu
- Department of Epidemiology and Biostatistics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing, 100005, China; Center of Environmental and Health Sciences, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, 100005, China.
| |
Collapse
|
6
|
Ju X, Yimaer W, Du Z, Wang X, Cai H, Chen S, Zhang Y, Wu G, Wu W, Lin X, Wang Y, Jiang J, Hu W, Zhang W, Hao Y. The impact of monthly air pollution exposure and its interaction with individual factors: Insight from a large cohort study of comprehensive hospitalizations in Guangzhou area. Front Public Health 2023; 11:1137196. [PMID: 37026147 PMCID: PMC10071997 DOI: 10.3389/fpubh.2023.1137196] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2023] [Accepted: 03/01/2023] [Indexed: 04/08/2023] Open
Abstract
Background Although the association between short-term air pollution exposure and certain hospitalizations has been well documented, evidence on the effect of longer-term (e. g., monthly) air pollution on a comprehensive set of outcomes is still limited. Method A total of 68,416 people in South China were enrolled and followed up during 2019-2020. Monthly air pollution level was estimated using a validated ordinary Kriging method and assigned to individuals. Time-dependent Cox models were developed to estimate the relationship between monthly PM10 and O3 exposures and the all-cause and cause-specific hospitalizations after adjusting for confounders. The interaction between air pollution and individual factors was also investigated. Results Overall, each 10 μg/m3 increase in PM10 concentration was associated with a 3.1% (95%CI: 1.3%-4.9%) increment in the risk of all-cause hospitalization. The estimate was even greater following O3 exposure (6.8%, 5.5%-8.2%). Furthermore, each 10 μg/m3 increase in PM10 was associated with a 2.3%-9.1% elevation in all the cause-specific hospitalizations except for those related to respiratory and digestive diseases. The same increment in O3 was relevant to a 4.7%-22.8% elevation in the risk except for respiratory diseases. Additionally, the older individuals tended to be more vulnerable to PM10 exposure (P interaction: 0.002), while the alcohol abused and those with an abnormal BMI were more vulnerable to the impact of O3 (P interaction: 0.052 and 0.011). However, the heavy smokers were less vulnerable to O3 exposure (P interaction: 0.032). Conclusion We provide comprehensive evidence on the hospitalization hazard of monthly PM10 and O3 exposure and their interaction with individual factors.
Collapse
Affiliation(s)
- Xu Ju
- Department of Medical Statistics, School of Public Health & Center for Health Information Research & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, China
| | - Wumitijiang Yimaer
- Department of Medical Statistics, School of Public Health & Center for Health Information Research & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, China
| | - Zhicheng Du
- Department of Medical Statistics, School of Public Health & Center for Health Information Research & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, China
| | - Xinran Wang
- Department of Medical Statistics, School of Public Health & Center for Health Information Research & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, China
| | - Huanle Cai
- Department of Medical Statistics, School of Public Health & Center for Health Information Research & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, China
| | - Shirui Chen
- Department of Medical Statistics, School of Public Health & Center for Health Information Research & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, China
| | - Yuqin Zhang
- Department of Medical Statistics, School of Public Health & Center for Health Information Research & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, China
| | - Gonghua Wu
- Department of Medical Statistics, School of Public Health & Center for Health Information Research & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, China
| | - Wenjing Wu
- Department of Medical Statistics, School of Public Health & Center for Health Information Research & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, China
| | - Xiao Lin
- Department of Medical Statistics, School of Public Health & Center for Health Information Research & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, China
| | - Ying Wang
- Department of Medical Statistics, School of Public Health & Center for Health Information Research & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, China
| | - Jie Jiang
- Peking University Center for Public Health and Epidemic Preparedness and Response, Peking, China
| | - Weihua Hu
- Peking University Center for Public Health and Epidemic Preparedness and Response, Peking, China
| | - Wangjian Zhang
- Department of Medical Statistics, School of Public Health & Center for Health Information Research & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, China
- *Correspondence: Wangjian Zhang
| | - Yuantao Hao
- Peking University Center for Public Health and Epidemic Preparedness and Response, Peking, China
- Yuantao Hao
| |
Collapse
|
7
|
Chen Y, Wang Y, Cui Z, Liu W, Liu B, Zeng Q, Zhao X, Dou J, Cao J. Endocrine disrupting chemicals: A promoter of non-alcoholic fatty liver disease. Front Public Health 2023; 11:1154837. [PMID: 37033031 PMCID: PMC10075363 DOI: 10.3389/fpubh.2023.1154837] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2023] [Accepted: 03/06/2023] [Indexed: 04/11/2023] Open
Abstract
Non-alcoholic fatty liver disease (NAFLD) is the most prevalent liver disorder. With the improvement in human living standards, the prevalence of NAFLD has been increasing in recent years. Endocrine-disrupting chemicals (EDCs) are a class of exogenous chemicals that simulate the effects of hormones in the body. There has been growing evidence regarding the potential effects of EDCs on liver health, especially in NAFLD. This paper aims to summarize the major EDCs that contribute to the growing burden of NAFLD and to raise public awareness regarding the hazards posed by EDCs with the objective of reducing the incidence of NAFLD.
Collapse
|
8
|
Anbari K, Khaniabadi YO, Sicard P, Naqvi HR, Rashidi R. Increased tropospheric ozone levels as a public health issue during COVID-19 lockdown and estimation the related pulmonary diseases. ATMOSPHERIC POLLUTION RESEARCH 2022; 13:101600. [PMID: 36439075 PMCID: PMC9676228 DOI: 10.1016/j.apr.2022.101600] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/22/2022] [Revised: 11/15/2022] [Accepted: 11/15/2022] [Indexed: 05/05/2023]
Abstract
The aims of this study were to i) investigate the variation of tropospheric ozone (O3) levels during the COVID-19 lockdown; ii) determine the relationships between O3 concentrations with the number of COVID-19 cases; and iii) estimate the O3-related health effects in Southwestern Iran (Khorramabad) over the time period 2019-2021. The hourly O3 data were collected from ground monitoring stations, as well as retrieved from Sentinel-5 satellite data for showing the changes in O3 levels pre, during, and after lockdown period. The concentration-response function model was applied using relative risk (RR) values and baseline incidence (BI) to assess the O3-related health effects. Compared to 2019, the annual O3 mean concentrations increased by 12.2% in 2020 and declined by 3.9% in 2021. The spatiotemporal changes showed a significant O3 increase during COVID-19 lockdown, and a negative correlation between O3 levels and the number of COVID-19 cases was found (r = - 0.59, p < 0.05). In 2020, the number of hospital admissions for cardiovascular diseases increased by 4.0 per 105 cases, the mortality for respiratory diseases increased by 0.7 per 105 cases, and the long-term mortality for respiratory diseases increased by 0.9 per 105 cases. Policy decisions are now required to reduce the surface O3 concentrations and O3-related health effects in Iran.
Collapse
Affiliation(s)
- Khatereh Anbari
- Social Determinants of Health Research Center, School of Medicine, Lorestan University of Medical Sciences, Khorramabad, Iran
| | - Yusef Omidi Khaniabadi
- Occupational and Environmental Health Research Center, Petroleum Industry Health Organization (PIHO), Ahvaz, Iran
| | - Pierre Sicard
- ARGANS, 260 Route Du Pin Montard, 06410, Biot, France
| | - Hasan Raja Naqvi
- Department of Geography, Faculty of Natural Sciences, Jamia Millia Islamia, New Delhi, India
| | - Rajab Rashidi
- Department of Occupational Health, Nutritional Health Research Center, School of Health and Nutrition, Lorestan University of Medical Sciences, Khorramabad, Iran
| |
Collapse
|
9
|
Mei Y, Zhao J, Zhou Q, Zhao M, Xu J, Li Y, Li K, Xu Q. Residential greenness attenuated association of long-term air pollution exposure with elevated blood pressure: Findings from polluted areas in Northern China. Front Public Health 2022; 10:1019965. [PMID: 36249254 PMCID: PMC9557125 DOI: 10.3389/fpubh.2022.1019965] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2022] [Accepted: 09/12/2022] [Indexed: 01/28/2023] Open
Abstract
Background Evidence on the hypertensive effects of long-term air pollutants exposure are mixed, and the joint hypertensive effects of air pollutants are also unclear. Sparse evidence exists regarding the modifying role of residential greenness in such effects. Methods A cross-sectional study was conducted in typically air-polluted areas in northern China. Particulate matter with diameter < 1 μm (PM1), particulate matter with diameter < 2.5 μm (PM2.5), particulate matter with diameter < 10 μm (PM10), nitrogen dioxide (NO2), sulfur dioxide (SO2), and ozone (O3) were predicted by space-time extremely randomized trees model. We used the Normalized Difference Vegetation Index (NDVI) to reflect residential green space. Systolic blood pressure (SBP) and diastolic blood pressure (DBP) were examined. We also calculated the pulse pressure (PP) and mean arterial pressure (MAP). Generalized additive model and quantile g-computation were, respectively, conducted to investigate individual and joint effects of air pollutants on blood pressure. Furthermore, beneficial effect of NDVI and its modification effect were explored. Results Long-term air pollutants exposure was associated with elevated DBP and MAP. Specifically, we found a 10-μg/m3 increase in PM2.5, PM10, and SO2 were associated with 2.36% (95% CI: 0.97, 3.76), 1.51% (95% CI: 0.70, 2.34), and 3.54% (95% CI: 1.55, 5.56) increase in DBP; a 10-μg/m3 increase in PM2.5, PM10, and SO2 were associated with 1.84% (95% CI: 0.74, 2.96), 1.17% (95% CI: 0.52, 1.83), and 2.43% (95% CI: 0.71, 4.18) increase in MAP. Air pollutants mixture (one quantile increase) was positively associated with increased values of DBP (8.22%, 95% CI: 5.49, 11.02) and MAP (4.15%, 95% CI: 2.05, 6.30), respectively. These identified harmful effect of air pollutants mainly occurred among these lived with low NDVI values. And participants aged ≥50 years were more susceptible to the harmful effect of PM2.5 and PM10 compared to younger adults. Conclusions Our study indicated the harmful effect of long-term exposure to air pollutants and these effects may be modified by living within higher green space place. These evidence suggest increasing residential greenness and air pollution control may have simultaneous effect on decreasing the risk of hypertension.
Collapse
Affiliation(s)
- Yayuan Mei
- Department of Epidemiology and Biostatistics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing, China,Center of Environmental and Health Sciences, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, China
| | - Jiaxin Zhao
- Department of Epidemiology and Biostatistics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing, China,Center of Environmental and Health Sciences, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, China
| | - Quan Zhou
- Department of Epidemiology and Biostatistics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing, China,Center of Environmental and Health Sciences, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, China
| | - Meiduo Zhao
- Department of Epidemiology and Biostatistics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing, China,Center of Environmental and Health Sciences, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, China
| | - Jing Xu
- Department of Epidemiology and Biostatistics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing, China,Center of Environmental and Health Sciences, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, China
| | - Yanbing Li
- Department of Epidemiology and Biostatistics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing, China,Center of Environmental and Health Sciences, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, China
| | - Kai Li
- Department of Epidemiology and Biostatistics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing, China,Center of Environmental and Health Sciences, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, China
| | - Qun Xu
- Department of Epidemiology and Biostatistics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing, China,Center of Environmental and Health Sciences, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, China,*Correspondence: Qun Xu
| |
Collapse
|
10
|
Li A, Zhou Q, Mei Y, Zhao J, Zhao M, Xu J, Ge X, Xu Q. Novel Strategies for Assessing Associations Between Selenium Biomarkers and Cardiometabolic Risk Factors: Concentration, Visit-to-Visit Variability, or Individual Mean? Evidence From a Repeated-Measures Study of Older Adults With High Selenium. Front Nutr 2022; 9:838613. [PMID: 35711534 PMCID: PMC9196882 DOI: 10.3389/fnut.2022.838613] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2021] [Accepted: 05/11/2022] [Indexed: 12/23/2022] Open
Abstract
Background and Aims Previous studies have focused only on the cardiometabolic effects of selenium concentrations. We explored whether selenium levels and their visit-to-visit variability (VVV) and individual mean (IM) are independently associated with cardiometabolic risk factors. Methods A three-wave repeated-measures study of older adults with high selenium (n = 201) was conducted in Beijing from 2016 to 2018. Whole blood selenium and urinary selenium concentrations were measured. VVV and IM were used to profile the homeostasis of the selenium biomarkers. Four indicators, namely standard deviation, coefficient of variation, average real variability, and variability independent of the mean, were employed to characterize VVV. We considered 13 cardiometabolic factors: four lipid profile indicators, three blood pressure indices, glucose, uric acid, waistline, hipline, waist-hip ratio, and sex-specific metabolic syndrome score. Linear mixed-effects regression models with random intercepts for the participants were employed to explore the associations of the selenium concentrations, VVV, and IM with the cardiometabolic factors. Results The geometric mean whole blood and urinary selenium levels were 134.30 and 18.00 μg/L, respectively. Selenium concentrations were significantly associated with numerous cardiometabolic factors. Specifically, whole blood selenium was positively associated with total cholesterol [0.22, 95% confidence interval (CI): 0.12, 0.33], low-density lipoprotein cholesterol (LDL-C; 0.28, 95% CI: 0.13, 0.42), glucose (0.22, 95% CI: 0.10, 0.34), and uric acid (0.16, 95% CI: 0.04, 0.28). After adjustment for VVV, the IM of whole blood selenium was positively correlated with total cholesterol (0.002, 95% CI: 0.001, 0.004), triglycerides (0.007, 95% CI: 0.004, 0.011), and LDL-C (0.002, 95% CI: 0.000, 0.004). However, we did not observe any robust associations between the VVV of the selenium biomarkers and cardiometabolic risk factors after adjustment for IM. Conclusion Our findings suggest that selenium concentrations and their IMs are significantly associated with cardiometabolic risk factors among older adults with high selenium. Longer repeated-measures studies among the general population are required to validate our findings and elucidate the relevant underlying mechanisms.
Collapse
Affiliation(s)
- Ang Li
- Department of Epidemiology and Biostatistics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing, China.,Center of Environmental and Health Sciences, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, China
| | - Quan Zhou
- Department of Epidemiology and Biostatistics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing, China.,Center of Environmental and Health Sciences, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, China
| | - Yayuan Mei
- Department of Epidemiology and Biostatistics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing, China.,Center of Environmental and Health Sciences, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, China
| | - Jiaxin Zhao
- Department of Epidemiology and Biostatistics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing, China.,Center of Environmental and Health Sciences, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, China
| | - Meiduo Zhao
- Department of Epidemiology and Biostatistics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing, China.,Center of Environmental and Health Sciences, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, China
| | - Jing Xu
- Department of Epidemiology and Biostatistics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing, China.,Center of Environmental and Health Sciences, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, China
| | - Xiaoyu Ge
- Department of Epidemiology and Biostatistics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing, China.,Center of Environmental and Health Sciences, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, China
| | - Qun Xu
- Department of Epidemiology and Biostatistics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing, China.,Center of Environmental and Health Sciences, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, China
| |
Collapse
|
11
|
Niu Y, Li H, Wang W, Wang C, Liu C, Du X, Zhang Q, Li J, Shi S, Meng X, Chen R, Kan H. Ozone exposure and prothrombosis: Mechanistic insights from a randomized controlled exposure trial. JOURNAL OF HAZARDOUS MATERIALS 2022; 429:128322. [PMID: 35086041 DOI: 10.1016/j.jhazmat.2022.128322] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/21/2021] [Revised: 01/06/2022] [Accepted: 01/19/2022] [Indexed: 06/14/2023]
Abstract
Epidemiological studies have associated ozone exposure with cardiovascular diseases, but the molecular mechanisms were not elucidated. We performed an untargeted serum proteomic analysis in a randomized, crossover, controlled exposure trial. We recruited 32 healthy young adults and asked them to receive filtered air and 200-ppb ozone exposures for 2 h in a random order before serum collection. Linear mixed-effect models were used to identify differentially expressed proteins (DEPs) between the two exposures and Gene Ontology enrichment and ingenuity pathway analysis were performed to determine their biological function. A total of 56 DEPs were identified. For example, acute ozone exposure increased coagulation factor X and factor VII-activating protease by 20.96% and 28.35%, respectively. Whereas, protein Z, protein Z-dependent protease inhibitor, and plasminogen decreased by 13.62%, 33.54%, and 10.47%, respectively. We also observed a 42.32% decrease in paraoxonase 3 and evident changes in four apolipoproteins. Additionally, we found 18.21% and 95.82% increases in L-selectin and β2-microglobulin, respectively, and significant changes in three complements. DEPs and enriched pathways suggest that short-term ozone exposure may promote coagulation, suppress fibrinolysis, disrupt lipoprotein metabolism, activate immune responses, and affect the complement system. These findings provide additional insights into the mechanisms linking acute ozone exposure to thrombosis.
Collapse
Affiliation(s)
- Yue Niu
- School of Public Health, Shanghai Institute of Infectious Disease and Biosecurity, Key Lab of Public Health Safety of the Ministry of Education and NHC Key Lab of Health Technology Assessment, Fudan University, Shanghai 200032, China
| | - Huichu Li
- Department of Environmental Health, Harvard TH Chan School of Public Health, Boston, MA 02215, USA
| | - Weidong Wang
- School of Public Health, Shanghai Institute of Infectious Disease and Biosecurity, Key Lab of Public Health Safety of the Ministry of Education and NHC Key Lab of Health Technology Assessment, Fudan University, Shanghai 200032, China
| | - Cuiping Wang
- School of Public Health, Shanghai Institute of Infectious Disease and Biosecurity, Key Lab of Public Health Safety of the Ministry of Education and NHC Key Lab of Health Technology Assessment, Fudan University, Shanghai 200032, China
| | - Cong Liu
- School of Public Health, Shanghai Institute of Infectious Disease and Biosecurity, Key Lab of Public Health Safety of the Ministry of Education and NHC Key Lab of Health Technology Assessment, Fudan University, Shanghai 200032, China
| | - Xihao Du
- School of Public Health, Shanghai Institute of Infectious Disease and Biosecurity, Key Lab of Public Health Safety of the Ministry of Education and NHC Key Lab of Health Technology Assessment, Fudan University, Shanghai 200032, China
| | - Qingli Zhang
- School of Public Health, Shanghai Institute of Infectious Disease and Biosecurity, Key Lab of Public Health Safety of the Ministry of Education and NHC Key Lab of Health Technology Assessment, Fudan University, Shanghai 200032, China
| | - Jingguang Li
- Shanghai Research Institute of Building Sciences (Group) Co., Ltd., Shanghai 200032, China
| | - Su Shi
- School of Public Health, Shanghai Institute of Infectious Disease and Biosecurity, Key Lab of Public Health Safety of the Ministry of Education and NHC Key Lab of Health Technology Assessment, Fudan University, Shanghai 200032, China
| | - Xia Meng
- School of Public Health, Shanghai Institute of Infectious Disease and Biosecurity, Key Lab of Public Health Safety of the Ministry of Education and NHC Key Lab of Health Technology Assessment, Fudan University, Shanghai 200032, China
| | - Renjie Chen
- School of Public Health, Shanghai Institute of Infectious Disease and Biosecurity, Key Lab of Public Health Safety of the Ministry of Education and NHC Key Lab of Health Technology Assessment, Fudan University, Shanghai 200032, China.
| | - Haidong Kan
- School of Public Health, Shanghai Institute of Infectious Disease and Biosecurity, Key Lab of Public Health Safety of the Ministry of Education and NHC Key Lab of Health Technology Assessment, Fudan University, Shanghai 200032, China; Children's Hospital of Fudan University, National Center for Children's Health, Shanghai 201102, China.
| |
Collapse
|
12
|
Li A, Zhao J, Liu L, Mei Y, Zhou Q, Zhao M, Xu J, Ge X, Xu Q. Association of Metals and Metalloids With Urinary Albumin/Creatinine Ratio: Evidence From a Cross-Sectional Study Among Elderly in Beijing. Front Public Health 2022; 10:832079. [PMID: 35433578 PMCID: PMC9008350 DOI: 10.3389/fpubh.2022.832079] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2021] [Accepted: 03/07/2022] [Indexed: 12/12/2022] Open
Abstract
Background Environmental exposure to toxic elements contributes to the pathogenesis of chronic kidney disease (CKD). Few studies focus on the association of urinary metals and metalloids concentrations with the urinary albumin/creatinine ratio (UACR) among elderly, especially in areas and seasons with severe air pollution. Objective We aimed to evaluate the associations of urinary metals and metalloids concentration with UACR, which is an early and sensitive indicator of CKD. Method We conducted a cross-sectional study among 275 elderly people in Beijing from November to December 2016, which has experienced the most severe air pollution in China. We measured 15 urinary metals and metalloids concentration and estimated their association with UACR using a generalized linear model (GLM). Bayesian kernel machine regression (BKMR) and quantile g-computation (qgcomp) models were also conducted to evaluate the combined effect of metal and metalloid mixtures concentration. Results Of the 275 elderly people included in the analysis, we found that higher urinary Cu concentration was positively associated with UACR using GLM (β = 0.36, 95% CI: 0.25, 0.46). Using the BKMR model, we found that the change in UACR was positively associated with a change in urinary Cu concentration from its 25th to 75th percentile value with all other metals and metalloids concentration fixed at their 25th, 50th, or 75th percentile levels. Urinary Cu concentration had the most significant positive contribution (59.15%) in the qgcomp model. Our finding was largely robust in three mixture modeling approaches: GLM, qgcomp, and BKMR. Conclusion This finding suggests that urinary Cu concentration was strongly positively associated with UACR. Further analyses in cohort studies are required to corroborate this finding.
Collapse
Affiliation(s)
- Ang Li
- Department of Epidemiology and Biostatistics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing, China
- Center of Environmental and Health Sciences, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, China
| | - Jiaxin Zhao
- Department of Epidemiology and Biostatistics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing, China
- Center of Environmental and Health Sciences, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, China
| | - Liu Liu
- Chaoyang District Center for Disease Control and Prevention, Beijing, China
| | - Yayuan Mei
- Department of Epidemiology and Biostatistics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing, China
- Center of Environmental and Health Sciences, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, China
| | - Quan Zhou
- Department of Epidemiology and Biostatistics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing, China
- Center of Environmental and Health Sciences, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, China
| | - Meiduo Zhao
- Department of Epidemiology and Biostatistics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing, China
- Center of Environmental and Health Sciences, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, China
| | - Jing Xu
- Department of Epidemiology and Biostatistics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing, China
- Center of Environmental and Health Sciences, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, China
| | - Xiaoyu Ge
- Department of Epidemiology and Biostatistics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing, China
- Center of Environmental and Health Sciences, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, China
| | - Qun Xu
- Department of Epidemiology and Biostatistics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing, China
- Center of Environmental and Health Sciences, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, China
- *Correspondence: Qun Xu
| |
Collapse
|
13
|
Wang W, Zhang W, Hu D, Li L, Cui L, Liu J, Liu S, Xu J, Wu S, Deng F, Guo X. Short-term ozone exposure and metabolic status in metabolically healthy obese and normal-weight young adults: A viewpoint of inflammatory pathways. JOURNAL OF HAZARDOUS MATERIALS 2022; 424:127462. [PMID: 34653859 DOI: 10.1016/j.jhazmat.2021.127462] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/27/2021] [Revised: 09/09/2021] [Accepted: 10/06/2021] [Indexed: 06/13/2023]
Abstract
Unhealthy metabolic status increases risks of cardiovascular and other diseases. This study aims to explore whether there is a link between O3 and metabolic health indicators through a viewpoint of inflammatory pathways. 49 metabolically healthy normal-weight (MH-NW) and 39 metabolically healthy obese (MHO) young adults aged 18-26 years were recruited from a panel study with three visits. O3 exposure were estimated based on fixed-site environmental monitoring data and time-activity diary for each participant. Compared to MH-NW people, MHO people were more susceptible to the adverse effects on metabolic status, including blood pressure, glucose, and lipid indicators when exposed to O3. For instance, O3 exposure was associated with significant decreases in high-density lipoprotein cholesterol (HDL-C), and increases in C-peptide and low-density lipoprotein cholesterol (LDL-C) among MHO people, while only weaker changes in HDL-C and LDL-C among MH-NW people. Mediation analyses indicated that leptin mediated the metabolic health effects in both groups, while eosinophils and MCP-1 were also important mediating factors for the MHO people. Although both with a metabolically healthy status, compared to normal-weight people, obese people might be more susceptible to the negative effects of O3 on metabolic status, possibly through inflammatory indicators such as leptin, eosinophils, and MCP-1.
Collapse
Affiliation(s)
- Wanzhou Wang
- Department of Occupational and Environmental Health Sciences, School of Public Health, Peking University, Beijing 100191, China
| | - Wenlou Zhang
- Department of Occupational and Environmental Health Sciences, School of Public Health, Peking University, Beijing 100191, China
| | - Dayu Hu
- Department of Occupational and Environmental Health Sciences, School of Public Health, Peking University, Beijing 100191, China
| | - Luyi Li
- Department of Occupational and Environmental Health Sciences, School of Public Health, Peking University, Beijing 100191, China
| | - Liyan Cui
- Department of Laboratory Medicine, Peking University Third Hospital, Beijing 100191, China
| | - Junxiu Liu
- Department of Otolaryngology Head and Neck Surgery, Peking University Third Hospital, Beijing 100191, China
| | - Shan Liu
- Department of Occupational and Environmental Health Sciences, School of Public Health, Peking University, Beijing 100191, China
| | - Junhui Xu
- Department of Occupational and Environmental Health Sciences, School of Public Health, Peking University, Beijing 100191, China
| | - Shaowei Wu
- Department of Occupational and Environmental Health, School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an, Shaanxi, China
| | - Furong Deng
- Department of Occupational and Environmental Health Sciences, School of Public Health, Peking University, Beijing 100191, China.
| | - Xinbiao Guo
- Department of Occupational and Environmental Health Sciences, School of Public Health, Peking University, Beijing 100191, China
| |
Collapse
|
14
|
Zhang W, Liu J, Hu D, Li L, Cui L, Xu J, Wang W, Deng F, Guo X. Joint effect of multiple air pollutants on lipid profiles in obese and normal-weight young adults: The key role of ozone. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2022; 292:118247. [PMID: 34624398 DOI: 10.1016/j.envpol.2021.118247] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/03/2021] [Revised: 09/24/2021] [Accepted: 09/25/2021] [Indexed: 06/13/2023]
Abstract
Dyslipidemia may be a potential mechanism linking air pollution to adverse cardiovascular outcomes and this may differ among obese and normal-weight populations. However, the joint effect of multiple air pollutants on lipid profiles and the role of each pollutant are still unclear. This panel study aims to investigate and compare the overall associations of major air pollutants with lipid parameters in obese and normal-weight adults, and assess the relative importance of each pollutant for lipid parameters. Forty-four obese and 53 normal-weight young adults were recruited from December 2017 to June 2018 in Beijing, China. Their fasting blood was collected and serum lipid levels were measured in three visits. Six major air pollutants were included in this study, which were PM2.5, PM10, NO2, SO2, O3 and CO. Bayesian kernel machine regression (BKMR) was implemented to estimate the joint effect of the six air pollutants on various lipid parameters. We found that decreased high-density lipoprotein cholesterol (HDL-C) in the obese group and increased low-density lipoprotein cholesterol (LDL-C) and non-HDL-C in the normal-weight group were associated with the exposure to the mixture of six air pollutants above. Significant increases in total cholesterol (TC)/HDL-C and non-HDL-C/HDL-C were observed in both groups, and the effect was stronger in obese group. Of the six air pollutants above, O3 had the largest posterior inclusion probability in above lipid indices, ranging from 0.75 to 1.00. In the obese group, approximately linear exposure-response relationships were observed over the whole range of logarithmic O3-8 h max concentration, while in the normal-weight group, these relationships existed when the logarithmic concentration exceeded about 2.8. Therefore, lipid profiles of obese adults may be more sensitive to air pollution and this study highlights the importance of strengthening emissions control efforts for O3 in the future.
Collapse
Affiliation(s)
- Wenlou Zhang
- Department of Occupational and Environmental Health Sciences, School of Public Health, Peking University, Beijing, 100191, China
| | - Junxiu Liu
- Department of Otolaryngology Head and Neck Surgery, Peking University Third Hospital, Beijing, 100191, China
| | - Dayu Hu
- Department of Occupational and Environmental Health Sciences, School of Public Health, Peking University, Beijing, 100191, China
| | - Luyi Li
- Department of Occupational and Environmental Health Sciences, School of Public Health, Peking University, Beijing, 100191, China
| | - Liyan Cui
- Department of Laboratory Medicine, Peking University Third Hospital, Beijing, 100191, China
| | - Junhui Xu
- Department of Occupational and Environmental Health Sciences, School of Public Health, Peking University, Beijing, 100191, China
| | - Wanzhou Wang
- Department of Occupational and Environmental Health Sciences, School of Public Health, Peking University, Beijing, 100191, China
| | - Furong Deng
- Department of Occupational and Environmental Health Sciences, School of Public Health, Peking University, Beijing, 100191, China.
| | - Xinbiao Guo
- Department of Occupational and Environmental Health Sciences, School of Public Health, Peking University, Beijing, 100191, China
| |
Collapse
|
15
|
Li A, Zhou Q, Xu Q. Prospects for ozone pollution control in China: An epidemiological perspective. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2021; 285:117670. [PMID: 34380231 DOI: 10.1016/j.envpol.2021.117670] [Citation(s) in RCA: 25] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/11/2021] [Revised: 06/17/2021] [Accepted: 06/26/2021] [Indexed: 06/13/2023]
Abstract
Severe surface ozone pollution has become widespread in China. To protect public health, Chinese scientific communities and government agencies have striven to mitigate ozone pollution. However, makers of pollution mitigation policies rarely consider epidemiological research, and communication between epidemiological researchers and the government is poor. Therefore, this article reviews the current mitigation policies and the National Ambient Air Quality Standard (NAAQS) for ozone from an epidemiological perspective and proposes recommendations for researchers and policy makers on the basis of epidemiological evidence. We review current nationwide ozone control measures for mitigating ozone pollution from four dimensions: the integration of ozone and particulate matter control, ozone precursors control, ozone control in different seasons, and regional cooperation on the prevention of ozone pollution. In addition, we present environmental and epidemiological evidence and propose recommendations and discuss relevant ozone metrics and the criteria values of the NAAQS. We finally conclude that the disease burden attributable to ozone exposure in China may be underestimated and that the epidemiological research regarding the health effects of integrating ozone and particulate matter control is insufficient. Furthermore, atmospheric volatile organic compounds are severely detrimental to health, and related control policies are urgently required in China. We recommend a greater focus on winter ozone pollution and conclude that the health benefits of regional cooperation on ozone control and prevention are salient. We argue that daily average ozone concentration may be a more biologically relevant ozone metric than those currently used by the NAAQS, and accumulating epidemiological evidence supports revision of the standards. This review provides new insight for ozone mitigation policies and related epidemiological studies in China.
Collapse
Affiliation(s)
- Ang Li
- Department of Epidemiology and Biostatistics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing, 100005, China; Center of Environmental and Health Sciences, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, 100005, China
| | - Quan Zhou
- Department of Epidemiology and Biostatistics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing, 100005, China; Center of Environmental and Health Sciences, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, 100005, China
| | - Qun Xu
- Department of Epidemiology and Biostatistics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing, 100005, China; Center of Environmental and Health Sciences, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, 100005, China.
| |
Collapse
|
16
|
Zheng S, Zhu W, Shi Q, Wang M, Nie Y, Zhang D, Cheng Z, Yin C, Miao Q, Luo Y, Bai Y. Effects of cold and hot temperature on metabolic indicators in adults from a prospective cohort study. THE SCIENCE OF THE TOTAL ENVIRONMENT 2021; 772:145046. [PMID: 33581536 DOI: 10.1016/j.scitotenv.2021.145046] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/26/2020] [Revised: 12/23/2020] [Accepted: 01/03/2021] [Indexed: 06/12/2023]
Abstract
BACKGROUND Previous studies have found that exposed to low and high outdoor temperature was associated with cardiovascular diseases morbidity and mortality. The risk factors for cardiovascular disease include high blood lipid, high uric acid (UA) and high fasting plasma glucose (FPG). However, few studies have explored the effects of low and high temperature on these metabolic indicators. OBJECTIVE To explore the effect of low and high temperature on metabolic indicators in adults from northwest of China. METHODS Based on a prospective cohort study, a total of 30,759 individuals who participated in both baseline and first follow-up from 2011 to 2015 were selected in this study. The meteorological observation data and environmental monitoring data were collected in the same period. Associations between cold and hot temperature and blood lipid (total cholesterol (TC), triglycerides (TG), low density lipoprotein-cholesterol (LDL-C), and high density lipoprotein-cholesterol (HDL-C)), UA and FPG were conducted with mixed effect models after adjusting for confounding factors. RESULTS A nonlinear relationship between outdoor temperature and metabolic indicators was found. For the cold effects, each 5 °C decrease of mean temperature was associated with an increase of 5.07% (95% CI: 3.52%, 6.63%) in TG and 2.85% (95% CI: 2.18%, 3.53%) in UA, While a decrease of 3.38% (95% CI: 2.67%, 4.09%) in HDL-C and 1.26% (95% CI: 0.48%, 2.04%) in LDL-C. For the heat effects, each 5 °C increase in mean temperature was associated with 1.82% (95% CI: 0.89%, 2.76%), 0.56% (95% CI: 0.11%, 1.00%), 5.82% (95% CI: 4.58%, 7.06%), 9.02% (95% CI: 7.17%, 10.87%), 0.20% (95% CI: 0.01%, 0.40%), and 1.22% (95% CI: 0.19%, 2.24%) decrease in TC, TG, HDL-C, LDL-C, UA and FPG. Age, smoking, drinking, high-oil diet and hyperlipidemia might modify the association between mean temperature and metabolic indicators. CONCLUSION There was a significant effect of cold and hot temperature on metabolic indicators in a high altitude area of northwestern China. These results provide a basis for understanding the underlying mechanism of the influence of temperature on metabolic diseases.
Collapse
Affiliation(s)
- Shan Zheng
- Institute of Epidemiology and Statistics, School of Public Health, Lanzhou University, Lanzhou 73000, China.
| | - Wenzhi Zhu
- Institute of Epidemiology and Statistics, School of Public Health, Lanzhou University, Lanzhou 73000, China
| | - Qin Shi
- Institute of Epidemiology and Statistics, School of Public Health, Lanzhou University, Lanzhou 73000, China
| | - Minzhen Wang
- Institute of Epidemiology and Statistics, School of Public Health, Lanzhou University, Lanzhou 73000, China
| | - Yonghong Nie
- Jinchang Center for Disease Prevention and Control, Jinchang 737100, China
| | - Desheng Zhang
- Workers' Hospital of Jinchuan Group Co., Ltd., Jinchang 737103, China
| | - Zhiyuan Cheng
- School of Public Health, Brown University, Providence, RI 02903, USA
| | - Chun Yin
- Workers' Hospital of Jinchuan Group Co., Ltd., Jinchang 737103, China
| | - Qian Miao
- Institute of Epidemiology and Statistics, School of Public Health, Lanzhou University, Lanzhou 73000, China
| | - Yan Luo
- Institute of Epidemiology and Statistics, School of Public Health, Lanzhou University, Lanzhou 73000, China
| | - Yana Bai
- Institute of Epidemiology and Statistics, School of Public Health, Lanzhou University, Lanzhou 73000, China.
| |
Collapse
|
17
|
Li A, Mei Y, Zhao M, Xu J, Li R, Zhao J, Zhou Q, Ge X, Xu Q. Associations between air pollutant exposure and renal function: A prospective study of older adults without chronic kidney disease. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2021; 277:116750. [PMID: 33676338 DOI: 10.1016/j.envpol.2021.116750] [Citation(s) in RCA: 25] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/13/2020] [Revised: 02/10/2021] [Accepted: 02/12/2021] [Indexed: 06/12/2023]
Abstract
We used real-world exposure scenarios to evaluate the effect of six ambient air pollutant (PM2.5, PM10, NO2, SO2, CO, and O3) exposure on renal function among older adults without chronic kidney disease (CKD). We recruited 169 older adults without CKD in Beijing, China, for a longitudinal study from 2016 to 2018. The Modification of Diet in Renal Disease (MDRD) and the Chronic Kidney Disease Epidemiology Collaboration (EPI) equations were employed to derive the estimated glomerular filtration rate (eGFR). A linear mixed-effects model with random intercepts for participants was employed to determine the effects of air pollutants on renal function evaluated on the basis of eGFR and urinary albumin/creatinine ratio at different exposure windows (1-, 2-, 3-, 5-, 7-, 14-, 28-, 45-, and 60-days moving averages). An interquartile range (IQR) increase in NO2 for was associated with significant decreases of in eGFR (MDRD equation) [percentage changes: -4.49 (95% confidence interval: -8.44, -0.37), -5.51 (-10.43, -0.33), -2.26 (-4.38, -0.08), -3.71 (-6.67, -0.65), -5.44 (-9.58, -1.11), -5.50 (-10.24, -0.51), -6.15 (-10.73, -1.33), and -6.34 (-11.17, -1.25) for 1-, 2-, 5-, 7-, 14-, 28-, 45-, and 60-days moving averages, respectively] and in eGFR (EPI equation) [percentage changes: -5.04 (-7.09, -2.94), -6.25 (-8.81, -3.62), -5.16 (-7.34, -2.92), -5.10 (-7.85, -2.28), -5.83 (-8.23, -3.36), -6.04 (-8.55, -3.47) for 1-, 2-, 14-, 28-, 45-, and 60-days moving averages, respectively]. In two-pollutant model, only the association of NO2 exposure with eGFR remained robust after adjustment for any other pollutant. This association was stronger for individuals with hypertension for the EPI equation or BMI <25 kg/m2 for the MDRD equation at lags 1 and 1-2. Our findings suggest that NO2 exposure is associated with eGFR reduction among older adults without CKD for short (1-, 2-days) and medium (14-, 28-, 45-, 60-days) term exposure periods; thus, NO2 exposure may contribute to renal impairment.
Collapse
Affiliation(s)
- Ang Li
- Department of Epidemiology and Biostatistics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing, 100005, China; Center of Environmental and Health Sciences, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, 100005, China
| | - Yayuan Mei
- Department of Epidemiology and Biostatistics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing, 100005, China; Center of Environmental and Health Sciences, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, 100005, China
| | - Meiduo Zhao
- Department of Epidemiology and Biostatistics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing, 100005, China; Center of Environmental and Health Sciences, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, 100005, China
| | - Jing Xu
- Department of Epidemiology and Biostatistics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing, 100005, China; Center of Environmental and Health Sciences, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, 100005, China
| | - Runkui Li
- College of Resources and Environment, University of Chinese Academy of Sciences, Beijing, 100049, China; State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China
| | - Jiaxin Zhao
- Department of Epidemiology and Biostatistics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing, 100005, China; Center of Environmental and Health Sciences, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, 100005, China
| | - Quan Zhou
- Department of Epidemiology and Biostatistics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing, 100005, China; Center of Environmental and Health Sciences, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, 100005, China
| | - Xiaoyu Ge
- Department of Epidemiology and Biostatistics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing, 100005, China; Center of Environmental and Health Sciences, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, 100005, China
| | - Qun Xu
- Department of Epidemiology and Biostatistics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing, 100005, China; Center of Environmental and Health Sciences, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, 100005, China.
| |
Collapse
|
18
|
Li A, Mei Y, Zhao M, Xu J, Seery S, Li R, Zhao J, Zhou Q, Ge X, Xu Q. The effect of ambient ozone on glucose-homoeostasis: A prospective study of non-diabetic older adults in Beijing. THE SCIENCE OF THE TOTAL ENVIRONMENT 2021; 761:143308. [PMID: 33223186 DOI: 10.1016/j.scitotenv.2020.143308] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/18/2020] [Revised: 10/07/2020] [Accepted: 10/19/2020] [Indexed: 06/11/2023]
Abstract
OBJECTIVE To investigate potential effects of short- and medium-term exposure to low levels of ozone (O3) on glucose-homeostasis in non-diabetic older adults. METHODS 166 non-diabetic, older participants in Beijing were deemed eligible to partake in this longitudinal population-based study. Observations were recorded on three separate occasions from November 2016 up until January 2018. Concentrations of outdoor O3 were monitored throughout the study period. Biomarkers indicative of glucose-homeostasis, including fasting blood glucose, insulin, HbAlc, glycated albumin percentage (glycated albumin/albumin), HOMA-IR and HOMA-B were measured at 3 sessions. A linear mixed effects model with random effects was adopted to quantify the effect of O3 across a comprehensive set of glucose-homeostasis markers. RESULTS Short-term O3 exposure positively associated with increased fasting blood glucose, insulin, HOMA-IR and HOMA-B. The effect on glucose occurred at 3-, 5-, 6- and 7-days, although the largest effect manifested on 6-days (5.6%, 95% CI: 1.4, 9.9). Significant associations with both insulin and HOMA-IR were observed on the 3- and 4-days. For HOMA-B, positive associations were identified from 3- to 7-days with estimates ranging from 40.0% (95% CI: 2.3, 91.5) to 83.1% (95% CI: 25.3, 167.5). Stratification suggests that women may be more susceptible to short-term O3 exposure. There does not appear to be a significant association between O3 and glucose-homeostasis in medium-term exposures. CONCLUSIONS In this study, we found that O3 exposure is at least partially associated with type II diabetes in older adults with no prior history of this condition. O3 therefore appears to be a potential risk factor, which is a particular concern when we consider the rise in global concentrations. Evidence also suggests that women may be more susceptible to short-term O3 exposure although we are not quite sure why. Future research may look to investigate this phenomenon further.
Collapse
Affiliation(s)
- Ang Li
- Department of Epidemiology and Biostatistics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing 100005, China; Center of Environmental and Health Sciences, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing 100005, China
| | - Yayuan Mei
- Department of Epidemiology and Biostatistics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing 100005, China; Center of Environmental and Health Sciences, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing 100005, China
| | - Meiduo Zhao
- Department of Epidemiology and Biostatistics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing 100005, China; Center of Environmental and Health Sciences, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing 100005, China
| | - Jing Xu
- Department of Epidemiology and Biostatistics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing 100005, China; Center of Environmental and Health Sciences, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing 100005, China
| | - Samuel Seery
- School of Humanities and Social Sciences, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100005, China
| | - Runkui Li
- College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China; State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
| | - Jiaxin Zhao
- Department of Epidemiology and Biostatistics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing 100005, China; Center of Environmental and Health Sciences, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing 100005, China
| | - Quan Zhou
- Department of Epidemiology and Biostatistics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing 100005, China; Center of Environmental and Health Sciences, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing 100005, China
| | - Xiaoyu Ge
- Department of Epidemiology and Biostatistics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing 100005, China; Center of Environmental and Health Sciences, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing 100005, China
| | - Qun Xu
- Department of Epidemiology and Biostatistics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing 100005, China; Center of Environmental and Health Sciences, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing 100005, China.
| |
Collapse
|
19
|
Analysis on the Temporal Distribution Characteristics of Air Pollution and Its Impact on Human Health under the Noticeable Variation of Residents' Travel Behavior: A Case of Guangzhou, China. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2020; 17:ijerph17144947. [PMID: 32659942 PMCID: PMC7399817 DOI: 10.3390/ijerph17144947] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/07/2020] [Accepted: 07/07/2020] [Indexed: 12/14/2022]
Abstract
During the large-scale outbreak of COVID-19 in China, the Chinese government adopted multiple measures to prevent the epidemic. The consequence was that a sudden variation in residents' travel behavior took place. In order to better evaluate the temporal distribution of air pollution, and to effectively explore the influence of human activities on air quality, especially under the special situation, this study was conducted based on the real data from a case city in China from this new perspective. Two case scenarios were constructed, in which the research before the changes of residents' travel behavior was taken as case one, and the research after the changes in residents' travel behavior as case two. The hourly real-time concentrations of PM2.5, PM10, SO2, NO2, CO and O3 that have passed the augmented Dickey-Fuller (ADF) test were employed as a data source. A series of detailed studies have been carried out using the correlation method, entropy weight method and the Air Quality Index (AQI) calculation method. Additionally, the research found that the decrease rate of NO2 concentration is 61.05%, and the decrease rate of PM10 concentration is 53.68%. On the contrary, the average concentration of O3 has increased significantly, and its growth rate has reached to 9.82%. Although the air quality in the first week with fewer travels was in the excellent category, and chief pollutant (CP), as well as excessive pollutant (EP), were not found, as traffic volume increased, it became worse in the second and third weeks. In addition to that, special attention should still be paid to the development trend of O3, as its average hourly concentration has increased. The findings of this study will have some guiding significance for the study of air pollution prevention, cleaner production, and indoor environmental safety issues, especially for the study of abnormal traffic environments where residents' travel behaviors have changed significantly.
Collapse
|