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Popovic I, Soares Magalhaes R, Yang S, Yang Y, Yang BY, Dong GH, Wei X, Van Buskirk J, Fox G, Ge E, Marks G, Knibbs L. Long-term exposure to ambient fine particulate matter (PM 2.5) and attributable pulmonary tuberculosis notifications in Ningxia Hui Autonomous Region, China: a health impact assessment. BMJ Open 2024; 14:e082312. [PMID: 38834325 PMCID: PMC11163650 DOI: 10.1136/bmjopen-2023-082312] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/20/2023] [Accepted: 05/16/2024] [Indexed: 06/06/2024] Open
Abstract
INTRODUCTION Long-term exposure to fine particulate matter (≤2.5 µm (PM2.5)) has been associated with pulmonary tuberculosis (TB) notifications or incidence in recent publications. Studies quantifying the relative contribution of long-term PM2.5 on TB notifications have not been documented. We sought to perform a health impact assessment to estimate the PM2.5- attributable TB notifications during 2007-2017 in Ningxia Hui Autonomous Region (NHAR), China. METHODS PM2.5 attributable TB notifications were estimated at township level (n=358), stratified by age group and summed across NHAR. PM2.5-associated TB-notifications were estimated for total and anthropogenic PM2.5 mass and expressed as population attributable fractions (PAFs). The main analysis used effect and uncertainty estimates from our previous study in NHAR, defining a counterfactual of the lowest annual PM2.5 (30 µg/m3) level, above which we assumed excess TB notifications. Sensitivity analyses included counterfactuals based on the 5th (31 µg/m3) and 25th percentiles (38 µg/m3), and substituting effect estimates from a recent meta-analysis. We estimated the influence of PM2.5 concentrations, population growth and baseline TB-notification rates on PM2.5 attributable TB notifications. RESULTS Over 2007-2017, annual PM2.5 had an estimated average PAF of 31.2% (95% CI 22.4% to 38.7%) of TB notifications while the anthropogenic PAF was 12.2% (95% CI 9.2% to 14.5%). With 31 and 38 µg/m3 as counterfactuals, the PAFs were 29.2% (95% CI 20.9% to 36.3%) and 15.4% (95% CI 10.9% to 19.6%), respectively. PAF estimates under other assumptions ranged between 6.5% (95% CI 2.9% to 9.6%) and 13.7% (95% CI 6.2% to 19.9%) for total PM2.5, and 2.6% (95% CI 1.2% to 3.8%) to 5.8% (95% CI 2.7% to 8.2%) for anthropogenic PM2.5. Relative to 2007, overall changes in PM2.5 attributable TB notifications were due to reduced TB-notification rates (-23.8%), followed by decreasing PM2.5 (-6.2%), and population growth (+4.9%). CONCLUSION We have demonstrated how the potential impact of historical or hypothetical air pollution reduction scenarios on TB notifications can be estimated, using public domain, PM2.5 and population data. The method may be transferrable to other settings where comparable TB-notification data are available.
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Affiliation(s)
- Igor Popovic
- Faculty of Medicine, School of Public Health, The University of Queensland, Herston, Queensland, Australia
- UQ Spatial Epidemiology Laboratory, School of Veterinary Science, The University of Queensland, Gatton, Queensland, Australia
| | - Ricardo Soares Magalhaes
- UQ Spatial Epidemiology Laboratory, School of Veterinary Science, The University of Queensland, Gatton, Queensland, Australia
- Children's Health and Environment Program, UQ Children's Health Research Center, The University of Queensland, South Brisbane, Queensland, Australia
| | - Shukun Yang
- Department of Radiology, The First People's Hospital in Yinchuan, The Second Affiliated Hospital of Ningxia Medical University, Yinchuan, Ningsia, China
| | - Yurong Yang
- Department of Pathogenic Biology & Medical Immunology, School of Basic Medical Science, Ningxia Medical University, Yinchuan, Ningxia, China
| | - Bo-Yi Yang
- Environmental Epidemiology, Sun Yat-Sen University, Guangzhou, China
| | - Guang-Hui Dong
- Guangzhou Key Laboratory of Environmental Pollution and Health Risk Assessment, Department of Preventive Medicine, School of Public Health, Sun Yat-Sen University, Guangzhou, Guangdong, China
| | - Xiaolin Wei
- Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada
| | - Joseph Van Buskirk
- Public Health Unit, Sydney Local Health District, Camperdown, New South Wales, Australia
- School of Public Health, The University of Sydney Faculty of Medicine and Health, Sydney, New South Wales, Australia
| | - Gregory Fox
- Faculty of Medicine and Health, Sydney Medical School, The University of Sydney, Sydney, New South Wales, Australia
| | - Erjia Ge
- University of Toronto Dalla Lana School of Public Health, Toronto, Ontario, Canada
| | - Guy Marks
- South Western Sydney Clinical School, University of New South Wales, The University of Sydney, Liverpool, New South Wales, Australia
- Woolcock Institute of Medical Research, Glebe, New South Wales, Australia
| | - Luke Knibbs
- Public Health Research Analytics and Methods for Evidence, Public Health Unit, Sydney Local Health District, Camperdown, New South Wales, Australia
- Faculty of Medicine and Health, School of Public Health, The University of Sydney, Sydney, New South Wales, Australia
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Zhang F, Zhu S, Zhao D, Tang H, Ruan L, Zhu W. Ambient temperature variations and AIDS-related mortality: A time-stratified case-crossover study in 103 counties, China. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 912:169474. [PMID: 38135089 DOI: 10.1016/j.scitotenv.2023.169474] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/30/2023] [Revised: 12/16/2023] [Accepted: 12/16/2023] [Indexed: 12/24/2023]
Abstract
BACKGROUND Climate change, characterized by the steady ascent of global temperatures and the escalating unpredictability of climate patterns, poses multifaceted challenges to public health worldwide. However, vulnerable groups, particularly the population affected by HIV/AIDS, have received little attention. OBJECTIVES We aimed to examine the impacts of temperature variations on AIDS-related mortality. METHODS Data on individuals with HIV/AIDS were collected from the HIV/AIDS Comprehensive Response Information Management System between 2013 and 2019. Temperature variation metrics were constructed by diurnal temperature range (DTR), temperature changes between neighboring days (TCN), and temperature variability (TV0-t). Time-stratified case-crossover design with conditional logistic regression models was used to investigate the associations between ambient temperature variations and AIDS-related mortality. RESULTS Each 1 °C elevated in DTR was linked with a 5.28 % [95 % confidence intervals (CIs): 1.61, 9.08] increment in AIDS-related mortality at a lag of 0-6 days. Stronger associations between DTR and AIDS-related mortality were observed in the married than in single, with corresponding excess ORs (%) of 5.33 (95 % CIs: 0.29, 10.62) versus 4.79 (95 % CIs: -0.50, 10.36) for 1 °C increased in DTR at lag 0-6 days. Additionally, we noticed the impact of DTR was more pronounced in the warm season, leading to a 7.32 % (95 % CIs: 0.57, 14.51) elevation in the risks of AIDS-related mortality for 1 °C increase in DTR at lag 0-6 days, while the effect value decreased to 5.16 % (95 % CIs: 0.71, 9.81) in the cold season. CONCLUSIONS Our findings indicated that DTR might be a significant risk factor for AIDS-related deaths among ambient temperature variation indicators, and underscored the importance of considering temperature variability in public health interventions aimed at mitigating this risk of AIDS-related mortality.
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Affiliation(s)
- Faxue Zhang
- Department of Occupational and Environmental Health, School of Public Health, Wuhan University, Wuhan 430071, China
| | - Shijie Zhu
- Department of Occupational and Environmental Health, School of Public Health, Wuhan University, Wuhan 430071, China
| | - Dingyuan Zhao
- Institute for the Prevention and Control of HIV/AIDS, Hubei Provincial Center for Disease Control and Prevention, Wuhan 430079, China
| | - Heng Tang
- Institute for the Prevention and Control of HIV/AIDS, Hubei Provincial Center for Disease Control and Prevention, Wuhan 430079, China
| | - Lianguo Ruan
- Wuhan Jinyintan Hospital, Tongji Medical College of Huazhong University of Science and Technology, Wuhan 430023, China; Hubei Clinical Research Center for Infectious Diseases, Wuhan 430023, China; Wuhan Research Center for Communicable Disease Diagnosis and Treatment, Chinese Academy of Medical Sciences, Wuhan 430023, China; Joint Laboratory of Infectious Diseases and Health, Wuhan Institute of Virology and Wuhan Jinyintan Hospital, Chinese Academy of Sciences, Wuhan 430023, China
| | - Wei Zhu
- Department of Occupational and Environmental Health, School of Public Health, Wuhan University, Wuhan 430071, China.
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Wang J, Li W, Huang W, Gao Y, Liu Y, Teng QH, Zhao Q, Chen M, Guo Y, Ma W. The associations of ambient fine particles with tuberculosis incidence and the modification effects of ambient temperature: A nationwide time-series study in China. JOURNAL OF HAZARDOUS MATERIALS 2023; 460:132448. [PMID: 37683354 DOI: 10.1016/j.jhazmat.2023.132448] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/29/2023] [Revised: 08/28/2023] [Accepted: 08/30/2023] [Indexed: 09/10/2023]
Abstract
Ambient fine particulate matter (PM2.5) is a major air pollutant that poses significant risks to human health. However, little is known about the association of PM2.5 with tuberculosis (TB) incidence, and whether temperature modifies the association.This study aimed to explore the association between ambient PM2.5 exposure and TB incidence in China and the modification effects of temperature. Weekly meteorological data, PM2.5 concentrations, and TB incidence numbers were collected for 22 cities across Mainland China, from 2011 to 2020. A quasi-Poisson regression with the distributed lag non-linear model was used to assess city-specific PM2.5-TB associations. A multivariate meta-regression model was then used to pool the city-specific effect estimates, at the national and regional levels. A J-shaped PM2.5-TB relationship was observed at the national level for China. Compared to those with minimum PM2.5-TB risk, people who were exposed to the highest PM2.5 concentrations had a 26 % (RR:1.26, 95 % confidence interval [CI]: 1.05, 1.52) higher risk for TB incidence. J-shaped PM2.5-TB associations were also observed for most sub-groups, however, no significant modifying effects were found. While a trend was observed between low temperatures and increased exposure-response associations, these results were not significant. Overall, approximately 20 % of TB cases in the 22 study cities, over the period 2011-2020, could be attributed to PM2.5 exposure. Strengthening the monitoring and emission control of PM2.5 could aid the prevention and control of TB incidence.
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Affiliation(s)
- Jia Wang
- National Center for Tuberculosis Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Wen Li
- Department of Epidemiology, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China; Shandong University Climate Change and Health Center, Jinan, Shandong, China; Climate, Air Quality Research Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
| | - Wenzhong Huang
- Climate, Air Quality Research Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
| | - Yuan Gao
- Climate, Air Quality Research Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
| | - Yanming Liu
- Climate, Air Quality Research Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
| | - Qian Hui Teng
- Climate, Air Quality Research Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
| | - Qi Zhao
- Department of Epidemiology, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China; Shandong University Climate Change and Health Center, Jinan, Shandong, China
| | - Mingting Chen
- National Center for Tuberculosis Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China.
| | - Yuming Guo
- Climate, Air Quality Research Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia.
| | - Wei Ma
- Department of Epidemiology, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China; Shandong University Climate Change and Health Center, Jinan, Shandong, China.
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Li JX, Luan Q, Li B, Dharmage SC, Heinrich J, Bloom MS, Knibbs LD, Popovic I, Li L, Zhong X, Xu A, He C, Liu KK, Liu XX, Chen G, Xiang M, Yu Y, Guo Y, Dong GH, Zou X, Yang BY. Outdoor environmental exposome and the burden of tuberculosis: Findings from nearly two million adults in northwestern China. JOURNAL OF HAZARDOUS MATERIALS 2023; 459:132222. [PMID: 37557043 DOI: 10.1016/j.jhazmat.2023.132222] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/12/2023] [Revised: 07/19/2023] [Accepted: 08/02/2023] [Indexed: 08/11/2023]
Abstract
We simultaneously assessed the associations for a range of outdoor environmental exposures with prevalent tuberculosis (TB) cases in a population-based health program with 1940,622 participants ≥ 15 years of age. TB status was confirmed through bacteriological and clinical assessment. We measured 14 outdoor environmental exposures at residential addresses. An exposome-wide association study (ExWAS) approach was used to estimate cross-sectional associations between environmental exposures and prevalent TB, an adaptive elastic net model (AENET) was implemented to select important exposure(s), and the Extreme Gradient Boosting algorithm was subsequently applied to assess their relative importance. In ExWAS analysis, 12 exposures were significantly associated with prevalent TB. Eight of the exposures were selected as predictors by the AENET model: particulate matter ≤ 2.5 µm (odds ratio [OR]=1.01, p = 0.3295), nitrogen dioxide (OR=1.09, p < 0.0001), carbon monoxide (OR=1.19, p < 0.0001), and wind speed (OR=1.08, p < 0.0001) were positively associated with the odds of prevalent TB while sulfur dioxide (OR=0.95, p = 0.0017), altitude (OR=0.97, p < 0.0001), artificial light at night (OR=0.98, p = 0.0001), and proportion of forests, shrublands, and grasslands (OR=0.95, p < 0.0001) were negatively associated with the odds of prevalent TB. Air pollutants had higher relative importance than meteorological and geographical factors, and the outdoor environment collectively explained 11% of TB prevalence.
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Affiliation(s)
- Jia-Xin Li
- Department of Occupational and Environmental Health, School of Public Health, Sun Yat-Sen University, Guangzhou 510080, China
| | - Qiyun Luan
- Department of Respiratory and Critical Care Medicine, The First People's Hospital of Kashi (The Affiliated Kashi Hospital of Sun Yat-Sen University), Kashgar City 844000, China
| | - Beibei Li
- Department of Respiratory and Critical Care Medicine, The First People's Hospital of Kashi (The Affiliated Kashi Hospital of Sun Yat-Sen University), Kashgar City 844000, China
| | - Shyamali C Dharmage
- Allergy and Lung Health Unit, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, VIC 3010, Australia
| | - Joachim Heinrich
- Allergy and Lung Health Unit, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, VIC 3010, Australia; Comprehensive Pneumology Center (CPC) Munich, Member DZL, Germany; Institute and Clinic for Occupational, Social and Environmental Medicine, University Hospital, Ludwig Maximilian University of Munich, Member DZL, Germany; German Center for Lung Research, Ziemssenstraße 1, 80336 Munich, Germany
| | - Michael S Bloom
- Department of Global and Community Health, George Mason University, Fairfax, VA 22030, USA
| | - Luke D Knibbs
- School of Public Health, The University of Sydney, NSW 2006, Australia
| | - Igor Popovic
- UQ Spatial Epidemiology Laboratory, School of Veterinary Science, University of Queensland, Gatton 4343, Australia; Faculty of Medicine, School of Public Health, University of Queensland, Herston, 4006, Australia, School of Veterinary Science, University of Queensland, Gatton 4343, Australia
| | - Li Li
- Department of Respiratory and Critical Care Medicine, The First People's Hospital of Kashi (The Affiliated Kashi Hospital of Sun Yat-Sen University), Kashgar City 844000, China
| | - Xuemei Zhong
- Department of Respiratory and Critical Care Medicine, The First People's Hospital of Kashi (The Affiliated Kashi Hospital of Sun Yat-Sen University), Kashgar City 844000, China
| | - Aimin Xu
- Department of Laboratory Medicine, The First People's Hospital of Kashgar, Kashgar 844000, China
| | - Chuanjiang He
- Department of Laboratory Medicine, The First People's Hospital of Kashgar, Kashgar 844000, China; Department of Laboratory Medicine, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou 510120, China
| | - Kang-Kang Liu
- Department of Research Center for Medicine, the Eighth Affiliated Hospital, Sun Yat-Sen University, Shenzhen, China
| | - Xiao-Xuan Liu
- Department of Occupational and Environmental Health, School of Public Health, Sun Yat-Sen University, Guangzhou 510080, China
| | - Gongbo Chen
- Department of Occupational and Environmental Health, School of Public Health, Sun Yat-Sen University, Guangzhou 510080, China
| | - Mingdeng Xiang
- State Environmental Protection Key Laboratory of Environmental Pollution Health Risk Assessment, South China Institute of Environmental Sciences, Ministry of Environmental Protection, Guangzhou 510080, China
| | - Yunjiang Yu
- State Environmental Protection Key Laboratory of Environmental Pollution Health Risk Assessment, South China Institute of Environmental Sciences, Ministry of Environmental Protection, Guangzhou 510080, China
| | - Yuming Guo
- Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
| | - Guang-Hui Dong
- Department of Occupational and Environmental Health, School of Public Health, Sun Yat-Sen University, Guangzhou 510080, China
| | - Xiaoguang Zou
- Department of Respiratory and Critical Care Medicine, The First People's Hospital of Kashi (The Affiliated Kashi Hospital of Sun Yat-Sen University), Kashgar City 844000, China.
| | - Bo-Yi Yang
- Department of Occupational and Environmental Health, School of Public Health, Sun Yat-Sen University, Guangzhou 510080, China.
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Zhu PP, Gao Y, Zhou GZ, Liu R, Li XB, Fu XX, Fu J, Lin F, Zhou YP, Li L. Short-term effects of high-resolution (1-km) ambient PM 2.5 and PM 10 on hospital admission for pulmonary tuberculosis: a case-crossover study in Hainan, China. Front Public Health 2023; 11:1252741. [PMID: 37736088 PMCID: PMC10509552 DOI: 10.3389/fpubh.2023.1252741] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2023] [Accepted: 08/16/2023] [Indexed: 09/23/2023] Open
Abstract
Introduction There is limited evidence regarding particulate matter (PM)'s short-term effects on pulmonary tuberculosis (PTB) hospital admission. Our study aimed to determine the short-term associations of the exposure to ambient PM with aerodynamic diameters <2.5 μm (PM2.5) and < 10 μm (PM10) with hospital admission for PTB in Hainan, a tropical province in China. Methods We collected individual data on patients hospitalized with PTB, PM2.5, PM10, and meteorological data from 2016 to 2019 in Hainan Province, China. Conditional logistic regression models with a time-stratified case-crossover design were used to assess the short-term effects of PM2.5 and PM10 on hospital admission for PTB at a spatial resolution of 1 km × 1 km. Stratified analyses were performed according to age at admission, sex, marital status, administrative division, and season of admission. Results Each interquartile range (IQR) increases in the concentrations of PM2.5 and PM10 were associated with 1.155 (95% confidence interval [CI]: 1.041-1.282) and 1.142 (95% CI: 1.033-1.263) hospital admission risks for PTB at lag 0-8 days, respectively. The stratified analyses showed that the effects of PM2.5 and PM10 were statistically significant for patients aged ≥65 years, males, married, and those residing in prefecture-level cities. Regarding seasonal differences, the associations between PM and hospital admission for PTB were statistically significant in the warm season but not in the cold season. The effect of PM2.5 was consistently stronger than that of PM10 in most subgroups. Conclusion Short-term exposure to PM increases the risk of hospital admission for PTB. The potential impact of PM with smaller aerodynamic diameter is more detrimental. Our findings highlight the importance of reducing ambient PM level to alleviate the burden of PTB.
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Affiliation(s)
- Pan-Pan Zhu
- State Key Laboratory of Organ Failure Research, Department of Biostatistics, Guangdong Provincial Key Laboratory of Tropical Disease Research, School of Public Health, Southern Medical University, Guangzhou, Guangdong, China
| | - Yi Gao
- Department of Infectious Disease and Hepatology Unit, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong, China
- Department of Infectious Disease, Hainan General Hospital, Hainan Medical University, Haikou, Hainan, China
| | - Gui-Zhong Zhou
- Department of Infectious Disease, The Second Affiliated Hospital, Hainan Medical University, Haikou, Hainan, China
| | - Rui Liu
- Department of Infectious Disease, The Second Affiliated Hospital, Hainan Medical University, Haikou, Hainan, China
| | - Xiao-Bo Li
- Department of Neurosurgery, Haikou Municipal People’s Hospital and Central South University Xiangya Medical College Affiliated Hospital, Haikou, Hainan, China
| | - Xian-Xian Fu
- Clinical Lab, Haikou Municipal People’s Hospital and Central South University Xiangya Medical College Affiliated Hospital, Haikou, Hainan, China
| | - Jian Fu
- Department of Infectious Disease, Hainan General Hospital, Hainan Medical University, Haikou, Hainan, China
| | - Feng Lin
- Department of Infectious Disease, Hainan General Hospital, Hainan Medical University, Haikou, Hainan, China
| | - Yuan-Ping Zhou
- Department of Infectious Disease and Hepatology Unit, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong, China
- Department of Gastroenterology, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong, China
| | - Li Li
- State Key Laboratory of Organ Failure Research, Department of Biostatistics, Guangdong Provincial Key Laboratory of Tropical Disease Research, School of Public Health, Southern Medical University, Guangzhou, Guangdong, China
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Lu JW, Mao JJ, Zhang RR, Li CH, Sun Y, Xu WQ, Zhuang X, Zhang B, Qin G. Association between long-term exposure to ambient air pollutants and the risk of tuberculosis: A time-series study in Nantong, China. Heliyon 2023; 9:e17347. [PMID: 37441410 PMCID: PMC10333459 DOI: 10.1016/j.heliyon.2023.e17347] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2023] [Revised: 06/01/2023] [Accepted: 06/14/2023] [Indexed: 07/15/2023] Open
Abstract
Background Increasing evidence has shown that the risk of tuberculosis (TB) might be related to the exposure to air pollutants; however, the findings are inconsistent and studies on long-term air pollutant exposure and TB risk are scarce. This study aime to assess the relationship between monthly exposure to air pollution and TB risk in Nantong, China. Methods We collected the time series data on the number of TB cases, as well as environmental and socioeconomic covariates from January 2005 to December 2020. The impact of air pollutant exposure on TB risk was evaluated using the distributed lag nonlinear model (DLNM). Stratified analyses were conducted to examine the effect modifications of sex and age on the association between air pollutants and TB risk. Sensitivity analyses were applied to test the stability of the model. Results There were a total of 54,096 cases of TB in Nantong during the study period. In the single-pollutant model, for each 10 μg/m3 increase in concentration, the pooled relative risks (RRs) of TB reached the maximum to 1.10 (95% confidence interval (CI): 1.04-1.16, lag 10 months) for particulate matter with aerodynamic diameter less than 2.5 μm (PM2.5), 1.05 (95% CI: 1.01-1.10, lag 9 months) for particulate matter with aerodynamic diameter less than 10 μm (PM10), and 1.11 (95%CI: 1.04-1.19, lag 10 months) for nitrogen dioxide (NO2). Ozone (O3) did not show significant effect on TB risk. Effect modifications of sex and age on the association between air pollutants and TB risk were not observed. The multi-pollutant model results showed no significant variation compared with the single-pollutant model. Conclusions Our study suggests that air pollutants pose a substantial threat to the TB risk. Reducing air pollution might be crucial for TB prevention and control.
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Affiliation(s)
- Jia-Wang Lu
- Department of Infectious Diseases, Affiliated Hospital of Nantong University, Nantong University Medical School, Nantong, China
| | - Jun-Jie Mao
- Department of Epidemiology and Biostatistics, Nantong University School of Public Health, Nantong, China
| | - Rong-Rong Zhang
- Nantong Centre for Disease Control and Prevention, Nantong, China
| | - Chun-Hu Li
- Department of Epidemiology and Biostatistics, Nantong University School of Public Health, Nantong, China
| | - Yu Sun
- Department of Infectious Diseases, Affiliated Hospital of Nantong University, Nantong University Medical School, Nantong, China
| | - Wan-Qing Xu
- Department of Internal Medicine, Nantong University Medical School, Nantong, China
| | - Xun Zhuang
- Department of Epidemiology and Biostatistics, Nantong University School of Public Health, Nantong, China
| | - Bin Zhang
- Department of Infectious Diseases, Affiliated Hospital of Nantong University, Nantong University Medical School, Nantong, China
| | - Gang Qin
- Department of Infectious Diseases, Affiliated Hospital of Nantong University, Nantong University Medical School, Nantong, China
- National Key Clinical Construction Specialty - Department of Respiratory and Critical Care Medicine, Affiliated Hospital of Nantong University, Nantong, China
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Popovic I, Soares Magalhães RJ, Yang Y, Yang S, Yang B, Dong G, Wei X, Fox GJ, Hammer MS, Martin RV, van Donkelaar A, Ge E, Marks GB, Knibbs LD. Effects of long-term ambient air pollution exposure on township-level pulmonary tuberculosis notification rates during 2005-2017 in Ningxia, China. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2023; 317:120718. [PMID: 36435281 DOI: 10.1016/j.envpol.2022.120718] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/09/2022] [Revised: 11/17/2022] [Accepted: 11/20/2022] [Indexed: 06/16/2023]
Abstract
Studies examining long-term effects of ambient air pollution exposure, measured as annual averages, on pulmonary tuberculosis (TB) incidence are scarce, particularly in endemic, rural settings. We performed a small-area study in Ningxia Hui Autonomous Region (NHAR), a high TB-burden area in rural China, using township-level (n = 358 non-overlapping townships) annual TB notification data (2005-2017). We aimed to determine if annual average concentrations of ambient air pollution (particulate matter <2·5 μm [PM2·5], nitrogen dioxide [NO2] ozone [O3]) were associated with TB notification rates (as a proxy for incidence). Air pollution effects on TB notification rates at township-level were estimated as incidence rate ratios (IRR), fitted using a generalised estimating equation (GEE) adjusted for covariates (age, sex, occupation, education, ethnicity, remoteness [urban or rural], household crowding and solid fuel use). A total of 38,942 TB notifications were reported in NHAR between 2005 and 2017. The mean annual TB notification rate was 67 (standard deviation [SD]; 7) per 100,000 people. Median concentrations of PM2·5, NO2, and O3 were 42 μg/m3 (interquartile range [IQR]; 38-48 μg/m3), 15 ppb (IQR; 12-16 ppb), and 56 ppb (IQR; 56-57 ppb), respectively. In single pollutant models, adjusted for covariates, an interquartile range (IQR) increase (10 μg/m3) in PM2·5 was significantly associated with higher TB notification rates (IRR: 1∙35; 95% CI: 1·25-1·48). Comparable effects on notifications of TB were observed for increases in NO2 exposure (IRR: 1·20 per IQR (4 ppb) increase; 95% CI: 1·08-1·31). Ground-level ozone was not associated with TB notification rate in any models. The observed effects were consistent over time, in multi-pollutant models, and appeared robust to additional adjustment for indicators of household crowding, solid fuel use and remoteness. More rigorous study designs are needed to understand if improving air quality has population-level benefits on TB disease incidence in endemic settings.
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Affiliation(s)
- Igor Popovic
- Faculty of Medicine, School of Public Health, University of Queensland, Herston, 4006, Australia; UQ Spatial Epidemiology Laboratory, School of Veterinary Science, University of Queensland, Gatton, 4343, Australia.
| | - Ricardo J Soares Magalhães
- UQ Spatial Epidemiology Laboratory, School of Veterinary Science, University of Queensland, Gatton, 4343, Australia; Children's Health and Environment Program, UQ Children's Health Research Center, The University of Queensland, South Brisbane, 4101, Australia
| | - Yurong Yang
- Department of Pathogenic Biology & Medical Immunology, School of Basic Medical Science, Ningxia Medical University, Yinchuan, 750004, China
| | - Shukun Yang
- Department of Radiology, The Second Affiliated Hospital of Ningxia Medical University, The First People's Hospital in Yinchuan, Yinchuan, 750004, China
| | - Boyi Yang
- Guangdong Provincial Engineering Technology Research Center of Environmental Pollution and Health Risk Assessment, Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou, 510085, China
| | - Guanghui Dong
- Guangzhou Key Laboratory of Environmental Pollution and Health Risk Assessment, Department of Preventive Medicine, School of Public Health, Sun Yat-sen University, Guangzhou, 510085, China
| | - Xiaolin Wei
- Dalla Lana School of Public Health, University of Toronto, Toronto, ON M5S 1A1, Canada
| | - Greg J Fox
- Faculty of Medicine and Health, Sydney Medical School, The University of Sydney, NSW, 2006, Australia
| | - Melanie S Hammer
- Department of Energy, Environmental, and Chemical Engineering, Washington University, St Louis, 63130, United States
| | - Randall V Martin
- Department of Energy, Environmental, and Chemical Engineering, Washington University, St Louis, 63130, United States; Department of Physics and Atmospheric Science, Dalhousie University, Halifax, B3H 3J5, Canada
| | - Aaron van Donkelaar
- Department of Energy, Environmental, and Chemical Engineering, Washington University, St Louis, 63130, United States; Department of Physics and Atmospheric Science, Dalhousie University, Halifax, B3H 3J5, Canada
| | - Erjia Ge
- Dalla Lana School of Public Health, University of Toronto, Toronto, ON M5S 1A1, Canada
| | - Guy B Marks
- South Western Sydney Clinical School, University of New South Wales, Liverpool, 2170, Australia; Woolcock Institute of Medical Research, Glebe, 2037, Australia
| | - Luke D Knibbs
- Public Health Unit, Sydney Local Health District, Camperdown, 2050, Australia; Faculty of Medicine and Health, School of Public Health, The University of Sydney, Camperdown, 2006, Australia
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8
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Huang K, Hu CY, Yang XY, Zhang Y, Wang XQ, Zhang KD, Li YQ, Wang J, Yu WJ, Cheng X, Cao JY, Zhang T, Kan XH, Zhang XJ. Contributions of ambient temperature and relative humidity to the risk of tuberculosis admissions: A multicity study in Central China. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 838:156272. [PMID: 35644395 DOI: 10.1016/j.scitotenv.2022.156272] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/14/2022] [Revised: 05/08/2022] [Accepted: 05/23/2022] [Indexed: 06/15/2023]
Abstract
BACKGROUND As a communicable disease and major public health issue, many studies have quantified the associations between tuberculosis (TB) and meteorological factors with inconsistent results. The purpose of this multicenter study was to characterize the associations between ambient temperature, humidity and the risk of TB hospitalizations and to investigate potential heterogeneity. METHOD Data on daily hospitalizations for TB, meteorological factors and ambient air pollutants for 16 cities in Anhui Province were collected from 2015 to 2020. A distributed lag nonlinear model (DLNM) was performed to obtain the estimates of meteorological-TB relationships by cities. Then, we used the multivariate meta-regression model to pool the city-specific estimates with air pollution, demographic indicators, medical resource and latitude as potential modifiers to explore the sources of heterogeneity. Finally, we divided the whole province into three regions to validate the meteorological-TB relationships by regions. RESULTS The overall pooled temperature-TB association presented an approximate S-shaped curve, with relative risk (RR) peaking at 5 °C (RR = 1.536, 95% CI: 1.303-1.811) compared to the reference temperature (27 °C). Lag-response curve suggested that low temperature exposure increased the risk of TB hospitalizations at lag 0 and 1 day (lag0 day: RR = 1.136, 95% CI: 1.048-1.231, lag1 day: RR = 1.052, 95% CI: 1.023-1.082). However, the overall exposure-response curve between relative humidity and TB showed almost horizontal line with reference relative humidity to 78%. The residual heterogeneity ranged from 27.1% to 36.9%, with air pollution, latitude and medical resource explained the largest proportion. CONCLUSION We found that low temperature exposure is associated with an acute increased risk of TB hospitalizations in Anhui Province. The association between temperature and TB admission varies depending on air pollution, latitude, and medical resources. Since the effect of short-term exposure to humidity is not significant, further studies are supposed to focus on the long-term effect of humidity.
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Affiliation(s)
- Kai Huang
- Department of Hospital Infection Prevention and Control, The Second Affiliated Hospital of Anhui Medical University, 678 Furong Road, Hefei 230601, China; Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei 230032, China
| | - Cheng-Yang Hu
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei 230032, China
| | - Xi-Yao Yang
- Department of Hospital Infection Prevention and Control, The Second Affiliated Hospital of Anhui Medical University, 678 Furong Road, Hefei 230601, China
| | - Yunquan Zhang
- Department of Epidemiology and Biostatistics, School of Public Health, Medical College, Wuhan University of Science and Technology, Wuhan 430065, China
| | - 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
| | - Ying-Qing Li
- 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
| | - Wen-Jie Yu
- 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
| | - Ji-Yu Cao
- Department of Occupational Health and Environmental Health, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei 230032, Anhui, China
| | - Tao Zhang
- Anhui Chest Hospital, 397 Jixi Road, Hefei 230022, China
| | - Xiao-Hong Kan
- Anhui Chest Hospital, 397 Jixi Road, Hefei 230022, China; Anhui Medical University Clinical College of Chest, 397 Jixi Road, Hefei 230022, China.
| | - Xiu-Jun Zhang
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei 230032, China.
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9
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Wu DW, Cheng YC, Wang CW, Hung CH, Chen PS, Chu-Sung Hu S, Richard Lin CH, Chen SC, Kuo CH. Impact of the synergistic effect of pneumonia and air pollutants on newly diagnosed pulmonary tuberculosis in southern Taiwan. ENVIRONMENTAL RESEARCH 2022; 212:113215. [PMID: 35367429 DOI: 10.1016/j.envres.2022.113215] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/26/2021] [Revised: 03/10/2022] [Accepted: 03/26/2022] [Indexed: 06/14/2023]
Abstract
BACKGROUND An increased incidence of pulmonary tuberculosis (PTB) among patients with pulmonary diseases exposed to air pollution has been reported. OBJECTIVE To comprehensively investigate the association between pneumonia (PN) and air pollution with PTB through a large-scale follow-up study. METHODS We conducted a retrospective study using data from the Kaohsiung Medical University Hospital Research Database and the Taiwan Air Quality Monitoring Database. We included adult patients with PN, PTB and other comorbidities according to ICD-9 codes. Control subjects without PN were matched by age, sex and ten comorbidities to each PN patient at a ratio of 4:1. RESULTS A total of 82,590 subjects were included. The PTB incidence rate was significantly higher in the PN group (2,391/100,000) than in the control group (1,388/100,000). The crude hazard ratio (HR) of PN-associated PTB incidence decreased with time, and the overall 7 years the HR (95% confidence interval; CI) was 1.74 (1.55-1.96). The overall adjusted HR and 95% CI of PN-related PTB in the multivariate Cox regression analysis was 3.38 (2.98-3.84). In addition, there was a cumulative lag effect of all air pollutants within 30 days of exposure. The peak adjusted HRs for PTB were noted on the 3rd, 8th, 12th and 12th days of PM2.5, O3, SO2 and NO exposure, respectively. The overall peak HRs (95% CI) of PM2.5, O3, SO2 and NO were 1.145 (1.139-1.152), 1.153 (1.145-1.161), 1.909 (1.839-1.982) and 1.312 (1.259-1.367), respectively, and there was a synergistic effect with pneumonia on the risk of PTB. CONCLUSIONS A strong association was found between past episodes of PN and the future risk of PTB. In addition, air pollutants including PM2.5, SO2, O3 and NO, together with previous episodes of PN, had both long-term and short-term impact on the incidence of PTB.
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Affiliation(s)
- Da-Wei Wu
- Doctoral Degree Program, Department of Public Health, College of Health Sciences, Kaohsiung Medical University, Kaohsiung, 807, Taiwan; Department of Internal Medicine, Kaohsiung Municipal Siaogang Hospital, Kaohsiung Medical University, Kaohsiung, 812, Taiwan; Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, Kaohsiung Medical University Hospital, Kaohsiung Medical University, Kaohsiung, 807, Taiwan; Research Center for Environmental Medicine, Kaohsiung Medical University, Kaohsiung, 807, Taiwan
| | - Yu-Cheng Cheng
- Department of Computer Science and Engineering, National Sun Yat-sen University, Kaohsiung, 80424, Taiwan
| | - Chih-Wen Wang
- Department of Internal Medicine, Kaohsiung Municipal Siaogang Hospital, Kaohsiung Medical University, Kaohsiung, 812, Taiwan; Research Center for Environmental Medicine, Kaohsiung Medical University, Kaohsiung, 807, Taiwan; Division of Hepatobiliary, Department of Internal Medicine, Kaohsiung Medical University Hospital, Kaohsiung Medical University, Kaohsiung, 807, Taiwan
| | - Chih-Hsing Hung
- Research Center for Environmental Medicine, Kaohsiung Medical University, Kaohsiung, 807, Taiwan; Department of Pediatrics, Kaohsiung Medical University Hospital, Kaohsiung Medical University, Kaohsiung, 807, Taiwan; Department of Pediatrics, Kaohsiung Municipal Siaogang Hospital, Kaohsiung Medical University, Kaohsiung, 807, Taiwan
| | - Pei-Shih Chen
- Research Center for Environmental Medicine, Kaohsiung Medical University, Kaohsiung, 807, Taiwan; Department of Public Health, College of Health Sciences, Kaohsiung Medical University, Kaohsiung, 807, Taiwan; Institute of Environmental Engineering, College of Engineering, National Sun Yat-Sen University, Kaohsiung, 804, Taiwan; Department of Medical Research, Kaohsiung Medical University Hospital, Kaohsiung, 807, Taiwan
| | - Stephen Chu-Sung Hu
- Department of Dermatology, Kaohsiung Medical University Hospital, Kaohsiung, 807, Taiwan; Department of Dermatology, College of Medicine, Kaohsiung Medical University, Kaohsiung, 807, Taiwan; Department of Dermatology, Kaohsiung Municipal Siaogang Hospital, Kaohsiung, 807, Taiwan
| | - Chun-Hung Richard Lin
- Department of Computer Science and Engineering, National Sun Yat-sen University, Kaohsiung, 80424, Taiwan.
| | - Szu-Chia Chen
- Department of Internal Medicine, Kaohsiung Municipal Siaogang Hospital, Kaohsiung Medical University, Kaohsiung, 812, Taiwan; Research Center for Environmental Medicine, Kaohsiung Medical University, Kaohsiung, 807, Taiwan; Division of Nephrology, Department of Internal Medicine, Kaohsiung Medical University Hospital, Kaohsiung Medical University, Kaohsiung, 807, Taiwan; Faculty of Medicine, College of Medicine, Kaohsiung Medical University, Kaohsiung, 807, Taiwan.
| | - Chao-Hung Kuo
- Department of Internal Medicine, Kaohsiung Municipal Siaogang Hospital, Kaohsiung Medical University, Kaohsiung, 812, Taiwan; Division of Gastroenterology, Department of Internal Medicine, Kaohsiung Medical University Hospital, Kaohsiung Medical University, Kaohsiung, 807, Taiwan
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10
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Dimala CA, Kadia BM. A systematic review and meta-analysis on the association between ambient air pollution and pulmonary tuberculosis. Sci Rep 2022; 12:11282. [PMID: 35788679 PMCID: PMC9253106 DOI: 10.1038/s41598-022-15443-9] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2021] [Accepted: 06/23/2022] [Indexed: 11/25/2022] Open
Abstract
There is inconclusive evidence on the association between ambient air pollution and pulmonary tuberculosis (PTB) incidence, tuberculosis-related hospital admission and mortality. This review aimed to assess the extent to which selected air pollutants are associated to PTB incidence, hospital admissions and mortality. This was a systematic review of studies published in English from January 1st, 1946, through May 31st, 2022, that quantitatively assessed the association between PM2.5, PM10, NO2, SO2, CO, O3 and the incidence of, hospital admission or death from PTB. Medline, Embase, Scopus and The Cochrane Library were searched. Extracted data from eligible studies were analysed using STATA software. Random-effect meta-analysis was used to derive pooled adjusted risk and odds ratios. A total of 24 studies (10 time-series, 5 ecologic, 5 cohort, 2 case–control, 1 case cross-over, 1 cross-sectional) mainly from Asian countries were eligible and involved a total of 437,255 tuberculosis cases. For every 10 μg/m3 increment in air pollutant concentration, there was a significant association between exposure to PM2.5 (pooled aRR = 1.12, 95% CI: 1.06–1.19, p < 0.001, N = 6); PM10 (pooled aRR = 1.06, 95% CI: 1.01–1.12, p = 0.022, N = 8); SO2 (pooled aRR = 1.08, 95% CI: 1.04–1.12, p < 0.001, N = 9); and the incidence of PTB. There was no association between exposure to CO (pooled aRR = 1.04, 95% CI: 0.98–1.11, p = 0.211, N = 4); NO2 (pooled aRR = 1.08, 95% CI: 0.99–1.17, p = 0.057, N = 7); O3 (pooled aRR = 1.00, 95% CI: 0.99–1.02, p = 0.910, N = 6) and the incidence of PTB. There was no association between the investigated air pollutants and mortality or hospital admissions due to PTB. Overall quality of evidence was graded as low (GRADE approach). Exposure to PM2.5, PM10 and SO2 air pollutants was found to be associated with an increased incidence of PTB, while exposure to CO, NO2 and O3 was not. There was no observed association between exposure to these air pollutants and hospital admission or mortality due to PTB. The quality of the evidence generated, however, remains low. Addressing the tuberculosis epidemic by 2030 as per the 4th Sustainable Development Goal may require a more rigorous exploration of this association.
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Affiliation(s)
- Christian Akem Dimala
- Health and Human Development (2HD) Research Network, Douala, Cameroon.,Department of Medicine, Reading Hospital, Tower Health System, West Reading, PA, USA
| | - Benjamin Momo Kadia
- Health Education and Research Organisation (HERO) Cameroon, Buea, Cameroon. .,Department of Clinical Sciences, Liverpool School of Tropical Medicine, Liverpool, UK.
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11
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Wang XQ, Zhao JW, Zhang KD, Yu WJ, Wang J, Li YQ, Cheng X, Li ZH, Mao YC, Hu CY, Huang K, Ding K, Yang XJ, Chen SS, Zhang XJ, Kan XH. Short-term effect of sulfur dioxide (SO 2) change on the risk of tuberculosis outpatient visits in 16 cities of Anhui Province, China: the first multi-city study to explore differences in occupational patients. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2022; 29:50304-50316. [PMID: 35224697 PMCID: PMC8882443 DOI: 10.1007/s11356-022-19438-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/19/2021] [Accepted: 02/21/2022] [Indexed: 06/14/2023]
Abstract
A growing number of biological studies suggest that exogenous sulfur dioxide (SO2) at a certain concentration may promote human resistance to Mycobacterium tuberculosis. However, the results of most relevant studies are inconsistent, and few studies have explored the relationship between SO2 exposure and tuberculosis risk at provincial level. In addition, occupational exposure has long been considered to have a certain impact on the human body, so for the first time, we discussed the differences between different occupations in the study on the relationship between air pollutant exposure and tuberculosis risk, and evaluated the impact of occupational exposure. This study aimed to explore the association between short-term SO2 exposure and the risk of outpatient visits to tuberculosis in Anhui province and 16 prefecture-level cities from 2015 to 2020. We used several models for multi-stage analysis, including distributed lag nonlinear model (DLNM), Poisson generalized linear regression model, and random-effects model. The association was assessed using the 28-day cumulative lag effect RR and 95%CI for each 10-unit increase in SO2 concentration. We divided all patients into the following six occupations: Worker, Farmer, Retired people, Children and Students, Cadre and Office clerk, and Service staff (catering, business, etc.). Sex, age, and season were analyzed by subgroup. Finally, the robustness of the multi-pollutant model was tested. At provincial level, the overall effect value of SO2 was RR=0.8191 (95%CI: 07702~0.8712); after grouping all patients by occupation, the association found only among Farmers (RR = 0.7150, 95%CI: 0.6699-0.7632, lag 0-28 days) and Workers (RR = 0.8566, 95%CI: 0.7930-0.9930, lag 0-4 days) was still statistically significant. Estimates for individual cities and using random-effects models to estimate average associations showed that SO2 exposure was associated with a reduced risk of outpatient TB visits in 14 municipalities, which remained significant when aggregated (RR = 0.9030, 95%CI: 0.8730-0.9340). Analysis of patients grouped by occupation in each municipality showed that statistical significance was again observed only in the Farmer (RR = 0.8880, 95%CI: 0.8610-0.9160) and Worker (RR = 0.8250, 95%CI: 0.7290-0.9340) groups. Stratified analysis of age, sex, and season showed that the effect of SO2 exposure was greater for middle-aged people (18-64 years old) and males, and less for seasonal changes. In summary, we found that exposure to SO2 reduces the risk of outpatient visits to tuberculosis, with farmers and workers more susceptible to SO2. Gender and age had a greater impact on the risk of TB outpatient visits than seasonal variations.
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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
| | - Jia-Wen Zhao
- 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
| | - Ying-Qing Li
- 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
| | - Zhen-Hua Li
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, 230032, China
| | - Yi-Cheng Mao
- 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
- The Second Affiliated Hospital of Anhui Medical University, 678 Furong Road, Hefei, 230601, 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
| | | | - 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.
- Anhui Chest Hospital, 397 Jixi Road, Hefei, 230022, China.
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12
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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. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 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] [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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13
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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. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 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] [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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Niu Z, Qi Y, Zhao P, Li Y, Tao Y, Peng L, Qiao M. Short-term effects of ambient air pollution and meteorological factors on tuberculosis in semi-arid area, northwest China: a case study in Lanzhou. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2021; 28:69190-69199. [PMID: 34291414 DOI: 10.1007/s11356-021-15445-6] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/14/2021] [Accepted: 07/10/2021] [Indexed: 05/21/2023]
Abstract
To investigate the short-term effects of ambient air pollution and meteorological factors on daily tuberculosis (TB), semi-parametric generalized additive model was used to assess the impacts of ambient air pollutants and meteorological factors on daily TB case from 2005 to 2010 in Chengguan District, Lanzhou, China. Then a non-stratification parametric model and a stratification parametric model were applied to study the interactive effect of air pollutants and meteorological factors on daily TB. The results show that sulfur dioxide (SO2), nitrogen dioxide (NO2), and particulate matter with aerodynamic diameter less than 10μm (PM10) were positively correlated with daily TB case; the excess risk (ER) and 95% confidence interval (CI) were 1.79% (0.40%, 3.20%), 3.86% (1.81%, 5.96%), and 0.32% (0.02%, 0.62%), respectively. Daily TB case was positively correlated with maximum temperature, minimum temperature, average temperature, vapor pressure, and relative humidity, but negatively correlated with atmospheric pressure, wind speed, and sunshine duration. The association with average temperature was the strongest, whose ER and 95% CI were 4.43% (3.15%, 5.72%). In addition, there were significant interaction effects between air pollutants and meteorological factors on daily TB case.
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Affiliation(s)
- Zhaocheng Niu
- Gansu Key Laboratory for Environmental Pollution Prediction and Control, College of Earth and Environmental Sciences, Lanzhou University, 222 South Tianshui Road, Chengguan District, Lanzhou, 730000, Gansu Province, People's Republic of China
- Key Laboratory of Western China's Environmental Systems (Ministry of Education), College of Earth and Environmental Sciences, Lanzhou University, 222 South Tianshui Road, Chengguan District, Lanzhou, 730000, Gansu Province, People's Republic of China
| | - Yuejun Qi
- Lanzhou Municipal Health Service Center, Lanzhou, 730030, China
| | - Puqiu Zhao
- Gansu Key Laboratory for Environmental Pollution Prediction and Control, College of Earth and Environmental Sciences, Lanzhou University, 222 South Tianshui Road, Chengguan District, Lanzhou, 730000, Gansu Province, People's Republic of China
- Key Laboratory of Western China's Environmental Systems (Ministry of Education), College of Earth and Environmental Sciences, Lanzhou University, 222 South Tianshui Road, Chengguan District, Lanzhou, 730000, Gansu Province, People's Republic of China
| | - Yidu Li
- Gansu Key Laboratory for Environmental Pollution Prediction and Control, College of Earth and Environmental Sciences, Lanzhou University, 222 South Tianshui Road, Chengguan District, Lanzhou, 730000, Gansu Province, People's Republic of China
- Key Laboratory of Western China's Environmental Systems (Ministry of Education), College of Earth and Environmental Sciences, Lanzhou University, 222 South Tianshui Road, Chengguan District, Lanzhou, 730000, Gansu Province, People's Republic of China
| | - Yan Tao
- Gansu Key Laboratory for Environmental Pollution Prediction and Control, College of Earth and Environmental Sciences, Lanzhou University, 222 South Tianshui Road, Chengguan District, Lanzhou, 730000, Gansu Province, People's Republic of China.
- Key Laboratory of Western China's Environmental Systems (Ministry of Education), College of Earth and Environmental Sciences, Lanzhou University, 222 South Tianshui Road, Chengguan District, Lanzhou, 730000, Gansu Province, People's Republic of China.
| | - Lu Peng
- Gansu Key Laboratory for Environmental Pollution Prediction and Control, College of Earth and Environmental Sciences, Lanzhou University, 222 South Tianshui Road, Chengguan District, Lanzhou, 730000, Gansu Province, People's Republic of China
- Key Laboratory of Western China's Environmental Systems (Ministry of Education), College of Earth and Environmental Sciences, Lanzhou University, 222 South Tianshui Road, Chengguan District, Lanzhou, 730000, Gansu Province, People's Republic of China
| | - Mingli Qiao
- Gansu Key Laboratory for Environmental Pollution Prediction and Control, College of Earth and Environmental Sciences, Lanzhou University, 222 South Tianshui Road, Chengguan District, Lanzhou, 730000, Gansu Province, People's Republic of China
- Key Laboratory of Western China's Environmental Systems (Ministry of Education), College of Earth and Environmental Sciences, Lanzhou University, 222 South Tianshui Road, Chengguan District, Lanzhou, 730000, Gansu Province, People's Republic of China
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15
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Song WM, Liu Y, Zhang QY, Liu SQ, Xu TT, Li SJ, An QQ, Liu JY, Tao NN, Liu Y, Yu CB, Yu CX, Li YF, Li HC. Ambient air pollutants, diabetes and risk of newly diagnosed drug-resistant tuberculosis. ECOTOXICOLOGY AND ENVIRONMENTAL SAFETY 2021; 219:112352. [PMID: 34044311 DOI: 10.1016/j.ecoenv.2021.112352] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/05/2021] [Revised: 05/08/2021] [Accepted: 05/16/2021] [Indexed: 06/12/2023]
Abstract
BACKGROUND Drug-resistant tuberculosis (DR-TB), diabetes and exposure to air pollution are thought to be important threat to human health, but no studies have explored the effects of ambient air pollutants on DR-TB when adjusting diabetes status so far. METHODS We performed a study among 3759 newly diagnosed TB cases with drug-susceptibility testing results, diabetes status, and individual air pollution data in Shandong from 2015 to 2019. Generalized linear mixed models (GLMM) including three models (Model 1: without covariates, Model 2: adjusted by diabetes status only, Model 3: with all covariates) were applied. RESULTS Of 3759 TB patients enrolled, 716 (19.05%) were DR-TB, and 333 (8.86%) had diabetes. High exposure to O3 was associated with an increased risk of RFP-resistance (Model 2 or 3: odds ratio (OR) = 1.008, 95% confidence intervals (CI): 1.002-1.014), ethambutol-resistance (Model 3: OR = 1.015, 95%CI: 1.004-1.027) and any rifampicin+streptomycin resistance (Model 1,2,3: OR = 1.01, 95%CI: 1.002-1.018) at 90 days. In contrast, NO2 was associated with a reduced risk of DR-TB (Model 3: OR = 0.99, 95%CI: 0.981-0.999) and multidrug-resistant TB (MDR-TB) (Model 3: OR = 0.977, 95%CI: 0.96-0.994) at 360 days. Additionally, SO2 (Model 1, 2, 3: OR = 0.987, 95%CI: 0.977-0.998) showed a protective effect on MDR-TB at 90 days. PM2.5 (90 days, Model 2: OR = 0.991, 95%CI: 0.983-0.999), PM10 (360 days, Model 2: OR = 0.992, 95%CI: 0.985-0.999) had protective effects on any RFP+SM resistance. CONCLUSIONS O3 contributed to an elevated risk of TB resistance but PM2.5, PM10, SO2, NO2 showed an inverse effect. Air pollutants may affect the development of drug resistance among TB cases by adjusting the status of diabetes.
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Affiliation(s)
- Wan-Mei Song
- Department of Respiratory and Critical Care Medicine, Shandong Provincial Hospital Affiliated to Shandong University, 250021 Jinan, Shandong, People's Republic of China; Cheeloo College of Medicine, Shandong University, 250012 Jinan, Shandong, People's Republic of China
| | - Yi Liu
- Department of Biostatistics, School of Public Health, Shandong University, 250012 Jinan, Shandong, People's Republic of China
| | - Qian-Yun Zhang
- Department of Respiratory and Critical Care Medicine, Shandong Provincial Hospital Affiliated to Shandong University, 250021 Jinan, Shandong, People's Republic of China; Cheeloo College of Medicine, Shandong University, 250012 Jinan, Shandong, People's Republic of China
| | - Si-Qi Liu
- Department of Respiratory and Critical Care Medicine, Shandong Provincial Hospital Affiliated to Shandong University, 250021 Jinan, Shandong, People's Republic of China; Cheeloo College of Medicine, Shandong University, 250012 Jinan, Shandong, People's Republic of China
| | - Ting-Ting Xu
- Department of Respiratory and Critical Care Medicine, Shandong Provincial Hospital Affiliated to Shandong First Medical University, 250021 Jinan, Shandong, People's Republic of China
| | - Shi-Jin Li
- Department of Respiratory and Critical Care Medicine, Shandong Provincial Hospital Affiliated to Shandong University, 250021 Jinan, Shandong, People's Republic of China; Cheeloo College of Medicine, Shandong University, 250012 Jinan, Shandong, People's Republic of China
| | - Qi-Qi An
- Department of Respiratory and Critical Care Medicine, Shandong Provincial Hospital Affiliated to Shandong University, 250021 Jinan, Shandong, People's Republic of China; Cheeloo College of Medicine, Shandong University, 250012 Jinan, Shandong, People's Republic of China
| | - Jin-Yue Liu
- Department of Critical Care Medicine, Shandong Provincial Third Hospital, 100191 Jinan, Shandong, People's Republic of China
| | - Ning-Ning Tao
- Department of Respiratory and Critical Care Medicine, Beijing Hospital, 100730 Beijing, People's Republic of China; Graduate School of Peking Union Medical College, Chinese Academy of Medical Sciences and Peking Union Medical College, 100730, Beijing, People's Republic of China
| | - Yao Liu
- Department of Respiratory and Critical Care Medicine, Shandong Provincial Hospital Affiliated to Shandong University, 250021 Jinan, Shandong, People's Republic of China; Department of Respiratory and Critical Care Medicine, Shandong Provincial Hospital Affiliated to Shandong First Medical University, 250021 Jinan, Shandong, People's Republic of China
| | - Chun-Bao Yu
- Katharine Hsu International Research Center of Human Infectious Diseases, Shandong Provincial Chest Hospital, 250013 Jinan, Shandong, People's Republic of China
| | - Cui-Xiang Yu
- Department of Respiratory Medicine, Shandong Qianfoshan Hospital Affiliated to Shandong University, 250014 Jinan, Shandong, People's Republic of China
| | - Yi-Fan Li
- Department of Respiratory and Critical Care Medicine, Shandong Provincial Hospital Affiliated to Shandong University, 250021 Jinan, Shandong, People's Republic of China; Department of Respiratory and Critical Care Medicine, Shandong Provincial Hospital Affiliated to Shandong First Medical University, 250021 Jinan, Shandong, People's Republic of China.
| | - Huai-Chen Li
- Department of Respiratory and Critical Care Medicine, Shandong Provincial Hospital Affiliated to Shandong University, 250021 Jinan, Shandong, People's Republic of China; Department of Respiratory and Critical Care Medicine, Shandong Provincial Hospital Affiliated to Shandong First Medical University, 250021 Jinan, Shandong, People's Republic of China; College of Traditional Chinese Medicine, Shandong University of Traditional Chinese Medicine, 250355 Jinan, Shandong, People's Republic of China.
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16
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Xiang K, Xu Z, Hu YQ, He YS, Dan YL, Wu Q, Fang XH, Pan HF. Association between ambient air pollution and tuberculosis risk: A systematic review and meta-analysis. CHEMOSPHERE 2021; 277:130342. [PMID: 33794431 DOI: 10.1016/j.chemosphere.2021.130342] [Citation(s) in RCA: 28] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/23/2020] [Revised: 03/15/2021] [Accepted: 03/18/2021] [Indexed: 06/12/2023]
Abstract
There is a growing body of evidence suggesting an association between air pollution exposure and tuberculosis (TB) incidence, but no meta-analysis has assembled all evidence so far. This review and meta-analysis aimed to derive a more reliable estimation on the association between air pollution and TB incidence. PubMed, Embase and Web of Science electronic databases were systemically searched for eligible literature. The PECO framework was used to form the eligibility criteria. Effect estimates and 95% confidence intervals (CIs) published in the included studies were pooled quantitatively. Seventeen articles met the inclusion criteria. The pooled estimates showed that long-term exposure to particulate matter with an aerodynamic diameter ≤10 μm (PM10) was associated with increased incidence of TB (per 10 μg/m3 increase in concentrations of PM10: risk ratios (RR) = 1.058, 95% CI: 1.021-1.095). Besides, long-term exposure to sulfur dioxide (SO2) and nitrogen dioxide (NO2) were significantly associated with TB incidence (per 1 ppb increase, SO2: RR = 1.016, 95% CI: 1.001-1.031; NO2: 1.010, 95% CI: 1.002-1.017). We did not find a significant association of PM2.5, ozone (O3) or carbon monoxide (CO) with TB risk, regardless of long-term or short-term exposure. However, in view of the 2016 ASA Statement and the biological plausibility of PM2.5 damaging host immunity, the association between PM2.5 and TB risk remains to be further established. This meta-analysis shows that long-term exposure to PM10, SO2 or NO2 is associated with increased odds of TB, and the specific biological mechanisms warrant further research.
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Affiliation(s)
- Kun Xiang
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, Anhui, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, 81 Meishan Road, Hefei, Anhui, China
| | - Zhiwei Xu
- School of Public Health, Faculty of Medicine, University of Queensland, Brisbane, Australia
| | - Yu-Qian Hu
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, Anhui, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, 81 Meishan Road, Hefei, Anhui, China
| | - Yi-Sheng He
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, Anhui, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, 81 Meishan Road, Hefei, Anhui, China
| | - Yi-Lin Dan
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, Anhui, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, 81 Meishan Road, Hefei, Anhui, China
| | - Qian Wu
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, Anhui, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, 81 Meishan Road, Hefei, Anhui, China
| | - Xue-Hui Fang
- Anhui Provincial TB (Tuberculosis) Institute, Hefei, Anhui, China
| | - Hai-Feng Pan
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, Anhui, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, 81 Meishan Road, Hefei, Anhui, China.
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17
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Wang W, Guo W, Cai J, Guo W, Liu R, Liu X, Ma N, Zhang X, Zhang S. Epidemiological characteristics of tuberculosis and effects of meteorological factors and air pollutants on tuberculosis in Shijiazhuang, China: A distribution lag non-linear analysis. ENVIRONMENTAL RESEARCH 2021; 195:110310. [PMID: 33098820 DOI: 10.1016/j.envres.2020.110310] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/24/2020] [Revised: 08/28/2020] [Accepted: 10/05/2020] [Indexed: 06/11/2023]
Abstract
BACKGROUND Tuberculosis (TB) is a serious public health problem in China. There is evidence to prove that meteorological factors and exposure to air pollutants have a certain impact on TB. But the evidence of this relationship is insufficient, and the conclusions are inconsistent. METHODS Descriptive epidemiological methods were used to describe the distribution characteristics of TB in Shijiazhuang in the past five years. Through the generalized linear regression model (GLM) and the generalized additive model (GAM), the risk factors that affect the incidence of TB are screened. A combination of GLM and distribution lag nonlinear model (DLNM) was used to evaluate the lag effect of environmental factors on the TB. Results were tested for robustness by sensitivity analysis. RESULTS The incidence of TB in Shijiazhuang showed a downward trend year by year, with seasonality and periodicity. Every 10 μg/m3 of PM10 changes, the RR distribution is bimodal. The first peak of RR occurs on the second day of lag (RR = 1.00166, 95% CI: 1.00023, 1.00390); the second risk period starts from 13th day of lag and peaks on15th day (RR = 1.00209, 95% CI: 1.00076, 1.00341), both of which are statistically significant. The cumulative effect of increasing 10 μg/m3 showed a similar bimodal distribution. Time zones where the RR makes sense are days 4-6 and 13-20. RR peaked on the 18th day (RR = 1.02239, 95% CI: 1.00623, 1.03882). The RR has a linear relationship with the concentration. Under the same concentration, the RR peaks within 15-20 days. CONCLUSION TB in Shijiazhuang City showed a downward trend year by year, with obvious seasonal fluctuations. The air pollutant PM10 increases the risk of TB. The development of TB has a short-term lag and cumulative lag effects. We should focus on protecting susceptible people from TB in spring and autumn, and strengthen the monitoring and emission management of PM10 in the atmosphere.
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Affiliation(s)
- Wenjuan Wang
- Department of Epidemiology and Statistics, School of Public Health, Hebei Medical University, Hebei Province Key Laboratory of Environment and Human Health, Shijiazhuang, China
| | - Weiheng Guo
- Department of Epidemiology and Statistics, School of Public Health, Hebei Medical University, Hebei Province Key Laboratory of Environment and Human Health, Shijiazhuang, China
| | - Jianning Cai
- Department of Epidemic Control and Prevention, Center for Disease Prevention and Control of Shijiazhuang City, Shijiazhuang, China
| | - Wei Guo
- Department of Epidemiology and Statistics, School of Public Health, Hebei Medical University, Hebei Province Key Laboratory of Environment and Human Health, Shijiazhuang, China
| | - Ran Liu
- Department of Epidemiology and Statistics, School of Public Health, Hebei Medical University, Hebei Province Key Laboratory of Environment and Human Health, Shijiazhuang, China
| | - Xuehui Liu
- Department of Epidemiology and Statistics, School of Public Health, Hebei Medical University, Hebei Province Key Laboratory of Environment and Human Health, Shijiazhuang, China
| | - Ning Ma
- Department of Epidemiology and Statistics, School of Public Health, Hebei Medical University, Hebei Province Key Laboratory of Environment and Human Health, Shijiazhuang, China
| | - Xiaolin Zhang
- Department of Epidemiology and Statistics, School of Public Health, Hebei Medical University, Hebei Province Key Laboratory of Environment and Human Health, Shijiazhuang, China.
| | - Shiyong Zhang
- Department of Epidemic Control and Prevention, Center for Disease Prevention and Control of Shijiazhuang City, Shijiazhuang, China.
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18
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Huang K, Ding K, Yang XJ, Hu CY, Jiang W, Hua XG, Liu J, Cao JY, Zhang T, Kan XH, Zhang XJ. Association between short-term exposure to ambient air pollutants and the risk of tuberculosis outpatient visits: A time-series study in Hefei, China. ENVIRONMENTAL RESEARCH 2020; 184:109343. [PMID: 32192989 DOI: 10.1016/j.envres.2020.109343] [Citation(s) in RCA: 49] [Impact Index Per Article: 12.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/11/2019] [Revised: 02/03/2020] [Accepted: 03/02/2020] [Indexed: 06/10/2023]
Abstract
BACKGROUND The current evidence has presented mixed results between air pollutants exposure and the progression of tuberculosis (TB). The purpose of this study was to explore the association between short-term exposure to air pollutants and the risk of TB outpatient visits in Hefei, China. METHODS Time-series analysis was used to assess the effect of short-term exposure to ambient air pollutants on the risk of TB outpatient visits. A Poisson generalized linear regression model combined with a distributed lag non-linear model (DLNM) was applied to explore the association. The effects of different gender (male, female), age (≤65 years old, >65 years old) and season (cold season, warm season) on the risk of TB were investigated by stratified analysis. Sensitivity analyses were conducted to test the robustness of our findings. RESULTS A total of 22,749 active TB cases were identified from November 1, 2013 to December 31, 2018 in Hefei. The overall exposure-response curve showed that the concentration of particulate matter with aerodynamic diameter less than 2.5 μm (PM2.5) and nitrogen dioxide (NO2) exposure were positively correlated with the risk of TB outpatient visits, while ozone (O3) and sulfur dioxide (SO2) exposure were negatively correlated with the risk of TB outpatient visits. The maximum lag-specific and cumulative relative risk (RR) of TB outpatient visits were 1.057 [95%CI: 1.002-1.115, lag 3 day] and 1.559 (95%CI: 1.057-2.300, lag 13 days) for each 10 μg/m³ increase in PM2.5; 1.026 (95% CI: 1.008-1.044, lag 0 day) and 1.559 (95%CI: 1.057-2.300, lag 07 days) for each 10 μg/m³ increase in NO2; 0.866 (95% CI: 0.801-0.935, lag 5 day) and 0.852 (95%CI: 1.01-1.11, lag 0-14 days) for each 10 μg/m³ increase in SO2 in the single-pollutant model. There was only a negative association between O3 exposure and the cumulative risk of TB outpatient visits (RR = 0.960, 95%CI: 0.936-0.984, lag 07 days). Stratified analyses showed that the effects of SO2 and O3 exposure were different between warm and cold seasons. The effect of NO2 exposure remained statistically significant in male, younger, and cold season subgroups. Besides, elderly people are more susceptible to PM2.5 exposure. CONCLUSION This study suggests that exposure to PM2.5, NO2, SO2, and O3 are associated with the risk of TB outpatient visits. Seasonal variation may have a greater impact on the risk of TB outpatient visits compared with gender and age.
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Affiliation(s)
- 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
| | - Cheng-Yang Hu
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, 230032, China
| | - Wen Jiang
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, 230032, China
| | - Xiao-Guo Hua
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, 230032, China
| | - Jie Liu
- Department of Occupational Health and Environmental Health, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, 230032, Anhui, China
| | - Ji-Yu Cao
- Department of Occupational Health and Environmental Health, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, 230032, Anhui, China
| | - Tao Zhang
- Anhui Chest Hospital, 397 Jixi Road, Hefei, 230022, 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.
| | - Xiu-Jun Zhang
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, 230032, China.
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19
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Joob B, Wiwanitkit V. Ambient air particulate matter 10 pollutant and newly diagnosed pulmonary tuberculosis: is there any exact association? EGYPTIAN JOURNAL OF CHEST DISEASES AND TUBERCULOSIS 2020. [DOI: 10.4103/ejcdt.ejcdt_26_19] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022] Open
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20
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Asghar MM, Wang Z, Wang B, Zaidi SAH. Nonrenewable energy-environmental and health effects on human capital: empirical evidence from Pakistan. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2020; 27:2630-2646. [PMID: 31836971 DOI: 10.1007/s11356-019-06686-7] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/14/2019] [Accepted: 10/09/2019] [Indexed: 05/21/2023]
Abstract
This research work reconnoiters the impact of nonrenewable energy (NRE) consumptions, environmental pollution, and mortality rate on human capital in the presence of economic growth and two common diseases, measles and tuberculosis (TB) in Pakistan. The study uses data from 1995 to 2017 and employs the Autoregressive Distributive Lag (ARDL) model to investigate cointegration and long-run dynamics. Results indicate that nonrenewable energy (oil, coal, and gas) increase air pollution, measles, TB cases, and mortality rate, which affect the human capital in Pakistan. The results of the ARDL confirm the long-run and short-run effects of fossils fuels, air pollution, and diseases on human capital. The results of the Granger Causality confirm the feedback hypothesis between nonrenewable consumption and human capital, between air pollution and human capital. Measles and TB diseases Granger cause human capital. The study recommends some essential points for energy management, environmental management, and diseases control programs to uplift the human capital in Pakistan.
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Affiliation(s)
| | - Zhaohua Wang
- School of Management and Economics, Beijing Institute of Technology, Beijing, 100081, China
- Center for Energy and Environmental Policy Research, Beijing Institute of Technology, Beijing, 100081, China
- Collaborative Innovation Center of Electric Vehicles in Beijing, Beijing, 100081, China
- Beijing Key Lab of Energy Economics and Environmental Management, Beijing, 100081, China
- Sustainable Development Research Institute for Economy and Society of Beijing, Beijing, 100081, China
| | - Bo Wang
- School of Management and Economics, Beijing Institute of Technology, Beijing, 100081, China
- Center for Energy and Environmental Policy Research, Beijing Institute of Technology, Beijing, 100081, China
| | - Syed Anees Haider Zaidi
- School of Management and Economics, Beijing Institute of Technology, Beijing, 100081, China.
- COMSATS University Islamabad, Sahiwal Campus, Islamabad, Pakistan.
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Sohn M, Kim H, Sung H, Lee Y, Choi H, Chung H. Association of social deprivation and outdoor air pollution with pulmonary tuberculosis in spatiotemporal analysis. INTERNATIONAL JOURNAL OF ENVIRONMENTAL HEALTH RESEARCH 2019; 29:657-667. [PMID: 30698032 DOI: 10.1080/09603123.2019.1566522] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/11/2018] [Accepted: 01/03/2019] [Indexed: 06/09/2023]
Abstract
The objective of this study was to identify the association between social deprivation, outdoor air pollution, and tuberculosis (TB) incidence rate or mortality rate. The study sample comprised 25 districts in Seoul, Korea. We used two public data derived from the Community Health Survey and Seoul Statistics. The geographic information system analysis and random effects Poisson regression were applied to explore the association of social deprivation and air pollution with TB incidence and mortality. An 1 ppb increase in sulfur dioxide (SO2) concentration was significantly associated with the risk of TB incidence (risk ratio [RR] = 1.046, 95% confidence interval [CI]: 1.028, 1.065). An 1 unit increase in the deprivation index was significantly related to a6% increase in the mortality of TB (RR = 1.063, 95% CI: 1.031, 1.097). : Our results imply that social deprivation and air pollution may affect the different TB outcomes. Effective policy-making for TB control should reflect the differing outcomes between TB incidence and mortality.
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Affiliation(s)
- Minsung Sohn
- Department of Public Health Sciences, Graduate School of Korea University, BK21Plus Program in Public Health Sciences , Seoul , Republic of Korea
- Department of Health and Care Administration, The Cyber University of Korea , Seoul , Republic of Korea
| | - Honghyok Kim
- Department of Public Health Sciences, Graduate School of Korea University, BK21Plus Program in Public Health Sciences , Seoul , Republic of Korea
| | - Hyoju Sung
- Department of Public Health Sciences, Graduate School of Korea University, BK21Plus Program in Public Health Sciences , Seoul , Republic of Korea
| | - Younsue Lee
- Policy Development and Research, The Korea National Enterprise for Clinical Trials , Seoul , Republic of Korea
| | - Hongjo Choi
- Department of Research and Development, The Korean Institute of Tuberculosis , Osong , Republic of Korea
| | - Haejoo Chung
- Department of Public Health Sciences, Graduate School of Korea University, BK21Plus Program in Public Health Sciences , Seoul , Republic of Korea
- School of Health Policy and Management, College of Public Health Science, Korea University , Seoul , Republic of Korea
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Xu M, Liao J, Yin P, Hou J, Zhou Y, Huang J, Liu B, Chen R, Ke L, Chen H, Hu P. Association of air pollution with the risk of initial outpatient visits for tuberculosis in Wuhan, China. Occup Environ Med 2019; 76:560-566. [DOI: 10.1136/oemed-2018-105532] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2018] [Revised: 05/14/2019] [Accepted: 06/12/2019] [Indexed: 12/18/2022]
Abstract
ObjectivesPrevious studies suggested the association of air pollution with initial Mycobacterium tuberculosis infection and the disease development. However, few studies have been conducted on air pollution and initial tuberculosis (TB) consults using short-interval data. We investigated the weekly association between air pollution and initial TB outpatient visits.MethodsWe used a Poisson regression model combined with a distributed lag non-linear model to conduct a time-series study with weekly air pollution data and TB cases during 2014–2017 in Wuhan, China.ResultsA 10 µg/m3 increase in NO2 (nitrogen dioxide) was associated with 11.74% (95% CI: 0.70 to 23.98, lag 0–1 weeks), 21.45% (95% CI: 1.44 to 45.41, lag 0–2 weeks) and 12.8% (95% CI: 0.97 to 26.02, lag 0–1 weeks) increase in initial TB consults among all patients with TB, old patients (≥60 years old) and male ones, respectively. A 10 µg/m3 increase in SO2 (sulfur dioxide) was associated with −22.23% (95% CI: −39.23 to −0.49, lag 0–16 weeks), −28.65% (95% CI: −44.3 to −8.58, lag 0–16 weeks), −23.85 (95% CI: −41.79 to −0.37, lag 0–8 weeks) and −23.82% (95% CI: −41.31 to −1.11, lag 0–16 weeks) increase in initial TB consults among the total, young (aged 15–59 years old), old and male patients, respectively. In old patients, a 0.1 mg/m3 increase in CO (carbon monoxide) and a 10 µg/m3 increase in PM2.5 (particulate matter) were separately associated with 42.32% (95% CI: 1.16 to 100.22, lag 0–16 weeks) and 17.38% (95% CI: 0.28 to 37.38, lag 0–16 weeks) increases in TB consults.ConclusionOur study first highlighted the importance of weekly association between air pollution and the risk of initial TB consults, which is helpful for the arrangements of TB screening and medical assistance.
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Katoto PDMC, Byamungu L, Brand AS, Mokaya J, Strijdom H, Goswami N, De Boever P, Nawrot TS, Nemery B. Ambient air pollution and health in Sub-Saharan Africa: Current evidence, perspectives and a call to action. ENVIRONMENTAL RESEARCH 2019; 173:174-188. [PMID: 30913485 DOI: 10.1016/j.envres.2019.03.029] [Citation(s) in RCA: 61] [Impact Index Per Article: 12.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/07/2019] [Revised: 03/04/2019] [Accepted: 03/11/2019] [Indexed: 05/20/2023]
Abstract
BACKGROUND People from low- and middle-income countries are disproportionately affected by the global burden of adverse health effects caused by ambient air pollution (AAP). However, data from Sub-Saharan Africa (SSA) are still scarce. We systematically reviewed the literature to describe the existing knowledge on AAP and health outcomes in SSA. METHODS We searched PubMed, Medline-OVID, EMBASE and Scopus databases to identify studies of AAP and health outcomes published up to November 15, 2017. We used a systematic review approach to critically analyze and summarize levels of outdoor air pollutants, and data on health effects associated with AAP. We excluded occupational and indoor exposure studies. RESULTS We identified 60 articles, with 37 only describing levels of AAP and 23 assessing the association between air pollution and health outcomes. Most studies (75%) addressing the relation between AAP and disease were cross-sectional. In general, exposure data were only obtained for selected cities in the framework of temporary international collaborative research initiatives without structural long-term continuation. Measurements of AAP revealed 10-20 fold higher levels than WHO standards. Of the 23 studies reporting health effects, 14 originated from South Africa, and most countries within SSA contributed no data at all. No studies, except from South Africa, were based on reliable morbidity or mortality statistics at regional or country level. The majority of studies investigated self-reported respiratory symptoms. Children and the elderly were found to be more susceptible to AAP. CONCLUSION AAP and its negative health effects have been understudied in SSA compared with other continents. The limited direct measurements of air pollutants indicate that AAP in SAA cities is high compared with international standards. Efforts are needed to monitor AAP in African cities, to identify its main sources, and to reduce adverse health effects by enforcing legislation.
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Affiliation(s)
- Patrick D M C Katoto
- Centre for Environment and Health, Department of Public Health and Primary Care, KU Leuven, Leuven, Belgium; Department of Internal Medicine, Faculty of Medicine, and Expertise Centre on Mining Governance (CEGEMI), Catholic University of Bukavu, Bukavu, Congo.
| | - Liliane Byamungu
- Department of Pediatric, Faculty of Medicine and Health Sciences, University of KwaZulu Natal, Durban, South Africa.
| | - Amanda S Brand
- Division of Epidemiology and Biostatistics, Department of Global Health, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa.
| | - Jolynne Mokaya
- Division of Epidemiology and Biostatistics, Department of Global Health, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa; Kenya Medical Research Institute, Nairobi, Kenya.
| | - Hans Strijdom
- Division of Medical Physiology, Department of Biomedical Sciences, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa.
| | - Nandu Goswami
- Department of Physiology and Otto Loewi Research Centre, Medical University of Graz, Austria.
| | - Patrick De Boever
- Environmental Risk and Health Unit, Flemish Institute for Technological Research (VITO), Mol, Belgium; Centre for Environmental Sciences, Hasselt University, Hasselt, Belgium.
| | - Tim S Nawrot
- Centre for Environment and Health, Department of Public Health and Primary Care, KU Leuven, Leuven, Belgium; Centre for Environmental Sciences, Hasselt University, Hasselt, Belgium.
| | - Benoit Nemery
- Centre for Environment and Health, Department of Public Health and Primary Care, KU Leuven, Leuven, Belgium.
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de Miguel-Díez J, Hernández-Vázquez J, López-de-Andrés A, Álvaro-Meca A, Hernández-Barrera V, Jiménez-García R. Analysis of environmental risk factors for chronic obstructive pulmonary disease exacerbation: A case-crossover study (2004-2013). PLoS One 2019; 14:e0217143. [PMID: 31120946 PMCID: PMC6532877 DOI: 10.1371/journal.pone.0217143] [Citation(s) in RCA: 30] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2018] [Accepted: 05/07/2019] [Indexed: 12/14/2022] Open
Abstract
Purpose We aim to assess if air pollution levels and climatological factors are associated with hospital admissions for exacerbation of chronic obstructive pulmonary disease (COPD) in Spain from 2004 to 2013. Methods We conducted a retrospective study. Information on pollution level and climatological factors were obtained from the Spanish Meteorological Agency and hospitalizations from the Spanish hospital discharge database. A case-crossover design was used to identify factors associated with hospitalizations and in hospital mortality. Postal codes were used to assign climatic and pollutant factors to each patient. Results We detected 162,338 hospital admissions for COPD exacerbation. When seasonal effects were evaluated we observed that hospital admissions and mortality were more frequent in autumn and winter. In addition, we found significant associations of temperature, humidity, ozone (O3), carbon monoxide (CO), particulate matter up to 10 μm in size (PM10) and nitrogen dioxide (NO2) with hospital admissions. Lower temperatures at admission with COPD exacerbation versus 1, 1.5, 2 and 3 weeks prior to hospital admission for COPD exacerbation, were associated with a higher probability of dying in the hospital. Other environmental factors that were related to in-hospital mortality were NO2, O3, PM10 and CO. Conclusions Epidemiology of hospital admissions by COPD exacerbation was negatively affected by colder climatological factors (seasonality and absolute temperature) and short-term exposure to major air pollution (NO2, O3, CO and PM10).
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Affiliation(s)
- Javier de Miguel-Díez
- Pneumology Department, Hospital General Universitario Gregorio Marañón, Universidad Complutense de Madrid, Madrid, Spain
| | | | - Ana López-de-Andrés
- Preventive Medicine and Public Health Teaching and Research Unit, Department of Health Sciences, Universidad Rey Juan Carlos, Alcorcón, Madrid, Spain
- * E-mail:
| | - Alejandro Álvaro-Meca
- Preventive Medicine and Public Health Teaching and Research Unit, Department of Health Sciences, Universidad Rey Juan Carlos, Alcorcón, Madrid, Spain
| | - Valentín Hernández-Barrera
- Preventive Medicine and Public Health Teaching and Research Unit, Department of Health Sciences, Universidad Rey Juan Carlos, Alcorcón, Madrid, Spain
| | - Rodrigo Jiménez-García
- Preventive Medicine and Public Health Teaching and Research Unit, Department of Health Sciences, Universidad Rey Juan Carlos, Alcorcón, Madrid, Spain
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25
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Cui Z, Lin D, Chongsuvivatwong V, Zhao J, Lin M, Ou J, Zhao J. Spatiotemporal patterns and ecological factors of tuberculosis notification: A spatial panel data analysis in Guangxi, China. PLoS One 2019; 14:e0212051. [PMID: 31048894 PMCID: PMC6497253 DOI: 10.1371/journal.pone.0212051] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2018] [Accepted: 01/04/2019] [Indexed: 01/04/2023] Open
Abstract
BACKGROUND Guangxi is one of the provinces having the highest notification rate of tuberculosis in China. However, spatial and temporal patterns and the association between environmental diversity and tuberculosis notification are still unclear. OBJECTIVE To detect the spatiotemporal pattern of tuberculosis notification rates from 2010 to 2016 and its potential association with ecological environmental factors in Guangxi Zhuang autonomous region, China. METHODS We performed a spatiotemporal analysis with prediction using time series analysis, Moran's I global and local spatial autocorrelation statistics, and space-time scan statistics to detect temporal and spatial clusters of tuberculosis notifications in Guangxi between 2010 and 2016. Spatial panel models were employed to identify potential associating factors. RESULTS The number of reported cases peaked in spring and summer and decreased in autumn and winter. The predicted number of reported cases was 49,946 in 2017. Moran's I global statistics were greater than 0 (0.363-0.536) during the study period. The most significant hot spots were mainly located in the central area. The eastern area exhibited a low-low relation. By the space-time scanning, the clusters identified were similar to those of the local autocorrelation statistics, and were clustered toward the early part of 2016. Duration of sunshine, per capita gross domestic product, the treatment success rate of tuberculosis and participation rate of the new cooperative medical care insurance scheme in rural areas had a significant negative association with tuberculosis notification rates. CONCLUSION The notification rate of tuberculosis in Guangxi remains high, with the highest notification cluster located in the central region. The notification rate is associated with economic level, treatment success rate and participation in the new cooperative medical care insurance scheme.
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Affiliation(s)
- Zhezhe Cui
- Department of Tuberculosis Control, Guangxi Zhuang Autonomous Region Center for Disease Control and Prevention, Nanning, Guangxi, China
- Epidemiology Unit, Faculty of Medicine, Prince of Songkla University, Songkhla, Thailand
| | - Dingwen Lin
- Department of Tuberculosis Control, Guangxi Zhuang Autonomous Region Center for Disease Control and Prevention, Nanning, Guangxi, China
| | | | - Jinming Zhao
- Department of Tuberculosis Control, Guangxi Zhuang Autonomous Region Center for Disease Control and Prevention, Nanning, Guangxi, China
| | - Mei Lin
- Department of Tuberculosis Control, Guangxi Zhuang Autonomous Region Center for Disease Control and Prevention, Nanning, Guangxi, China
| | - Jing Ou
- Department of Tuberculosis Control, Guangxi Zhuang Autonomous Region Center for Disease Control and Prevention, Nanning, Guangxi, China
| | - Jinghua Zhao
- Institute for Communicable Disease Control and Prevention, Qinghai Center for Disease Control and Prevention, Xining, China
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26
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Wang X, Yin S, Li Y, Wang W, Du M, Guo W, Xue M, Wu J, Liang D, Wang R, Liu D, Chu D. Spatiotemporal epidemiology of, and factors associated with, the tuberculosis prevalence in northern China, 2010-2014. BMC Infect Dis 2019; 19:365. [PMID: 31039734 PMCID: PMC6492399 DOI: 10.1186/s12879-019-3910-x] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2018] [Accepted: 03/17/2019] [Indexed: 11/24/2022] Open
Abstract
Background Tuberculosis (TB) is an important public health issue worldwide. However, evidence concerning the impact of environmental factors on TB is sparse. We performed a retrospective analysis to determine the spatiotemporal trends and geographic variations of, and the factors associated with, the TB prevalence in Inner Mongolia. Methods We performed a retrospective analysis of the epidemiology of TB. A Bayesian spatiotemporal model was used to investigate the spatiotemporal distribution and trends of the TB prevalence. A spatial panel data model was used to identify factors associated with the TB prevalence in the 101 counties of Inner Mongolia, using county-level aggregated data collected by the Inner Mongolia Center for Disease Control and Prevention. Results From January 2010 to December 2014, 79,466 (6.36‱) incident TB cases were recorded. The TB prevalence ranged from 4.97‱ (12,515/25,167,547) in 2014 to 7.49‱ (18,406/ 24,578,678) in 2010; the majority of TB cases were in males, and in those aged 46–60 years; by occupation, farmers and herdsmen were the most frequently affected. The Bayesian spatiotemporal model showed that the overall TB prevalence decreased linearly from 2010 to 2014 and occupation-stratified analyses yielded similar results, corroborating the reliability of the findings. The decrease of TB prevalence in the central-western and eastern regions was more rapid than that in the overall TB prevalence. A spatial correlation analysis showed spatial clustering of the TB prevalence from 2011 to 2014 (Moran’s index > 0, P < 0.05); in the spatial panel data model, rural residence, birth rate, number of beds, population density, precipitation, air pressure, and sunshine duration were associated with the TB prevalence. Conclusions The overall TB prevalence in Inner Mongolia decreased from 2010 to 2014; however, the incidence of TB was high throughout this period. The TB prevalence was influenced by a spatiotemporal interaction effect and was associated with epidemiological, healthcare, and environmental factors. Electronic supplementary material The online version of this article (10.1186/s12879-019-3910-x) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Xuemei Wang
- School of Public Health, Inner Mongolia Medical University, Hohhot, 010110, China.,School of Public Health, Peking University, Beijing, 100191, China
| | - Shaohua Yin
- School of Public Health, Inner Mongolia Medical University, Hohhot, 010110, China.,School of Public Health, Peking University, Beijing, 100191, China
| | - Yunpeng Li
- Inner Mongolia Ecology and Agrometeorology Center, Hohhot, 010110, China
| | - Wenrui Wang
- Inner Mongolia Center for Disease Control and Prevention, Hohhot, 010031, China.
| | - Maolin Du
- School of Public Health, Inner Mongolia Medical University, Hohhot, 010110, China.
| | - Weidong Guo
- Inner Mongolia Center for Disease Control and Prevention, Hohhot, 010031, China
| | - Mingming Xue
- School of Basic Medicine, Inner Mongolia Medical University, Hohhot, 010110, China
| | - Jing Wu
- National Center for Chronic and Non-Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 100050, China
| | - Danyan Liang
- School of Public Health, Inner Mongolia Medical University, Hohhot, 010110, China
| | - Ruiqi Wang
- School of Public Health, Inner Mongolia Medical University, Hohhot, 010110, China
| | - Dan Liu
- School of Public Health, Inner Mongolia Medical University, Hohhot, 010110, China
| | - Di Chu
- Inner Mongolia Center for Disease Control and Prevention, Hohhot, 010031, China
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27
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Popovic I, Soares Magalhaes RJ, Ge E, Marks GB, Dong GH, Wei X, Knibbs LD. A systematic literature review and critical appraisal of epidemiological studies on outdoor air pollution and tuberculosis outcomes. ENVIRONMENTAL RESEARCH 2019; 170:33-45. [PMID: 30557690 DOI: 10.1016/j.envres.2018.12.011] [Citation(s) in RCA: 51] [Impact Index Per Article: 10.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/05/2018] [Revised: 11/21/2018] [Accepted: 12/06/2018] [Indexed: 06/09/2023]
Abstract
Ambient air pollution is the leading environmental risk factor for disease globally. Air pollutants can increase the risk of some respiratory infections, but their effects on tuberculosis (TB) are unclear. In this systematic literature review, we aimed to assess epidemiological studies on the association between outdoor air pollutants and TB incidence, hospital admissions and death (collectively referred to here as 'TB outcomes'). We sought to consolidate available evidence on this topic and propose recommendations for future studies. Following PRISMA guidelines, we searched PubMed, Web of Science, Google Scholar, and Scopus with no restrictions imposed on year of publication. A total of 11 epidemiological studies, performed in Asia, Europe and North America, met our inclusion criteria (combined sample size: 215,337 people). We extracted key study characteristics from each eligible publication, including design, exposure assessment, analytical approaches and effect estimates. The studies were assessed for overall quality and risk of bias using standard criteria. The pollutant most frequently associated with statistically significant effects on TB outcomes was fine particulate matter ( < 2.5 µm; PM2.5); 6/11 studies assessed PM2.5, of which 4/6 demonstrated a significant association). There was some evidence of significant associations between PM10 ( < 10 µm), nitrogen dioxide (NO2) and sulfur dioxide (SO2) and TB outcomes, but these associations were inconsistent. The existing epidemiological evidence is limited and shows mixed results. However, it is plausible that exposure to air pollutants, particularly PM2.5, may suppress important immune defence mechanisms, increasing an individual's susceptibility to development of active TB and TB-related mortality. Considering the small number of studies relative to the demonstrably large global health burdens of air pollution and TB, further research is required to corroborate the findings in the current literature. Based on a critical assessment of existing evidence, we conclude with methodological suggestions for future studies.
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Affiliation(s)
- Igor Popovic
- School of Public Health, Faculty of Medicine, University of Queensland, Herston, Australia.
| | - Ricardo J Soares Magalhaes
- UQ Spatial Epidemiology Laboratory, School of Veterinary Science, University of Queensland, Gatton, Australia; Children's Health and Environment Program, Child Health Research Centre, University of Queensland, Brisbane, Australia
| | - Erjia Ge
- Division of Epidemiology, Dalla Lana School of Public Health, University of Toronto, Canada
| | - Guy B Marks
- South Western Sydney Clinical School, University of New South Wales, Sydney, Australia; Woolcock Institute of Medical Research, Sydney, Australia; Centre for Air Pollution, Energy and Health Research, Glebe, NSW, Australia
| | - Guang-Hui Dong
- Guangzhou Key Laboratory of Environmental Pollution and Health Risk Assessment, Department of Preventive Medicine, School of Public Health, Sun Yat-sen University, Guangzhou, China
| | - Xiaolin Wei
- Division of Epidemiology, Dalla Lana School of Public Health, University of Toronto, Canada
| | - Luke D Knibbs
- School of Public Health, Faculty of Medicine, University of Queensland, Herston, Australia; Centre for Air Pollution, Energy and Health Research, Glebe, NSW, Australia
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28
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Drivers of Seasonal Variation in Tuberculosis Incidence: Insights from a Systematic Review and Mathematical Model. Epidemiology 2019; 29:857-866. [PMID: 29870427 DOI: 10.1097/ede.0000000000000877] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Abstract
BACKGROUND Seasonality in tuberculosis incidence has been widely observed across countries and populations; however, its drivers are poorly understood. We conducted a systematic review of studies reporting seasonal patterns in tuberculosis to identify demographic and ecologic factors associated with timing and magnitude of seasonal variation. METHODS We identified studies reporting seasonal variation in tuberculosis incidence through PubMed and EMBASE and extracted incidence data and population metadata. We described key factors relating to seasonality and, when data permitted, quantified seasonal variation and its association with metadata. We developed a dynamic tuberculosis natural history and transmission model incorporating seasonal differences in disease progression and/or transmission rates to examine magnitude of variation required to produce observed seasonality in incidence. RESULTS Fifty-seven studies met inclusion criteria. In the majority of studies (n=49), tuberculosis incidence peaked in spring or summer and reached a trough in late fall or winter. A standardized seasonal amplitude was calculated for 34 of the studies, resulting in a mean of 17.1% (range: 2.7-85.5%) after weighting by sample size. Across multiple studies, stronger seasonality was associated with younger patients, extrapulmonary disease, and latitudes farther from the Equator. The mathematical model was generally able to reproduce observed levels of seasonal case variation; however, substantial variation in transmission or disease progression risk was required to replicate several extreme values. CONCLUSIONS We observed seasonal variation in tuberculosis, with consistent peaks occurring in spring, across countries with varying tuberculosis burden. Future research is needed to explore and quantify potential gains from strategically conducting mass screening interventions in the spring.
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29
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Elf JL, Kinikar A, Khadse S, Mave V, Suryavanshi N, Gupte N, Kulkarni V, Patekar S, Raichur P, Paradkar M, Kulkarni V, Pradhan N, Breysse PN, Gupta A, Golub JE. The association of household fine particulate matter and kerosene with tuberculosis in women and children in Pune, India. Occup Environ Med 2018; 76:40-47. [PMID: 30194271 DOI: 10.1136/oemed-2018-105122] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2018] [Revised: 07/11/2018] [Accepted: 08/14/2018] [Indexed: 12/31/2022]
Abstract
OBJECTIVES Household air pollution (HAP) is a risk factor for respiratory disease, however has yet to be definitively associated with tuberculosis (TB). We aimed to assess the association between HAP and TB. METHODS A matched case-control study was conducted among adult women and children patients with TB and healthy controls matched on geography, age and sex. HAP was assessed using questionnaires for pollution sources and 24-hour household concentrations of particulate matter <2.5 μm in diameter (PM2.5). RESULTS In total, 192 individuals in 96 matched pairs were included. The median 24-hour time-weighted average PM2.5 was nearly seven times higher than the WHO's recommendation of 25 µg/m3, and did not vary between controls (179 µg/m3; IQR: 113-292) and cases (median 157 µg/m3; 95% CI 93 to 279; p=0.57). Reported use of wood fuel was not associated with TB (OR 2.32; 95% CI 0.65 to 24.20) and kerosene was significantly associated with TB (OR 5.49, 95% CI 1.24 to 24.20) in adjusted analysis. Household PM2.5 was not associated with TB in univariate or adjusted analysis. Controlling for PM2.5 concentration, kerosene was not significantly associated with TB, but effect sizes ranged from OR 4.30 (95% CI 0.78 to 30.86; p=0.09) to OR 5.49 (0.82 to 36.75; p=0.08). CONCLUSIONS Use of kerosene cooking fuel is positively associated with TB in analysis using reported sources of exposure. Ubiquitously high levels of particulates limited detection of a difference in household PM2.5 between cases and controls.
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Affiliation(s)
- Jessica L Elf
- Department of Medicine, Division of Infectious Diseases, Center for Clinical Global Health Education, Johns Hopkins School of Medicine, Baltimore, Maryland, USA.,Department of Medicine, Division of Infectious Diseases, Center for TB Research, Johns Hopkins School of Public Health, Baltimore, Maryland, USA.,Division of Infectious Diseases, Johns Hopkins School of Medicine, Baltimore, Maryland, USA
| | - Aarti Kinikar
- Pediatrics Department, Byramjee Jeejeebhoy Government Medical College and Sassoon General Hospitals, Pune, India
| | - Sandhya Khadse
- Pediatrics Department, Byramjee Jeejeebhoy Government Medical College and Sassoon General Hospitals, Pune, India
| | - Vidya Mave
- Department of Medicine, Division of Infectious Diseases, Center for Clinical Global Health Education, Johns Hopkins School of Medicine, Baltimore, Maryland, USA.,Byramjee Jeejeebhoy Government Medical College-Johns Hopkins Clinical Trials Unit, Pune, India
| | - Nishi Suryavanshi
- Byramjee Jeejeebhoy Government Medical College-Johns Hopkins Clinical Trials Unit, Pune, India
| | - Nikhil Gupte
- Department of Medicine, Division of Infectious Diseases, Center for Clinical Global Health Education, Johns Hopkins School of Medicine, Baltimore, Maryland, USA
| | - Vaishali Kulkarni
- Byramjee Jeejeebhoy Government Medical College and Sassoon Government Hospitals, Pune, India
| | - Sunita Patekar
- Byramjee Jeejeebhoy Government Medical College and Sassoon Government Hospitals, Pune, India
| | - Priyanka Raichur
- Byramjee Jeejeebhoy Government Medical College-Johns Hopkins Clinical Trials Unit, Pune, India
| | - Mandar Paradkar
- Byramjee Jeejeebhoy Government Medical College-Johns Hopkins Clinical Trials Unit, Pune, India
| | - Vandana Kulkarni
- Byramjee Jeejeebhoy Government Medical College-Johns Hopkins Clinical Trials Unit, Pune, India
| | - Neeta Pradhan
- Byramjee Jeejeebhoy Government Medical College-Johns Hopkins Clinical Trials Unit, Pune, India
| | - Patrick N Breysse
- Division of Infectious Diseases, Johns Hopkins School of Medicine, Baltimore, Maryland, USA.,Currently employed by the Centers for Disease Control and Prevention. Patrick Breysse is serving in his personal capacity
| | - Amita Gupta
- Department of Medicine, Division of Infectious Diseases, Center for Clinical Global Health Education, Johns Hopkins School of Medicine, Baltimore, Maryland, USA.,Division of Infectious Diseases, Johns Hopkins School of Medicine, Baltimore, Maryland, USA
| | - Jonathan E Golub
- Department of Medicine, Division of Infectious Diseases, Center for TB Research, Johns Hopkins School of Public Health, Baltimore, Maryland, USA.,Division of Infectious Diseases, Johns Hopkins School of Medicine, Baltimore, Maryland, USA
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