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Tsukada YT, Aoki-Kamiya C, Mizuno A, Nakayama A, Ide T, Aoyama R, Honye J, Hoshina K, Ikegame T, Inoue K, Bando YK, Kataoka M, Kondo N, Maemura K, Makaya M, Masumori N, Mito A, Miyauchi M, Miyazaki A, Nakano Y, Nakao YM, Nakatsuka M, Nakayama T, Oginosawa Y, Ohba N, Otsuka M, Okaniwa H, Saito A, Saito K, Sakata Y, Harada-Shiba M, Soejima K, Takahashi S, Takahashi T, Tanaka T, Wada Y, Watanabe Y, Yano Y, Yoshida M, Yoshikawa T, Yoshimatsu J, Abe T, Dai Z, Endo A, Fukuda-Doi M, Ito-Hagiwara K, Harima A, Hirakawa K, Hosokawa K, Iizuka G, Ikeda S, Ishii N, Izawa KP, Kagiyama N, Umeda-Kameyama Y, Kanki S, Kato K, Komuro A, Konagai N, Konishi Y, Nishizaki F, Noma S, Norimatsu T, Numao Y, Oishi S, Okubo K, Ohmori T, Otaki Y, Shibata T, Shibuya J, Shimbo M, Shiomura R, Sugiyama K, Suzuki T, Tajima E, Tsukihashi A, Yasui H, Amano K, Kohsaka S, Minamino T, Nagai R, Setoguchi S, Terada K, Yumino D, Tomoike H. JCS/JCC/JACR/JATS 2024 Guideline on Cardiovascular Practice With Consideration for Diversity, Equity, and Inclusion. Circ J 2025; 89:658-739. [PMID: 39971310 DOI: 10.1253/circj.cj-23-0890] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/21/2025]
Affiliation(s)
| | - Chizuko Aoki-Kamiya
- Department of Obstetrics and Gynecology, National Cerebral and Cardiovascular Center
| | - Atsushi Mizuno
- Department of Cardiology, St. Luke's International Hospital
| | | | - Tomomi Ide
- Department of Cardiovascular Medicine, Kyushu University
| | - Rie Aoyama
- Department of Cardiology, Heart and Vascular Institute, Funabashi Municipal Medical Center
| | - Junko Honye
- Cardiovascular Center, Kikuna Memorial Hospital
| | | | | | - Koki Inoue
- Department of Neuropsychiatry, Graduate School of Medicine, Osaka Metropolitan University
| | - Yasuko K Bando
- Department of Molecular Physiology and Cardiovascular Biology, Mie University Graduate School of Medicine
| | - Masaharu Kataoka
- The Second Department of Internal Medicine, University of Occupational and Environmental Health, Japan
| | - Naoki Kondo
- Department of Social Epidemiology, Graduate School of Medicine and School of Public Health, Kyoto University
| | - Koji Maemura
- Department of Cardiovascular Medicine, Nagasaki University Graduate School of Biomedical Sciences
| | | | - Naoya Masumori
- Department of Urology, Sapporo Medical University School of Medicine
| | - Asako Mito
- Division of Maternal Medicine, Center for Maternal-Fetal-Reproductive Medicine, National Center for Child Health and Development
| | - Mizuho Miyauchi
- Department of Cardiovascular Medicine, Nippon Medical School
| | - Aya Miyazaki
- Department of Pediatric Cardiology, Department of Adult Congenital Heart Disease, Seirei Hamamatsu General Hospital
| | - Yukiko Nakano
- Department of Cardiovascular Medicine, Hiroshima University Graduate School of Biomedical and Health Sciences
| | - Yoko M Nakao
- Department of Pharmacoepidemiology, Graduate School of Medicine and Public Health, Kyoto University
| | - Mikiya Nakatsuka
- Faculty of Health Sciences, Okayama University Graduate School of Medicine
| | - Takeo Nakayama
- Department of Health Informatics, School of Public Health, Kyoto University
| | - Yasushi Oginosawa
- The Second Department of Internal Medicine, University of Occupational and Environmental Health, Japan
| | | | - Maki Otsuka
- Division of Cardiovascular Medicine, Department of Internal Medicine, Kurume University School of Medicine
| | - Hiroki Okaniwa
- Department of Technology, Gunma Prefectural Cardiovascular Center
| | - Aya Saito
- Department of Surgery, Division of Cardiovascular Surgery, Yokohama City University, Graduate School of Medicine
| | - Kozue Saito
- Department of Neurology, Stroke Center, Nara Medical University
| | - Yasushi Sakata
- Department of Cardiovascular Medicine, Osaka University Graduate School of Medicine
| | | | - Kyoko Soejima
- Department of Cardiovascular Medicine, Kyorin University School of Medicine
| | | | - Tetsuya Takahashi
- Department of Physical Therapy, Faculty of Health Science, Juntendo University
| | - Toshihiro Tanaka
- Department of Human Genetics and Disease Diversity, Tokyo Medical and Dental University
| | - Yuko Wada
- Division of Cardiovascular Surgery, Department of Surgery, Shinshu University School of Medicine
| | | | - Yuichiro Yano
- Department of General Medicine, Juntendo University Faculty of Medicine
| | - Masayuki Yoshida
- Department of Life Sciences and Bioethics, Graduate School of Medical and Dental Sciences, Tokyo Medical and Dental University (TMDU)
| | - Toru Yoshikawa
- Research Center for Overwork-Related Disorders (RECORDs), National Institute of Occuatopnal Safety and Health, Japan (JNIOSH)
| | - Jun Yoshimatsu
- Department of Obstetrics and Gynecology, National Cerebral and Cardiovascular Center
| | - Takahiro Abe
- Department of Rehabilitation Medicine, Hokkaido University Hospital
| | - Zhehao Dai
- Department of Cardiovascular Medicine, The University of Tokyo Hospital
| | - Ayaka Endo
- Department of Cardiology, Tokyo Saiseikai Central Hospital
| | - Mayumi Fukuda-Doi
- Department of Data Science, National Cerebral and Cardiovascular Center
- Department of Cerebrovascular Medicine, National Cerebral and Cardiovascular Center
| | | | | | - Kyoko Hirakawa
- Department of Cardiovascular Medicine, Kumamoto University
| | | | | | - Satoshi Ikeda
- Stroke and Cardiovascular Diseases Support Center, Nagasaki University Hospital
| | - Noriko Ishii
- Department of Nursing, Sakakibara Heart Institute
| | - Kazuhiro P Izawa
- Department of Public Health, Graduate School of Health Sciences, Kobe University
| | - Nobuyuki Kagiyama
- Department of Cardiovascular Biology and Medicine, Juntendo University Graduate School of Medicine
| | | | - Sachiko Kanki
- Department of Thoracic and Cardiovascular Surgery, Osaka Medical and Pharmaceutical University
| | - Katsuhito Kato
- Department of Hygiene and Public Health, Nippon Medical School
| | - Aya Komuro
- Department of Geriatric Medicine, The University of Tokyo Hospital
| | - Nao Konagai
- Department of Obstetrics and Gynecology, National Cerebral and Cardiovascular Center
| | - Yuto Konishi
- Department of Cardiovascular Medicine, The University of Tokyo Hospital
| | - Fumie Nishizaki
- Department of Cardiology and Nephrology, Hirosaki University Graduate School of Medicine
| | - Satsuki Noma
- Department of Cardiovascular Medicine, Nippon Medical School
| | | | - Yoshimi Numao
- Department of Cardiology, Itabasih Chuo Medical Center
| | | | - Kimie Okubo
- Division of Cardiology, Department of Medicine, Nihon University School of Medicine Itabashi Hospital
| | | | - Yuka Otaki
- Department of Radiology, Sakakibara Heart Institute
| | | | - Junsuke Shibuya
- Division of Cardiovascular Intensive Care, Nippon Medical School Hospital
| | - Mai Shimbo
- Department of Cardiovascular Medicine, Department of Computational Diagnostic Radiology and Preventive Medicine, The University of Tokyo
| | - Reiko Shiomura
- Division of Cardiovascular Intensive Care, Nippon Medical School Hospital
| | | | - Takahiro Suzuki
- Department of Cardiovascular Medicine, St. Luke's International Hospital
| | - Emi Tajima
- Department of Cardiology, Tokyo General Hospital
| | - Ayako Tsukihashi
- Department of Cardiovascular Medicine, The University of Tokyo Hospital
| | - Haruyo Yasui
- Department of Cardiovascular Medicine, Osaka University Graduate School of Medicine
| | | | - Shun Kohsaka
- Department of Cardiology, Keio University School of Medicine
| | - Tohru Minamino
- Department of Cardiovascular Biology and Medicine, Juntendo University Graduate School of Medicine
| | | | - Soko Setoguchi
- Division of Education, Department of Medicine, Rutgers Robert Wood Johnson Medical School
- Division of Cardiovascular Disease and Hypertension, Department of Medicine, Rutgers Robert Wood Johnson Medical School
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Gyaase S, Nyame S, Klipstein-Grobusch K, Asante KP, Downward GS. Climate, Air Quality and Their Contribution to Cardiovascular Disease Morbidity and Mortality in Low- and Middle-Income Countries: A Systematic Review and Meta-Analysis. Glob Heart 2025; 20:35. [PMID: 40161860 PMCID: PMC11951997 DOI: 10.5334/gh.1409] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2024] [Accepted: 02/13/2025] [Indexed: 04/02/2025] Open
Abstract
Background Increasing exposure to climatic features is strongly linked to various adverse health outcomes and mortality. While the link between these features and cardiovascular outcomes is well established, most studies are from high-income countries. Objectives This review synthesizes evidence as well as research gaps on the relationship between climate indicators, household/ambient air pollution, and all-cause cardiovascular disease (CVD) morbidity and mortality in low- and middle-income countries (LMICs). Methods Seven electronic databases were searched up to June 15, 2024. Articles were included if they focused on LMICs, addressed all-cause CVD morbidity and/or mortality, and studied climate or environmental exposures. Studies were selected using ASReview LAB, extracted and analyzed with random effect meta-analysis performed if sufficient articles were identified. Results & Conclusion Out of 7,306 articles, 58 met the inclusion criteria: 26 on morbidity, 29 on mortality, and 3 on both. Exposures included PM10, PM2.5, NO2, SO2, BC, O3, CO, solid fuel usage, and temperature variation. Short-term exposure to PM2.5 was significantly associated with CVD morbidity (RR per 10 µg/m3 increase:1.006, 95% CI 1.003-1.009) and mortality (RR:1.007, 95% CI 1.002-1.012). Short-term exposure to NO2 and O3 also increased CVD mortality risk. Long-term exposure to PM2.5 elevated CVD morbidity (RR per 10 µg/m3 increase:1.131, 95% CI 1.057-1.210) and mortality (RR:1.092, 95% CI 1.030-1.159). High and low temperatures and long-term solid fuel use were linked to CVD deaths. The bulk of studies were from mainland China (72%), which may not accurately reflect the situation in other LMICs. Sub-Saharan Africa was particularly lacking, representing a major research gap.
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Affiliation(s)
- Stephaney Gyaase
- Kintampo Health Research Centre, Research and Development Division, Ghana Health Service, Kintampo, Ghana
- Julius Global Health, Department of Global Public Health and Bioethics, Julius Center for Health Sciences, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Solomon Nyame
- Kintampo Health Research Centre, Research and Development Division, Ghana Health Service, Kintampo, Ghana
- Julius Global Health, Department of Global Public Health and Bioethics, Julius Center for Health Sciences, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Kerstin Klipstein-Grobusch
- Julius Global Health, Department of Global Public Health and Bioethics, Julius Center for Health Sciences, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
- Division of Epidemiology and Biostatistics, School of Public Health, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Kwaku Poku Asante
- Kintampo Health Research Centre, Research and Development Division, Ghana Health Service, Kintampo, Ghana
| | - George S. Downward
- Julius Global Health, Department of Global Public Health and Bioethics, Julius Center for Health Sciences, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
- Institute for Risk Assessment Sciences, Utrecht University, The Netherlands
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3
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Pan C, Qi X, Yang X, Cheng B, Cheng S, Liu L, Meng P, He D, Wei W, Hui J, Zhao B, Wen Y, Jia Y, Liu H, Zhang F. Large-scale plasma proteomics uncovers novel targets linking ambient air pollution and depression. Mol Psychiatry 2025:10.1038/s41380-025-02953-x. [PMID: 40108257 DOI: 10.1038/s41380-025-02953-x] [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: 03/15/2024] [Revised: 02/12/2025] [Accepted: 03/11/2025] [Indexed: 03/22/2025]
Abstract
Despite the growing recognition of association between air pollution and increased risk of depression, the intricate biological mechanisms underlying it remains unclear. In this study, a total of 1463 plasma proteins were measured by the Olink Explore platform for 50,553 participants in a large prospective cohort. Four air pollutants were assessed using land-use regression models: particulate matter with aerodynamic diameter ≤ 2.5μm (PM2.5), particulate matter with aerodynamic diameter > 2.5μm and ≤ 10μm (PM2.5-10), nitrogen dioxide (NO2), and nitric oxide (NO). The air pollution index was calculated using principal components analysis to assess joint exposure to air pollution. Logistic regression and Cox proportional hazards regression analyses were respectively used to explore the impact of the interaction between air pollution exposure and plasma proteins on the prevalence and incidence of depression. Functional enrichment analysis and drug prediction analysis were conducted to explore the biological mechanisms and drugs associated with identified plasma proteins with interaction effects. Logistic regression analysis detected seven significant air pollutant and plasma protein interactions for the prevalence of depression, such as CDHR5 vs. PM2.5 (OR: 0.58; 95% CI: 0.48-0.71), TNFRSF13C vs. NO (OR :0.70, 95% CI: 0.58-0.84) and ICAM5 vs. air pollution index (OR: 1.38, 95% CI: 1.17-1.63). Two significant interactions were identified for the incidence of depression: CDHR5 vs. PM2.5 (HR: 0.62, 95% CI: 0.50-0.76) and HSD11B1 vs. PM2.5 (HR: 1.48, 95% CI: 1.22-1.81). The plasma proteins that interacted with air pollutants were enriched in various Gene Ontology terms and pathways involving immunity, endocrine, inflammation, neurological function and metabolism, such as neuroinflammatory response, neuron projection guidance, regulation of lymphocyte mediated immunity, steroid biosynthetic process and lipid digestion. We also found that these proteins interacted with multiple drugs, such as risperidone, olanzapine and progesterone. This study identified novel targets linking ambient air pollution and depression, providing the insights for biological mechanisms of air pollution affecting the risk of depression.
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Affiliation(s)
- Chuyu Pan
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, China
| | - Xin Qi
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, China
- Precision Medicine Center, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, P. R. China
| | - Xuena Yang
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, China
| | - Bolun Cheng
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, China
| | - Shiqiang Cheng
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, China
| | - Li Liu
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, China
| | - Peilin Meng
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, China
| | - Dan He
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, China
| | - Wenming Wei
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, China
| | - Jingni Hui
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, China
| | - Boyue Zhao
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, China
| | - Yan Wen
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, China
| | - Yumeng Jia
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, China
| | - Huan Liu
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, China
| | - Feng Zhang
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, China.
- Department of Psychiatry, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, P. R. China.
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Zhang S, Liu Y, Qi J, Yan Y, Gao T, Zhang X, Sun D, Wang T, Zeng P. Accelerated aging as a mediator of the association between co-exposure to multiple air pollutants and risk of chronic kidney disease. ECOTOXICOLOGY AND ENVIRONMENTAL SAFETY 2025; 290:117582. [PMID: 39719816 DOI: 10.1016/j.ecoenv.2024.117582] [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: 09/18/2024] [Revised: 12/18/2024] [Accepted: 12/18/2024] [Indexed: 12/26/2024]
Abstract
BACKGROUND The association between co-exposure to multiple air pollutants and the occurrence of chronic kidney disease (CKD) was not well-established, and the mediating role of accelerated aging in this association remained uncertain. METHODS Using a cohort of 313,908 participants without CKD at baseline from the UK Biobank, we examined the potential association between co-exposure to multiple air pollutants, including PM2.5, PM10, PM2.5-10, NO2 and NOx, and the incidence of CKD by calculating an air pollution score. Mediation analyses were performed to examine the mediating role of accelerated aging (PhenoAgeAccel or KDM-BioAgeAccel) in this association. RESULTS During the median follow-up time of 12.9 years, 11,117 participants developed CKD. The results showed that per interquartile range (IQR) increment in air pollution score led to an approximately 9.0 % (6.6-11.4 %) elevated risk of occurring CKD. Compared to the first quartile (Q1) of air pollution score, those in the highest quartile (Q4) had a 21.2 % (14.8-27.9 %) higher risk of developing CKD (Ptrend<0.001). Mediation analyses suggested that PhenoAgeAccel and KDM-BioAgeAccel significantly mediated 1.5 % and 5.7 % of the association between air pollution score and incident CKD, respectively. CONCLUSION Co-exposure to multiple air pollutants could increase the risk of developing CKD, with accelerated aging serving as a partial mechanism in the relationship between air pollution and CKD. These findings highlight the importance of reducing air pollution, and suggest a possible mechanism from air pollution to CKD through accelerated aging.
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Affiliation(s)
- Shuo Zhang
- Department of Biostatistics, School of Public Health, Xuzhou Medical University, Xuzhou, Jiangsu 221004, China
| | - Yuxin Liu
- Department of Biostatistics, School of Public Health, Xuzhou Medical University, Xuzhou, Jiangsu 221004, China
| | - Jike Qi
- Department of Biostatistics, School of Public Health, Xuzhou Medical University, Xuzhou, Jiangsu 221004, China
| | - Yu Yan
- Department of Biostatistics, School of Public Health, Xuzhou Medical University, Xuzhou, Jiangsu 221004, China
| | - Tongyu Gao
- Department of Biostatistics, School of Public Health, Xuzhou Medical University, Xuzhou, Jiangsu 221004, China
| | - Xin Zhang
- Department of Biostatistics, School of Public Health, Xuzhou Medical University, Xuzhou, Jiangsu 221004, China
| | - Dong Sun
- Department of Nephrology and Clinical Research Center for Kidney Disease, Affiliated Hospital of Xuzhou Medical University, Xuzhou 221004, China; Clinical Research Center for Kidney Disease, Xuzhou Medical University, Xuzhou 221004, China
| | - Ting Wang
- Department of Biostatistics, School of Public Health, Xuzhou Medical University, Xuzhou, Jiangsu 221004, China
| | - Ping Zeng
- Department of Biostatistics, School of Public Health, Xuzhou Medical University, Xuzhou, Jiangsu 221004, China; Jiangsu Engineering Research Center of Biological Data Mining and Healthcare Transformation, Xuzhou Medical University, Xuzhou, Jiangsu 221004, China.
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5
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Li H, Yuan S, Zhao Y, Mavoa S, Liu H, Guo Y, Ye T, Yang J, Xu R, Xie Y, Song X, Shan H, Wang G, Han K, Shi Y, Wang L, Gao W, Han C. Geographic and socioeconomic disparities in mortality burden attributable to long-term exposure to NO 2 across 231 cities in China from 2015 to 2019. INTERNATIONAL JOURNAL OF ENVIRONMENTAL HEALTH RESEARCH 2024:1-11. [PMID: 39729307 DOI: 10.1080/09603123.2024.2446522] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/27/2024] [Accepted: 12/20/2024] [Indexed: 12/28/2024]
Abstract
Research on geographic and socioeconomic disparities of NO2 attributed mortality burden is limited. This study aims to quantify the geographic and socioeconomic differences in the association between long-term exposure to NO2 and mortality burden in China. We estimated the all-cause mortality burden of adults over 16 years old attributable to NO2 exposure above 10 µg/m3 for 231 Chinese cities from 2015 to 2019, and geographic and socioeconomic differences . Attributed fraction (AF), attributed deaths (AD), attributed mortality rate (AMR) and total value of statistical life lost (VSL) were used as the mortality burden measurements. Between 2015 and 2019, we estimated 1356.3 thousand deaths (95% CI: 513.7-2050.7) attributed to NO2 exposure above 10 µg/m3 per year and VSL of 958.2 billion USD (95% CI: 362.9-1448.8). Cities in the northern region, cities with high levels of GDP per capita (PGDP) and urbanization suffered the highest mortality burden and corresponding economic loss. Consequently, significant geographic and socioeconomic disparities of NO2 attributed mortality burden exist across cities in China.
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Affiliation(s)
- Hongyu Li
- School of Public Health, Binzhou Medical University, Yantai, Shandong Province, PR China
| | - Shijia Yuan
- School of Public Health, Binzhou Medical University, Yantai, Shandong Province, PR China
| | - Yang Zhao
- The George Institute for Global Health at Peking University Health Science Center, Beijing, PR China
- WHO Collaborating Centre on Implementation Research for Prevention & Control of NCDs, VIC, Australia
| | - Suzanne Mavoa
- Environmental Public Health Branch, Environment Protection Authority Victoria, Melbourne, Australia
- Melbourne School of Population & Global Health, University of Melbourne, Melbourne, Australia
| | - Haiyun Liu
- Department of public health, Shandong College of Traditional Chinese Medicine, Yantai, Shandong Province, PR China
| | - Yuming Guo
- School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
| | - Tingting Ye
- School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
| | - Jun Yang
- School of Public Health, Guangzhou Medical University, Guangzhou, Guangdong Province, PR China
| | - Rongbin Xu
- School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
| | - Yang Xie
- School of Economics and Management, Beihang University, Beijing, PR China
- Key Laboratory of Big Data-Based Precision Medicine, Ministry of Industry and Information Technology, Beihang University, Beijing, PR China
| | - Xiaohui Song
- School of Public Health, Binzhou Medical University, Yantai, Shandong Province, PR China
| | - Haifeng Shan
- Zibo Mental Health Center, Shandong Province, PR China
| | - Guangcheng Wang
- School of Public Health, Binzhou Medical University, Yantai, Shandong Province, PR China
| | - Kun Han
- GuotaiJunan Securities, Zibo, Shanghai, PR China
- School of Economics, Fudan University, Shanghai, PR China
| | - Yukun Shi
- General Services Department, Binzhou Polytechnic, Binzhou, Shandong, China
| | - Luyang Wang
- Zhangdian Center for Disease Control and Prevention, Shandong, China
| | - Wenhui Gao
- School of Public Health, Binzhou Medical University, Yantai, Shandong Province, PR China
| | - Chunlei Han
- School of Public Health, Binzhou Medical University, Yantai, Shandong Province, PR China
- School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
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6
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Pan C, Cheng B, Cheng S, Liu L, Yang X, Meng P, Qi X, Zhang N, Qin X, He D, Wei W, Hui J, Wen Y, Jia Y, Liu H, Zhang F. Long-term ambient air pollution and the risk of major mental disorder: A prospective cohort study. Eur Psychiatry 2024; 68:e1. [PMID: 39690525 PMCID: PMC11823001 DOI: 10.1192/j.eurpsy.2024.1809] [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: 06/19/2024] [Revised: 11/27/2024] [Accepted: 12/08/2024] [Indexed: 12/19/2024] Open
Abstract
BACKGROUND Despite growing awareness of the mental health damage caused by air pollution, the epidemiologic evidence on impact of air pollutants on major mental disorders (MDs) remains limited. We aim to explore the impact of various air pollutants on the risk of major MD. METHODS This prospective study analyzed data from 170 369 participants without depression, anxiety, bipolar disorder, and schizophrenia at baseline. The concentrations of particulate matter with aerodynamic diameter ≤ 2.5 μm (PM2.5), particulate matter with aerodynamic diameter > 2.5 μm, and ≤ 10 μm (PM2.5-10), nitrogen dioxide (NO2), and nitric oxide (NO) were estimated using land-use regression models. The association between air pollutants and incident MD was investigated by Cox proportional hazard model. RESULTS During a median follow-up of 10.6 years, 9 004 participants developed MD. Exposure to air pollution in the highest quartile significantly increased the risk of MD compared with the lowest quartile: PM2.5 (hazard ratio [HR]: 1.16, 95% CI: 1.09-1.23), NO2 (HR: 1.12, 95% CI: 1.05-1.19), and NO (HR: 1.10, 95% CI: 1.03-1.17). Subgroup analysis showed that participants with lower income were more likely to experience MD when exposed to air pollution. We also observed joint effects of socioeconomic status or genetic risk with air pollution on the MD risk. For instance, the HR of individuals with the highest genetic risk and highest quartiles of PM2.5 was 1.63 (95% CI: 1.46-1.81) compared to those with the lowest genetic risk and lowest quartiles of PM2.5. CONCLUSIONS Our findings highlight the importance of air pollution control in alleviating the burden of MD.
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Affiliation(s)
- Chuyu Pan
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, School of Public Health, Health Science Center, Xi’an Jiaotong University, Xi’an, China
| | - Bolun Cheng
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, School of Public Health, Health Science Center, Xi’an Jiaotong University, Xi’an, China
| | - Shiqiang Cheng
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, School of Public Health, Health Science Center, Xi’an Jiaotong University, Xi’an, China
| | - Li Liu
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, School of Public Health, Health Science Center, Xi’an Jiaotong University, Xi’an, China
| | - Xuena Yang
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, School of Public Health, Health Science Center, Xi’an Jiaotong University, Xi’an, China
| | - Peilin Meng
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, School of Public Health, Health Science Center, Xi’an Jiaotong University, Xi’an, China
| | - Xin Qi
- Precision Medicine Center, The First Affiliated Hospital of Xi’an Jiaotong University, Xi’an, China
| | - Na Zhang
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, School of Public Health, Health Science Center, Xi’an Jiaotong University, Xi’an, China
| | - Xiaoyue Qin
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, School of Public Health, Health Science Center, Xi’an Jiaotong University, Xi’an, China
| | - Dan He
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, School of Public Health, Health Science Center, Xi’an Jiaotong University, Xi’an, China
| | - Wenming Wei
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, School of Public Health, Health Science Center, Xi’an Jiaotong University, Xi’an, China
| | - Jingni Hui
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, School of Public Health, Health Science Center, Xi’an Jiaotong University, Xi’an, China
| | - Yan Wen
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, School of Public Health, Health Science Center, Xi’an Jiaotong University, Xi’an, China
| | - Yumeng Jia
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, School of Public Health, Health Science Center, Xi’an Jiaotong University, Xi’an, China
| | - Huan Liu
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, School of Public Health, Health Science Center, Xi’an Jiaotong University, Xi’an, China
| | - Feng Zhang
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, School of Public Health, Health Science Center, Xi’an Jiaotong University, Xi’an, China
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7
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Li A, Wang Y, Qi Q, Li Y, Jia H, Zhou X, Guo H, Xie S, Liu J, Mu Y. Improved PM 2.5 prediction with spatio-temporal feature extraction and chemical components: The RCG-attention model. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 955:177183. [PMID: 39471939 DOI: 10.1016/j.scitotenv.2024.177183] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/19/2024] [Revised: 10/21/2024] [Accepted: 10/21/2024] [Indexed: 11/01/2024]
Abstract
Deep learning models are widely used for PM2.5 prediction. However, neglecting temporal and spatial characteristics leads to low prediction accuracy. In this work, a new deep learning model (RCG - Attention model) was developed, which combines the residual neural network (ResNet) and the convolution gated recurrent network (ConvGRU) and is applied to extract the spatio - temporal features for predicting PM2.5 concentration over the subsequent 24 h. The ResNet extracts the spatial distribution features of pollutants, and the ConvGRU extracts temporal features. The spatial and temporal features are fused by the multi - head attention mechanism to obtain multi - dimensional features. These features are finally fed into a series of fully connected layers to predict the future results. Incorporating these chemical components enhances the scientific validity of the dataset and strengthens the inherent logical connections among variables. The Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE), Root Mean Square Error (RMSE), and R - squared (R2) results indicate that the prediction performance of the RCG - Attention model surpasses that of other baseline models. The model demonstrates superior prediction performance across multiple monitoring stations, suggesting robust generalization capabilities and adaptability for various regions in one city. The SHAP results show that PM10, NO2, RH, NO3-, OC and NH4+ are significant influencing features. The RCG - Attention model provides a comprehensive solution for PM2.5 concentration prediction by integrating spatial and temporal feature extraction with chemical components.
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Affiliation(s)
- Ao Li
- Beijing Institute of Petrochemical Technology, China
| | - Yafei Wang
- Beijing Institute of Petrochemical Technology, China.
| | - Qianqian Qi
- Beijing Institute of Petrochemical Technology, China
| | - Yunfeng Li
- Beijing Institute of Petrochemical Technology, China
| | - Haixia Jia
- Beijing Daxing District Ecology and Environment Bureau, China
| | - Xin Zhou
- Beijing Daxing District Ecology and Environment Bureau, China
| | - Haixin Guo
- Agro-Environmental Protection Institute, Ministry of Agriculture and Rural Affairs, Tianjin 300191, China
| | - Shuyang Xie
- State Key Joint Laboratory of Environment Simulation and Pollution Control, Research Center for Eco-environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China; State Key Joint Laboratory of Environment Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China
| | - Junfeng Liu
- State Key Joint Laboratory of Environment Simulation and Pollution Control, Research Center for Eco-environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
| | - Yujing Mu
- State Key Joint Laboratory of Environment Simulation and Pollution Control, Research Center for Eco-environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
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8
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Wang Y, Chang J, Hu P, Deng C, Luo Z, Zhao J, Zhang Z, Yi W, Zhu G, Zheng G, Wang S, He K, Liu J, Liu H. Key factors in epidemiological exposure and insights for environmental management: Evidence from meta-analysis. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2024; 362:124991. [PMID: 39303936 PMCID: PMC7616677 DOI: 10.1016/j.envpol.2024.124991] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/02/2024] [Revised: 08/14/2024] [Accepted: 09/17/2024] [Indexed: 09/22/2024]
Abstract
In recent years, the precision of exposure assessment methods has been rapidly improved and more widely adopted in epidemiological studies. However, such methodological advancement has introduced additional heterogeneity among studies. The precision of exposure assessment has become a potential confounding factors in meta-analyses, whose impacts on effect calculation remain unclear. To explore, we conducted a meta-analysis to integrate the long- and short-term exposure effects of PM2.5, NO2, and O3 on all-cause, cardiovascular, and respiratory mortality in the Chinese population. Literature was identified through Web of Science, PubMed, Scopus, and China National Knowledge Infrastructure before August 28, 2023. Sub-group analyses were performed to quantify the impact of exposure assessment precisions and pollution levels on the estimated risk. Studies achieving merely city-level resolution and population exposure are classified as using traditional assessment methods, while those achieving sub-kilometer simulations and individual exposure are considered finer assessment methods. Using finer assessment methods, the RR (under 10 μg/m3 increment, with 95% confidence intervals) for long-term NO2 exposure to all-cause mortality was 1.13 (1.05-1.23), significantly higher (p-value = 0.01) than the traditional assessment result of 1.02 (1.00-1.03). Similar trends were observed for long-term PM2.5 and short-term NO2 exposure. A decrease in short-term PM2.5 levels led to an increase in the RR for all-cause and cardiovascular mortality, from 1.0035 (1.0016-1.0053) and 1.0051 (1.0021-1.0081) to 1.0055 (1.0035-1.0075) and 1.0086 (1.0061-1.0111), with weak between-group significance (p-value = 0.13 and 0.09), respectively. Based on the quantitative analysis and literature information, we summarized four key factors influencing exposure assessment precision under a conceptualized framework: pollution simulation resolution, subject granularity, micro-environment classification, and pollution levels. Our meta-analysis highlighted the urgency to improve pollution simulation resolution, and we provide insights for researchers, policy-makers and the public. By integrating the most up-to-date epidemiological research, our study has the potential to provide systematic evidence and motivation for environmental management.
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Affiliation(s)
- Yongyue Wang
- State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, 100084, China
| | - Jie Chang
- National Center for Neurological Disorders, Xuanwu Hospital, Capital Medical University, Beijing, 100084, China; Centre for Clinical and Epidemiologic Research, Beijing an Zhen Hospital, Capital Medical University, Beijing Institute of Heart, Lung and Blood Vessel Diseases, Beijing, 100029, China
| | - Piaopiao Hu
- Centre for Clinical and Epidemiologic Research, Beijing an Zhen Hospital, Capital Medical University, Beijing Institute of Heart, Lung and Blood Vessel Diseases, Beijing, 100029, China
| | - Chun Deng
- State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, 100084, China
| | - Zhenyu Luo
- State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, 100084, China
| | - Junchao Zhao
- State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, 100084, China
| | - Zhining Zhang
- State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, 100084, China
| | - Wen Yi
- State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, 100084, China
| | - Guanlin Zhu
- State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, 100084, China
| | - Guangjie Zheng
- State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, 100084, China
| | - Shuxiao Wang
- State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, 100084, China
| | - Kebin He
- State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, 100084, China
| | - Jing Liu
- Centre for Clinical and Epidemiologic Research, Beijing an Zhen Hospital, Capital Medical University, Beijing Institute of Heart, Lung and Blood Vessel Diseases, Beijing, 100029, China
| | - Huan Liu
- State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, 100084, China.
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Siregar S, Idiawati N, Berekute AK, Maulana M, Pan WC, Yu KP. Association between long-term PM 2.5 exposure and mortality on Sumatra Island: Indonesian Family Life Survey (IFLS) 2000-2014. ENVIRONMENTAL MONITORING AND ASSESSMENT 2024; 196:1173. [PMID: 39503939 PMCID: PMC11541269 DOI: 10.1007/s10661-024-13323-5] [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: 12/01/2023] [Accepted: 10/25/2024] [Indexed: 11/09/2024]
Abstract
The concentration of PM2.5 (particulate matter with a diameter < 2.5 µm) on Sumatra Island has increased, mainly because of forest and peatland fires, transportation, and industry. Biomass burning releases partially burned carbon into the atmosphere, resulting in a smoky haze containing PM2.5. Air quality has deteriorated quickly, and PM2.5 has become a major health hazard in Indonesia. Studies on long-term exposure to PM2.5 have indicated its associations with both morbidity and mortality. Here, we measured long-term (2000-2014) exposure to PM2.5 on the basis of satellite-derived aerosol optical depth measurements (1 × 1 km2) used to predict ground-level PM2.5 concentrations. Additionally, population data on Sumatra Island residents from the fourth wave of the Indonesian Family Life Survey (IFLS) were obtained. We investigated the association between long-term PM2.5 exposure and mortality with a retrospective cohort study design. A total of 2409 subjects aged ≥ 40 years participated in the IFLS-3 beginning in November 2000, and we examined mortality outcomes until the IFLS-5 in September 2014. We used Cox regression models to calculate hazard ratios (HRs) of mortality associated with PM2.5 exposure. According to the adjusted model, the mortality HRs per 10 µg/m3 increase in PM2.5 concentration were 1.10 (95% CI 1.03, 1.17) for all natural causes, 1.17 (95% CI 1.05, 1.25) for cardiovascular causes, and 1.19 (95% CI 1.04, 1.36) for respiratory causes. Long-term exposure to PM2.5 was associated with all-natural, cardiovascular, and respiratory mortality on Sumatra Island, where PM2.5 levels exceed the WHO and US-EPA air quality standards.
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Affiliation(s)
- Sepridawati Siregar
- Faculty of Medicine, Abdurrab University, Pekanbaru, Indonesia
- Institute of Environmental and Occupational Health Sciences, National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Nora Idiawati
- Faculty of Math and Science, Tanjungpura University, Pontianak, Indonesia
| | - Abiyu Kerebo Berekute
- Institute of Environmental and Occupational Health Sciences, National Yang Ming Chiao Tung University, Taipei, Taiwan
- Department of Chemistry, College of Natural and Computational Sciences, Arba Minch University, Arba Minch, Ethiopia
| | - Muchsin Maulana
- Institute of Public Health, National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Wen-Chi Pan
- Institute of Environmental and Occupational Health Sciences, National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Kuo-Pin Yu
- Institute of Environmental and Occupational Health Sciences, National Yang Ming Chiao Tung University, Taipei, Taiwan.
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10
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Wang Y, Wang Z, Jiang J, Guo T, Chen S, Li Z, Yuan Z, Lin Q, Du Z, Wei J, Hao Y, Zhang W. The Effect of Long-Term Particulate Matter Exposure on Respiratory Mortality: Cohort Study in China. JMIR Public Health Surveill 2024; 10:e56059. [PMID: 39316790 PMCID: PMC11444524 DOI: 10.2196/56059] [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: 01/04/2024] [Revised: 07/01/2024] [Accepted: 07/02/2024] [Indexed: 09/26/2024] Open
Abstract
Background Particulate matter (PM), which affects respiratory health, has been well documented; however, substantial evidence from large cohorts is still limited, particularly in highly polluted countries and for PM1. Objective Our objective was to examine the potential causal links between long-term exposure to PMs (PM2.5, PM10, and more importantly, PM1) and respiratory mortality. Methods A total of 580,757 participants from the Guangzhou area, China, were recruited from 2009 to 2015 and followed up through 2020. The annual average concentrations of PMs at a 1-km spatial resolution around the residential addresses were estimated using validated spatiotemporal models. The marginal structural Cox model was used to estimate the associations of PM exposure with respiratory mortality, accounting for time-varying PM exposure. Results were stratified by demographics and lifestyle behaviors factors. Results Among the participants, the mean age was 48.33 (SD 17.55) years, and 275,676 (47.47%) of them were men. During the follow-up period, 7260 deaths occurred due to respiratory diseases. The annual average concentrations of PM1, PM2.5, and PM10 showed a declining trend during the follow-up period. After adjusting for confounders, a 6.6% (95% CI 5.6%-7.6%), 4.2% (95% CI 3.6%-4.7%), and 4.0% (95% CI 3.6%-4.5%) increase in the risk of respiratory mortality was observed following each 1-μg/m3 increase in concentrations of PM1, PM2.5, and PM10, respectively. In addition, older participants, nonsmokers, participants with higher exercise frequency, and those exposed to a lower normalized difference vegetation index tended to be more susceptible to the effects of PMs. Furthermore, participants in the low-exposure group tended to be at a 7.6% and 2.7% greater risk of respiratory mortality following PM1 and PM10 exposure, respectively, compared to the entire cohort. Conclusions This cohort study provides causal clues of the respiratory impact of long-term ambient PM exposure, indicating that PM reduction efforts may continuously benefit the population's respiratory health.
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Affiliation(s)
- Ying Wang
- Department of Medical Statistics, School of Public Health & Research Center for Health Information, Sun Yat-sen Global Health Institute, Sun Yat-sen University, 2nd Zhongshan Road, Guangzhou, 510000, China
| | - Zhuohao Wang
- School of Public Health, Sun Yat-sen University, Guangzhou, China
| | - Jie Jiang
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Peking, China
| | - Tong Guo
- Department of Medical Statistics, School of Public Health & Research Center for Health Information, Sun Yat-sen Global Health Institute, Sun Yat-sen University, 2nd Zhongshan Road, Guangzhou, 510000, China
| | - Shimin Chen
- Department of Medical Statistics, School of Public Health & Research Center for Health Information, Sun Yat-sen Global Health Institute, Sun Yat-sen University, 2nd Zhongshan Road, Guangzhou, 510000, China
| | - Zhiqiang Li
- Department of Medical Statistics, School of Public Health & Research Center for Health Information, Sun Yat-sen Global Health Institute, Sun Yat-sen University, 2nd Zhongshan Road, Guangzhou, 510000, China
| | - Zhupei Yuan
- Department of Medical Statistics, School of Public Health & Research Center for Health Information, Sun Yat-sen Global Health Institute, Sun Yat-sen University, 2nd Zhongshan Road, Guangzhou, 510000, China
| | - Qiaoxuan Lin
- Department of Statistics, Guangzhou Health Technology Identification, Human Resources Assessment Center, Guangzhou, China
| | - Zhicheng Du
- Department of Medical Statistics, School of Public Health & Research Center for Health Information, Sun Yat-sen Global Health Institute, Sun Yat-sen University, 2nd Zhongshan Road, Guangzhou, 510000, 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, Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Peking, China
| | - Wangjian Zhang
- Department of Medical Statistics, School of Public Health & Research Center for Health Information, Sun Yat-sen Global Health Institute, Sun Yat-sen University, 2nd Zhongshan Road, Guangzhou, 510000, China
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11
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Stevenin G, Canonge J, Gervais M, Fiore A, Lareyre F, Touma J, Desgranges P, Raffort J, Sénémaud J. e-Health and environmental sustainability in vascular surgery. Semin Vasc Surg 2024; 37:333-341. [PMID: 39277350 DOI: 10.1053/j.semvascsurg.2024.08.005] [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: 06/14/2024] [Revised: 08/18/2024] [Accepted: 08/20/2024] [Indexed: 09/17/2024]
Abstract
e-Health technology holds great promise for improving the management of patients with vascular diseases and offers a unique opportunity to mitigate the environmental impact of vascular care, which remains an under-investigated field. The innovative potential of e-Health operates in a complex environment with finite resources. As the expansion of digital health will increase demand for devices, contributing to the environmental burden of electronics and energy use, the sustainability of e-Health technology is of crucial importance, especially in the context of increasing prevalence of cardiovascular diseases. This review discusses the environmental impact of care related to vascular surgery and e-Health innovation, the potential of e-Health technology to mitigate greenhouse gas emissions generated by the health care sector, and to provide leads to research promoting e-Heath technology sustainability. A multifaceted approach, including ethical design, validated eco-audits methodology and reporting standards, technological refinement, electronic and medical devices reuse and recycling, and effective policies is required to provide a sustainable and optimal level of care to vascular patients.
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Affiliation(s)
- Gabrielle Stevenin
- Department of Vascular Surgery, Henri Mondor University Hospital, 1 rue Gustave Eiffel, 94000 Créteil, France; Université Paris-Est, Créteil, France
| | - Jennifer Canonge
- Department of Vascular Surgery, Henri Mondor University Hospital, 1 rue Gustave Eiffel, 94000 Créteil, France; Université Paris-Est, Créteil, France
| | - Marianne Gervais
- Université Paris-Est, Créteil, France; Institut Mondor de Recherche Biomédicale, U955 INSERM, Créteil, France
| | - Antonio Fiore
- Université Paris-Est, Créteil, France; Department of Cardiac Surgery, Henri Mondor University Hospital, Créteil, France
| | - Fabien Lareyre
- Department of Vascular Surgery, Hospital of Antibes Juan-les-Pins, France,; Université Côte d'Azur, Le Centre National de la Recherche Scientifique, UMR7370, LP2M, Nice, France; Fédération Hospitalo-Universitaire Plan&Go, Nice, France
| | - Joseph Touma
- Department of Vascular Surgery, Henri Mondor University Hospital, 1 rue Gustave Eiffel, 94000 Créteil, France; Université Paris-Est, Créteil, France
| | - Pascal Desgranges
- Department of Vascular Surgery, Henri Mondor University Hospital, 1 rue Gustave Eiffel, 94000 Créteil, France; Université Paris-Est, Créteil, France
| | - Juliette Raffort
- Université Côte d'Azur, Le Centre National de la Recherche Scientifique, UMR7370, LP2M, Nice, France; Fédération Hospitalo-Universitaire Plan&Go, Nice, France; Clinical Chemistry Laboratory, University Hospital of Nice, France; Institute 3IA Côte d'Azur, Université Côte d'Azur, France
| | - Jean Sénémaud
- Department of Vascular Surgery, Henri Mondor University Hospital, 1 rue Gustave Eiffel, 94000 Créteil, France; Université Paris-Est, Créteil, France; Laboratory for Vascular Translational Science, U1148 INSERM, Paris, France.
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Singh A, Bartington SE, Abreu P, Anderson R, Cowell N, Leach FC. Impacts of daily household activities on indoor particulate and NO 2 concentrations; a case study from oxford UK. Heliyon 2024; 10:e34210. [PMID: 39165984 PMCID: PMC11333897 DOI: 10.1016/j.heliyon.2024.e34210] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2024] [Revised: 07/02/2024] [Accepted: 07/04/2024] [Indexed: 08/22/2024] Open
Abstract
This study explores indoor air pollutant (PM1, PM2.5 and NO2) concentrations over a 15-week period during the COVID-19 pandemic in a typical suburban household in Oxford, UK. A multi-room intensive monitoring study was conducted in a single dwelling using 10 air quality sensors measuring real-time pollutant concentrations at 10 second intervals to assess temporal and spatial variability in PM1, PM2.5 and NO2 concentrations, identify pollution-prone areas, and investigate the impact of residents' activities on indoor air quality. Significant spatial variations in PM concentrations were observed within the study dwelling, with highest hourly concentrations (769.0 & 300.9 μg m-3 for PM2.5, and PM1, respectively) observed in the upstairs study room, which had poor ventilation. Cooking activities were identified as a major contributor to indoor particulate pollution, with peak concentrations aligning with cooking events. Indoor NO2 levels were typically higher than outdoor levels, particularly in the kitchen where a gas-cooking appliance was used. There was no significant association observed between outdoor and indoor PM concentrations; however, a clear correlation was evident between kitchen PM emissions and indoor levels. Similarly, outdoor NO2 had a limited influence on indoor air quality compared to kitchen activities. Indoor sources were found to dominate for both PM and NO2, with higher Indoor/Outdoor (I/O) ratios observed in the upstairs bedroom and the kitchen. Overall, our findings highlight the contribution of indoor air pollutant sources and domestic activities to indoor air pollution exposure, notably during the COVID-19 pandemic when people were typically spending more time in domestic settings. Our novel findings, which suggest high levels of pollutant concentrations in upstairs (first floor) rooms, underscore the necessity for targeted interventions. These interventions include the implementation of source control measures, effective ventilation strategies and occupant education for behaviour change, all aimed at improving indoor air quality and promoting healthier living environments.
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Affiliation(s)
- Ajit Singh
- Institute of Applied Health Research, University of Birmingham, Edgbaston Park Road, Birmingham, B15 2TT, UK
- School of Geography, Earth and Environmental Sciences, University of Birmingham, Edgbaston Park Road, Birmingham, B15 2TT, UK
| | - Suzanne E. Bartington
- Institute of Applied Health Research, University of Birmingham, Edgbaston Park Road, Birmingham, B15 2TT, UK
| | - Pedro Abreu
- Oxford City Council, St Aldates Chambers, 109 St Aldates, Oxford, OX1 1DS, UK
| | - Ruth Anderson
- Oxfordshire County Council, County Hall, New Road, Oxford, OX1 1ND, UK
| | - Nicole Cowell
- School of Geography, Earth and Environmental Sciences, University of Birmingham, Edgbaston Park Road, Birmingham, B15 2TT, UK
- Centre for Environmental Policy, Imperial College London, Weeks Building, 16-18 Prince's Garden, London SW7 1NE, UK
| | - Felix C.P. Leach
- Department for Engineering Science, University of Oxford, Parks Road, Oxford, OX1 3PJ, UK
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Zhang T, Lui KH, Ho SSH, Chen J, Chuang HC, Ho KF. Characterization of airborne endotoxin in personal exposure to fine particulate matter (PM 2.5) and bioreactivity for elderly residents in Hong Kong. ECOTOXICOLOGY AND ENVIRONMENTAL SAFETY 2024; 280:116530. [PMID: 38833976 DOI: 10.1016/j.ecoenv.2024.116530] [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: 02/28/2024] [Revised: 05/17/2024] [Accepted: 05/29/2024] [Indexed: 06/06/2024]
Abstract
The heavy metals and bioreactivity properties of endotoxin in personal exposure to fine particulate matter (PM2.5) were characterized in the analysis. The average personal exposure concentrations to PM2.5 were ranged from 6.8 to 96.6 μg/m3. The mean personal PM2.5 concentrations in spring, summer, autumn, and winter were 32.1±15.8, 22.4±11.8, 35.3±11.9, and 50.2±19.9 μg/m3, respectively. There were 85 % of study targets exceeded the World Health Organization (WHO) PM2.5 threshold (24 hours). The mean endotoxin concentrations ranged from 1.086 ± 0.384-1.912 ± 0.419 EU/m3, with a geometric mean (GM) varied from 1.034 to 1.869. The concentration of iron (Fe) (0.008-1.16 μg/m3) was one of the most abundant transition metals in the samples that could affect endotoxin toxicity under Toll-Like Receptor 4 (TLR4) stimulation. In summer, the interleukin 6 (IL-6) levels showed statistically significant differences compared to other seasons. Spearman correlation analysis showed endotoxin concentrations were positively correlated with chromium (Cr) and nickel (Ni), implying possible roles as nutrients and further transport via adhering to the surface of fine inorganic particles. Mixed-effects model analysis demonstrated that Tumor necrosis factor-α (TNF-α) production was positively associated with endotoxin concentration and Cr as a combined exposure factor. The Cr contained the highest combined effect (0.205-0.262), suggesting that Cr can potentially exacerbate the effect of endotoxin on inflammation and oxidative stress. The findings will be useful for practical policies for mitigating air pollution to protect the public health of the citizens.
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Affiliation(s)
- Tianhang Zhang
- The Jockey Club School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong, China
| | - Ka Hei Lui
- The Jockey Club School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong, China
| | - Steven Sai Hang Ho
- Division of Atmosphere Sciences, Desert Research Institute, Reno, NV 89512, United States; Hong Kong Premium Services and Research Laboratory, Cheung Sha Wan, Kowloon, Hong Kong, China
| | - Jiayao Chen
- School of Architecture, Planning and Environmental Policy, University College Dublin, Dublin, Ireland
| | - Hsiao-Chi Chuang
- School of Respiratory Therapy, College of Medicine, Taipei Medical University, Taipei, Taiwan
| | - Kin Fai Ho
- The Jockey Club School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong, China.
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Jiřík V, Římanová V, Janulková T, Siemiatkowski G, Osrodka L, Krajny E. Lifetime losses due to cardiovascular and respiratory diseases attributable to air pollution in polluted and unpolluted areas. INTERNATIONAL JOURNAL OF ENVIRONMENTAL HEALTH RESEARCH 2024; 34:1525-1539. [PMID: 37356040 DOI: 10.1080/09603123.2023.2225426] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/12/2023] [Accepted: 06/12/2023] [Indexed: 06/27/2023]
Abstract
The article assesses differences in lifetime losses caused by premature deaths from cardiopulmonary disease in populations living in areas with different environmental burdens. The results provide different perspectives on data on total years lost and lifetime losses attributable to air pollution. Such lifetime losses in the industrial area related to cardiovascular causes of death are 7.6 or 5.1 years per male or female deceased, representing an average lifetime loss of 0.01907 years (i.e. 7 days) per 1 male or 0.01273 years (i.e. 4.6 days) per 1 female in the entire population. Losses related to cerebrovascular or respiratory causes of death are about 5.4 or 5.9 years per 1 deceased male or 3.9 or 5 years per 1 deceased female, respectively, which represents a loss of 0.00481 (1.8 days), or 0.00148 years (0.5 days) per 1 male or 0.00466 (1.7 days), or 0.00058 years (0.2 days) per 1 female.
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Affiliation(s)
- Vítězslav Jiřík
- Centre for Epidemiological Research, Faculty of Medicine, University of Ostrava, Ostrava, Czech Republic
- Department of Epidemiology and Public Health, Faculty of Medicine, University of Ostrava, Ostrava, Czech Republic
| | - Veronika Římanová
- Centre for Epidemiological Research, Faculty of Medicine, University of Ostrava, Ostrava, Czech Republic
| | - Tereza Janulková
- Centre for Epidemiological Research, Faculty of Medicine, University of Ostrava, Ostrava, Czech Republic
| | | | - Leszek Osrodka
- Centrum Badań i Rozwoju, Institute of Meteorology and Water Management National Research Institute, Warsaw, Poland
| | - Ewa Krajny
- Centrum Badań i Rozwoju, Institute of Meteorology and Water Management National Research Institute, Warsaw, Poland
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15
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Wei Y, Feng Y, Danesh Yazdi M, Yin K, Castro E, Shtein A, Qiu X, Peralta AA, Coull BA, Dominici F, Schwartz JD. Exposure-response associations between chronic exposure to fine particulate matter and risks of hospital admission for major cardiovascular diseases: population based cohort study. BMJ 2024; 384:e076939. [PMID: 38383041 PMCID: PMC10879983 DOI: 10.1136/bmj-2023-076939] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 01/02/2024] [Indexed: 02/23/2024]
Abstract
OBJECTIVE To estimate exposure-response associations between chronic exposure to fine particulate matter (PM2.5) and risks of the first hospital admission for major cardiovascular disease (CVD) subtypes. DESIGN Population based cohort study. SETTING Contiguous US. PARTICIPANTS 59 761 494 Medicare fee-for-service beneficiaries aged ≥65 years during 2000-16. Calibrated PM2.5 predictions were linked to each participant's residential zip code as proxy exposure measurements. MAIN OUTCOME MEASURES Risk of the first hospital admission during follow-up for ischemic heart disease, cerebrovascular disease, heart failure, cardiomyopathy, arrhythmia, valvular heart disease, thoracic and abdominal aortic aneurysms, or a composite of these CVD subtypes. A causal framework robust against confounding bias and bias arising from errors in exposure measurements was developed for exposure-response estimations. RESULTS Three year average PM2.5 exposure was associated with increased relative risks of first hospital admissions for ischemic heart disease, cerebrovascular disease, heart failure, cardiomyopathy, arrhythmia, and thoracic and abdominal aortic aneurysms. For composite CVD, the exposure-response curve showed monotonically increased risk associated with PM2.5: compared with exposures ≤5 µg/m3 (the World Health Organization air quality guideline), the relative risk at exposures between 9 and 10 µg/m3, which encompassed the US national average of 9.7 µg/m3 during the study period, was 1.29 (95% confidence interval 1.28 to 1.30). On an absolute scale, the risk of hospital admission for composite CVD increased from 2.59% with exposures ≤5 µg/m3 to 3.35% at exposures between 9 and 10 µg/m3. The effects persisted for at least three years after exposure to PM2.5. Age, education, accessibility to healthcare, and neighborhood deprivation level appeared to modify susceptibility to PM2.5. CONCLUSIONS The findings of this study suggest that no safe threshold exists for the chronic effect of PM2.5 on overall cardiovascular health. Substantial benefits could be attained through adherence to the WHO air quality guideline.
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Affiliation(s)
- Yaguang Wei
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA 02215, USA
| | - Yijing Feng
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA 02215, USA
| | - Mahdieh Danesh Yazdi
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA 02215, USA
- Program in Public Health, Department of Family, Population, and Preventive Medicine, Renaissance School of Medicine at Stony Brook University, Stony Brook, NY, USA
| | - Kanhua Yin
- Department of Surgery, University of Missouri-Kansas City School of Medicine, Kansas City, MO, USA
| | - Edgar Castro
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA 02215, USA
| | - Alexandra Shtein
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA 02215, USA
| | - Xinye Qiu
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA 02215, USA
| | - Adjani A Peralta
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA 02215, USA
| | - Brent A Coull
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA 02215, USA
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Francesca Dominici
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA 02215, USA
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Joel D Schwartz
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA 02215, USA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
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16
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Wang J, Hu X, Yang T, Jin J, Hao J, Kelly FJ, Huang J, Li G. Ambient air pollution and the dynamic transitions of stroke and dementia: a population-based cohort study. EClinicalMedicine 2024; 67:102368. [PMID: 38169700 PMCID: PMC10758736 DOI: 10.1016/j.eclinm.2023.102368] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/04/2023] [Revised: 11/25/2023] [Accepted: 11/28/2023] [Indexed: 01/05/2024] Open
Abstract
Background Stroke and dementia are the leading causes of neurological disease burden. Detrimental effects of air pollution on both conditions are increasingly recognised, while the impacts on the dynamic transitions have not yet been explored, and whether critical time intervals exist is unknown. Methods This prospective study was conducted based on the UK Biobank. Annual average air pollution concentrations at baseline year 2010 estimated by land-use regression models were used as a proxy for long-term air pollution exposure. Associations between multiple air pollutants (PM2.5, PM2.5-10, and NO2) indicated by air pollution score and the dynamic transitions of stroke and dementia were estimated, and the impacts during critical time intervals were explored. The date cutoff of this study was February 29, 2020. Findings During a median follow-up of 10.9 years in 413,372 participants, 6484, 3813, and 376 participants developed incident stroke, dementia, and comorbidity of stroke and dementia. For the overall transition from stroke to comorbid dementia, the hazard ratio (HR) for each interquartile range (IQR) increase in air pollution score was 1.38 (95% CI, 1.15, 1.65), and the risks were limited to two time intervals (within 1 year and over 5 years after stroke). As for the transition from dementia to comorbid stroke, increased risk was only observed during 2-3 years after dementia. Interpretation Our findings suggested that air pollution played an important role in the dynamic transition of stroke and dementia even at concentrations below the current criteria. The findings provided new evidence for alleviating the disease burden of neurological disorders related to air pollution during critical time intervals. Funding The State Scholarship Fund of China Scholarship Council.
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Affiliation(s)
- Jiawei Wang
- Department of Occupational and Environmental Health Sciences, Peking University School of Public Health, Beijing, China
| | - Xin Hu
- Department of Occupational and Environmental Health Sciences, Peking University School of Public Health, Beijing, China
| | - Teng Yang
- Department of Occupational and Environmental Health Sciences, Peking University School of Public Health, Beijing, China
| | - Jianbo Jin
- Department of Occupational and Environmental Health Sciences, Peking University School of Public Health, Beijing, China
| | - Junwei Hao
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Frank J. Kelly
- Environmental Research Group, Faculty of Medicine, School of Public Health, Imperial College London, London, UK
| | - Jing Huang
- Department of Occupational and Environmental Health Sciences, Peking University School of Public Health, Beijing, China
- Institute for Global Health and Development, Peking University, Beijing, China
| | - Guoxing Li
- Department of Occupational and Environmental Health Sciences, Peking University School of Public Health, Beijing, China
- Environmental Research Group, Faculty of Medicine, School of Public Health, Imperial College London, London, UK
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17
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Wang Q, Cao J. Atmospheric PM 2.5 exposure and risk of ischemic heart disease: A systematic review and meta-analysis of observational studies. Perfusion 2024; 39:210-222. [PMID: 36342821 DOI: 10.1177/02676591221131485] [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] [Indexed: 12/22/2023]
Abstract
Fine particulate matter <2.5 μm in diameter (PM2.5) has been validated to associate with cardiovascular diseases (CVD) incidence and mortality. So far, no study has quantitatively evaluated the relationship between the atmospheric PM2.5 exposure and ischemic heart disease (IHD). We conducted a meta-analysis to illustrate the relationship between PM2.5 and IHD. Published articles were systematically searched (until June 2022) from PubMed, EMBASE, Cochrane Library. A random-effect model was performed to summarize the total relative risks (RRs) and 95% confidence intervals (CIs). Meta-analysis was performed using Stata 12.0 software. A total of 28 studies among 23 cohorts (23.38 million individuals and 256256 IHD cases) were included. With PM2.5 increasing 10 μg/m3, the total RRs of IHD incidence and mortality were 1.07 (95% CI: 0.99-1.17), 1.21 (95% CI: 1.15-1.28), respectively. In sub-analyses, our study revealed that the combined RRs of exposure to PM2.5 on IHD mortality in Asian and European population [1.11 (95% CI: 0.93-1.33); 1.06 (95% CI: 1.02-1.11)] were much lower compared with American and Canadian people [1.27 (95% CI: 1.17-1.37); 1.30 (95% CI: 1.24-1.35)]. Furthermore, study duration, size and some adjustments were related with the total RR. Our findings indicated that exposure of an increase in the concentration of atmospheric PM2.5 may increase the risk of IHD incidence and mortality. Further evidence is needed to confirmed the association.
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Affiliation(s)
- Qingli Wang
- Department of Cardiology, Yancheng Clinical College of Xuzhou Medical University, Yancheng, China
| | - Jingyan Cao
- Department of Cardiology, Yancheng Clinical College of Xuzhou Medical University, Yancheng, China
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18
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Li W, Tian A, Shi Y, Chen B, Ji R, Ge J, Su X, Pu B, Lei L, Ma R, Wang Q, Ban J, Song L, Xu W, Zhang Y, He W, Yang H, Li X, Li T, Li J. Associations of long-term fine particulate matter exposure with all-cause and cause-specific mortality: results from the ChinaHEART project. THE LANCET REGIONAL HEALTH. WESTERN PACIFIC 2023; 41:100908. [PMID: 37767374 PMCID: PMC10520991 DOI: 10.1016/j.lanwpc.2023.100908] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/02/2023] [Revised: 08/14/2023] [Accepted: 09/05/2023] [Indexed: 09/29/2023]
Abstract
Background The chronic effects of fine particulate matter (PM2.5) at high concentrations remains uncertain. We aimed to examine the relationship of long-term PM2.5 exposure with all-cause and the top three causes of death (cardiovascular disease [CVD], cancer, and respiratory disease), and to analyze their concentration-response functions over a wide range of concentrations. Methods We enrolled community residents aged 35-75 years from 2014 to 2017 from all 31 provinces of the Chinese Mainland, and followed them up until 2021. We used a long-term estimation dataset for both PM2.5 and O3 concentrations with a high spatiotemporal resolution to assess the individual exposure, and used Cox proportional hazards models to estimate the associations between PM2.5 and mortalities. Findings We included 1,910,923 participants, whose mean age was 55.6 ± 9.8 years and 59.4% were female. A 10 μg/m3 increment in PM2.5 exposure was associated with increased risk for all-cause death (hazard ratio 1.02 [95% confidence interval 1.012-1.028]), CVD death (1.024 [1.011-1.037]), cancer death (1.037 [1.023-1.052]), and respiratory disease death (1.083 [1.049-1.117]), respectively. Long-term PM2.5 exposure nonlinearly related with all-cause, CVD, and cancer mortalities, while linearly related with respiratory disease mortality. Interpretation The overall effects of long-term PM2.5 exposure on mortality in the high concentration settings are weaker than previous reports from settings of PM2.5 concentrations < 35 μg/m³. The distinct concentration-response relationships of CVD, cancer, and respiratory disease mortalities could facilitate targeted public health efforts to prevent death caused by air pollution. Funding The Chinese Academy of Medical Sciences Innovation Fund for Medical Science, the National High Level Hospital Clinical Research Funding, the Ministry of Finance of China and National Health Commission of China, the 111 Project from the Ministry of Education of China.
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Affiliation(s)
- Wei Li
- National Clinical Research Center for Cardiovascular Diseases, NHC Key Laboratory of Clinical Research for Cardiovascular Medications, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, National Center for Cardiovascular Diseases, Beijing, People’s Republic of China
| | - Aoxi Tian
- National Clinical Research Center for Cardiovascular Diseases, NHC Key Laboratory of Clinical Research for Cardiovascular Medications, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, National Center for Cardiovascular Diseases, Beijing, People’s Republic of China
| | - Yu Shi
- National Clinical Research Center for Cardiovascular Diseases, Fuwai Hospital Chinese Academy of Medical Sciences, Shenzhen, Guangdong Province, People’s Republic of China
| | - Bowang Chen
- National Clinical Research Center for Cardiovascular Diseases, NHC Key Laboratory of Clinical Research for Cardiovascular Medications, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, National Center for Cardiovascular Diseases, Beijing, People’s Republic of China
| | - Runqing Ji
- National Clinical Research Center for Cardiovascular Diseases, NHC Key Laboratory of Clinical Research for Cardiovascular Medications, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, National Center for Cardiovascular Diseases, Beijing, People’s Republic of China
| | - Jinzhuo Ge
- National Clinical Research Center for Cardiovascular Diseases, NHC Key Laboratory of Clinical Research for Cardiovascular Medications, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, National Center for Cardiovascular Diseases, Beijing, People’s Republic of China
| | - Xiaoming Su
- National Clinical Research Center for Cardiovascular Diseases, NHC Key Laboratory of Clinical Research for Cardiovascular Medications, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, National Center for Cardiovascular Diseases, Beijing, People’s Republic of China
| | - Boxuan Pu
- National Clinical Research Center for Cardiovascular Diseases, NHC Key Laboratory of Clinical Research for Cardiovascular Medications, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, National Center for Cardiovascular Diseases, Beijing, People’s Republic of China
| | - Lubi Lei
- National Clinical Research Center for Cardiovascular Diseases, NHC Key Laboratory of Clinical Research for Cardiovascular Medications, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, National Center for Cardiovascular Diseases, Beijing, People’s Republic of China
| | - Runmei Ma
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, People’s Republic of China
| | - Qing Wang
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, People’s Republic of China
| | - Jie Ban
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, People’s Republic of China
| | - Lijuan Song
- National Clinical Research Center for Cardiovascular Diseases, NHC Key Laboratory of Clinical Research for Cardiovascular Medications, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, National Center for Cardiovascular Diseases, Beijing, People’s Republic of China
| | - Wei Xu
- National Clinical Research Center for Cardiovascular Diseases, NHC Key Laboratory of Clinical Research for Cardiovascular Medications, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, National Center for Cardiovascular Diseases, Beijing, People’s Republic of China
| | - Yan Zhang
- National Clinical Research Center for Cardiovascular Diseases, NHC Key Laboratory of Clinical Research for Cardiovascular Medications, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, National Center for Cardiovascular Diseases, Beijing, People’s Republic of China
| | - Wenyan He
- National Clinical Research Center for Cardiovascular Diseases, NHC Key Laboratory of Clinical Research for Cardiovascular Medications, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, National Center for Cardiovascular Diseases, Beijing, People’s Republic of China
| | - Hao Yang
- National Clinical Research Center for Cardiovascular Diseases, NHC Key Laboratory of Clinical Research for Cardiovascular Medications, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, National Center for Cardiovascular Diseases, Beijing, People’s Republic of China
| | - Xi Li
- National Clinical Research Center for Cardiovascular Diseases, NHC Key Laboratory of Clinical Research for Cardiovascular Medications, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, National Center for Cardiovascular Diseases, Beijing, People’s Republic of China
- Central China Sub-center of the National Center for Cardiovascular Diseases, Zhengzhou, People’s Republic of China
| | - Tiantian Li
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, People’s Republic of China
| | - Jing Li
- National Clinical Research Center for Cardiovascular Diseases, NHC Key Laboratory of Clinical Research for Cardiovascular Medications, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, National Center for Cardiovascular Diseases, Beijing, People’s Republic of China
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Mallah MA, Soomro T, Ali M, Noreen S, Khatoon N, Kafle A, Feng F, Wang W, Naveed M, Zhang Q. Cigarette smoking and air pollution exposure and their effects on cardiovascular diseases. Front Public Health 2023; 11:967047. [PMID: 38045957 PMCID: PMC10691265 DOI: 10.3389/fpubh.2023.967047] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2022] [Accepted: 06/26/2023] [Indexed: 12/05/2023] Open
Abstract
Cardiovascular disease (CVD) has no socioeconomic, topographical, or sex limitations as reported by the World Health Organization (WHO). The significant drivers of CVD are cardio-metabolic, behavioral, environmental, and social risk factors. However, some significant risk factors for CVD (e.g., a pitiable diet, tobacco smoking, and a lack of physical activities), have also been linked to an elevated risk of cardiovascular disease. Lifestyles and environmental factors are known key variables in cardiovascular disease. The familiarity with smoke goes along with the contact with the environment: air pollution is considered a source of toxins that contribute to the CVD burden. The incidence of myocardial infarction increases in males and females and may lead to fatal coronary artery disease, as confirmed by epidemiological studies. Lipid modification, inflammation, and vasomotor dysfunction are integral components of atherosclerosis development and advancement. These aspects are essential for the identification of atherosclerosis in clinical investigations. This article aims to show the findings on the influence of CVD on the health of individuals and human populations, as well as possible pathology and their involvement in smoking-related cardiovascular diseases. This review also explains lifestyle and environmental factors that are known to contribute to CVD, with indications suggesting an affiliation between cigarette smoking, air pollution, and CVD.
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Affiliation(s)
| | - Tahmina Soomro
- Department of Sociology, Shah Abdul Latif University, Khairpur, Pakistan
| | - Mukhtiar Ali
- Department of Chemical Engineering, Quaid-e-Awam University of Engineering, Science and Technology, Nawabshah, Sindh, Pakistan
| | - Sobia Noreen
- Department of Pharmaceutics Technology, Institute of Pharmacy, University of Innsbruck, Insbruck, Austria
| | - Nafeesa Khatoon
- College of Public Health, Zhengzhou University, Zhengzhou, China
| | - Akriti Kafle
- School of Nursing, Zhengzhou University, Zhengzhou, China
| | - Feifei Feng
- College of Public Health, Zhengzhou University, Zhengzhou, China
| | - Wei Wang
- College of Public Health, Zhengzhou University, Zhengzhou, China
| | - Muhammad Naveed
- Department of Physiology and Pharmacology, College of Medicine and Life Sciences, University of Toledo, Toledo, OH, United States
| | - Qiao Zhang
- College of Public Health, Zhengzhou University, Zhengzhou, China
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20
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Vallée A. Sex Associations Between Air Pollution and Estimated Atherosclerotic Cardiovascular Disease Risk Determination. Int J Public Health 2023; 68:1606328. [PMID: 37841972 PMCID: PMC10569126 DOI: 10.3389/ijph.2023.1606328] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2023] [Accepted: 09/19/2023] [Indexed: 10/17/2023] Open
Abstract
Objective: The purpose of this study was to investigate the sex correlations of particulate matters (PM2.5, PM10, PM2.5-10), NO2 and NOx with ASCVD risk in the UK Biobank population. Methods: Among 285,045 participants, pollutants were assessed and correlations between ASCVD risk were stratified by sex and estimated using multiple linear and logistic regressions adjusted for length of time at residence, education, income, physical activity, Townsend deprivation, alcohol, smocking pack years, BMI and rural/urban zone. Results: Males presented higher ASCVD risk than females (8.63% vs. 2.65%, p < 0.001). In males PM2.5, PM10, NO2, and NOx each were associated with an increased ASCVD risk >7.5% in the adjusted logistic models, with ORs [95% CI] for a 10 μg/m3 increase were 2.17 [1.87-2.52], 1.15 [1.06-1.24], 1.06 [1.04-1.08] and 1.05 [1.04-1.06], respectively. In females, the ORs for a 10 μg/m3 increase were 1.55 [1.19-2.05], 1.22 [1.06-1.42], 1.07 [1.03-1.10], and 1.04 [1.02-1.05], respectively. No association was observed in both sexes between ASCVD risk and PM2.5-10. Conclusion: Our findings may suggest the possible actions of air pollutants on ASCVD risk.
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Affiliation(s)
- Alexandre Vallée
- Department of Epidemiology and Public Health, Foch Hospital, Suresnes, France
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21
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Zhang Y, Yin Z, Li S, Zhang JJ, Sun HZ, Liu K, Shirai K, Hu K, Qiu C, Liu X, Li Y, Zeng Y, Yao Y. Ambient PM 2.5, ozone and mortality in Chinese older adults: A nationwide cohort analysis (2005-2018). JOURNAL OF HAZARDOUS MATERIALS 2023; 454:131539. [PMID: 37149946 PMCID: PMC11758737 DOI: 10.1016/j.jhazmat.2023.131539] [Citation(s) in RCA: 24] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/22/2023] [Revised: 04/17/2023] [Accepted: 04/27/2023] [Indexed: 05/09/2023]
Abstract
BACKGROUND Cohort evidence linking long-term survival with exposure to multiple air pollutants (e.g., fine particulate matter [PM2.5] and ozone) was extensively sparse in low- and middle-income countries, especially among older adults. This study aimed to investigate potential associations of long-term exposures to PM2.5 and ozone with all-cause mortality in Chinese older adults. METHODS A dynamic nationwide prospective cohort comprising 20,352 adults aged ≥65 years were enrolled from the Chinese Longitudinal Healthy Longevity Study and followed up through 2005-2018. Participants' annual exposures to warm-season ozone and year-round PM2.5 were assigned using satellite-derived spatiotemporal estimates. A directed acyclic graph (DAG) was developed to identify confounding variables. Associations of annual mean exposures to PM2.5 and ozone with mortality were evaluated using single- and two-pollutant Cox proportional hazards models, adjusting for time-dependent individual risk factors and ambient temperature. RESULTS During 100 thousand person-years of follow-up (median: 3.6 years), a total of 14,313 death events occurred. The participants were averagely aged 87.1 years at baseline and exposed to a wide range of annual average concentrations of warm-season maximum 8-hour ozone (mean, 54.4 ppb; range, 23.3-81.6 ppb) and year-round PM2.5 (mean, 65.5 μg/m3; range, 10.1-162.9 μg/m3). Approximately linear concentration-response relationship was identified for ozone, whereas significant increases in PM2.5-associated mortality risks were observed only when concentrations were above 60 μg/m3. Rises of 10 ppb in ozone and 10 µg/m3 in PM2.5 above 60 µg/m3 were associated with increases in all-cause mortality of 13.2% (95% confidence interval [CI]: 10.2-16.2%) and 6.2% (95% CI: 4.6-7.7%) in DAG-based single-pollutant model, and of 9.7% (95% CI: 6.6-13.0%) and 5.3% (95% CI: 3.7-6.9%) in DAG-based two-pollutant model, respectively. We detected significant effect modification by temperature in associations of mortality with ozone (P <0.001 for interaction), suggesting greater ozone-related risks among participants in warmer locations. CONCLUSIONS This study provided longitudinal evidence that long-term exposure to ambient PM2.5 and ozone significantly and independently contributed to elevated risks of all-cause mortality among older adults in China.
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Affiliation(s)
- Yunquan Zhang
- Institute of Social Development and Health Management, Hubei Province Key Laboratory of Occupational Hazard Identification and Control, School of Public Health, Wuhan University of Science and Technology, Wuhan 430065, China
| | - Zhouxin Yin
- Institute of Social Development and Health Management, Hubei Province Key Laboratory of Occupational Hazard Identification and Control, School of Public Health, Wuhan University of Science and Technology, Wuhan 430065, China; School of Public Health and Emergency Management, Southern University of Science and Technology, Shenzhen 518055, China
| | - Shaojie Li
- China Center for Health Development Studies, Peking University, Beijing, China
| | - Junfeng Jim Zhang
- Nicholas School of the Environment and Duke Global Health Institute, Duke University, Durham, NC, USA
| | - Haitong Zhe Sun
- Centre for Atmospheric Science, Yusuf Hamied Department of Chemistry, University of Cambridge, Cambridge CB2 1EW, UK; Department of Earth Sciences, University of Cambridge, Cambridge CB2 3EQ, UK
| | - Keyang Liu
- Public Health, Department of Social Medicine, Osaka University Graduate School of Medicine, Suita Shi, Osaka, Japan
| | - Kokoro Shirai
- Public Health, Department of Social Medicine, Osaka University Graduate School of Medicine, Suita Shi, Osaka, Japan
| | - Kejia Hu
- Institute of Big Data in Health Science, School of Public Health, Zhejiang University, Hangzhou 310058, China
| | - Chengxuan Qiu
- Aging Research Center, Karolinska Institutet, Widerströmska Huset, SE-171 65 Solna, Sweden
| | - Xiaoyun Liu
- China Center for Health Development Studies, Peking University, Beijing, China
| | - Yachen Li
- Institute of Social Development and Health Management, Hubei Province Key Laboratory of Occupational Hazard Identification and Control, School of Public Health, Wuhan University of Science and Technology, Wuhan 430065, China
| | - Yi Zeng
- Center for Healthy Aging and Development Studies, National School of Development, Peking University, Beijing, China; Center for the Study of Aging and Human Development and Geriatrics Division, Medical School of Duke University, Durham, NC, US.
| | - Yao Yao
- China Center for Health Development Studies, Peking University, Beijing, China; Center for Healthy Aging and Development Studies, National School of Development, Peking University, Beijing, China.
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Mazeli MI, Pahrol MA, Abdul Shakor AS, Kanniah KD, Omar MA. Cardiovascular, respiratory and all-cause (natural) health endpoint estimation using a spatial approach in Malaysia. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 874:162130. [PMID: 36804978 DOI: 10.1016/j.scitotenv.2023.162130] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/07/2022] [Revised: 01/14/2023] [Accepted: 02/05/2023] [Indexed: 06/18/2023]
Abstract
In 2016, the World Health Organization (WHO) estimated that approximately 4.2 million premature deaths worldwide were attributable to exposure to particulate matter 2.5 μm (PM2.5). This study assessed the environmental burden of disease attributable to PM2.5 at the national level in Malaysia. We estimated the population-weighted exposure level (PWEL) of PM10 concentrations in Malaysia for 2000, 2008, and 2013 using aerosol optical density (AOD) data from publicly available remote sensing satellite data (MODIS Terra). The PWEL was then converted to PM2.5 using Malaysia's WHO ambient air conversion factor. We used AirQ+ 2.0 software to calculate all-cause (natural), ischemic heart disease (IHD), stroke, chronic obstructive pulmonary disease (COPD), lung cancer (LC), and acute lower respiratory infection (ALRI) excess deaths from the National Burden of Disease data for 2000, 2008 and 2013. The average PWELs for annual PM2.5 for 2000, 2008, and 2013 were 22 μg m-3, 18 μg m-3 and 24 μg m-3, respectively. Using the WHO 2005 Air Quality Guideline cut-off point of PM2.5 of 10 μg m-3, the estimated excess deaths for 2000, 2008, and 2013 from all-cause (natural) mortality were between 5893 and 9781 (95 % CI: 3347-12,791), COPD was between 164 and 957 (95 % CI: 95-1411), lung cancer was between 109 and 307 (95 % CI: 63-437), IHD was between 3 and 163 deaths, according to age groups (95 % CI: 2-394) and stroke was between 6 and 155 deaths, according to age groups (95 % CI: 3-261). An increase in estimated health endpoints was associated with increased estimated PWEL PM2.5 for 2013 compared to 2000 and 2008. Adhering the ambient PM2.5 level to the Malaysian Air Quality Standard IT-2 would reduce the national health endpoints mortality.
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Affiliation(s)
- Mohamad Iqbal Mazeli
- Environmental Health Research Centre, Institute for Medical Research, National Institute of Health Malaysia, Ministry of Health Malaysia, 40170 Shah Alam, Selangor Darul Ehsan, Malaysia.
| | - Muhammad Alfatih Pahrol
- Environmental Health Research Centre, Institute for Medical Research, National Institute of Health Malaysia, Ministry of Health Malaysia, 40170 Shah Alam, Selangor Darul Ehsan, Malaysia.
| | - Ameerah Su'ad Abdul Shakor
- Environmental Health Research Centre, Institute for Medical Research, National Institute of Health Malaysia, Ministry of Health Malaysia, 40170 Shah Alam, Selangor Darul Ehsan, Malaysia.
| | - Kasturi Devi Kanniah
- Faculty of Built Environment and Surveying, Universiti Teknologi Malaysia, 81310 Johor Bahru, Johor, Malaysia; Centre for Environmental Sustainability and Water Security (IPASA), Research Institute for Sustainable Environment (RISE), Universiti Teknologi Malaysia, 81310 Johor Bahru, Johor, Malaysia.
| | - Mohd Azahadi Omar
- Sector for Biostatistics and Data Repository, Office of NIH Manager, National Institute of Health Malaysia, Ministry of Health Malaysia, 40170 Shah Alam, Selangor Darul Ehsan, Malaysia.
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Downward GS, Vermeulen R. Ambient Air Pollution and All-Cause and Cause-Specific Mortality in an Analysis of Asian Cohorts. Res Rep Health Eff Inst 2023; 2016:1-53. [PMID: 37424069 PMCID: PMC7266370] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/11/2023] Open
Abstract
INTRODUCTION Much of what is currently known about the adverse effects of ambient air pollution comes from studies conducted in high-income regions, with relatively low air pollution levels. The aim of the current project is to examine the relationship between exposure to ambient air pollution (as predicted from satellite-based models) and all-cause and cause-specific mortality in several Asian cohorts. METHODS Cohorts were recruited from the Asia Cohort Consortium (ACC). The geocoded residences of participants were assigned levels of ambient particulate material with aerodynamic diameter of 2.5 μm or less (PM2.5) and nitrogen dioxide (NO2) utilizing global satellite-derived models and assigned for the year of enrollment (or closest available year). The association between ambient exposure and mortality was established with Cox proportional hazard models, after adjustment for common confounders. Both single- and two-pollutant models were generated. Model robustness was evaluated, and hazard ratios were calculated for each cohort separately and combined via random effect meta-analysis for pooled risk estimates. RESULTS Six cohort studies from the ACC participated: the Community-based Cancer Screening Program (CBCSCP, Taiwan), the Golestan Cohort Study (Iran), the Health Effects for Arsenic Longitudinal Study (HEALS, Bangladesh), the Japan Public Health Center-based Prospective Study (JPHC), the Korean Multi-center Cancer Cohort Study (KMCC), and the Mumbai Cohort Study (MCS, India). The cohorts represented over 340,000 participants. Mean exposures to PM2.5 ranged from 8 to 58 μg/m3. Mean exposures to NO2 ranged from 7 to 23 ppb. For PM2.5, a positive, borderline nonsignificant relationship was observed between PM2.5 and cardiovascular mortality. Other relationships with PM2.5 tended toward the null in meta-analysis. For NO2, an overall positive relationship was observed between exposure to NO2 and all cancers and lung cancer. A borderline association between NO2 and nonmalignant lung disease was also observed. The findings within individual cohorts remained consistent across a variety of subgroups and alternative analyses, including two-pollutant models. CONCLUSIONS In a pooled examination of cohort studies across Asia, ambient PM2.5 exposure appears to be associated with an increased risk of cardiovascular mortality and ambient NO2 exposure is associated with an increased cancer (and lung cancer) mortality. This project has shown that satellite-derived models of pollution can be used in examinations of mortality risk in areas with either incomplete or missing air pollution monitoring.
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Affiliation(s)
- G S Downward
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, the Netherlands
- Institute for Risk Assessment Sciences, Utrecht University, the Netherlands
| | - R Vermeulen
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, the Netherlands
- Institute for Risk Assessment Sciences, Utrecht University, the Netherlands
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Zhang Y, Wang Y, Du Z, Chen S, Qu Y, Hao C, Ju X, Lin Z, Wu W, Xiao J, Chen X, Lin X, Chen S, Chen L, Jiang J, Zhang W, Hao Y. Potential causal links between long-term ambient particulate matter exposure and cardiovascular mortality: New evidence from a large community-based cohort in South China. ECOTOXICOLOGY AND ENVIRONMENTAL SAFETY 2023; 254:114730. [PMID: 36905844 DOI: 10.1016/j.ecoenv.2023.114730] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/20/2022] [Revised: 03/01/2023] [Accepted: 03/03/2023] [Indexed: 06/18/2023]
Abstract
BACKGROUND Cardiovascular disease (CVD) mortality is associated with long-term particulate matter (PM) exposure. However, evidence from large, highly-exposed population cohort and observational-data-based causal inference approaches remains limited. AIMS We examined the potential causal links between PM exposure and the CVD mortality in South China. METHODS 580,757 participants were recruited during 2009-2015 and followed up through 2020. Satellite-based annual concentrations of PM2.5, PM10, and PMcoarse (i.e., PM10 - PM2.5) at 1 km2 spatial resolution were estimated and assigned to each participant. Marginal structural Cox models with time-varying covariates, adjusted using inverse probability weighting, were developed to evaluate the association between prolonged PM exposure and CVD mortality. RESULTS For overall CVD mortality, the hazard ratios and 95% confidence interval for each 1 μg/m3 increase in the annual average concentration of PM2.5, PM10, and PMcoarse were 1.033 (1.028-1.037), 1.028 (1.024-1.032), and 1.022 (1.012-1.033), respectively. All three PMs were linked to a higher mortality risk for myocardial infarction and ischemic heart disease (IHD). The mortality risk of chronic IHD and hypertension was linked to PM2.5 and PM10. Significant association between PMcoarse and other heart disease mortality was also observed. The older, women, less-educated participants, or inactive participants exhibited particularly higher susceptibility. Participants who were generally exposed to PM10 concentrations below 70 μg/m3 were more vulnerable to PM2.5-, PM10- and PMcoarse-CVD mortality risks. CONCLUSION This large cohort study provides evidence for the potential causal links between increased CVD mortality and ambient PM exposure, as well as socio-demographics linked to the highest vulnerability.
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Affiliation(s)
- 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
| | - Ying Wang
- Department of Medical Statistics, School of Public Health & Center for Health Information Research & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, China
| | - Zhicheng Du
- Department of Medical Statistics, School of Public Health & Center for Health Information Research & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, China
| | - 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
| | - Yanji Qu
- Global Health Research Center, Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, China
| | - 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
| | - Xu Ju
- Department of Medical Statistics, School of Public Health & Center for Health Information Research & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, China
| | - Ziqiang Lin
- Department of Preventive Medicine, School of Basic Medicine and Public Health, Jinan 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
| | - Jianpeng Xiao
- Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China
| | - Xiuyuan 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
| | - Xiao Lin
- Department of Medical Statistics, School of Public Health & Center for Health Information Research & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, China
| | - Shimin 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
| | - Lichang 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
| | - Jie Jiang
- Peking University Center for Public Health and Epidemic Preparedness & Response, Peking, China
| | - Wangjian Zhang
- Department of Medical Statistics, School of Public Health & Center for Health Information Research & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, China.
| | - Yuantao Hao
- Peking University Center for Public Health and Epidemic Preparedness & Response, Peking, China.
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25
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Yang T, Wang J, Huang J, Kelly FJ, Li G. Long-term Exposure to Multiple Ambient Air Pollutants and Association With Incident Depression and Anxiety. JAMA Psychiatry 2023; 80:305-313. [PMID: 36723924 PMCID: PMC10077109 DOI: 10.1001/jamapsychiatry.2022.4812] [Citation(s) in RCA: 103] [Impact Index Per Article: 51.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/31/2022] [Accepted: 11/18/2022] [Indexed: 02/02/2023]
Abstract
Importance Air pollution is increasingly recognized as an important environmental risk factor for mental health. However, epidemiologic evidence on long-term exposure to low levels of air pollutants with incident depression and anxiety is still very limited. Objectives To investigate the association of long-term joint exposure to multiple air pollutants with incident depression and anxiety. Design, Setting, and Participants This prospective, population-based cohort study used data from the UK Biobank. The participants were recruited between March 13, 2006, and October 1, 2010, and included individuals who had never been diagnosed with depression or anxiety at baseline and had full information on exposure and covariates. Data were analyzed from May 1 to October 10, 2022. Exposures Annual mean air pollution concentrations of particulate matter (PM) with aerodynamic diameter of 2.5 μm or less (PM2.5) and PM with aerodynamic diameter between 2.5 μm and 10 μm (PM2.5-10). Nitrogen dioxide (NO2) and nitric oxide (NO) were estimated for each participant's residential address using the land use regression model, and joint exposure to air pollution reflected by air pollution score was calculated by principal components analysis. Main Outcomes and Measures Incidence of diagnosed depression (F32-F33) and anxiety (F40-F48) were ascertained with International Statistical Classification of Diseases and Related Health Problems, Tenth Revision codes. Results During a median (IQR) follow-up of 10.9 (10.1-11.6) years, among 389 185 participants (mean [SD] age, 56.7 [8.1] years, 205 855 female individuals [52.9%]), a total of 13 131 and 15 835 patients were diagnosed with depression and anxiety, respectively. The median (IQR) concentration of pollutants was as follows: PM2.5, 9.9 (9.3-10.6) μg/m3; PM2.5-10, 6.1 (5.8-6.6) μg/m3; NO2, 26.0 (21.3-31.1) μg/m3; and NO, 15.9 (11.6-20.6) μg/m3. Long-term estimated exposure to multiple air pollutants was associated with increased risk of depression and anxiety, and the exposure-response curves were nonlinear, with steeper slopes at lower concentrations and plateauing trends at higher exposure. The hazard ratios (HRs) and 95% CIs for depression and anxiety were 1.16 (95% CI, 1.09-1.23; P < .001) and 1.11 (95% CI, 1.05-1.17; P < .001) in the highest quartile compared with the lowest quartile of air pollution score, respectively. Similar trends were shown for PM2.5, NO2, and NO. Subgroup analysis showed the association between PM2.5 and anxiety tended to be higher in male individuals than in female individuals (quartile 4: male individuals, 1.18; 95% CI, 1.08-1.29; female individuals, 1.07; 95% CI, 1.00-1.14; P = .009). Conclusions and Relevance Study results suggest that estimates of long-term exposure to multiple air pollutants was associated with increased risk of depression and anxiety. The nonlinear associations may have important implications for policy making in air pollution control. Reductions in joint exposure to multiple air pollutants may alleviate the disease burden of depression and anxiety.
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Affiliation(s)
- Teng Yang
- Department of Occupational and Environmental Health Sciences, Peking University School of Public Health, Beijing, China
| | - Jiawei Wang
- Department of Occupational and Environmental Health Sciences, Peking University School of Public Health, Beijing, China
| | - Jing Huang
- Department of Occupational and Environmental Health Sciences, Peking University School of Public Health, Beijing, China
- Deep Medicine, Nuffield Department of Women’s and Reproductive Health, University of Oxford, Oxford, United Kingdom
| | - Frank J. Kelly
- Environmental Research Group, Faculty of Medicine, School of Public Health, Imperial College London, London, United Kingdom
| | - Guoxing Li
- Department of Occupational and Environmental Health Sciences, Peking University School of Public Health, Beijing, China
- Environmental Research Group, Faculty of Medicine, School of Public Health, Imperial College London, London, United Kingdom
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26
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Wang Y, Du Z, Zhang Y, Chen S, Lin S, Hopke PK, Rich DQ, Zhang K, Romeiko XX, Deng X, Qu Y, Liu Y, Lin Z, Zhu S, Zhang W, Hao Y. Long-term exposure to particulate matter and COPD mortality: Insights from causal inference methods based on a large population cohort in southern China. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 863:160808. [PMID: 36502970 DOI: 10.1016/j.scitotenv.2022.160808] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/18/2022] [Revised: 11/17/2022] [Accepted: 12/05/2022] [Indexed: 06/17/2023]
Abstract
BACKGROUND Evidence of the association between long-term exposure to particulate matter (PM) and chronic obstructive pulmonary disease (COPD) mortality from large population-based cohort study is limited and often suffers from residual confounding issues with traditional statistical methods. We hereby assessed the casual relationship between long-term PM (PM2.5, PM10 and PM10-2.5) exposure and COPD mortality in a large cohort of Chinese adults using state-of-the-art causal inference approaches. METHODS A total of 580,757 participants in southern China were enrolled in a prospective cohort study from 2009 to 2015 and followed up until December 2020. Exposures to PM at each residential address were obtained from the Long-term Gap-free High-resolution Air Pollutant Concentration dataset. Marginal structural Cox models were used to investigate the association between COPD mortality and annual average exposure levels of PM exposure. RESULTS During an average follow-up of 8.0 years, 2250 COPD-related deaths occurred. Under a set of causal inference assumptions, the hazard ratio (HR) for COPD mortality was estimated to be 1.046 (95 % confidence interval: 1.034-1057), 1.037 (1.028-1.047), and 1.032 (1.006-1.058) for each 1-μg/m3 increase in annual average concentrations of PM2.5, PM10, and PM10-2.5 respectively. Additionally, the detrimental effects appeared to be more pronounced among the elderly (age ≥ 65) and inactive participants. The effect estimates of PM2.5, PM10, and PM10-2.5 tend to be greater among participants who were generally exposed to PM10 concentrations below 70 μg/m3 than that among the general population. CONCLUSION Our results support causal links between long-term PM exposure and COPD mortality, highlighting the urgency for more effective strategies to reduce PM exposure, with particular attention on protecting potentially vulnerable groups.
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Affiliation(s)
- Ying Wang
- Department of Medical Statistics, School of Public Health & Center for Health Information Research & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, China
| | - Zhicheng Du
- Department of Medical Statistics, School of Public Health & Center for Health Information Research & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, China
| | - 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
| | - 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
| | - Shao Lin
- Department of Environmental Health Sciences, School of Public Health, University at Albany, the State University of New York, Rensselaer, NY, USA
| | - Philip K Hopke
- Institute for a Sustainable Environment, Clarkson University, Potsdam, NY, USA; Department of Public Health Sciences, University of Rochester Medical Center, Rochester, NY, USA
| | - David Q Rich
- Department of Public Health Sciences, University of Rochester Medical Center, Rochester, NY, USA
| | - Kai Zhang
- Department of Environmental Health Sciences, School of Public Health, University at Albany, the State University of New York, Rensselaer, NY, USA
| | - Xiaobo X Romeiko
- Department of Environmental Health Sciences, School of Public Health, University at Albany, the State University of New York, Rensselaer, NY, USA
| | - Xinlei Deng
- Department of Environmental Health Sciences, School of Public Health, University at Albany, the State University of New York, Rensselaer, NY, USA
| | - Yanji Qu
- Department of Cardiovascular Epidemiology, Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital & Guangdong Academy of Medical Sciences, Guangzhou, China
| | - Yu Liu
- 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 Psychiatry, New York University School of Medicine, NY, USA
| | - Shuming Zhu
- 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
| | - 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.
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27
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Alexeeff SE, Deosaransingh K, Van Den Eeden S, Schwartz J, Liao NS, Sidney S. Association of Long-term Exposure to Particulate Air Pollution With Cardiovascular Events in California. JAMA Netw Open 2023; 6:e230561. [PMID: 36826819 PMCID: PMC9958530 DOI: 10.1001/jamanetworkopen.2023.0561] [Citation(s) in RCA: 30] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/21/2022] [Accepted: 12/27/2022] [Indexed: 02/25/2023] Open
Abstract
Importance Long-term exposure to fine particulate air pollution (PM2.5) is a known risk factor for cardiovascular events, but controversy remains as to whether the current National Ambient Air Quality Standard (12 μg/m3 for 1-year mean PM2.5) is sufficiently protective. Objective To evaluate the associations between long-term fine particulate air pollution and cardiovascular events using electronic health record and geocoded address data. Design, Setting, and Participants This retrospective cohort study included adults in the Kaiser Permanente Northern California integrated health care system during 2007 to 2016 and followed for up to 10 years. Study participants had no prior stroke or acute myocardial infarction (AMI), and lived in Northern California for at least 1 year. Analyses were conducted January 2020 to December 2022. Exposure Long-term exposure to PM2.5. Individual-level time-varying 1-year mean PM2.5 exposures for every study participant were updated monthly from baseline through the end of follow-up, accounting for address changes. Main Outcomes and Measures Incident AMI, ischemic heart disease (IHD) mortality, and cardiovascular disease (CVD) mortality. Cox proportional hazards models were fit with age as time scale, adjusted for sex, race and ethnicity, socioeconomic status, smoking, body mass index, baseline comorbidities, and baseline medication use. Associations below the current regulation limit were also examined. Results The study cohort included 3.7 million adults (mean [SD] age: 41.1 [17.2] years; 1 992 058 [52.5%] female, 20 205 [0.5%] American Indian or Alaskan Native, 714 043 [18.8%] Asian, 287 980 [7.6%] Black, 696 796 [18.4%] Hispanic, 174 261 [4.6%] multiracial, 1 904 793 [50.2%] White). There was a 12% (95% CI, 7%-18%) increased risk of incident AMI, a 21% (95% CI, 13%-30%) increased risk of IHD mortality, and an 8% (95% CI, 3%-13%) increased risk of CVD mortality associated with a 10 μg/m3 increase in 1-year mean PM2.5. PM2.5 exposure at moderate concentrations (10.0 to 11.9 μg/m3) was associated with increased risks of incident AMI (6% [95% CI, 3%-10%]) and IHD mortality (7% [95% CI, 2%-12%]) compared with low concentrations (less than 8 μg/m3). Conclusions and Relevance In this study, long-term PM2.5 exposure at moderate concentrations was associated with increased risks of incident AMI, IHD mortality, and CVD mortality. This study's findings add to the evidence that the current regulatory standard is not sufficiently protective.
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Affiliation(s)
| | | | | | - Joel Schwartz
- Harvard T.H. Chan School of Public Health, Boston, Massachusetts
| | - Noelle S. Liao
- Kaiser Permanente Division of Research, Oakland, California
| | - Stephen Sidney
- Kaiser Permanente Division of Research, Oakland, California
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Chung CY, Yang J, Yang X, He J. A novel mathematical model for estimating the relative risk of mortality attributable to the combined effect of ambient fine particulate matter (PM 2.5) and cold ambient temperature. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 858:159634. [PMID: 36280065 DOI: 10.1016/j.scitotenv.2022.159634] [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: 08/22/2022] [Revised: 10/17/2022] [Accepted: 10/18/2022] [Indexed: 06/16/2023]
Abstract
Exposures to ambient fine particulate matter (PM2.5) and cold ambient temperatures have been identified as important risk factors in contributing towards the global mortality from chronic obstructive pulmonary disease (COPD). Despite China currently being the country with the largest population in the world, previous relative risk (RR) models have considered little or no information from the ambient air pollution related cohort studies in the country. This likely provides a less accurate picture of the trend in air pollution attributable mortality in the country over time. A novel relative risk model called pollutant-temperature exposure (PTE) model is proposed to estimate the RR attributable to the combined effect of air pollution and ambient temperature in a population. In this paper, the pollutant concentration-response curve was extrapolated from the cohort studies in China, whereas the temperature response curve was extracted from a study in Yangtze River Delta (YRD) region. The performance of the PTE model was compared with the integrated exposure-response (IER) model using the data of YRD region, which revealed that the estimated relative risks of the PTE model were noticeably higher than the IER model during the winter season. Furthermore, the predictive ability of the PTE model was validated using actual data of Ningbo city, which showed that the estimated RR using the PTE model with 1-month moving average data showed a good result with the trend of actual COPD mortality, indicated by a lower root mean square error (RMSE = 0.956). By considering the combined effect of ambient air pollutant and ambient temperature, the PTE model is expected to provide more accurate relative risk estimates for the regions with high levels of ambient PM2.5 and seasonal variation of ambient temperature.
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Affiliation(s)
- Chee Yap Chung
- Department of Chemical and Environmental Engineering, University of Nottingham Ningbo China, Ningbo 315100, PR China
| | - Jie Yang
- Department of Mathematics, University of Hull, Hull HU6 7RX, UK
| | - Xiaogang Yang
- Department of Mechanical, Materials and Manufacturing Engineering, University of Nottingham Ningbo China, Ningbo 315100, PR China.
| | - Jun He
- Department of Chemical and Environmental Engineering, University of Nottingham Ningbo China, Ningbo 315100, PR China
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Thangavel P, Kim KY, Park D, Lee YC. Evaluation of Health Economic Loss Due to Particulate Matter Pollution in the Seoul Subway, South Korea. TOXICS 2023; 11:113. [PMID: 36850988 PMCID: PMC9960099 DOI: 10.3390/toxics11020113] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/19/2022] [Revised: 01/20/2023] [Accepted: 01/21/2023] [Indexed: 06/18/2023]
Abstract
Evaluating an illness's economic impact is critical for developing and executing appropriate policies. South Korea has mandatory national health insurance in the form of NHIS that provides propitious conditions for assessing the national financial burden of illnesses. The purpose of our study is to provide a comprehensive assessment of the economic impact of PM2.5 exposure in the subway and a comparative analysis of cause-specific mortality outcomes based on the prevalent health-risk assessment of the health effect endpoints (chronic obstructive pulmonary disease (COPD), asthma, and ischemic heart disease (IHD)). We used the National Health Insurance database to calculate the healthcare services provided to health-effect endpoints, with at least one primary diagnosis in 2019. Direct costs associated with health aid or medicine, treatment, and indirect costs (calculated based on the productivity loss in health effect endpoint patients, transportation, and caregivers, including morbidity and mortality costs) were both considered. The total cost for the exposed population for these endpoints was estimated to be USD 437 million per year. Medical costs were the largest component (22.08%), followed by loss of productivity and premature death (15.93%) and other costs such as transport and caregiver costs (11.46%). The total incurred costs (per 1000 persons) were accounted to be USD 0.1771 million, USD 0.42 million, and USD 0.8678 million for COPD, Asthma, and IHD, respectively. Given that the economic burden will rise as the prevalence of these diseases rises, it is vital to adopt effective preventative and management methods strategies aimed at the appropriate population.
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Affiliation(s)
- Prakash Thangavel
- Department of BioNano Technology, Gachon University, 1342 Seongnam-daero, Sujeong-gu, Seongnam-si 13120, Gyeonggi-do, Republic of Korea
| | - Kyoung Youb Kim
- Department of Mobile IoT, Osan University, 45 Cheonghak-ro, Osan-si 18119, Gyeonggi-do, Republic of Korea
| | - Duckshin Park
- Korea Railroad Research Institute (KRRI), 176 Cheoldobakmulkwan-ro, Uiwang-si 16105, Gyeonggi-do, Republic of Korea
| | - Young-Chul Lee
- Department of BioNano Technology, Gachon University, 1342 Seongnam-daero, Sujeong-gu, Seongnam-si 13120, Gyeonggi-do, Republic of Korea
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Wang Y, Wei J, Zhang Y, Guo T, Chen S, Wu W, Chen S, Li Z, Qu Y, Xiao J, Deng X, Liu Y, Du Z, Zhang W, Hao Y. Estimating causal links of long-term exposure to particulate matters with all-cause mortality in South China. ENVIRONMENT INTERNATIONAL 2023; 171:107726. [PMID: 36638656 DOI: 10.1016/j.envint.2022.107726] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/27/2022] [Revised: 12/03/2022] [Accepted: 12/29/2022] [Indexed: 06/17/2023]
Abstract
BACKGROUND The association between long-term particulate matter (PM) exposure and all-cause mortality has been well-documented. However, evidence is still limited from high-exposed cohorts, especially for PM1 which is smaller while more toxic than other commonly investigated particles. We aimed to examine the potential casual links of long-term PMs exposure with all-cause mortality in high-exposed areas. METHODS A total of 580,757 participants in southern China were enrolled during 2009-2015 and followed up to 2020. The annual average concentration of PM1, PM2.5, and PM10 at 1 km2 spatial resolution was assessed for each residential address through validated spatiotemporal models. We used marginal structural Cox models to estimate the PM-mortality associations which were further stratified by sociodemographic, lifestyle factors and general exposure levels. RESULTS 37,578 deaths were totally identified during averagely 8.0 years of follow-up. Increased exposure to all 3 PM size fractions were significantly associated with increased risk of all-cause mortality, with hazard ratios (HRs) of 1.042 (95 % confidence interval (CI): 1.037-1.046), 1.031 (95 % CI: 1.028-1.033), and 1.029 (95 % CI: 1.027-1.031) per 1 μg/m3 increase in PM1, PM2.5, and PM10 concentrations, respectively. We observed greater effect estimates among the elderly (age ≥ 65 years), unmarried participants, and those with low education attainment. Additionally, the effect of PM1, PM2.5, and PM10 tend to be higher in the low-exposure group than in the general population. CONCLUSIONS We provided comprehensive evidence for the potential causal links betweenlong-term PM exposureand all-cause mortality, and suggested stronger links for PM1compared to large particles and among certain vulnerable subgroups.
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Affiliation(s)
- Ying Wang
- Department of Medical Statistics, School of Public Health & Center for Health Information Research & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, China
| | - Jing Wei
- Department of Atmospheric and Oceanic Science, Earth System Science Interdisciplinary Center, University of Maryland, College Park, USA
| | - 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
| | - 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
| | - 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
| | - 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
| | - Shimin 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
| | - Ziqiang Li
- Department of Preventive Medicine, School of Basic Medicine and Public Health, Jinan University, Guangzhou, China
| | - Yanji Qu
- Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital, Guangzhou, China
| | - Jianpeng Xiao
- Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China
| | - Xinlei Deng
- Epidemiology Branch, National Institute of Environmental Health Sciences, NIH, Research Triangle Park, NC, USA
| | - Yu Liu
- Department of Medical Statistics, School of Public Health & Center for Health Information Research & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, China
| | - Zhicheng Du
- Department of Medical Statistics, School of Public Health & Center for Health Information Research & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, China.
| | - 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, Beijing, China.
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Peng J, Han H, Yi Y, Huang H, Xie L. Machine learning and deep learning modeling and simulation for predicting PM2.5 concentrations. CHEMOSPHERE 2022; 308:136353. [PMID: 36084831 DOI: 10.1016/j.chemosphere.2022.136353] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/04/2022] [Revised: 08/14/2022] [Accepted: 09/02/2022] [Indexed: 06/15/2023]
Abstract
Particulate matter (PM) pollution greatly endanger human physical and mental health, and it is of great practical significance to predict PM concentrations accurately. This study measured one-year monitoring data of six main meteorological parameters and PM2.5 concentrations independently at two monitoring sites in central China's Hunan Province. These datasets were then employed to train, validate, and evaluate the proposed extreme gradient boosting (XGBoost) machine learning model and the fully connected neural network deep learning model, respectively. The performances of the two models were compared, analyzed, and optimized through model parameter tuning. The XGBoost model had better prediction ability with R2 higher than 0.761 in the complete test dataset. When the complete dataset was divided into stratified sub-sets by daytime-nighttime periods, the value of R2 increased to 0.856 in the nighttime test dataset. The feature importance and influential mechanism of meteorological variables on PM2.5 concentrations were analyzed and discussed.
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Affiliation(s)
- Jian Peng
- School of Minerals Processing and Bioengineering, Central South University, Changsha, 410083, China
| | - Haisheng Han
- School of Minerals Processing and Bioengineering, Central South University, Changsha, 410083, China
| | - Yong Yi
- Atmospheric Environment Monitoring Department, Changsha Environmental Monitoring Centre of Hunan Province, Changsha, 410001, China
| | - Huimin Huang
- Atmospheric Environment Monitoring Department, Changsha Environmental Monitoring Centre of Hunan Province, Changsha, 410001, China
| | - Le Xie
- College of Chemistry and Chemical Engineering, Central South University, Changsha, 410083, China.
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Wang Y, Xiong H, Chen C. Agricultural non-point source pollution and health of the elderly in rural China. PLoS One 2022; 17:e0274027. [PMID: 36240140 PMCID: PMC9565375 DOI: 10.1371/journal.pone.0274027] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2021] [Accepted: 08/20/2022] [Indexed: 11/24/2022] Open
Abstract
Large input and high loss of chemical fertilizer are the major causes of agricultural non-point source pollution in China. Employing fertilizer loss and micro-health data, this paper analyzes the effects of chemical fertilizer loss on the health of rural elderly and the medical cost in China. Results of the difference-in-differences (DID) method indicate that one kg/ha increase in fertilizer loss alters a key medical disability index (Activities of Daily Living) by 0.0147 (0.2 percent changes) and the number of diseases by 0.0057 for rural residents of 65 and older. This is equivalent to CNY 316 million (USD 45 million) at national medical cost. Furthermore, the age of onset is younger in regions with higher fertilizer loss. One kg/ha increase of fertilizer loss advances the age of onset by 0.267 year, which will cause long-term effect on public health. Our results are robust to a variety of robustness checks.
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Affiliation(s)
- Ying Wang
- College of Economics and Management, Nanjing Agricultural University, Nanjing, Jiangsu, P.R.China
| | - Hang Xiong
- College of Economics and Management, Nanjing Agricultural University, Nanjing, Jiangsu, P.R.China
- China Center for Food Security Studies, Nanjing Agricultural University, Nanjing, Jiangsu, P.R.China
| | - Chao Chen
- College of Economics and Management, Nanjing Agricultural University, Nanjing, Jiangsu, P.R.China
- China Center for Food Security Studies, Nanjing Agricultural University, Nanjing, Jiangsu, P.R.China
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Han C, Xu R, Ye T, Xie Y, Zhao Y, Liu H, Yu W, Zhang Y, Li S, Zhang Z, Ding Y, Han K, Fang C, Ji B, Zhai W, Guo Y. Mortality burden due to long-term exposure to ambient PM 2.5 above the new WHO air quality guideline based on 296 cities in China. ENVIRONMENT INTERNATIONAL 2022; 166:107331. [PMID: 35728411 DOI: 10.1016/j.envint.2022.107331] [Citation(s) in RCA: 28] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/15/2021] [Revised: 05/26/2022] [Accepted: 05/30/2022] [Indexed: 05/17/2023]
Abstract
OBJECTIVE Quantifying the spatial and socioeconomic variation of mortality burden attributable to particulate matters with aerodynamic diameter ≤ 2.5 µm (PM2.5) has important implications for pollution control policy. This study aims to examine the regional and socioeconomic disparities in the mortality burden attributable to long-term exposure to ambient PM2.5 in China. METHODS Using data of 296 cities across China from 2015 to 2019, we estimated all-cause mortality (people aged ≥ 16 years) attributable to the long-term exposure to ambient PM2.5 above the new WHO air quality guideline (5 µg/m3). Attributed fraction (AF), attributed deaths (AD), attributed mortality rate (AMR) and total value of statistical life lost (VSL) by regional and socioeconomic levels were reported. RESULTS Over the period of 2015-2019, 17.0% [95% confidence interval (CI): 7.4-25.2] of all-cause mortality were attributable to long-term exposure to ambient PM2.5, corresponding to 1,425.2 thousand deaths (95% CI: 622.4-2,099.6), 103.5/105 (95% CI: 44.9-153.3) AMR, and 1006.9 billion USD (95% CI: 439.8-1483.4) total VSL per year. The AMR decreased from 120.5/105 (95% CI: 52.9-176.6) to 92.7/105 (95% CI:39.9-138.5) from 2015 to 2019. The highest mortality burden was observed in the north region (annual average AF = 24.2%, 95% CI: 10.8-35.1; annual average AMR = 137.0/105, 95% CI: 60.9-198.5). The highest AD and economic loss were observed in the east region (annual average AD = 390.0 thousand persons, 95% CI: 170.3-574.6; annual total VSL = 275.6 billion USD, 95% CI: 120.3-406.0). Highest AMR was in the cities with middle level of GDP per capita (PGDP)/urbanization. The majority of the top ten cities of AF, AMR and VSL were in high and middle PGDP/urbanization regions. CONCLUSION There were significant regional and socioeconomic disparities in PM2.5 attributed mortality burden among Chinese cities, suggesting differential mitigation policies are required for different regions in China.
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Affiliation(s)
- Chunlei Han
- School of Public Health and Management, Binzhou Medical University, Yantai, Shandong Province 264003, PR China
| | - Rongbin Xu
- School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC 3004, Australia
| | - Tingting Ye
- School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC 3004, Australia
| | - Yang Xie
- School of Economics and Management, Beihang University, Beijing 100191, PR China; Key Laboratory of Big Data-Based Precision Medicine, Ministry of Industry and Information Technology, Beihang University, Beijing 100191, PR China
| | - Yang Zhao
- The George Institute for Global Health at Peking University Health Science Center, Beijing 100600, PR China; WHO Collaborating Centre on Implementation Research for Prevention & Control of NCDs, VIC 3010, Australia
| | - Haiyun Liu
- Yantai Center for Disease Control and Prevention, Yantai, Shandong 264003, PR China
| | - Wenhua Yu
- School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC 3004, Australia
| | - Yajuan Zhang
- School of Public Health and Management, Ningxia Medical University, Yinchuan, Ningxia Hui Autonomous Region 750004, PR China
| | - Shanshan Li
- School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC 3004, Australia
| | - Zhongwen Zhang
- School of Public Health and Management, Binzhou Medical University, Yantai, Shandong Province 264003, PR China
| | - Yimin Ding
- School of Software, Tongji University, Shanghai 200092, PR China
| | - Kun Han
- GuotaiJunan Securities, Shanghai 200030, PR China; School of Economics, Fudan University, Shanghai 200433, PR China
| | - Chang Fang
- School of Public Health, Haerbin Medical University, Harbin, Heilongjiang 150081, PR China
| | - Baocheng Ji
- Linyi Municipal Ecology and Environment Bureau, Linyi, Shandong 276000, PR China
| | - Wenhui Zhai
- College of Mathematics and Physics, Beijing University of Chemical Technology, Beijing 100029, PR China
| | - Yuming Guo
- School of Public Health and Management, Binzhou Medical University, Yantai, Shandong Province 264003, PR China; School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC 3004, Australia.
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Colonna KJ, Koutrakis P, Kinney PL, Cooke RM, Evans JS. Mortality Attributable to Long-Term Exposure to Ambient Fine Particulate Matter: Insights from the Epidemiologic Evidence for Understudied Locations. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2022; 56:6799-6812. [PMID: 35442648 DOI: 10.1021/acs.est.1c08343] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/17/2023]
Abstract
Epidemiologic cohort studies have consistently demonstrated that long-term exposure to ambient fine particles (PM2.5) is associated with mortality. Nevertheless, extrapolating results to understudied locations may involve considerable uncertainty. To explore this issue, this review discusses the evidence for (i) the associated risk of mortality, (ii) the shape of the concentration-response function, (iii) a causal interpretation, and (iv) how the source mix/composition of PM2.5 and population characteristics may alter the effect. The accumulated evidence suggests the following: (i) In the United States, the change in all-cause mortality risk per μg/m3 is about 0.8%. (ii) The concentration-response function appears nonlinear. (iii) Causation is overwhelmingly supported. (iv) Fossil fuel combustion-related sources are likely more toxic than others, and age, race, and income may modify the effect. To illustrate the use of our findings in support of a risk assessment in an understudied setting, we consider Kuwait. However, given the complexity of this relationship and the heterogeneity in reported effects, it is unreasonable to think that, in such circumstances, point estimates can be meaningful. Consequently, quantitative probabilistic estimates, which cannot be derived objectively, become essential. Formally elicited expert judgment can provide such estimates, and this review provides the evidence to support an elicitation.
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Affiliation(s)
- Kyle J Colonna
- Department of Environmental Health, Harvard University T.H. Chan School of Public Health, Boston, Massachusetts 02115, United States
| | - Petros Koutrakis
- Department of Environmental Health, Harvard University T.H. Chan School of Public Health, Boston, Massachusetts 02115, United States
| | - Patrick L Kinney
- Department of Environmental Health, Boston University School of Public Health, Boston, Massachusetts 02118, United States
| | - Roger M Cooke
- Resources for the Future, Washington, DC 20036, United States
- Department of Mathematics, Delft University of Technology, Delft, NL 2628 XE, Netherlands
| | - John S Evans
- Department of Environmental Health, Harvard University T.H. Chan School of Public Health, Boston, Massachusetts 02115, United States
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Guo C, Yu T, Bo Y, Lin C, Chang LY, Wong MCS, Yu Z, Lau AKH, Tam T, Lao XQ. Long-term Exposure to Fine Particulate Matter and Mortality A Longitudinal Cohort Study of 400,459 Adults. Epidemiology 2022; 33:309-317. [PMID: 35067568 DOI: 10.1097/ede.0000000000001464] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Abstract
BACKGROUND Cohort studies on the association between long-term exposure to fine particulate matter (PM2.5) and mortality have been well established for America and Europe, but limited and inconsistent in Asia with much higher air pollution. This study aims to investigate the associations between ambient PM2.5 and all-cause and cause-specific mortality over a period of rising and then declining PM2.5. METHODS We enrolled a total of 400,459 adults from an open cohort between 2001 and 2016, and followed them up until 31 May 2019. We obtained mortality data from the National Death Registry maintained by the Ministry of Health and Welfare in Taiwan. We estimated ambient PM2.5 exposures using a satellite-based spatiotemporal model. We performed a Cox regression model with time-dependent covariates to investigate the associations of PM2.5 with deaths from all causes and specific causes. RESULTS This study identified 14,627 deaths and had a total of 5 million person-years of follow-up. Each 10 µg/m3 increase in PM2.5 was associated with an increased hazard risk of 29% (95% confidence interval: 24%-35%) in all-cause mortality. Risk of death increased by 30% for natural causes, 20% for cancer, 42% for cardiovascular disease (CVD) causes, and 53% for influenza and pneumonia causes, for each 10 µg/m3 increase in PM2.5. Sensitivity analyses generally yielded similar results. CONCLUSION Long-term exposure to ambient PM2.5 was associated with increased risks of all-cause mortality and deaths from cancers, natural causes, CVD, and influenza and pneumonia. Longitudinal study design should be encouraged for air pollution epidemiologic investigation.
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Affiliation(s)
- Cui Guo
- From the Jockey Club School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong SAR, China
| | - Tsung Yu
- Department of Public Health, National Cheng Kung University, Tainan, Taiwan
| | - Yacong Bo
- From the Jockey Club School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong SAR, China
| | - Changqing Lin
- Division of Environment and Sustainability, The Hong Kong University of Science and Technology, Hong Kong SAR, China
| | | | - Martin C S Wong
- From the Jockey Club School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong SAR, China
- The School of Public Health, The Chinese Academy of Medical Sciences and Peking Union Medical Colleges, Beijing, China
- The School of Public Health, The Peking University, Beijing, China
| | - Zengli Yu
- Department of Nutrition and Food Hygiene, School of Public Health, Zhengzhou University, Henan, China
| | - Alexis K H Lau
- Division of Environment and Sustainability, The Hong Kong University of Science and Technology, Hong Kong SAR, China
- Department of Civil and Environmental Engineering, The Hong Kong University of Science and Technology, Hong Kong SAR, China
| | - Tony Tam
- Department of Sociology, the Chinese University of Hong Kong, Hong Kong
| | - Xiang Qian Lao
- From the Jockey Club School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong SAR, China
- Shenzhen Research Institute of the Chinese University of Hong Kong, Shenzhen, China
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36
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Zhang J, Wang X, Yan M, Shan A, Wang C, Yang X, Tang N. Sex Differences in Cardiovascular Risk Associated With Long-Term PM 2.5 Exposure: A Systematic Review and Meta-Analysis of Cohort Studies. Front Public Health 2022; 10:802167. [PMID: 35186842 PMCID: PMC8847390 DOI: 10.3389/fpubh.2022.802167] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2021] [Accepted: 01/11/2022] [Indexed: 12/30/2022] Open
Abstract
Background Established evidence suggests risks of developing cardiovascular disease are different by sex. However, it remains unclear whether associations of PM2.5 with cardiovascular risk are comparable between women and men. The meta-analysis aimed to examine sex differences in associations of ischemic heart disease (IHD) and stroke with long-term PM2.5 exposure. Methods PubMed, EMBASE and Cochrane Library were searched until May 2, 2021. We included cohort studies reporting sex-specific associations of long-term PM2.5 exposure (e.g., ≥1 year) with IHD and stroke. The primary analysis was to estimate relative risk (RR) of PM2.5-outcome in women and men separately, and the additional women-to-men ratio of RR (RRR) was explored to compare sex differences, using random-effect models. Results We identified 25 eligible studies with 3.6 million IHD and 1.3 million stroke cases among 63.7 million participants. A higher level of PM2.5 exposure was significantly associated with increased risk of IHD in both women (RR = 1.21; 95% CI, 1.15–1.27) and men (RR = 1.12; 95% CI, 1.07–1.17). The women-to-men RRR of IHD was 1.05 (95% CI, 1.02–1.08) per 10 μg/m3 increment in PM2.5 exposure, indicating significant excess risk of IHD in women. The significant risks of stroke associated with PM2.5 were obtained in both women (RR = 1.11; 95% CI, 1.08–1.13) and men (RR = 1.11; 95% CI, 1.07–1.14), but no significant women-to-men RRR was observed in stroke (RRR = 1.00; 95% CI, 0.96–1.04). Conclusions The study identified excess risk of IHD associated with long-term PM2.5 exposure in women. The findings would not only have repercussions on efforts to precisely evaluate the burden of IHD attributable to PM2.5, but would also provide novel clues for cardiovascular risk prevention accounting for sex-based differences.
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Affiliation(s)
- Jia Zhang
- Institute of Epidemiology and Health Statistics, School of Public Health, Lanzhou University, Lanzhou, China.,Department of Occupational and Environmental Health, School of Public Health, Tianjin Medical University, Tianjin, China
| | - Xinyan Wang
- Center for Reproductive Medicine, Tianjin Central Hospital of Obstetrics and Gynecology, Tianjin, China
| | - Mengfan Yan
- Department of Occupational and Environmental Health, School of Public Health, Tianjin Medical University, Tianjin, China.,Tianjin Key Laboratory of Environment, Nutrition and Public Health, Tianjin, China
| | - Anqi Shan
- Department of Occupational and Environmental Health, School of Public Health, Tianjin Medical University, Tianjin, China.,Tianjin Key Laboratory of Environment, Nutrition and Public Health, Tianjin, China
| | - Chao Wang
- Department of Epidemiology and Biostatistics, Beijing Research Institute of Traumatology and Orthopaedics, Beijing Jishuitan Hospital, Beijing, China.,Department of Molecular Orthopaedics, Beijing Research Institute of Traumatology and Orthopaedics, Beijing Jishuitan Hospital, Beijing, China
| | - Xueli Yang
- Department of Occupational and Environmental Health, School of Public Health, Tianjin Medical University, Tianjin, China.,Tianjin Key Laboratory of Environment, Nutrition and Public Health, Tianjin, China
| | - Naijun Tang
- Department of Occupational and Environmental Health, School of Public Health, Tianjin Medical University, Tianjin, China.,Tianjin Key Laboratory of Environment, Nutrition and Public Health, Tianjin, China
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Burnett RT, Spadaro JV, Garcia GR, Pope CA. Designing health impact functions to assess marginal changes in outdoor fine particulate matter. ENVIRONMENTAL RESEARCH 2022; 204:112245. [PMID: 34687750 DOI: 10.1016/j.envres.2021.112245] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/06/2021] [Revised: 10/17/2021] [Accepted: 10/17/2021] [Indexed: 06/13/2023]
Abstract
Estimating health benefits from improvements in ambient air quality requires the characterization of the magnitude and shape of the association between marginal changes in exposure and marginal changes in risk, and its uncertainty. Several attempts have been made to do this, each requiring different assumptions. These include the Log-Linear(LL), IntegratedExposure-Response(IER), and GlobalExposureMortalityModel(GEMM). In this paper we develop an improved relative risk model suitable for use in health benefits analysis that incorporates features of existing models while addressing limitations in each model. We model the derivative of the relative risk function within a meta-analytic framework; a quantity directly applicable to benefits analysis, incorporating a Fusion of algebraic functions used in previous models. We assume a constant derivative in concentration over low exposures, like the LL model, a declining derivative over moderate exposures observed in cohort studies, and a derivative declining as the inverse of concentration over high global exposures in a similar manner to the GEMM. The model properties are illustrated with examples of fitting it to data for the six specific causes of death previously examined by the GlobalBurdenofDisease program with ambient fine particulate matter (PM2.5). In a test case analysis assuming a 1% (benefits analysis) or 100% (burden analysis), reduction in country-specific fine particulate matter concentrations, corresponding estimated global attributable deaths using the Fusion model were found to lie between those of the IER and LL models, with the GEMM estimates similar to those based on the LL model.
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Affiliation(s)
- Richard T Burnett
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, 98195, USA.
| | - Joseph V Spadaro
- Spadaro Environmental Research Consultants (SERC), Philadelphia, PA, 19142, USA
| | - George R Garcia
- School of Law, Stanford University, Palo Alto, CA, 94305, USA
| | - C Arden Pope
- Department of Economics, Brigham Young University, Provo, UT, 84602, USA
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Jin JQ, Han D, Tian Q, Chen ZY, Ye YS, Lin QX, Ou CQ, Li L. Individual exposure to ambient PM 2.5 and hospital admissions for COPD in 110 hospitals: a case-crossover study in Guangzhou, China. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2022; 29:11699-11706. [PMID: 34545525 PMCID: PMC8794997 DOI: 10.1007/s11356-021-16539-x] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/12/2021] [Accepted: 09/10/2021] [Indexed: 05/22/2023]
Abstract
Few studies have evaluated the short-term association between hospital admissions and individual exposure to ambient particulate matter (PM2.5). Particularly, no studies focused on hospital admissions for chronic obstructive pulmonary disease (COPD) at the individual level. We assessed the short-term effects of PM2.5 on hospitalization admissions for COPD in Guangzhou, China, during 2014-2015, based on satellite-derived estimates of ambient PM2.5 concentrations at a 1-km resolution near the residential address as individual-level exposure for each patient. Around 40,002 patients with COPD admitted to 110 hospitals were included in this study. A time-stratified case-crossover design with conditional logistic regression models was applied to assess the effects of PM2.5 based on a 1-km grid data of aerosol optical depth provided by the National Aeronautics and Space Administration on hospital admissions for COPD. Further, we performed stratified analyses by individual demographic characteristics and season of hospital admission. Around 10 μg/m3 increase in individual-level PM2.5 was associated with an increase of 1.6% (95% confidence interval [CI]: 0.6%, 2.7%) in hospitalization for COPD at a lag of 0-5 days. The impact of PM2.5 on hospitalization for COPD was greater significantly in males and patients admitted in summer. Our study strengthened the evidence for the adverse effect of PM2.5 based on satellite-based individual-level exposure data.
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Affiliation(s)
- Jie-Qi Jin
- National Clinical Research Center for Kidney Disease, State Key Laboratory of Organ Failure Research, Department of Biostatistics, Guangdong Provincial Key Laboratory of Tropical Disease Research, School of Public Health, Southern Medical University, Guangzhou, 510515, China
| | - Dong Han
- National Clinical Research Center for Kidney Disease, State Key Laboratory of Organ Failure Research, Department of Biostatistics, Guangdong Provincial Key Laboratory of Tropical Disease Research, School of Public Health, Southern Medical University, Guangzhou, 510515, China
- The Third Affiliated Hospital of Southern Medical University, Guangzhou, 510630, China
| | - Qi Tian
- Guangzhou Health Technology Identification & Human Resources Assessment Center, Guangzhou, 510080, China
| | - Zhao-Yue Chen
- National Clinical Research Center for Kidney Disease, State Key Laboratory of Organ Failure Research, Department of Biostatistics, Guangdong Provincial Key Laboratory of Tropical Disease Research, School of Public Health, Southern Medical University, Guangzhou, 510515, China
| | - Yun-Shao Ye
- Guangzhou Health Technology Identification & Human Resources Assessment Center, Guangzhou, 510080, China
| | - Qiao-Xuan Lin
- Guangzhou Health Technology Identification & Human Resources Assessment Center, Guangzhou, 510080, China
| | - Chun-Quan Ou
- National Clinical Research Center for Kidney Disease, State Key Laboratory of Organ Failure Research, Department of Biostatistics, Guangdong Provincial Key Laboratory of Tropical Disease Research, School of Public Health, Southern Medical University, Guangzhou, 510515, China
| | - Li Li
- National Clinical Research Center for Kidney Disease, State Key Laboratory of Organ Failure Research, Department of Biostatistics, Guangdong Provincial Key Laboratory of Tropical Disease Research, School of Public Health, Southern Medical University, Guangzhou, 510515, China.
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Abstract
PURPOSE OF REVIEW With cardiovascular disease (CVD) being the top cause of deaths worldwide, it is important to ensure healthy cardiovascular aging through enhanced understanding and prevention of adverse health effects exerted by external factors. This review aims to provide an updated understanding of environmental influences on cardiovascular aging, by summarizing epidemiological and mechanistic evidence for the cardiovascular health impact of major environmental stressors, including air pollution, endocrine-disrupting chemicals (EDCs), metals, and climate change. RECENT FINDINGS Recent studies generally support positive associations of exposure to multiple chemical environmental stressors (air pollution, EDCs, toxic metals) and extreme temperatures with increased risks of cardiovascular mortality and morbidity in the population. Environmental stressors have also been associated with a number of cardiovascular aging-related subclinical changes including biomarkers in the population, which are supported by evidence from relevant experimental studies. The elderly and patients are the most vulnerable demographic groups to majority environmental stressors. Future studies should account for the totality of individuals' exposome in addition to single chemical pollutants or environmental factors. Specific factors most responsible for the observed health effects related to cardiovascular aging remain to be elucidated.
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Affiliation(s)
- Yang Lan
- Department of Occupational and Environmental Health, School of Public Health, Xi'an Jiaotong University Health Science Center, 76 Yanta West Road, Yanta District, Xi'an City, Shaanxi Province, 710061, People's Republic of China
- Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Xi'an, Shaanxi, China
- Key Laboratory of Trace Elements and Endemic Diseases in Ministry of Health, Xi'an, Shaanxi, China
| | - Shaowei Wu
- Department of Occupational and Environmental Health, School of Public Health, Xi'an Jiaotong University Health Science Center, 76 Yanta West Road, Yanta District, Xi'an City, Shaanxi Province, 710061, People's Republic of China.
- Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Xi'an, Shaanxi, China.
- Key Laboratory of Trace Elements and Endemic Diseases in Ministry of Health, Xi'an, Shaanxi, China.
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Kasdagli MI, Katsouyanni K, de Hoogh K, Lagiou P, Samoli E. Investigating the association between long-term exposure to air pollution and greenness with mortality from neurological, cardio-metabolic and chronic obstructive pulmonary diseases in Greece. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2022; 292:118372. [PMID: 34656679 DOI: 10.1016/j.envpol.2021.118372] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/13/2021] [Revised: 10/12/2021] [Accepted: 10/13/2021] [Indexed: 05/20/2023]
Abstract
Long-term exposure to air pollution has been associated with increased natural-cause mortality, but the evidence on diagnoses-specific mortality outcomes is limited. Few studies have examined the potential synergistic effects of exposure to pollutants and greenness. We investigated the association between exposure to air pollution and greenness with nervous system related mortality, cardiometabolic and chronic obstructive pulmonary diseases (COPD) mortality in Greece, using an ecological study design. We collected socioeconomic and mortality data for 1035 municipal units from the 2011 Census. Annual PM2.5, NO2, BC and O3 concentrations for 2010 were predicted at 100 × 100 m grids by hybrid land use regression models. The normalized difference vegetation index (NDVI) was used for greenness. We applied single and two-exposure Poisson regression models on standardized mortality rates accounting for spatial autocorrelation. We assessed interactions between pollutants and greenness. An interquartile range increase in PM2.5, NO2 and BC was associated with increased risk in mortality from diseases of the nervous system (relative risk (RR): 1.14, 95% confidence interval (CI): 1.01, 1.28); 1.03 (95% CI: 0.99, 1.07); 1.05 (95% CI: 1.00, 1.10) respectively) and from cerebrovascular disease (RR: 1.14, 95% CI: 1.10, 1.18); 1.02 (95% CI: 1.01, 1.04); 1.02 (95% CI: 1.00, 1.04) respectively). PM2.5 was associated with ischemic heart disease mortality (RR: 1.05, 95% CI: 1.01, 1.10). We estimated inverse associations for all outcomes with O3 and for mortality from diseases of the nervous system or COPD with greenness. Estimates were mostly robust to co-exposure adjustment. Interactions were identified between NDVI and O3 or PM2.5 on mortality from the diseases of the nervous system, with higher effect estimates in greener areas. Our findings support the adverse effects of air pollution and the beneficial role of greenness on cardiovascular and nervous system related mortality. Further research is needed on diabetes mellitus.
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Affiliation(s)
- Maria-Iosifina Kasdagli
- Department of Hygiene, Epidemiology and Medical Statistics, School of Medicine, National and Kapodistrian University of Athens, Athens, Greece
| | - Klea Katsouyanni
- Department of Hygiene, Epidemiology and Medical Statistics, School of Medicine, National and Kapodistrian University of Athens, Athens, Greece; Environmental Research Group, MRC Centre for Environment and Health, Imperial College, United Kingdom
| | - Kees de Hoogh
- Swiss Tropical and Public Health Institute, Basel, Switzerland; University of Basel, Basel, Switzerland
| | - Pagona Lagiou
- Department of Hygiene, Epidemiology and Medical Statistics, School of Medicine, National and Kapodistrian University of Athens, Athens, Greece; Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Evangelia Samoli
- Department of Hygiene, Epidemiology and Medical Statistics, School of Medicine, National and Kapodistrian University of Athens, Athens, Greece.
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Elkama A, Şüküroğlu AA, Çakmak G. Exposure to particulate matter: a brief review with a focus on cardiovascular effects, children, and research conducted in Turkey. Arh Hig Rada Toksikol 2021; 72:244-253. [PMID: 34985835 PMCID: PMC8785112 DOI: 10.2478/aiht-2021-72-3563] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2021] [Revised: 06/01/2021] [Accepted: 11/01/2021] [Indexed: 11/20/2022] Open
Abstract
Exposure to environmental particulate matter (PM), outdoor air pollution in particular, has long been associated with adverse health effects. Today, PM has widely been accepted as a systemic toxicant showing adverse effects beyond the lungs. There are numerous studies, from those in vitro to epidemiological ones, suggesting various direct and indirect PM toxicity mechanisms associated with cardiovascular risks, including inflammatory responses, oxidative stress, changes in blood pressure, autonomic regulation of heart rate, suppression of endothelium-dependent vasodilation, thrombogenesis, myocardial infarction, and fibrinolysis. In addition to these and other health risks, considerations about air quality standards should include individual differences, lifestyle, and vulnerable populations such as children. Urban air pollution has been a major environmental issue for Turkey, and this review will also address current situation, research, and measures taken in our country.
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Affiliation(s)
- Aylin Elkama
- Gazi University Faculty of Pharmacy, Department of Toxicology, Ankara, Turkey
| | | | - Gonca Çakmak
- Gazi University Faculty of Pharmacy, Department of Toxicology, Ankara, Turkey
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Yang L, Chan KL, Yuen JWM, Wong FKY, Han L, Ho HC, Chang KKP, Ho YS, Siu JYM, Tian L, Wong MS. Effects of Urban Green Space on Cardiovascular and Respiratory Biomarkers in Chinese Adults: Panel Study Using Digital Tracking Devices. JMIR Cardio 2021; 5:e31316. [PMID: 34967754 PMCID: PMC8759022 DOI: 10.2196/31316] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2021] [Revised: 10/28/2021] [Accepted: 11/16/2021] [Indexed: 11/13/2022] Open
Abstract
Background The health benefits of urban green space have been widely reported in the literature; however, the biological mechanisms remain unexplored, and a causal relationship cannot be established between green space exposure and cardiorespiratory health. Objective Our aim was to conduct a panel study using personal tracking devices to continuously collect individual exposure data from healthy Chinese adults aged 50 to 64 years living in Hong Kong. Methods A panel of cardiorespiratory biomarkers was tested each week for a period of 5 consecutive weeks. Data on weekly exposure to green space, air pollution, and the physical activities of individual participants were collected by personal tracking devices. The effects of green space exposure measured by the normalized difference vegetation index (NDVI) at buffer zones of 100, 250, and 500 meters on a panel of cardiorespiratory biomarkers were estimated by a generalized linear mixed-effects model, with adjustment for confounding variables of sociodemographic characteristics, exposure to air pollutants and noise, exercise, and nutrient intake. Results A total of 39 participants (mean age 56.4 years, range 50-63 years) were recruited and followed up for 5 consecutive weeks. After adjustment for sex, income, occupation, physical activities, dietary intake, noise, and air pollution, significant negative associations with the NDVI for the 250-meter buffer zone were found in total cholesterol (–21.6% per IQR increase in NDVI, 95% CI –32.7% to –10.6%), low-density lipoprotein (–14.9%, 95% CI –23.4% to –6.4%), glucose (–11.2%, 95% CI –21.9% to –0.5%), and high-sensitivity C-reactive protein (–41.3%, 95% CI –81.7% to –0.9%). Similar effect estimates were found for the 100-meter and 250-meter buffer zones. After adjustment for multiple testing, the effect estimates of glucose and high-sensitivity C-reactive protein were no longer significant. Conclusions The health benefits of green space can be found in some metabolic and inflammatory biomarkers. Further studies are warranted to establish the causal relationship between green space and cardiorespiratory health.
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Affiliation(s)
- Lin Yang
- School of Nursing, The Hong Kong Polytechnic University, Hong Kong, Hong Kong
| | - Ka Long Chan
- Department of Land Surveying and Geo-Informatics, The Hong Kong Polytechnic University, Hong Kong, Hong Kong
| | - John W M Yuen
- School of Nursing, The Hong Kong Polytechnic University, Hong Kong, Hong Kong
| | - Frances K Y Wong
- School of Nursing, The Hong Kong Polytechnic University, Hong Kong, Hong Kong
| | - Lefei Han
- School of Nursing, The Hong Kong Polytechnic University, Hong Kong, Hong Kong.,School of Global Health, Chinese Center for Tropical Diseases Research, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Hung Chak Ho
- Department of Urban Planning and Design, The University of Hong Kong, Hong Kong, Hong Kong
| | - Katherine K P Chang
- School of Nursing, The Hong Kong Polytechnic University, Hong Kong, Hong Kong
| | - Yuen Shan Ho
- School of Nursing, The Hong Kong Polytechnic University, Hong Kong, Hong Kong
| | - Judy Yuen-Man Siu
- Department of Applied Social Sciences, The Hong Kong Polytechnic University, Hong Kong, Hong Kong
| | - Linwei Tian
- School of Public Health, The University of Hong Kong, Hong Kong, Hong Kong
| | - Man Sing Wong
- Department of Land Surveying and Geo-Informatics, The Hong Kong Polytechnic University, Hong Kong, Hong Kong
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Liu C, Wu M, Fu M, Wang H, Nie J. Dose-response relationships between polycyclic aromatic hydrocarbon exposure and blood cell counts among coke oven workers: a sex-stratified analysis. BMJ Open 2021; 11:e046843. [PMID: 35099406 PMCID: PMC8719181 DOI: 10.1136/bmjopen-2020-046843] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/06/2023] Open
Abstract
OBJECTIVES To explore sex differences and dose-response relationships between nine urinary polycyclic aromatic hydrocarbon (PAH) metabolites and neutrophil-lymphocyte ratio (NLR), platelet-lymphocyte ratio (PLR) and complete blood counts among coke oven workers. DESIGN AND SETTING A cross-sectional study with stratified sex was conducted in Shanxi, China. PARTICIPANTS A total of 458 male workers and 226 female workers were selected. PRIMARY AND SECONDARY OUTCOME MEASURES General linear models, p values for trend tests and natural cubic spline models were used to explore the dose-response relationships between nine urinary PAH metabolites and NLR, PLR and complete blood counts. RESULT Compared with male workers, female workers had lower exposure level of PAH (0.95 ng/mL vs 1.38 ng/mL). Only among female workers did we observe that a 1-unit increase in lg(1-OHPyr) was related to a 0.149 (95% CI: 0.055 to 0.242; p for trend=0.041) and 0.103 (95% CI: 0.025 to 0.181; p for trend=0.007) increase in lg(NLR) and lg(PLR), and a 0.116 (95% CI: -0.179 to -0.054; p for trend=0.007) decrease in lg(lymphocyte counts (LYMs)). A 1-unit increase in lg(2-OHNap) was related to a 0.045 (95% CI: 0.003 to 0.086; p for trend=0.037) increase in lg(PLR) and a 0.029 (95% CI: -0.056 to -0.002; p for trend=0.030) and 0.016 (95% CI: -0.029 to -0.003; p for trend=0.010) decrease in lg(white blood cell counts (WBCs)) and lg(haemoglobin (HGB)). CONCLUSION Female workers' NLR, PLR, WBCs, HGB and LYMs may be more susceptible than those of male workers when affected by PAH.
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Affiliation(s)
- Chengjuan Liu
- Occupational Health, Shanxi Medical University School of Public Health, Taiyuan, Shanxi, China
| | - Min Wu
- Occupational Health, Shanxi Medical University School of Public Health, Taiyuan, Shanxi, China
| | - Mengmeng Fu
- Occupational Health, Shanxi Medical University School of Public Health, Taiyuan, Shanxi, China
| | - Huimin Wang
- Occupational Health, Shanxi Medical University School of Public Health, Taiyuan, Shanxi, China
| | - Jisheng Nie
- Occupational Health, Shanxi Medical University School of Public Health, Taiyuan, Shanxi, China
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Goudarzi G, Hopke PK, Yazdani M. Forecasting PM 2.5 concentration using artificial neural network and its health effects in Ahvaz, Iran. CHEMOSPHERE 2021; 283:131285. [PMID: 34182649 DOI: 10.1016/j.chemosphere.2021.131285] [Citation(s) in RCA: 31] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/23/2021] [Revised: 06/13/2021] [Accepted: 06/17/2021] [Indexed: 05/28/2023]
Abstract
The main objective of the present study was to predict the associated health endpoint of PM2.5 using an artificial neural network (ANN). The neural network used in this work contains a hidden layer with 27 neurons, an input layer with 8 parameters, and an output layer. First, the artificial neural network was implemented with 80% of data for training then with 90% of data for training. The value of R for the data validation of these two networks was 0.80 and 0.83 respectively. The World Health Organization AirQ + software was utilized for assessing Health effects of PM2.5 levels. The mean PM2.5 over the 9-year study period was 63.27(μg/m3), about six times higher than the WHO guideline. However, the PM2.5 concentration in the last year decreased by about 25% compared to the first year, which is statistically significant (P-value = 0.0048). This reduced pollutant concentration led to a decrease in the number of deaths from 1785 in 2008 to 1059 in 2016. Moreover, a positive correlation was found between PM2.5 concentration and temperature and wind speed. Considering the importance of predicting PM2.5 concentration for accurate and timely decisions as well as the accuracy of the artificial neural network used in this study, the artificial neural network can be utilized as an effective instrument to reduce health and economic effects.
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Affiliation(s)
- Gholamreza Goudarzi
- Air Pollution and Respiratory Diseases Research Center, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran; Environmental Technologies Research Center (ETRC), Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran
| | - Philip K Hopke
- Center for Air Resources Engineering and Science, Clarkson University, Potsdam, NY, USA; Department of Public Health Sciences, University of Rochester School of Medicine and Dentistry, Rochester, NY, USA
| | - Mohsen Yazdani
- Department of Environmental Health Engineering, School of Public Health, Student Research Committee, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran.
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Hsiao MC, Lin WY, Lai LW, Lai HC. Application of a health index using PM 2.5 concentration reductions for evaluating cross-administrative region air quality policies. JOURNAL OF THE AIR & WASTE MANAGEMENT ASSOCIATION (1995) 2021; 71:949-963. [PMID: 33705254 DOI: 10.1080/10962247.2021.1902422] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/18/2020] [Revised: 02/08/2021] [Accepted: 02/25/2021] [Indexed: 06/12/2023]
Abstract
The primary goal of air quality policies is to reduce the impact of air pollution on human health, in particular, it is very important in the attainment-closing geographic areas with densely populated like Taiwan. Air quality policies in general only consider the reduction of emission as well as concentration, in order to highlight the effects of air pollution reduction responded on human health, a health index using PM2.5 concentration reductions (HI-cr) was adopted to evaluate air quality policies in this study. To investigate priorities of cross-administrative region air quality policies, the HI-cr were calculated by using annual results of atmospheric modeling and air quality modeling, which involved the meteorological effect and spatial distribution of air pollution. By studying the emission reduction targets of three administrative regions, Taichung, Changhwa, and Nantau in the Central Taiwan, 8 reduction scenarios were designed and examined. It is found that HI-cr can present detailed information in human health.From the results of adaptability assessement based on health, the equal reduction of emission in present air quality policy gave the most concentration reduction area with lower HI-cr. But according to the analysis in different proportion of emission reduction scenarios, it found that emission reduced more in the most population region, even the concentration reduction is not the highest but HI-cr increased. According to the analysis of different emission reduction policies, this study suggests HI-cr is an important index to evaluate the air pollution control policies instead of considering the impact of air pollutant concentrations only, especially in cross-administrative regions.Implications: In this study, we present a modified health index, HI-cr, to determine the priority of cross-administrative air quality policies using PM2.5 concentration reduction. HI-cr is adaptable for any types of geography, in particular for areas where the air quality is almost attainment like Taiwan. Cross-administrative air quality policies could be evaluated using HI-cr, it could highlight the high performance on population health improvement rather than high concentration reduction. In particular, for economies where the air quality is almost attainment and with complex terrain and dense population, air quality policies should consider the health prevention issues.
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Affiliation(s)
- Min-Chuan Hsiao
- Institute of Environmental Engineering and Management, National Taipei University of Technology, Taipei, Taiwan
| | - Wen-Yinn Lin
- Institute of Environmental Engineering and Management, National Taipei University of Technology, Taipei, Taiwan
| | - Li-Wei Lai
- Environmental Research and Information Center, Chang Jung Christian University, Tainan, Taiwan
| | - Hsin-Chih Lai
- Environmental Research and Information Center, Chang Jung Christian University, Tainan, Taiwan
- Department of Green Energy and Environmental Resources, Chang Jung Christian University, Tainan, Taiwan
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Jankowska-Kieltyka M, Roman A, Nalepa I. The Air We Breathe: Air Pollution as a Prevalent Proinflammatory Stimulus Contributing to Neurodegeneration. Front Cell Neurosci 2021; 15:647643. [PMID: 34248501 PMCID: PMC8264767 DOI: 10.3389/fncel.2021.647643] [Citation(s) in RCA: 47] [Impact Index Per Article: 11.8] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2020] [Accepted: 06/02/2021] [Indexed: 12/12/2022] Open
Abstract
Air pollution is regarded as an important risk factor for many diseases that affect a large proportion of the human population. To date, accumulating reports have noted that particulate matter (PM) is closely associated with the course of cardiopulmonary disorders. As the incidence of Alzheimer’s disease (AD), Parkinson’s disease (PD), and autoimmune disorders have risen and as the world’s population is aging, there is an increasing interest in environmental health hazards, mainly air pollution, which has been slightly overlooked as one of many plausible detrimental stimuli contributing to neurodegenerative disease onset and progression. Epidemiological studies have indicated a noticeable association between exposure to PM and neurotoxicity, which has been gradually confirmed by in vivo and in vitro studies. After entering the body directly through the olfactory epithelium or indirectly by passing through the respiratory system into the circulatory system, air pollutants are subsequently able to reach the brain. Among the potential mechanisms underlying particle-induced detrimental effects in the periphery and the central nervous system (CNS), increased oxidative stress, inflammation, mitochondrial dysfunction, microglial activation, disturbance of protein homeostasis, and ultimately, neuronal death are often postulated and concomitantly coincide with the main pathomechanisms of neurodegenerative processes. Other complementary mechanisms by which PM could mediate neurotoxicity and contribute to neurodegeneration remain unconfirmed. Furthermore, the question of how strong and proven air pollutants are as substantial adverse factors for neurodegenerative disease etiologies remains unsolved. This review highlights research advances regarding the issue of PM with an emphasis on neurodegeneration markers, symptoms, and mechanisms by which air pollutants could mediate damage in the CNS. Poor air quality and insufficient knowledge regarding its toxicity justify conducting scientific investigations to understand the biological impact of PM in the context of various types of neurodegeneration.
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Affiliation(s)
- Monika Jankowska-Kieltyka
- Department of Brain Biochemistry, Maj Institute of Pharmacology, Polish Academy of Sciences, Krakow, Poland
| | - Adam Roman
- Department of Brain Biochemistry, Maj Institute of Pharmacology, Polish Academy of Sciences, Krakow, Poland
| | - Irena Nalepa
- Department of Brain Biochemistry, Maj Institute of Pharmacology, Polish Academy of Sciences, Krakow, Poland
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Lim YH, Oh J, Han C, Bae HJ, Kim S, Jang Y, Ha E, Hong YC. Long-term exposure to moderate fine particulate matter concentrations and cause-specific mortality in an ageing society. Int J Epidemiol 2021; 49:1792-1801. [PMID: 33079997 DOI: 10.1093/ije/dyaa146] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/28/2020] [Indexed: 12/19/2022] Open
Abstract
BACKGROUND Long-term exposure to particulate matter <2.5 μm in size (PM2.5) is considered a risk factor for premature death. However, only a few studies have been conducted in areas with moderate PM2.5 concentrations. Moreover, an ageing society may be more susceptible to environmental exposure and future burden of mortality due to PM2.5. METHODS This study estimates hazard ratios (HRs) for all-cause and cause-specific mortality from long-term exposure to moderate PM2.5 concentrations in the elderly populations of seven cities in South Korea. We also projected nationwide elderly mortality caused by long-term exposure to PM2.5, accounting for population ageing until 2045. Mortality in 1 720 230 elderly adults aged ≥65 years in 2008 was monitored across 2009-16 and linked to modelled PM2.5 concentrations. RESULTS A total of 421 100 deaths occurred in 2009-16, and the mean of annual PM2.5 concentration ranged between 21.1 and 31.9 μg/m3 in most regions. The overall HR for a 10 μg/m3 increase in a 36-month PM2.5 moving average was 1.024 (95% confidence intervals: 1.009, 1.039). We estimated that 11 833 all-cause nationwide elderly deaths were attributable to PM2.5 exposure. Annual death tolls may increase to 17 948 by 2045. However, if PM2.5 is reduced to 5 μg/m3 by 2045, the tolls may show a lower increase to 3646. CONCLUSIONS Long-term exposure to moderately high levels of PM2.5 was associated with increased mortality risk among the elderly. Thus, PM2.5 reduction in response to the projected ageing-associated mortality in South Korea is critical.
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Affiliation(s)
- Youn-Hee Lim
- Section of Environmental Health, Department of Public Health, University of Copenhagen, Copenhagen, Denmark.,Institute of Environmental Medicine, Seoul National University Medical Research Center, Seoul, Republic of Korea
| | - Jongmin Oh
- Department of Occupational and Environmental Medicine, School of Medicine, Ewha Womans University, Seoul, Republic of Korea
| | - Changwoo Han
- Department of Preventive Medicine, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Hyun-Joo Bae
- Korea Environment Institute, Sejong, Republic of Korea
| | - Soontae Kim
- Department of Environmental and Safety Engineering, Ajou University, Suwon, Republic of Korea
| | - Yoonyoung Jang
- Department of Preventive Medicine, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Eunhee Ha
- Department of Occupational and Environmental Medicine, School of Medicine, Ewha Womans University, Seoul, Republic of Korea
| | - Yun-Chul Hong
- Section of Environmental Health, Department of Public Health, University of Copenhagen, Copenhagen, Denmark.,Institute of Environmental Medicine, Seoul National University Medical Research Center, Seoul, Republic of Korea.,Department of Preventive Medicine, Seoul National University College of Medicine, Seoul, Republic of Korea
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48
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Shinohara N, Yoshida-Ohuchi H. Resuspension and deposition of PM 2.5 and PM 10 containing radiocesium during and after indoor cleaning of uninhabited houses in Fukushima, Japan. CHEMOSPHERE 2021; 272:129934. [PMID: 35534979 DOI: 10.1016/j.chemosphere.2021.129934] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/19/2020] [Revised: 02/01/2021] [Accepted: 02/07/2021] [Indexed: 06/14/2023]
Abstract
Radiocesium contamination in homes could be a serious concern following Japan's 2011 Fukushima Daiichi Nuclear Power Plant accident, including exposure to radiocesium during cleaning when residents return home after the lifting of evacuation orders. This study measured PM2.5 and PM10 concentrations containing radiocesium during cleaning (dusting, vacuuming with a cordless cyclone unit, and vacuuming with a corded paper-pack unit), as well as air exchange rates, in 12 residential houses in Fukushima. Surface dusting of walls, shelves, and furniture significantly increased concentrations of PM2.5 and PM10 by up to 6.3 and 16 times the background (outdoor) level, respectively. Vacuuming with a paper-pack unit increased levels by 2.2 and 3.3 times, while vacuuming with a cordless cyclone unit increased these by 1.3 and 1.5 times, respectively. Measurements in 11 houses revealed an average air exchange rate of 0.22/h and dry deposition rates for PM2.5 and PM10 of 0.13/h and 0.32/h, respectively. Dry deposition rates were not correlated with building age, although the air exchange rates showed statistically significant increases with increasing building age. Dry deposition rates of PM2.5 significantly decreased with increasing air exchange rates.
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Affiliation(s)
- Naohide Shinohara
- Research Institute of Science for Safety and Sustainability (RISS), National Institute of Advanced Industrial Science and Technology (AIST), 16-1 Onogawa, Tsukuba, Ibaraki, 305-8569, Japan.
| | - Hiroko Yoshida-Ohuchi
- Graduate School of Pharmaceutical Sciences, Tohoku University, 6-3 Aramaki-Aoba, Aoba-ku, Sendai, Miyagi, 980-8578, Japan
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The joint association of physical activity and fine particulate matter exposure with incident dementia in elderly Hong Kong residents. ENVIRONMENT INTERNATIONAL 2021; 156:106645. [PMID: 34015665 DOI: 10.1016/j.envint.2021.106645] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/01/2021] [Revised: 04/13/2021] [Accepted: 05/12/2021] [Indexed: 02/05/2023]
Abstract
OBJECTIVE The evidence for the beneficial effects of physical activity (PA) and potentially detrimental effects of long-term exposure to fine particulate matter (PM2.5) on neurodegeneration diseases is accumulating. However, their joint effects remain unclear. We evaluated joint associations of habitual PA and PM2.5 exposure with incident dementia in a longitudinal elderly cohort in Hong Kong. METHODS A total of 57,775 elderly participants (≥65 years) without dementia were enrolled during 1998-2001 and followed up till 2011. Their information on PA and other relevant covariates were collected at baseline (1998-2001) by a standard self-administered questionnaire, including PA volumes (high, moderate, low, and inactive) and types (aerobic exercise, traditional Chinese exercise, stretching exercise, walking slowly, and no exercise). Their annual mean PM2.5 exposures at the residential address were estimated using a satellite-based spatiotemporal model. We then adopted the Cox proportional hazards model to examine the joint associations with the incidence of all-cause dementia, Alzheimer's diseases, and vascular dementia on additive and multiplicative scales. RESULTS During the follow-up period, we identified 1,157 incident cases of dementia, including 642 cases of Alzheimer's disease and 324 cases of vascular dementia. A higher PA level was associated with a lower risk of incident all-cause dementia (hazard ratio (HR) for the high-PA volume was 0.59 (95% CI, 0.47, 0.75), as compared with the inactive-PA), whereas a high level of PM2.5 was related to the higher risk with an HR of 1.15 (95%CI: 1.00, 1.33) compared with the low-level of PM2.5. No clear evidence was observed of interaction between habitual PA (volume and type) and PM2.5 inhalation to incident dementia on either additive or multiplicative scale. CONCLUSION Habitual PA and long-term PM2.5 exposure were oppositely related to incident dementia in the Hong Kong aged population. The benefits of PA remain in people irrespective of exposure to air pollution.
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The Research Progress of the Influence of Agricultural Activities on Atmospheric Environment in Recent Ten Years: A Review. ATMOSPHERE 2021. [DOI: 10.3390/atmos12050635] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/21/2023]
Abstract
In recent years, the industrial emission of air pollution has been reduced via a series of measures. However, with the rapid development of modern agriculture, air pollution caused by agricultural activities is becoming more and more serious. Agricultural activities can generate a large amount of air pollutants, such as ammonia, methane, nitrogen oxides, volatile organic compounds, and persistent organic pollutants, the sources of which mainly include farmland fertilization, livestock breeding, pesticide use, agricultural residue burning, agricultural machinery, and agricultural irrigation. Greenhouse gases emitted by agricultural activities can affect regional climate change, while atmospheric particulates and persistent organic pollutants can even seriously harm the health of surrounding residents. With the increasing threat of agricultural air pollution, more and more relevant studies have been carried out, as well as some recommendations for reducing emissions. The emissions of ammonia and greenhouse gases can be significantly reduced by adopting reasonable fertilization methods, scientific soil management, and advanced manure treatment systems. Regarding pesticide use and agricultural residues burning, emission reduction are more dependent on the restriction and support of government regulations, such as banning certain pesticides, prohibiting open burning of straw, and supporting the recycling and reuse of residues. This review, summarizing the relevant research in the past decade, discusses the current situation, health effects, and emission reduction measures of agricultural air pollutants from different sources, in order to provide some help for follow-up research.
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