Short-term effects of air pollution on mortality in the cities of Rouen and Le Havre, France, 1990-1995.
Identifieur interne : 003323 ( Main/Exploration ); précédent : 003322; suivant : 003324Short-term effects of air pollution on mortality in the cities of Rouen and Le Havre, France, 1990-1995.
Auteurs : A. Zeghnoun [France] ; P. Czernichow ; P. Beaudeau ; A. Hautemanière ; L. Froment ; A. Le Tertre ; P. QuénelSource :
- Archives of environmental health [ 0003-9896 ]
Descripteurs français
- Wicri :
- geographic : France.
English descriptors
- KwdEn :
- Air Pollutants (adverse effects), Air Pollutants (analysis), Air Pollution (adverse effects), Air Pollution (analysis), Air Pollution (statistics & numerical data), Cardiovascular Diseases (mortality), Confidence Intervals, Environmental Monitoring, Epidemiological Monitoring, France (epidemiology), Humans, Influenza, Human (epidemiology), Mortality (trends), Nitrogen Dioxide (adverse effects), Nitrogen Dioxide (analysis), Oxidants, Photochemical (adverse effects), Oxidants, Photochemical (analysis), Ozone (adverse effects), Ozone (analysis), Population Surveillance, Regression Analysis, Risk Factors, Smoke (adverse effects), Smoke (analysis), Statistics, Nonparametric, Sulfur Dioxide (adverse effects), Sulfur Dioxide (analysis), Time Factors, Urban Health (statistics & numerical data), Urban Health (trends), Weather.
- MESH :
- chemical , adverse effects : Air Pollutants, Nitrogen Dioxide, Oxidants, Photochemical, Ozone, Smoke, Sulfur Dioxide.
- chemical , analysis : Air Pollutants, Nitrogen Dioxide, Oxidants, Photochemical, Ozone, Smoke, Sulfur Dioxide.
- geographic , epidemiology : France.
- adverse effects : Air Pollution.
- analysis : Air Pollution.
- epidemiology : Influenza, Human.
- mortality : Cardiovascular Diseases.
- statistics & numerical data : Air Pollution, Urban Health.
- trends : Mortality, Urban Health.
- Confidence Intervals, Environmental Monitoring, Epidemiological Monitoring, Humans, Population Surveillance, Regression Analysis, Risk Factors, Statistics, Nonparametric, Time Factors, Weather.
Abstract
In this study, the authors examined the short-term effects of ambient air pollution on mortality across 2 French cities: Rouen and Le Havre. In Poisson regression models, which controlled for day-of-week effects, the authors used nonparametric smoothing to control for temporal trend, weather, and influenza epidemics. In Rouen, an interquartile range increase of 60.5-94.1 microg/m3 of ozone was associated with an increase of 4.1% (95% confidence interval = 0.6, 7.8) of total mortality. Daily variations in sulfur dioxide (interquartile range increase = 17.6-36.4 microg/m3) were also associated with an 8.2% increase (95% confidence interval = 0.4, 16.6) in respiratory mortality. An increase of 6.1% (95% confidence interval = 1.5, 10.9) of cardiovascular mortality was also observed with an interquartile range increase of nitrogen dioxide (i.e., 25.3-42.2 microg/m3). With respect to Le Havre, an interquartile range increase in daily levels of sulfur dioxide (11.3-35.6 microg/m3) was associated with an increase of approximately 3% (95% confidence interval = 0.8, 5) of cardiovascular mortality. For particulate matter less than or equal to 13 microm in diameter (interquartile increase = 21.5, 45.4 microg/m3), an increase of 6.2% (95% confidence interval = 0.1, 12.8) was observed. The estimates of pollutant effects and their standard deviations were slightly affected by the degree of smoothing temporal variations in this study. When low collinearity was present, the 2-pollutant models provided acceptable estimates of pollutant effects. They suggested that the ozone effect was independent of the Black Smoke effect, and that the effects of sulfur dioxide and nitrogen dioxide were unlikely to be confounded by ozone concentrations. However, high collinearity leads to large estimates of the pollutant coefficient variances and, therefore, leads to inaccurate estimates of pollutant effects. The analysis of the contributory effects of different pollutant mixtures requires further investigation in those instances in which high collinearity between pollutants is present.
DOI: 10.1080/00039890109604464
PubMed: 11572276
Affiliations:
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Le document en format XML
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<term>Air Pollution (statistics & numerical data)</term>
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<term>Confidence Intervals</term>
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<front><div type="abstract" xml:lang="en">In this study, the authors examined the short-term effects of ambient air pollution on mortality across 2 French cities: Rouen and Le Havre. In Poisson regression models, which controlled for day-of-week effects, the authors used nonparametric smoothing to control for temporal trend, weather, and influenza epidemics. In Rouen, an interquartile range increase of 60.5-94.1 microg/m3 of ozone was associated with an increase of 4.1% (95% confidence interval = 0.6, 7.8) of total mortality. Daily variations in sulfur dioxide (interquartile range increase = 17.6-36.4 microg/m3) were also associated with an 8.2% increase (95% confidence interval = 0.4, 16.6) in respiratory mortality. An increase of 6.1% (95% confidence interval = 1.5, 10.9) of cardiovascular mortality was also observed with an interquartile range increase of nitrogen dioxide (i.e., 25.3-42.2 microg/m3). With respect to Le Havre, an interquartile range increase in daily levels of sulfur dioxide (11.3-35.6 microg/m3) was associated with an increase of approximately 3% (95% confidence interval = 0.8, 5) of cardiovascular mortality. For particulate matter less than or equal to 13 microm in diameter (interquartile increase = 21.5, 45.4 microg/m3), an increase of 6.2% (95% confidence interval = 0.1, 12.8) was observed. The estimates of pollutant effects and their standard deviations were slightly affected by the degree of smoothing temporal variations in this study. When low collinearity was present, the 2-pollutant models provided acceptable estimates of pollutant effects. They suggested that the ozone effect was independent of the Black Smoke effect, and that the effects of sulfur dioxide and nitrogen dioxide were unlikely to be confounded by ozone concentrations. However, high collinearity leads to large estimates of the pollutant coefficient variances and, therefore, leads to inaccurate estimates of pollutant effects. The analysis of the contributory effects of different pollutant mixtures requires further investigation in those instances in which high collinearity between pollutants is present.</div>
</front>
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