Background: Outdoor traffic-related air pollution has negative effects on respiratory health. In this study, we aimed to explore the effect of outdoor traffic-related air pollution on chronic obstructive pulmonary disease (COPD) in Guangzhou.
Methods: We enrolled 1,460 residents aged 40 years or older between 21 January 2014 and 31 January 2018. We administered questionnaires and spirometry tests. The distance of participants' residences or locations of outdoor activities from busy roads (as indicators of outdoor traffic-related air pollution), indoor air pollution, and smoking history were queried in the questionnaires.
Results: Of the 1,460 residents with valid survey and test results, 292 were diagnosed with COPD, with a detection rate of 20%. Participants who lived and did their outdoor activities near busy roads had a higher detection rate of COPD. Among residents living at distances of <50 meters, 50-199 meters, and more than 200 meters from busy roads, the detection rates were 20.6, 21.2, and 14.8%, respectively; the rates for outdoor activities at these distances were 23.8, 24.5, and 13.7%, respectively ( < 0.05). After adjusting for sex, age, smoking status, family history, and smoking index, the distance of outdoor activities from busy roads was an independent risk factor for COPD. Participants whose outdoor activities were conducted <50 meters and 50-199 meters of main roads had odds ratios of 1.54 (95% confidence interval 1.01-2.36) and 1.84 (95% interval 1.23-2.76) for the risk of COPD in comparison with a distance of more than 200 meters from busy roads.
Conclusions: Residents of Guangzhou whose outdoor activities were close to busy roads had a high risk of COPD. Traffic-related air pollution presents a risk to human health and a risk of COPD.
Download full-text PDF |
Source |
|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9769455 | PMC |
| http://dx.doi.org/10.3389/fpubh.2022.1036192 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Spatio-temporal analysis of formaldehyde and its association with atmospheric and environmental variables over the Southeast Asian region using satellite data.
Environ Monit Assess
January 2025
Bhaskaracharya College of Applied Sciences, University of Delhi, New Delhi, Delhi, 110078, India.
This study investigates the spatio-temporal distribution of formaldehyde (HCHO) over the mainland Southeast Asian region (including Northeast India) from 2019 to 2022 using TROPOMI satellite data. HCHO is a key atmospheric trace gas which is influenced by both natural processes and anthropogenic activities. We analyze HCHO levels in relation to atmospheric species including carbon monoxide (CO), nitrogen dioxide (NO), and environmental factors such as land surface temperature (LST), precipitation (PPT), fire radiative power (FRP), and enhanced vegetation index (EVI).
View Article and Find Full Text PDFThe global air pollution and undernutrition among children under five.
Sci Rep
January 2025
Research Center for Social Determinants of Health, Jahrom University of Medical Sciences, Jahrom, Iran.
Malnutrition and PM pollution remain a pressing global public health concern, especially to vulnerable populations like children under five years old. This study aimed to investigate the correlation between undernutrition in children under five years old and air pollution (exposure to PM) on a global scale. This ecological study evaluated the correlation between undernutrition (wasting and stunting) and air pollution in 123 countries.
View Article and Find Full Text PDFExploration of transfer learning techniques for the prediction of PM.
Sci Rep
January 2025
Institute for Anthropological Research, 10000, Zagreb, Croatia.
Modelling of pollutants provides valuable insights into air quality dynamics, aiding exposure assessment where direct measurements are not viable. Machine learning (ML) models can be employed to explore such dynamics, including the prediction of air pollution concentrations, yet demanding extensive training data. To address this, techniques like transfer learning (TL) leverage knowledge from a model trained on a rich dataset to enhance one trained on a sparse dataset, provided there are similarities in data distribution.
View Article and Find Full Text PDFUnravelling biotic and abiotic mechanisms of mature compost to alleviate gaseous emissions in kitchen waste composting by metagenomic analysis.
Bioresour Technol
January 2025
Beijing Key Laboratory of Farmland Soil Pollution Prevention and Remediation, College of Resources and Environmental Sciences, China Agricultural University, Beijing 100193, China. Electronic address:
Mature compost can reduce gaseous emissions in composting, but its regulation mechanisms via biotic and abiotic functions are largely unknown. This study used fresh and inactivated mature compost as additives in kitchen waste composting to unveil the relevant mechanisms using metagenomic analysis. Results showed that mature compost reduce gaseous emission by improving physiochemical properties and inoculating functional microbes.
View Article and Find Full Text PDFPreparation of magnetic hydrophobic Cu-containing mesoporous materials and their performance in adsorption and removal of organic sulfides from simulated gasoline.
J Environ Manage
January 2025
Shaanxi Key Laboratory of Catalysis, College of Chemical and Environment Science, Shaanxi University of Technology, Hanzhong 723000, PR China.
Sulfur-containing gases produced during the utilization of petroleum fuels are the main cause of air pollution. To remove organic sulfur-containing compounds from simulated gasoline, magnetic hydrophobic Cu-containing SBA-15 mesoporous molecular sieves (PMS-Cu) were prepared by magnetization of the sample, loading and reduction of copper ion and hydrophobic treatment of the sample. The composition and structure of the synthesized composites were characterized by XRD, FTIR, SEM, TEM, and XPS, which proved the successful preparation of the adsorbent PMS-Cu.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!