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Hughes F, Parsons L, Levy JH, Shindell D, Alhanti B, Ohnuma T, Kasibhatla P, Montgomery H, Krishnamoorthy V. Impact of Wildfire Smoke on Acute Illness. Anesthesiology 2024; 141:779-789. [PMID: 39105660 DOI: 10.1097/aln.0000000000005115] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/07/2024]
Abstract
Climate change increases wildfire smoke exposure. Inhaled smoke causes inflammation, oxidative stress, and coagulation, which exacerbate cardiovascular and respiratory disease while worsening obstetric and neonatal outcomes.
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Affiliation(s)
- Fintan Hughes
- Department of Anesthesiology, Duke University School of Medicine, Durham, North Carolina
| | - Luke Parsons
- Global Science, Nature Conservancy and Nicholas School of the Environment, Duke University, Durham, North Carolina
| | - Jerrold H Levy
- Departments of Anesthesiology and Surgery (Cardiothoracic), Duke University School of Medicine, Durham, North Carolina
| | - Drew Shindell
- Nicholas School of the Environment, Duke University, Durham, North Carolina
| | - Brooke Alhanti
- Duke Clinical Research Institute, Duke University, Durham, North Carolina
| | - Tetsu Ohnuma
- Department of Anesthesiology, Duke University School of Medicine, Durham, North Carolina
| | - Prasad Kasibhatla
- Nicholas School of the Environment, Duke University, Durham, North Carolina
| | - Hugh Montgomery
- Department of Intensive Care Medicine, University College London, London, United Kingdom
| | - Vijay Krishnamoorthy
- Department of Anesthesiology, Duke University School of Medicine, Durham, North Carolina
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Sun Z, Chen L, Liu Z, Feng L, Cui Y, Zhang X, Wu Y, Zhang J. Modifying effects of green space on the relationships between air pollution and ischemic cerebrovascular event recurrence in Tianjin, China. INTERNATIONAL JOURNAL OF ENVIRONMENTAL HEALTH RESEARCH 2024; 34:3648-3658. [PMID: 38357761 DOI: 10.1080/09603123.2024.2314636] [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: 08/28/2023] [Accepted: 02/01/2024] [Indexed: 02/16/2024]
Abstract
This study aimed to explore how air pollution and green space influence ICE recurrence and whether they might interact with each other. A case-cross design was used in this study, which was carried out in Tianjin, China. A total of 8306 patients with recurrent ICE were collected from 2019 to 2020. The maximum effects of PM2.5, PM10, SO2, NO2, CO were 1.012 (95%CI: 1.004, 1.019), 1.010 (95%CI: 1.004, 1.016), 1.035 (95%CI: 0.982, 1.091), 1.067 (95%CI: 1.043, 1.091) and 1.012 (95%CI: 1.004, 1.021) , respectively, and the risk was higher in males and in the 50-60 age group. In the stratification of greening, it was found that air pollution except O3 had the highest risk of ICE recurrence for those with lower green space. Our study found that air pollution (except O3) can increase the risk of ICE recurrence, and this risk can be reduced by increasing green space.
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Affiliation(s)
- Zhiying Sun
- Environmental Health and School Health, Tianjin Centers for Disease Control and Prevention, Tianjin, China
| | - Lu Chen
- Environmental Health and School Health, Tianjin Centers for Disease Control and Prevention, Tianjin, China
| | - Zhonghui Liu
- Environmental Health and School Health, Tianjin Centers for Disease Control and Prevention, Tianjin, China
| | - Lihong Feng
- Environmental Health and School Health, Tianjin Centers for Disease Control and Prevention, Tianjin, China
| | - Yushan Cui
- Environmental Health and School Health, Tianjin Centers for Disease Control and Prevention, Tianjin, China
| | - Xianwei Zhang
- Environmental Health and School Health, Tianjin Centers for Disease Control and Prevention, Tianjin, China
| | - Yan Wu
- Environmental Health and School Health, Tianjin Centers for Disease Control and Prevention, Tianjin, China
| | - Jingwei Zhang
- Environmental Health and School Health, Tianjin Centers for Disease Control and Prevention, Tianjin, China
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Wu P, Guo Q, Zhao Y, Bian M, Wang G, Wu W, Shao J, Wang Q, Duan X, Zhang JJ. Construction of a minute ventilation model to address inter-individual inhaled dose variability within identical exposure scenarios using wearable devices. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 954:176415. [PMID: 39312972 DOI: 10.1016/j.scitotenv.2024.176415] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/15/2024] [Revised: 09/18/2024] [Accepted: 09/18/2024] [Indexed: 09/25/2024]
Abstract
Inhaled dose is crucial for accurately assessing exposure to air pollution, determined by pollutant concentration and minute ventilation (VE). However, the VE predictive models and its application to assess the health effects of air pollution are still lacking. In this study, we developed VE predictive models using machine learning techniques, utilizing data obtained from eighty participants who underwent a laboratory cardiopulmonary exercise test (CPET). VE predictive models were developed using generalized additive model (GAM), random forest model (RF) and extreme gradient boosting (XGBoost) and analyzed for explanation of input variables. The Random Forest model, cross-validated, exhibited outstanding performance with an R2 of 0.986 and a MAE of 1.816 L/min. The median difference between the measured VE and the predicted VE was 0.18 L/min, and the median difference between the black carbon (BC) inhaled dose based on predicted VE and measured VE was 0.02 ng. Employing explainable machine learning, the results showed that metabolic equivalent (METs), heart rate, and body weight are the three top important variables, emphasizing the significance of incorporating METs variables when constructing VE models. Through multiple linear regression models and an adjusted stratified analysis model, the significant adverse association between BC concentration and inhaled dose on diastolic blood pressure (DBP) was only observed in female. The disparity in the effect of BC inhaled dose compared to BC concentration on DBP reached up to 115 %. This study is the first to explore the ability of different machine learning algorithms to construct VE prediction models and directly apply the models to assess health effects of an example pollutant. This study contributes to the accurate assessment of air pollution exposure leveraging wearable devices, an approach useful for environmental epidemiology studies.
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Affiliation(s)
- Pengpeng Wu
- School of Energy and Environmental Engineering, University of Science and Technology Beijing, Beijing 100083, China
| | - Qian Guo
- China North Artificial Intelligence & Innovation Research Institute, Beijing 100072. China; Collective Intelligence & Collaboration Laboratory, Beijing 100072, China
| | - Yuchen Zhao
- School of Energy and Environmental Engineering, University of Science and Technology Beijing, Beijing 100083, China
| | - Mengyao Bian
- School of Energy and Environmental Engineering, University of Science and Technology Beijing, Beijing 100083, China
| | - Gang Wang
- Department of Otolaryngology-Head and Neck Surgery, PLA Strategic Support Force Characteristic Medical Center, Beijing 100101, China
| | - Wei Wu
- Department of Otolaryngology-Head and Neck Surgery, PLA Strategic Support Force Characteristic Medical Center, Beijing 100101, China
| | - Jing Shao
- National Institute of Sports Medicine, General Administration of Sport of China, Beijing 100029, China
| | - Qirong Wang
- National Institute of Sports Medicine, General Administration of Sport of China, Beijing 100029, China
| | - Xiaoli Duan
- School of Energy and Environmental Engineering, University of Science and Technology Beijing, Beijing 100083, China.
| | - Junfeng Jim Zhang
- Nicholas School of the Environment and Global Health Institute, Duke University, Durham, NC 27708, USA; Duke Kunshan University, Kunshan 215316, China
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Chen S, Zhang Y, Wei J, Hao C, Wu W, Li Z, Guo T, Lin Z, Zhang W, Hao Y. Risk of stroke admission after long-term exposure to PM 1: Evidence from a large cohort in South China. ECOTOXICOLOGY AND ENVIRONMENTAL SAFETY 2024; 283:116720. [PMID: 39053181 DOI: 10.1016/j.ecoenv.2024.116720] [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: 01/21/2024] [Revised: 07/04/2024] [Accepted: 07/09/2024] [Indexed: 07/27/2024]
Abstract
BACKGROUND Limited attention has been paid to the health effects of long-term PM1 exposure on stroke admission. Current investigations exploring the long-term PM exposure effect are largely based on observational studies, and PM generally is not allocated randomly to participants. Using traditional regression models might confuse messaging and hinder policy recommendations for pollution control and disease prevention policies. METHODS We conducted a cohort study among 36,271 adults from one of the largest cities in China in 2015 and followed up through 2020. Hazard ratios of stroke admissions following long-term PM1 exposure were estimated via a causal inference approach, marginal structural time-varying Cox proportional hazard model, accounting for multiple confounders. Additionally, several sensitivity analyses and impact modification analyses were carried out. RESULTS AND DISCUSSION Associations with 1 μg/m3 increase in long-term PM1 were identified for total (HR, 1.079; 95 %CI, 1.012-1.151) and ischemic stroke admissions (HR, 1.092; 95 %CI, 1.018-1.171). The harmful associations varied with exposure duration, initially increasing and then decreasing. The 2-3 years cumulative exposure was associated with a 3.3-5.4 % raised risk for total stroke. For every 1 μg/m³ increase in long-term PM1 exposure, females exhibited a higher risk of both total and ischemic stroke (13 % and 16 %) than men (4 % and 5 %). Low-exposure individuals (whose annual PM1 concentrations were under the third quartile among the annual concentrations for all the participants) exhibited greater sensitivity to PM1 effects (total stroke: 1.079 vs. 1.107; ischemic stroke: 1.092 vs. 1.116). The results underline the importance of safeguarding low-exposed people in highly polluted areas and suggest that long-term PM1 exposure may increase stroke admission risk, warranting attention to vulnerable groups.
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Affiliation(s)
- 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
| | - Jing Wei
- Department of Atmospheric and Oceanic Science, Earth System Science Interdisciplinary Center, University of Maryland, College Park, MD, USA
| | - Chun Hao
- 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
| | - Zhiqiang Li
- 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
| | - Tong Guo
- 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
| | - Ziqiang Lin
- Department of Preventive Medicine, School of Basic Medicine and Public Health, Jinan University, Guangzhou, 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.
| | - Yuantao Hao
- Peking University Center for Public Health and Epidemic Preparedness & Response, Peking, China; Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, China.
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Chen Z, Zhu M, Ni W, Wu B, Liu T, Lin B, Lai L, Jing Y, Jiang L, Ouyang Z, Hu J, Zheng H, Peng W, Yu X, Fan J. Association of PM 2.5 exposure in early pregnancy and maternal liver function: A retrospective cohort study in Shenzhen, China. ENVIRONMENTAL RESEARCH 2024; 263:119934. [PMID: 39276834 DOI: 10.1016/j.envres.2024.119934] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/02/2024] [Revised: 09/02/2024] [Accepted: 09/03/2024] [Indexed: 09/17/2024]
Abstract
OBJECTIVE Studies have shown that fine particulate matter (PM2.5) has adverse effects on the liver function, but epidemiological evidence is limited, especially regarding pregnant women. This study aims to investigate the association between PM2.5 exposure in early pregnancy and maternal liver function during pregnancy. METHODS This retrospective cohort study included 13,342 pregnant participants. PM2.5 and Ozone (O3) exposure level, mean temperature, and relative humidity for each participant were assessed according to their residential address. The levels of serum aspartate aminotransferase (AST), alanine aminotransferase (ALT), and total bilirubin (TBIL) were measured during the second and third trimesters. Data on PM2.5 and O3 exposure level were sourced from Tracking Air Pollution in China (TAP), while the mean temperature and relative humidity were obtained from the ERA5 dataset. The Generalized Additive Model (GAM) was used to analyze the associations between PM2.5 exposure and maternal liver function during pregnancy, adjusting for potential confounding factors. RESULTS According to the results, each 10 μg/m3 increase in PM2.5 was associated with an increase of 3.57% (95% CI: 0.29%, 6.96%) in ALT and 4.25% (95% CI: 2.33%, 6.21%) in TBIL during the second trimester and 4.51% (95% CI: 2.59%, 6.47%) in TBIL during the third trimester, respectively. After adjusting for O3, these associations remained significant, and the effect of PM2.5 on ALT during the second trimester was further strengthened. No significant association observed between PM2.5 and AST. CONCLUSIONS PM2.5 exposure in early pregnancy is associated with increasement of maternal ALT and TBIL, suggesting that PM2.5 exposure may have an adverse effect on maternal liver function. Although this finding indicates an association between PM2.5 exposure and maternal liver function, more research is needed to confirm our findings and explore the underlying biological mechanisms.
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Affiliation(s)
- Zhijian Chen
- Department of Preventive Healthcare, Shenzhen Maternity and Child Healthcare Hospital, Shenzhen 518028, China; Faculty of Medicine, Macau University of Science and Technology, Avenida Wai Long, Taipa, Macau, China
| | - Minting Zhu
- School of Public Health, Southern Medical University, Guangzhou 510515, China
| | - Weigui Ni
- Department of Preventive Healthcare, Shenzhen Maternity and Child Healthcare Hospital, Shenzhen 518028, China
| | - Bo Wu
- Department of Preventive Healthcare, Shenzhen Maternity and Child Healthcare Hospital, Shenzhen 518028, China
| | - Tao Liu
- China Greater Bay Area Research Center of Environmental Health, School of Medicine, Jinan University, Guangzhou 510632, China; Key Laboratory of Viral Pathogenesis & Infection Prevention and Control, Jinan University, Ministry of Education, Guangzhou 510632, China
| | - Bingyi Lin
- Department of Preventive Healthcare, Shenzhen Maternity and Child Healthcare Hospital, Shenzhen 518028, China
| | - Lijuan Lai
- Department of Preventive Healthcare, Shenzhen Maternity and Child Healthcare Hospital, Shenzhen 518028, China
| | - Yi Jing
- Department of Preventive Healthcare, Shenzhen Maternity and Child Healthcare Hospital, Shenzhen 518028, China
| | - Long Jiang
- Department of Preventive Healthcare, Shenzhen Maternity and Child Healthcare Hospital, Shenzhen 518028, China
| | - Zhongai Ouyang
- Department of Preventive Healthcare, Shenzhen Maternity and Child Healthcare Hospital, Shenzhen 518028, China; School of Public Health, Southern Medical University, Guangzhou 510515, China
| | - Jianxiong Hu
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou 510632, China
| | - Haoqu Zheng
- Faculty of Medicine, Macau University of Science and Technology, Avenida Wai Long, Taipa, Macau, China
| | - Wan Peng
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou 510632, China
| | - Xi Yu
- Faculty of Medicine, Macau University of Science and Technology, Avenida Wai Long, Taipa, Macau, China.
| | - Jingjie Fan
- Department of Preventive Healthcare, Shenzhen Maternity and Child Healthcare Hospital, Shenzhen 518028, China.
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Abelenda-Alonso G, Satorra P, Marí-Dell'Olmo M, Tebé C, Padullés A, Vergara A, Gudiol C, Pujol M, Carratalà J. Short-Term Exposure to Ambient Air Pollution and Antimicrobial Use for Acute Respiratory Symptoms. JAMA Netw Open 2024; 7:e2432245. [PMID: 39240563 PMCID: PMC11380104 DOI: 10.1001/jamanetworkopen.2024.32245] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 09/07/2024] Open
Abstract
Importance Ambient air pollution and antimicrobial resistance pose significant global public health challenges. It is not known whether ambient air pollution is associated with increased consumption of antimicrobials. Objective To assess whether a short-term association exists between ambient air pollution levels and antimicrobial consumption among the general population seeking primary care consultations for acute respiratory symptoms. Design, Setting, and Participants This 2-stage cross-sectional ecological time series analysis study using data on daily ambient air pollution and antimicrobial consumption was conducted in the 11 largest cities in Catalonia, Spain, from June 23, 2012, to December 31, 2019, among all inhabitants aged 12 years or older. Statistical analysis was performed from November 2022 to December 2023. Exposures Daily ambient air pollution (particulate matter of 10 μg/m3 [PM10], particulate matter of 2.5 μg/m3 [PM2.5], and nitrogen dioxide [NO2]). Main Outcomes and Measures The main outcome was antimicrobial consumption associated with primary care consultations for acute respiratory symptoms in the 30 days before and after the dispensing of the antimicrobial. Antimicrobial consumption was measured as defined daily doses (DDDs) per 1000 inhabitants per day. Results Among 1 938 333 inhabitants (median age, 48 years [IQR, 34-65 years]; 55% female participants), there were 8 421 404 antimicrobial dispensations, with a median of 12.26 DDDs per 1000 inhabitants per day (IQR, 6.03-15.32 DDDs per 1000 inhabitants per day). The median adjusted morbidity score was 2.0 (IQR, 1.0-5.0). For the 1 924 814 antimicrobial dispensations associated with primary care consultations for acute respiratory symptoms, there was a significant correlation between increases of 10 μg/m3 in the concentration of the 3 pollutants studied and heightened antimicrobial consumption at day 0 (PM10: relative risk [RR], 1.01 [95% CI, 1.01-1.02]; PM2.5: RR, 1.03 [95% CI, 1.01-1.04]; NO2: RR, 1.04 [95% CI, 1.03-1.05]). A delayed association emerged between increases in PM2.5 concentration and antimicrobial consumption between day 7 (RR, 1.00 [95% CI, 1.00-1.01]) and day 10 (RR, 1.00 [95% CI, 1.00-1.01]) after exposure. Conclusions and Relevance In this 2-stage cross-sectional study using ecological time series analysis, short-term exposure to air pollution was associated with increased antimicrobial use associated with primary care consultations for acute respiratory symptoms in the general population. This finding could contribute to informing policy decisions aimed at reducing air pollution and its associated risks, thereby promoting respiratory health and reducing antimicrobial use.
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Affiliation(s)
- Gabriela Abelenda-Alonso
- Department of Infectious Diseases, Bellvitge University Hospital, L'Hospitalet de LLobregat, Barcelona, Catalonia, Spain
- Bellvitge Biomedical Research Institute (IDIBELL), L'Hospitalet de Llobregat, Barcelona, Catalonia, Spain
- Consortium for Biomedical Research in Infectious Diseases (CIBERINFEC), Instituto de Salud Carlos III, Madrid, Spain
| | - Pau Satorra
- Germans Trias i Pujol Research Institute and Hospital (IGTP), Badalona, Catalonia, Spain
| | - Marc Marí-Dell'Olmo
- Public Health Agency of Barcelona, Barcelona, Catalonia, Spain
- Sant Pau Biomedical Research Institute (IIB Sant Pau), Barcelona, Catalonia, Spain
- Consortium for Biomedical Research in the Epidemiology and Public Health Network (CIBERESP), Instituto de Salud Carlos III, Madrid, Spain
| | - Cristian Tebé
- Germans Trias i Pujol Research Institute and Hospital (IGTP), Badalona, Catalonia, Spain
| | - Ariadna Padullés
- Bellvitge Biomedical Research Institute (IDIBELL), L'Hospitalet de Llobregat, Barcelona, Catalonia, Spain
- Consortium for Biomedical Research in Infectious Diseases (CIBERINFEC), Instituto de Salud Carlos III, Madrid, Spain
- Department of Pharmacy, Bellvitge University Hospital, L'Hospitalet de Llobregat, Barcelona, Catalonia, Spain
| | - Andrea Vergara
- Department of Microbiology, Hospital Clínic, Barcelona, Catalonia, Spain
| | - Carlota Gudiol
- Department of Infectious Diseases, Bellvitge University Hospital, L'Hospitalet de LLobregat, Barcelona, Catalonia, Spain
- Bellvitge Biomedical Research Institute (IDIBELL), L'Hospitalet de Llobregat, Barcelona, Catalonia, Spain
- Consortium for Biomedical Research in Infectious Diseases (CIBERINFEC), Instituto de Salud Carlos III, Madrid, Spain
- Department of Clinical Sciences, Faculty of Medicine and Health Sciences, University of Barcelona, Barcelona, Catalonia, Spain
| | - Miquel Pujol
- Department of Infectious Diseases, Bellvitge University Hospital, L'Hospitalet de LLobregat, Barcelona, Catalonia, Spain
- Bellvitge Biomedical Research Institute (IDIBELL), L'Hospitalet de Llobregat, Barcelona, Catalonia, Spain
- Consortium for Biomedical Research in Infectious Diseases (CIBERINFEC), Instituto de Salud Carlos III, Madrid, Spain
| | - Jordi Carratalà
- Department of Infectious Diseases, Bellvitge University Hospital, L'Hospitalet de LLobregat, Barcelona, Catalonia, Spain
- Bellvitge Biomedical Research Institute (IDIBELL), L'Hospitalet de Llobregat, Barcelona, Catalonia, Spain
- Consortium for Biomedical Research in Infectious Diseases (CIBERINFEC), Instituto de Salud Carlos III, Madrid, Spain
- Department of Clinical Sciences, Faculty of Medicine and Health Sciences, University of Barcelona, Barcelona, Catalonia, Spain
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Liu Q, Yang S, Chen H. Global trends and hotspots in the study of the effects of PM2.5 on ischemic stroke. JOURNAL OF HEALTH, POPULATION, AND NUTRITION 2024; 43:133. [PMID: 39198927 PMCID: PMC11360839 DOI: 10.1186/s41043-024-00622-3] [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: 06/16/2024] [Accepted: 08/14/2024] [Indexed: 09/01/2024]
Abstract
AIM The objective of this study was to visually analyse global research trends and hotspots regarding the role of PM2.5 in ischemic stroke. METHODS The Web of Science core collection database was used to search the literature on PM2.5 and ischemic stroke from 2006 to 2024. Visualization analysis was conducted using CiteSpace, VOSviewer, and an online bibliometric platform. RESULTS The analysis comprises 190 articles published between 2006 and 2024 by 1229 authors from 435 institutions in 39 countries, across 78 journals. Wellenius GA has the highest number of published and cited papers. China has the highest number of papers, while Canada has the highest citation frequency. Capital Medical University published the highest number of papers, and Harvard University had the highest citation frequency for a single paper. The study investigated the impact of PM2.5 on ischemic stroke in three phases. The first phase analysed hospitalisation rates for correlations. The second phase utilised large-scale multi-cohort data from around the world. The third phase involved studying global exposure risk through machine learning and model construction. Currently, there is limited research on the mechanisms involved, and further in-depth investigation is required. CONCLUSION This paper presents a bibliometric analysis of the research framework and hotspots concerning the effect of PM2.5 on ischemic stroke. The analysis aims to provide a comprehensive understanding of this field for researchers. It is expected that research on the effect of PM2.5 on ischemic stroke will remain an important research topic in the future.
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Affiliation(s)
- Qian Liu
- Cerebrovascular Disease Department, Gansu Provincial Hospital, No.204 West Donggang Road, Lanzhou, 730000, Gansu Province, China
- Key Laboratory of Cerebrovascular Disease of Gansu Province, Gansu Provincial Hospital, Lanzhou, Gansu, China
| | - Shijie Yang
- The First Clinical Medical College of Lanzhou University, Lanzhou, China
| | - HeCheng Chen
- Cerebrovascular Disease Department, Gansu Provincial Hospital, No.204 West Donggang Road, Lanzhou, 730000, Gansu Province, China.
- Key Laboratory of Cerebrovascular Disease of Gansu Province, Gansu Provincial Hospital, Lanzhou, Gansu, China.
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Wang Y, Dang Y, Wang J, Yang S, Sun J, Tu L. A novel hybrid features grey incidence model and its application in identifying key factors influencing air pollution in Jiangsu Province. ENVIRONMENTAL RESEARCH 2024; 262:119820. [PMID: 39181295 DOI: 10.1016/j.envres.2024.119820] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/13/2024] [Revised: 08/01/2024] [Accepted: 08/19/2024] [Indexed: 08/27/2024]
Abstract
Accurately assessing the key factors influencing air pollution is crucial for effective air pollution control. To address this need, we propose a novel Hybrid Features Grey Incidence Model (HFGIM), which integrates geometric feature differences from both proximity and similarity perspectives. Firstly, we extract geometric feature difference vectors of proximity and similarity from time series data and measure the overall feature difference degree by calculating vector norms. Secondly, we calculate the relative feature differences and information contribution rates of proximity and similarity to derive the hybrid feature differences coefficient between sequences, thereby obtaining the hybrid features incidence degree. After detailing the model's properties and modeling steps, we introduce the Cross-sectional Data Hybrid Features Grey Incidence Model (C-HFGIM) and the Panel Data Hybrid Features Grey Incidence Model (P-HFGIM) for handling cross-sectional and panel data, respectively. Applying HFGIM, we identified the key pollutants and primary pollution source indicators of air pollution in Jiangsu Province. We also compared HFGIM with other classical grey incidence models to verify the proposed model's effectiveness. Based on the analysis results, we propose policy recommendations for air pollution control in Jiangsu Province.
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Affiliation(s)
- Yibo Wang
- College of Economics and Management, Nanjing University of Aeronautics and Astronautics, Nanjing, Jiangsu 211106, China.
| | - Yaoguo Dang
- College of Economics and Management, Nanjing University of Aeronautics and Astronautics, Nanjing, Jiangsu 211106, China.
| | - Junjie Wang
- College of Economics and Management, Nanjing University of Aeronautics and Astronautics, Nanjing, Jiangsu 211106, China.
| | - Shaowen Yang
- College of Economics and Management, Nanjing University of Aeronautics and Astronautics, Nanjing, Jiangsu 211106, China.
| | - Jing Sun
- College of Economics and Management, Nanjing University of Aeronautics and Astronautics, Nanjing, Jiangsu 211106, China.
| | - Leping Tu
- College of Economics and Management, Nanjing University of Aeronautics and Astronautics, Nanjing, Jiangsu 211106, China.
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Yu P, Xu R, Wu Y, Huang W, Coelho MSZS, Saldiva PHN, Ye T, Wen B, Liu Y, Yang Z, Li S, Abramson MJ, Guo Y. Cancer mortality risk from short-term PM 2.5 exposure and temporal variations in Brazil. JOURNAL OF HAZARDOUS MATERIALS 2024; 473:134606. [PMID: 38788590 DOI: 10.1016/j.jhazmat.2024.134606] [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: 02/01/2024] [Revised: 04/30/2024] [Accepted: 05/11/2024] [Indexed: 05/26/2024]
Abstract
Although some studies have found that short-term PM2.5 exposure is associated with lung cancer deaths, its impact on other cancer sites is unclear. To answer this research question, this time-stratified case-crossover study used individual cancer death data between January 1, 2000, and December 31, 2019, extracted from the Brazilian mortality information system to quantify the associations between short-term PM2.5 exposure and cancer mortality from 25 common cancer sites. Daily PM2.5 concentration was aggregated at the municipality level as the key exposure. The study included a total of 34,516,120 individual death records, with the national daily mean PM2.5 exposure 15.3 (SD 4.3) μg/m3. For every 10-μg/m3 increase in three-day average PM2.5 exposure, the odds ratio (OR) for all-cancer mortality was 1.04 (95% CI 1.03-1.04). Apart from all-cancer deaths, PM2.5 exposure may impact cancers of oesophagus (1.04, 1.00-1.08), stomach (1.05, 1.02-1.08), colon-rectum (1.04, 1.01-1.06), lung (1.04, 1.02-1.06), breast (1.03, 1.00-1.06), prostate (1.07, 1.04-1.10), and leukaemia (1.05, 1.01-1.09). During the study period, acute PM2.5 exposure contributed to an estimated 1,917,994 cancer deaths, ranging from 0 to 6,054 cases in each municipality. Though there has been a consistent downward trend in PM2.5-related all-cancer mortality risks from 2000 to 2019, the impact remains significant, indicating the continued importance of cancer patients avoiding PM2.5 exposure. This nationwide study revealed a notable association between acute PM2.5 exposure and heightened overall and site-specific cancer mortality for the first time to our best knowledge. The findings suggest the importance of considering strategies to minimize such exposure in cancer care guidelines. ENVIRONMENTAL IMPLICATION: The 20-year analysis of nationwide death records in Brazil revealed that heightened short-term exposure to PM2.5 is associated with increased cancer mortality at various sites, although this association has gradually decreased over time. Despite the declining impact, the research highlights the persistent adverse effects of PM2.5 on cancer mortality, emphasizing the importance of continued research and preventive measures to address the ongoing public health challenges posed by air pollution.
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Affiliation(s)
- Pei Yu
- Climate Air quality Research Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
| | - Rongbin Xu
- Climate Air quality Research Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
| | - Yao Wu
- Climate Air quality Research Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
| | - Wenzhong Huang
- Climate Air quality Research Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
| | - Micheline S Z S Coelho
- Laboratory of Urban Health Insper/Faculty of Medicine of the University of São Paulo, Brazil
| | - Paulo H N Saldiva
- Laboratory of Urban Health Insper/Faculty of Medicine of the University of São Paulo, Brazil
| | - Tingting Ye
- Climate Air quality Research Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
| | - Bo Wen
- Climate Air quality Research Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
| | - Yanming Liu
- Climate Air quality Research Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
| | - Zhengyu Yang
- Climate Air quality Research Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
| | - Shanshan Li
- Climate Air quality Research Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
| | - Michael J Abramson
- Climate Air quality Research Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
| | - Yuming Guo
- Climate Air quality Research Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia.
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10
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Li L, Ran Y, Zhuang Y, Wang L, Chen J, Sun Y, Lu S, Ye F, Mei L, Ning Y, Dai F. Risk analysis of air pollutants and types of anemia: a UK Biobank prospective cohort study. INTERNATIONAL JOURNAL OF BIOMETEOROLOGY 2024; 68:1343-1356. [PMID: 38607561 DOI: 10.1007/s00484-024-02670-0] [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: 02/01/2024] [Revised: 02/01/2024] [Accepted: 04/01/2024] [Indexed: 04/13/2024]
Abstract
Previous studies have suggested that exposure to air pollutants may be associated with specific blood indicators or anemia in certain populations. However, there is insufficient epidemiological data and prospective evidence to evaluate the relationship between environmental air pollution and specific types of anemia. We conducted a large-scale prospective cohort study based on the UK Biobank. Annual average concentrations of NO2, PM2.5, PM2.5-10, and PM10 were obtained from the ESCAPE study using the Land Use Regression (LUR) model. The association between atmospheric pollutants and different types of anemia was investigated using the Cox proportional hazards model. Furthermore, restricted cubic splines were used to explore exposure-response relationships for positive associations, followed by stratification and effect modification analyses by gender and age. After adjusting for demographic characteristics, 3-4 of the four types of air pollution were significantly associated with an increased risk of iron deficiency, vitamin B12 deficiency and folate deficiency anemia, while there was no significant association with other defined types of anemia. After full adjustment, we estimated that the hazard ratios (HRs) of iron deficiency anemia associated with each 10 μg/m3 increase in NO2, PM2.5, and PM10 were 1.04 (95%CI: 1.02, 1.07), 2.00 (95%CI: 1.71, 2.33), and 1.10 (95%CI: 1.02, 1.20) respectively. The HRs of folate deficiency anemia with each 10 μg/m3 increase in NO2, PM2.5, PM2.5-10, and PM10 were 1.25 (95%CI: 1.12, 1.40), 4.61 (95%CI: 2.03, 10.47), 2.81 (95%CI: 1.11, 7.08), and 1.99 (95%CI: 1.25, 3.15) respectively. For vitamin B12 deficiency anemia, no significant association with atmospheric pollution was found. Additionally, we estimated almost linear exposure-response curves between air pollution and anemia, and interaction analyses suggested that gender and age did not modify the association between air pollution and anemia. Our research provided reliable evidence for the association between long-term exposure to PM10, PM2.5, PM2.5-10, NO2, and several types of anemia. NO2, PM2.5, and PM10 significantly increased the risk of iron deficiency anemia and folate deficiency anemia. Additionally, we found that the smaller the PM diameter, the higher the risk, and folate deficiency anemia was more susceptible to air pollution than iron deficiency anemia. No association was observed between the four types of air pollution and hemolytic anemia, aplastic anemia, and other types of anemia. Although the mechanisms are not well understood, we emphasize the need to limit the levels of PM and NO2 in the environment to reduce the potential impact of air pollution on folate and iron deficiency anemia.
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Affiliation(s)
- Laifu Li
- Department of Gastroenterology, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
- Shaanxi Province Key Laboratory of Gastrointestinal Motility Disorders, Xi'an, China
| | - Yan Ran
- Department of Gastroenterology, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
- Shaanxi Province Key Laboratory of Gastrointestinal Motility Disorders, Xi'an, China
| | - Yan Zhuang
- Department of Gastroenterology, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
- Shaanxi Province Key Laboratory of Gastrointestinal Motility Disorders, Xi'an, China
| | - Lianli Wang
- Department of Gastroenterology, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
- Shaanxi Province Key Laboratory of Gastrointestinal Motility Disorders, Xi'an, China
| | - Jiamiao Chen
- Department of Gastroenterology, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
- Shaanxi Province Key Laboratory of Gastrointestinal Motility Disorders, Xi'an, China
| | - Yating Sun
- Department of Gastroenterology, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
- Shaanxi Province Key Laboratory of Gastrointestinal Motility Disorders, Xi'an, China
| | - Shiwei Lu
- Department of Gastroenterology, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
- Shaanxi Province Key Laboratory of Gastrointestinal Motility Disorders, Xi'an, China
| | - Fangchen Ye
- Department of Gastroenterology, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
- Shaanxi Province Key Laboratory of Gastrointestinal Motility Disorders, Xi'an, China
| | - Lin Mei
- Department of Gastroenterology, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
- Shaanxi Province Key Laboratory of Gastrointestinal Motility Disorders, Xi'an, China
| | - Yu Ning
- Department of Gastroenterology, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
- Shaanxi Province Key Laboratory of Gastrointestinal Motility Disorders, Xi'an, China
| | - Fei Dai
- Department of Gastroenterology, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.
- Shaanxi Province Key Laboratory of Gastrointestinal Motility Disorders, Xi'an, China.
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11
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Achebak H, Garatachea R, Pay MT, Jorba O, Guevara M, Pérez García-Pando C, Ballester J. Geographic sources of ozone air pollution and mortality burden in Europe. Nat Med 2024; 30:1732-1738. [PMID: 38830993 PMCID: PMC11186783 DOI: 10.1038/s41591-024-02976-x] [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: 10/24/2023] [Accepted: 04/04/2024] [Indexed: 06/05/2024]
Abstract
Ground-level ozone (O3) is a harmful air pollutant formed in the atmosphere by the interaction between sunlight and precursor gases. Exposure to current O3 levels in Europe is a major source of premature mortality from air pollution. However, mitigation actions have been mainly designed and implemented at the national and regional scales, lacking a comprehensive assessment of the geographic sources of O3 pollution and its associated health impacts. Here we quantify both national and imported contributions to O3 and their related mortality burden across 813 contiguous regions in 35 European countries, representing about 530 million people. Imported O3 contributed to 88.3% of all O3-attributable deaths (intercountry range 83-100%). The greatest share of imported O3 had its origins outside the study domain (that is, hemispheric sources), which was responsible for 56.7% of total O3-attributable mortality (range 42.5-87.2%). It was concluded that achieving the air-quality guidelines set out by the World Health Organization and avoiding the health impacts of O3 require not only the implementation of national or coordinated pan-European actions but also global strategies.
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Affiliation(s)
- Hicham Achebak
- Inserm, France Cohortes, Paris, France.
- ISGlobal, Barcelona, Spain.
| | | | - María Teresa Pay
- Barcelona Supercomputing Center (BSC), Barcelona, Spain
- Department of Genetics, Microbiology and Statistics, University of Barcelona (UB), Barcelona, Spain
| | - Oriol Jorba
- Barcelona Supercomputing Center (BSC), Barcelona, Spain
| | - Marc Guevara
- Barcelona Supercomputing Center (BSC), Barcelona, Spain
| | - Carlos Pérez García-Pando
- Barcelona Supercomputing Center (BSC), Barcelona, Spain
- Catalan Institution for Research and Advanced Studies (ICREA), Barcelona, Spain
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12
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Du X, Chen R, Kan H. Challenges of Air Pollution and Health in East Asia. Curr Environ Health Rep 2024; 11:89-101. [PMID: 38321318 DOI: 10.1007/s40572-024-00433-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 01/27/2024] [Indexed: 02/08/2024]
Abstract
PURPOSE OF REVIEW Air pollution has been a serious environmental and public health issue worldwide, particularly in Asian countries. There have been significant increases in epidemiological studies on fine particulate matter (PM2.5) and ozone pollution in East Asia, and an in-depth review of epidemiological evidence is urgent. Thus, we carried out a systematic review of the epidemiological research on PM2.5 and ozone pollution in East Asia released in recent years. RECENT FINDINGS Recent studies have indicated that PM2.5 and ozone are the most detrimental air pollutants to human health, resulting in substantial disease burdens for Asian populations. Many epidemiological studies of PM2.5 and ozone have been mainly performed in three East Asian countries (China, Japan, and South Korea). We derived the following summary findings: (1) both short-term and long-term exposure to PM2.5 and ozone could raise the risks of mortality and morbidity, emphasizing the need for continuing improvements in air quality in East Asia; (2) the long-term associations between PM2.5 and mortality in East Asia are comparable to those observed in Europe and North America, whereas the short-term associations are relatively smaller in magnitude; and (3) further cohort and intervention studies are required to yield robust and precise evidence that can promote evidence-based policymaking in East Asia. This updated review presented an outline of the health impacts of PM2.5 and ozone in East Asia, which may be beneficial for the development of future regulatory policies and standards, as well as for designing subsequent investigations.
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Affiliation(s)
- Xihao Du
- School of Public Health, Key Lab of Public Health Safety of the Ministry of Education and NHC Key Lab of Health Technology Assessment, Shanghai Institute of Infectious Disease and Biosecurity, Fudan University, Shanghai, 200032, China
| | - Renjie Chen
- School of Public Health, Key Lab of Public Health Safety of the Ministry of Education and NHC Key Lab of Health Technology Assessment, Shanghai Institute of Infectious Disease and Biosecurity, Fudan University, Shanghai, 200032, China.
| | - Haidong Kan
- School of Public Health, Key Lab of Public Health Safety of the Ministry of Education and NHC Key Lab of Health Technology Assessment, Shanghai Institute of Infectious Disease and Biosecurity, Fudan University, Shanghai, 200032, China.
- Children's Hospital of Fudan University, National Center for Children's Health, Shanghai, China.
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13
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Ye Y, Ma H, Dong J, Wang J. Association between short-term ambient air pollutants and type 2 diabetes outpatient visits: a time series study in Lanzhou, China. ENVIRONMENTAL SCIENCE. PROCESSES & IMPACTS 2024; 26:778-790. [PMID: 38546508 DOI: 10.1039/d3em00464c] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/25/2024]
Abstract
Diabetes is a global public health problem, and the impact of air pollutants on type 2 diabetes mellitus (T2DM) has attracted people's attention. This study aimed to assess the association of short-term exposure to six criteria air pollutants with T2DM outpatient visits in Lanzhou, China. We collected data on daily outpatient visits for T2DM, daily meteorological data and hourly concentrations of air pollutants in Lanzhou from 2013 to 2019. An over-dispersed passion generalized addictive model combined with a distributed lag non-linear model was applied to estimate the associations and stratified analyses were performed by gender, age, and season. The models were fitted with different lag structures, including single lag days from the current to the previous seven days (lag0 to lag7) and moving average concentrations over seven lag days (lag01 to lag07). A positive association between multiple air pollutants, especially PM2.5, NO2, O38h and CO and hospital outpatient visits for T2DM was observed. The largest association between T2DM outpatient visits and PM2.5 was observed at lag06 (RR 1.013, 95% CI: 1.001, 1.027), NO2 at lag03 (RR 1.034, 95% CI: 1.018, 1.050), O38h at lag05 (RR 1.012, 95% CI: 1.001, 1.023) for an increase of 10 μg m-3 and CO at lag03 (RR 1.084, 95% CI: 1.029, 1.142) for an increase of 1 mg m-3 in the concentrations. In addition, people aged <65 and males are more susceptible, and air pollutants have a greater impact on the cold season. This study showed that although the air pollution in Lanzhou was improved, there was still a statistical correlation between air pollution exposure and T2DM outpatient visits. Therefore, the local government still needs to strengthen the control of air pollution and enhance the protection awareness of the diabetic population through education and publicity.
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Affiliation(s)
- Yilin Ye
- School of Public Health, Lanzhou University, Lanzhou 730000, People's Republic of China.
| | - Hongran Ma
- School of Public Health, Lanzhou University, Lanzhou 730000, People's Republic of China.
| | - Jiyuan Dong
- School of Public Health, Lanzhou University, Lanzhou 730000, People's Republic of China.
| | - Jiancheng Wang
- Gansu Health Vocational College, Lanzhou 730050, People's Republic of China
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14
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Li J, He C, Ying J, Hua B, Yang Y, Chen W, Liu W, Ye D, Sun X, Mao Y, Chen K. Air pollutants, genetic susceptibility, and the risk of incident gastrointestinal diseases: A large prospective cohort study. ENVIRONMENTAL RESEARCH 2024; 247:118182. [PMID: 38218525 DOI: 10.1016/j.envres.2024.118182] [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: 10/26/2023] [Revised: 12/10/2023] [Accepted: 01/10/2024] [Indexed: 01/15/2024]
Abstract
A comprehensive overview of the associations between air pollution and the risk of gastrointestinal (GI) diseases has been lacking. We aimed to examine the relationships of long-term exposure to ambient particulate matter (PM) with aerodynamic diameter ≤2.5 μm (PM2.5), 2.5-10 μm (PMcoarse), ≤10 μm (PM10), nitrogen dioxide (NO2), and nitrogen oxides (NOx), with the risk of incident GI diseases, and to explore the interplay between air pollution and genetic susceptibility. A total of 465,703 participants free of GI diseases in the UK Biobank were included at baseline. Land use regression models were employed to calculate the residential air pollutants concentrations. Cox proportional hazard models were used to evaluate the associations of air pollutants with the risk of GI diseases. The dose-response relationships of air pollutants with the risk of GI diseases were evaluated by restricted cubic spline curves. We found that long-term exposure to ambient air pollutants was positively associated with the risk of peptic ulcer (PM2.5 : Q4 vs. Q1: hazard ratio (HR) 1.272, 95% confidence interval (CI) 1.179-1.372, NO2: 1.220, 1.131-1.316, and NOx: 1.277, 1.184-1.376) and chronic gastritis (PM2.5: 1.454, 1.309-1.616, PM10 : 1.232, 1.112-1.366, NO2: 1.456, 1.311-1.617, and NOx: 1.419, 1.280-1.574) after Bonferroni correction. Participants with high genetic risk and high air pollution exposure had the highest risk of peptic ulcer, compared to those with low genetic risk and low air pollution exposure (PM2.5: HR 1.558, 95%CI 1.384-1.754, NO2: 1.762, 1.395-2.227, and NOx: 1.575, 1.403-1.769). However, no significant additive or multiplicative interaction between air pollution and genetic risk was found. In conclusion, long-term exposure to ambient air pollutants was associated with increased risk of peptic ulcer and chronic gastritis.
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Affiliation(s)
- Jiayu Li
- Department of Epidemiology, School of Public Health, Zhejiang Chinese Medical University, Hangzhou, China
| | - Chunlei He
- Department of Epidemiology, School of Public Health, Zhejiang Chinese Medical University, Hangzhou, China
| | - Jiacheng Ying
- The Fourth School of Clinical Medicine, Zhejiang Chinese Medical University, Hangzhou, China
| | - Baojie Hua
- Department of Epidemiology, School of Public Health, Zhejiang Chinese Medical University, Hangzhou, China
| | - Yudan Yang
- Department of Epidemiology, School of Public Health, Zhejiang Chinese Medical University, Hangzhou, China
| | - Weiwei Chen
- Department of Epidemiology, School of Public Health, Zhejiang Chinese Medical University, Hangzhou, China
| | - Wei Liu
- Department of Epidemiology, School of Public Health, Zhejiang Chinese Medical University, Hangzhou, China
| | - Ding Ye
- Department of Epidemiology, School of Public Health, Zhejiang Chinese Medical University, Hangzhou, China
| | - Xiaohui Sun
- Department of Epidemiology, School of Public Health, Zhejiang Chinese Medical University, Hangzhou, China.
| | - Yingying Mao
- Department of Epidemiology, School of Public Health, Zhejiang Chinese Medical University, Hangzhou, China.
| | - Kun Chen
- Department of Public Health, Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.
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15
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Jiang S, Tang L, Lou Z, Wang H, Huang L, Zhao W, Wang Q, Li R, Ding Z. The changing health effects of air pollution exposure for respiratory diseases: a multicity study during 2017-2022. Environ Health 2024; 23:36. [PMID: 38609898 PMCID: PMC11015632 DOI: 10.1186/s12940-024-01083-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2023] [Accepted: 04/10/2024] [Indexed: 04/14/2024]
Abstract
BACKGROUND Multifaceted SARS-CoV-2 interventions have modified exposure to air pollution and dynamics of respiratory diseases. Identifying the most vulnerable individuals requires effort to build a complete picture of the dynamic health effects of air pollution exposure, accounting for disparities across population subgroups. METHODS We use generalized additive model to assess the likely changes in the hospitalisation and mortality rate as a result of exposure to PM2.5 and O3 over the course of COVID-19 pandemic. We further disaggregate the population into detailed age categories and illustrate a shifting age profile of high-risk population groups. Additionally, we apply multivariable logistic regression to integrate demographic, socioeconomic and climatic characteristics with the pollution-related excess risk. RESULTS Overall, a total of 1,051,893 hospital admissions and 34,954 mortality for respiratory disease are recorded. The findings demonstrate a transition in the association between air pollutants and hospitalisation rates over time. For every 10 µg/m3 increase of PM2.5, the rate of hospital admission increased by 0.2% (95% CI: 0.1-0.7%) and 1.4% (1.0-1.7%) in the pre-pandemic and dynamic zero-COVID stage, respectively. Conversely, O3-related hospitalization rate would be increased by 0.7% (0.5-0.9%) in the pre-pandemic stage but lowered to 1.7% (1.5-1.9%) in the dynamic zero-COVID stage. Further assessment indicates a shift of high-risk people from children and young adolescents to the old, primarily the elevated hospitalization rates among the old people in Lianyungang (RR: 1.53, 95%CI: 1.46, 1.60) and Nantong (RR: 1.65, 95%CI: 1.57, 1.72) relative to those for children and young adolescents. Over the course of our study period, people with underlying diseases would have 26.5% (22.8-30.3%) and 12.7% (10.8-14.6%) higher odds of having longer hospitalisation and over 6 times higher odds of deaths after hospitalisation. CONCLUSIONS Our estimates provide the first comprehensive evidence on the dynamic pollution-health associations throughout the pandemic. The results suggest that age and underlying diseases collectively determines the disparities of pollution-related health effect across population subgroups, underscoring the urgency to identifying the most vulnerable individuals to air pollution.
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Affiliation(s)
- Siyu Jiang
- School of Public Health, Nanjing Medical University, 101 Longmian AV, Nanjing, 211166, Jiangsu, China
| | - Longjuan Tang
- School of Public Health, Nanjing Medical University, 101 Longmian AV, Nanjing, 211166, Jiangsu, China
| | - Zhe Lou
- School of Public Health, Nanjing Medical University, 101 Longmian AV, Nanjing, 211166, Jiangsu, China
| | - Haowei Wang
- School of Public Health, Imperial College London, London, UK
- MRC Centre for Global Infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergency Analytics, Imperial College London, London, UK
| | - Ling Huang
- College of Urban and Environmental Sciences, Peking University, Beijing, China
| | - Wei Zhao
- School of Public Health, Nanjing Medical University, 101 Longmian AV, Nanjing, 211166, Jiangsu, China
| | - Qingqing Wang
- Jiangsu Provincial Center for Disease Prevention and Control, 172 Jiangsu Rd, Nanjing, 210009, Jiangsu, China
| | - Ruiyun Li
- School of Public Health, Nanjing Medical University, 101 Longmian AV, Nanjing, 211166, Jiangsu, China.
- Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing, China.
| | - Zhen Ding
- Jiangsu Provincial Center for Disease Prevention and Control, 172 Jiangsu Rd, Nanjing, 210009, Jiangsu, China.
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16
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Levy M, Buckell J, Clarke R, Wu N, Pei P, Sun D, Avery D, Zhang H, Lv J, Yu C, Li L, Chen Z, Yip W, Chen Y, Mihaylova B. Association between health insurance cost-sharing and choice of hospital tier for cardiovascular diseases in China: a prospective cohort study. THE LANCET REGIONAL HEALTH. WESTERN PACIFIC 2024; 45:101020. [PMID: 38380231 PMCID: PMC10876671 DOI: 10.1016/j.lanwpc.2024.101020] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/01/2023] [Revised: 12/13/2023] [Accepted: 01/16/2024] [Indexed: 02/22/2024]
Abstract
Background Hospitals in China are classified into tiers (1, 2 or 3), with the largest (tier 3) having more equipment and specialist staff. Differential health insurance cost-sharing by hospital tier (lower deductibles and higher reimbursement rates in lower tiers) was introduced to reduce overcrowding in higher tier hospitals, promote use of lower tier hospitals, and limit escalating healthcare costs. However, little is known about the effects of differential cost-sharing in health insurance schemes on choice of hospital tiers. Methods In a 9-year follow-up of a prospective study of 0.5 M adults from 10 areas in China, we examined the associations between differential health insurance cost-sharing and choice of hospital tiers for patients with a first hospitalisation for stroke or ischaemic heart disease (IHD) in 2009-2017. Analyses were performed separately in urban areas (stroke: n = 20,302; IHD: n = 19,283) and rural areas (stroke: n = 21,130; IHD: n = 17,890), using conditional logit models and adjusting for individual socioeconomic and health characteristics. Findings About 64-68% of stroke and IHD cases in urban areas and 27-29% in rural areas chose tier 3 hospitals. In urban areas, higher reimbursement rates in each tier and lower tier 3 deductibles were associated with a greater likelihood of choosing their respective hospital tiers. In rural areas, the effects of cost-sharing were modest, suggesting a greater contribution of other factors. Higher socioeconomic status and greater disease severity were associated with a greater likelihood of seeking care in higher tier hospitals in urban and rural areas. Interpretation Patient choice of hospital tiers for treatment of stroke and IHD in China was influenced by differential cost-sharing in urban areas, but not in rural areas. Further strategies are required to incentivise appropriate health seeking behaviour and promote more efficient hospital use. Funding Wellcome Trust, Medical Research Council, British Heart Foundation, Cancer Research UK, Kadoorie Charitable Foundation, China Ministry of Science and Technology, and National Natural Science Foundation of China.
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Affiliation(s)
- Muriel Levy
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, UK
- Health Economics Research Centre, Nuffield Department of Population Health, University of Oxford, UK
| | - John Buckell
- Health Economics Research Centre, Nuffield Department of Population Health, University of Oxford, UK
| | - Robert Clarke
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, UK
- Medical Research Council Population Health Research Unit (MRC PHRU), Nuffield Department of Population Health, University of Oxford, UK
| | - Nina Wu
- School of Public Health, Capital Medical University, Beijing, China
| | - Pei Pei
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing, China
| | - Dianjianyi Sun
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing, China
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Centre, Beijing, China
| | - Daniel Avery
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, UK
| | - Hua Zhang
- NCDs Prevention and Control Department, Qingdao Centre for Disease Control and Prevention, Qingdao, China
| | - Jun Lv
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing, China
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Centre, Beijing, China
| | - Canqing Yu
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing, China
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Centre, Beijing, China
| | - Liming Li
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing, China
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Centre, Beijing, China
| | - Zhengming Chen
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, UK
| | - Winnie Yip
- Harvard T H Chan School of Public Health, Boston, MA, USA
| | - Yiping Chen
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, UK
- Medical Research Council Population Health Research Unit (MRC PHRU), Nuffield Department of Population Health, University of Oxford, UK
| | - Borislava Mihaylova
- Health Economics Research Centre, Nuffield Department of Population Health, University of Oxford, UK
- Health Economics and Policy Research Unit, Wolfson Institute of Population Health, Queen Mary University of London, London, UK
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17
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Zhang J, Xu Z, Han P, Fu Y, Wang Q, Wei X, Wang Q, Yang L. Exploring the Modifying Role of GDP and Greenness on the Short Effect of Air Pollutants on Respiratory Hospitalization in Beijing. GEOHEALTH 2024; 8:e2023GH000930. [PMID: 38505689 PMCID: PMC10949333 DOI: 10.1029/2023gh000930] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/16/2023] [Revised: 01/31/2024] [Accepted: 02/28/2024] [Indexed: 03/21/2024]
Abstract
It is unclear whether Gross Domestic Product (GDP) and greenness have additional modifying effects on the association between air pollution and respiratory system disease. Utilizing a time-stratified case-crossover design with a distributed lag linear model, we analyzed the association between six pollutants (PM2.5, PM10, NO2, SO2, O3, and CO) and 555,498 respiratory hospital admissions in Beijing from 1st January 2016 to 31st December 2019. We employed conditional logistic regression, adjusting for meteorological conditions, holidays and influenza, to calculate percent change of hospitalization risk. Subsequently, we performed subgroup analysis to investigate potential effect modifications using a two-sample z test. Every 10 μg/m3 increase in PM2.5, PM10, NO2, SO2, and O3 led to increases of 0.26% (95%CI: 0.17%, 0.35%), 0.15% (95%CI: 0.09%, 0.22%), 0.61% (95%CI: 0.44%, 0.77%), 1.72% (95%CI: 1.24%, 2.21%), and 0.32% (95%CI: 0.20%, 0.43%) in admissions, respectively. Also, a 1 mg/m3 increase in CO levels resulted in a 2.50% (95%CI: 1.96%, 3.04%) rise in admissions. The links with NO2 (p < 0.001), SO2 (p < 0.001), O3 (during the warm season, p < 0.001), and CO (p < 0.001) were significantly weaker among patients residing in areas with higher levels of greenness. No significant modifying role of GDP was observed. Greenness can help mitigate the effects of air pollutants, while the role of GDP needs further investigation.
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Affiliation(s)
- Jiawei Zhang
- Department of Health Policy and ManagementPeking University School of Public HealthBeijingChina
| | - Zhihu Xu
- Department of Occupational and Environmental Health SciencesPeking University School of Public HealthBeijingChina
| | - Peien Han
- Department of Health Policy and ManagementPeking University School of Public HealthBeijingChina
| | - Yaqun Fu
- Department of Health Policy and ManagementPeking University School of Public HealthBeijingChina
| | - Quan Wang
- Department of Health Policy and ManagementPeking University School of Public HealthBeijingChina
- Brown SchoolWashington University in St. LouisSt. LouisMOUSA
| | - Xia Wei
- Department of Health Policy and ManagementPeking University School of Public HealthBeijingChina
- Department of Health Services Research and PolicyLondon School of Hygiene & Tropical MedicineLondonUK
| | - Qingbo Wang
- Department of Health Policy and ManagementPeking University School of Public HealthBeijingChina
| | - Li Yang
- Department of Health Policy and ManagementPeking University School of Public HealthBeijingChina
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18
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Lei J, Liu C, Meng X, Sun Y, Huang S, Zhu Y, Gao Y, Shi S, Zhou L, Luo H, Kan H, Chen R. Associations between fine particulate air pollution with small-airway inflammation: A nationwide analysis in 122 Chinese cities. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2024; 344:123330. [PMID: 38199484 DOI: 10.1016/j.envpol.2024.123330] [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: 08/19/2023] [Revised: 11/24/2023] [Accepted: 01/06/2024] [Indexed: 01/12/2024]
Abstract
Alveolar nitric oxide is a non-invasive indicator of small-airway inflammation, a key pathophysiologic mechanism underlying lower respiratory diseases. However, no epidemiological studies have investigated the impact of fine particulate matter (PM2.5) exposure on the concentration of alveolar nitric oxide (CANO). To explore the associations between PM2.5 exposure in multiple periods and CANO, we conducted a nationwide cross-sectional study in 122 Chinese cities between 2019 and 2021. Utilizing a satellite-based model with a spatial resolution of 1 × 1 km, we matched long-term, mid-term, and short-term PM2.5 exposure for 28,399 individuals based on their home addresses. Multivariable linear regression models were applied to estimate the associations between PM2.5 at multiple exposure windows and CANO. Stratified analyses were also performed to identify potentially vulnerable subgroups. We found that per interquartile range (IQR) unit higher in 1-year average, 1-month average, and 7-day average PM2.5 concentration was significantly associated with increments of 17.78% [95% confidence interval (95%CI): 12.54%, 23.26%], 8.76% (95%CI: 7.35%, 10.19%), and 4.00% (95%CI: 2.81%, 5.20%) increment in CANO, respectively. The exposure-response relationship curves consistently increased with the slope becoming statistically significant beyond 20 μg/m3. Males, children, smokers, individuals with respiratory symptoms or using inhaled corticosteroids, and those living in Southern China were more vulnerable to PM2.5 exposure. In conclusion, our study provided novel evidence that PM2.5 exposure in long-term, mid-term, and short-term periods could significantly elevate small-airway inflammation represented by CANO. Our results highlight the significance of CANO measurement as a non-invasive tool for early screening in the management of PM2.5-related inflammatory respiratory diseases.
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Affiliation(s)
- Jian Lei
- School of Public Health, Key Lab of Public Health Safety of the Ministry of Education, NHC Key Lab of Health Technology Assessment, Fudan University, Shanghai, 200032, China; Department of Occupational and Environmental Health, Key Laboratory of Environment and Genes Related to Diseases, Ministry of Education, School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an, 710061, China.
| | - Cong Liu
- School of Public Health, Key Lab of Public Health Safety of the Ministry of Education, NHC Key Lab of Health Technology Assessment, Fudan University, Shanghai, 200032, China.
| | - Xia Meng
- School of Public Health, Key Lab of Public Health Safety of the Ministry of Education, NHC Key Lab of Health Technology Assessment, Fudan University, Shanghai, 200032, China
| | - Yiqing Sun
- Eberly College of Science, The Pennsylvania State University, University Park, PA, 16802, USA
| | - Suijie Huang
- Guangzhou Homesun Medical Technology Co., Ltd, Guangdong, 518040, China
| | - Yixiang Zhu
- School of Public Health, Key Lab of Public Health Safety of the Ministry of Education, NHC Key Lab of Health Technology Assessment, Fudan University, Shanghai, 200032, China
| | - Ya Gao
- School of Public Health, Key Lab of Public Health Safety of the Ministry of Education, NHC Key Lab of Health Technology Assessment, Fudan University, Shanghai, 200032, China
| | - Su Shi
- School of Public Health, Key Lab of Public Health Safety of the Ministry of Education, NHC Key Lab of Health Technology Assessment, Fudan University, Shanghai, 200032, China
| | - Lu Zhou
- School of Public Health, Key Lab of Public Health Safety of the Ministry of Education, NHC Key Lab of Health Technology Assessment, Fudan University, Shanghai, 200032, China
| | - Huihuan Luo
- School of Public Health, Key Lab of Public Health Safety of the Ministry of Education, NHC Key Lab of Health Technology Assessment, Fudan University, Shanghai, 200032, China
| | - Haidong Kan
- School of Public Health, Key Lab of Public Health Safety of the Ministry of Education, NHC Key Lab of Health Technology Assessment, Fudan University, Shanghai, 200032, China
| | - Renjie Chen
- School of Public Health, Key Lab of Public Health Safety of the Ministry of Education, NHC Key Lab of Health Technology Assessment, Fudan University, Shanghai, 200032, China.
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19
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Hegelund ER, Mehta AJ, Andersen ZJ, Lim YH, Loft S, Brunekreef B, Hoek G, de Hoogh K, Mortensen LH. Air pollution and human health: a phenome-wide association study. BMJ Open 2024; 14:e081351. [PMID: 38423777 PMCID: PMC10910582 DOI: 10.1136/bmjopen-2023-081351] [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: 10/25/2023] [Accepted: 02/19/2024] [Indexed: 03/02/2024] Open
Abstract
OBJECTIVES To explore the associations of long-term exposure to air pollution with onset of all human health conditions. DESIGN Prospective phenome-wide association study. SETTING Denmark. PARTICIPANTS All Danish residents aged ≥30 years on 1 January 2000 were included (N=3 323 612). After exclusion of individuals with missing geocoded residential addresses, 3 111 988 participants were available for the statistical analyses. MAIN OUTCOME MEASURE First registered diagnosis of every health condition according to the International Classification of Diseases, 10th revision, from 2000 to 2017. RESULTS Long-term exposure to fine particulate matter (PM2.5) and nitrogen dioxide (NO2) were both positively associated with the onset of more than 700 health conditions (ie, >80% of the registered health conditions) after correction for multiple testing, while the remaining associations were inverse or insignificant. As regards the most common health conditions, PM2.5 and NO2 were strongest positively associated with chronic obstructive pulmonary disease (PM2.5: HR 1.06 (95% CI 1.05 to 1.07) per 1 IQR increase in exposure level; NO2: 1.14 (95% CI 1.12 to 1.15)), type 2 diabetes (PM2.5: 1.06 (95% CI 1.05 to 1.06); NO2: 1.12 (95% CI 1.10 to 1.13)) and ischaemic heart disease (PM2.5: 1.05 (95% CI 1.04 to 1.05); NO2: 1.11 (95% CI 1.09 to 1.12)). Furthermore, PM2.5 and NO2 were both positively associated with so far unexplored, but highly prevalent outcomes relevant to public health, including senile cataract, hearing loss and urinary tract infection. CONCLUSIONS The findings of this study suggest that air pollution has a more extensive impact on human health than previously known. However, as this study is the first of its kind to investigate the associations of long-term exposure to air pollution with onset of all human health conditions, further research is needed to replicate the study findings.
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Affiliation(s)
| | | | | | | | | | | | - Gerard Hoek
- Utrecht University, Utrecht, the Netherlands
| | - Kees de Hoogh
- Swiss Tropical and Public Health Institute, Allschwil, Switzerland
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20
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Feng Y, Castro E, Wei Y, Jin T, Qiu X, Dominici F, Schwartz J. Long-term exposure to ambient PM2.5, particulate constituents and hospital admissions from non-respiratory infection. Nat Commun 2024; 15:1518. [PMID: 38374182 PMCID: PMC10876532 DOI: 10.1038/s41467-024-45776-0] [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: 04/21/2023] [Accepted: 02/05/2024] [Indexed: 02/21/2024] Open
Abstract
The association between PM2.5 and non-respiratory infections is unclear. Using data from Medicare beneficiaries and high-resolution datasets of PM2.5 and its constituents across 39,296 ZIP codes in the U.S between 2000 and 2016, we investigated the associations between annual PM2.5, PM2.5 constituents, source-specific PM2.5, and hospital admissions from non-respiratory infections. Each standard deviation (3.7-μg m-3) increase in PM2.5 was associated with a 10.8% (95%CI 10.8-11.2%) increase in rate of hospital admissions from non-respiratory infections. Sulfates (30.8%), Nickel (22.5%) and Copper (15.3%) contributed the largest weights in the observed associations. Each standard deviation increase in PM2.5 components sourced from oil combustion, coal burning, traffic, dirt, and regionally transported nitrates was associated with 14.5% (95%CI 7.6-21.8%), 18.2% (95%CI 7.2-30.2%), 20.6% (95%CI 5.6-37.9%), 8.9% (95%CI 0.3-18.4%) and 7.8% (95%CI 0.6-15.5%) increases in hospital admissions from non-respiratory infections. Our results suggested that non-respiratory infections are an under-appreciated health effect of PM2.5.
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Affiliation(s)
- Yijing Feng
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
| | - Edgar Castro
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Yaguang Wei
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Tingfan Jin
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Xinye Qiu
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Francesca Dominici
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Joel Schwartz
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA, USA
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21
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Zhang R, Liu M, Zhang W, Ling J, Dong J, Ruan Y. Short-term association between air pollution and daily genitourinary disorder admissions in Lanzhou, China. ENVIRONMENTAL GEOCHEMISTRY AND HEALTH 2024; 46:74. [PMID: 38367071 DOI: 10.1007/s10653-023-01821-3] [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: 07/14/2023] [Accepted: 11/27/2023] [Indexed: 02/19/2024]
Abstract
The aim of this study was to determine the relationship between short-term exposure to ambient air pollution and the number of daily hospital admissions for genitourinary disorders in Lanzhou. Hospital admission data and air pollutants, including PM2.5, PM10, SO2, NO2, O38h and CO, were obtained from the period 2013 to 2020. A generalized additive model (GAM) combined with distribution lag nonlinear model (DLNM) based on quasi-Poisson distribution was used by the controlling for trends, weather, weekdays and holidays. Short-term exposure to PM2.5, NO2 and CO increased the risk of genitourinary disorder admissions with RR of 1.0096 (95% CI 1.0002-1.0190), 1.0255 (95% CI 1.0123-1.0389) and 1.0686 (95% CI 1.0083-1.1326), respectively. PM10, O38h and SO2 have no significant effect on genitourinary disorders. PM2.5 and NO2 are more strongly correlated in female and ≥ 65 years patients. CO is more strongly correlated in male and < 65 years patients. PM2.5, NO2 and CO are risk factors for genitourinary morbidity, and public health interventions should be strengthened to protect vulnerable populations.
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Affiliation(s)
- Runping Zhang
- School of Public Health, Lanzhou University, Lanzhou, 730000, People's Republic of China
| | - Miaoxin Liu
- School of Public Health, Lanzhou University, Lanzhou, 730000, People's Republic of China
| | - Wancheng Zhang
- School of Public Health, Lanzhou University, Lanzhou, 730000, People's Republic of China
| | - Jianglong Ling
- School of Public Health, Lanzhou University, Lanzhou, 730000, People's Republic of China
| | - Jiyuan Dong
- School of Public Health, Lanzhou University, Lanzhou, 730000, People's Republic of China
| | - Ye Ruan
- School of Public Health, Lanzhou University, Lanzhou, 730000, People's Republic of China.
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22
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Humphrey JL, Kinnee EJ, Robinson LF, Clougherty JE. Disentangling impacts of multiple pollutants on acute cardiovascular events in New York city: A case-crossover analysis. ENVIRONMENTAL RESEARCH 2024; 242:117758. [PMID: 38029813 PMCID: PMC11378578 DOI: 10.1016/j.envres.2023.117758] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/14/2022] [Revised: 10/29/2023] [Accepted: 11/21/2023] [Indexed: 12/01/2023]
Abstract
BACKGROUND Ambient air pollution contributes to an estimated 6.67 million deaths annually, and has been linked to cardiovascular disease (CVD), the leading cause of death. Short-term increases in air pollution have been associated with increased risk of CVD event, though relatively few studies have directly compared effects of multiple pollutants using fine-scale spatio-temporal data, thoroughly adjusting for co-pollutants and temperature, in an exhaustive citywide hospitals dataset, towards identifying key pollution sources within the urban environment to most reduce, and reduce disparities in, the leading cause of death worldwide. OBJECTIVES We aimed to examine multiple pollutants against multiple CVD diagnoses, across lag days, in models adjusted for co-pollutants and meteorology, and inherently adjusted by design for non-time-varying individual and aggregate-level covariates, using fine-scale space-time exposure estimates, in an exhaustive dataset of emergency department visits and hospitalizations across an entire city, thereby capturing the full population-at-risk. METHODS We used conditional logistic regression in a case-crossover design - inherently controlling for all confounders not varying within case month - to examine associations between spatio-temporal nitrogen dioxide (NO2), fine particulate matter (PM2.5), sulfur dioxide (SO2), and ozone (O3) in New York City, 2005-2011, on individual risk of acute CVD event (n = 837,523), by sub-diagnosis [ischemic heart disease (IHD), heart failure (HF), stroke, ischemic stroke, acute myocardial infarction]. RESULTS We found significant same-day associations between NO2 and risk of overall CVD, IHD, and HF - and between PM2.5 and overall CVD or HF event risk - robust to all adjustments and multiple comparisons. Results were comparable by sex and race - though median age at CVD was 10 years younger for Black New Yorkers than White New Yorkers. Associations for NO2 were comparable for adults younger or older than 69 years, though PM2.5 associations were stronger among older adults. DISCUSSION Our results indicate immediate, robust effects of combustion-related pollution on CVD risk, by sub-diagnosis. Though acute impacts differed minimally by age, sex, or race, the much younger age-at-event for Black New Yorkers calls attention to cumulative social susceptibility.
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Affiliation(s)
- Jamie L Humphrey
- Center Public Health Methods; RTI International, Research Triangle Park, NC, 27709, USA
| | - Ellen J Kinnee
- University Center for Social and Urban Research, University of Pittsburgh, Pittsburgh, PA, 15260, USA
| | - Lucy F Robinson
- Department of Epidemiology and Biostatistics, Dornsife School of Public Health, Drexel University, Philadelphia, PA, 19104, USA
| | - Jane E Clougherty
- Department of Environmental and Occupational Health, Dornsife School of Public Health, Drexel University, Philadelphia, PA, 19104, USA.
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23
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Wang Y, Li W, Chen S, Zhang J, Liu X, Jiang J, Chen L, Tang Z, Wan X, Lian X, Liang B, Xie S, Ma J, Guo X, Dong Y, Wu L, Li J, Koutrakis P. PM 2.5 constituents associated with childhood obesity and larger BMI growth trajectory: A 14-year longitudinal study. ENVIRONMENT INTERNATIONAL 2024; 183:108417. [PMID: 38199130 DOI: 10.1016/j.envint.2024.108417] [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: 07/12/2023] [Revised: 12/31/2023] [Accepted: 01/02/2024] [Indexed: 01/12/2024]
Abstract
BACKGROUND The association of specific PM2.5 chemical constituents with childhood overweight or obesity (OWOB) remain unclear. Furthermore, the long-term impacts of PM2.5 exposure on the trajectory of children's body mass index (BMI) have not been explored. METHODS We conducted a longitudinal study among 1,450,830 Chinese children aged 6-19 years from Beijing and Zhongshan in China during 2005-2018 to examine the associations of PM2.5 and its chemical constituents with incident OWOB risk. We extracted PM2.5 mass and five main component exposure from Tracking Air Pollution in China (TAP) dataset. Cox proportional hazards models were applied to quantify exposure-response associations. We further performed principal component analysis (PCA) to handle the multi-collinearity and used quantile g-computation (QGC) approach to analyze the impacts of exposure mixtures. Additionally, we selected 125,863 children with at least 8 physical examination measurements and combined group-based trajectory models (GBTM) with multinomial logistic regression models to explore the impacts of exposure to PM2.5 mass and five constituents on BMI and BMI Z-score trajectories during 6-19 years. RESULTS We observed each interquartile range increment in PM2.5 exposure was significantly associated with a 5.1 % increase in the risk of incident OWOB (95 % confidence Interval [CI]: 1.036-1.066). We also found black carbon, sulfate, organic matter, often linked to fossil combustion, had comparable or larger estimates of the effect (HR = 1.139-1.153) than PM2.5. Furthermore, Exposure to PM2.5 mass, sulfate, nitrate, ammonium, organic matter and black carbon was significantly associated with an increased odds of being in a larger BMI trajectory and being assigned to persistent OWOB trajectory. CONCLUSIONS Our findings provide evidence that the constituents mainly from fossil fuel combustion may have a perceptible influence on increased OWOB risk associated with PM2.5 exposure in China. Moreover, long-term exposure to PM2.5 contributes to an increased odds of being in a lager BMI and a persistent OWOB trajectories.
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Affiliation(s)
- Yaqi Wang
- Institute of Child and Adolescent Health, School of Public Health, Peking University, Beijing 100191, China
| | - Weiming Li
- Beijing Health Center for Physical Examination, Beijing 100191, China; Department of Epidemiology and Health Statistics, Capital Medical University School of Public Health, Beijing 100069, China
| | - Shuo Chen
- Beijing Health Center for Physical Examination, Beijing 100191, China; Department of Epidemiology and Health Statistics, Capital Medical University School of Public Health, Beijing 100069, China
| | - Jingbo Zhang
- Beijing Health Center for Physical Examination, Beijing 100191, China; Department of Epidemiology and Health Statistics, Capital Medical University School of Public Health, Beijing 100069, China
| | - Xiangtong Liu
- Beijing Health Center for Physical Examination, Beijing 100191, China; Department of Epidemiology and Health Statistics, Capital Medical University School of Public Health, Beijing 100069, China
| | - Jun Jiang
- Institute of Child and Adolescent Health, School of Public Health, Peking University, Beijing 100191, China
| | - Li Chen
- Institute of Child and Adolescent Health, School of Public Health, Peking University, Beijing 100191, China
| | - Ziqi Tang
- Institute of Child and Adolescent Health, School of Public Health, Peking University, Beijing 100191, China
| | - Xiaoyu Wan
- Institute of Child and Adolescent Health, School of Public Health, Peking University, Beijing 100191, China
| | - Xinyao Lian
- Institute of Child and Adolescent Health, School of Public Health, Peking University, Beijing 100191, China
| | - Baosheng Liang
- Department of Biostatistics, School of Public Health, Peking University, Beijing 100191, China
| | - Shaodong Xie
- State Key Joint Laboratory of Environment Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China
| | - Jun Ma
- Institute of Child and Adolescent Health, School of Public Health, Peking University, Beijing 100191, China
| | - Xiuhua Guo
- Beijing Health Center for Physical Examination, Beijing 100191, China; Department of Epidemiology and Health Statistics, Capital Medical University School of Public Health, Beijing 100069, China
| | - Yanhui Dong
- Institute of Child and Adolescent Health, School of Public Health, Peking University, Beijing 100191, China.
| | - Lijuan Wu
- Beijing Health Center for Physical Examination, Beijing 100191, China; Department of Epidemiology and Health Statistics, Capital Medical University School of Public Health, Beijing 100069, China.
| | - Jing Li
- Institute of Child and Adolescent Health, School of Public Health, Peking University, Beijing 100191, China.
| | - Petros Koutrakis
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA
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24
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Hu T, Xu ZY, Wang J, Su Y, Guo BB. Meteorological factors, ambient air pollution, and daily hospital admissions for depressive disorder in Harbin: A time-series study. World J Psychiatry 2023; 13:1061-1078. [PMID: 38186723 PMCID: PMC10768489 DOI: 10.5498/wjp.v13.i12.1061] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/21/2023] [Revised: 10/23/2023] [Accepted: 11/08/2023] [Indexed: 12/19/2023] Open
Abstract
BACKGROUND The literature has discussed the relationship between environmental factors and depressive disorders; however, the results are inconsistent in different studies and regions, as are the interaction effects between environmental factors. We hypothesized that meteorological factors and ambient air pollution individually affect and interact to affect depressive disorder morbidity. AIM To investigate the effects of meteorological factors and air pollution on depressive disorders, including their lagged effects and interactions. METHODS The samples were obtained from a class 3 hospital in Harbin, China. Daily hospital admission data for depressive disorders from January 1, 2015 to December 31, 2022 were obtained. Meteorological and air pollution data were also collected during the same period. Generalized additive models with quasi-Poisson regression were used for time-series modeling to measure the non-linear and delayed effects of environmental factors. We further incorporated each pair of environmental factors into a bivariate response surface model to examine the interaction effects on hospital admissions for depressive disorders. RESULTS Data for 2922 d were included in the study, with no missing values. The total number of depressive admissions was 83905. Medium to high correlations existed between environmental factors. Air temperature (AT) and wind speed (WS) significantly affected the number of admissions for depression. An extremely low temperature (-29.0 ℃) at lag 0 caused a 53% [relative risk (RR)= 1.53, 95% confidence interval (CI): 1.23-1.89] increase in daily hospital admissions relative to the median temperature. Extremely low WSs (0.4 m/s) at lag 7 increased the number of admissions by 58% (RR = 1.58, 95%CI: 1.07-2.31). In contrast, atmospheric pressure and relative humidity had smaller effects. Among the six air pollutants considered in the time-series model, nitrogen dioxide (NO2) was the only pollutant that showed significant effects over non-cumulative, cumulative, immediate, and lagged conditions. The cumulative effect of NO2 at lag 7 was 0.47% (RR = 1.0047, 95%CI: 1.0024-1.0071). Interaction effects were found between AT and the five air pollutants, atmospheric temperature and the four air pollutants, WS and sulfur dioxide. CONCLUSION Meteorological factors and the air pollutant NO2 affect daily hospital admissions for depressive disorders, and interactions exist between meteorological factors and ambient air pollution.
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Affiliation(s)
- Ting Hu
- Department of Five Therapy, The First Psychiatric Hospital of Harbin, Harbin 150026, Heilongjiang Province, China
| | - Zhao-Yuan Xu
- Medical Section, The First Psychiatric Hospital of Harbin, Harbin 150026, Heilongjiang Province, China
| | - Jian Wang
- Department of Out-Patient, The First Psychiatric Hospital of Harbin, Harbin 150026, Heilongjiang Province, China
| | - Yao Su
- Science and Education, The First Psychiatric Hospital of Harbin, Harbin 150026, Heilongjiang Province, China
| | - Bing-Bing Guo
- Department of 22 Therapy, Harbin Psychiatric Baiyupao Hospital, Harbin 150000, Heilongjiang Province, China
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25
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Gudziunaite S, Shabani Z, Weitensfelder L, Moshammer H. Time series analysis in environmental epidemiology: challenges and considerations. Int J Occup Med Environ Health 2023; 36:704-716. [PMID: 37782034 PMCID: PMC10743348 DOI: 10.13075/ijomeh.1896.02237] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2023] [Accepted: 08/24/2023] [Indexed: 10/03/2023] Open
Abstract
In environmental epidemiology, time series analyses represent a widely used statistical tool. However, though being commonly used, there is soften confusion regarding the specific requirements, such as which link function might be most appropriate, when or how to control for seasonality or how to account for lags. The present overview draws from experiences in other disciplines and discusses the proper execution of time series analyses based on considerations that are relevant in environmental epidemiology. Time series analysis in environmental epidemiology focuses on acute events caused by short-term changes in exposure. These exposures should be fairly wide-spread affecting a large number of persons, usually all inhabitants of a political entity. Pollutants in air or drinking water as well as meteorological factors serve as typical examples. Despite the many time series analyses performed world-wide, some health effects that would lend themselves to that approach are still under-explored. This would include also some neurological and psychiatric endpoints. Int J Occup Med Environ Health. 2023;36(6):704-16.
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Affiliation(s)
- Sandra Gudziunaite
- Medical University of Vienna, Department of Environmental Health, Center for Public Health, Vienna, Austria
| | - Zana Shabani
- University of Hasan Pristina, Medical Faculty, Pristina, Kosovo
| | - Lisbeth Weitensfelder
- Medical University of Vienna, Department of Environmental Health, Center for Public Health, Vienna, Austria
| | - Hanns Moshammer
- Medical University of Vienna, Department of Environmental Health, Center for Public Health, Vienna, Austria
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Gan X, Zhang Y, He P, Ye Z, Zhou C, Liu M, Yang S, Zhang Y, Qin X. Positive association between ambient air pollutants and incident kidney stones. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2023; 30:124067-124077. [PMID: 37996579 DOI: 10.1007/s11356-023-31136-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: 08/19/2023] [Accepted: 11/16/2023] [Indexed: 11/25/2023]
Abstract
We aimed to assess the association between exposure to various air pollutants, individually or jointly, and incident kidney stones, and examine whether genetic susceptibility for kidney stones may modify this association. 453,977 participants without prior kidney stones from the UK Biobank were included. Annual mean concentrations of PM2.5, PM2.5-10, PM10, NO2, and NOx were estimated with a land use regression model. A weighted air pollution score was constructed that incorporates the five pollutants mentioned above. A genetic risk score (GRS) was calculated based on 20 single-nucleotide polymorphisms associated with kidney stones. The primary outcome was incident kidney stones. During a median follow-up of 11.9 years, 5,375 kidney stones were recorded. The adjusted HRs (95%CI) of incident kidney stones were 1.04 (1.01-1.07), 1.02 (1.00-1.05), 1.03 (1.01-1.06), 1.05 (1.02-1.08), and 1.04 (1.01-1.07), for per standard deviation (SD) increment in PM2.5 (SD:1.06 μg/m3), PM2.5-10 (SD:0.90 μg/m3), PM10 (SD:1.90 μg/m3), NO2 (SD:7.63 μg/m3), and NOx (SD: 15.63 μg/m3), respectively. Moreover, there was a significantly linear association between the air pollution score and incident kidney stones (per SD increment: HR, 1.05, 95%CI: 1.02-1.08), especially in those without diabetes (vs. participants with diabetes; P-interaction = 0.037). In addition, the association between air pollution and kidney stones was statistically significant only in participants within intermediate-high kidney stone GRS, but not in those with low GRS kidney stone, though the interaction was not significant (P-interaction = 0.385). In conclusion, exposure to air pollution was associated with a higher risk of incident kidney stones, calling for the need to improve air quality.
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Affiliation(s)
- Xiaoqin Gan
- Division of Nephrology, Nanfang Hospital, Southern Medical University, National Clinical Research Center for Kidney Disease, State Key Laboratory of Organ Failure Research, Guangdong Provincial Institute of Nephrology, Guangdong Provincial Key Laboratory of Renal Failure Research, Guangzhou Regenerative Medicine and Health Guangdong Laboratory, Guangzhou, 510515, China
| | - Yanjun Zhang
- Division of Nephrology, Nanfang Hospital, Southern Medical University, National Clinical Research Center for Kidney Disease, State Key Laboratory of Organ Failure Research, Guangdong Provincial Institute of Nephrology, Guangdong Provincial Key Laboratory of Renal Failure Research, Guangzhou Regenerative Medicine and Health Guangdong Laboratory, Guangzhou, 510515, China
| | - Panpan He
- Division of Nephrology, Nanfang Hospital, Southern Medical University, National Clinical Research Center for Kidney Disease, State Key Laboratory of Organ Failure Research, Guangdong Provincial Institute of Nephrology, Guangdong Provincial Key Laboratory of Renal Failure Research, Guangzhou Regenerative Medicine and Health Guangdong Laboratory, Guangzhou, 510515, China
| | - Ziliang Ye
- Division of Nephrology, Nanfang Hospital, Southern Medical University, National Clinical Research Center for Kidney Disease, State Key Laboratory of Organ Failure Research, Guangdong Provincial Institute of Nephrology, Guangdong Provincial Key Laboratory of Renal Failure Research, Guangzhou Regenerative Medicine and Health Guangdong Laboratory, Guangzhou, 510515, China
| | - Chun Zhou
- Division of Nephrology, Nanfang Hospital, Southern Medical University, National Clinical Research Center for Kidney Disease, State Key Laboratory of Organ Failure Research, Guangdong Provincial Institute of Nephrology, Guangdong Provincial Key Laboratory of Renal Failure Research, Guangzhou Regenerative Medicine and Health Guangdong Laboratory, Guangzhou, 510515, China
| | - Mengyi Liu
- Division of Nephrology, Nanfang Hospital, Southern Medical University, National Clinical Research Center for Kidney Disease, State Key Laboratory of Organ Failure Research, Guangdong Provincial Institute of Nephrology, Guangdong Provincial Key Laboratory of Renal Failure Research, Guangzhou Regenerative Medicine and Health Guangdong Laboratory, Guangzhou, 510515, China
| | - Sisi Yang
- Division of Nephrology, Nanfang Hospital, Southern Medical University, National Clinical Research Center for Kidney Disease, State Key Laboratory of Organ Failure Research, Guangdong Provincial Institute of Nephrology, Guangdong Provincial Key Laboratory of Renal Failure Research, Guangzhou Regenerative Medicine and Health Guangdong Laboratory, Guangzhou, 510515, China
| | - Yuanyuan Zhang
- Division of Nephrology, Nanfang Hospital, Southern Medical University, National Clinical Research Center for Kidney Disease, State Key Laboratory of Organ Failure Research, Guangdong Provincial Institute of Nephrology, Guangdong Provincial Key Laboratory of Renal Failure Research, Guangzhou Regenerative Medicine and Health Guangdong Laboratory, Guangzhou, 510515, China
| | - Xianhui Qin
- Division of Nephrology, Nanfang Hospital, Southern Medical University, National Clinical Research Center for Kidney Disease, State Key Laboratory of Organ Failure Research, Guangdong Provincial Institute of Nephrology, Guangdong Provincial Key Laboratory of Renal Failure Research, Guangzhou Regenerative Medicine and Health Guangdong Laboratory, Guangzhou, 510515, China.
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27
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Li J, Liang L, Lyu B, Cai YS, Zuo Y, Su J, Tong Z. Double trouble: The interaction of PM 2.5 and O 3 on respiratory hospital admissions. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2023; 338:122665. [PMID: 37806428 DOI: 10.1016/j.envpol.2023.122665] [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: 06/12/2023] [Revised: 09/28/2023] [Accepted: 09/29/2023] [Indexed: 10/10/2023]
Abstract
The co-occurrence of fine particulate matter (PM2.5) and ozone (O3) pollution during the warm season has become a growing public health concern. The interaction between PM2.5 and O3 and its contribution to disease burden associated with co-pollution has not been thoroughly examined. We collected data on hospital admissions for respiratory diseases from a city-wide hospital discharge database in Beijing between 2013 and 2019. City-wide 24-h mean PM2.5 and daily maximum 8-h mean O3 were averaged from 35 monitoring stations across Beijing. Conditional Poisson regression was employed to estimate the interaction between warm-season PM2.5 and O3 on respiratory admissions. A model incorporating a tensor product term was used to fit the non-linear interaction and estimate the number of respiratory admissions attributable to PM2.5 and O3 pollution. From January 18, 2013 to December 31, 2019, 1,191,308 respiratory admissions were recorded. We observed multiplicative interactions between warm-season PM2.5 and O3 on upper respiratory infections (P = 0.004), pneumonia (P = 0.002), chronic obstructive pulmonary disease (P = 0.041), and total respiratory disease (P < 0.001). PM2.5-O3 co-pollution during warm season exhibited a super-additive effect on respiratory admissions, with a relative excess risk due to interaction of 1.65% (95%CI: 0.46%-2.84%). There was a non-linear pattern of the synergistic effect between PM2.5 and O3 on respiratory admissions. Based on the World Health Organization global air quality guidelines, 12,421 respiratory admissions would be reduced if both daily PM2.5 and O3 concentrations had not exceeded the target (PM2.5 15 μg/m3, O3 100 μg/m3). The number of respiratory admissions attributable to either PM2.5 or O3 pollution decreased by 48.7% from 2013 to 2019. Prioritizing O3 control during the warm season is a cost-effective strategy for Beijing. These findings underscore the significance of concurrently addressing both PM2.5 pollution and O3 pollution during the warm season to alleviate the burden of respiratory diseases.
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Affiliation(s)
- Jiachen Li
- Department of Clinical Epidemiology, Beijing Institute of Respiratory Medicine and Beijing Chao-Yang Hospital, Capital Medical University, Beijing, China.
| | - Lirong Liang
- Department of Clinical Epidemiology, Beijing Institute of Respiratory Medicine and Beijing Chao-Yang Hospital, Capital Medical University, Beijing, China.
| | - Baolei Lyu
- Huayun Sounding Meteorology Technology Corporation, Beijing, China; Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology (CICAEET), Nanjing University of Information Science & Technology, Nanjing, China.
| | - Yutong Samuel Cai
- Centre for Environmental Health and Sustainability, Department of Population Health Sciences, University of Leicester, Leicester, UK.
| | - Yingting Zuo
- Department of Clinical Epidemiology, Beijing Institute of Respiratory Medicine and Beijing Chao-Yang Hospital, Capital Medical University, Beijing, China.
| | - Jian Su
- School of Economics, Peking University, Beijing, China.
| | - Zhaohui Tong
- Department of Respiratory and Critical Care Medicine, Beijing Institute of Respiratory Medicine and Beijing Chao Yang Hospital, Capital Medical University, Beijing, China.
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28
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Chen S, Zhang Y, Wang Y, Lawrence WR, Rhee J, Guo T, Chen S, Du Z, Wu W, Li Z, Wei J, Hao Y, Zhang W. Long-term particulate matter exposure and the risk of neurological hospitalization: Evidence from causal inference of a large longitudinal cohort in South China. CHEMOSPHERE 2023; 345:140397. [PMID: 37838030 PMCID: PMC10841469 DOI: 10.1016/j.chemosphere.2023.140397] [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: 06/29/2023] [Revised: 09/12/2023] [Accepted: 10/08/2023] [Indexed: 10/16/2023]
Abstract
With limited evidence on the neurological impact of particulate matter (PM) exposure in China, particularly for PM1 which is smaller but more toxic, we conducted a large Chinese cohort study using causal inference approaches to comprehensively clarify such impact. A total of 36,271 participants in southern China were recruited in 2015 and followed up through 2020. We obtained the neurological hospitalizations records by linking the cohort data to the electronic reports from 418 medical institutions across the study area. By using high-resolution PM concentrations from satellite-based spatiotemporal models and the cohort data, we performed marginal structural Cox models under causal assumptions to assess the potential causal links between time-varying PM exposure and neurological hospitalizations. Our findings indicated that increasing PM1, PM2.5, and PM10 concentrations by 1 μg/m³ were associated with higher overall neurological hospitalization risks, with hazard ratios (HRs) of 1.10 (95% confidence interval (CI) 1.04-1.16), 1.09 (95% CI 1.04-1.14), and 1.03 (95% CI 1.00-1.06), respectively. PM1 appeared to have a stronger effect on neurological hospitalization, with a 1% and 7% higher impact compared to PM2.5 and PM10, respectively. Additionally, each 1-μg/m3 increase in the annual PM1 concentration was associated with an elevated risk of hospitalizations for ischemic stroke (HR: 1.15; 95% CI, 1.06-1.26), which tended to be larger than the estimates for PM2.5 (HR: 1.13, 95% CI, 1.04-1.23) and PM10 (HR: 1.05, 95% CI, 1.00-1.09). Furthermore, never-married or female individuals tended be at a greater risk compared with their counterparts. Our study provides important insights into the health impact of particles, particularly smaller particles, on neurological hospitalization risk and highlights the need for clean-air policies that specifically target these particles.
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Affiliation(s)
- Shimin Chen
- Department of Medical Statistics, School of Health & Center for Health Information Research & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, Guangdong, China
| | - Yuqin Zhang
- Department of Medical Statistics, School of Health & Center for Health Information Research & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, Guangdong, China
| | - Ying Wang
- Department of Medical Statistics, School of Health & Center for Health Information Research & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, Guangdong, China
| | - Wayne R Lawrence
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Rockville, MD, United States
| | - Jongeun Rhee
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Rockville, MD, United States
| | - Tong Guo
- Department of Medical Statistics, School of Health & Center for Health Information Research & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, Guangdong, China
| | - Shirui Chen
- Department of Medical Statistics, School of Health & Center for Health Information Research & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, Guangdong, China
| | - Zhicheng Du
- Department of Medical Statistics, School of Health & Center for Health Information Research & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, Guangdong, China
| | - Wenjing Wu
- Department of Medical Statistics, School of Health & Center for Health Information Research & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, Guangdong, China
| | - Zhiqiang Li
- Department of Medical Statistics, School of Health & Center for Health Information Research & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, Guangdong, China
| | - Jing Wei
- Department of Atmospheric and Oceanic Science, Earth System Science Interdisciplinary Center, University of Maryland, College Park, MD, United States.
| | - Yuantao Hao
- Peking University Center for Public Health and Epidemic Preparedness & Response, Peking, China; Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, China.
| | - Wangjian Zhang
- Department of Medical Statistics, School of Health & Center for Health Information Research & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, Guangdong, China.
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29
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Ziou M, Gao CX, Wheeler AJ, Zosky GR, Stephens N, Knibbs LD, Melody SM, Venn AJ, Dalton MF, Dharmage SC, Johnston FH. Contrasting Health Outcomes following a Severe Smoke Episode and Ambient Air Pollution in Early Life: Findings from an Australian Data Linkage Cohort Study of Hospital Utilization. ENVIRONMENTAL HEALTH PERSPECTIVES 2023; 131:117005. [PMID: 37962441 PMCID: PMC10644899 DOI: 10.1289/ehp12238] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/04/2022] [Revised: 10/22/2023] [Accepted: 10/23/2023] [Indexed: 11/15/2023]
Abstract
BACKGROUND Episodic spikes in air pollution due to landscape fires are increasing, and their potential for longer term health impacts is uncertain. OBJECTIVE Our objective is to evaluate associations between exposure in utero and in infancy to severe pollution from a mine fire, background ambient air pollution, and subsequent hospital care. METHODS We linked health records of births, emergency department (ED) visits, and hospitalizations of children born in the Latrobe Valley, Australia, 2012-2015, which included a severe pollution episode from a mine fire (9 February 2014 to 25 March 2014). We assigned modeled exposure estimates for fire-related and ambient particulate matter with an aerodynamic diameter of 2.5 μ m (PM 2.5 ) to residential address. We used logistic regression to estimate associations with hospital visits for any cause and groupings of infectious, allergic, and respiratory conditions. Outcomes were assessed for the first year of life in the in utero cohort and the year following the fire in the infant cohort. We estimated exposure-response for both fire-related and ambient PM 2.5 and also employed inverse probability weighting using the propensity score to compare exposed and not/minimally exposed children. RESULTS Prenatal exposure to fire-related PM 2.5 was associated with ED presentations for allergies/skin rash [odds ratio ( OR ) = 1.34 , 95% confidence interval (CI): 1.01, 1.76 per 240 μ g / m 3 increase]. Exposure in utero to ambient PM 2.5 was associated with overall presentations (OR = 1.18 , 95% CI: 1.05, 1.33 per 1.4 μ g / m 3 ) and visits for infections (ED: OR = 1.13 , 95% CI: 0.98, 1.29; hospitalizations: OR = 1.23 , 95% CI: 1.00, 1.52). Exposure in infancy to fire-related PM 2.5 compared to no/minimal exposure, was associated with ED presentations for respiratory (OR = 1.37 , 95% CI: 1.05, 1.80) and infectious conditions (any: OR = 1.21 , 95% CI: 0.98, 1.49; respiratory-related: OR = 1.39 , 95% CI: 1.05, 1.83). Early life exposure to ambient PM 2.5 was associated with overall ED visits (OR = 1.17 , 95% CI: 1.05, 1.30 per 1.4 μ g / m 3 increase). DISCUSSION Higher episodic and lower ambient concentrations of PM 2.5 in early life were associated with visits for allergic, respiratory, and infectious conditions. Our findings also indicated differences in associations at the two developmental stages. https://doi.org/10.1289/EHP12238.
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Affiliation(s)
- Myriam Ziou
- Menzies Institute for Medical Research, University of Tasmania, Hobart, Tasmania, Australia
| | - Caroline X. Gao
- Department of Epidemiology and Preventive Medicine, Monash University, Melbourne, Victoria, Australia
- Centre for Youth Mental Health, The University of Melbourne, Parkville, Victoria, Australia
| | - Amanda J. Wheeler
- Menzies Institute for Medical Research, University of Tasmania, Hobart, Tasmania, Australia
- Commonwealth Scientific and Industrial Research Organisation (CSIRO) Oceans and Atmosphere, Aspendale, Victoria, Australia
| | - Graeme R. Zosky
- Menzies Institute for Medical Research, University of Tasmania, Hobart, Tasmania, Australia
- Tasmanian School of Medicine, University of Tasmania, Hobart, Tasmania, Australia
| | - Nicola Stephens
- Tasmanian School of Medicine, University of Tasmania, Hobart, Tasmania, Australia
| | - Luke D. Knibbs
- School of Public Health, The University of Sydney, New South Wales, Australia
- Public Health Research Analytics and Methods for Evidence, Public Health Unit, Sydney Local Health District, Camperdown, New South Wales, Australia
| | - Shannon M. Melody
- Menzies Institute for Medical Research, University of Tasmania, Hobart, Tasmania, Australia
| | - Alison J. Venn
- Menzies Institute for Medical Research, University of Tasmania, Hobart, Tasmania, Australia
| | - Marita F. Dalton
- Menzies Institute for Medical Research, University of Tasmania, Hobart, Tasmania, Australia
| | - Shyamali C. Dharmage
- Allergy and Lung Health Unit, School of Population and Global Health, The University of Melbourne, Carlton, Victoria, Australia
| | - Fay H. Johnston
- Menzies Institute for Medical Research, University of Tasmania, Hobart, Tasmania, Australia
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Song D, Liu D, Ning W, Chen Y, Yang J, Zhao C, Zhang H. Incidence, prevalence and characteristics of multimorbidity in different age groups among urban hospitalized patients in China. Sci Rep 2023; 13:18798. [PMID: 37914899 PMCID: PMC10620234 DOI: 10.1038/s41598-023-46227-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2023] [Accepted: 10/30/2023] [Indexed: 11/03/2023] Open
Abstract
The aim of the study was to investigate the incidence, prevalence and characteristics of multimorbidity in urban inpatients of different age groups. This study used data from the National Insurance Claim for Epidemiology Research (NICER) to calculate the overall incidence, prevalence, geographic and age distribution patterns, health care burden, and multimorbidity patterns for multimorbidity in 2017. According to our study, the overall prevalence of multimorbidity was 6.68%, and the overall prevalence was 14.87% in 2017. The prevalence of multimorbidity increases with age. The pattern of the geographic distribution of multimorbidity shows that the prevalence of multimorbidity is relatively high in South East China. The average annual health care expenditure of patients with multimorbidity increased with age and rose rapidly, especially among older patients. Patients with cancer and chronic kidney disease have higher treatment costs. Patients with hypertension or ischemic heart disease had a significantly higher relative risk of multimorbidity than other included noncommunicable diseases (NCDs). Hyperlipidemia has generated the highest number of association rules, which may suggest that hyperlipidemia may be both a risk factor for other NCDs and an outcome of them.
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Affiliation(s)
- Dixiang Song
- Department of Neurosurgery, Sanbo Brain Hospital, Capital Medical University, Beijing, China
| | - Deshan Liu
- Department of Neurosurgery, Sanbo Brain Hospital, Capital Medical University, Beijing, China
| | - Weihai Ning
- Department of Neurosurgery, Sanbo Brain Hospital, Capital Medical University, Beijing, China
| | - Yujia Chen
- Department of Neurosurgery, Sanbo Brain Hospital, Capital Medical University, Beijing, China
| | - Jingjing Yang
- Department of Neurosurgery, Sanbo Brain Hospital, Capital Medical University, Beijing, China
| | - Chao Zhao
- Department of Neurosurgery, Sanbo Brain Hospital, Capital Medical University, Beijing, China
| | - Hongwei Zhang
- Department of Neurosurgery, Sanbo Brain Hospital, Capital Medical University, Beijing, China.
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31
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Yin P, Luo H, Gao Y, Liu W, Shi S, Li X, Meng X, Kan H, Zhou M, Li G, Chen R. Criteria air pollutants and diabetes mortality classified by different subtypes and complications: A nationwide, case-crossover study. JOURNAL OF HAZARDOUS MATERIALS 2023; 460:132412. [PMID: 37696209 DOI: 10.1016/j.jhazmat.2023.132412] [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: 06/14/2023] [Revised: 08/09/2023] [Accepted: 08/24/2023] [Indexed: 09/13/2023]
Abstract
The associations between air pollution and diabetes mortality of different subtypes and complications were largely unclear. We performed an individual-level, time-stratified case-crossover study among over 0.9 million diabetes deaths from all administrative regions of Chinese mainland during 2013-2019. Daily concentrations of fine particles (PM2.5), coarse particles (PM2.5-10), nitrogen dioxide (NO2) and ozone (O3) were obtained for each decedent using high-resolution prediction models. Conditional logistic regression models were utilized to analyze the data. Each interquartile range increment in PM2.5, PM2.5-10, NO2 and O3 concentrations on lag 0-2 d increased the risks of overall diabetes mortality by 2.81 %, 1.92 %, 3.96 % and 2.15 %, respectively. Type 2 diabetes had stronger associations with air pollution than type 1 diabetes. Air pollutants were associated with diabetic ketoacidosis and diabetic nephropathy, but not other complications. The exposure-response curves were approximately linear with a plateau at higher concentrations of PM2.5, PM2.5-10, and NO2, while the associations for O3 appear to be statistically significant beyond 60 μg/m3. This nationwide study reinforces the evidence of higher risks of acute diabetic events following short-term air pollution exposure. We identified differential effects of air pollutants on various subtypes and complications of diabetes, which require further mechanistic investigations.
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Affiliation(s)
- Peng Yin
- National Center for Chronic Noncommunicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Huihuan Luo
- School of Public Health, Key Lab of Public Health Safety of the Ministry of Education and NHC Key Lab 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 Lab of Health Technology Assessment, Fudan University, Shanghai, China
| | - Wei Liu
- National Center for Chronic Noncommunicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Su Shi
- School of Public Health, Key Lab of Public Health Safety of the Ministry of Education and NHC Key Lab of Health Technology Assessment, Fudan University, Shanghai, China
| | - Xinyue Li
- School of Public Health, Key Lab of Public Health Safety of the Ministry of Education and NHC Key Lab of Health Technology Assessment, Fudan University, Shanghai, China
| | - Xia Meng
- School of Public Health, Key Lab of Public Health Safety of the Ministry of Education and NHC Key Lab of Health Technology Assessment, Fudan University, Shanghai, China
| | - Haidong Kan
- School of Public Health, Key Lab of Public Health Safety of the Ministry of Education and NHC Key Lab of Health Technology Assessment, Fudan University, Shanghai, China
| | - Maigeng Zhou
- National Center for Chronic Noncommunicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Guanglin Li
- Chinese Preventive Medicine Association, Beijing, China.
| | - Renjie Chen
- School of Public Health, Key Lab of Public Health Safety of the Ministry of Education and NHC Key Lab of Health Technology Assessment, Fudan University, Shanghai, China.
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32
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Xue Y, Li J, Xu YN, Cui JS, Li Y, Lu YQ, Luo XZ, Liu DZ, Huang F, Zeng ZY, Huang RJ. Mediating effect of body fat percentage in the association between ambient particulate matter exposure and hypertension: a subset analysis of China hypertension survey. BMC Public Health 2023; 23:1897. [PMID: 37784103 PMCID: PMC10544618 DOI: 10.1186/s12889-023-16815-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2023] [Accepted: 09/22/2023] [Indexed: 10/04/2023] Open
Abstract
BACKGROUND Hypertension caused by air pollution exposure is a growing concern in China. The association between air pollutant exposure and hypertension has been found to be potentiated by obesity, however, little is known about the processes mediating this association. This study investigated the association between fine particulate matter (aerodynamic equivalent diameter ≤ 2.5 microns, PM2.5) exposure and the prevalence of hypertension in a representative population in southern China and tested whether obesity mediated this association. METHODS A total of 14,308 adults from 48 communities/villages in southern China were selected from January 2015 to December 2015 using a stratified multistage random sampling method. Hourly PM2.5 measurements were collected from the China National Environmental Monitoring Centre. Restricted cubic splines were used to analyze the nonlinear dose-response relationship between PM2.5 exposure and hypertension risk. The mediating effect mechanism of obesity on PM2.5-associated hypertension was tested in a causal inference framework following the approach proposed by Imai and Keele. RESULTS A total of 20.7% (2966/14,308) of participants in the present study were diagnosed with hypertension. Nonlinear exposure-response analysis revealed that exposure to an annual mean PM2.5 concentration above 41.8 µg/m3 was associated with increased hypertension risk at an incremental gradient. 9.1% of the hypertension burden could be attributed to exposure to elevated annual average concentrations of PM2.5. It is noteworthy that an increased body fat percentage positively mediated 59.3% of the association between PM2.5 exposure and hypertension risk, whereas body mass index mediated 34.3% of this association. CONCLUSIONS This study suggests that a significant portion of the estimated effect of exposure to PM2.5 on the risk of hypertension appears to be attributed to its effect on alterations in body composition and the development of obesity. These findings could inform intersectoral actions in future studies to protect populations with excessive fine particle exposure from developing hypertension.
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Affiliation(s)
- Yan Xue
- Department of Cardiology, The First Affiliated Hospital of Guangxi Medical University, No.6 Shuangyong Road, Nanning, 530021, China
- Guangxi Key Laboratory of Precision Medicine in Cardio-Cerebrovascular Diseases Control and Prevention, Nanning, China
- Guangxi Clinical Research Center for Cardio-Cerebrovascular Diseases, Nanning, China
| | - Jin Li
- Department of Cardiology, The First Affiliated Hospital of Guangxi Medical University, No.6 Shuangyong Road, Nanning, 530021, China
- Guangxi Key Laboratory of Precision Medicine in Cardio-Cerebrovascular Diseases Control and Prevention, Nanning, China
- Guangxi Clinical Research Center for Cardio-Cerebrovascular Diseases, Nanning, China
| | - Yu-Nan Xu
- Department of Medical Research, The First Affiliated Hospital of Guangxi Medical University, Nanning, China
| | - Jia-Sheng Cui
- Department of Cardiology, The First Affiliated Hospital of Guangxi Medical University, No.6 Shuangyong Road, Nanning, 530021, China
- Guangxi Key Laboratory of Precision Medicine in Cardio-Cerebrovascular Diseases Control and Prevention, Nanning, China
- Guangxi Clinical Research Center for Cardio-Cerebrovascular Diseases, Nanning, China
| | - Yue Li
- Department of Cardiology, The First Affiliated Hospital of Guangxi Medical University, No.6 Shuangyong Road, Nanning, 530021, China
- Guangxi Key Laboratory of Precision Medicine in Cardio-Cerebrovascular Diseases Control and Prevention, Nanning, China
- Guangxi Clinical Research Center for Cardio-Cerebrovascular Diseases, Nanning, China
| | - Yao-Qiong Lu
- Department of Cardiology, The First Affiliated Hospital of Guangxi Medical University, No.6 Shuangyong Road, Nanning, 530021, China
- Guangxi Key Laboratory of Precision Medicine in Cardio-Cerebrovascular Diseases Control and Prevention, Nanning, China
- Guangxi Clinical Research Center for Cardio-Cerebrovascular Diseases, Nanning, China
| | - Xiao-Zhi Luo
- Department of Cardiology, The First Affiliated Hospital of Guangxi Medical University, No.6 Shuangyong Road, Nanning, 530021, China
- Guangxi Key Laboratory of Precision Medicine in Cardio-Cerebrovascular Diseases Control and Prevention, Nanning, China
- Guangxi Clinical Research Center for Cardio-Cerebrovascular Diseases, Nanning, China
| | - De-Zhao Liu
- Department of Cardiology, The First Affiliated Hospital of Guangxi Medical University, No.6 Shuangyong Road, Nanning, 530021, China
- Guangxi Key Laboratory of Precision Medicine in Cardio-Cerebrovascular Diseases Control and Prevention, Nanning, China
- Guangxi Clinical Research Center for Cardio-Cerebrovascular Diseases, Nanning, China
| | - Feng Huang
- Department of Cardiology, The First Affiliated Hospital of Guangxi Medical University, No.6 Shuangyong Road, Nanning, 530021, China.
- Guangxi Key Laboratory of Precision Medicine in Cardio-Cerebrovascular Diseases Control and Prevention, Nanning, China.
- Guangxi Clinical Research Center for Cardio-Cerebrovascular Diseases, Nanning, China.
| | - Zhi-Yu Zeng
- Department of Cardiology, The First Affiliated Hospital of Guangxi Medical University, No.6 Shuangyong Road, Nanning, 530021, China.
- Guangxi Key Laboratory of Precision Medicine in Cardio-Cerebrovascular Diseases Control and Prevention, Nanning, China.
- Guangxi Clinical Research Center for Cardio-Cerebrovascular Diseases, Nanning, China.
| | - Rong-Jie Huang
- Department of Cardiology, The First Affiliated Hospital of Guangxi Medical University, No.6 Shuangyong Road, Nanning, 530021, China.
- Guangxi Key Laboratory of Precision Medicine in Cardio-Cerebrovascular Diseases Control and Prevention, Nanning, China.
- Guangxi Clinical Research Center for Cardio-Cerebrovascular Diseases, Nanning, China.
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He YS, Wu ZD, Wang GH, Wang X, Mei YJ, Sui C, Tao SS, Zhao CN, Wang P, Ni J, Pan HF. Impact of short-term exposure to ambient air pollution on osteoarthritis: a multi-city time-series analysis in Central-Eastern China. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2023; 30:104258-104269. [PMID: 37700129 DOI: 10.1007/s11356-023-29694-0] [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: 02/09/2023] [Accepted: 08/31/2023] [Indexed: 09/14/2023]
Abstract
Osteoarthritis (OA) is a threat to public health issue with high morbidity and disability worldwide. However, unequivocal evidence on the link between air pollution and OA remains little, especially in multi-study sites. This study aimed to explore the relationship between short-term exposure to main air pollutants and the risk of OA outpatient visits in multi-study sites. A multi-city time-series analysis was performed in Anhui Province, Central-Eastern China from January 1, 2015, to December 31, 2020. We used a two-stage analysis to assess the association between air pollution and daily OA outpatient visits. City-specific associations were estimated with a distributed lag nonlinear model and then pooled by random-effects or fixed-effects meta-analysis. Stratified analysis was conducted by gender, age, and season. Additionally, the disease burden of OA attributable to air pollutant exposure was calculated. A total of 35,700 OA outpatients were included during the study period. The pooled exposure-response curves showed that PM2.5 and PM10 concentrations below the reference values could increase the risk of OA outpatient visits. Concretely, per 10 ug/m3 increase in PM2.5 concentration was linked to an elevated risk of OA outpatient visits at lag 2 and lag 3 days, where the effect reached its highest value on lag 2 day (RR: 1.023, 95%CI: 1.005-1.041). We observed that a 10 μg/m3 increase in PM10 was positively correlated with OA outpatient visits (lag2 day, RR: 1.011, 95%CI: 1.001-1.025). Nevertheless, no statistical significance was discovered in gaseous pollutants (including SO2, O3, and CO). Additionally, a significant difference was found between cold and warm seasons, but not between different genders or age groups. This study reveals that particulate matter is an important factor for the onset of OA in Anhui Province, China. However, there is no evidence of a relationship of gaseous pollutants with OA in this area.
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Affiliation(s)
- Yi-Sheng He
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, 230032, Anhui, People's Republic of China
- Institute of Kidney Disease, Inflammation & Immunity Mediated Diseases, The Second Hospital of Anhui Medical University, Hefei, 230032, Anhui, People's Republic of China
- Anhui Provincial Institute of Translational Medicine, Anhui Medical University, 81 Meishan Road, Hefei, 230032, Anhui, People's Republic of China
| | - Zheng-Dong Wu
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, 230032, Anhui, People's Republic of China
- Institute of Kidney Disease, Inflammation & Immunity Mediated Diseases, The Second Hospital of Anhui Medical University, Hefei, 230032, Anhui, People's Republic of China
- Anhui Provincial Institute of Translational Medicine, Anhui Medical University, 81 Meishan Road, Hefei, 230032, Anhui, People's Republic of China
| | - Gui-Hong Wang
- Department of Rheumatology, Anqing Hospital Affiliated to Anhui Medical University, Anqing, Anhui, People's Republic of China
| | - Xiaohu Wang
- The First Affiliated Hospital of Anhui Medical University, Hefei, People's Republic of China
| | - Yong-Jun Mei
- Department of Rheumatology and Immunology, The First Affiliated Hospital of Bengbu Medical College, Bengbu, People's Republic of China
| | - Cong Sui
- Department of Orthopedics Trauma, the First Affiliated Hospital of Anhui Medical University, Hefei, 230032, Anhui, People's Republic of China
| | - Sha-Sha Tao
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, 230032, Anhui, People's Republic of China
- Institute of Kidney Disease, Inflammation & Immunity Mediated Diseases, The Second Hospital of Anhui Medical University, Hefei, 230032, Anhui, People's Republic of China
- Anhui Provincial Institute of Translational Medicine, Anhui Medical University, 81 Meishan Road, Hefei, 230032, Anhui, People's Republic of China
| | - Chan-Na Zhao
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, 230032, Anhui, People's Republic of China
- Institute of Kidney Disease, Inflammation & Immunity Mediated Diseases, The Second Hospital of Anhui Medical University, Hefei, 230032, Anhui, People's Republic of China
- Anhui Provincial Institute of Translational Medicine, Anhui Medical University, 81 Meishan Road, Hefei, 230032, Anhui, People's Republic of China
| | - Peng Wang
- Teaching Center for Preventive Medicine, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, 230016, Anhui, People's Republic of China
| | - Jing Ni
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, 230032, Anhui, People's Republic of China
- Institute of Kidney Disease, Inflammation & Immunity Mediated Diseases, The Second Hospital of Anhui Medical University, Hefei, 230032, Anhui, People's Republic of China
- Anhui Provincial Institute of Translational Medicine, Anhui Medical University, 81 Meishan Road, Hefei, 230032, Anhui, People's Republic of China
| | - Hai-Feng Pan
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, 230032, Anhui, People's Republic of China.
- Institute of Kidney Disease, Inflammation & Immunity Mediated Diseases, The Second Hospital of Anhui Medical University, Hefei, 230032, Anhui, People's Republic of China.
- Anhui Provincial Institute of Translational Medicine, Anhui Medical University, 81 Meishan Road, Hefei, 230032, Anhui, People's Republic of China.
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Wang C, Amini H, Xu Z, Peralta AA, Yazdi MD, Qiu X, Wei Y, Just A, Heiss J, Hou L, Zheng Y, Coull BA, Kosheleva A, Baccarelli AA, Schwartz JD. Long-term exposure to ambient fine particulate components and leukocyte epigenome-wide DNA Methylation in older men: the Normative Aging Study. Environ Health 2023; 22:54. [PMID: 37550674 PMCID: PMC10405403 DOI: 10.1186/s12940-023-01007-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2023] [Accepted: 07/26/2023] [Indexed: 08/09/2023]
Abstract
BACKGROUND Epigenome-wide association studies of ambient fine particulate matter (PM2.5) have been reported. However, few have examined PM2.5 components (PMCs) and sources or included repeated measures. The lack of high-resolution exposure measurements is the key limitation. We hypothesized that significant changes in DNA methylation might vary by PMCs and the sources. METHODS We predicted the annual average of 14 PMCs using novel high-resolution exposure models across the contiguous U.S., between 2000-2018. The resolution was 50 m × 50 m in the Greater Boston Area. We also identified PM2.5 sources using positive matrix factorization. We repeatedly collected blood samples and measured leukocyte DNAm with the Illumina HumanMethylation450K BeadChip in the Normative Aging Study. We then used median regression with subject-specific intercepts to estimate the associations between long-term (one-year) exposure to PMCs / PM2.5 sources and DNA methylation at individual cytosine-phosphate-guanine CpG sites. Significant probes were identified by the number of independent degrees of freedom approach, using the number of principal components explaining > 95% of the variation of the DNA methylation data. We also performed regional and pathway analyses to identify significant regions and pathways. RESULTS We included 669 men with 1,178 visits between 2000-2013. The subjects had a mean age of 75 years. The identified probes, regions, and pathways varied by PMCs and their sources. For example, iron was associated with 6 probes and 6 regions, whereas nitrate was associated with 15 probes and 3 regions. The identified pathways from biomass burning, coal burning, and heavy fuel oil combustion sources were associated with cancer, inflammation, and cardiovascular diseases, whereas there were no pathways associated with all traffic. CONCLUSIONS Our findings showed that the effects of PM2.5 on DNAm varied by its PMCs and sources.
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Affiliation(s)
- Cuicui Wang
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA, 02115, USA.
| | - Heresh Amini
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA, 02115, USA
- Department of Public Health, Faculty of Health and Medical Sciences, Section of Environmental Health, University of Copenhagen, Copenhagen, Denmark
| | - Zongli Xu
- Biostatistics & Computational Biology Branch, National Institute of Environmental Health Sciences, NIH, Research Triangle Park, Durham, NC, USA
| | - Adjani A Peralta
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA, 02115, USA
| | - Mahdieh Danesh Yazdi
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA, 02115, USA
- Program in Public Health, Department of Family, Population, and Preventive Medicine, Renaissance School of Medicine at Stony Brook University, Stony Brook, NY, USA
| | - Xinye Qiu
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA, 02115, USA
| | - Yaguang Wei
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA, 02115, USA
| | - Allan Just
- Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Jonathan Heiss
- Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Lifang Hou
- Department of Preventive Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL, 60611, USA
| | - Yinan Zheng
- Department of Preventive Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL, 60611, USA
| | - Brent A Coull
- Department of Biostatistics, Harvard T. H. Chan School of Public Health, Boston, MA, 02115, USA
| | - Anna Kosheleva
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA, 02115, USA
| | - Andrea A Baccarelli
- Department of Environmental Health Sciences, Columbia Mailman School of Public Health, New York, NY, 10032, USA
| | - Joel D Schwartz
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA, 02115, USA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, 02115, USA
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Hou X, Mao Z, Song X, Li R, Liao W, Kang N, Zhang C, Liu X, Chen R, Huo W, Wang C, Hou J. Synergistic association of long-term ozone exposure and solid fuel use with biomarkers of advanced fibrosis. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2023; 30:85318-85329. [PMID: 37382821 DOI: 10.1007/s11356-023-28337-8] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/01/2023] [Accepted: 06/13/2023] [Indexed: 06/30/2023]
Abstract
This study aims to explore the association of combined exposure to cooking fuel type and ambient ozone (O3) levels with hepatic fibrosis indices among rural adults. A total of 21,010 participants were derived from the Henan Rural Cohort. Information regarding cooking fuel type was collected through a questionnaire, and the concentration of ground-level O3 for each subject was obtained from the Tracking Air Pollution in China (TAP) dataset. A generalized linear model was used to examine the independent association of cooking fuel type or O3 exposure with hepatic fibrosis indices (FIB-4, APRI, and AST/ALT), and their possible interactions with advanced fibrosis were conducted. Compared to clean fuel users, solid fuel users had increased the risk of advanced fibrosis, the adjusted odds ratio (OR) of its assessment by FIB-4 1.240 (1.151, 1.336), by APRI 1.298 (1.185, 1.422), and by AST/ALT 1.135 (1.049, 1.227), respectively. Compared to low O3 exposure, the adjusted ORs of advanced fibrosis assessed by FIB-4, APRI, and AST/ALT in women with high O3 exposure were correspondingly 1.219 (1.138, 1.305), 1.110 (1.017, 1.212), and 0.883 (0.822, 0.949). The adjusted ORs of advanced fibrosis assessed by FIB-4, APRI, and AST/ALT for solid fuel users with high O3 exposure relative to clean fuel users with low O3 exposure in women were 1.557 (1.381, 1.755), 1.427 (1.237, 1.644), and 0.979 (0.863, 1.108), respectively. Significant additive effect of O3 exposure and solid fuel use on FIB-4-defined advanced fibrosis was observed in women, which was quantified by RERI (0.265, 95%CI: 0.052, 0.477), AP (0.170 95%CI: 0.045, 0.295), and SI (1.906, 95%CI: 1.058, 3.432). Solid fuel users with high O3 exposure were significantly associated with elevated hepatic fibrosis indices among rural women, suggesting that poor air quality may induce hepatocellular injury, and women might be more vulnerable to air pollution. The findings indicate that using cleaner fuels in cooking is an effective measure to maintain sustainable development of the environment and gain beneficial effect on human health. Clinical trial registration: The Henan Rural Cohort Study has been registered at the 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)
- Xiaoyu Hou
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, 450001, Henan, People's Republic of China
| | - Zhenxing Mao
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, 450001, Henan, People's Republic of China
| | - Xiaoqin Song
- Physical Examination Center, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, People's Republic of China
| | - Ruiying Li
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, 450001, Henan, People's Republic of China
| | - Wei Liao
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, 450001, Henan, People's Republic of China
| | - Ning Kang
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, 450001, Henan, People's Republic of China
| | - Caiyun Zhang
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, 450001, Henan, People's Republic of China
| | - Xiaotian Liu
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, 450001, Henan, People's Republic of China
| | - Ruoling Chen
- Faculty of Education, Health and Wellbeing, University of Wolverhampton, Wolverhampton, UK
| | - Wenqian Huo
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, 450001, Henan, People's Republic of China
| | - Chongjian Wang
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, 450001, Henan, People's Republic of China
| | - Jian Hou
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, 450001, Henan, People's Republic of China.
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Zhang W, Zhang R, Tian T, Liu T, Dong J, Ruan Y. Acute effects of air pollution on type II diabetes mellitus hospitalization in Lanzhou, China. ENVIRONMENTAL GEOCHEMISTRY AND HEALTH 2023; 45:5927-5941. [PMID: 37184722 DOI: 10.1007/s10653-023-01604-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: 12/04/2022] [Accepted: 05/02/2023] [Indexed: 05/16/2023]
Abstract
Studies on the effects of short-term air pollution exposure on hospitalization for type 2 diabetes mellitus (T2DM) are relatively scarce in developing regions. The time-series study was used to explore the acute effects of air pollutants on hospitalization for T2DM in Lanzhou, China. A distribution lag nonlinear model based on the generalized additive model was used to analyze the hospitalization impact of air pollution on T2DM. Stratified analysis by gender, age and season was obtained. The results were indicated as the relative risk (RR) with 95% confidence interval (CI) for single-day lags (from lag0 to lag7) and cumulative lag days (from lag0-1 to lag0-7). The strongest correlations (RR, 95% CI) of hospitalization for T2DM and PM10 (RR = 1.003, 95% CI 1.000, 1.001) at lag7 and NO2 (RR = 1.022, 95% CI 1.000, 1.045) at lag0-4 were observed for an increase of 10 µg/m3 in the concentrations and CO (RR = 1.091, 95% CI 1.017, 1.170) at lag0-4 for an increase of 1 mg/m3 in the concentration. The hazardous impacts of PM10, NO2 and CO were greater for females, people aged ≥ 65 years and in the cold season. However, there was no significant association between PM2.5, SO2 and O38h and the number of hospitalizations for T2DM.
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Affiliation(s)
- Wancheng Zhang
- School of Public Health, Lanzhou University, Lanzhou, 730000, People's Republic of China
| | - Runping Zhang
- School of Public Health, Lanzhou University, Lanzhou, 730000, People's Republic of China
| | - Tian Tian
- School of Public Health, Lanzhou University, Lanzhou, 730000, People's Republic of China
| | - Tong Liu
- School of Public Health, Lanzhou University, Lanzhou, 730000, People's Republic of China
| | - Jiyuan Dong
- School of Public Health, Lanzhou University, Lanzhou, 730000, People's Republic of China
| | - Ye Ruan
- School of Public Health, Lanzhou University, Lanzhou, 730000, People's Republic of China.
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Chu L, Chen K, Di Q, Crowley S, Dubrow R. Associations between short-term exposure to PM 2.5, NO 2 and O 3 pollution and kidney-related conditions and the role of temperature-adjustment specification: A case-crossover study in New York state. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2023; 328:121629. [PMID: 37054868 DOI: 10.1016/j.envpol.2023.121629] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/08/2023] [Revised: 03/24/2023] [Accepted: 04/11/2023] [Indexed: 05/09/2023]
Abstract
Epidemiologic evidence on the relationship between air pollution and kidney disease remains inconclusive. We evaluated associations between short-term exposure to PM2.5, NO2 and O3 and unplanned hospital visits for seven kidney-related conditions (acute kidney failure [AKF], urolithiasis, glomerular diseases [GD], renal tubulo-interstitial diseases, chronic kidney disease, dysnatremia, and volume depletion; n = 1,209,934) in New York State (2007-2016). We applied a case-crossover design with conditional logistic regression, controlling for temperature, dew point temperature, wind speed, and solar radiation. We used a three-pollutant model at lag 0-5 days of exposure as our main model. We also assessed the influence of model adjustment using different specifications of temperature by comparing seven temperature metrics (e.g., dry-bulb temperature, heat index) and five intraday temperature measures (e.g., daily mean, daily minimum, nighttime mean), according to model performance and association magnitudes between air pollutants and kidney-related conditions. In our main models, we adjusted for daytime mean outdoor wet-bulb globe temperature, which showed good model performance across all kidney-related conditions. We observed the odds ratios (ORs) for 5 μg/m3 increase in daily mean PM2.5 to be 1.013 (95% confidence interval [CI]: 1.001, 1.025) for AKF, 1.107 (95% CI: 1.018, 1.203) for GD, and 1.027 (95% CI: 1.015, 1.038) for volume depletion; and the OR for 5 ppb increase in daily 1-hour maximum NO2 to be 1.014 (95% CI; 1.008, 1.021) for AKF. We observed no associations with daily 8-hour maximum O3 exposure. Association estimates varied by adjustment for different intraday temperature measures: estimates adjusted for measures with poorer model performance resulted in the greatest deviation from estimates adjusted for daytime mean, especially for AKF and volume depletion. Our findings indicate that short-term exposure to PM2.5 and NO2 is a risk factor for specific kidney-related conditions and underscore the need for careful adjustment of temperature in air pollution epidemiologic studies.
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Affiliation(s)
- Lingzhi Chu
- Department of Environmental Health Sciences, Yale School of Public Health, 60 College Street, New Haven, CT, 06520-8034, USA; Yale Center on Climate Change and Health, Yale School of Public Health, 60 College Street, New Haven, CT, 06520-8034, USA.
| | - Kai Chen
- Department of Environmental Health Sciences, Yale School of Public Health, 60 College Street, New Haven, CT, 06520-8034, USA; Yale Center on Climate Change and Health, Yale School of Public Health, 60 College Street, New Haven, CT, 06520-8034, USA
| | - Qian Di
- Vanke School of Public Health, Tsinghua University, Beijing, 100084, China
| | - Susan Crowley
- Department of Medicine (Nephrology), Yale University School of Medicine, New Haven, CT, 06520, USA; Veterans Administration Health Care System of Connecticut, West Haven, CT, 06516, USA
| | - Robert Dubrow
- Department of Environmental Health Sciences, Yale School of Public Health, 60 College Street, New Haven, CT, 06520-8034, USA; Yale Center on Climate Change and Health, Yale School of Public Health, 60 College Street, New Haven, CT, 06520-8034, USA
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Lei J, Chen R, Liu C, Zhu Y, Xue X, Jiang Y, Shi S, Gao Y, Kan H, Xuan J. Fine and coarse particulate air pollution and hospital admissions for a wide range of respiratory diseases: a nationwide case-crossover study. Int J Epidemiol 2023; 52:715-726. [PMID: 37159523 DOI: 10.1093/ije/dyad056] [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: 08/31/2022] [Accepted: 04/20/2023] [Indexed: 05/11/2023] Open
Abstract
BACKGROUND The associations between fine and coarse particulate matter (PM2.5 and PM2.5-10) air pollution and hospital admissions for full-spectrum respiratory diseases were rarely investigated, especially for age-specific associations. We aim to estimate the age-specific associations of short-term exposures to PM2.5 and PM2.5-10 with hospital admissions for full-spectrum respiratory diseases in China. METHODS We conducted an individual-level case-crossover study based on a nationwide hospital-based registry including 153 hospitals across 20 provincial regions in China in 2013-20. We applied conditional logistic regression models and distributed lag models to estimate the exposure- and lag-response associations. RESULTS A total of 1 399 955 hospital admission records for various respiratory diseases were identified. The associations of PM2.5 and PM2.5-10 with total respiratory hospitalizations lasted for 4 days, and an interquartile range increase in PM2.5 (34.5 μg/m3) and PM2.5-10 (26.0 μg/m3) was associated with 1.73% [95% confidence interval (95% CI): 1.34%, 2.12%)] and 1.70% (95% CI: 1.31%, 2.10%) increases, respectively, in total respiratory hospitalizations over lag 0-4 days. Acute respiratory infections (i.e. pneumonia, bronchitis and bronchiolitis) were consistently associated with PM2.5 or PM2.5-10 exposure across different age groups. We found the disease spectrum varied by age, including rarely reported findings (i.e. acute laryngitis and tracheitis, and influenza) among children and well-established associations (i.e. chronic obstructive pulmonary disease, asthma, acute bronchitis and emphysema) among older populations. Besides, the associations were stronger in females, children and older populations. CONCLUSIONS This nationwide case-crossover study provides robust evidence that short-term exposure to both PM2.5 and PM2.5-10 was associated with increased hospital admissions for a wide range of respiratory diseases, and the spectra of respiratory diseases varied by age. Females, children and older populations were more susceptible.
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Affiliation(s)
- Jian Lei
- Department of Environmental Health, School of Public Health, Key Lab of Public Health Safety of the Ministry of Education, NHC Key Lab of Health Technology Assessment, IRDR ICoE on Risk Interconnectivity and Governance on Weather/Climate Extremes Impact and Public Health, Fudan University, Shanghai, China
| | - Renjie Chen
- Department of Environmental Health, School of Public Health, Key Lab of Public Health Safety of the Ministry of Education, NHC Key Lab of Health Technology Assessment, IRDR ICoE on Risk Interconnectivity and Governance on Weather/Climate Extremes Impact and Public Health, Fudan University, Shanghai, China
| | - Cong Liu
- Department of Environmental Health, School of Public Health, Key Lab of Public Health Safety of the Ministry of Education, NHC Key Lab of Health Technology Assessment, IRDR ICoE on Risk Interconnectivity and Governance on Weather/Climate Extremes Impact and Public Health, Fudan University, Shanghai, China
| | - Yixiang Zhu
- Department of Environmental Health, School of Public Health, Key Lab of Public Health Safety of the Ministry of Education, NHC Key Lab of Health Technology Assessment, IRDR ICoE on Risk Interconnectivity and Governance on Weather/Climate Extremes Impact and Public Health, Fudan University, Shanghai, China
| | - Xiaowei Xue
- Department of Environmental Health, School of Public Health, Key Lab of Public Health Safety of the Ministry of Education, NHC Key Lab of Health Technology Assessment, IRDR ICoE on Risk Interconnectivity and Governance on Weather/Climate Extremes Impact and Public Health, Fudan University, Shanghai, China
| | - Yixuan Jiang
- Department of Environmental Health, School of Public Health, Key Lab of Public Health Safety of the Ministry of Education, NHC Key Lab of Health Technology Assessment, IRDR ICoE on Risk Interconnectivity and Governance on Weather/Climate Extremes Impact and Public Health, Fudan University, Shanghai, China
| | - Su Shi
- Department of Environmental Health, School of Public Health, Key Lab of Public Health Safety of the Ministry of Education, NHC Key Lab of Health Technology Assessment, IRDR ICoE on Risk Interconnectivity and Governance on Weather/Climate Extremes Impact and Public Health, Fudan University, Shanghai, China
| | - Ya Gao
- Department of Environmental Health, School of Public Health, Key Lab of Public Health Safety of the Ministry of Education, NHC Key Lab of Health Technology Assessment, IRDR ICoE on Risk Interconnectivity and Governance on Weather/Climate Extremes Impact and Public Health, Fudan University, Shanghai, China
| | - Haidong Kan
- Department of Environmental Health, School of Public Health, Key Lab of Public Health Safety of the Ministry of Education, NHC Key Lab of Health Technology Assessment, IRDR ICoE on Risk Interconnectivity and Governance on Weather/Climate Extremes Impact and Public Health, Fudan University, Shanghai, China
- National Center for Children's Health, Children's Hospital of Fudan University, Shanghai, China
| | - Jianwei Xuan
- Health Economic Research Institute, School of Pharmacy, Sun Yat-Shen University, Guangzhou, China
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Lu YK, Liu XL, Liu YH, Chen N, Gao HY, Jin YH, Yan YX. The effects of short-term exposure to air pollution on mortality in Baotou, China, during 2015-2019. ENVIRONMENTAL GEOCHEMISTRY AND HEALTH 2023; 45:3387-3404. [PMID: 36322227 DOI: 10.1007/s10653-022-01419-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/28/2022] [Accepted: 09/27/2022] [Indexed: 06/01/2023]
Abstract
Air pollution was considered one of the main causes linked to increased morbidity and mortality around the world. This study aimed to estimate the effect of air pollutants on daily death in Baotou city of Inner Mongolia. Daily deaths data were provided by Baotou Centers for Disease Control and Prevention for the years 2015-2019 (Baotou CDC). The air pollutants, PM2.5, PM10, NO2, SO2, CO and maximum 8-h average concentrations of O3, came from the eight environmental monitoring stations in Baotou city. Time-series plots were used to exploit the trend of air pollutants at calendar time. Generalized additive model was used to estimate the effect of air pollutants on daily death. Restricted cubic spline was employed to investigate non-line relationships between air pollutants and daily death. After adjusting the meteorological factors, non-accidental daily deaths were related to PM2.5 (ER = 0.074%) and PM10 (ER = 0.023%), respectively. In stratified analysis, population aged over 65 years and females were more sensitive to air pollutants exposure and warm season might make people more susceptible to air pollutants compared with cold season. PM2.5 and PM10 increase the risk of non-accidental and cardiovascular daily death, but not respiratory daily death.
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Affiliation(s)
- Ya-Ke Lu
- Department of Epidemiology and Biostatistics, School of Public Health, Capital Medical University, Beijing, 100069, China
| | - Xiao-Ling Liu
- Baotou Center for Disease Control and Prevention, Baotou, 014000, Inner Mongolia, China
| | - Yu-Hong Liu
- Department of Epidemiology and Biostatistics, School of Public Health, Capital Medical University, Beijing, 100069, China
| | - Ning Chen
- Department of Epidemiology and Biostatistics, School of Public Health, Capital Medical University, Beijing, 100069, China
| | - Hao-Yu Gao
- Department of Epidemiology and Biostatistics, School of Public Health, Capital Medical University, Beijing, 100069, China
| | - Yan-Hui Jin
- Baotou Center for Disease Control and Prevention, Baotou, 014000, Inner Mongolia, China.
| | - Yu-Xiang Yan
- Department of Epidemiology and Biostatistics, School of Public Health, Capital Medical University, Beijing, 100069, China.
- Municipal Key Laboratory of Clinical Epidemiology, Beijing, 100069, China.
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Fan R, Xu L, Cui B, Li D, Sun X, Qi Y, Rao J, Wang K, Wang C, Zhao K, Zhao Y, Dai J, Chen W, Shen H, Liu Y, Yu D. Genomic Characterization Revealed PM 2.5-Associated Mutational Signatures in Lung Cancer Including Activation of APOBEC3B. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2023; 57:6854-6864. [PMID: 37071573 DOI: 10.1021/acs.est.2c08092] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/03/2023]
Abstract
Fine particulate matter (PM2.5) exposure causes DNA mutations and abnormal gene expression leading to lung cancer, but the detailed mechanisms remain unknown. Here, analysis of genomic and transcriptomic changes upon a PM2.5 exposure-induced human bronchial epithelial cell-based malignant transformed cell model in vitro showed that PM2.5 exposure led to APOBEC mutational signatures and transcriptional activation of APOBEC3B along with other potential oncogenes. Moreover, by analyzing mutational profiles of 1117 non-small cell lung cancers (NSCLCs) from patients across four different geographic regions, we observed a significantly higher prevalence of APOBEC mutational signatures in non-smoking NSCLCs than smoking in the Chinese cohorts, but this difference was not observed in TCGA or Singapore cohorts. We further validated this association by showing that the PM2.5 exposure-induced transcriptional pattern was significantly enriched in Chinese NSCLC patients compared with other geographic regions. Finally, our results showed that PM2.5 exposure activated the DNA damage repair pathway. Overall, here we report a previously uncharacterized association between PM2.5 and APOBEC activation, revealing a potential molecular mechanism of PM2.5 exposure and lung cancer.
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Affiliation(s)
- Rongrong Fan
- School of Public Health, Qingdao University, 308 Ningxia Road, Qingdao 266071, China
| | - Lin Xu
- School of Public Health, Qingdao University, 308 Ningxia Road, Qingdao 266071, China
| | - Bowen Cui
- Pediatric Translational Medicine Institute, Shanghai Children's Medical Center, School of Medicine, Shanghai Jiao Tong University, Shanghai 200127, China
| | - Daochuan Li
- Department of Toxicology, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China
| | - Xueying Sun
- School of Public Health, Qingdao University, 308 Ningxia Road, Qingdao 266071, China
| | - Yuan Qi
- School of Public Health, Qingdao University, 308 Ningxia Road, Qingdao 266071, China
| | - Jianan Rao
- Pediatric Translational Medicine Institute, Shanghai Children's Medical Center, School of Medicine, Shanghai Jiao Tong University, Shanghai 200127, China
| | - Kai Wang
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, China
| | - Cheng Wang
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, China
- Department of Bioinformatics, School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing 211166, China
| | - Kunming Zhao
- School of Public Health, Qingdao University, 308 Ningxia Road, Qingdao 266071, China
| | - Yanjie Zhao
- School of Public Health, Qingdao University, 308 Ningxia Road, Qingdao 266071, China
| | - Juncheng Dai
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, China
- Department of Bioinformatics, School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing 211166, China
| | - Wen Chen
- Department of Toxicology, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China
| | - Hongbing Shen
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, China
- Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine and China International Cooperation Center for Environment and Human Health, Genomic Science and Precision Medicine Institute, Gusu School, Nanjing Medical University, Nanjing 211166, China
| | - Yu Liu
- Pediatric Translational Medicine Institute, Shanghai Children's Medical Center, School of Medicine, Shanghai Jiao Tong University, Shanghai 200127, China
- Key Laboratory of Pediatric Hematology & Oncology Ministry of Health, Department of Hematology & Oncology, Shanghai Children's Medical Center, School of Medicine, Shanghai Jiao Tong University, Shanghai 200127, China
- Fujian Children's Hospital, Fujian Branch of Shanghai Children's Medical Center Affiliated to Shanghai Jiao Tong University School of Medicine, Fuzhou 350000, China
| | - Dianke Yu
- School of Public Health, Qingdao University, 308 Ningxia Road, Qingdao 266071, China
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Zhang Y, Liu Y, Li S, Xu R, Yu P, Ramos C, Ebrahimifakhar A, Guo Y. Efficiency of portable air purification on public buses: A pilot study. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2023; 329:121696. [PMID: 37088254 DOI: 10.1016/j.envpol.2023.121696] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/21/2023] [Revised: 04/15/2023] [Accepted: 04/20/2023] [Indexed: 05/03/2023]
Abstract
High concentrations of fine particulate matter (PM2.5) have been frequently reported in public transit systems and can cause adverse health effect. The portable air purifier is an inexpensive solution that could potentially clean in-cabin PM2.5. This study aims to find the PM2.5 removal efficiency of portable air purifiers in a public transit bus. In various scenarios, after artificially preloading the in-cabin PM2.5 concentration to 400 μg/m3, the concentrations were measured every 10 s, with and without the intervention of air purifiers. In a test bus with a volume of approximately 62.5 m3, three portable air purifiers were capable of reducing the average concentration of PM2.5 by 42-74%, from 400 μg/m3, to levels below 15 μg/m3, the acceptable short-term exposure concentration recommended by WHO. When high concentrations of outdoor PM2.5 entered the bus, purifiers maintained a relatively low level of in-cabin PM2.5. Air purifiers were more effective in reducing in-cabin PM2.5 than traditional air filtration and ventilation methods (air conditioning system filtration and door opening) in public transit buses. The deployed air purifiers reduced the concentration of particulate matter inside the bus, which may reduce the health risk of PM2.5 exposure and the spreading of airborne infections in public transit, thus, implying the potential to enhance passengers' and drivers' health.
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Affiliation(s)
- Yuxi Zhang
- School of Public Health and Preventive Medicine, Monash University, Melbourne, 3004, Australia
| | - Yanming Liu
- School of Public Health and Preventive Medicine, Monash University, Melbourne, 3004, Australia
| | - Shanshan Li
- School of Public Health and Preventive Medicine, Monash University, Melbourne, 3004, Australia
| | - Rongbin Xu
- School of Public Health and Preventive Medicine, Monash University, Melbourne, 3004, Australia
| | - Pei Yu
- School of Public Health and Preventive Medicine, Monash University, Melbourne, 3004, Australia
| | | | | | - Yuming Guo
- School of Public Health and Preventive Medicine, Monash University, Melbourne, 3004, Australia.
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Chen J, Liao Y, Luo M, Tang S, Huang J, Chen R, Xiao Z. Environmental polycyclic aromatic hydrocarbon exposure is associated with low back pain. ENVIRONMENTAL GEOCHEMISTRY AND HEALTH 2023:10.1007/s10653-023-01567-y. [PMID: 37069329 DOI: 10.1007/s10653-023-01567-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/04/2023] [Accepted: 04/05/2023] [Indexed: 06/19/2023]
Abstract
Several studies have assessed the influence of several often-ignored environmental factors on low back pain (LBP), but the effects of environmental polycyclic aromatic hydrocarbon (PAH) exposure on LBP are unclear. During the 2001-2004 cycle of the National Health and Nutrition Examination Survey (NHANES), our study was given to a representative sample of US participants older than 20 (N = 2743). Environmental PAH exposure was calculated using urinary PAH metabolite concentrations. Weighted logistic regression was performed to assess the connection between PAH levels and LBP, with mediation analysis utilised to explore the underlying mechanism. Levels of 1-hydroxynaphthalene (1-OHNa), 2-hydroxynaphthalene (2-OHNa) and total PAHs had a statistically significant positive association with LBP. The odds ratios per 1-unit increase for log-transformed levels of urinary 1-OHNa, 2-OHNa, and total PAHs with LBP were 1.01 (95% CI 1.02-1.19), 1.19 (95% CI 1.04-1.36) and 1.16 (95% CI 1.03-1.32), respectively. The results revealed a strong dose-response association between 1-OHNa, 2-OHNa, total PAHs, and LBP risk. Subgroup analysis indicated that 2&3-OHPh may increase the risk of LBP in the lower family income subgroup. Gamma-glutamyl transaminase (GGT), known as a biomarker of oxidative stress, was strongly related to PAHs. The relationship between total PAHs and LBP was mediated in part by GGT. Our study demonstrates associations between environmental PAH exposure and LBP that need more research to determine the precise effects of various PAH compounds on LBP.
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Affiliation(s)
- Jiang Chen
- Hengyang Medical School, The Second Affiliated Hospital, University of South China, Hengyang, China
| | - Yangjie Liao
- Department of Gastroenterology, The Third Xiangya Hospital of Central South University, Changsha, 410013, Hunan, China
| | - Mingjiang Luo
- Hengyang Medical School, The Second Affiliated Hospital, University of South China, Hengyang, China
| | - Siliang Tang
- Hengyang Medical School, The Second Affiliated Hospital, University of South China, Hengyang, China
| | - Jinshan Huang
- Hengyang Medical School, The Second Affiliated Hospital, University of South China, Hengyang, China
| | | | - Zhihong Xiao
- Hengyang Medical School, The Second Affiliated Hospital, University of South China, Hengyang, China.
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Zheng J, Xu M, Xu H, Ye F, Liu X, Liu Y, Jin X. Acute effects of ambient air pollution on daily neurology clinic visits for vertigo: a time-series study in Wuhan, China. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2023; 30:57707-57716. [PMID: 36971932 DOI: 10.1007/s11356-023-26575-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/11/2023] [Accepted: 03/16/2023] [Indexed: 05/10/2023]
Abstract
This study aimed to disclose the relationship between ambient air pollution and neurology clinic visits (NCVs) for vertigo. A time-series study was conducted to examine relationships between six different criteria air pollutants (SO2, NO2, PM2.5, PM10, CO, and O3) and daily NCVs for vertigo in Wuhan, China, from January 1st, 2017 to November 30th, 2019. Stratified analyses were computed according to gender, age, and season. A total of 14,749 records of NCVs for vertigo were enrolled in this study. Data showed that the increase in daily NCVs for vertigo corresponding to 10 μg/m3 increase of respective pollutants are: SO2 (- 7.60%; 95% CI: - 14.25 to - 0.44%), NO2 (3.14%; 95% CI: 0.23 to 6.13%), PM2.5 (0.53%; 95% CI: - 0.66 to 1.74%), PM10 (1.32%; 95% CI: - 0.36 to 3.06%), CO (0.00%; 95% CI: - 0.12 to 0.13%), and O3 (0.90%; 95% CI: - 0.01% to 1.83%). Males were more susceptible to acute exposure to SO2 and NO2, compared to females (SO2: - 11.91% vs. - 4.16%; NO2: 3.95% vs. 2.92%), whereas the acute effect of O3 exposure was more significantly obvious in females than males (0.94% vs. 0.87%). Moreover, correlations between daily NCVs for vertigo and acute exposure to SO2, NO2, and O3 were all stronger in individuals under 50 years old (SO2: - 12.75% vs. - 4.41%; NO2: 4.55% vs. 2.75%; O3: 1.27% vs. 0.70%). Short-term exposure to PM2.5 was more significantly associated with daily NCVs for vertigo in cool seasons (1.62% vs. - 0.68%), while the correlation between CO exposure and daily NCVs for vertigo was stronger in warm seasons (0.21% vs. - 0.03%). Our study demonstrated acute exposure to ambient NO2 and O3 positively associated with daily NCVs for vertigo. Acute effects of air pollution on daily NCVs for vertigo varied according to gender, age, and season.
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Affiliation(s)
- Jiachen Zheng
- Emergency Center, Zhongnan Hospital of Wuhan University, No. 169, Donghu Road, Wuchang District, Wuhan, 430071, Hubei, China
- Hubei Clinical Research Center for Emergency and Resuscitation, Zhongnan Hospital of Wuhan University, Wuhan, 430071, China
- The Second Clinical School, Wuhan University, Wuhan, 430071, Hubei, China
| | - Min Xu
- Department of Geriatrics, Zhongnan Hospital of Wuhan University, Wuhan, 430071, Hubei, China
| | - Haoyue Xu
- The Second Clinical School, Wuhan University, Wuhan, 430071, Hubei, China
| | - Fei Ye
- Department of Neurology, Wuhan Central Hospital Affiliated to Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430071, Hubei, China
| | - Xiaozhou Liu
- Department of Neurology, Wuhan Central Hospital Affiliated to Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430071, Hubei, China
| | - Yumin Liu
- Department of Neurology, Zhongnan Hospital of Wuhan University, Wuhan, 430071, Hubei, China
| | - Xiaoqing Jin
- Emergency Center, Zhongnan Hospital of Wuhan University, No. 169, Donghu Road, Wuchang District, Wuhan, 430071, Hubei, China.
- Hubei Clinical Research Center for Emergency and Resuscitation, Zhongnan Hospital of Wuhan University, Wuhan, 430071, China.
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Wang J, Huang Z, Liu X, Yang C, Yang H, Liao J, Jiao K, Chen Q, Ma X, Liao J, Ma L. Effects of ambient air pollution on cause-specific hospitalizations in Wuhan during 2017-2019. ECOTOXICOLOGY AND ENVIRONMENTAL SAFETY 2023; 253:114686. [PMID: 36863162 DOI: 10.1016/j.ecoenv.2023.114686] [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: 11/09/2022] [Revised: 02/21/2023] [Accepted: 02/23/2023] [Indexed: 06/18/2023]
Abstract
BACKGROUND Few studies have focused on the associations between air pollutants and multiple organ system diseases in the entire hospitalized population. The present study aims to explore the short-term effects of six routinely monitored air pollutants on the broad causes of hospital admissions and estimate the resulting hospital admission burdens. METHODS Daily hospital admission records from 2017 to 2019 were obtained from the Wuhan Information center of Health and Family Planning. Generalized additive models (GAMs) were employed to evaluate the effects of air pollutants on the percent increase in the cause-specific daily number of hospital admissions. Increased hospital admission numbers, days, and expenses were also estimated. RESULTS A total of 2636,026 hospital admissions were identified. We found that both PM2.5 and PM10 increased the risk of hospital admissions for most disease categories. Short-term exposure to PM2.5 was positively associated with hospitalizations of several rarely studied disease categories, such as diseases of the eye and adnexa (2.83%, 95%CI: 0.96-4.73%, P < 0.01) and diseases of the musculoskeletal system and connective tissue (2.17%, 95% CI: 0.88-3.47%, P < 0.001). NO2 was observed to have a robust effect on diseases of the respiratory system (1.36%, 95%CI: 0.74-1.98%, P < 0.001). CO was significantly associated with hospital admissions for six disease categories. Furthermore, each 10-μg/m3 increase in PM2.5 was associated with an annual increase of 13,444 hospital admissions (95% CI: 6239-20,649), 124,344 admission days (95% CI: 57,705-190,983), and 166-million-yuan admission expenses (95% CI: 77-255). CONCLUSION Our study suggested that particulate matter (PM) had a short-term effect on hospital admissions of most major disease categories and resulted in a considerable hospital admission burden. In addition, the health effects of NO2 and CO emissions require more attention in megacities.
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Affiliation(s)
- Jing Wang
- Department of Biostatistics, School of Public Health, Wuhan University, No. 115 Donghu Road, Wuhan 430071, China
| | - Zenghui Huang
- Department of Biostatistics, School of Public Health, Wuhan University, No. 115 Donghu Road, Wuhan 430071, China
| | - Xingyuan Liu
- Wuhan Information Center of Health and Family Planning, Wuhan 430021, China
| | - Can Yang
- Department of Biostatistics, School of Public Health, Wuhan University, No. 115 Donghu Road, Wuhan 430071, China
| | - Haomin Yang
- Department of Biostatistics, School of Public Health, Wuhan University, No. 115 Donghu Road, Wuhan 430071, China
| | - Jianpeng Liao
- Department of Biostatistics, School of Public Health, Wuhan University, No. 115 Donghu Road, Wuhan 430071, China
| | - Kuizhuang Jiao
- Department of Biostatistics, School of Public Health, Wuhan University, No. 115 Donghu Road, Wuhan 430071, China
| | - Qihao Chen
- Department of Biostatistics, School of Public Health, Wuhan University, No. 115 Donghu Road, Wuhan 430071, China
| | - Xuxi Ma
- Department of Global Health, School of Public Health, Wuhan University, Wuhan 430071, China
| | - Jingling Liao
- Department of Nutrition and Food Hygiene, School of Public Health, Medical College, Wuhan University of Science and Technology, No. 2 Huangjiahu West Road, Hongshan District, Wuhan 430081, China
| | - Lu Ma
- Department of Biostatistics, School of Public Health, Wuhan University, No. 115 Donghu Road, Wuhan 430071, China.
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Hu S, Ji Y, Pei M, Yang B, Chen H, Gao X, He Q, Yang H, Ye L. The impact of long-term exposure to ambient air pollution in patients undergoing peritoneal dialysis: A cohort study in China. CHEMOSPHERE 2023; 316:137871. [PMID: 36646184 DOI: 10.1016/j.chemosphere.2023.137871] [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: 08/16/2022] [Revised: 12/04/2022] [Accepted: 01/12/2023] [Indexed: 06/17/2023]
Abstract
There is increasing evidence for an association of air pollutants and the incidence of chronic kidney disease, and the progression to end stage kidney disease (ESKD). Despite the global expansion of peritoneal dialysis (PD), the impact of environmental and climatic factors in PD patients has not been studied in detail. We aimed to assess the association of long-term residential exposure to air pollutants, with patient survival and incidence of hospitalizations. This was a cohort study of all prevalent ESKD patients who were stable on PD therapy for more than 90 days in our PD center from 2013/01/01 to 2018/12/31. The enrolled patients were followed until death, cessation of PD, loss to follow-up, or 2018/12/31. Time-varying pollutant exposures were modeled as the key time-dependent variables. We used time-dependent Cox model to evaluate the risk of mortality and hospitalizations associated with air pollutant exposures adjusted for potential confounders. A total of 886 subjects who meets inclusion criteria with 27,024 patient-months were modeled. Over a mean follow-up of 30.5 ± 21.3 months, we ascertained 246 cases of death and 2611 cases of hospital admission. Significant hazard ratios (HRs) were observed for all four air pollutants including PM2.5 (hazard ratio [HR] 1.27, 95% confidence interval [95%CI] 1.05-1.54), PM10 (HR 1.31, 95%CI 1.04-1.65), NO2 (HR 1.45, 95%CI 1.02-2.06), and SO2 (HR 1.20, 95%CI 1.10-1.32) in fully adjusted model, corresponding to per interquartile range μg/m3 increase of air pollutant concentrations for mortality, and non-significant HRs for incidence of hospitalization. Non-linear associations with respect to different air pollutants were observed in models for all-cause mortality and recurrent hospitalization. The estimates for mortality were significantly higher in certain groups of patients. Our findings suggest long-term exposure to ambient air pollution was associated with higher risk of all-cause mortality in PD patients, but the association with incidence of hospitalizations was less clear.
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Affiliation(s)
- Shouci Hu
- Division of Nephrology, First Affiliated Teaching Hospital, Tianjin University of Traditional Chinese Medicine, Tianjin, China; Department of Nephrology, The First Affiliated Hospital of Zhejiang Chinese Medical University (Zhejiang Provincial Hospital of Chinese Medicine), Hangzhou, China
| | - Yue Ji
- Division of Nephrology, First Affiliated Teaching Hospital, Tianjin University of Traditional Chinese Medicine, Tianjin, China
| | - Ming Pei
- Division of Nephrology, First Affiliated Teaching Hospital, Tianjin University of Traditional Chinese Medicine, Tianjin, China
| | - Bo Yang
- Division of Nephrology, First Affiliated Teaching Hospital, Tianjin University of Traditional Chinese Medicine, Tianjin, China
| | - Hongbo Chen
- Department of Nephrology, The First Affiliated Hospital of Zhejiang Chinese Medical University (Zhejiang Provincial Hospital of Chinese Medicine), Hangzhou, China
| | - Xiangfu Gao
- Department of Nephrology, The First Affiliated Hospital of Zhejiang Chinese Medical University (Zhejiang Provincial Hospital of Chinese Medicine), Hangzhou, China
| | - Qiang He
- Department of Nephrology, The First Affiliated Hospital of Zhejiang Chinese Medical University (Zhejiang Provincial Hospital of Chinese Medicine), Hangzhou, China
| | - Hongtao Yang
- Division of Nephrology, First Affiliated Teaching Hospital, Tianjin University of Traditional Chinese Medicine, Tianjin, China.
| | - Liqing Ye
- Department of Nephrology, The First Affiliated Hospital of Zhejiang Chinese Medical University (Zhejiang Provincial Hospital of Chinese Medicine), Hangzhou, China.
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Jin L, Zhou T, Fang S, Zhou X, Bai Y. Association of air pollutants and hospital admissions for respiratory diseases in Lanzhou, China, 2014-2019. ENVIRONMENTAL GEOCHEMISTRY AND HEALTH 2023; 45:941-959. [PMID: 35384572 PMCID: PMC8985563 DOI: 10.1007/s10653-022-01256-2] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/11/2021] [Accepted: 03/07/2022] [Indexed: 05/10/2023]
Abstract
The aim of this study was to assess the effects of air pollutants on hospital admissions for respiratory disease (RD) by using distributed lag nonlinear model (DLNM) in Lanzhou during 2014-2019. In this study, the dataset of air pollutants, meteorological, and daily hospital admissions for RD in Lanzhou, from January 1st, 2014 to December 31st, 2019, were collected from three national environmental monitoring stations, China meteorological data service center, and three large general hospitals, respectively. A time-series analysis with DLNM was used to estimate the associations between air pollutants and hospital admissions for RD including the stratified analysis of age, gender, and season. The key findings were expressed as the relative risk (RR) with a 95% confidence interval (CI) for single-day and cumulative lag effects (0-7). A total of 90, 942 RD hospitalization cases were identified during the study period. The highest association (RR, 95% CI) of hospital admissions for RD and PM2.5 (1.030, 1.012-1.049), and PM10 (1.009, 1.001-1.015), and NO2 (1.047, 1.024-1.071) were observed at lag 07 for an increase of 10 μg/m3 in the concentrations, and CO at lag07 (1.140, 1.052-1.236) for an increase of 1 mg/m3 in the concentration. We observed that the RR estimates for gaseous pollutants (e.g., CO and NO2) were larger than those of particulate matter (e.g., PM2.5 and PM10). The harmful effects of PM2.5, PM10, NO2, and CO were greater in male, people aged 0-14 group and in the cold season. However, no significant association was observed for SO2, O38h, and total hospital admissions for RD. Therefore, some effective intervention strategies should be taken to strengthen the treatment of the ambient air pollutants, especially gaseous pollutants (e.g., CO and NO2), thereby, reducing the burden of respiratory diseases.
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Affiliation(s)
- Limei Jin
- College of Earth and Environmental Sciences, Lanzhou University, Lanzhou, 73000 China
- School of Public Health, Gansu University of Chinese Medicine, Lanzhou, 73000 China
| | - Tian Zhou
- College of Atmospheric Sciences, Lanzhou University, Lanzhou, 73000 China
| | - Shuya Fang
- College of Atmospheric Sciences, Lanzhou University, Lanzhou, 73000 China
| | - Xiaowen Zhou
- College of Atmospheric Sciences, Lanzhou University, Lanzhou, 73000 China
| | - Yana Bai
- School of Public Health, Lanzhou University, Lanzhou, 73000 China
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Zou H, Zhang S, Cai M, Qian ZM, Zhang Z, Chen L, Wang X, Arnold LD, Howard SW, Li H, Lin H. Ambient air pollution associated with incidence and progression trajectory of cardiometabolic diseases: A multi-state analysis of a prospective cohort. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 862:160803. [PMID: 36493826 DOI: 10.1016/j.scitotenv.2022.160803] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/18/2022] [Revised: 12/05/2022] [Accepted: 12/05/2022] [Indexed: 06/17/2023]
Abstract
BACKGROUND Previous studies on the association between ambient air pollution and cardiometabolic diseases (CMDs) focused on a single disease, without considering cardiometabolic multimorbidity (CMM) and the progression trajectory of CMDs. METHODS Based on the UK Biobank cohort, we included 372,530 participants aged 37-73 years at baseline (2006-2010) with follow-up until September 2021. Incident CMDs cases were identified based on self-reported information and multiple health-related records in the UK Biobank. CMM was defined as the occurrence of at least two CMDs, including ischemic heart disease (IHD), stroke and type 2 diabetes (T2D). Exposure to ambient air pollutants, including particulate matter (PM) with aerodynamic diameter ≤2.5 μm (PM2.5), ≤10 μm (PM10), nitrogen dioxide (NO2), and nitrogen oxides (NOx) were estimated at participants' geocoded residential addresses based on the high-resolution (1 × 1 km) pollution data from 2001 to 2021 provided by UK Department for Environment, Food and Rural Affairs. Multi-state models with adjustment for potential confounders were used to examine the impact of long-term exposure to ambient air pollution on transitions from healthy to first CMD (FCMD), subsequently to CMM, and further to death. RESULTS During a median follow-up of 12.6 years, 40,112 participants developed at least one CMD, 3896 developed CMM, and 21,739 died. Among the four pollutants, PM2.5 showed the strongest associations with all transitions from healthy to FCMD, to CMM, and then to death [hazard ratios (95 % confidence intervals) per interquartile range (IQR) increment: 1.62 (1.60, 1.64) and 1.68 (1.61, 1.76) for transitions from healthy to FCMD and from FCMD to CMM, and 1.62 (1.59, 1.66), 1.67 (1.61, 1.73), and 1.52 (1.38, 1.67) for death risk from healthy, FCMD, and CMM, respectively]. After dividing FCMDs into three specific CMDs, we found that ambient air pollution had differential impacts on disease-specific transitions within the same transition phase. CONCLUSIONS Our findings indicate that there is potential for air pollution mitigation in contributing to the prevention of the development and progression of CMDs.
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Affiliation(s)
- Hongtao Zou
- Department of Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China
| | - Shiyu Zhang
- Department of Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China
| | - Miao Cai
- Department of Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China
| | - Zhengmin Min Qian
- Department of Epidemiology and Biostatistics, College for Public Health & Social Justice, Saint Louis University, Saint Louis, MO 63104, USA
| | - Zilong Zhang
- Department of Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China
| | - Lan Chen
- Department of Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China
| | - Xiaojie Wang
- Department of Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China
| | - Lauren D Arnold
- Department of Epidemiology and Biostatistics, College for Public Health & Social Justice, Saint Louis University, Saint Louis, MO 63104, USA
| | - Steven W Howard
- Department of Health Management and Policy, College for Public Health & Social Justice, Saint Louis University, Saint Louis, MO 63104, USA
| | - Haitao Li
- Department of Social Medicine and Health Service Management, Health Science Center, Shenzhen University, Shenzhen 518055, China
| | - Hualiang Lin
- Department of Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China.
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Prada D, Crandall CJ, Kupsco A, Kioumourtzoglou MA, Stewart JD, Liao D, Yanosky JD, Ramirez A, Wactawski-Wende J, Shen Y, Miller G, Ionita-Laza I, Whitsel EA, Baccarelli AA. Air pollution and decreased bone mineral density among Women's Health Initiative participants. EClinicalMedicine 2023; 57:101864. [PMID: 36820096 PMCID: PMC9938170 DOI: 10.1016/j.eclinm.2023.101864] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/31/2022] [Revised: 01/25/2023] [Accepted: 01/26/2023] [Indexed: 02/17/2023] Open
Abstract
Background Osteoporosis heavily affects postmenopausal women and is influenced by environmental exposures. Determining the impact of criteria air pollutants and their mixtures on bone mineral density (BMD) in postmenopausal women is an urgent priority. Methods We conducted a prospective observational study using data from the ethnically diverse Women's Health Initiative Study (WHI) (enrollment, September 1994-December 1998; data analysis, January 2020 to August 2022). We used log-normal, ordinary kriging to estimate daily mean concentrations of PM10, NO, NO2, and SO2 at participants' geocoded addresses (1-, 3-, and 5-year averages before BMD assessments). We measured whole-body, total hip, femoral neck, and lumbar spine BMD at enrollment and follow-up (Y1, Y3, Y6) via dual-energy X-ray absorptiometry. We estimated associations using multivariable linear and linear mixed-effects models and mixture effects using Bayesian kernel machine regression (BKMR) models. Findings In cross-sectional and longitudinal analyses, mean PM10, NO, NO2, and SO2 averaged over 1, 3, and 5 years before the visit were negatively associated with whole-body, total hip, femoral neck, and lumbar spine BMD. For example, lumbar spine BMD decreased 0.026 (95% CI: 0.016, 0.036) g/cm2/year per a 10% increase in 3-year mean NO2 concentration. BKMR suggested that nitrogen oxides exposure was inversely associated with whole-body and lumbar spine BMD. Interpretation In this cohort study, higher levels of air pollutants were associated with bone damage, particularly on lumbar spine, among postmenopausal women. These findings highlight nitrogen oxides exposure as a leading contributor to bone loss in postmenopausal women, expanding previous findings of air pollution-related bone damage. Funding US National Institutes of Health.
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Affiliation(s)
- Diddier Prada
- Department of Environmental Health Science, Mailman School of Public Health, Columbia University, New York, NY, USA
- Instituto Nacional de Cancerología – México, Mexico City, Mexico
| | - Carolyn J. Crandall
- Division of General Internal Medicine and Health Services Research, David Geffen School of Medicine at University of California, Los Angeles, CA, USA
| | - Allison Kupsco
- Department of Environmental Health Science, Mailman School of Public Health, Columbia University, New York, NY, USA
| | | | - James D. Stewart
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, USA
| | - Duanping Liao
- Department of Public Health Sciences, Pennsylvania State University College of Medicine, Hershey, PA, USA
| | - Jeff D. Yanosky
- Department of Public Health Sciences, Pennsylvania State University College of Medicine, Hershey, PA, USA
| | - Andrea Ramirez
- Instituto Nacional de Cancerología – México, Mexico City, Mexico
| | - Jean Wactawski-Wende
- School of Public Health and Health Professions, University at Buffalo, State University of New York, New York, USA
| | - Yike Shen
- Department of Environmental Health Science, Mailman School of Public Health, Columbia University, New York, NY, USA
| | - Gary Miller
- Department of Environmental Health Science, Mailman School of Public Health, Columbia University, New York, NY, USA
| | - Iuliana Ionita-Laza
- Department of Environmental Health Science, Mailman School of Public Health, Columbia University, New York, NY, USA
| | - Eric A. Whitsel
- Department of Epidemiology, Gillings School of Global Public Health and Department of Medicine, School of Medicine, University of North Carolina, Chapel Hill, NC, USA
| | - Andrea A. Baccarelli
- Department of Environmental Health Science, Mailman School of Public Health, Columbia University, New York, NY, USA
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Long H, Xie D, Zeng C, Wang H, Lei G, Yang T. Burden and Characteristics of Revision Total Knee Arthroplasty in China: a National Study Based on Hospitalized Cases. J Arthroplasty 2023:S0883-5403(23)00183-3. [PMID: 36849014 DOI: 10.1016/j.arth.2023.02.052] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/06/2022] [Revised: 02/14/2023] [Accepted: 02/17/2023] [Indexed: 03/01/2023] Open
Abstract
BACKGROUND National epidemiological data in China are absent for revision total knee arthroplasty (TKA). This study aimed to investigate the burden and characteristics of revision TKA in China. METHODS We reviewed 4,503 revision TKA cases registered in the Hospital Quality Monitoring System in China between 2013 and 2018 using International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) codes. Revision burden was determined by the ratio of the number of revision procedures to the total number of TKA procedures. Demographic characteristics, hospital characteristics, and hospitalization charges were identified. RESULTS The revision TKA cases accounted for 2.4% of all TKA cases. The revision burden showed an increasing trend from 2013 to 2018 (2.3 to 2.5%) (P for trend = 0.034). Gradual increases in revision TKA were observed in patients aged > 60 years. The most common causes for revision TKA were infection (33.0%) and mechanical failure (19.5%). More than 70% of the patients were hospitalized in provincial hospitals. A total of 17.6% patients were hospitalized in a hospital outside the province of their residence. The hospitalization charges continued to increase between 2013 and 2015 and remained roughly stable over the next three years. CONCLUSIONS This study provided epidemiological data for revision TKA in China based on a national database. There was a growing trend of revision burden during the study period. The focalized nature of operations in a few higher volume regions was observed and many patients had to travel to obtain their revision procedure.
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Affiliation(s)
- Huizhong Long
- Department of Orthopaedics, Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Dongxing Xie
- Department of Orthopaedics, Xiangya Hospital, Central South University, Changsha, Hunan, China; Hunan Key Laboratory of Joint Degeneration and Injury, Changsha, Hunan, China
| | - Chao Zeng
- Department of Orthopaedics, Xiangya Hospital, Central South University, Changsha, Hunan, China; Hunan Key Laboratory of Joint Degeneration and Injury, Changsha, Hunan, China; Hunan Engineering Research Center for Osteoarthritis, Changsha, Hunan, China; National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Haibo Wang
- Clinical Trial Unit, First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, Guangdong, China; China Standard Medical Information Research Center, Shenzhen, Guangdong, China
| | - Guanghua Lei
- Department of Orthopaedics, Xiangya Hospital, Central South University, Changsha, Hunan, China; Hunan Key Laboratory of Joint Degeneration and Injury, Changsha, Hunan, China; Hunan Engineering Research Center for Osteoarthritis, Changsha, Hunan, China; National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Tuo Yang
- Hunan Key Laboratory of Joint Degeneration and Injury, Changsha, Hunan, China; National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, Hunan, China; Health Management Center, Xiangya Hospital, Central South University, Changsha, Hunan, China.
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50
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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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