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Tan Y, Yang Y, Zhang Y, Peng C, Zhang Y, He M, Peng A. Prenatal ambient air pollutants exposure and the risk of stillbirth in Wuhan, central of China. Environ Res 2023; 228:115841. [PMID: 37028538 DOI: 10.1016/j.envres.2023.115841] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/25/2023] [Revised: 03/26/2023] [Accepted: 04/03/2023] [Indexed: 05/16/2023]
Abstract
BACKGROUND The existing studies on the relationships of prenatal ambient air pollutants exposure with stillbirth in the Chinese population are very limited and the results are inconsistent, and the susceptible windows and potential modifiers for air pollutants exposure on stillbirth remain unanswered. OBJECTIVE We aimed to determine the relationships between exposure to ambient air pollutants and stillbirth, and explored the susceptible windows and potential modifiers for air pollutants exposure on stillbirth. METHODS A population-based cohort was established through the Wuhan Maternal and Child Health Management Information System involving 509,057 mother-infant pairs in Wuhan from January 1, 2011 through September 30, 2017. Personal exposure concentrations of fine particles (PM2.5), inhalable particles (PM10), sulfur dioxide (SO2), nitrogen dioxide (NO2), carbon monoxide (CO), and ozone (O3) for mothers were estimated based on their residential address during pregnancy using the inverse distance weighted (IDW) method. We used the logistic regression models to determine the associations at different stages of pregnancy with adjustment for confounding factors. RESULTS There were 3218 stillbirths and 505,839 live births among the participants. For each 100 μg/m3 of CO and 10 μg/m3 of O3 increase in the first trimester (conception to 13+6 weeks), the risk of stillbirth increased by 1.0% (OR = 1.01, 95%CI: 1.00-1.03) and 7.0% (OR = 1.07, 95%CI: 1.05-1.09). In the second trimester (14 weeks-27+6 weeks), PM2.5, PM10, CO, and O3 exposure were closely related to the risk of stillbirth (P<0.05). In the third trimester (28 weeks to delivery), for each 10 μg/m3 increase in exposure concentrations of PM2.5, SO2, and O3, the risk of stillbirth increased by 3.4%, 5.9%, and 4.0%, respectively. O3 exposure was positively relevant to the risk of stillbirth (OR = 1.11, 95%CI: 1.08-1.14) in the whole pregnancy. Exposure to NO2 was not significantly associated with the risk of stillbirth. Stratified analyses also presented a stronger association among mothers with boy infant, living in rural areas, delivering between 2011 and 2013, and those without gestational hypertension and history of stillbirth. CONCLUSION This study provides evidence that maternal exposure to PM2.5, PM10, SO2, CO, and O3 were related to the increased risk of stillbirth. Both the second and third trimesters might be vital susceptible windows for stillbirth. Our findings expand the evidence base for the important impacts of air pollution on fetal growth.
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Affiliation(s)
- Yafei Tan
- Wuhan Children's Hospital (Wuhan Maternal and Child Healthcare Hospital), Tongji Medical College, Huazhong University of Science & Technology, No. 100 Hongkong Road, Jiangan District, Wuhan, 430016, Hubei, China
| | - Yifan Yang
- Wuhan Children's Hospital (Wuhan Maternal and Child Healthcare Hospital), Tongji Medical College, Huazhong University of Science & Technology, No. 100 Hongkong Road, Jiangan District, Wuhan, 430016, Hubei, China
| | - Yu Zhang
- Wuhan Children's Hospital (Wuhan Maternal and Child Healthcare Hospital), Tongji Medical College, Huazhong University of Science & Technology, No. 100 Hongkong Road, Jiangan District, Wuhan, 430016, Hubei, China
| | - Chang Peng
- School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, No. 13 Hangkong Road, Qiaokou District, Wuhan, 430030, Hubei, China
| | - Yan Zhang
- Wuhan Children's Hospital (Wuhan Maternal and Child Healthcare Hospital), Tongji Medical College, Huazhong University of Science & Technology, No. 100 Hongkong Road, Jiangan District, Wuhan, 430016, Hubei, China
| | - Meian He
- School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, No. 13 Hangkong Road, Qiaokou District, Wuhan, 430030, Hubei, China.
| | - Anna Peng
- Wuhan Children's Hospital (Wuhan Maternal and Child Healthcare Hospital), Tongji Medical College, Huazhong University of Science & Technology, No. 100 Hongkong Road, Jiangan District, Wuhan, 430016, Hubei, China.
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Choo ELW, Janhavi A, Koo JR, Yim SHL, Dickens BL, Lim JT. Association between ambient air pollutants and upper respiratory tract infection and pneumonia disease burden in Thailand from 2000 to 2022: a high frequency ecological analysis. BMC Infect Dis 2023; 23:379. [PMID: 37280547 DOI: 10.1186/s12879-023-08185-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2022] [Accepted: 03/21/2023] [Indexed: 06/08/2023] Open
Abstract
BACKGROUND A pertinent risk factor of upper respiratory tract infections (URTIs) and pneumonia is the exposure to major ambient air pollutants, with short term exposures to different air pollutants being shown to exacerbate several respiratory conditions. METHODS Here, using disease surveillance data comprising of reported disease case counts at the province level, high frequency ambient air pollutant and climate data in Thailand, we delineated the association between ambient air pollution and URTI/Pneumonia burden in Thailand from 2000 - 2022. We developed mixed-data sampling methods and estimation strategies to account for the high frequency nature of ambient air pollutant concentration data. This was used to evaluate the effects past concentrations of fine particulate matter (PM2.5), sulphur dioxide (SO2), and carbon monoxide (CO) and the number of disease case count, after controlling for the confounding meteorological and disease factors. RESULTS Across provinces, we found that past increases in CO, SO2, and PM2.5 concentration were associated to changes in URTI and pneumonia case counts, but the direction of their association mixed. The contributive burden of past ambient air pollutants on contemporaneous disease burden was also found to be larger than meteorological factors, and comparable to that of disease related factors. CONCLUSIONS By developing a novel statistical methodology, we prevented subjective variable selection and discretization bias to detect associations, and provided a robust estimate on the effect of ambient air pollutants on URTI and pneumonia burden over a large spatial scale.
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Affiliation(s)
- Esther Li Wen Choo
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore
- Department of Biological Sciences, National University of Singapore, Singapore, Singapore
| | - A Janhavi
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore
- Department of Biological Sciences, National University of Singapore, Singapore, Singapore
| | - Joel Ruihan Koo
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore
| | - Steve H L Yim
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore
- Asian School of the Environment, Nanyang Technological University, Singapore, Singapore
- Earth Observatory of Singapore, Nanyang Technological University, Singapore, Singapore
| | - Borame L Dickens
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore.
| | - Jue Tao Lim
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore
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Lin Y, Gao Y, Sun X, Wang J, Ye S, Wu IXY, Xiao F. Long-term exposure to ambient air pollutants and their interaction with physical activity on insomnia: A prospective cohort study. Environ Res 2023; 224:115495. [PMID: 36813065 DOI: 10.1016/j.envres.2023.115495] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/11/2022] [Revised: 02/10/2023] [Accepted: 02/12/2023] [Indexed: 06/18/2023]
Abstract
Exposure to air pollution or lack of physical activity (PA) increases the risk of insomnia. However, evidence on joint exposure to air pollutants is limited, and the interaction of joint air pollutants and PA on insomnia is unknown. This prospective cohort study included 40,315 participants with related data from the UK Biobank, which recruited participants from 2006 to 2010. Insomnia was assessed by self-reported symptoms. The annual average air pollutant concentrations of particulate matter (PM2.5, PM10), nitrogen oxides (NO2, NOX), sulfur dioxide (SO2) and carbon monoxide (CO) were calculated based on participants' addresses. We applied a weighted Cox regression model to evaluate the correlation between air pollutants and insomnia and newly proposed an air pollution score to assess joint air pollutants effect using a weighted concentration summation after obtaining the weights of each pollutant in the Weighted-quantile sum regression. With a median follow-up of 8.7 years, 8511 participants developed insomnia. For each 10 μg/m³ increase in NO2, NOX, PM10, SO2, the average hazard ratios (AHRs) and 95% confidence interval (CI) of insomnia were 1.10 (1.06, 1.14), 1.06 (1.04, 1.08), 1.35 (1.25, 1.45) and 2.58 (2.31, 2.89), respectively; For each 5 μg/m³ increase in PM2.5 and each 1 mg/m³ increase in CO, the corresponding AHRs (95%CI) were 1.27 (1.21, 1.34) and 1.83 (1.10, 3.04), respectively. The AHR (95%CI) for insomnia associated with per interquartile range (IQR) increase in air pollution scores were 1.20 (1.15, 1.23). In addition, potential interactions were examined by setting cross-product terms of air pollution score with PA in the models. We observed an interaction between air pollution scores and PA (P = 0.032). The associations between joint air pollutants and insomnia were attenuated among participants with higher PA. Our study provides evidence on developing strategies for improving healthy sleep by promoting PA and reducing air pollution.
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Affiliation(s)
- Yijuan Lin
- Xiangya School of Public Health, Central South University, Changsha, 410078, PR China
| | - Yinyan Gao
- Xiangya School of Public Health, Central South University, Changsha, 410078, PR China
| | - Xuemei Sun
- Xiangya School of Public Health, Central South University, Changsha, 410078, PR China
| | - Jiali Wang
- Xiangya School of Public Health, Central South University, Changsha, 410078, PR China
| | - Shuzi Ye
- Xiangya School of Public Health, Central South University, Changsha, 410078, PR China
| | - Irene X Y Wu
- Xiangya School of Public Health, Central South University, Changsha, 410078, PR China
| | - Fang Xiao
- Xiangya School of Public Health, Central South University, Changsha, 410078, PR China.
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Wang XQ, Zhang KD, Yu WJ, Zhao JW, Huang K, Hu CY, Zhang XJ, Kan XH. Associations of exposures to air pollution and greenness with mortality in a newly treated tuberculosis cohort. Environ Sci Pollut Res Int 2023; 30:34229-34242. [PMID: 36504301 PMCID: PMC9742034 DOI: 10.1007/s11356-022-24433-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 06/27/2022] [Accepted: 11/23/2022] [Indexed: 06/17/2023]
Abstract
Some previous studies had linked air pollutants and greenness to the risk of death from tuberculosis (TB). Only a few studies had examined the effect of particulate matter (PM2.5) on the mortality of TB, and few studies had assessed the impact and interaction of multiple air pollutants and greenness on the mortality of newly treated TB patients. The study included 29,519 newly treated TB patients from three cities in Anhui province. We collected meteorological data and five pollutants data from The National Meteorological Science Center and air quality monitoring stations. Greenness data were generated by remote sensing inversion of medium-resolution satellite images. We geocoded each patient based on the residential address to calculate the average exposure to air pollutants and the average greenness exposure for each patient during treatment. The Cox proportional risk regression model was used to evaluate the effects of air pollutants and greenness on mortality in newly treated tuberculosis patients. Our results found that the higher the concentration of air pollutants in the living environment of newly treated TB patients, the greater the risk of death: HR 1.135 (95% CI: 1.123-1.147) and HR 1.333 (95% CI: 1.296-1.370) per 10 μg/m3 of PM2.5 and SO2, respectively. Greenness reduced the mortality among newly treated TB patients: HR for NDVI exposure 0.936 (95% CI: 0.925-0.947), HR for NDVI_250m exposure 0.927 (95% CI: 0.916-0.938), and HR for NDVI_500m exposure 0.919 (95% CI: 0.908-0.931). Stratifying the cohort by median greenness exposure, HRs for air pollutants were lower in the high greenness exposure group. Mortality in newly treated TB patients is influenced by air pollutants and greenness. Higher green exposure can mitigate the effects of air pollution. Improving air quality may help reduce mortality among newly treated TB patients.
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Affiliation(s)
- Xin-Qiang Wang
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, 230032, China
| | - Kang-Di Zhang
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, 230032, China
| | - Wen-Jie Yu
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, 230032, China
| | - Jia-Wen Zhao
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, 230032, China
| | - Kai Huang
- The Second Affiliated Hospital of Anhui Medical University, 678 Furong Road, Hefei, 230601, China
| | - Cheng-Yang Hu
- Department of Humanistic Medicine, School of Humanistic Medicine, Anhui Medical University, 81 Meishan Road, Hefei, 230032, China
| | - Xiu-Jun Zhang
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, 230032, China
| | - Xiao-Hong Kan
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, 230032, China.
- Clinical College of Chest, Anhui Chest Hospital, Anhui Medical University, 397 Jixi Road, Hefei, 230022, China.
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5
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Wu M, Pang Y, Chen M, Li L, Yan L, Ning J, Liu Q, Zhang Y, Jiang T, Kang A, Huang X, Hu W, Hu H, Geng Z, He L, Wang H, Wang M, Yang P, Chen J, Wu R, Shi B, Niu Y, Zhang R. Moderate physical activity against effects of short-term PM 2.5 exposure on BP via myokines-induced inflammation. Sci Total Environ 2023; 854:158598. [PMID: 36108849 DOI: 10.1016/j.scitotenv.2022.158598] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/11/2022] [Revised: 08/24/2022] [Accepted: 09/04/2022] [Indexed: 06/15/2023]
Abstract
Exposure to PM2.5 increases blood pressure (BP) and cardiovascular morbidity and mortality. We conducted a randomized controlled panel study in Shijiazhuang, China among 55 healthy college students randomly assigned to either the control (CON) or SPORTS group with intervention of 2000 m jogging in 20 min for 3 times in 4 days, and 3-round health examinations from November 15, 2020 to December 6, 2020. We aimed to evaluate whether moderate physical activity (PA) protected BP health against PM2.5 exposure and explore potential mechanisms through myokines and inflammation. Individual PM2.5 exposure was calculated based on outdoor and indoor PM2.5 concentration monitoring data as well as time-activity diary of each subject. In the CON group, the exposure-response curve for SBP was linear with a threshold concentration of approximately 31 μg/m3, while an increment of SBP level was 4.38 mm Hg (95%CI: 0.17 mm Hg, 8.59 mm Hg) at lag03 for each 10-μg/m3 increase in PM2.5, using linear mixed-effect models. For inflammatory indicators, PM2.5 exposure was associated with significant increases in eosinophil counts and proportion in CON group, but decreases in MCP-1 and TNF-α in SPORTS group. Meanwhile, higher myokines including CLU and IL-6 were observed in SPORTS group compared to the CON group. Further mediation analyses revealed that eosinophil counts mediated the elevated BP in CON group, whereas MCP-1 and TNF-α were also crucial mediating cytokines for the SPORTS group, as well as CLU and IL-6 acted as mediators on BP and inflammation indicators in SPORTS group. This study suggests that moderate PA could counteract the elevated BP induced by PM2.5 exposure via myokines-suppressed inflammation pathways.
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Affiliation(s)
- Mengqi Wu
- Department of Toxicology, Hebei Medical University, Shijiazhuang 050017, Hebei, China
| | - Yaxian Pang
- Department of Toxicology, Hebei Medical University, Shijiazhuang 050017, Hebei, China
| | - Meiyu Chen
- Department of Toxicology, Hebei Medical University, Shijiazhuang 050017, Hebei, China
| | - Lipeng Li
- Department of Toxicology, Hebei Medical University, Shijiazhuang 050017, Hebei, China; Department of Reproductive Medicine, The Second Hospital of Hebei Medical University, Shijiazhuang 050017, Hebei, China
| | - Lina Yan
- Department of Toxicology, Hebei Medical University, Shijiazhuang 050017, Hebei, China
| | - Jie Ning
- Department of Toxicology, Hebei Medical University, Shijiazhuang 050017, Hebei, China
| | - Qingping Liu
- Department of Toxicology, Hebei Medical University, Shijiazhuang 050017, Hebei, China
| | - Yaling Zhang
- Department of Toxicology, Hebei Medical University, Shijiazhuang 050017, Hebei, China
| | - Tao Jiang
- Department of Toxicology, Hebei Medical University, Shijiazhuang 050017, Hebei, China
| | - Aijuan Kang
- Department of Occupational Health and Environmental Health, Hebei Medical University, Shijiazhuang 050017, Hebei, China
| | - Xiaoyan Huang
- Department of Occupational Health and Environmental Health, Hebei Medical University, Shijiazhuang 050017, Hebei, China
| | - Wentao Hu
- Department of Toxicology, Hebei Medical University, Shijiazhuang 050017, Hebei, China
| | - Huaifang Hu
- Department of Toxicology, Hebei Medical University, Shijiazhuang 050017, Hebei, China
| | - Zihan Geng
- Department of Occupational Health and Environmental Health, Hebei Medical University, Shijiazhuang 050017, Hebei, China
| | - Liyi He
- Department of Occupational Health and Environmental Health, Hebei Medical University, Shijiazhuang 050017, Hebei, China
| | - Hui Wang
- Department of Occupational Health and Environmental Health, Hebei Medical University, Shijiazhuang 050017, Hebei, China
| | - Mengruo Wang
- Department of Toxicology, Hebei Medical University, Shijiazhuang 050017, Hebei, China
| | - Peihao Yang
- Department of Toxicology, Hebei Medical University, Shijiazhuang 050017, Hebei, China
| | - Jiawei Chen
- Department of Occupational Health and Environmental Health, Hebei Medical University, Shijiazhuang 050017, Hebei, China
| | - Ruiting Wu
- Department of Occupational Health and Environmental Health, Hebei Medical University, Shijiazhuang 050017, Hebei, China
| | - Beibei Shi
- Department of Occupational Health and Environmental Health, Hebei Medical University, Shijiazhuang 050017, Hebei, China
| | - Yujie Niu
- Department of Occupational Health and Environmental Health, Hebei Medical University, Shijiazhuang 050017, Hebei, China; Hebei Key Laboratory of Environment and Human Health, Hebei Medical University, Shijiazhuang 050017, Hebei, China
| | - Rong Zhang
- Department of Toxicology, Hebei Medical University, Shijiazhuang 050017, Hebei, China; Hebei Key Laboratory of Environment and Human Health, Hebei Medical University, Shijiazhuang 050017, Hebei, China.
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Puvvula J, Poole JA, Gonzalez S, Rogan EG, Gwon Y, Rorie AC, Ford LB, Bell JE. Joint association between ambient air pollutant mixture and pediatric asthma exacerbations. Environ Epidemiol 2022; 6:e225. [PMID: 36249268 DOI: 10.1097/EE9.0000000000000225] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2022] [Accepted: 07/07/2022] [Indexed: 11/23/2022] Open
Abstract
Exposure to air pollutants is known to exacerbate asthma, with prior studies focused on associations between single pollutant exposure and asthma exacerbations. As air pollutants often exist as a complex mixture, there is a gap in understanding the association between complex air pollutant mixtures and asthma exacerbations. We evaluated the association between the air pollutant mixture (52 pollutants) and pediatric asthma exacerbations. Method This study focused on children (age ≤ 19 years) who lived in Douglas County, Nebraska, during 2016-2019. A seasonal-scale joint association between the outdoor air pollutant mixture adjusting for potential confounders (temperature, precipitation, wind speed, and wind direction) in relation to pediatric asthma exacerbation-related emergency department (ED) visits was evaluated using the generalized weighted quantile sum (qWQS) regression with repeated holdout validation. Results We observed associations between air pollutant mixture and pediatric asthma exacerbations during spring (lagged by 5 days), summer (lag 0-5 days), and fall (lag 1-3 days) seasons. The estimate of the joint outdoor air pollutant mixture effect was higher during the summer season (adjusted-βWQS = 1.11, 95% confidence interval [CI]: 0.66, 1.55), followed by spring (adjusted-βWQS = 0.40, 95% CI: 0.16, 0.62) and fall (adjusted-βWQS = 0.20, 95% CI: 0.06, 0.33) seasons. Among the air pollutants, PM2.5, pollen, and mold contributed higher weight to the air pollutant mixture. Conclusion There were associations between outdoor air pollutant mixture and pediatric asthma exacerbations during the spring, summer, and fall seasons. Among the 52 outdoor air pollutant metrics investigated, PM2.5, pollen (sycamore, grass, cedar), and mold (Helminthosporium, Peronospora, and Erysiphe) contributed the highest weight to the air pollutant mixture.
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Wang XQ, Li YQ, Hu CY, Huang K, Ding K, Yang XJ, Cheng X, Zhang KD, Yu WJ, Wang J, Zhang YZ, Ding ZT, Zhang XJ, Kan XH. Short-term effect of ambient air pollutant change on the risk of tuberculosis outpatient visits: a time-series study in Fuyang, China. Environ Sci Pollut Res Int 2022; 29:30656-30672. [PMID: 34993790 DOI: 10.1007/s11356-021-17323-7] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/05/2021] [Accepted: 10/29/2021] [Indexed: 06/14/2023]
Abstract
There is growing evidence that air pollution plays a role in TB, and most studies have been conducted in the core countries with inconsistent results. Few studies have comprehensively included the six common air pollutants, so they cannot consider whether various pollutants interact with each other. Our objectives were to investigate the association between short-term exposure to six common air pollutants and the risk of tuberculosis outpatient visits in Fuyang, China, 2015-2020. We combined the two models to explore the effects of exposure to six air pollutants on the risk of tuberculosis outpatient visits, including the Poisson generalized linear regression model and distributed lag non-linear model (DLNM). We performed stratified analyses for the season, type of cases, gender, and age. We used the lag-specific relative risks and cumulative relative risk obtained by increasing pollutant concentration by per 10 units to evaluate the connection between six air pollutants and TB; PM2.5 (RR = 1.0018, 95% CI: 1.0004-1.0032, delay of 12 days) and SO2 (RR = 1.0169, 95% CI: 1.0007-1.0333, lag 0-16 days) were 0.9549 (95% CI: 0.9389-0.9712, lag 0 day) and 0.8212 (95% CI: 0.7351-0.9173, 0-20-day lag). Stratified analyses showed that seasonal differences had a greater impact on TB, males were more likely to develop TB than females, older people were more likely to develop TB than younger people, and air pollution had a great impact on new cases. Exposure to O3, CO, PM10, PM2.5, and NO2 increases the risk of TB outpatient visits, except SO2 which reduces the risk. The incidence of TB has seasonal fluctuations. It is necessary for the government to establish a sound environmental monitoring and early warning system to strengthen the monitoring and emission management of pollutants in the atmosphere. Management, prevention, and treatment measures should be developed for high-risk groups (males and older people), reducing the risk of TB by reducing their specific behaviors and changing their lifestyle. We need to pay more attention to the impact of seasonal effects on TB to protect TB patients and avoid a shortage of medical resources, and it is necessary for the government to develop some seasonal preventive measures in the future.
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Affiliation(s)
- Xin-Qiang Wang
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, 230032, China
| | - Ying-Qing Li
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, 230032, China
| | - Cheng-Yang Hu
- Department of Humanistic Medicine, School of Humanistic Medicine, Anhui Medical University, 81 Meishan Road, Hefei, 230032, China
| | - Kai Huang
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, 230032, China
| | - Kun Ding
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, 230032, China
| | - Xiao-Jing Yang
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, 230032, China
| | - Xin Cheng
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, 230032, China
| | - Kang-Di Zhang
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, 230032, China
| | - Wen-Jie Yu
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, 230032, China
| | - Jie Wang
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, 230032, China
| | - Yong-Zhong Zhang
- Anhui Institute of Tuberculosis Prevention and Control, 397 Jixi Road, Hefei, 230022, China
| | - Zhen-Tao Ding
- Fuyang Provincial Center for Disease Control and Prevention, 19 Zhongnan Avenue, Fuyang, 236030, China
| | - Xiu-Jun Zhang
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, 230032, China.
| | - Xiao-Hong Kan
- Anhui Medical University Clinical College of Chest, 397 Jixi Road, Hefei, 230022, China.
- Anhui Chest Hospital, 397 Jixi Road, Hefei, 230022, China.
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Gorrochategui E, Hernandez I, Pérez-Gabucio E, Lacorte S, Tauler R. Temporal air quality (NO 2, O 3, and PM 10) changes in urban and rural stations in Catalonia during COVID-19 lockdown: an association with human mobility and satellite data. Environ Sci Pollut Res Int 2022; 29:18905-18922. [PMID: 34705210 PMCID: PMC8549430 DOI: 10.1007/s11356-021-17137-7] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/21/2021] [Accepted: 10/17/2021] [Indexed: 05/09/2023]
Abstract
In this study, changes in air quality by NO2, O3, and PM10 in Barcelona metropolitan area and other parts of Catalonia during the COVID-19 lockdown with respect to pre-lockdown and to previous years (2018 and 2019) were evaluated. Selected air monitoring stations included 3 urban (Gràcia, Vall d'Hebron, and Granollers), 1 control site (Fabra Observatory), 1 semi-urban (Manlleu), and 3 rural (Begur, Bellver de Cerdanya, and Juneda). NO2 lockdown levels showed a diminution, which in relative terms was maximum in two rural stations (Bellver de Cerdanya, - 63% and Begur, - 61%), presumably due to lower emissions from the ceasing hotel and ski resort activities during eastern holidays. In absolute terms and from an epidemiologic perspective, decrease in NO2, also reinforced by the high amount of rainfall registered in April 2020, was more relevant in the urban stations around Barcelona. O3 levels increased in the transited urban stations (Gràcia, + 42%, and Granollers, + 64%) due to the lower titration effect by NOx. PM10 lockdown levels decreased, mostly in Gràcia, Vall d'Hebron, and Granollers (- 35, - 39%, and - 39%, respectively) due to traffic depletion (- 90% in Barcelona's transport). Correlation among mobility index in Barcelona (- 100% in retail and recreation) and contamination was positive for NO2 and PM10 and negative for O3 (P < 0.001). Satellite images evidenced two hotspots of NO2 in Spain (Madrid and Barcelona) in April 2018 and 2019 that disappeared in 2020. Overall, the benefits of lockdown on air quality in Catalonia were evidenced with NO2, O3 and PM10 levels below WHOAQG values in most of stations opposed to the excess registered in previous years.
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Affiliation(s)
- Eva Gorrochategui
- Institute of Environmental Assessment and Water Research (IDAEA), Consejo Superior de Investigaciones Científicas (CSIC), 08034, Barcelona, Spain.
| | - Isabel Hernandez
- Direcció General de Qualitat Ambiental I Canvi Climàtic, Generalitat de Catalunya, Barcelona, Spain
| | - Eva Pérez-Gabucio
- Direcció General de Qualitat Ambiental I Canvi Climàtic, Generalitat de Catalunya, Barcelona, Spain
| | - Sílvia Lacorte
- Institute of Environmental Assessment and Water Research (IDAEA), Consejo Superior de Investigaciones Científicas (CSIC), 08034, Barcelona, Spain
| | - Romà Tauler
- Institute of Environmental Assessment and Water Research (IDAEA), Consejo Superior de Investigaciones Científicas (CSIC), 08034, Barcelona, Spain
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Xu M, Hu P, Chen R, Liu B, Chen H, Hou J, Ke L, Huang J, Ren H, Hu H. Association of long-term exposure to ambient air pollution with the number of tuberculosis cases notified: a time-series study in Hong Kong. Environ Sci Pollut Res Int 2022; 29:21621-21633. [PMID: 34767173 DOI: 10.1007/s11356-021-17082-5] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/08/2020] [Accepted: 10/13/2021] [Indexed: 05/25/2023]
Abstract
To analyze the association of long-term exposure to air pollution and its attributable risks with the number of tuberculosis (TB) cases notified, a quasi-Poisson regression model combined with a distributed lag nonlinear model (DLNM) was constructed using monthly data on air pollution and TB cases notified in Hong Kong from 1999 to 2018. Nonlinear relationships between PM10, PM2.5, and CO and TB cases notified were identified. The concentrations of PM10, PM2.5, and CO corresponding to the minimum numbers of TB cases notified (the minimum TB notification concentrations, MTNCs) were 58.3 μg/m3, 41.7 μg/m3, and 0.1 mg/m3, respectively. Compared with the MTNCs, the overall cumulative numbers of TB cases notified increased by 76.93% (95% CI: 13.08%, 176.83%), 88.81% (95% CI: 26.09%, 182.71%), and 233.43% (95% CI: 13.56%, 879.03%) for the 95th percentiles of PM10 and PM2.5 and for the 97.5th percentiles of CO, respectively. The TB notification rate attributed to concentration ranges above the 97.5th percentile of PM10, PM2.5, and CO was 3.38% (95% empirical confidence intervals [eCI]: 0.93%, 5.61%), 4.73% (95% eCI: 1.87%, 7.15%), and 3.34% (95% eCI: 0.29%, 5.83%), respectively. Long-term exposure to high concentrations of air pollution in Hong Kong may be associated with increases in the number of TB cases notified for this area.
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Affiliation(s)
- Man Xu
- School of Nursing, Hubei University of Chinese Medicine, 16 Huangjiahu West Road, Hongshan District, Wuhan City, 430065, Hubei Province, China
| | - Ping Hu
- Key Laboratory of Environment and Health (HUST), Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health (Incubation), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, Hubei, China
| | - Ruoling Chen
- Faculty of Education, Health and Wellbeing, University of Wolverhampton, Wolverhampton, UK
| | - Bing Liu
- Center of Health Administration and Development Studies, Hubei University of Medicine, Shiyan, 442000, Hubei, China
| | - Hongying Chen
- Biological Products Management Office, Hubei Provincial Center for Disease Control and Prevention, Wuhan, Hubei, China
| | - Jian Hou
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, 450052, Henan, China
| | - Li Ke
- Center of Health Administration and Development Studies, Hubei University of Medicine, Shiyan, 442000, Hubei, China
| | - Jiao Huang
- Center for Evidence-Based and Translational Medicine, Wuhan University Zhongnan Hospital, Wuhan, 430030, Hubei, China
| | - Hairong Ren
- School of Nursing, Hubei University of Chinese Medicine, 16 Huangjiahu West Road, Hongshan District, Wuhan City, 430065, Hubei Province, China.
| | - Hui Hu
- School of Nursing, Hubei University of Chinese Medicine, 16 Huangjiahu West Road, Hongshan District, Wuhan City, 430065, Hubei Province, China.
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Zhou L, Li L, Hao G, Li B, Yang S, Wang N, Liang J, Sun H, Ma S, Yan L, Zhao C, Wei Y, Niu Y, Zhang R. Sperm mtDNA copy number, telomere length, and seminal spermatogenic cells in relation to ambient air pollution: Results of a cross-sectional study in Jing-Jin-Ji region of China. J Hazard Mater 2021; 406:124308. [PMID: 33257117 DOI: 10.1016/j.jhazmat.2020.124308] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/03/2020] [Revised: 09/15/2020] [Accepted: 10/15/2020] [Indexed: 06/12/2023]
Abstract
Evidences on the association of air pollutants and semen quality were limited and mechanism-based biomarkers were sparse. We enrolled 423 men at a fertility clinic in Shijiazhuang, China to evaluate associations between air pollutants and semen quality parameters including the conventional ones, sperm mitochondrial DNA copy number (mtDNAcn), sperm telomere length (STL) and seminal spermatogenic cells. PM2.5, PM10, CO, SO2, NO2 and O3 exposure during lag0-90, lag0-9, lag10-14 and lag70-90 days were evaluated with ordinary Kringing model. The exposure-response correlations were analyzed with multiple linear regression models. CO, PM2.5 and PM10 were adversely associated with conventional semen parameters including sperm count, motility and morphology. Besides, CO was positively associated with seminal primary spermatocyte (lag70-90, 0.49; 0.14, 0.85) and mtDNAcn (lag0-90, 0.37; 0.12, 0.62, lag10-14, 0.31; 0.12, 0.49), negatively associated with STL (lag0-9, -0.30; -0.57, -0.03). PM2.5 was positively associated with mtDNAcn (0.50; 0.24, 0.75 and 0.38; 0.02, 0.75 for lag0-90 and lag70-90) while negatively associated with STL (lag70-90, -0.49; -0.96, -0.01). PM10 and NO2 were positively associated with mtDNAcn. Our findings indicate CO and PM might impair semen quality testicularly and post-testicularly while seminal spermatogenic cell, STL and mtDNAcn change indicate necessity for more attention on these mechanisms.
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Affiliation(s)
- Lixiao Zhou
- Department of Toxicology, School of Public Health, Hebei Medical University, Shijiazhuang 050017, PR China; School of Public Health and Management, Chongqing Medical University, Chongqing 400016, PR China
| | - Lipeng Li
- Department of Toxicology, School of Public Health, Hebei Medical University, Shijiazhuang 050017, PR China; Department of Reproductive Medicine, The Second Hospital of Hebei Medical University, Shijiazhuang 050017, PR China
| | - Guimin Hao
- Department of Reproductive Medicine, The Second Hospital of Hebei Medical University, Shijiazhuang 050017, PR China
| | - Binghua Li
- Department of Occupational Health and Environmental Health, School of Public Health, Hebei Medical University, Shijiazhuang 050017, PR China
| | - Sujuan Yang
- Department of Reproductive Medicine, The Second Hospital of Hebei Medical University, Shijiazhuang 050017, PR China
| | - Ning Wang
- Department of Reproductive Medicine, The Second Hospital of Hebei Medical University, Shijiazhuang 050017, PR China
| | - Jiaming Liang
- Department of Toxicology, School of Public Health, Hebei Medical University, Shijiazhuang 050017, PR China
| | - Hongyue Sun
- Department of Toxicology, School of Public Health, Hebei Medical University, Shijiazhuang 050017, PR China
| | - Shitao Ma
- Department of Occupational Health and Environmental Health, School of Public Health, Hebei Medical University, Shijiazhuang 050017, PR China
| | - Lina Yan
- Department of Toxicology, School of Public Health, Hebei Medical University, Shijiazhuang 050017, PR China
| | - Chunfang Zhao
- Department of Histology and Embryology, Schoolof Basic Medical Science, Hebei Medical University, Shijiazhuang 050017, PR China
| | - Yanjing Wei
- Department of Laboratory Diagnostics, School of Basic Medical Science, Hebei Medical University, Shijiazhuang 050017, PR China
| | - Yujie Niu
- Department of Occupational Health and Environmental Health, School of Public Health, Hebei Medical University, Shijiazhuang 050017, PR China; Hebei Key Laboratory of Environment and Human Health, Shijiazhuang 050017, PR China
| | - Rong Zhang
- Department of Toxicology, School of Public Health, Hebei Medical University, Shijiazhuang 050017, PR China; Hebei Key Laboratory of Environment and Human Health, Shijiazhuang 050017, PR China.
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11
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Hu Y, Yao M, Liu Y, Zhao B. Personal exposure to ambient PM 2.5, PM 10, O 3, NO 2, and SO 2 for different populations in 31 Chinese provinces. Environ Int 2020; 144:106018. [PMID: 32771828 DOI: 10.1016/j.envint.2020.106018] [Citation(s) in RCA: 41] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/10/2020] [Revised: 07/04/2020] [Accepted: 07/27/2020] [Indexed: 05/06/2023]
Abstract
Most epidemiological studies usually employ ambient air pollutant concentrations as a proxy of personal exposure to air pollutants originating outdoors, which could lead to a biased estimation of health effects. Herein, we modeled infiltration and exposure factors as the modifications of personal exposure to ambient PM2.5, PM10, O3, NO2, and SO2 for all seasons, genders, and ages in 31 Chinese provinces. The annual average exposure factors of PM10, PM2.5, O3, NO2, and SO2 were 0.42 ± 0.13 (arithmetic mean ± standard deviation), 0.68 ± 0.14, 0.34 ± 0.12, 0.50 ± 0.14, and 0.40 ± 0.13, respectively. We observed significant age, gender, seasonal, and geographical differences in infiltration and exposure factors for all studied ambient air pollutants. These factors were higher in southern China than in the north, and they were the highest in summer and the lowest in winter. The exposure factor of minors (age < 18 years) was significantly lower than that of adults (age ≥ 18 years, P < 0.01). Adult males had higher exposure factors than females (P < 0.01). Epidemiological studies utilizing outdoor concentrations of air pollutants could overestimate personal exposure to these pollutants. The present study could help in reducing the bias in the estimation of the health effects of air pollutants.
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Affiliation(s)
- Ying Hu
- Department of Building Science, School of Architecture, Tsinghua University, Beijing 100084, China
| | - Mingyao Yao
- Department of Building Science, School of Architecture, Tsinghua University, Beijing 100084, China
| | - Yumeng Liu
- Department of Building Science, School of Architecture, Tsinghua University, Beijing 100084, China
| | - Bin Zhao
- Department of Building Science, School of Architecture, Tsinghua University, Beijing 100084, China; Beijing Key Laboratory of Indoor Air Quality Evaluation and Control, Tsinghua University, Beijing 100084, China.
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12
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Liu W, Cai J, Fu Q, Zou Z, Sun C, Zhang J, Huang C. Associations of ambient air pollutants with airway and allergic symptoms in 13,335 preschoolers in Shanghai, China. Chemosphere 2020; 252:126600. [PMID: 32234631 DOI: 10.1016/j.chemosphere.2020.126600] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/08/2019] [Revised: 03/14/2020] [Accepted: 03/22/2020] [Indexed: 06/11/2023]
Abstract
Findings are inconsistent in studies for impacts of outdoor air pollutants on airway health in childhood. In this paper, we collected data regarding airway and allergic symptoms in the past year before a survey in 13,335 preschoolers from a cross-sectional study. Daily averaged concentrations of ambient sulphur dioxide (SO2), nitrogen dioxide (NO2), and particulate matter with an aerodynamic diameter ≤10 μm (PM10) in the past year before the survey were collected in the kindergarten-located district. We investigated associations of 12-month average concentrations of these pollutants with childhood airway and allergic symptoms. In the two-level (district-child) logistic regression analyses, exposure to higher level of NO2 and of PM10 increased odds of wheeze symptoms (adjusted OR, 95%CI: 1.03, 1.01-1.05 for per 3.0 μg/m3 increase in NO2; 1.22, 1.09-1.39 for per 7.6 μg/m3 increase in PM10), wheeze with a cold (1.03, 1.01-1.06; 1.22, 1.08-1.39), dry cough during night (1.05, 1.03-1.08; 1.23, 1.09-1.40), rhinitis symptoms (1.11, 1.08-1.13; 1.32, 1.07-1.63), rhinitis on pet (1.11, 1.05-1.18; 1.37, 0.95-1.98) and pollen (1.12, 1.03-1.21; 1.23, 0.84-1.82) exposure, eczema symptoms (1.09, 1.05-1.12; 1.22, 0.98-1.52), and lack of sleep due to eczema (1.12, 1.07-1.18; 1.58, 1.25-1.98). Exposures to NO2 and PM10 were also significantly and positively associated with the accumulative score of airway symptoms. Similar positive associations were found of NO2 and of PM10 with the individual symptoms and symptom scores among preschoolers from different kindergarten-located district. These results indicate that ambient NO2 and PM10 likely are risk factors for airway and allergic symptoms in childhood in Shanghai, China.
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Affiliation(s)
- Wei Liu
- Institute for Health and Environment, Chongqing University of Science and Technology, Chongqing, China; School of Civil Engineering and Architecture, Chongqing University of Science and Technology, Chongqing, China
| | - Jiao Cai
- Joint International Research Laboratory of Green Buildings and Built Environments (Ministry of Education), Chongqing University, Chongqing, China
| | - Qingyan Fu
- Shanghai Environmental Monitoring Center, Shanghai, China
| | - Zhijun Zou
- Department of Building Environment and Energy Engineering, School of Environment and Architecture, University of Shanghai for Science and Technology, Shanghai, China
| | - Chanjuan Sun
- Department of Building Environment and Energy Engineering, School of Environment and Architecture, University of Shanghai for Science and Technology, Shanghai, China
| | - Jialing Zhang
- Department of Building Environment and Energy Engineering, School of Environment and Architecture, University of Shanghai for Science and Technology, Shanghai, China
| | - Chen Huang
- Department of Building Environment and Energy Engineering, School of Environment and Architecture, University of Shanghai for Science and Technology, Shanghai, China.
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Zhang L, An J, Liu M, Li Z, Liu Y, Tao L, Liu X, Zhang F, Zheng D, Gao Q, Guo X, Luo Y. Spatiotemporal variations and influencing factors of PM 2.5 concentrations in Beijing, China. Environ Pollut 2020; 262:114276. [PMID: 32179215 DOI: 10.1016/j.envpol.2020.114276] [Citation(s) in RCA: 30] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/11/2019] [Revised: 02/22/2020] [Accepted: 02/25/2020] [Indexed: 05/28/2023]
Abstract
Fine particulate matter (PM2.5) pollution has become a worldwide environmental concern because of its adverse impacts on human health. This study aimed to explore the spatiotemporal variations and influencing factors of PM2.5 concentrations in Beijing during the 2013-2018 period, and further analyzed the impacts of environmental protection policies implemented in recent years. Notably, this study employed various statistical methods, i.e., ordinary Kriging interpolation, spatial autocorrelation analysis, time-series analysis and the Bonferroni test, to evaluate the regional and seasonal differences of PM2.5 concentrations based on long-term monitoring data. The results illustrated that PM2.5 concentrations decreased on a yearly basis, demonstrating that air pollution control policies have achieved initial success. Furthermore, PM2.5 concentrations were higher in the winter and in the southern regions. Diurnal variation presented a bimodal distribution, which varied slightly with the season. Relative humidity and wind speed were the principal meteorological factors affecting the distribution of PM2.5 concentrations, while precipitation had essentially no effect. A high positive correlation between PM2.5 and gaseous pollutants (SO2, NO2, and CO) indirectly reflected the contribution of automobile exhaust and coal-fired emissions. Generally, PM2.5 concentrations demonstrated strong spatiotemporal variations, and meteorological factors and pollutant emissions played an important role in this.
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Affiliation(s)
- Licheng Zhang
- School of Public Health, Capital Medical University, No.10 Xitoutiao, Youanmen Wai Street, Fengtai District, Beijing, 100069, China
| | - Ji An
- School of Public Health, Capital Medical University, No.10 Xitoutiao, Youanmen Wai Street, Fengtai District, Beijing, 100069, China
| | - Mengyang Liu
- School of Public Health, Capital Medical University, No.10 Xitoutiao, Youanmen Wai Street, Fengtai District, Beijing, 100069, China
| | - Zhiwei Li
- School of Public Health, Capital Medical University, No.10 Xitoutiao, Youanmen Wai Street, Fengtai District, Beijing, 100069, China
| | - Yue Liu
- School of Public Health, Capital Medical University, No.10 Xitoutiao, Youanmen Wai Street, Fengtai District, Beijing, 100069, China
| | - Lixin Tao
- School of Public Health, Capital Medical University, No.10 Xitoutiao, Youanmen Wai Street, Fengtai District, Beijing, 100069, China
| | - Xiangtong Liu
- School of Public Health, Capital Medical University, No.10 Xitoutiao, Youanmen Wai Street, Fengtai District, Beijing, 100069, China
| | - Feng Zhang
- School of Public Health, Capital Medical University, No.10 Xitoutiao, Youanmen Wai Street, Fengtai District, Beijing, 100069, China
| | - Deqiang Zheng
- School of Public Health, Capital Medical University, No.10 Xitoutiao, Youanmen Wai Street, Fengtai District, Beijing, 100069, China
| | - Qi Gao
- School of Public Health, Capital Medical University, No.10 Xitoutiao, Youanmen Wai Street, Fengtai District, Beijing, 100069, China
| | - Xiuhua Guo
- School of Public Health, Capital Medical University, No.10 Xitoutiao, Youanmen Wai Street, Fengtai District, Beijing, 100069, China
| | - Yanxia Luo
- School of Public Health, Capital Medical University, No.10 Xitoutiao, Youanmen Wai Street, Fengtai District, Beijing, 100069, China.
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Faridi S, Niazi S, Yousefian F, Azimi F, Pasalari H, Momeniha F, Mokammel A, Gholampour A, Hassanvand MS, Naddafi K. Spatial homogeneity and heterogeneity of ambient air pollutants in Tehran. Sci Total Environ 2019; 697:134123. [PMID: 31484089 DOI: 10.1016/j.scitotenv.2019.134123] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/10/2019] [Revised: 07/14/2019] [Accepted: 08/25/2019] [Indexed: 06/10/2023]
Abstract
To investigate spatial inequality of ambient air pollutants and comparison of their heterogeneity and homogeneity across Tehran, the following quantitative indicators were utilized: coefficient of divergence (COD), the 90th percentile of the absolute differences between ambient air pollutant concentrations and coefficient of variation (CV). Real-time hourly concentrations of particulate matter (PM) and gaseous air pollutants (GAPs) of twenty-two air quality monitoring stations (AQMSs) were obtained from Tehran Air Quality Control Company (TAQCC) in 2017. Annual mean concentrations of PM2.5, PM10-2.5, and PM10 (PMX) ranged from 21.7 to 40.5, 37.3 to 75.0 and 58.0 to 110.4 μg m-3, respectively. Annual mean PM2.5 and PM10 concentrations were higher than the World Health Organization air quality guideline (WHO AQG) and national standard levels. NO2, O3, SO2 and CO annual mean concentrations ranged from 27.0 to 76.8, 15.5 to 25.1, 4.6 to 12.2 ppb, and 1.9 to 3.8 ppm over AQMSs, respectively. Our generated spatial maps exhibited that ambient PMX concentrations increased from the north into south and south-western areas as the hotspots of ambient PMX in Tehran. O3 hotspots were observed in the north and south-west, while NO2 hotspots were in the west and south. COD values of PMX demonstrated more results lower than the 0.2 cut off compared to GAPs; indicating high to moderate spatial homogeneity for PMX and moderate to high spatial heterogeneity for GAPs. Regarding CV approach, the spatial variabilities of air pollutants followed in the order of O3 (87.3%) > SO2 (65.2%) > CO (61.8%) > PM10-2.5 (52.5%) > PM2.5 (48.9%) > NO2 (48.1%) > PM10 (42.9%), which were mainly in agreement with COD results, except for NO2. COD values observed a statistically (P < 0.05) positive correlation with the values of the 90th percentile across AQMSs. Our study, for the first time, highlights spatial inequality of ambient PMX and GAPs in Tehran in detail to better facilitate establishing new intra-urban control policies.
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Affiliation(s)
- Sasan Faridi
- Centre for Air Pollution Research (CAPR), Institute for Environmental Research (IER), Tehran University of Medical Sciences, Tehran, Iran; Department of Environmental Health Engineering, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran
| | - Sadegh Niazi
- International Laboratory for Air Quality and Health, Queensland University of Technology (QUT), Brisbane, Queensland, Australia
| | - Fatemeh Yousefian
- Department of Environmental Health Engineering, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran
| | - Faramarz Azimi
- Nutrition Health Research Centre, Department of Environment Health, School of Health and Nutrition, Lorestan University of Medical Sciences, Khorramabad, Iran
| | - Hasan Pasalari
- Department of Environmental Health Engineering, School of Public Health, Iran University of Medical Sciences, Tehran, Iran
| | - Fatemeh Momeniha
- Department of Environmental Health Engineering, School of Public Health, Iran University of Medical Sciences, Tehran, Iran
| | - Adel Mokammel
- Department of Environmental Health Engineering, School of Public Health, Khalkhal University of Medical Sciences, Khalkhal, Iran
| | - Akbar Gholampour
- Department of Environmental Health Engineering, School of Public Health, Tabriz University of Medical Sciences, Tabriz, Iran
| | - Mohammad Sadegh Hassanvand
- Centre for Air Pollution Research (CAPR), Institute for Environmental Research (IER), Tehran University of Medical Sciences, Tehran, Iran; Department of Environmental Health Engineering, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran.
| | - Kazem Naddafi
- Centre for Air Pollution Research (CAPR), Institute for Environmental Research (IER), Tehran University of Medical Sciences, Tehran, Iran; Department of Environmental Health Engineering, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran.
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15
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Liu F, Qu F, Zhang H, Chao L, Li R, Yu F, Guan J, Yan X. The effect and burden modification of heating on adult asthma hospitalizations in Shijiazhuang: a time-series analysis. Respir Res 2019; 20:122. [PMID: 31200718 PMCID: PMC6570879 DOI: 10.1186/s12931-019-1092-0] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2018] [Accepted: 06/05/2019] [Indexed: 12/25/2022] Open
Abstract
Background Previous studies have found associations between asthma morbidity and air pollution especially in young population, (PLoS One 12:e0180522, 2017; Can J Public Health 103:4-8, 2012; Environ Health Perspect 118:449-57, 2010; Am J Respir Crit Care Med 182:307-16, 2010; J Allergy Clin Immunol 104:717-22, 2008; J Allergy Clin Immunol 104:717-22, 1999; Environ Res 111:1137-47, 2011) but most of them were conducted in areas with relatively low air pollutant level. Moreover, very few studies have investigated the effect and burden modification of heating season during which the ambient air pollution level is significantly different from that during non-heating season in north China. Objectives This study aimed to evaluate the effect and burden modification of heating on short-term associations between adult asthma hospitalizations and ambient air pollution in the north China city of Shijiazhuang. Methods Generalized additive models combined with penalized distributed lag nonlinear models were used to model associations between daily asthma hospitalizations and ambient air pollutants from 1 January 2013 to 16 December 2016 in Shijiazhuang city, adjusting for long-term and seasonality trend, day of week, statutory holiday, daily mean air pressure and temperature. Attributable risks were calculated to evaluate the burden of asthma hospitalizations due to air pollutants exposure. The effect of pollutants on hospitalization and the attributable measures were estimated in heating and non-heating season separately and the comparisons between the two seasons were conducted. Results All pollutants demonstrated positive and significant impacts on asthma hospitalizations both in heating season and non-heating season, except for O3 in heating season where a negative association was observed. However, the differences of the pollutant-specific effects between the two seasons were not significant. SO2 and NO2 exposure were associated with the heaviest burden among all pollutants in heating season; meanwhile, PM10 and PM2.5 were associated with the heaviest burden in heating season. Conclusions In conclusion, we found evidence of the effect of ambient air pollutants on asthma hospitalizations in Shijiazhuang. The central heating period could modify the effects in terms of attributable risks. The disease burden modification of heating should be taken into consideration when planning intervention measures to reduce the risk of asthma hospitalization.
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Affiliation(s)
- Feifei Liu
- The Second Hospital of Hebei Medical University, Shijiazhuang city, Hebei province, China
| | - Fangfang Qu
- The Second Hospital of Hebei Medical University, Shijiazhuang city, Hebei province, China
| | - Huiran Zhang
- The Second Hospital of Hebei Medical University, Shijiazhuang city, Hebei province, China
| | - Lingshan Chao
- The Second Hospital of Hebei Medical University, Shijiazhuang city, Hebei province, China
| | - Rongqin Li
- The Second Hospital of Hebei Medical University, Shijiazhuang city, Hebei province, China
| | - Fengxue Yu
- The Second Hospital of Hebei Medical University, Shijiazhuang city, Hebei province, China
| | - Jitao Guan
- The Second Hospital of Hebei Medical University, Shijiazhuang city, Hebei province, China
| | - Xixin Yan
- The Second Hospital of Hebei Medical University, Shijiazhuang city, Hebei province, China.
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Li H, Duan D, Xu J, Feng X, Astell-Burt T, He T, Xu G, Zhao J, Zhang L, You D, Han L. Ambient air pollution and risk of type 2 diabetes in the Chinese. Environ Sci Pollut Res Int 2019; 26:16261-16273. [PMID: 30977004 DOI: 10.1007/s11356-019-04971-z] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/12/2018] [Accepted: 03/22/2019] [Indexed: 06/09/2023]
Abstract
We performed a time series analysis to investigate the potential association between exposure to ambient air pollution and type 2 diabetes (T2D) incidence in the Chinese population. Monthly time series data between 2008 and 2015 on ambient air pollutants and incident T2D (N = 25,130) were obtained from the Environment Monitoring Center of Ningbo and the Chronic Disease Surveillance System of Ningbo. Relative risks (RRs) and 95% confidence intervals (95% CIs) of incident T2D per 10 μg/m3 increases in ambient air pollutants were estimated from Poisson generalized additive models. Exposure to particulate matter < 10 μm (PM10) and sulfur dioxide (SO2) was associated with increased T2D incidence. The relative risks (RRs) of each increment in 10 μg/m3 of PM10 and SO2 were 1.62 (95% CI, 1.16-2.28) and 1.63 (95% CI, 1.12-2.38) for overall participants, whereas for ozone (O3) exposure, the RRs were 0.78 (95% CI, 0.68-0.90) for overall participants, 0.78 (95% CI, 0.69-0.90) for males, and 0.78 (95% CI, 0.67-0.91) for females, respectively. Exposure to PM10 and SO2 is positively associated with T2D incidence, whereas O3 is negatively associated with T2D incidence.
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Affiliation(s)
- Hui Li
- Ningbo Municipal Center for Disease Control and Prevention, Ningbo, 315010, China
| | - Donghui Duan
- Ningbo Municipal Center for Disease Control and Prevention, Ningbo, 315010, China
| | - Jiaying Xu
- Department of Epidemiology, School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA, 70112, USA
| | - Xiaoqi Feng
- Population Wellbeing and Environment Research Lab (Power Lab), Faculty of Social Sciences, University of Wollongong, Wollongong, NSW, 2522, Australia
- Early Start, Faculty of Social Sciences, University of Wollongong, Wollongong, NSW, 2522, Australia
- Menzies Centre for Health Policy, University of Sydney, Sydney, NSW, 2006, Australia
| | - Thomas Astell-Burt
- Population Wellbeing and Environment Research Lab (Power Lab), Faculty of Social Sciences, University of Wollongong, Wollongong, NSW, 2522, Australia
- Early Start, Faculty of Social Sciences, University of Wollongong, Wollongong, NSW, 2522, Australia
- Menzies Centre for Health Policy, University of Sydney, Sydney, NSW, 2006, Australia
| | - Tianfeng He
- Ningbo Municipal Center for Disease Control and Prevention, Ningbo, 315010, China
| | - Guodong Xu
- Department of Preventive Medicine, Medical School of Ningbo University, Ningbo, 315211, China
| | - Jinshun Zhao
- Department of Preventive Medicine, Medical School of Ningbo University, Ningbo, 315211, China
| | - Lina Zhang
- Department of Preventive Medicine, Medical School of Ningbo University, Ningbo, 315211, China
| | - Dingyun You
- School of Public Health, Kunming Medical University, Kunming, China.
| | - Liyuan Han
- Department of Preventive Medicine, Medical School of Ningbo University, Ningbo, 315211, China
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Guo H, Yang W, Jiang L, Lyu Y, Cheng T, Gao B, Li X. Association of short-term exposure to ambient air pollutants with exhaled nitric oxide in hospitalized patients with respiratory-system diseases. Ecotoxicol Environ Saf 2019; 168:394-400. [PMID: 30396136 DOI: 10.1016/j.ecoenv.2018.10.094] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/17/2018] [Revised: 10/21/2018] [Accepted: 10/24/2018] [Indexed: 06/08/2023]
Abstract
BACKGROUND Previous studies have suggested that exposure to ambient air pollutants may adversely affect human health. However, few studies have examined the health effects of exposure to ambient air pollutants in hospitalized patients. OBJECTIVES To evaluate the association between short-term exposure to ambient air pollutants and exhaled nitric oxide fraction (FeNO) in a large cohort of hospitalized patients. METHODS FeNO was detected for 2986 hospitalized patients (ages 18-88 years). Daily average concentrations of SO2, NO2, O3, CO, PM2.5 and PM10 in 2014 and 2015 were obtained from nine fixed-site monitoring stations. Multiple linear regression models were chosen to assess the associations of exposure to ambient air pollutants with FeNO while adjusting for confounding variables. Lagged variable models were selected to determine the association between FeNO and ambient air pollutants concentrations with lags of up to 7 days prior to FeNO testing. RESULTS Interquartile-range (IQR) increases in the daily average SO2 (8.00 μg/m3) and PM2.5 (37.0 μg/m3) were strongly associated with increases in FeNO, with increases of 3.41% [95% confidence interval (CI), 0.94-5.93%] and 2.72% (95%CI, -0.09% to 5.61%), respectively. However, FeNO levels were not statistically associated with PM10, NO2, O3 or CO. In the two-pollutant models, the maximum correlation was for ambient SO2. We also found that FeNO was associated with IQR increases in daily average ambient concentrations of SO2 up to 3 and 4 days after the exposure events. CONCLUSIONS Short-term exposure to SO2 and PM2.5 were positively correlated with FeNO levels in hospitalized patients in Shanghai.
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Affiliation(s)
- Huibin Guo
- Department of Environmental Science & Engineering, Fudan University, Shanghai 200438, PR China
| | - Wenlan Yang
- Department of Respiratory Medicine, Shanghai Pulmonary Hospital, Tongji University School of Medicine, Shanghai 200433, China
| | - Li Jiang
- Department of Environmental Science & Engineering, Fudan University, Shanghai 200438, PR China
| | - Yan Lyu
- Department of Environmental Science & Engineering, Fudan University, Shanghai 200438, PR China
| | - Tiantao Cheng
- Department of Environmental Science & Engineering, Fudan University, Shanghai 200438, PR China
| | - Beilan Gao
- Department of Respiratory Medicine, Shanghai Pulmonary Hospital, Tongji University School of Medicine, Shanghai 200433, China
| | - Xiang Li
- Department of Environmental Science & Engineering, Fudan University, Shanghai 200438, PR China; Shanghai Institute of Pollution Control and Ecological Security, Shanghai 200092, PR China.
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Lee H, Myung W, Kim SE, Kim DK, Kim H. Ambient air pollution and completed suicide in 26 South Korean cities: Effect modification by demographic and socioeconomic factors. Sci Total Environ 2018; 639:944-951. [PMID: 29929333 DOI: 10.1016/j.scitotenv.2018.05.210] [Citation(s) in RCA: 26] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/04/2018] [Revised: 05/02/2018] [Accepted: 05/17/2018] [Indexed: 06/08/2023]
Abstract
Air pollution has been recently associated with suicide mortality. However, limited studies have examined possible effect modification of the association by various demographic and socioeconomic factors, despite their crucial roles on suicide risk. In 73,445 completed suicide cases from 26 South Korean cities from 2002 to 2013, we studied the association of suicide risk with exposure to particles <10 μm (PM10), nitrogen dioxide (NO2), sulfur dioxide (SO2), ozone (O3), and carbon monoxide (CO), using a city-specific conditional logistic regression analysis with a case-crossover design. Random effects meta-analysis was used to pool the results. We considered a delayed effect of air pollution by constructing lags of up to 7 days. We explored effect modification by demographic and socioeconomic factors (sex, age, education level, job, and marital status) as well as place of death, method of suicide, and season, through stratified subgroup analyses. Among five pollutants, NO2 showed the strongest association at immediate lags (percent change in odds ratio; PM10: 1.2% [95% CI, 0.2%, 2.3%]; NO2: 4.3% [95% CI, 1.9%, 6.7%]; SO2: 2.2% [95% CI, 0.7%, 3.8%]; O3: 1.5% [95% CI, -0.3%, 3.2%]; and CO: 2.4% [95% CI, 0.9%, 3.8%] per interquartile range increase at lag0). In subgroup analyses by socioeconomic factors, stronger associations were observed in the male sex, the elderly, those with lower education status, white-collar workers, and the married; the largest association was an 11.0% increase (95% CI, 4.1%, 18.4%) by NO2 among white-collar workers. We add evidence of effect modification of the association between air pollution exposure and suicide risk by various demographic and socioeconomic factors. These findings can serve as the basis for suicide prevention strategies by providing information regarding susceptible subgroups.
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Affiliation(s)
- Hyewon Lee
- Institute of Health and Environment, Seoul National University, 1 Gwanak-ro, Gwanak-gu, Seoul 08826, South Korea; Department of Neuropsychiatry, Seoul National University Bundang Hospital, Bundang-gu, Seongnam-si, Gyeonggi-do 13619, South Korea
| | - Woojae Myung
- Department of Neuropsychiatry, Seoul National University Bundang Hospital, Bundang-gu, Seongnam-si, Gyeonggi-do 13619, South Korea
| | - Satbyul Estella Kim
- Center for Social and Environmental Systems Research, National Institute for Environmental Studies, Tsukuba 305-8506, Japan
| | - Doh Kwan Kim
- Department of Psychiatry, Samsung Medical Center, Sungkyunkwan University School of Medicine, Gangnam-gu, Seoul 06351, South Korea
| | - Ho Kim
- Institute of Health and Environment, Seoul National University, 1 Gwanak-ro, Gwanak-gu, Seoul 08826, South Korea; Department of Public Health Sciences, Graduate School of Public Health, Seoul National University, 1 Gwanak-ro, Gwanak-gu, Seoul 08826, South Korea.
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