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Yin P, Brauer M, Cohen A, Burnett RT, Liu J, Liu Y, Liang R, Wang W, Qi J, Wang L, Zhou M. Long-term Fine Particulate Matter Exposure and Nonaccidental and Cause-specific Mortality in a Large National Cohort of Chinese Men. ENVIRONMENTAL HEALTH PERSPECTIVES 2017; 125:117002. [PMID: 29116930 PMCID: PMC5947939 DOI: 10.1289/ehp1673] [Citation(s) in RCA: 209] [Impact Index Per Article: 29.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/24/2017] [Revised: 09/01/2017] [Accepted: 09/05/2017] [Indexed: 05/18/2023]
Abstract
BACKGROUND Cohort studies in North America and western Europe have reported increased risk of mortality associated with long-term exposure to fine particles (PM2.5), but to date, no such studies have been reported in China, where higher levels of exposure are experienced. OBJECTIVES We estimated the association between long-term exposure to PM2.5 with nonaccidental and cause-specific mortality in a cohort of Chinese men. METHODS We conducted a prospective cohort study of 189,793 men 40 y old or older during 1990-91 from 45 areas in China. Annual average PM2.5 levels for the years 1990, 1995, 2000, and 2005 were estimated for each cohort location using a combination of satellite-based estimates, chemical transport model simulations, and ground-level measurements developed for the Global Burden of Disease (GBD) 2013 study. A Cox proportional hazards regression model was used to estimate hazard ratios (HR) for nonaccidental cardiovascular disease (CVD), chronic obstructive pulmonary disease (COPD), and lung-cancer mortality. We also assessed the shape of the concentration-response relationship and compared the risk estimates with those predicted by Integrated Exposure-Response (IER) function, which incorporated estimates of mortality risk from previous cohort studies in western Europe and North America. RESULTS The mean level of PM2.5 exposure during 2000-2005 was 43.7 μg/m3 (ranging from 4.2 to 83.8 μg/m3). Mortality HRs (95% CI) per 10-μg/m3 increase in PM2.5 were 1.09 (1.08, 1.09) for nonaccidental causes; 1.09 (1.08, 1.10) for CVD, 1.12 (1.10, 1.13) for COPD; and 1.12 (1.07, 1.14) for lung cancer. The HR estimate from our cohort was consistently higher than IER predictions. CONCLUSIONS Long-term exposure to PM2.5 was associated with nonaccidental, CVD, lung cancer, and COPD mortality in China. The IER estimator may underestimate the excess relative risk of cause-specific mortality due to long-term exposure to PM2.5 over the exposure range experienced in China and other low- and middle-income countries. https://doi.org/10.1289/EHP1673.
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Affiliation(s)
- Peng Yin
- National Center for Chronic Noncommunicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Michael Brauer
- School of Population and Public Health, University of British Columbia, Vancouver, British Columbia, Canada
| | - Aaron Cohen
- Health Effects Institute, Boston, Massachusetts, USA
| | | | - Jiangmei Liu
- National Center for Chronic Noncommunicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Yunning Liu
- National Center for Chronic Noncommunicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Ruiming Liang
- National Center for Chronic Noncommunicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Weihua Wang
- Shaanxi Provincial Center for Disease Control and Prevention, Xian, China
| | - Jinlei Qi
- National Center for Chronic Noncommunicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Lijun Wang
- National Center for Chronic Noncommunicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Maigeng Zhou
- National Center for Chronic Noncommunicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
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Li Z, Xin J, Chen W, Liu J, Zhu M, Zhao C, Yuan J, Jin G, Ma H, Du J, Hu Z, Wu T, Shen H, Dai J, Yu H. Genetic variants in autophagy associated genes are associated with DNA damage levels in Chinese population. Gene 2017; 626:414-419. [PMID: 28512061 DOI: 10.1016/j.gene.2017.05.017] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2017] [Revised: 05/03/2017] [Accepted: 05/09/2017] [Indexed: 10/19/2022]
Abstract
Autophagy associated genes (ATGs) played an important role in the repair process of DNA damage and decreased autophagy may weaken the repair process and aggravate DNA damage. Based on this, we hypothesized that DNA damage levels might be modified by genetic variants in autophagy associated genes. In order to validate our hypothesis, 307 subjects were recruited from three different cities (Zhuhai, Wuhan and Tianjin) in China. Demographic data, individual 24-h PM2.5 exposure and peripheral blood DNA damage levels were also detected. Seven potentially functional polymorphisms in four essential autophagy associated genes (ATG5, ATG7, ATG8 and ATG13) were screened to evaluate the relationship between the polymorphisms of autophagy associated genes and DNA damage levels. This association was assessed by using multivariable linear regression model, age, sex, smoke and PM2.5 exposure levels were adjusted in each city. We found that rs12599322 in ATG8 (A>G, β=0.263, 95% CI: 0.108-0.419, P=8.98×10-4) and rs7484002 in ATG13 (A>G, β=0.396, 95% CI: 0.085-0.708, P=0.013) were significantly associated with higher DNA damage levels. Furthermore, functional annotations showed that both rs12599322 and rs7484002 located at transcription factor binding sites (TFBS), indicating that they could regulate the expression of related genes through TF regulation. Following allelic trend analysis revealed that the DNA damage levels were significantly aggravated with the increasing number of risk variants in autophagy associated genes (P for trend: 8.09×10-5). Our findings suggested that the polymorphisms in ATGs may influence DNA damage levels in one of the Chinese population.
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Affiliation(s)
- Zhihua Li
- Department of Epidemiology and Biostatistics, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, China; Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Medicine, Nanjing Medical University, Nanjing, Jiangsu, China
| | - Junyi Xin
- Department of Epidemiology and Biostatistics, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, China; Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Medicine, Nanjing Medical University, Nanjing, Jiangsu, China
| | - Weihong Chen
- Ministry of Education Key Laboratory for Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Jia Liu
- Department of Epidemiology and Biostatistics, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, China; Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Medicine, Nanjing Medical University, Nanjing, Jiangsu, China
| | - Meng Zhu
- Department of Epidemiology and Biostatistics, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, China; Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Medicine, Nanjing Medical University, Nanjing, Jiangsu, China
| | - Congwen Zhao
- Department of Epidemiology and Biostatistics, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, China
| | - Jing Yuan
- Ministry of Education Key Laboratory for Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Guangfu Jin
- Department of Epidemiology and Biostatistics, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, China; Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Medicine, Nanjing Medical University, Nanjing, Jiangsu, China
| | - Hongxia Ma
- Department of Epidemiology and Biostatistics, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, China; Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Medicine, Nanjing Medical University, Nanjing, Jiangsu, China
| | - Jiangbo Du
- Department of Epidemiology and Biostatistics, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, China; Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Medicine, Nanjing Medical University, Nanjing, Jiangsu, China
| | - Zhibin Hu
- Department of Epidemiology and Biostatistics, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, China; Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Medicine, Nanjing Medical University, Nanjing, Jiangsu, China
| | - Tangchun Wu
- Ministry of Education Key Laboratory for Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Hongbing Shen
- Department of Epidemiology and Biostatistics, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, China; Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Medicine, Nanjing Medical University, Nanjing, Jiangsu, China
| | - Juncheng Dai
- Department of Epidemiology and Biostatistics, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, China; Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Medicine, Nanjing Medical University, Nanjing, Jiangsu, China
| | - Hao Yu
- Department of Epidemiology and Biostatistics, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, China.
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Huang L, Rao C, van der Kuijp TJ, Bi J, Liu Y. A comparison of individual exposure, perception, and acceptable levels of PM 2.5 with air pollution policy objectives in China. ENVIRONMENTAL RESEARCH 2017; 157:78-86. [PMID: 28525860 DOI: 10.1016/j.envres.2017.05.012] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/20/2017] [Revised: 05/05/2017] [Accepted: 05/09/2017] [Indexed: 06/07/2023]
Abstract
Atmospheric pollution has emerged as a major public health issue in China. Public perception and acceptable risk levels of air pollution can prompt individual behavioral changes and play a major role in the public's response to health risks. Therefore, to explore these responses and evaluate what constitutes publicly acceptable concentrations of fine particulate matter (PM2.5), questionnaire surveys were conducted in three representative cities of China: Beijing, Nanjing, and Guangzhou. Great differences in public risk perception were revealed. Public perception of the health effects of air pollution (Effect) and familiarity with it (Familiarity) were significantly higher in the winter than in the summer, and also during severe haze days compared with typical days. The public perception of trust in the government (Trust) was consistent across all conditions. Exposure to severe haze pollution and experiencing harms from it were key factors influencing public willingness to respond to haze. These results reflected individual exposure levels correlating closely with risk perception and acceptance of PM2.5. However, a crucial gap exists between public acceptable risk levels (PARL) of air pollution and the policy objectives of the State Council's Action Plan. Thus, policymakers can utilize this study to develop more targeted measures to combat air pollution.
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Affiliation(s)
- Lei Huang
- State Key Laboratory of Pollution Control and Resource Reuse, School of the Environment, Nanjing University, Xianlin Campus, Box 624, 163 Xianlin Avenue, Nanjing 210023, China; Lamont-Doherty Earth Observatory, Columbia University, P.O. Box 1000, 61 Rt. 9W. Palisades, NY 10964, USA.
| | - Chao Rao
- State Key Laboratory of Pollution Control and Resource Reuse, School of the Environment, Nanjing University, Xianlin Campus, Box 624, 163 Xianlin Avenue, Nanjing 210023, China
| | | | - Jun Bi
- State Key Laboratory of Pollution Control and Resource Reuse, School of the Environment, Nanjing University, Xianlin Campus, Box 624, 163 Xianlin Avenue, Nanjing 210023, China.
| | - Yang Liu
- Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, GA 30322, USA
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Chen F, Deng Z, Deng Y, Qiao Z, Lan L, Meng Q, Luo B, Zhang W, Ji K, Qiao X, Fan Z, Zhang M, Cui Y, Zhao X, Li X. Attributable risk of ambient PM 10 on daily mortality and years of life lost in Chengdu, China. THE SCIENCE OF THE TOTAL ENVIRONMENT 2017; 581-582:426-433. [PMID: 28069303 DOI: 10.1016/j.scitotenv.2016.12.151] [Citation(s) in RCA: 32] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/23/2016] [Revised: 12/01/2016] [Accepted: 12/15/2016] [Indexed: 06/06/2023]
Abstract
Attributable risk is an important indicator for planning and evaluating public health interventions. However, most current measures of the attributable risk of air pollutants have not considered temporal relationships between exposure and risk. More importantly, limited information is available regarding the attributable risk due to ambient air pollutants in basin regions like the Sichuan Basin, China. To quantify the association between PM10 and deaths in the Basin region, we used a measure proposed recently within the framework of the distributed lag non-linear model to estimate the attributable risk in Chengdu, China. Meanwhile, we examined the association between PM10 and years of life lost (YLL). Our analysis showed that population-attributable fractions for non-accidental, respiratory, and cardiovascular mortality were 0.569% (95% CI: -3.474%, 4.374%), 0.695% (95% CI: -5.260%, 6.457%), and 0.631% (95% CI: -6.973%, 7.390%), respectively. On average, a 1μg/m3 increase in PM10 was associated with cumulative increases of 0.26893, 0.30437, and 0.21924 YLL for non-accidental, respiratory, and cardiovascular mortality, respectively, referring to 20μg/m3. In addition, we found an inverse U-shaped pattern for the cumulative risk with 350μg/m3 as the reverse point. With a 1μg/m3 increase in PM10, YLL changed more significantly than mortality. Moreover, PM10 demonstrated remarkable effects on YLL among men and the elderly.
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Affiliation(s)
- Fei Chen
- Department of Epidemiology and Health Statistics, West China School of Public Health, Sichuan University, Chengdu 610041, Sichuan, China
| | - Zibing Deng
- Department of Epidemiology and Health Statistics, West China School of Public Health, Sichuan University, Chengdu 610041, Sichuan, China
| | - Ying Deng
- Sichuan Centre for Disease Control and Prevention, Chengdu 610041, Sichuan, China
| | - Zhijiao Qiao
- Department of Epidemiology and Health Statistics, West China School of Public Health, Sichuan University, Chengdu 610041, Sichuan, China
| | - Lan Lan
- Department of Epidemiology and Health Statistics, West China School of Public Health, Sichuan University, Chengdu 610041, Sichuan, China
| | - Qiong Meng
- School of Public Health, Kunming Medical University, Kunming, 650500, Yunnan, China
| | - Bin Luo
- Sichuan Environmental Monitoring Centre, Chengdu 610041, Sichuan, China
| | - Wei Zhang
- Sichuan Environmental Monitoring Centre, Chengdu 610041, Sichuan, China
| | - Kui Ji
- Sichuan Centre for Disease Control and Prevention, Chengdu 610041, Sichuan, China
| | - Xue Qiao
- Institute of New Energy and Low-Carbon Technology, Sichuan University, Chengdu, Sichuan, China
| | - Zhiwei Fan
- Department of Epidemiology and Health Statistics, West China School of Public Health, Sichuan University, Chengdu 610041, Sichuan, China
| | - Meixia Zhang
- Department of Epidemiology and Health Statistics, West China School of Public Health, Sichuan University, Chengdu 610041, Sichuan, China
| | - Yan Cui
- Department of Epidemiology and Health Statistics, West China School of Public Health, Sichuan University, Chengdu 610041, Sichuan, China
| | - Xing Zhao
- Department of Epidemiology and Health Statistics, West China School of Public Health, Sichuan University, Chengdu 610041, Sichuan, China.
| | - Xiaosong Li
- Department of Epidemiology and Health Statistics, West China School of Public Health, Sichuan University, Chengdu 610041, Sichuan, China.
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Sameem S, Sylwester K. The business cycle and mortality: Urban versus rural counties. Soc Sci Med 2017; 175:28-35. [DOI: 10.1016/j.socscimed.2016.12.023] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2016] [Revised: 12/07/2016] [Accepted: 12/16/2016] [Indexed: 10/20/2022]
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Fernie KJ, Cruz-Martinez L, Peters L, Palace V, Smits JEG. Inhaling Benzene, Toluene, Nitrogen Dioxide, and Sulfur Dioxide, Disrupts Thyroid Function in Captive American Kestrels (Falco sparverius). ENVIRONMENTAL SCIENCE & TECHNOLOGY 2016; 50:11311-11318. [PMID: 27646166 DOI: 10.1021/acs.est.6b03026] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/06/2023]
Abstract
Research investigating the effects of air contaminants on biota has been limited to date. Captive adult female American kestrels (Falco sparverius) were exposed to a mixture of benzene (0.6 ppm), toluene (1 ppm), nitrogen dioxide (NO2; 2 ppm) and sulfur dioxide (SO2; 5.6 ppm), in a whole-body inhalation chamber. Thyroid axis responses to meet metabolic demands were examined through thyroid histology, plasma thyroxine (T4), and triiodothyronine (T3), and hepatic outer ring deiodination (T4-ORD). Plasma free (F) T3 and T4 were measured at baseline, and at 9 days and 18 days of exposure, whereas total (T) T3 and TT4, thyroid histology and hepatic T4-ORD were determined at the final 18 day exposure. Inhalation of these contaminants significantly suppressed plasma FT4 and TT4, and depleted follicular colloid and increased epithelial cell height at 18 days, and significantly altered the temporal pattern of plasma FT4. Significant histological changes in the follicular colloid:epithelial cell height ratio indicated sustained T4 production and release by the thyroid glands. There was no effect on plasma FT3, TT3, or hepatic T4-ORD. We hypothesize that contaminant-related activation of the hypothalamus-pituitary-thyroid axis in the kestrels increased elimination of plasma T4 through Phase II enzymes. Further research is required to test this hypothesis in wild birds.
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Affiliation(s)
- Kim J Fernie
- Ecotoxicology and Wildlife Health Division, Science and Technology Branch, Environment and Climate Change Canada, 867 Lakeshore Rd., Burlington, Ontario Canada , L7R 4A6
| | - Luis Cruz-Martinez
- Department of Ecosystem and Public Health, Faculty of Veterinary Medicine, University of Calgary , 3280 Hospital Drive NW, Calgary, Alberta Canada , T2N4Z6
- Ross University , School of Veterinarian Medicine, Box 334, Basseterre, St. Kitts West Indies
| | - Lisa Peters
- Stantec Consulting Ltd., 500-311 Portage Ave., Winnipeg, MB Canada R3B 2B9
| | - Vince Palace
- IISD-Experimental Lakes Area, 111 Lombard Ave., Suite 325 Winnipeg, MB Canada R3B 0T4
| | - Judit E G Smits
- Department of Ecosystem and Public Health, Faculty of Veterinary Medicine, University of Calgary , 3280 Hospital Drive NW, Calgary, Alberta Canada , T2N4Z6
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Yin P, Wang H, Vos T, Li Y, Liu S, Liu Y, Liu J, Wang L, Naghavi M, Murray CJL, Zhou M. A Subnational Analysis of Mortality and Prevalence of COPD in China From 1990 to 2013: Findings From the Global Burden of Disease Study 2013. Chest 2016; 150:1269-1280. [PMID: 27693597 DOI: 10.1016/j.chest.2016.08.1474] [Citation(s) in RCA: 76] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2016] [Revised: 08/22/2016] [Accepted: 08/31/2016] [Indexed: 11/30/2022] Open
Abstract
BACKGROUND The trends of COPD mortality and prevalence over the past 2 decades across all provinces remain unknown in China. We used data from the Global Burden of Disease Study 2013 (GBD 2013) to estimate the mortality and prevalence of COPD during 1990 to 2013 at a provincial level. METHODS Following the general analytic strategy used in GBD 2013, we analyzed the age- sex- and province-specific mortality and prevalence of COPD in China. Levels of and trends in COPD mortality and prevalence were assessed for 33 province-level administrative units during 1990 to 2013. RESULTS In 2013, there were 910,809 deaths from COPD in China, accounting for 31.1% of the total deaths from COPD in the world. From 1990 to 2013, the age-standardized COPD mortality rate decreased in all provinces, with the highest reduction in Heilongjiang (70.2%) and Jilin (70.0%) and the lowest reduction in Guizhou (26.8%). In 2013, the death rate per 100,000 was highest in Guizhou (196.0) and lowest in Tianjin (34.0) among men and highest in Gansu (141.1) and lowest in Beijing (23.7) among women. The number of COPD cases increased dramatically from 32.4 million in 1990 to 54.8 million in 2013. The age-standardized prevalence rate of COPD remained stable overall and varied little for all provinces. CONCLUSIONS COPD remains a huge health burden in many western provinces in China. The substantial increase in COPD cases represents an ongoing challenge given the rapidly aging Chinese population. A targeted control and prevention strategy should be developed at a provincial level to reduce the burden caused by COPD.
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Affiliation(s)
- Peng Yin
- National Center for Chronic and Noncommunicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Haidong Wang
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA
| | - Theo Vos
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA
| | - Yichong Li
- National Center for Chronic and Noncommunicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Shiwei Liu
- National Center for Chronic and Noncommunicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Yunning Liu
- National Center for Chronic and Noncommunicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Jiangmei Liu
- National Center for Chronic and Noncommunicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Lijun Wang
- National Center for Chronic and Noncommunicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Mohsen Naghavi
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA
| | | | - Maigeng Zhou
- National Center for Chronic and Noncommunicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China.
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Fang X, Li R, Kan H, Bottai M, Fang F, Cao Y. Bayesian model averaging method for evaluating associations between air pollution and respiratory mortality: a time-series study. BMJ Open 2016; 6:e011487. [PMID: 27531727 PMCID: PMC5013441 DOI: 10.1136/bmjopen-2016-011487] [Citation(s) in RCA: 8] [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: 11/30/2022] Open
Abstract
OBJECTIVE To demonstrate an application of Bayesian model averaging (BMA) with generalised additive mixed models (GAMM) and provide a novel modelling technique to assess the association between inhalable coarse particles (PM10) and respiratory mortality in time-series studies. DESIGN A time-series study using regional death registry between 2009 and 2010. SETTING 8 districts in a large metropolitan area in Northern China. PARTICIPANTS 9559 permanent residents of the 8 districts who died of respiratory diseases between 2009 and 2010. MAIN OUTCOME MEASURES Per cent increase in daily respiratory mortality rate (MR) per interquartile range (IQR) increase of PM10 concentration and corresponding 95% confidence interval (CI) in single-pollutant and multipollutant (including NOx, CO) models. RESULTS The Bayesian model averaged GAMM (GAMM+BMA) and the optimal GAMM of PM10, multipollutants and principal components (PCs) of multipollutants showed comparable results for the effect of PM10 on daily respiratory MR, that is, one IQR increase in PM10 concentration corresponded to 1.38% vs 1.39%, 1.81% vs 1.83% and 0.87% vs 0.88% increase, respectively, in daily respiratory MR. However, GAMM+BMA gave slightly but noticeable wider CIs for the single-pollutant model (-1.09 to 4.28 vs -1.08 to 3.93) and the PCs-based model (-2.23 to 4.07 vs -2.03 vs 3.88). The CIs of the multiple-pollutant model from two methods are similar, that is, -1.12 to 4.85 versus -1.11 versus 4.83. CONCLUSIONS The BMA method may represent a useful tool for modelling uncertainty in time-series studies when evaluating the effect of air pollution on fatal health outcomes.
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Affiliation(s)
- Xin Fang
- Unit of Biostatistics, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Runkui Li
- College of Resources and Environment, University of Chinese Academy of Sciences, Beijing, China
- State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China
| | - Haidong Kan
- Key Laboratory of Public Health Safety of the Ministry of Education and Key Laboratory of Health Technology Assessment of the Ministry of Health, School of Public Health, Fudan University, Shanghai, China
- Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention (LAP), Fudan University, Shanghai, China
| | - Matteo Bottai
- Unit of Biostatistics, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Fang Fang
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Yang Cao
- Unit of Biostatistics, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
- Clinical Epidemiology and Biostatistics, School of Medical Sciences, Örebro University, Örebro, Sweden
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Liu L, Yang X, Liu H, Wang M, Welles S, Márquez S, Frank A, Haas CN. Spatial-Temporal Analysis of Air Pollution, Climate Change, and Total Mortality in 120 Cities of China, 2012-2013. Front Public Health 2016; 4:143. [PMID: 27486572 PMCID: PMC4947578 DOI: 10.3389/fpubh.2016.00143] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2016] [Accepted: 06/22/2016] [Indexed: 11/13/2022] Open
Abstract
China has had a rapid increase in its economy over the past three decades. However, the economic boom came at a certain cost of depleting air quality. In the study, we aimed to examine the burden of air pollution and its association with climatic factors and health outcomes using data from Chinese national and city-level air quality and public health surveillance systems. City-level daily air pollution index (API, a sum weighted index of SO2, NO2, PM10, CO, and Ozone) in 120 cities in 2012 and 2013, and its association with climate factors were analyzed using multiple linear regression analysis, spatial autocorrelation analysis, and panel fixed models. City-level ecological association between annual average API and total mortality were examined using univariate and partial correlation analysis. Sensitivity analysis was conducted by taking the consideration of time-lag effect between exposures and outcomes. The results show that among the 120 cities, annual average API significantly increased from 2012 to 2013 (65.05 vs. 75.99, p < 0.0001). The highest average API was in winter, and the lowest in summer. A significantly spatial clustering of elevated API was observed, with the highest API in northwest China in 2012 and with the highest in east China in 2013. In 2012, 5 (4%) of the 120 cities had ≥60 days with API >100 (defined as "slightly polluted"), however, it increased to 21 cities (18%) that experienced API >100 for ≥60 days in 2013. Furthermore, 16 cities (13%) in 2012 and 35 (29%) in 2013 experienced a maximum API >300 (defined as "severely polluted"). API was negatively and significantly correlated with heat index, precipitation, and sunshine hours, but positively with air pressure. Cities with higher API concentrations had significantly higher total mortality rates than those with lower API. About a 4-7% of the variation in total mortality could be explained by the difference in API across the nation. In conclusion, the study highlights an increased trend of air pollution from 2012 to 2013 in China. The magnitude of air pollution varied by seasons and regions and correlated with climatic factors and total mortality across the country.
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Affiliation(s)
- Longjian Liu
- Department of Epidemiology and Biostatistics, Drexel University Dornsife School of Public Health , Philadelphia, PA , USA
| | - Xuan Yang
- Department of Epidemiology and Biostatistics, Drexel University Dornsife School of Public Health , Philadelphia, PA , USA
| | - Hui Liu
- Department of Epidemiology and Biostatistics, Drexel University Dornsife School of Public Health , Philadelphia, PA , USA
| | - Mingquan Wang
- Shanghai Advanced Research Institute, Chinese Academy of Sciences , Shanghai , China
| | - Seth Welles
- Department of Epidemiology and Biostatistics, Drexel University Dornsife School of Public Health , Philadelphia, PA , USA
| | - Shannon Márquez
- Department of Environmental and Occupational Health, Drexel University Dornsife School of Public Health , Philadelphia, PA , USA
| | - Arthur Frank
- Department of Environmental and Occupational Health, Drexel University Dornsife School of Public Health , Philadelphia, PA , USA
| | - Charles N Haas
- Department of Civil, Architectural, and Environmental Engineering, Drexel University College of Engineering , Philadelphia, PA , USA
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Morakinyo OM, Mokgobu MI, Mukhola MS, Hunter RP. Health Outcomes of Exposure to Biological and Chemical Components of Inhalable and Respirable Particulate Matter. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2016; 13:ijerph13060592. [PMID: 27314370 PMCID: PMC4924049 DOI: 10.3390/ijerph13060592] [Citation(s) in RCA: 93] [Impact Index Per Article: 11.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/14/2016] [Revised: 06/03/2016] [Accepted: 06/08/2016] [Indexed: 02/04/2023]
Abstract
Particulate matter (PM) is a key indicator of air pollution and a significant risk factor for adverse health outcomes in humans. PM is not a self-contained pollutant but a mixture of different compounds including chemical and biological fractions. While several reviews have focused on the chemical components of PM and associated health effects, there is a dearth of review studies that holistically examine the role of biological and chemical components of inhalable and respirable PM in disease causation. A literature search using various search engines and (or) keywords was done. Articles selected for review were chosen following predefined criteria, to extract and analyze data. The results show that the biological and chemical components of inhalable and respirable PM play a significant role in the burden of health effects attributed to PM. These health outcomes include low birth weight, emergency room visit, hospital admission, respiratory and pulmonary diseases, cardiovascular disease, cancer, non-communicable diseases, and premature death, among others. This review justifies the importance of each or synergistic effects of the biological and chemical constituents of PM on health. It also provides information that informs policy on the establishment of exposure limits for PM composition metrics rather than the existing exposure limits of the total mass of PM. This will allow for more effective management strategies for improving outdoor air quality.
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Affiliation(s)
- Oyewale Mayowa Morakinyo
- Department of Environmental Health, Faculty of Science, Tshwane University of Technology, Private Bag X680, Pretoria 0001, South Africa.
| | - Matlou Ingrid Mokgobu
- Department of Environmental Health, Faculty of Science, Tshwane University of Technology, Private Bag X680, Pretoria 0001, South Africa.
| | - Murembiwa Stanley Mukhola
- Department of Environmental Health, Faculty of Science, Tshwane University of Technology, Private Bag X680, Pretoria 0001, South Africa.
| | - Raymond Paul Hunter
- Department of Environmental Health, Faculty of Science, Tshwane University of Technology, Private Bag X680, Pretoria 0001, South Africa.
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Factors Affecting Parent's Perception on Air Quality-From the Individual to the Community Level. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2016; 13:ijerph13050493. [PMID: 27187432 PMCID: PMC4881118 DOI: 10.3390/ijerph13050493] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/26/2016] [Revised: 05/03/2016] [Accepted: 05/06/2016] [Indexed: 11/17/2022]
Abstract
The perception of air quality significantly affects the acceptance of the public of the government’s environmental policies. The aim of this research is to explore the relationship between the perception of the air quality of parents and scientific monitoring data and to analyze the factors that affect parents’ perceptions. Scientific data of air quality were obtained from Wuhan’s environmental condition reports. One thousand parents were investigated for their knowledge and perception of air quality. Scientific data show that the air quality of Wuhan follows an improving trend in general, while most participants believed that the air quality of Wuhan has deteriorated, which indicates a significant difference between public perception and reality. On the individual level, respondents with an age of 40 or above (40 or above: OR = 3.252; 95% CI: 1.170–9.040), a higher educational level (college and above: OR = 7.598; 95% CI: 2.244–25.732) or children with poor healthy conditions (poor: OR = 6.864; 95% CI: 2.212–21.302) have much more negative perception of air quality. On the community level, industrial facilities, vehicles and city construction have major effects on parents’ perception of air quality. Our investigation provides baseline information for environmental policy researchers and makers regarding the public’s perception and expectation of air quality and the benefits to the environmental policy completing and enforcing.
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Zúñiga J, Tarajia M, Herrera V, Urriola W, Gómez B, Motta J. Assessment of the Possible Association of Air Pollutants PM10, O3, NO2 With an Increase in Cardiovascular, Respiratory, and Diabetes Mortality in Panama City: A 2003 to 2013 Data Analysis. Medicine (Baltimore) 2016; 95:e2464. [PMID: 26765444 PMCID: PMC4718270 DOI: 10.1097/md.0000000000002464] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/25/2022] Open
Abstract
In recent years, Panama has experienced a marked economic growth, and this, in turn, has been associated with rapid urban development and degradation of air quality. This study is the first evaluation done in Panama on the association between air pollution and mortality. Our objective was to assess the possible association between monthly levels of PM10, O3, and NO2, and cardiovascular, respiratory, and diabetes mortality, as well as the seasonal variation of mortality in Panama City, Panama.The study was conducted in Panama City, using air pollution data from January 2003 to December 2013. We utilized a Poisson regression model based on generalized linear models, to evaluate the association between PM10, NO2, and O3 exposure and mortality from diabetes, cardiovascular, and respiratory diseases. The sample size for PM10, NO2, and O2 was 132, 132, and 108 monthly averages, respectively.We found that levels of PM10, O3, and NO2 were associated with increases in cardiovascular, respiratory, and diabetes mortality. For PM10 levels ≥ 40 μg/m3, we found an increase in cardiovascular mortality of 9.7% (CI 5.8-13.6%), and an increase of 12.6% (CI 0.2-24.2%) in respiratory mortality. For O3 levels ≥ 20 μg/m3 we found an increase of 32.4% (IC 14.6-52.9) in respiratory mortality, after a 2-month lag period following exposure in the 65 to <74 year-old age group. For NO2 levels ≥20 μg/m3 we found an increase in respiratory mortality of 11.2% (IC 1.9-21.3), after a 2-month lag period following exposure among those aged between 65 and <74 years.There could be an association between the air pollution in Panama City and an increase in cardiovascular, respiratory, and diabetes mortality. This study confirms the urgent need to improve the measurement frequency of air pollutants in Panama.
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Affiliation(s)
- Julio Zúñiga
- From the Gorgas Memorial Institute for Health Studies (JZ, VH, BG, JM); Centro de Biología Molecular y Celular de Enfermedades, Instituto de Investigaciones Científicas y Servicios de Alta Tecnología (MT); Región de Panamá Oeste, Caja de Seguro Social, Panama City, Panama (MT); and Institute of Specialized Analysis of the University of Panama, Miraflores, Panama City, Panama (WU)
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Madaniyazi L, Nagashima T, Guo Y, Yu W, Tong S. Projecting Fine Particulate Matter-Related Mortality in East China. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2015; 49:11141-11150. [PMID: 26226638 DOI: 10.1021/acs.est.5b01478] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/04/2023]
Abstract
China is suffering from severe air pollution from fine particulate matter [≤ 2.5 μm in aerodynamic diameter (PM2.5)], especially East China. But its future trends and potential health impacts remain unclear. The study objectives were to project future trends of PM2.5 and its short-term effect on mortality in East China by 2030. First, daily changes in PM2.5 concentrations between 2005 and 2030 were projected under the "current legislation" scenario (CLE) and the "maximum technically feasible reduction" scenario (MFR). Then, they were linked to six population projections, two mortality rate projections, and PM2.5-mortality associations to estimate the changes in PM2.5-related mortality in East China between 2005 and 2030. Under the CLE scenario, the annual mean PM2.5 concentration was projected to decrease by 0.62 μg/m(3) in East China, which could cause up to 124,000 additional deaths, when considering the population growth. Under the MFR scenario, the annual mean PM2.5 concentration was projected to decrease by 20.41 μg/m(3) in East China. At least 230,000 deaths could be avoided by such a large reduction in PM2.5 concentration under MFR scenario, even after accounting for the population growth. Therefore, our results suggest that reducing PM2.5 concentration substantially in East China would benefit the public health. Otherwise, it may still remain as a great health risk in the future, especially when the population keeps growing.
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Affiliation(s)
- Lina Madaniyazi
- Lina Madaniyazi, School of Public Health and Social Work, Queensland University of Technology , Kelvin Grove, Queensland 4059, Australia
| | - Tatsuya Nagashima
- Center for Regional Environmental Research (Regional Atmospheric Modeling Section), National Institute for Environmental Studies , 16-2 Onogawa, Tsukuba, Ibaraki 305-8506, Japan
| | - Yuming Guo
- School of Public Health, University of Queensland , Herston, Queensland 4006, Australia
| | - Weiwei Yu
- School of Public Health, University of Queensland , Herston, Queensland 4006, Australia
| | - Shilu Tong
- Lina Madaniyazi, School of Public Health and Social Work, Queensland University of Technology , Kelvin Grove, Queensland 4059, Australia
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Cen S. Biological Monitoring of Air Pollutants and Its Influence on Human Beings. Open Biomed Eng J 2015; 9:219-23. [PMID: 26628931 PMCID: PMC4645973 DOI: 10.2174/1874120701509010219] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2015] [Revised: 05/20/2015] [Accepted: 06/15/2015] [Indexed: 11/22/2022] Open
Abstract
Monitoring air pollutants via plants is an economic, convenient and credible method compared with the traditional ways. Plants show different damage symptoms to different air pollutants, which can be used to determine the species of air pollutants. Besides, pollutants mass concentration scope can be estimated by the damage extent of plants and the span of polluted time. Based on the domestic and foreign research, this paper discusses the principles, mechanism, advantages and disadvantages of plant-monitoring, and exemplifies plenty of such plants and the minimum mass concentration and pollution time of the plants showing damage symptoms. Finally, this paper introduced the human health effects of air pollutants on immune function of the body, such as decrease of the body's immune function, decline of lung function, respiratory and circulatory system changes, inducing and promoting human allergic diseases, respiratory diseases and other diseases.
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Affiliation(s)
- Shihong Cen
- Zhengzhou University of Industrial Technology, China
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Wang C, Chen R, Zhao Z, Cai J, Lu J, Ha S, Xu X, Chen X, Kan H. Particulate air pollution and circulating biomarkers among type 2 diabetic mellitus patients: the roles of particle size and time windows of exposure. ENVIRONMENTAL RESEARCH 2015; 140:112-118. [PMID: 25863184 DOI: 10.1016/j.envres.2015.03.026] [Citation(s) in RCA: 28] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/19/2014] [Revised: 03/23/2015] [Accepted: 03/25/2015] [Indexed: 06/04/2023]
Abstract
BACKGROUND Short-term associations between size-fractionated particulate matter (PM) air pollution and circulating biomarkers are not well established, especially among diabetes patients. METHODS We conducted a longitudinal panel study involving 6 repeated measurements of 12 circulating biomarkers among 35 diabetes patients from April to June, 2013 in Shanghai, China. Real-time number and mass concentrations of PM with multiple size fractions between 0.25 and 10 μm were measured. Linear mixed-effect models were used to explore the associations between size-fractionated PM concentrations and blood biomarkers at different time windows. RESULTS Short-term exposure to PM was significantly associated with elevated levels of 5 biomarkers of inflammation, 3 biomarkers of coagulation and 1 vasoconstrictor. The effects varied considerably by particle size and time windows. Overall, PM with smaller size had stronger associations, and the most significant size fractions were 0.25-0.40 μm. Even 2 h exposure to PM can lead to a significant increase in biomarkers. The effects on biomarkers of inflammation and vasoconstriction were restricted to the first 12h after exposure, but the effects on coagulation persisted for 24-72 h. For example, an interquartile range increase in 2h average exposure to PM(0.25-0.40) was associated with 6-20% increase in biomarkers of inflammation, 19-38% in coagulation and 17% in vasoconstriction. PM had a stronger effect among male patients than female patients. CONCLUSIONS Our results provided important evidence on the roles of the size and time windows of exposure in the PM-mediated effects on circulating biomarkers of inflammation, coagulation and vasoconstriction in diabetes patients in China.
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Affiliation(s)
- Cuicui Wang
- School of Public Health, Key Lab of Public Health Safety of the Ministry of Education, & Key Lab of Health Technology Assessment of the Ministry of Health, Fudan University, Shanghai, China; Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention (LAP(3)), Fudan University, Shanghai, China
| | - Renjie Chen
- School of Public Health, Key Lab of Public Health Safety of the Ministry of Education, & Key Lab of Health Technology Assessment of the Ministry of Health, Fudan University, Shanghai, China; Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention (LAP(3)), Fudan University, Shanghai, China
| | - Zhuohui Zhao
- School of Public Health, Key Lab of Public Health Safety of the Ministry of Education, & Key Lab of Health Technology Assessment of the Ministry of Health, Fudan University, Shanghai, China
| | - Jing Cai
- School of Public Health, Key Lab of Public Health Safety of the Ministry of Education, & Key Lab of Health Technology Assessment of the Ministry of Health, Fudan University, Shanghai, China; Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention (LAP(3)), Fudan University, Shanghai, China
| | - Jianxiong Lu
- Tianping Community Health Center, Xuhui District, Shanghai, China
| | - Sandie Ha
- School of Public Health, Key Lab of Public Health Safety of the Ministry of Education, & Key Lab of Health Technology Assessment of the Ministry of Health, Fudan University, Shanghai, China; Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention (LAP(3)), Fudan University, Shanghai, China; Tianping Community Health Center, Xuhui District, Shanghai, China
| | - Xiaohui Xu
- School of Public Health, Key Lab of Public Health Safety of the Ministry of Education, & Key Lab of Health Technology Assessment of the Ministry of Health, Fudan University, Shanghai, China; Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention (LAP(3)), Fudan University, Shanghai, China; Tianping Community Health Center, Xuhui District, Shanghai, China
| | - Xuan Chen
- Tianping Community Health Center, Xuhui District, Shanghai, China
| | - Haidong Kan
- School of Public Health, Key Lab of Public Health Safety of the Ministry of Education, & Key Lab of Health Technology Assessment of the Ministry of Health, Fudan University, Shanghai, China; Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention (LAP(3)), Fudan University, Shanghai, China.
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