1
|
Azimi F, Hafezi F, Ghaderpoori M, Kamarehie B, Karami MA, Sorooshian A, Baghani AN. Temporal characteristics and health effects related to NO 2, O 3, and SO 2 in an urban area of Iran. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2024; 349:123975. [PMID: 38615834 DOI: 10.1016/j.envpol.2024.123975] [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: 02/07/2024] [Revised: 03/22/2024] [Accepted: 04/11/2024] [Indexed: 04/16/2024]
Abstract
This study reports on temporal variations of NO2, O3, and SO2 pollutants and their related health effects in urban air of Khorramabad, Iran using AirQ 2.2.3 software. Based on data between 2015 and 2021, hourly NO2, O3, and SO2 concentrations increase starting at 6:00 a.m. local time until 9:00 p.m., 3:00 p.m., and 7:00 p.m. local time, respectively, before gradually decreasing. The highest monthly NO2, O3, and SO2 concentrations are observed in October, August, and September, respectively. Annual median NO2, O3, and SO2 concentrations range between 17 ppb and 38.8 ppb, 17.5 ppb-36.6 ppb, and ∼14 ppb-30.8 ppb, respectively. Two to 93 days and 17-156 days between 2015 and 2021 exhibit daily concentrations of NO2 and SO2 ≤ WHO AQGs, respectively, while 187-294 days have 8-h maximum O3 concentrations ≤ WHO AQGs. The mean excess mortality ascribed to respiratory mortality, cardiovascular mortality, hospital admissions for COPD, and acute myocardial infraction are 121, 603, 39, and 145 during 2015-2021, respectively. O3 is found to exert more significant health effects compared to SO2 and NO2, resulting in higher cardiovascular mortality. The gradual increase in NO2 and possibly O3 over the study period is suspected to be due to economic sanctions, while SO2 decreased due to regulatory activity. Sustainable control strategies such as improving fuel quality, promoting public transportation and vehicle retirement, applying subsidies for purchase of electric vehicles, and application of European emission standards on automobiles can help decrease target pollutant levels in ambient air of cities in developing countries.
Collapse
Affiliation(s)
- Faramarz Azimi
- Environmental Health Research Center, Lorestan University of Medical Sciences, Khorramabad, Iran
| | - Fariba Hafezi
- Department of Environmental Health Engineering, School of Health and Nutrition, Lorestan University of Medical Sciences, Khorramabad, Iran
| | - Mansour Ghaderpoori
- Environmental Health Research Center, Lorestan University of Medical Sciences, Khorramabad, Iran
| | - Bahram Kamarehie
- Environmental Health Research Center, Lorestan University of Medical Sciences, Khorramabad, Iran
| | - Mohammad Amin Karami
- Environmental Health Research Center, Lorestan University of Medical Sciences, Khorramabad, Iran
| | - Armin Sorooshian
- Department of Chemical and Environmental Engineering, University of Arizona, Tucson, AZ, USA; Department of Hydrology and Atmospheric Sciences, University of Arizona, Tucson, AZ, USA
| | - Abbas Norouzian Baghani
- Environmental Health Research Center, Lorestan University of Medical Sciences, Khorramabad, Iran.
| |
Collapse
|
2
|
Yu T, Wong TJ, Chang JW, Lao XQ. Trajectories of body mass index before the diagnosis of type 2 diabetes in a cohort of Taiwanese adults. Obes Res Clin Pract 2024; 18:21-27. [PMID: 38331596 DOI: 10.1016/j.orcp.2024.02.002] [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: 08/01/2023] [Revised: 01/18/2024] [Accepted: 02/01/2024] [Indexed: 02/10/2024]
Abstract
BACKGROUND Although the prevalence of overweight/obesity is lower in Asian countries, the risk of type 2 diabetes (T2DM) is disproportionally higher. We identified and characterized the trajectory patterns of body mass index (BMI) before the onset of T2DM in a Taiwanese population. METHODS Using the Taiwan MJ cohort study, we sampled the health examination data of 22,934 participants, including 7618 cases of T2DM and 15,316 controls. We used latent class trajectory analysis to identify distinct groups of pre-disease BMI trajectory. To compare the trajectories of cardiometabolic risk factors among different groups, we used linear mixed-effects models. RESULTS These 22,934 participants included 13,074 men (57%) and 9860 women (43%) who were on average followed for 9.0 years. We identified three distinct pre-disease BMI trajectories in cases: "stable overweight" (n = 7016, 92.1%), "weight gain" (n = 333, 4.4%) and "obesity" (n = 269, 3.5%). The "stable overweight" group had a mean BMI of 24.6 kg/m2 at 15 years prior to diagnosis, had a 1.2 unit increase during follow-up, and had a mean BMI of 25.8 kg/m2 at the time of diagnosis. The "weight gain" group had the most increasing trends in blood pressure/low-density lipoprotein cholesterol over time. CONCLUSION The BMI trajectory patterns among individuals who later developed diabetes in Taiwan seemed comparable to that of Western populations, but our population developed T2DM at a much lower BMI. Given that most cases belong to the "stable overweight" group, we also support using a population-based strategy for diabetes prevention instead of focusing on the high risk individuals.
Collapse
Affiliation(s)
- Tsung Yu
- Department of Public Health, College of Medicine, National Cheng Kung University, Tainan, Taiwan.
| | - Tzu-Jung Wong
- Department of Healthcare Information and Management, School of Health and Medical Engineering, Ming Chuan University, Taoyuan, Taiwan
| | - Jen-Wen Chang
- Department of Pharmacy, Chi Mei Medical Center, Tainan, Taiwan
| | - Xiang-Qian Lao
- Department of Biomedical Sciences, City University of Hong Kong, Kowloon Tong, Hong Kong; School of Public Health, Zhengzhou University, Zhengzhou, China
| |
Collapse
|
3
|
Li Y, Fan Z, Lu W, Xu R, Liu T, Liu L, Chen G, Lv Z, Huang S, Zhou Y, Liu Y, Sun H. Long-term exposure to ambient fine particulate matter-bound polycyclic aromatic hydrocarbons and cancer mortality: A difference-in-differences approach. CHEMOSPHERE 2023; 340:139800. [PMID: 37572709 DOI: 10.1016/j.chemosphere.2023.139800] [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: 05/18/2023] [Revised: 07/19/2023] [Accepted: 08/10/2023] [Indexed: 08/14/2023]
Abstract
The association of ambient fine particulate matter (PM2.5) exposure with cancer mortality was controversial, which may ascribe to the difference in PM2.5 constituents. Polycyclic aromatic hydrocarbons (PAHs) are carcinogenic constituents in PM2.5, which are suspected to account for PM2.5-induced cancer mortality but are yet to be investigated. We aimed to assess the association between long-term exposure to PM2.5-bound PAHs and cancer mortality and estimate the attributable mortality. A difference-in-differences approach was used to investigate the causal effect of long-term exposure to PM2.5-bound PAHs on cancer mortality. We divided Jiangsu province, China into 53 spatial units and summarized the annual number of cancer deaths in each spatial unit during 2016-2020. Annual population-weighted exposure to PM2.5-bound PAHs of each spatial unit was assessed by an inverse distance weighting method. The association between PM2.5-bound PAHs exposures and cancer mortality was evaluated by controlling spatial differences, temporal trends, PM2.5 mass exposures, temperatures, and socioeconomic status. Records of 793,269 cancer deaths were identified among 84.7 million population. Each ln-unit increase of exposure to total benzo[a]pyrene equivalents (∑BaPeq), total carcinogenic PAHs (∑PAH7c), and total PAHs (∑PAHs) was significantly associated with a 3.21%, 3.48%, and 2.64% increased risk of cancer mortality, respectively; the risk increased monotonically at low-level exposures but attenuated or flattened afterward (all p for nonlinearity <0.05). Similar exposure-response associations were identified for specific PAHs except that the associations for both fluoranthene and benzo[a]anthracene were linear. We estimated that exposure to ∑BaPeq, ∑PAH7c, and ∑PAHs contributed to 5.73%, 8.73%, and 7.33% of cancer deaths, respectively. In conclusion, long-term exposure to PM2.5-bound PAHs was associated with an increased risk of cancer mortality and contributed to substantial cancer deaths. Our findings highlight the importance to prevent deaths from cancer by reducing PM2.5-bound PAHs exposures and the necessity to take into consideration specific constituents in particulate pollution management in future.
Collapse
Affiliation(s)
- Yingxin Li
- Department of Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou, Guangdong, China
| | - Zhaoyu Fan
- Department of Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou, Guangdong, China
| | - Wenfeng Lu
- Department of Preventive Medicine, School of Public Health, Guangzhou Medical University, Guangzhou, Guangdong, China
| | - Ruijun Xu
- Department of Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou, Guangdong, China
| | - Tingting Liu
- Department of Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou, Guangdong, China
| | - Likun Liu
- Department of Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou, Guangdong, China
| | - Gongbo Chen
- Climate, Air Quality Research Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, Australia
| | - Ziquan Lv
- Central Laboratory of Shenzhen Center for Disease Control and Prevention, Shenzhen, Guangdong, China
| | - Suli Huang
- Department of Environment and Health, Shenzhen Center for Disease Control and Prevention, Shenzhen, Guangdong, China
| | - Yun Zhou
- Department of Preventive Medicine, School of Public Health, Guangzhou Medical University, Guangzhou, Guangdong, China
| | - Yuewei Liu
- Department of Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou, Guangdong, China.
| | - Hong Sun
- Department of Environment and Health, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, Jiangsu, China.
| |
Collapse
|
4
|
Huang W, Zhou Y, Chen X, Zeng X, Knibbs LD, Zhang Y, Jalaludin B, Dharmage SC, Morawska L, Guo Y, Yang X, Zhang L, Shan A, Chen J, Wang T, Heinrich J, Gao M, Lin L, Xiao X, Zhou P, Yu Y, Tang N, Dong G. Individual and joint associations of long-term exposure to air pollutants and cardiopulmonary mortality: a 22-year cohort study in Northern China. THE LANCET REGIONAL HEALTH. WESTERN PACIFIC 2023; 36:100776. [PMID: 37547049 PMCID: PMC10398602 DOI: 10.1016/j.lanwpc.2023.100776] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/05/2022] [Revised: 04/11/2023] [Accepted: 04/14/2023] [Indexed: 08/08/2023]
Abstract
Background Evidence on the associations between long-term exposure to multiple air pollutants and cardiopulmonary mortality is limited, especially for developing regions with higher pollutant levels. We aimed to characterise the individual and joint (multi-pollutant) associations of long-term exposure to air pollutants with cardiopulmonary mortality, and to identify air pollutant that primarily contributes to the mortality risk. Methods We followed 37,442 participants with a mean age of 43.5 years in four cities in northern China (Tianjin, Shenyang, Taiyuan, and Rizhao) from January 1998 to December 2019. Annual particulate matter (PM) with diameters ≤2.5 μm (PM2.5), ≤10 μm (PM10), sulfur dioxide (SO2) and nitrogen dioxide (NO2) were estimated using daily average values from satellite-derived machine learning models and monitoring stations. Time-varying Cox proportional hazards model was used to evaluate the individual association between air pollutants and mortality from non-accidental causes, cardiovascular diseases (CVDs), non-malignant respiratory diseases (RDs) and lung cancer, accounting for demographic and socioeconomic factors. Effect modifications by age, sex, income and education level were also examined. Quantile-based g-Computation integrated with time-to-event data was additionally applied to evaluate the co-effects and the relative weight of contributions for air pollutants. Findings During 785,807 person-years of follow-up, 5812 (15.5%) died from non-accidental causes, among which 2932 (7.8%) were from all CVDs, 479 (1.3%) from non-malignant RDs, and 552 (1.4%) from lung cancer. Long-term exposure to PM10 (mean [baseline]: 136.5 μg/m3), PM2.5 (mean [baseline]: 70.2 μg/m3), SO2 (mean [baseline]: 113.0 μg/m3) and NO2 (mean [baseline]: 39.2 μg/m3) were adversely and consistently associated with all mortality outcomes. A 10 μg/m3 increase in PM2.5 was associated with higher mortality from non-accidental causes (hazard ratio 1.20; 95% confidence interval 1.17-1.23), CVDs (1.23; 1.19-1.28), non-malignant RDs (1.37; 1.25-1.49) and lung cancer (1.14; 1.05-1.23). A monotonically increasing curve with linear or supra-linear shape with no evidence of a threshold was observed for the exposure-response relationship of mortality with individual or joint exposure to air pollutants. PM2.5 consistently contributed most to the elevated mortality risks related to air pollutant mixture, followed by SO2 or PM10. Interpretation There was a strong and positive association of long-term individual and joint exposure to PM10, PM2.5, SO2, and NO2 with mortalities from non-accidental causes, CVDs, non-malignant RDs and lung cancer in high-exposure settings, with PM2.5 potentially being the main contributor. The shapes of associations were consistent with a linear or supra-linear exposure-response relationship, with no lower threshold observed within the range of concentrations in this study. Funding National Key Research and Development Program of China, the China Scholarship Council, the National Natural Science Foundation of China, Natural Science Foundation of Guangdong Province.
Collapse
Affiliation(s)
- Wenzhong Huang
- Guangdong Provincial Engineering Technology Research Center of Environmental Pollution and Health Risk Assessment, Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China
- Climate, Air Quality Research Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
| | - Yang Zhou
- State Environmental Protection Key Laboratory of Environmental Pollution Health Risk Assessment, South China Institute of Environmental Sciences, Ministry of Environmental Protection, Guangzhou 510655, China
| | - Xi Chen
- Department of Occupational and Environmental Health, School of Public Health, Tianjin Medical University, Tianjin 300070, China
- Tianjin Key Laboratory of Environment, Nutrition and Public Health, Tianjin Medical University, Tianjin 300070, China
- Center for International Collaborative Research on Environment, Nutrition and Public Health, Tianjin 300070, China
| | - Xiaowen Zeng
- Guangdong Provincial Engineering Technology Research Center of Environmental Pollution and Health Risk Assessment, Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China
| | - Luke D. Knibbs
- Faculty of Medicine and Health, School of Public Health, The University of Sydney, NSW 2006, Australia
- Public Health Research Analytics and Methods for Evidence, Public Health Unit, Sydney Local Health District, Camperdown, NSW 2050, Australia
| | - Yunting Zhang
- Guangdong Provincial Engineering Technology Research Center of Environmental Pollution and Health Risk Assessment, Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China
| | - Bin Jalaludin
- Centre for Air Quality and Health Research and Evaluation, Glebe, NSW 2037, Australia
- Ingham Institute for Applied Medial Research, Liverpool, NSW 2170, Australia
- School of Public Health and Community Medicine, The University of New South Wales, Kensington, NSW 2052, Australia
| | - Shyamali C. Dharmage
- Allergy and Lung Health Unit, Melbourne School of Population and Global Health, University of Melbourne, Melbourne, VIC 3052, Australia
| | - Lidia Morawska
- International Laboratory for Air Quality and Health, Queensland University of Technology, Brisbane, QLD 4001, Australia
| | - Yuming Guo
- Climate, Air Quality Research Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
| | - Xueli Yang
- Department of Occupational and Environmental Health, School of Public Health, Tianjin Medical University, Tianjin 300070, China
- Tianjin Key Laboratory of Environment, Nutrition and Public Health, Tianjin Medical University, Tianjin 300070, China
- Center for International Collaborative Research on Environment, Nutrition and Public Health, Tianjin 300070, China
| | - Liwen Zhang
- Department of Occupational and Environmental Health, School of Public Health, Tianjin Medical University, Tianjin 300070, China
- Tianjin Key Laboratory of Environment, Nutrition and Public Health, Tianjin Medical University, Tianjin 300070, China
- Center for International Collaborative Research on Environment, Nutrition and Public Health, Tianjin 300070, China
| | - Anqi Shan
- Department of Occupational and Environmental Health, School of Public Health, Tianjin Medical University, Tianjin 300070, China
- Tianjin Key Laboratory of Environment, Nutrition and Public Health, Tianjin Medical University, Tianjin 300070, China
- Center for International Collaborative Research on Environment, Nutrition and Public Health, Tianjin 300070, China
| | - Jie Chen
- Department of Occupational and Environmental Health, School of Public Health, China Medical University, Shenyang 110122, China
| | - Tong Wang
- School of Public Health, Shanxi Medical University, Taiyuan 030001, China
| | - Joachim Heinrich
- Institute and Clinic for Occupational, Social and Environmental Medicine, University Hospital, LMU Munich, Munich 80336, Germany
| | - Meng Gao
- Department of Geography, Hong Kong Baptist University, Hong Kong SAR, China
| | - Lizi Lin
- Guangdong Provincial Engineering Technology Research Center of Environmental Pollution and Health Risk Assessment, Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China
| | - Xiang Xiao
- Department of Geography, Hong Kong Baptist University, Hong Kong SAR, China
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA
| | - Peien Zhou
- Department of Public Health & Primary Care, University of Cambridge, Cambridge CB2 1TN, United Kingdom
| | - Yunjiang Yu
- State Environmental Protection Key Laboratory of Environmental Pollution Health Risk Assessment, South China Institute of Environmental Sciences, Ministry of Environmental Protection, Guangzhou 510655, China
| | - Naijun Tang
- Department of Occupational and Environmental Health, School of Public Health, Tianjin Medical University, Tianjin 300070, China
| | - Guanghui Dong
- Guangdong Provincial Engineering Technology Research Center of Environmental Pollution and Health Risk Assessment, Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China
| |
Collapse
|
5
|
Zhao X, Xu H, Li Y, Liu Y, Guo C, Li Y. Status and frontier analysis of indoor PM 2.5-related health effects: a bibliometric analysis. REVIEWS ON ENVIRONMENTAL HEALTH 2023; 0:reveh-2022-0228. [PMID: 36976918 DOI: 10.1515/reveh-2022-0228] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/17/2022] [Accepted: 03/02/2023] [Indexed: 06/18/2023]
Abstract
Epidemiological data indicate atmospheric particulate matter, especially fine particulate matter (PM2.5), has many negative effects on human health. Of note, people spend about 90% of their time indoors. More importantly, according to the World Health Organization (WHO) statistics, indoor air pollution causes nearly 1.6 million deaths each year, and it is considered as one of the major health risk factors. In order to obtain a deeper understanding of the harmful effects of indoor PM2.5 on human health, we used bibliometric software to summarize articles in this field. In conclusion, since 2000, the annual publication volume has increased year by year. America topped the list for the number of articles, and Professor Petros Koutrakis and Harvard University were the author and institution with the most published in this research area, respectively. Over the past decade, scholars gradually paid attention to molecular mechanisms, therefore, the toxicity can be better explored. Particularly, apart from timely intervention and treatment for adverse consequences, it is necessary to effectively reduce indoor PM2.5 through technologies. In addition, the trend and keywords analysis are favorable ways to find out future research hotspots. Hopefully, various countries and regions strengthen academic cooperation and integration of multi-disciplinary.
Collapse
Affiliation(s)
- Xinying Zhao
- Department of Toxicology and Sanitary Chemistry, School of Public Health, Capital Medical University, Beijing, China
- Beijing Key Laboratory of Environmental Toxicology, Capital Medical University, Beijing, China
| | - Hailin Xu
- Department of Toxicology and Sanitary Chemistry, School of Public Health, Capital Medical University, Beijing, China
- Beijing Key Laboratory of Environmental Toxicology, Capital Medical University, Beijing, China
| | - Yan Li
- Beijing Key Laboratory of Environmental Toxicology, Capital Medical University, Beijing, China
- Department of Occupational Health and Environmental Health, School of Public Health, Capital Medical University, Beijing, China
| | - Yufan Liu
- Department of Toxicology and Sanitary Chemistry, School of Public Health, Capital Medical University, Beijing, China
- Beijing Key Laboratory of Environmental Toxicology, Capital Medical University, Beijing, China
| | - Caixia Guo
- Beijing Key Laboratory of Environmental Toxicology, Capital Medical University, Beijing, China
- Department of Occupational Health and Environmental Health, School of Public Health, Capital Medical University, Beijing, China
| | - Yanbo Li
- Department of Toxicology and Sanitary Chemistry, School of Public Health, Capital Medical University, Beijing, China
- Beijing Key Laboratory of Environmental Toxicology, Capital Medical University, Beijing, China
| |
Collapse
|
6
|
Vienneau D, Stafoggia M, Rodopoulou S, Chen J, Atkinson RW, Bauwelinck M, Klompmaker JO, Oftedal B, Andersen ZJ, Janssen NAH, So R, Lim YH, Flückiger B, Ducret-Stich R, Röösli M, Probst-Hensch N, Künzli N, Strak M, Samoli E, de Hoogh K, Brunekreef B, Hoek G. Association between exposure to multiple air pollutants, transportation noise and cause-specific mortality in adults in Switzerland. Environ Health 2023; 22:29. [PMID: 36967400 PMCID: PMC10041702 DOI: 10.1186/s12940-023-00983-y] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2023] [Accepted: 03/13/2023] [Indexed: 05/23/2023]
Abstract
BACKGROUND Long-term exposure to air pollution and noise is detrimental to health; but studies that evaluated both remain limited. This study explores associations with natural and cause-specific mortality for a range of air pollutants and transportation noise. METHODS Over 4 million adults in Switzerland were followed from 2000 to 2014. Exposure to PM2.5, PM2.5 components (Cu, Fe, S and Zn), NO2, black carbon (BC) and ozone (O3) from European models, and transportation noise from source-specific Swiss models, were assigned at baseline home addresses. Cox proportional hazards models, adjusted for individual and area-level covariates, were used to evaluate associations with each exposure and death from natural, cardiovascular (CVD) or non-malignant respiratory disease. Analyses included single and two exposure models, and subset analysis to study lower exposure ranges. RESULTS During follow-up, 661,534 individuals died of natural causes (36.6% CVD, 6.6% respiratory). All exposures including the PM2.5 components were associated with natural mortality, with hazard ratios (95% confidence intervals) of 1.026 (1.015, 1.038) per 5 µg/m3 PM2.5, 1.050 (1.041, 1.059) per 10 µg/m3 NO2, 1.057 (1.048, 1.067) per 0.5 × 10-5/m BC and 1.045 (1.040, 1.049) per 10 dB Lden total transportation noise. NO2, BC, Cu, Fe and noise were consistently associated with CVD and respiratory mortality, whereas PM2.5 was only associated with CVD mortality. Natural mortality associations persisted < 20 µg/m3 for PM2.5 and NO2, < 1.5 10-5/m BC and < 53 dB Lden total transportation noise. The O3 association was inverse for all outcomes. Including noise attenuated all outcome associations, though many remained significant. Across outcomes, noise was robust to adjustment to air pollutants (e.g. natural mortality 1.037 (1.033, 1.042) per 10 dB Lden total transportation noise, after including BC). CONCLUSION Long-term exposure to air pollution and transportation noise in Switzerland contribute to premature mortality. Considering co-exposures revealed the importance of local traffic-related pollutants such as NO2, BC and transportation noise.
Collapse
Affiliation(s)
- Danielle Vienneau
- Department of Epidemiology and Public Health, Swiss Tropical and Public Health Institute, Kreuzstrasse 2, Allschwil, CH-4123, Switzerland.
- University of Basel, Basel, Switzerland.
| | - Massimo Stafoggia
- Department of Epidemiology, Lazio Region Health Service / ASL Roma 1, Rome, Italy
- Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Sophia Rodopoulou
- Department of Hygiene, Epidemiology and Medical Statistics, Medical School, National and Kapodistrian University of Athens, Athens, Greece
| | - Jie Chen
- Institute for Risk Assessment Sciences, Utrecht University, Utrecht, Netherlands
| | - Richard W Atkinson
- Population Health Research Institute, St George's, University of London, London, UK
| | - Mariska Bauwelinck
- Interface Demography - Department of Sociology, Vrije Universiteit Brussel, Pleinlaan 2, Brussels, 1050, Belgium
| | - Jochem O Klompmaker
- National Institute for Public Health and the Environment (RIVM), Bilthoven, Netherlands
| | - Bente Oftedal
- Department of Environmental Health, Norwegian Institute of Public Health, Oslo, Norway
| | - Zorana J Andersen
- Section of Environmental Health, Department of Public Health, University of Copenhagen, Copenhagen, 1165, Denmark
| | - Nicole A H Janssen
- National Institute for Public Health and the Environment (RIVM), Bilthoven, Netherlands
| | - Rina So
- Section of Environmental Health, Department of Public Health, University of Copenhagen, Copenhagen, 1165, Denmark
| | - Youn-Hee Lim
- Section of Environmental Health, Department of Public Health, University of Copenhagen, Copenhagen, 1165, Denmark
| | - Benjamin Flückiger
- Department of Epidemiology and Public Health, Swiss Tropical and Public Health Institute, Kreuzstrasse 2, Allschwil, CH-4123, Switzerland
- University of Basel, Basel, Switzerland
| | - Regina Ducret-Stich
- Department of Epidemiology and Public Health, Swiss Tropical and Public Health Institute, Kreuzstrasse 2, Allschwil, CH-4123, Switzerland
- University of Basel, Basel, Switzerland
| | - Martin Röösli
- Department of Epidemiology and Public Health, Swiss Tropical and Public Health Institute, Kreuzstrasse 2, Allschwil, CH-4123, Switzerland
- University of Basel, Basel, Switzerland
| | - Nicole Probst-Hensch
- Department of Epidemiology and Public Health, Swiss Tropical and Public Health Institute, Kreuzstrasse 2, Allschwil, CH-4123, Switzerland
- University of Basel, Basel, Switzerland
| | - Nino Künzli
- Department of Epidemiology and Public Health, Swiss Tropical and Public Health Institute, Kreuzstrasse 2, Allschwil, CH-4123, Switzerland
- University of Basel, Basel, Switzerland
| | - Maciek Strak
- National Institute for Public Health and the Environment (RIVM), Bilthoven, Netherlands
| | - Evangelia Samoli
- Department of Hygiene, Epidemiology and Medical Statistics, Medical School, National and Kapodistrian University of Athens, Athens, Greece
| | - Kees de Hoogh
- Department of Epidemiology and Public Health, Swiss Tropical and Public Health Institute, Kreuzstrasse 2, Allschwil, CH-4123, Switzerland
- University of Basel, Basel, Switzerland
| | - Bert Brunekreef
- Institute for Risk Assessment Sciences, Utrecht University, Utrecht, Netherlands
| | - Gerard Hoek
- Institute for Risk Assessment Sciences, Utrecht University, Utrecht, Netherlands
| |
Collapse
|