Objectives: To explore the long-term effect of exposure to ambient air pollution on the risk of active tuberculosis (TB).
Methods: We constructed a distributed-lag nonlinear model (DLNM) to evaluate the relatively long-term influence of outdoor PM, PM, SO and NO exposure on active TB risk in the city of Lianyungang in Jiangsu Province, China.
Results: There were 7,282 TB cases reported in the study area during 2014-2017, with annual median (interquartile range) concentrations of PM, PM, SO and NO at 45.86 (34.57-64.14) μg/m, 85.43 (62.86-116.14) μg/m, 22.00 (15.71-30.86) μg/m and 30.00 (23.29-38.57) μg/m, respectively. The single-pollutant model showed that for each 10 μg/m increase in concentration, the cumulative relative risk of TB was 1.12 (lag 0-24 weeks, 95% CI: 1.03-1.22) for PM with reference to 35 μg/m; 1.11 (lag 0-21 weeks, 95% CI: 1.06-1.17) for PM with reference to 70 μg/m; 1.37 (lag 0-20 weeks, 95% CI: 1.16-1.62) for SO with reference to 60 μg/m; and 1.29 (lag 0-22 weeks, 95% CI: 1.11-1.49) for NO with reference to 40 μg/m. In the multipollutant model considering both PM and NO, the association remained significant.
Conclusions: Our results revealed a potential association between outdoor exposure to PM, PM, SO, and NO and active TB. Considering that people from developing countries continue to be exposed to both severe outdoor air pollution and high rates of latent TB infection, the association between worsening air pollution and active TB deserves further attention.
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http://dx.doi.org/10.1016/j.ijid.2019.07.027 | DOI Listing |
BMC Public Health
January 2025
Department of Ophthalmology, Guangdong Eye Institute, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, 106 Zhongshan Er Road, Guangzhou, 510080, Guangdong, PR China.
Background: Traffic-related air pollution especially in highly socioeconomically developed megacity is usually considered as a severe problem leading to inevitable adverse health outcomes. This study aimed to investigate the associations between traffic-related air pollutants with risk of dry eye disease (DED) outpatient visits in a megacity (Guangzhou) along the subtropical coast in South China.
Methods: Daily data on DED outpatient visits and environmental variables from 1 January 2014 to 31 December 2020 in Guangzhou were obtained.
J Expo Sci Environ Epidemiol
January 2025
Environmental Research Group, School of Public Health, Imperial College London, London, UK.
Background: Accurate estimates of personal exposure to ambient air pollution are difficult to obtain and epidemiological studies generally rely on residence-based estimates, averaged spatially and temporally, derived from monitoring networks or models. Few epidemiological studies have compared the associated health effects of personal exposure and residence-based estimates.
Objective: To evaluate the association between exposure to air pollution and cognitive function using exposure estimates taking mobility and location into account.
Chempluschem
January 2025
China University of Mining and Technology, School of electrical and power engineering, NO.1, Daxue Road, 221116, Xuzhou, CHINA.
The mining industry produces a large amount of industrial solid waste every year. Among them, fly ash (FA), slag and tailings are the three main solid wastes, which can cause soil pollution, air pollution, water pollution and serious threat to human health if not handled properly. At present, the treatment methods of industrial solid waste mainly include direct landfill, recovery of high-value components, production of construction materials, etc.
View Article and Find Full Text PDFJ Prev Alzheimers Dis
January 2025
National Center for Disease Prevention and Health Promotion, Italian National Institute of Health Rome, Italy.
Background: Dementia is a major global public health challenge, with over 50 million cases in 2020, projected to reach 152 million by 2050. Effective prevention strategies are needed to reduce the impact of modifiable risk factors associated with dementia, particularly in countries with ageing populations like Italy. The Population Attributable Fraction (PAF) and Potential Impact Fraction (PIF) are key metrics for understanding and reducing dementia cases through targeted interventions.
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