Asthmatic symptoms and air pollution: a panel study on children living in the Italian Po Valley
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Author(s)
Type
Journal Article
Abstract
The Po Valley (Northern Italy) has elevated levels of air-pollution due to various sources of pollution and adverse weather conditions. This study evaluates the short-term effects of exposure to particulate matter with a diameter of 10 microns or less (PM10) on asthma symptoms in school-aged children. An initial cross-sectional survey was conducted in the area to estimate asthma prevalence in children. Out of a total of 250 asthmatic children identified by the study, 69 agreed to participate in a panel study. The PM10 exposure assessment was based on a combination of geographic and environmental measurements leading to a focus on three different areas, each characterised by its own daily PM10 level. Participants were monitored daily for respiratory symptoms for eight weeks (January-March 2006). We assessed the relationship between daily PM10 exposure and occurrence of asthma symptoms with a generalised linear model based on a total of 3864 person-days of observation. Exposure to PM10 per m3 was found to be particularly associated with cough (OR=1.03, CI 95% 0.99; 1.08) and phlegm (OR=1.05, CI 95% 1.00; 1.10). In the most polluted area, exposure to PM10 was also associated with wheezing (OR=1.18, CI 95% 1.02; 1.37).
Date Issued
2015-11-04
Date Acceptance
2015-08-24
Citation
Geospatial Health, 2015, 10 (2)
ISSN
1970-7096
Publisher
PAGEpress
Journal / Book Title
Geospatial Health
Volume
10
Issue
2
Copyright Statement
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
License URL
Subjects
Air Pollutants
Air Pollution
Asthma
Child
Cross-Sectional Studies
Female
Geographic Information Systems
Humans
Italy
Linear Models
Male
Mass Screening
Models, Statistical
Particulate Matter
Population Density
Prevalence
Risk Factors
Surveys and Questionnaires
Weather
Tropical Medicine
Publication Status
Published
Article Number
366